ORCID Profile
0000-0001-7421-3357
Current Organisations
University of Queensland
,
University of Oxford
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Psychology | Quantitative Genetics | Medical and Health Sciences not elsewhere classified | Statistics Not Elsewhere Classified | Bioinformatics and computational biology | Biological Psychology (Neuropsychology, Psychopharmacology, | Learning, Memory, Cognition And Language | Animal reproduction and breeding | Genetics | Biological Psychology (Neuropsychology, Psychopharmacology, Physiological Psychology) | Quantitative Genetics (incl. Disease and Trait Mapping Genetics) | Clinical Sciences | Gene mapping | Psychiatry | Animal Breeding | Statistical and quantitative genetics |
ANZSRC Socio-Economic Objective (SEO)
Education and training not elsewhere classified | Dairy Cattle | Inherited Diseases (incl. Gene Therapy) | Expanding Knowledge in Psychology and Cognitive Sciences | Inherited diseases (incl. gene therapy) | Behavioural and cognitive sciences | Mental health | Expanding Knowledge in the Biological Sciences | Preventive medicine | Health status (e.g. indicators of “well-being”)
Related Links
Publications
The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936
Publisher: Oxford University Press (OUP)
Date: 22-01-2015
DOI: 10.1093/IJE/DYU277
Research Review: Polygenic methods and their application to psychiatric traits.
Publisher: Wiley
Date: 08-2014
DOI: 10.1111/JCPP.12295
Abstract: Despite evidence from twin and family studies for an important contribution of genetic factors to both childhood and adult onset psychiatric disorders, identifying robustly associated specific DNA variants has proved challenging. In the pregenomics era the genetic architecture (number, frequency and effect size of risk variants) of complex genetic disorders was unknown. Empirical evidence for the genetic architecture of psychiatric disorders is emerging from the genetic studies of the last 5 years. We review the methods investigating the polygenic nature of complex disorders. We provide mini-guides to genomic profile (or polygenic) risk scoring and to estimation of variance (or heritability) from common SNPs a glossary of key terms is also provided. We review results of applications of the methods to psychiatric disorders and related traits and consider how these methods inform on missing heritability, hidden heritability and still-missing heritability. Genome-wide genotyping and sequencing studies are providing evidence that psychiatric disorders are truly polygenic, that is they have a genetic architecture of many genetic variants, including risk variants that are both common and rare in the population. S le sizes published to date are mostly underpowered to detect effect sizes of the magnitude presented by nature, and these effect sizes may be constrained by the biological validity of the diagnostic constructs. Increasing the s le size for genome wide association studies of psychiatric disorders will lead to the identification of more associated genetic variants, as already found for schizophrenia. These loci provide the starting point of functional analyses that might eventually lead to new prevention and treatment options and to improved biological validity of diagnostic constructs. Polygenic analyses will contribute further to our understanding of complex genetic traits as s le sizes increase and as s le resources become richer in phenotypic descriptors, both in terms of clinical symptoms and of nongenetic risk factors.
The genetic and phenotypic correlates of neonatal Complement Component 3 and 4 protein concentrations with a focus on psychiatric and autoimmune disorders
Publisher: Cold Spring Harbor Laboratory
Date: 15-11-2022
DOI: 10.1101/2022.11.09.22281216
Abstract: The complement system, including complement components 3 and 4 (C3, C4), traditionally has been linked to innate immunity. More recently, complement components have also been implicated in brain development and the risk of schizophrenia. Based on a large, population-based case-cohort study, we measured the blood concentrations of C3 and C4 in 68,768 neonates. We found a strong correlation between the concentrations of C3 and C4 (phenotypic correlation = 0.65, P -value 1.0×10 −100 , genetic correlation = 0.38, P -value = 1.9×10 −35 ). A genome-wide association study (GWAS) for C4 protein concentration identified 36 independent loci, 30 of which were in or near the major histocompatibility complex on chromosome 6 (which includes the C4 gene), while six loci were found on six other chromosomes. A GWAS for C3 identified 15 independent loci, seven of which were located in the C3 gene on chromosome 19, and eight loci on five other chromosomes. We found no association between (a) measured neonatal C3 and C4 concentrations, imputed C4 haplotypes, or predicted C4 gene expression, with (b) schizophrenia (SCZ), bipolar disorder (BIP), depression (DEP), autism spectrum disorder, attention deficit hyperactivity disorder or anorexia nervosa diagnosed in later life. Mendelian randomisation (MR) suggested a small positive association between higher C4 protein concentration and an increased risk of SCZ, BIP, and DEP, but these findings did not persist in more stringent analyses. Evidence from MR supported causal relationships between C4 concentration and several autoimmune disorders: systemic lupus erythematosus (SLE, OR and 95% confidence interval, 0.37, 0.34 – 0.42) type-1 diabetes (T1D, 0.54, 0.50 - 0.58) multiple sclerosis (MS, 0.68, 0.63 - 0.74) rheumatoid arthritis (0.85, 0.80 - 0.91) and Crohn’s disease (1.26, 1.19 - 1.34). A phenome-wide association study (PheWAS) in UK Biobank confirmed that the genetic correlates of C4 concentration were associated a range of autoimmune disorders including coeliac disease, thyrotoxicosis, hypothyroidism, T1D, sarcoidosis, psoriasis, SLE and ankylosing spondylitis. We found no evidence of associations between C3 versus mental or autoimmune disorders based on either MR or PheWAS. In general, our results do not support the hypothesis that C4 is causally associated with the risk of SCZ (nor several other mental disorders). We provide new evidence to support the hypothesis that higher C4 concentration is associated with lower risks of autoimmune disorders.
Association of Body Mass Index with DNA Methylation and Gene Expression in Blood Cells and Relations to Cardiometabolic Disease: A Mendelian Randomization Approach
Publisher: Public Library of Science (PLoS)
Date: 17-01-2017
Association between the TRAX/DISC locus and both bipolar disorder and schizophrenia in the Scottish population.
Publisher: Springer Science and Business Media LLC
Date: 24-06-2005
Association of Antihypertensive Drug Target Genes With Psychiatric Disorders: A Mendelian Randomization Study.
Publisher: American Medical Association (AMA)
Date: 06-2021
Linking Polygenic Risk of Schizophrenia to Variation in Magnetic Resonance Imaging Brain Measures: A Comprehensive Systematic Review
Publisher: Oxford University Press (OUP)
Date: 24-06-2023
Abstract: Schizophrenia is highly heritable, with a polygenic effect of many genes conferring risk. Evidence on whether cumulative risk also predicts alterations in brain morphology and function is inconsistent. This systematic review examined evidence for schizophrenia polygenic risk score (sczPRS) associations with commonly used magnetic resonance imaging (MRI) measures. We expected consistent evidence to emerge for significant sczPRS associations with variation in structure and function, specifically in frontal, temporal, and insula cortices that are commonly implicated in schizophrenia pathophysiology. In accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched MEDLINE, Embase, and PsycINFO for peer-reviewed studies published between January 2013 and March 2022. Studies were screened against predetermined criteria and National Institutes of Health (NIH) quality assessment tools. In total, 57 studies of T1-weighted structural, diffusion, and functional MRI were included (age range = 9–80 years, Nrange = 64–76 644). We observed moderate, albeit preliminary, evidence for higher sczPRS predicting global reductions in cortical thickness and widespread variation in functional connectivity, and to a lesser extent, region-specific reductions in frontal and temporal volume and thickness. Conversely, sczPRS does not predict whole-brain surface area or gray/white matter volume. Limited evidence emerged for sczPRS associations with diffusion tensor measures of white matter microstructure in a large community s le and smaller cohorts of children and young adults. These findings were broadly consistent across community and clinical populations. Our review supports the hypothesis that schizophrenia is a disorder of disrupted within and between-region brain connectivity, and points to specific whole-brain and regional MRI metrics that may provide useful intermediate phenotypes.
Genetic risk scores for major psychiatric disorders and the risk of postpartum psychiatric disorders
Publisher: Springer Science and Business Media LLC
Date: 11-11-2019
DOI: 10.1038/S41398-019-0629-9
Abstract: Postpartum psychiatric disorders are heritable, but how genetic liability varies by other significant risk factors is unknown. We aimed to (1) estimate associations of genetic risk scores (GRS) for major depression (MD), bipolar disorder (BD), and schizophrenia (SCZ) with postpartum psychiatric disorders, (2) examine differences by prior psychiatric history, and (3) compare genetic and familial risk of postpartum psychiatric disorders. We conducted a nested case-control study based on Danish population-based registers of all women in the iPSYCH2012 cohort who had given birth before December 31, 2015 ( n = 8850). Cases were women with a diagnosed psychiatric disorder or a filled psychotropic prescription within one year after delivery ( n = 5829 cases, 3021 controls). Association analyses were conducted between GRS calculated from Psychiatric Genomics Consortium discovery meta-analyses for MD, BD, and SCZ and case-control status of a postpartum psychiatric disorder. Parental psychiatric history was associated with postpartum psychiatric disorders among women with previous psychiatric history (OR, 1.14 95% CI 1.02–1.28) but not without psychiatric history (OR, 1.08 95% CI: 0.81–1.43). GRS for MD was associated with an increased risk of postpartum psychiatric disorders in both women with (OR, 1.44 95% CI: 1.19–1.74) and without (OR, 1.88 95% CI: 1.26–2.81) personal psychiatric history. SCZ GRS was only minimally associated with postpartum disorders and BD GRS was not. Results suggest GRS of lifetime psychiatric illness can be applied to the postpartum period, which may provide clues about distinct environmental or genetic elements of postpartum psychiatric disorders and ultimately help identify vulnerable groups.
Association between ORMDL3, IL1RL1 and a deletion on chromosome 17q21 with asthma risk in Australia
Publisher: Springer Science and Business Media LLC
Date: 08-12-2011
Mutations in heat shock protein beta-1 (HSPB1) are associated with a range of clinical phenotypes related to different patterns of motor neuron dysfunction: A case series
Publisher: Elsevier BV
Date: 06-2020
Multi-locus models of genetic risk of disease
Publisher: Springer Science and Business Media LLC
Date: 2010
DOI: 10.1186/GM131
Correction: GWAS on family history of Alzheimer’s disease
Publisher: Springer Science and Business Media LLC
Date: 06-06-2019
DOI: 10.1038/S41398-019-0498-2
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Where GWAS and epidemiology meet: opportunities for the simultaneous study of genetic and environmental risk factors in schizophrenia.
Publisher: Oxford University Press (OUP)
Date: 08-2013
Correction: Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes
Publisher: Springer Science and Business Media LLC
Date: 08-02-2021
DOI: 10.1038/S41467-021-21294-1
Abstract: A Correction to this paper has been published: 0.1038/s41467-021-21294-1.
Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions
Publisher: Elsevier BV
Date: 08-2023
Publisher Correction: Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection
Publisher: Springer Science and Business Media LLC
Date: 03-06-2019
DOI: 10.1038/S41588-019-0450-7
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
The Australian Genetics of Depression Study: new risk loci and dissecting heterogeneity between subtypes
Publisher: Elsevier BV
Date: 08-2021
DOI: 10.1016/J.BIOPSYCH.2021.10.021
Abstract: Major depressive disorder (MDD) is a common and highly heterogeneous psychiatric disorder, but little is known about the genetic characterization of this heterogeneity. Understanding the genetic etiology of MDD can be challenging because large s le sizes are needed for gene discovery-often achieved with a trade-off in the depth of phenotyping. The Australian Genetics of Depression Study is the largest stand-alone depression cohort with both genetic data and in-depth phenotyping and comprises a total of 15,792 participants of European ancestry, 92% of whom met diagnostic criteria for MDD. We leveraged the unique nature of this cohort to conduct a meta-analysis with the largest publicly available depression genome-wide association study to date and subsequently used polygenic scores to investigate genetic heterogeneity across various clinical subtypes of MDD. We increased the number of known genome-wide significant variants associated with depression from 103 to 126 and found evidence of association of novel genes implicated in neuronal development. We found that a polygenic score for depression explained 5.7% of variance in MDD liability in our s le. Finally, we found strong support for genetic heterogeneity in depression with differential associations of multiple psychiatric and comorbid traits with age of onset, longitudinal course, and various subtypes of MDD. Until now, this degree of detailed phenotyping in such a large s le of MDD cases has not been possible. Along with the discovery of novel loci, we provide support for differential pathways to illness models that recognize the overlap with other common psychiatric disorders as well as pathophysiological differences.
Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology
Publisher: Springer Science and Business Media LLC
Date: 12-2021
DOI: 10.1038/S41588-021-00973-1
Abstract: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 in iduals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons.
A bias-reducing pathway enrichment analysis of genome-wide association data confirmed association of the MHC region with schizophrenia
Publisher: BMJ
Date: 20-12-2012
DOI: 10.1136/JMEDGENET-2011-100397
Abstract: After the recent successes of genome-wide association studies (GWAS), one key challenge is to identify genetic variants that might have a significant joint effect on complex diseases but have failed to be identified in idually due to weak to moderate marginal effect. One popular and effective approach is gene set based analysis, which investigates the joint effect of multiple functionally related genes (eg, pathways). However, a typical gene set analysis method is biased towards long genes, a problem that is especially severe in psychiatric diseases. A novel approach was proposed, namely generalised additive model (GAM) for GWAS (gamGWAS), for gene set enrichment analysis of GWAS data, specifically adjusting the gene length bias or the number of single-nucleotide polymorphisms per gene. GAM is applied to estimate the probability of a gene to be selected as significant given its gene length, followed by weighted res ling and computation of empirical p values for the rank of pathways. We demonstrated gamGWAS in two schizophrenia GWAS datasets from the International Schizophrenia Consortium and the Genetic Association Information Network. The gamGWAS results not only confirmed previous findings, but also highlighted several immune related pathways. Comparison with other methods indicated that gamGWAS could effectively reduce the correlation between pathway p values and its median gene length. gamGWAS can effectively relieve the long gene bias and generate reliable results for GWAS data analysis. It does not require genotype data or permutation of s le labels in the original GWAS data thus, it is computationally efficient.
Don't give up on GWAS
Publisher: Springer Science and Business Media LLC
Date: 09-08-2011
DOI: 10.1038/MP.2011.94
Polygenic burden could explain high rates of affective disorders in a community with restricted founder population
Publisher: Wiley
Date: 09-2021
DOI: 10.1002/AJMG.B.32876
Abstract: This study investigates if genetic factors could contribute to the high rate of mood disorders reported in a U.S. community known to have a restricted early founder population (confirmed here through runs of homozygosity analysis). Polygenic scores (PGSs) for eight common diseases, disorders, or traits, including psychiatric disorders, were calculated in 274 participants (125 mood disorder cases) who each reported three or four grandparents born in the community. Ancestry‐matched controls were selected from the UK Biobank (UKB three sets of N = 1,822 each). The mean PGSs were significantly higher in the community for major depression PRS ( p = 2.1 × 10 −19 , 0.56 SD units), bipolar disorder ( p = 2.5 × 10 −15 , 0.56 SD units), and schizophrenia ( p = 3.8 × 10 −21 , 0.64 SD units). The PGSs were not significantly different between the community participants and UKB controls for the traits of body mass index, Type 2 diabetes, coronary artery disease, and chronotype. The mean PGSs for height were significantly lower in the community s le compared to controls (−0.21 SD units, p = 1.2 × 10 −5 ). The results are consistent with enrichment of polygenic risk factors for psychiatric disorders in this community.
Estimation of non-additive genetic variance in human complex traits from a large sample of unrelated individuals
Publisher: Cold Spring Harbor Laboratory
Date: 09-11-2020
DOI: 10.1101/2020.11.09.375501
Abstract: Non-additive genetic variance for complex traits is traditionally estimated from data on relatives. It is notoriously difficult to estimate without bias in non-laboratory species, including humans, because of possible confounding with environmental covariance among relatives. In principle, non-additive variance attributable to common DNA variants can be estimated from a random s le of unrelated in iduals with genome-wide SNP data. Here, we jointly estimate the proportion of variance explained by additive , dominance and additive-by-additive genetic variance in a single analysis model. We first show by simulations that our model leads to unbiased estimates and provide new theory to predict standard errors estimated using either least squares or maximum likelihood. We then apply the model to 70 complex traits using 254,679 unrelated in iduals from the UK Biobank and 1.1M genotyped and imputed SNPs. We found strong evidence for additive variance (average across traits . In contrast, the average estimate of across traits was 0.001, implying negligible dominance variance at causal variants tagged by common SNPs. The average epistatic variance across the traits was 0.058, not significantly different from zero because of the large s ling variance. Our results provide new evidence that genetic variance for complex traits is predominantly additive, and that s le sizes of many millions of unrelated in iduals are needed to estimate epistatic variance with sufficient precision.
Using information of relatives in genomic prediction to apply effective stratified medicine
Publisher: Springer Science and Business Media LLC
Date: 09-02-2017
DOI: 10.1038/SREP42091
Abstract: Genomic prediction shows promise for personalised medicine in which diagnosis and treatment are tailored to in iduals based on their genetic profiles for complex diseases. We present a theoretical framework to demonstrate that prediction accuracy can be improved by targeting more informative in iduals in the data set used to generate the predictors (“discovery s le”) to include those with genetically close relationships with the subjects put forward for risk prediction. Increase of prediction accuracy from closer relationships is achieved under an additive model and does not rely on any family or interaction effects. Using theory, simulations and real data analyses, we show that the predictive accuracy or the area under the receiver operating characteristic curve (AUC) increased exponentially with decreasing effective size ( N e ), i.e. when in iduals are closely related. For ex le, with the s le size of discovery set N = 3000, heritability h 2 = 0.5 and population prevalence K = 0.1, AUC value approached to 0.9 and the top percentile of the estimated genetic profile scores had 23 times higher proportion of cases than the general population. This suggests that there is considerable room to increase prediction accuracy by using a design that does not exclude closer relationships.
Publisher Correction: 33 years of globally calibrated wave height and wind speed data based on altimeter observations
Publisher: Springer Science and Business Media LLC
Date: 19-06-2019
DOI: 10.1038/S41597-019-0108-4
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Protocol for a collaborative meta-analysis of 5-HTTLPR, stress, and depression
Publisher: Springer Science and Business Media LLC
Date: 12-11-2013
Gene expression imputation across multiple brain regions provides insights into schizophrenia risk
Publisher: Springer Science and Business Media LLC
Date: 25-03-2019
Sporadic cases are the norm for complex disease
Publisher: Springer Science and Business Media LLC
Date: 14-10-2009
Novel genetic analysis for case-control genome-wide association studies: quantification of power and genomic prediction accuracy.
Publisher: Public Library of Science (PLoS)
Date: 19-08-2013
Simultaneous discovery, estimation and prediction analysis of complex traits using a bayesian mixture model
Publisher: Public Library of Science (PLoS)
Date: 07-04-2015
Common Disease Is More Complex Than Implied by the Core Gene Omnigenic Model
Publisher: Elsevier BV
Date: 06-2018
DOI: 10.1016/J.CELL.2018.05.051
Abstract: The evidence that most adult-onset common diseases have a polygenic genetic architecture fully consistent with robust biological systems supported by multiple back-up mechanisms is now overwhelming. In this context, we consider the recent "omnigenic" or "core genes" model. A key assumption of the model is that there is a relatively small number of core genes relevant to any disease. While intuitively appealing, this model may underestimate the biological complexity of common disease, and therefore, the goal to discover core genes should not guide experimental design. We consider other implications of polygenicity, concluding that a focus on patient stratification is needed to achieve the goals of precision medicine.
Lifetime stress accelerates epigenetic aging in an urban, African American cohort: relevance of glucocorticoid signaling.
Publisher: Springer Science and Business Media LLC
Date: 12-2015
Linear mixed models minimise false positive rate and enhance precision of mass univariate vertex-wise analyses of grey-matter
Publisher: IEEE
Date: 04-2020
Genetic and environmental influences on the co-morbidity between depression, panic disorder, agoraphobia, and social phobia: a twin study.
Publisher: Hindawi Limited
Date: 11-2009
DOI: 10.1002/DA.20611
Genetic correlations of polygenic disease traits: from theory to practice
Publisher: Springer Science and Business Media LLC
Date: 06-06-2019
DOI: 10.1038/S41576-019-0137-Z
Abstract: The genetic correlation describes the genetic relationship between two traits and can contribute to a better understanding of the shared biological pathways and/or the causality relationships between them. The rarity of large family cohorts with recorded instances of two traits, particularly disease traits, has made it difficult to estimate genetic correlations using traditional epidemiological approaches. However, advances in genomic methodologies, such as genome-wide association studies, and widespread sharing of data now allow genetic correlations to be estimated for virtually any trait pair. Here, we review the definition, estimation, interpretation and uses of genetic correlations, with a focus on applications to human disease.
Phenotypic covariance across the entire spectrum of relatedness for 86 billion pairs of individuals
Publisher: Springer Science and Business Media LLC
Date: 16-02-2021
DOI: 10.1038/S41467-021-21283-4
Abstract: Attributing the similarity between in iduals to genetic and non-genetic factors is central to genetic analyses. In this paper we use the genomic relationship ( $$\\pi$$ π ) among 417,060 in iduals to investigate the phenotypic covariance between pairs of in iduals for 32 traits across the spectrum of relatedness, from unrelated pairs through to identical twins. We find linear relationships between phenotypic covariance and $$\\pi$$ π that agree with the SNP-based heritability ( $$\\hat h_{SNP}^2$$ h ̂ S N P 2 ) in unrelated pairs ( $$\\pi \\, \\, 0.02$$ π 0.02 ), and with pedigree-estimated heritability in close relatives ( $$\\pi \\, \\, 0.05$$ π 0.05 ). The covariance increases faster than $$\\pi \\hat h_{SNP}^2$$ π h ̂ S N P 2 in distant relatives ( $$0.02 \\, \\, \\pi \\, \\, 0.05$$ 0.02 π 0.05 ), and we attribute this to imperfect linkage disequilibrium between causal variants and the common variants used to construct $$\\pi$$ π . We also examine the effect of assortative mating on heritability estimates from different experimental designs. We find that full-sib identity-by-descent regression estimates for height (0.66 s.e. 0.07) are consistent with estimates from close relatives (0.82 s.e. 0.04) after accounting for the effect of assortative mating.
Joint analysis of GWAS and multi-omics QTL summary statistics reveals a large fraction of GWAS signals shared with molecular phenotypes
Publisher: Elsevier BV
Date: 08-2023
Epigenetic prediction of complex traits and death
Publisher: Springer Science and Business Media LLC
Date: 27-09-2018
Cohort profile: the Australian genetics of depression study.
Publisher: BMJ
Date: 05-2020
DOI: 10.1136/BMJOPEN-2019-032580
Abstract: Depression is the most common psychiatric disorder and the largest contributor to global disability. The Australian Genetics of Depression study was established to recruit a large cohort of in iduals who have been diagnosed with depression at some point in their lifetime. The purpose of establishing this cohort is to investigate genetic and environmental risk factors for depression and response to commonly prescribed antidepressants. A total of 20 689 participants were recruited through the Australian Department of Human Services and a media c aign, 75% of whom were female. The average age of participants was 43 years±15 years. Participants completed an online questionnaire that consisted of a compulsory module that assessed self-reported psychiatric history, clinical depression using the Composite Interview Diagnostic Interview Short Form and experiences of using commonly prescribed antidepressants. Further voluntary modules assessed a wide range of traits of relevance to psychopathology. Participants who reported they were willing to provide a DNA s le (75%) were sent a saliva kit in the mail. 95% of participants reported being given a diagnosis of depression by a medical practitioner and 88% met the criteria for a lifetime depressive episode. 68% of the s le report having been diagnosed with another psychiatric disorder in addition to depression. In line with findings from clinical trials, only 33% of the s le report responding well to the first antidepressant they were prescribed. A number of analyses to investigate the genetic architecture of depression and common comorbidities will be conducted. The cohort will contribute to the global effort to identify genetic variants that increase risk to depression. Furthermore, a thorough investigation of genetic and psychosocial predictors of antidepressant response and side effects is planned.
Genome‐wide association study reveals greater polygenic loading for schizophrenia in cases with a family history of illness
Publisher: Wiley
Date: 11-12-2015
DOI: 10.1002/AJMG.B.32402
Genome-wide association study identifies 30 loci associated with bipolar disorder
Publisher: Springer Science and Business Media LLC
Date: 05-2019
Synthetic associations created by rare variants do not explain most GWAS results.
Publisher: Public Library of Science (PLoS)
Date: 18-01-2011
Evidence for Genetic Overlap Between Schizophrenia and Age at First Birth in Women
Publisher: American Medical Association (AMA)
Date: 05-2016
Sex-specific association between bipolar affective disorder in women and GPR50, an X-linked orphan G protein-coupled receptor.
Publisher: Springer Science and Business Media LLC
Date: 28-09-2005
Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data
Publisher: Springer Science and Business Media LLC
Date: 28-04-2020
DOI: 10.1038/S41467-020-15587-0
Abstract: Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation. Current high-throughput technologies for detecting PAIs, such as promoter capture Hi-C, are not scalable to large cohorts. Here, we present an analytical approach that uses summary-level data from cohort-based DNA methylation (DNAm) quantitative trait locus (mQTL) studies to predict PAIs. Using mQTL data from human peripheral blood ( $$n = 1980$$ n = 1980 ), we predict 34,797 PAIs which show strong overlap with the chromatin contacts identified by previous experimental assays. The promoter-interacting DNAm sites are enriched in enhancers or near expression QTLs. Genes whose promoters are involved in PAIs are more actively expressed, and gene pairs with promoter-promoter interactions are enriched for co-expression. Integration of the predicted PAIs with GWAS data highlight interactions among 601 DNAm sites associated with 15 complex traits. This study demonstrates the use of mQTL data to predict PAIs and provides insights into the role of PAIs in complex trait variation.
Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index
Publisher: Springer Science and Business Media LLC
Date: 31-08-2015
DOI: 10.1038/NG.3390
A DNA methylation biomarker of alcohol consumption
Publisher: Springer Science and Business Media LLC
Date: 15-11-2016
DOI: 10.1038/MP.2016.192
Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes
Publisher: Elsevier BV
Date: 06-2018
Rare genetic variants underlie outlying levels of DNA methylation and gene-expression
Publisher: Oxford University Press (OUP)
Date: 15-02-2023
DOI: 10.1093/HMG/DDAD028
Abstract: Testing the effect of rare variants on phenotypic variation is difficult due to the need for extremely large cohorts to identify associated variants given expected effect sizes. An alternative approach is to investigate the effect of rare genetic variants on DNA methylation (DNAm) as effect sizes are expected to be larger for molecular traits compared with complex traits. Here, we investigate DNAm in healthy ageing populations—the Lothian Birth Cohorts of 1921 and 1936—and identify both transient and stable outlying DNAm levels across the genome. We find an enrichment of rare genetic single nucleotide polymorphisms (SNPs) within 1 kb of DNAm sites in in iduals with stable outlying DNAm, implying genetic control of this extreme variation. Using a family-based cohort, the Brisbane Systems Genetics Study, we observed increased sharing of DNAm outliers among more closely related in iduals, consistent with these outliers being driven by rare genetic variation. We demonstrated that outlying DNAm levels have a functional consequence on gene expression levels, with extreme levels of DNAm being associated with gene expression levels toward the tails of the population distribution. This study demonstrates the role of rare SNPs in the phenotypic variation of DNAm and the effect of extreme levels of DNAm on gene expression.
Estimation of pleiotropy between complex diseases using single-nucleotide polymorphism-derived genomic relationships and restricted maximum likelihood.
Publisher: Oxford University Press (OUP)
Date: 26-07-2012
DOI: 10.1093/BIOINFORMATICS/BTS474
Abstract: Summary: Genetic correlations are the genome-wide aggregate effects of causal variants affecting multiple traits. Traditionally, genetic correlations between complex traits are estimated from pedigree studies, but such estimates can be confounded by shared environmental factors. Moreover, for diseases, low prevalence rates imply that even if the true genetic correlation between disorders was high, co-aggregation of disorders in families might not occur or could not be distinguished from chance. We have developed and implemented statistical methods based on linear mixed models to obtain unbiased estimates of the genetic correlation between pairs of quantitative traits or pairs of binary traits of complex diseases using population-based case–control studies with genome-wide single-nucleotide polymorphism data. The method is validated in a simulation study and applied to estimate genetic correlation between various diseases from Wellcome Trust Case Control Consortium data in a series of bivariate analyses. We estimate a significant positive genetic correlation between risk of Type 2 diabetes and hypertension of ~0.31 (SE 0.14, P = 0.024). Availability: Our methods, appropriate for both quantitative and binary traits, are implemented in the freely available software GCTA (oftware/gcta/reml_bivar.html). Contact: hong.lee@uq.edu.au Supplementary Information: Supplementary data are available at Bioinformatics online.
Genetics of schizophrenia and bipolar affective disorder: Strategies to identify candidate genes
Publisher: Cold Spring Harbor Laboratory
Date: 2003
Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank
Publisher: Springer Science and Business Media LLC
Date: 10-02-2021
DOI: 10.1186/S13229-020-00407-5
Abstract: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition whose biological basis is yet to be elucidated. The Australian Autism Biobank (AAB) is an initiative of the Cooperative Research Centre for Living with Autism (Autism CRC) to establish an Australian resource of biospecimens, phenotypes and genomic data for research on autism. Genome-wide single-nucleotide polymorphism genotypes were available for 2,477 in iduals (after quality control) from 546 families (436 complete), including 886 participants aged 2 to 17 years with diagnosed ( n = 871) or suspected ( n = 15) ASD, 218 siblings without ASD, 1,256 parents, and 117 unrelated children without an ASD diagnosis. The genetic data were used to confirm familial relationships and assign ancestry, which was majority European ( n = 1,964 European in iduals). We generated polygenic scores (PGS) for ASD, IQ, chronotype and height in the subset of Europeans, and in 3,490 unrelated ancestry-matched participants from the UK Biobank. We tested for group differences for each PGS, and performed prediction analyses for related phenotypes in the AAB. We called copy-number variants (CNVs) in all participants, and intersected these with high-confidence ASD- and intellectual disability (ID)-associated CNVs and genes from the public domain. The ASD ( p = 6.1e−13), sibling ( p = 4.9e−3) and unrelated ( p = 3.0e−3) groups had significantly higher ASD PGS than UK Biobank controls, whereas this was not the case for height—a control trait. The IQ PGS was a significant predictor of measured IQ in undiagnosed children ( r = 0.24, p = 2.1e−3) and parents ( r = 0.17, p = 8.0e−7 4.0% of variance), but not the ASD group. Chronotype PGS predicted sleep disturbances within the ASD group ( r = 0.13, p = 1.9e−3 1.3% of variance). In the CNV analysis, we identified 13 in iduals with CNVs overlapping ASD/ID-associated CNVs, and 12 with CNVs overlapping ASD/ID/developmental delay-associated genes identified on the basis of de novo variants. This dataset is modest in size, and the publicly-available genome-wide-association-study (GWAS) summary statistics used to calculate PGS for ASD and other traits are relatively underpowered. We report on common genetic variation and rare CNVs within the AAB. Prediction analyses using currently available GWAS summary statistics are largely consistent with expected relationships based on published studies. As the size of publicly-available GWAS summary statistics grows, the phenotypic depth of the AAB dataset will provide many opportunities for analyses of autism profiles and co-occurring conditions, including when integrated with other omics datasets generated from AAB biospecimens (blood, urine, stool, hair).
Methods for predicting rates of inbreeding in selected populations.
Publisher: Springer Science and Business Media LLC
Date: 10-1990
DOI: 10.1007/BF00226752
Comparison of genotypic and phenotypic correlations: Cheverud's conjecture in humans
Publisher: Oxford University Press (OUP)
Date: 08-05-2018
DOI: 10.1534/GENETICS.117.300630
Abstract: Cheverud’s conjecture asserts that the use of phenotypic correlations as proxies for genetic correlations in situations where genetic data is not available is appropriate. Although empirical evidence for this has been found across... Accurate estimation of genetic correlation requires large s le sizes and access to genetically informative data, which are not always available. Accordingly, phenotypic correlations are often assumed to reflect genotypic correlations in evolutionary biology. Cheverud’s conjecture asserts that the use of phenotypic correlations as proxies for genetic correlations is appropriate. Empirical evidence of the conjecture has been found across plant and animal species, with results suggesting that there is indeed a robust relationship between the two. Here, we investigate the conjecture in human populations, an analysis made possible by recent developments in availability of human genomic data and computing resources. A s le of 108,035 British European in iduals from the UK Biobank was split equally into discovery and replication datasets. Seventeen traits were selected based on s le size, distribution, and heritability. Genetic correlations were calculated using linkage disequilibrium score regression applied to the genome-wide association summary statistics of pairs of traits, and compared within and across datasets. Strong and significant correlations were found for the between-dataset comparison, suggesting that the genetic correlations from one independent s le were able to predict the phenotypic correlations from another independent s le within the same population. Designating the selected traits as morphological or nonmorphological indicated little difference in correlation. The results of this study support the existence of a relationship between genetic and phenotypic correlations in humans. This finding is of specific interest in anthropological studies, which use measured phenotypic correlations to make inferences about the genetics of ancient human populations.
10 years of GWAS discovery: biology, function, and translation
Publisher: Elsevier BV
Date: 07-2017
Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders
Publisher: Springer Science and Business Media LLC
Date: 26-03-2021
DOI: 10.1186/S13059-021-02275-5
Abstract: People with neurodegenerative disorders show erse clinical syndromes, genetic heterogeneity, and distinct brain pathological changes, but studies report overlap between these features. DNA methylation (DNAm) provides a way to explore this overlap and heterogeneity as it is determined by the combined effects of genetic variation and the environment. In this study, we aim to identify shared blood DNAm differences between controls and people with Alzheimer’s disease, amyotrophic lateral sclerosis, and Parkinson’s disease. We use a mixed-linear model method (MOMENT) that accounts for the effect of (un)known confounders, to test for the association of each DNAm site with each disorder. While only three probes are found to be genome-wide significant in each MOMENT association analysis of amyotrophic lateral sclerosis and Parkinson’s disease (and none with Alzheimer’s disease), a fixed-effects meta-analysis of the three disorders results in 12 genome-wide significant differentially methylated positions. Predicted immune cell-type proportions are disrupted across all neurodegenerative disorders. Protein inflammatory markers are correlated with profile sum-scores derived from disease-associated immune cell-type proportions in a healthy aging cohort. In contrast, they are not correlated with MOMENT DNAm-derived profile sum-scores, calculated using effect sizes of the 12 differentially methylated positions as weights. We identify shared differentially methylated positions in whole blood between neurodegenerative disorders that point to shared pathogenic mechanisms. These shared differentially methylated positions may reflect causes or consequences of disease, but they are unlikely to reflect cell-type proportion differences.
Estimation and partition of heritability in human populations using whole-genome analysis methods.
Publisher: Annual Reviews
Date: 23-11-2013
DOI: 10.1146/ANNUREV-GENET-111212-133258
Abstract: Understanding genetic variation of complex traits in human populations has moved from the quantification of the resemblance between close relatives to the dissection of genetic variation into the contributions of in idual genomic loci. However, major questions remain unanswered: How much phenotypic variation is genetic how much of the genetic variation is additive and can be explained by fitting all genetic variants simultaneously in one model, and what is the joint distribution of effect size and allele frequency at causal variants? We review and compare three whole-genome analysis methods that use mixed linear models (MLMs) to estimate genetic variation. In all methods, genetic variation is estimated from the relationship between close or distant relatives on the basis of pedigree information and/or single nucleotide polymorphisms (SNPs). We discuss theory, estimation procedures, bias, and precision of each method and review recent advances in the dissection of genetic variation of complex traits in human populations. By using genome-wide data, it is now established that SNPs in total account for far more of the genetic variation than the statistically highly significant SNPs that have been detected in genome-wide association studies. All SNPs together, however, do not account for all of the genetic variance estimated by pedigree-based methods. We explain possible reasons for this remaining “missing heritability.”
Genetic analyses of medication-use and implications for precision medicine
Publisher: Cold Spring Harbor Laboratory
Date: 20-12-2018
DOI: 10.1101/501049
Abstract: It is common that one medication is prescribed for several indications, and conversely that several medications are prescribed for the same indication, suggesting a complex biological network for disease risk and its relationship with pharmacological function. Genome-wide association studies (GWASs) of medication-use may contribute to understanding of disease etiology, generation of new leads relevant for drug discovery and quantify prospects for precision medicine. We conducted GWAS to profile self-reported medication-use from 23 categories in approximately 320,000 in iduals from the UK Biobank. A total of 505 independent genetic loci that met stringent criteria for statistical significance were identified. We investigated the implications of these GWAS findings in relation to biological mechanism, drug target identification and genetic risk stratification of disease. Amongst the medication-associated genes were 16 known therapeutic-effect target genes for medications from 9 categories.
150 risk variants for diverticular disease of intestine prioritize cell types and enable polygenic prediction of disease susceptibility
Publisher: Elsevier BV
Date: 07-2023
Unraveling the Genetic Etiology of Adult Antisocial Behavior: A Genome-Wide Association Study
Publisher: Public Library of Science (PLoS)
Date: 15-10-2012
Nick Martin and the Genetics of Depression: Sample Size, Sample Size, Sample Size
Publisher: Cambridge University Press (CUP)
Date: 04-2020
DOI: 10.1017/THG.2020.13
Abstract: Nick Martin is a pioneer in recognizing the need for large s le size to study the complex, heterogeneous and polygenic disorders of common mental disorders. In the predigital era, questionnaires were mailed to thousands of twin pairs around Australia. Always quick to adopt new technology, Nick’s studies progressed to phone interviews and then online. Moreover, Nick was early to recognize the value of collecting DNA s les. As genotyping technologies improved over the years, these twin and family cohorts were used for linkage, candidate gene and genome-wide association studies. These cohorts have underpinned many analyses to disentangle the complex web of genetic and lifestyle factors associated with mental health. With characteristic foresight, Nick is chief investigator of our Australian Genetics of Depression Study, which has recruited 16,000 people with self-reported depression (plus DNA s les) over a time frame of a few months — analyses are currently ongoing. The mantra of s le size, s le size, s le size has guided Nick’s research over the last 30 years and continues to do so.
Intrinsically Stretchable Electroluminescent Elastomers with Self‐Confinement Effect for Highly Efficient Non‐Blended Stretchable OLEDs
Publisher: Wiley
Date: 07-12-2022
Abstract: Ultra‐flexible stretchable organic light‐emitting diodes (OLEDs) are emerging as a basic component of flexible electronics and human‐machine interfaces. However, the brightness and efficiency of stretchable OLEDs remain still far inferior to their rigid counterparts, owing to the scarcity of satisfactory stretchable electroluminescent materials. Herein, we explore a general concept based on the self‐confinement effect to dramatically improve the stretchability of elastomers, without affecting electroluminescent properties. The balanced rigid/flexible chain dynamics under self‐confinement significantly reduces the modulus of the elastomers, resulting in the maximum strain reaching 806 %. Ultra‐flexible stretchable OLEDs have been constructed based on the resulting ISEEs, achieving unprecedented high‐performance non‐blended stretchable OLEDs. The results suggest an effective molecular design strategy for highly deformable stretchable displays and flexible electronics.
ALS in Danish Registries
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 20-02-2020
DOI: 10.1212/NXG.0000000000000398
Abstract: To investigate the genetic contribution to amyotrophic lateral sclerosis (ALS) and the phenotypic and genetic associations between ALS and psychiatric and cardiovascular disorders (CVD) we used the national registry data from Denmark linked to first-degree relatives to estimate heritability and cross-trait parameters. ALS cases and 100 sex and birth-matched controls per case from the Danish Civil Registration System were linked to their records in the Danish National Patient Registry. Cases and controls were compared for (1) risk of ALS in first-degree relatives, used to estimate heritability, (2) comorbidity with psychiatric disorders and CVD, and (3) risk of psychiatric disorders and CVD in first-degree relatives. 5,808 ALS cases and 580,800 controls were identified. Fifteen percent of cases and controls could be linked to both parents and full siblings, whereas 70% could be linked to children. (1) We estimated the heritability of ALS to be 0.43 (95% CI, 0.34–0.53). (2) We found increased rates of diagnosis of mental disorders (risk ratio = 1.18 95% CI, 1.09–1.29) and CVD in those later diagnosed with ALS. (3) In first-degree relatives of those with ALS, we found increased rate of schizophrenia (1.17 95% CI, 0.96–1.42), but no evidence for increased risk CVD. Heritability of ALS is lower than commonly reported. There is likely a genetic relationship between ALS and schizophrenia, and a nongenetic relationship between ALS and CVD.
Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders
Publisher: Springer Science and Business Media LLC
Date: 11-11-2019
DOI: 10.1038/S41380-019-0558-2
Abstract: Multiplex families with a high prevalence of a psychiatric disorder are often examined to identify rare genetic variants with large effect sizes. In the present study, we analysed whether the risk for bipolar disorder (BD) in BD multiplex families is influenced by common genetic variants. Furthermore, we investigated whether this risk is conferred mainly by BD-specific risk variants or by variants also associated with the susceptibility to schizophrenia or major depression. In total, 395 in iduals from 33 Andalusian BD multiplex families (166 BD, 78 major depressive disorder, 151 unaffected) as well as 438 subjects from an independent, BD case/control cohort (161 unrelated BD, 277 unrelated controls) were analysed. Polygenic risk scores (PRS) for BD, schizophrenia (SCZ), and major depression were calculated and compared between the cohorts. Both the familial BD cases and unaffected family members had higher PRS for all three psychiatric disorders than the independent controls, with BD and SCZ being significant after correction for multiple testing, suggesting a high baseline risk for several psychiatric disorders in the families. Moreover, familial BD cases showed significantly higher BD PRS than unaffected family members and unrelated BD cases. A plausible hypothesis is that, in multiplex families with a general increase in risk for psychiatric disease, BD development is attributable to a high burden of common variants that confer a specific risk for BD. The present analyses demonstrated that common genetic risk variants for psychiatric disorders are likely to contribute to the high incidence of affective psychiatric disorders in the multiplex families. However, the PRS explained only part of the observed phenotypic variance, and rare variants might have also contributed to disease development.
Sleep Disorders and Risk of Incident Depression: A Population Case–Control Study
Publisher: Cambridge University Press (CUP)
Date: 06-2019
DOI: 10.1017/THG.2019.22
Abstract: We sought to investigate the risk of incident major depressive disorder (MDD) attributable to a range of sleep disorders in the Danish population. Data were obtained by linking longitudinal Danish population-based registers. A total of 65,739 in iduals who had first onset of depression between 1995 and 2013 were selected as cases. For each case, a set of 20 controls of the same sex, birth month and year and who had not had depression by the date that the case was diagnosed were selected at random form the population ( N = 1,307,580 in total). We examined whether there was an increased rate of prior sleep disorders in MDD cases compared to controls using conditional logistic regression. An increased risk of incident depression in cases was found for all sleep disorders analyzed. Highest incidence rate ratios (IRRs) were found for circadian rhythm disorders (IRR = 7.06 [2.78–17.91]) and insomnia of inorganic origin (IRR = 6.76 [4.37–10.46]). The lowest estimated IRR was for narcolepsy (IRR = 2.00 [1.26–3.17]). Those diagnosed with a sleep disorder in the last 6 months were at highest risk of developing depression compared to those with at least 1 year since diagnosis (3.10 vs. 2.36). Our results suggest that having any sleep disorder is a risk factor for incident depression. Depression screening should be considered for patients with sleep disorders, and where possible, long-term follow-up for mental health problems is advisable.
Exploring Boundaries for the Genetic Consequences of Assortative Mating for Psychiatric Traits
Publisher: American Medical Association (AMA)
Date: 11-2016
DOI: 10.1001/JAMAPSYCHIATRY.2016.2566
Abstract: Considerable partner resemblances have been found for a wide range of psychiatric disorders, meaning that partners of affected in iduals have an increased risk of being affected compared with partners of unaffected in iduals. If this resemblance is reflected in genetic similarity between partners, genetic risk is anticipated to accumulate in offspring, but these potential consequences have not been quantified and have been left implicit. The anticipated consequences of partner resemblance on prevalence and heritability of psychiatric traits in the offspring generation were modeled for disorders with varying heritabilities, population prevalence (lifetime risk), and magnitudes of partner resemblance. These models facilitate interpretation for a wide range of psychiatric disorders, such as autism, schizophrenia, and depression. The genetic consequences of partner resemblance are most pronounced when attributable to phenotypic assortment (driven by the psychiatric trait). Phenotypic assortment results in increased genetic variance in the offspring generation, which may result in increased heritability and population prevalence. These consequences add generation after generation to a limit, but assortative mating is unlikely to balance the impact of reduced fecundity of patients with psychiatric disorders in the long term. This modeling suggests that the heritabilities of psychiatric disorders are unlikely to increase by more than 5% from 1 generation of assortative mating (maximally 13% across multiple generations). The population prevalence will increase most for less common disorders with high heritability for ex le, the prevalence of autism might increase by 1.5-fold after 1 generation of assortative mating (≥2.4-fold in the long term) depending on several assumptions. The considerable partner resemblances found for psychiatric disorders deserve more detailed interpretation than has been provided thus far. Although the limitations of modeling are emphasized, the anticipated consequences are at most modest for the heritability but may be considerable for the population prevalence of rare disorders with a high heritability.
Genetic effects influencing risk for major depressive disorder in China and Europe
Publisher: Springer Science and Business Media LLC
Date: 28-03-2017
DOI: 10.1038/TP.2016.292
Abstract: Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30–40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33 female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497 log 10 Bayes Factor=8.08) but failed to replicate in an independent European s le ( P =0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies.
Gut microbiota in ALS: possible role in pathogenesis?
Publisher: Informa UK Limited
Date: 29-05-2019
Prediction of rates of inbreeding in selected populations
Publisher: Hindawi Limited
Date: 02-1990
DOI: 10.1017/S0016672300025180
Abstract: A method is presented for the prediction of rate of inbreeding for populations with discrete generations. The matrix of Wright's numerator relationships is partitioned into ‘contribution’ matrices which describe the contribution of the Mendelian s ling of genes of ancestors in a given generation to the relationship between in iduals in later generations. These contributions stabilize with time and the value to which they stabilize is shown to be related to the asymptotic rate of inbreeding and therefore also the effective population size, where N is the number of in iduals per generation and μ r and are the mean and variance of long-term relationships or long-term contributions. These stabilized values are then predicted using a recursive equation via the concept of selective advantage for populations with hierarchical mating structures undergoing mass selection. Account is taken of the change in genetic parameters as a consequence of selection and also the increasing ‘competitiveness’ of contemporaries as selection proceeds. Ex les are given and predicted rates of inbreeding are compared to those calculated in simulations. For populations of 20 males and 20, 40, 100 or 200 females the rate of inbreeding was found to increase by as much as 75% over the rate of inbreeding in an unselected population depending on mating ratio, selection intensity and heritability of the selected trait. The prediction presented here estimated the rate of inbreeding usually within 5% of that calculated from simulation.
Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle
Publisher: Cold Spring Harbor Laboratory
Date: 31-05-2022
DOI: 10.1101/2022.05.30.494093
Abstract: Many quantitative trait loci (QTL) are located in non-coding genomic regions. Therefore, QTL are assumed to affect gene regulation. Gene expression and RNA splicing are primary steps of transcription so QTL changing gene expression (eQTL) or RNA splicing (sQTL) are expected to significantly contribute to phenotypic variations. Here, we quantify the contribution of eQTL and sQTL detected from 16 tissues (N~5,000) to 37 complex traits of ~120k cattle. Using Bayesian methods, we show that including more regulatory variants in the model explains larger proportions of heritability. Across traits, cis and trans eQTL and sQTL detected from 16 tissues jointly explain ~70% (SE=0.5%) of heritability, 44% more than expected from the same number of random variants, where trans e/sQTL contribute 24% (14% more than expected). Multi-tissue cis and trans e/sQTL also explain 71% (SE=0.3%) of heritability for the metabolome, demonstrating the essential role of proximal and distal regulatory variants in shaping mammalian phenotypes.
Appraisals of Stressful Life Events as a Genetically-Linked Mechanism in the Stress–Depression Relationship
Publisher: Springer Science and Business Media LLC
Date: 10-05-2011
Students’, colleagues’ and research partners’ experience about work and accomplishments from collaborating with Robin Thompson
Publisher: Wiley
Date: 27-06-2019
DOI: 10.1111/JBG.12418
A common missense variant of LILRB5 is associated with statin intolerance and myalgia
Publisher: Oxford University Press (OUP)
Date: 29-08-2017
W21. EXPLORING THE GENETIC ASSOCIATION BETWEEN MULTI-OMIC TRAITS AND PSYCHIATRIC DIAGNOSIS, PROGNOSIS AND TREATMENT RESPONSE
Publisher: Elsevier BV
Date: 10-2023
Spatial clustering of childhood leukaemia: summary results from the EUROCLUS project
Publisher: Springer Science and Business Media LLC
Date: 03-1998
DOI: 10.1038/BJC.1998.133
Abstract: The interpretation of reports of clusters of childhood leukaemia is difficult, first because little is known about the causes of the disease, and second because there is insufficient information on whether cases show a generalized tendency to cluster geographically. The EUROCLUS project is a European collaborative study whose primary objective is to determine whether the residence locations of cases at diagnosis show a general tendency towards spatial clustering. The second objective is to interpret any patterns observed and, in particular, to see if clustering can be explained in terms of either infectious agents or environmental hazards as aetiological agents. The spatial distribution of 13351 cases of childhood leukaemia diagnosed in 17 countries between 1980 and 1989 has been analysed using the Potthoff-Whittinghill method. The overall results show statistically significant evidence of clustering of total childhood leukaemia within small census areas (P=0.03) but the magnitude of the clustering is small (extra-Poisson component of variance (%) = 1.7 with 90% confidence interval 0.2-3.1). The clustering is most marked in areas that have intermediate population density (150-499 persons km[-2]). It cannot be attributed to any specific age group at diagnosis or cell type and involves spatial aggregation of cases of different ages and cell types. The results indicate that intense clusters are a rare phenomenon that merit careful investigation, although aetiological insights are more likely to come from investigation of large numbers of cases. We present a method for detecting clustering that is simple and readily available to cancer registries and similar groups.
Phenotypic and discordant-monozygotic analyses of stress and perceived social support as antecedents to or sequelae of risk for depression.
Publisher: Cambridge University Press (CUP)
Date: 10-2009
Abstract: The associations between social support and depression, and between stress and depression have been the subject of considerable research, and although this has included longitudinal designs, these have rarely controlled for genetic effects that mediate these associations. The s le comprised 7,356 female and 4,882 male participants aged 18–95 from the Australian NHMRC Twin Registry (ATR). Of these, between 100 and 324 female pairs and between 41 and 169 male pairs, depending on the measure, were monozygotic (MZ) pairs discordant for depression. We use the co-twin control design in combination with prospective analyses to explore the association between a composite of predictors (perceived social support, stress, and support × stress) and depression. With familial effects included, both perceived support and stress were antecedents to, and sequelae of, depression, but no stress-buffering occurred. With familial effects controlled, stress was a sequela of a prior depressive episode, and neither lack of support nor stress were antecedents to depression, though their interaction approached significance for males. The male twin who later became depressed had previously reported lower perceived support in the face of multiple stressors compared to his co-twin who did not become depressed. We show that associations commonly observed with prospective designs are partly due to familial factors.
Schizophrenia polygenic risk scores in youth mental health: preliminary associations with diagnosis, clinical stage and functioning
Publisher: Royal College of Psychiatrists
Date: 22-02-2021
DOI: 10.1192/BJO.2021.14
Abstract: The schizophrenia polygenic risk score (SCZ-PRS) is an emerging tool in psychiatry. We aimed to evaluate the utility of SCZ-PRS in a young, transdiagnostic, clinical cohort. SCZ-PRSs were calculated for young people who presented to early-intervention youth mental health clinics, including 158 patients of European ancestry, 113 of whom had longitudinal outcome data. We examined associations between SCZ-PRS and diagnosis, clinical stage and functioning at initial assessment, and new-onset psychotic disorder, clinical stage transition and functional course over time in contact with services. Compared with a control group, patients had elevated PRSs for schizophrenia, bipolar disorder and depression, but not for any non-psychiatric phenotype (for ex le cardiovascular disease). Higher SCZ-PRSs were elevated in participants with psychotic, bipolar, depressive, anxiety and other disorders. At initial assessment, overall SCZ-PRSs were associated with psychotic disorder (odds ratio (OR) per s.d. increase in SCZ-PRS was 1.68, 95% CI 1.08–2.59, P = 0.020), but not assignment as clinical stage 2+ (i.e. discrete, persistent or recurrent disorder) (OR = 0.90, 95% CI 0.64–1.26, P = 0.53) or functioning ( R = 0.03, P = 0.76). Longitudinally, overall SCZ-PRSs were not significantly associated with new-onset psychotic disorder (OR = 0.84, 95% CI 0.34–2.03, P = 0.69), clinical stage transition (OR = 1.02, 95% CI 0.70–1.48, P = 0.92) or persistent functional impairment (OR = 0.84, 95% CI 0.52–1.38, P = 0.50). In this preliminary study, SCZ-PRSs were associated with psychotic disorder at initial assessment in a young, transdiagnostic, clinical cohort accessing early-intervention services. Larger clinical studies are needed to further evaluate the clinical utility of SCZ-PRSs, especially among in iduals with high SCZ-PRS burden.
High loading of polygenic risk in cases with chronic schizophrenia
Publisher: Springer Science and Business Media LLC
Date: 09-2015
DOI: 10.1038/MP.2015.130
Abstract: Genomic risk profile scores (GRPSs) have been shown to predict case-control status of schizophrenia (SCZ), albeit with varying sensitivity and specificity. The extent to which this variability in prediction accuracy is related to differences in s ling strategies is unknown. Danish population-based registers and Neonatal Biobanks were used to identify two independent incident data sets (denoted target and replication) comprising together 1861 cases with SCZ and 1706 controls. A third data set was a German prevalent s le with diagnoses assigned to 1773 SCZ cases and 2161 controls based on clinical interviews. GRPSs were calculated based on the genome-wide association results from the largest SCZ meta-analysis yet conducted. As measures of genetic risk prediction, Nagelkerke pseudo-R(2) and variance explained on the liability scale were calculated. GRPS for SCZ showed positive correlations with the number of psychiatric admissions across all P-value thresholds in both the incident and prevalent s les. In permutation-based test, Nagelkerke pseudo-R(2) values derived from s les enriched for frequently admitted cases were found to be significantly higher than for the full data sets (Ptarget=0.017, Preplication=0.04). Overs ling of frequently admitted cases further resulted in a higher proportion of variance explained on the liability scale (improvementtarget= 50% improvementreplication= 162%). GRPSs are significantly correlated with chronicity of SCZ. Overs ling of cases with a high number of admissions significantly increased the amount of variance in liability explained by GRPS. This suggests that at least part of the effect of common single-nucleotide polymorphisms is on the deteriorative course of illness.
Additive Genetic Variation in Schizophrenia Risk Is Shared by Populations of African and European Descent
Publisher: Elsevier BV
Date: 09-2013
Hair Cortisol in Twins: Heritability and Genetic Overlap with Psychological Variables and Stress-System Genes
Publisher: Springer Science and Business Media LLC
Date: 10-11-2017
DOI: 10.1038/S41598-017-11852-3
Abstract: Hair cortisol concentration (HCC) is a promising measure of long-term hypothalamus-pituitary-adrenal (HPA) axis activity. Previous research has suggested an association between HCC and psychological variables, and initial studies of inter-in idual variance in HCC have implicated genetic factors. However, whether HCC and psychological variables share genetic risk factors remains unclear. The aims of the present twin study were to: (i) assess the heritability of HCC (ii) estimate the phenotypic and genetic correlation between HPA axis activity and the psychological variables perceived stress, depressive symptoms, and neuroticism using formal genetic twin models and molecular genetic methods, i.e. polygenic risk scores (PRS). HCC was measured in 671 adolescents and young adults. These included 115 monozygotic and 183 dizygotic twin-pairs. For 432 subjects PRS scores for plasma cortisol, major depression, and neuroticism were calculated using data from large genome wide association studies. The twin model revealed a heritability for HCC of 72%. No significant phenotypic or genetic correlation was found between HCC and the three psychological variables of interest. PRS did not explain variance in HCC. The present data suggest that HCC is highly heritable. However, the data do not support a strong biological link between HCC and any of the investigated psychological variables.
Phenotypic and genetic factors associated with donation of DNA and consent to record linkage for prescription history in the Australian Genetics of Depression Study
Publisher: Springer Science and Business Media LLC
Date: 24-11-2022
DOI: 10.1007/S00406-022-01527-0
Abstract: S les can be prone to ascertainment and attrition biases. The Australian Genetics of Depression Study is a large publicly recruited cohort (n = 20,689) established to increase the understanding of depression and antidepressant treatment response. This study investigates differences between participants who donated a saliva s le or agreed to linkage of their records compared to those who did not. We observed that older, male participants with higher education were more likely to donate a saliva s le. Self-reported bipolar disorder, ADHD, panic disorder, PTSD, substance use disorder, and social anxiety disorder were associated with lower odds of donating a saliva s le, whereas anorexia was associated with higher odds of donation. Male and younger participants showed higher odds of agreeing to record linkage. Participants with higher neuroticism scores and those with a history of bipolar disorder were also more likely to agree to record linkage whereas participants with a diagnosis of anorexia were less likely to agree. Increased likelihood of consent was associated with increased genetic susceptibility to anorexia and reduced genetic risk for depression, and schizophrenia. Overall, our results show moderate differences among these subs les. Most current epidemiological studies do not search for attrition biases at the genetic level. The possibility to do so is a strength of s les such as the AGDS. Our results suggest that analyses can be made more robust by identifying attrition biases both on the phenotypic and genetic level, and either contextualising them as a potential limitation or performing sensitivity analyses adjusting for them.
Genetic control of temperament traits across species: association of autism spectrum disorder risk genes with cattle temperament
Publisher: Springer Science and Business Media LLC
Date: 26-08-2020
DOI: 10.1186/S12711-020-00569-Z
Abstract: Temperament traits are of high importance across species. In humans, temperament or personality traits correlate with psychological traits and psychiatric disorders. In cattle, they impact animal welfare, product quality and human safety, and are therefore of direct commercial importance. We hypothesized that genetic factors that contribute to variation in temperament among in iduals within a species will be shared between humans and cattle. Using imputed whole-genome sequence data from 9223 beef cattle from three cohorts, a series of genome-wide association studies was undertaken on cattle flight time, a temperament phenotype measured as the time taken for an animal to cover a short-fixed distance after release from an enclosure. We also investigated the association of cattle temperament with polymorphisms in bovine orthologs of risk genes for neuroticism, schizophrenia, autism spectrum disorders (ASD), and developmental delay disorders in humans. Variants with the strongest associations were located in the bovine orthologous region that is involved in several behavioural and cognitive disorders in humans. These variants were also partially validated in independent cattle cohorts. Genes in these regions ( BARHL2 , NDN , SNRPN , MAGEL2 , A BCA12 , KIFAP3 , TOPAZ1 , FZD3 , UBE3A , and GABRA5 ) were enriched for the GO term neuron migration and were differentially expressed in brain and pituitary tissues in humans. Moreover, variants within 100 kb of ASD susceptibility genes were associated with cattle temperament and explained 6.5% of the total additive genetic variance in the largest cattle cohort. The ASD genes with the most significant associations were GABRB3 and CUL3 . Using the same 100 kb window, a weak association was found with polymorphisms in schizophrenia risk genes and no association with polymorphisms in neuroticism and developmental delay disorders risk genes. Our analysis showed that genes identified in a meta-analysis of cattle temperament contribute to neuron development functions and are differentially expressed in human brain tissues. Furthermore, some ASD susceptibility genes are associated with cattle temperament. These findings provide evidence that genetic control of temperament might be shared between humans and cattle and highlight the potential for future analyses to leverage results between species.
Research Review: The role of cytokines in depression in adolescents: a systematic review
Publisher: Wiley
Date: 04-06-2013
DOI: 10.1111/JCPP.12080
Abstract: While cytokines have been implicated in the pathophysiology of depression in adults, the potential role in younger age groups such as adolescents is less clear. This article therefore reviews the literature (a) to explore the relationship between cytokines and depression in adolescents, and (b) to examine how cytokines may be related to adolescent depression in the context of other neurobiological theories of depression. A systematic review of the scientific literature on the subject was conducted in February 2013, searching the Web of Knowledge, PubMed (Medline), PsycInfo and Cochrane electronic databases. Eighteen studies were identified measuring both depression or depressive symptoms and cytokines or immune markers in adolescents. Adolescents with depression show age-specific characteristics of the immune and inflammatory system, specifically in NK cell activity and in pro-inflammatory cytokines (such as IL-1β and TNF-α). In addition, the role of cytokines in adolescent depression is influenced by neurodevelopment, hormonal changes, stress and trauma. There may be differences in the neurobiology of adolescent major depressive disorder (MDD) compared with adult MDD. Increased understanding of the role of cytokines in adolescent MDD may lead to improved outcomes in the treatment of adolescent depression.
Genetic and phenotypic stability of measures of neuroticism over 22 years.
Publisher: Cambridge University Press (CUP)
Date: 10-2007
Abstract: People meeting diagnostic criteria for anxiety or depressive disorders tend to score high on the personality scale of neuroticism. Studying this dimension of personality can therefore give insights into the etiology of important psychiatric disorders. Neuroticism can be assessed easily via self-report questionnaires in large population s les. We have examined the genetic and phenotypic stability of neuroticism, measured up to 4 times over 22 years, on different scales, on a data set of 4999 families with over 20,000 in iduals completing at least 1 neuroticism questionnaire. The neuroticism scales used were the Eysenck Personality Questionnaire revised (EPQ-R), the EPQ-R shortened form, and the NEO 5 factor inventory personality questionnaire. The estimates of heritability of the in idual measures ranged from .26 ± .04 to .36 ± .03. Genetic, environmental, and phenotypic correlations averaged .91, .42, and .57 respectively. Despite the range in heritabilities, a more parsimonious ‘repeatability model’ of equal additive genetic variances and genetic correlations of unity could not be rejected. Use of multiple measures increases the effective heritability from .33 for a single measure to .43 for mean score because of the reduction in the estimate of the environmental variance, and this will increase power in genetic linkage or association studies of neuroticism.
CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits
Publisher: Springer Science and Business Media LLC
Date: 29-09-2017
DOI: 10.1038/S41467-017-00556-X
Abstract: There are few ex les of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult s les from 26 cohorts. The study reveals five CNV associations at 1q21.1, 3q29, 7q11.23, 11p14.2, and 18q21.32 and confirms two known loci at 16p11.2 and 22q11.21, implicating at least one anthropometric trait. The discovered CNVs are recurrent and rare (0.01–0.2%), with large effects on height ( .4 cm), weight ( kg), and body mass index (BMI) ( .5 kg/m 2 ). Burden analysis shows a 0.41 cm decrease in height, a 0.003 increase in waist-to-hip ratio and increase in BMI by 0.14 kg/m 2 for each Mb of total deletion burden ( P = 2.5 × 10 −10 , 6.0 × 10 −5 , and 2.9 × 10 −3 ). Our study provides evidence that the same genes (e.g., MC4R , FIBIN , and FMO5 ) harbor both common and rare variants affecting body size and that anthropometric traits share genetic loci with developmental and psychiatric disorders.
Disease and polygenic architecture: avoid trio design and appropriately account for unscreened control subjects for common disease
Publisher: Elsevier BV
Date: 02-2016
Expression of eEF1A2 is associated with clear cell histology in ovarian carcinomas: overexpression of the gene is not dependent on modifications at the EEF1A2 locus.
Publisher: Springer Science and Business Media LLC
Date: 17-04-2007
Multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults
Publisher: Springer Science and Business Media LLC
Date: 08-07-2020
Prediction of individual genetic risk to disease from genome-wide association studies.
Publisher: Cold Spring Harbor Laboratory
Date: 04-09-2007
DOI: 10.1101/GR.6665407
Abstract: Empirical studies suggest that the effect sizes of in idual causal risk alleles underlying complex genetic diseases are small, with most genotype relative risks in the range of 1.1–2.0. Although the increased risk of disease for a carrier is small for any single locus, knowledge of multiple-risk alleles throughout the genome could allow the identification of in iduals that are at high risk. In this study, we investigate the number and effect size of risk loci that underlie complex disease constrained by the disease parameters of prevalence and heritability. Then we quantify the value of prediction of genetic risk to disease using a range of realistic combinations of the number, size, and distribution of risk effects that underlie complex diseases. We propose an approach to assess the genetic risk of a disease in healthy in iduals, based on dense genome-wide SNP panels. We test this approach using simulation. When the number of loci contributing to the disease is , a large case-control study is needed to identify a set of risk loci for use in predicting the disease risk of healthy people not included in the case-control study. For diseases controlled by 1000 loci of mean relative risk of only 1.04, a case-control study with 10,000 cases and controls can lead to selection of ∼75 loci that explain % of the genetic variance. The 5% of people with the highest predicted risk are three to seven times more likely to suffer the disease than the population average, depending on heritability and disease prevalence. Whether an in idual with known genetic risk develops the disease depends on known and unknown environmental factors.
From Mendel to quantitative genetics in the genome era: the scientific legacy of W. G. Hill
Publisher: Springer Science and Business Media LLC
Date: 07-2022
DOI: 10.1038/S41588-022-01103-1
Abstract: The quantitative geneticist W. G. ('Bill') Hill, awardee of the 2018 Darwin Medal of the Royal Society and the 2019 Mendel Medal of the Genetics Society (United Kingdom), died on 17 December 2021 at the age of 81 years. Here, we pay tribute to his multiple key scientific contributions, which span population and evolutionary genetics, animal and plant breeding and human genetics. We discuss his theoretical research on the role of linkage disequilibrium (LD) and mutational variance in the response to selection, the origin of the widely used LD metric r
Asymptotic rates of response from index selection
Publisher: Cambridge University Press (CUP)
Date: 10-1989
DOI: 10.1017/S0003356100032347
Abstract: The reduction in additive genetic variance due to selection is investigated when index selection using family records is practised. A population of infinite size with no accumulation of inbreeding, an infinitesimal model and discrete generations are assumed. After several generations of selection, the additive genetic variance and the rate of response to selection reach an asymptote. A prediction of the asymptotic rate of response is considered to be more appropriate for comparing response from alternative breeding programmes and for comparing predicted and realized response than the response following the first generation of selection that is classically used. Algorithms to calculate asymptotic response rate are presented for selection based on indices which include some or all of the records of an in idual, its full- and half-sibs and its parental estimated breeding values. An index using all this information is used to predict response when selection is based on breeding values estimated by using a Best Linear Unbiased Prediction (BLUP) animal model, and predictions agree well with simulation results. The predictions are extended to multiple trait selection. Asymptotic responses are compared with one-generation responses for a variety of alternative breeding schemes differing in population structure, selection intensity and heritability of the trait. Asymptotic responses can be up to one-quarter less than one-generation responses, the difference increasing with selection intensity and accuracy of the index. Between family variance is reduced considerably by selection, perhaps to less than half its original value, so selection indices which do not account for this tend to place too much emphasis on family information. Asymptotic rates of response to selection, using indices including family information for traits not measurable on the in iduals available for selection, such as sex limited or post-slaughter traits, are found to be as much as two-fifths less than their expected one-generation responses. Despite this, the ranking of the breeding schemes is not greatly altered when compared by one-generation rather than asymptotic responses, so the one-generation prediction is usually likely to be adequate for determining optimum breeding structure.
Genome-wide study of DNA methylation in Amyotrophic Lateral Sclerosis identifies differentially methylated loci and implicates metabolic, inflammatory and cholesterol pathways
Publisher: Cold Spring Harbor Laboratory
Date: 24-03-2021
DOI: 10.1101/2021.03.12.21253115
Abstract: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with an estimated heritability of around 50%. DNA methylation patterns can serve as biomarkers of (past) exposures and disease progression, as well as providing a potential mechanism that mediates genetic or environmental risk. Here, we present a blood-based epigenome-wide association study (EWAS) meta-analysis in 10,462 s les (7,344 ALS patients and 3,118 controls), representing the largest case-control study of DNA methylation for any disease to date. We identified a total of 45 differentially methylated positions (DMPs) annotated to 42 genes, which are enriched for pathways and traits related to metabolism, cholesterol biosynthesis, and immunity. We show that DNA-methylation-based proxies for HDL-cholesterol, BMI, white blood cell (WBC) proportions and alcohol intake were independently associated with ALS. Integration of these results with our latest GWAS showed that cholesterol biosynthesis was causally related to ALS. Finally, we found that DNA methylation levels at several DMPs and blood cell proportion estimates derived from DNA methylation data, are associated with survival rate in patients, and could represent indicators of underlying disease processes.
Author Correction: Misestimation of heritability and prediction accuracy of male-pattern baldness
Publisher: Springer Science and Business Media LLC
Date: 20-11-2018
DOI: 10.1038/S41467-018-07400-W
Abstract: The original version of this Article contained an error in the spelling of the author Julia Sidorenko, which was incorrectly given as Julia Sirodenko. This has now been corrected in both the PDF and HTML versions of the Article. Further, the sixth sentence of the second paragraph of the Correspondence and the legend to Fig. 1 incorrectly omitted citation of work by Heilmann-Helmbach, S. et al. This has now been corrected in both the PDF and HTML versions of the Article.
Genetic predisposition to schizophrenia associated with increased use of cannabis
Publisher: Springer Science and Business Media LLC
Date: 24-06-2014
DOI: 10.1038/MP.2014.51
Choosing the best tools for comparative analyses of texts
Publisher: John Benjamins Publishing Company
Date: 29-10-2010
Abstract: What measurements should linguists use when comparing texts written by different writers? We report aspects of a systematic evaluation of 381 different language measures derived from 200 analytic tools, carried out during the pilot for a study exploring genetic contributions to language variation. The measures covered lexis, structure, meaning, and discourse features, and were evaluated with a focus on capturing numerically the qualitative features that linguists consider central to differentiating one text from another. We review principles for selecting analytic tools, and the choices faced by the researcher in processing and analysing data. We then identify and demonstrate five of the measures, which between them provide a useful profile of different linguistic features, and note correlations with psychometric measures taken for each writer. We conclude with some caveats regarding general issues of validity and some indications about potential links between our work and research into authorship attribution for forensic purposes
Partitioning the Heritability of Tourette Syndrome and Obsessive Compulsive Disorder Reveals Differences in Genetic Architecture
Publisher: Public Library of Science (PLoS)
Date: 24-10-2013
Association analysis of the chromosome 4p15-p16 candidate region for bipolar disorder and schizophrenia.
Publisher: Springer Science and Business Media LLC
Date: 24-04-2007
Abstract: Several independent linkage studies have identified chromosome 4p15-p16 as a putative region of susceptibility for bipolar disorder (BP), schizophrenia (SCZ) and related phenotypes. Previously, we identified two subregions (B and D) of the 4p15-p16 region that are shared by three of four 4p-linked families examined. Here, we describe a large-scale association analysis of regions B and D (3.8 and 4.5 Mb, respectively). We selected 408 haplotype-tagging single nucleotide polymorphisms (SNPs) on a block-by-block basis from the International HapMap project and tested them in 368 BP, 386 SCZ and 458 control in iduals. Nominal significance thresholds were determined using principal component analysis as implemented in the program SNPSpD. In region B, overlapping SNPs and haplotypes met the region-wide threshold (P<or=0.0005) at the global and in idual haplotype test level and clustered in two regions. In region D, no in idual SNPs were nominally significant, but multiple global and in idual haplotypes were associated with BP and/or SCZ (region-wide threshold, P<or=0.0003). These overlapping haplotypes fell into two regions. Within each of these four clusters, at least one globally significant haplotype withstood permutation testing (P(gp)<or=0.05). Five predicted genes were found within these associated regions, while Known/RefSeq genes, including KIAA0746 and PPARGC1A, mapped nearby. There were also nine other clusters within regions B and D with nominally significant haplotypes, but only at the in idual haplotype level. KIAA0746, PPARGC1A, GPR125, CCKAR and DKFZp761B107 overlapped with these regions. This study has identified significant associations between BP and SCZ within the chromosome 4p linkage region, resulting in candidate regions worthy of further investigation.
Multi-ancestry GWAS of major depression aids locus discovery, fine-mapping, gene prioritisation, and causal inference
Publisher: Cold Spring Harbor Laboratory
Date: 21-07-2022
DOI: 10.1101/2022.07.20.500802
Abstract: Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in s les of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 studies with 88,316 MD cases and 902,757 controls to previously reported data from in iduals of European ancestry. This includes s les of African (36% of effective s le size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latinx participants (32%). The multi-ancestry GWAS identified 190 significantly associated loci, 53 of them novel. For previously reported loci from GWAS in European ancestry the power-adjusted transferability ratio was 0.6 in the Hispanic/Latinx group and 0.3 in each of the other groups. Fine-mapping benefited from additional s le ersity: the number of credible sets with ≤5 variants increased from 3 to 12. A transcriptome-wide association study identified 354 significantly associated genes, 205 of them novel. Mendelian Randomisation showed a bidirectional relationship with BMI exclusively in s les of European ancestry. This first multi-ancestry GWAS of MD demonstrates the importance of large erse s les for the identification of target genes and putative mechanisms.
Assessment of Bidirectional Relationships Between Physical Activity and Depression Among Adults
Publisher: American Medical Association (AMA)
Date: 04-2019
DOI: 10.1001/JAMAPSYCHIATRY.2018.4175
Abstract: Increasing evidence shows that physical activity is associated with reduced risk for depression, pointing to a potential modifiable target for prevention. However, the causality and direction of this association are not clear physical activity may protect against depression, and/or depression may result in decreased physical activity. To examine bidirectional relationships between physical activity and depression using a genetically informed method for assessing potential causal inference. This 2-s le mendelian randomization (MR) used independent top genetic variants associated with 2 physical activity phenotypes—self-reported (n = 377 234) and objective accelerometer-based (n = 91 084)—and with major depressive disorder (MDD) (n = 143 265) as genetic instruments from the largest available, nonoverlapping genome-wide association studies (GWAS). GWAS were previously conducted in erse observational cohorts, including the UK Biobank (for physical activity) and participating studies in the Psychiatric Genomics Consortium (for MDD) among adults of European ancestry. Mendelian randomization estimates from each genetic instrument were combined using inverse variance weighted meta-analysis, with alternate methods (eg, weighted median, MR Egger, MR–Pleiotropy Residual Sum and Outlier [PRESSO]) and multiple sensitivity analyses to assess horizontal pleiotropy and remove outliers. Data were analyzed from May 10 through July 31, 2018. MDD and physical activity. GWAS summary data were available for a combined s le size of 611 583 adult participants. Mendelian randomization evidence suggested a protective relationship between accelerometer-based activity and MDD (odds ratio [OR], 0.74 for MDD per 1-SD increase in mean acceleration 95% CI, 0.59-0.92 P = .006). In contrast, there was no statistically significant relationship between MDD and accelerometer-based activity (β = −0.08 in mean acceleration per MDD vs control status 95% CI, −0.47 to 0.32 P = .70). Furthermore, there was no significant relationship between self-reported activity and MDD (OR, 1.28 for MDD per 1-SD increase in metabolic-equivalent minutes of reported moderate-to-vigorous activity 95% CI, 0.57-3.37 P = .48), or between MDD and self-reported activity (β = 0.02 per MDD in standardized metabolic-equivalent minutes of reported moderate-to-vigorous activity per MDD vs control status 95% CI, −0.008 to 0.05 P = .15). Using genetic instruments identified from large-scale GWAS, robust evidence supports a protective relationship between objectively assessed—but not self-reported—physical activity and the risk for MDD. Findings point to the importance of objective measurement of physical activity in epidemiologic studies of mental health and support the hypothesis that enhancing physical activity may be an effective prevention strategy for depression.
Sex differences in symptoms of depression in unrelated individuals and opposite-sex twin and sibling pairs.
Publisher: Cambridge University Press (CUP)
Date: 10-2006
DOI: 10.1375/TWIN.9.5.632
Abstract: Diagnosis of a major depressive episode by the Diagnostic and Statistical Manual of Mental Disorders of the American Psychiatric Association requires 5 out of 9 symptoms to be present. Therefore, in iduals may differ in the specific symptoms they experience and reach a diagnosis of depression via different pathways. It has been suggested that depressed women more often report symptoms of sleep disturbance, appetite or weight disturbance, fatigue, feelings of guilt/worthlessness and psychomotor retardation than depressed men. In the current study, we investigate whether depressed men and women differ in the symptoms they report. Two s les were selected from a s le of Dutch and Australian twins and siblings. First, Dutch and Australian unrelated depressed in iduals were selected. Second, a matched epidemiological s le was created consisting of opposite-sex twin and sibling pairs in which both members were depressed. No sex differences in prevalence rates for symptoms were found, with the exception of decreased weight in women in the s le of unrelated in iduals. In general, the similarities in symptoms seem to far outweigh the differences in symptoms between men and women. This signifies that men and women are alike in their symptom profiles for major depression and genes for depression are probably expressed in the same way in the two sexes.
Identification of 55,000 Replicated DNA Methylation QTL
Publisher: Springer Science and Business Media LLC
Date: 04-12-2018
DOI: 10.1038/S41598-018-35871-W
Abstract: DNA methylation plays an important role in the regulation of transcription. Genetic control of DNA methylation is a potential candidate for explaining the many identified SNP associations with disease that are not found in coding regions. We replicated 52,916 cis and 2,025 trans DNA methylation quantitative trait loci (mQTL) using methylation from whole blood measured on Illumina HumanMethylation450 arrays in the Brisbane Systems Genetics Study (n = 614 from 177 families) and the Lothian Birth Cohorts of 1921 and 1936 (combined n = 1366). The trans mQTL SNPs were found to be over-represented in 1 Mbp subtelomeric regions, and on chromosomes 16 and 19. There was a significant increase in trans mQTL DNA methylation sites in upstream and 5′ UTR regions. The genetic heritability of a number of complex traits and diseases was partitioned into components due to mQTL and the remainder of the genome. Significant enrichment was observed for height (p = 2.1 × 10 −10 ), ulcerative colitis (p = 2 × 10 −5 ), Crohn’s disease (p = 6 × 10 −8 ) and coronary artery disease (p = 5.5 × 10 −6 ) when compared to a random s le of SNPs with matched minor allele frequency, although this enrichment is explained by the genomic location of the mQTL SNPs.
Dissection of genetic variation and evidence for pleiotropy in male pattern baldness
Publisher: Springer Science and Business Media LLC
Date: 20-12-2018
DOI: 10.1038/S41467-018-07862-Y
Abstract: Male pattern baldness (MPB) is a sex-limited, age-related, complex trait. We study MPB genetics in 205,327 European males from the UK Biobank. Here we show that MPB is strongly heritable and polygenic, with pedigree-heritability of 0.62 (SE = 0.03) estimated from close relatives, and SNP-heritability of 0.39 (SE = 0.01) from conventionally-unrelated males. We detect 624 near-independent genome-wide loci, contributing SNP-heritability of 0.25 (SE = 0.01), of which 26 X-chromosome loci explain 11.6%. Autosomal genetic variance is enriched for common variants and regions of lower linkage disequilibrium. We identify plausible genetic correlations between MPB and multiple sex-limited markers of earlier puberty, increased bone mineral density ( r g = 0.15) and pancreatic β-cell function ( r g = 0.12). Correlations with reproductive traits imply an effect on fitness, consistent with an estimated linear selection gradient of -0.018 per MPB standard deviation. Overall, we provide genetic insights into MPB: a phenotype of interest in its own right, with value as a model sex-limited, complex trait.
Detection and quantification of inbreeding depression for complex traits from SNP data
Publisher: Proceedings of the National Academy of Sciences
Date: 26-07-2017
Abstract: Inbreeding depression (ID) is the reduction of fitness in offspring of related parents. This phenomenon can be quantified from SNP data through a number of measures of inbreeding. Our study addresses two key questions. How accurate are the different methods to estimate ID? And how and why should investigators choose among the multiple inbreeding measures to detect and quantify ID? Here, we compare the behaviors of ID estimates from three commonly used SNP-based measures of inbreeding and provide both theoretical and empirical arguments to answer these questions. Our work illustrates how to analyze SNP data efficiently to detect and quantify ID, across species and traits.
Concepts and misconceptions about the polygenic additive model applied to disease
Publisher: S. Karger AG
Date: 2016
DOI: 10.1159/000446931
Abstract: It is nearly one hundred years, since R.A. Fisher published his now famous paper that started the field of quantitative genetics. That paper reconciled Mendelian genetics (as exemplified by Mendel's peas) and the biometrical approach to quantitative traits (as exemplified by the correlation and regression approaches from Galton and Pearson), by showing that a simple model of many genes of small effects, each following Mendel's laws of segregation and inheritance, plus environmental variation could account for the observed resemblance between relatives. In this review, we discuss a number of concepts and misconceptions about the assumptions and limitations of polygenic models of common diseases in human populations.
A recessive genetic model and runs of homozygosity in major depressive disorder
Publisher: Wiley
Date: 30-01-2014
DOI: 10.1002/AJMG.B.32217
Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions
Publisher: Cold Spring Harbor Laboratory
Date: 09-10-2018
DOI: 10.1101/433367
Abstract: Major depression is a debilitating psychiatric illness that is typically associated with low mood, anhedonia and a range of comorbidities. Depression has a heritable component that has remained difficult to elucidate with current s le sizes due to the polygenic nature of the disorder. To maximise s le size, we meta-analysed data on 807,553 in iduals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 gene-sets associated with depression, including both genes and gene-pathways associated with synaptic structure and neurotransmission. Further evidence of the importance of prefrontal brain regions in depression was provided by an enrichment analysis. In an independent replication s le of 1,306,354 in iduals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant following multiple testing correction. Based on the putative genes associated with depression this work also highlights several potential drug repositioning opportunities. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding aetiology and developing new treatment approaches.
Investigating the relationship between iron and depression
Publisher: Elsevier BV
Date: 11-2017
DOI: 10.1016/J.JPSYCHIRES.2017.07.006
Abstract: Lower levels of circulating iron have been associated with depression. Our objective was to investigate the phenotypic and genetic relationship between measures of circulating levels of iron (serum iron, transferrin, transferrin saturation, and ferritin) and depressive symptoms. Data were available from ongoing studies at QIMR Berghofer Medical Research Institute (QIMRB), including twin adolescents (mean age 15.1 years, standard deviation (SD) 3.2 years), and twin adults (mean age 23.2 years, SD 2.2 years). In the adolescent cohort, there were 3416 participants from 1688 families. In the adult cohort there were 9035 participants from 4533 families. We estimated heritabilities of, and phenotypic and genetic correlations between, traits. We conducted analyses that linked results from published large-scale genome-wide association studies (including iron and Major Depressive Disorder) with our study s les using single SNP and multi-SNP genetic risk score analyses, and LD score regression analyses. In both cohorts, measures of iron, transferrin, transferrin saturation, and log 10 of ferritin (L10Fer) were all highly heritable, while depressive measures were moderately heritable. In adolescents, depression measures were higher in those in the middle 10th versus top 10th percentile of transferrin saturation measures (p = 0.002). Genetic profile risk scores of the iron measures were not significantly associated with depression in study participants. LD score analyses showed no significant genetic relationship between iron and depression. Genetic factors strongly influence iron measures in adolescents and adults. Using several different strategies we find no evidence for a genetic contribution to the relationship between blood measures of iron and measures of depression.
Investigating the potential effect of antihypertensive medication on psychiatric disorders: a mendelian randomisation study
Publisher: Cold Spring Harbor Laboratory
Date: 23-03-2020
DOI: 10.1101/2020.03.19.20039412
Abstract: There is growing evidence from observational studies that drugs used for the prevention and treatment of CVD may cause, exacerbate, or relieve neuropsychiatric symptoms. Use Mendelian randomisation (MR) analysis to investigate the potential effect of different antihypertensive drugs on schizophrenia, bipolar disorder and major depressive disorder. We conduct two s le MR using expression quantitative trait loci (eQTLs) for antihypertensive drug target genes as genetic instruments, together with summary data from published genome-wide association studies, to investigate the causal effect of changes in drug target gene expression (as proxies of drug exposure) on psychiatric disorders. A 1 standard deviation lower expression of the ACE gene in blood was associated with 4.0 mmHg (95% CI = 2.7 – 5.3) lower systolic blood pressure, but increased risk of schizophrenia (OR (95% CI) = 1.75 (1.28 – 2.38)). A concordant direction of effect was observed with ACE expression in brain tissue. Findings suggest an adverse effect of lower ACE expression on schizophrenia risk. This warrants further investigation to determine if lowering ACE activity for treatment of hypertension using ACE inhibitors (particularly centrally-acting drugs) may worsen symptoms in patients with schizophrenia, and whether there is any association between ACE inhibitor use and risk of (mainly late-onset) schizophrenia.
Empirical evaluation of the genetic similarity of samples from twin registries in Australia and the Netherlands using 359 STRP markers.
Publisher: Cambridge University Press (CUP)
Date: 08-2006
DOI: 10.1375/TWIN.9.4.600
Abstract: One way to achieve the large s le sizes required for genetic studies of complex traits is to combine s les collected by different groups. It is not often clear, however, whether this practice is reasonable from a genetic perspective. To assess the comparability of s les from the Australian and the Netherlands twin studies, we estimated F st (the proportion of total genetic variability attributable to genetic differences between cohorts) based on 359 short tandem repeat polymorphisms in 1068 in iduals. F st was estimated to be 0.30% between the Australian and the Netherlands cohorts, a smaller value than between many European groups. We conclude that it is reasonable to combine the Australian and the Netherlands s les for joint genetic analyses.
Project MinE: study design and pilot analyses of a large-scale whole-genome sequencing study in amyotrophic lateral sclerosis
Publisher: Springer Science and Business Media LLC
Date: 28-06-2018
Heritability in the genomics era — concepts and misconceptions
Publisher: Springer Science and Business Media LLC
Date: 04-03-2008
DOI: 10.1038/NRG2322
Abstract: Heritability allows a comparison of the relative importance of genes and environment to the variation of traits within and across populations. The concept of heritability and its definition as an estimable, dimensionless population parameter was introduced by Sewall Wright and Ronald Fisher nearly a century ago. Despite continuous misunderstandings and controversies over its use and application, heritability remains key to the response to selection in evolutionary biology and agriculture, and to the prediction of disease risk in medicine. Recent reports of substantial heritability for gene expression and new estimation methods using marker data highlight the relevance of heritability in the genomics era.
Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration
Publisher: Cold Spring Harbor Laboratory
Date: 06-12-2019
DOI: 10.1101/860767
Abstract: Vitamin D deficiency is a candidate risk factor for a range of adverse health outcomes. In a genome-wide association study of 25 hydroxyvitamin D (25OHD) concentration in 417,580 Europeans we identified 143 independent loci in 112 1-Mb regions providing new insights into the physiology of vitamin D and implicating genes involved in (a) lipid and lipoprotein metabolism, (b) dermal tissue properties, and (c) the sulphonation and glucuronidation of 25OHD. Mendelian randomization models found no robust evidence that 25OHD concentration had causal effects on candidate phenotypes (e.g. BMI, psychiatric disorders), but many phenotypes had (direct or indirect) causal effects on 25OHD concentration, clarifying the relationship between 25OHD status and health.
Neurobiology Youth Follow-up Study: protocol to establish a longitudinal and prospective research database using multimodal assessments for current and past mental health treatment-seeking young peopl
Publisher: BMJ
Date: 06-2021
DOI: 10.1136/BMJOPEN-2020-044731
Abstract: Approximately 75% of major mental illness occurs before the age of 25 years. Despite this, our capacity to provide effective, early and personalised interventions is limited by insufficient evidence for characterising early-stage, and less specific, presentations of major mental disorders in youth populations. This article describes the protocol for setting up a large-scale database that will collect longitudinal, prospective data that incorporate clinical, social and occupational function, neuropsychological, circadian, metabolic, family history and genetic metrics. By collecting data in a research-purposed, standardised manner, the ‘Neurobiology Youth Follow-up Study’ should improve identification, characterisation and profiling of youth attending mental healthcare, to better inform diagnosis and treatment at critical time points. The overall goal is enhanced long-term clinical and functional outcomes. This longitudinal clinical cohort study will invite participation from youth (12–30 years) who seek help for mental health-related issues at an early intervention service (headspace C erdown) and linked services. Participants will be prospectively tracked over 3 years with a series of standardised multimodal assessments at baseline, 6, 12, 24 and 36 months. Evaluations will include: (1) clinician-administered and self-report assessments determining clinical stage, pathophysiological pathways to illness, diagnosis, symptomatology, social and occupational function (2) neuropsychological profile (3) sleep–wake patterns and circadian rhythms (4) metabolic markers and (5) genetics. These data will be used to: (1) model the impact of demographic, phenomenological and treatment variables, on clinical and functional outcomes (2) map neurobiological profiles and changes onto a transdiagnostic clinical stage and pathophysiological mechanisms framework. This study protocol has been approved by the Human Research Ethics Committee of the Sydney Local Health District (2020/ETH01272, protocol V.1.3, 14 October 2020). Research findings will be disseminated through peer-reviewed journals and presentations at scientific conferences and to user and advocacy groups. Participant data will be de-identified.
Large-scale GWAS identifies multiple loci for hand grip strength providing biological insights into muscular fitness
Publisher: Springer Science and Business Media LLC
Date: 12-07-2017
DOI: 10.1038/NCOMMS16015
Abstract: Hand grip strength is a widely used proxy of muscular fitness, a marker of frailty, and predictor of a range of morbidities and all-cause mortality. To investigate the genetic determinants of variation in grip strength, we perform a large-scale genetic discovery analysis in a combined s le of 195,180 in iduals and identify 16 loci associated with grip strength ( P × 10 −8 ) in combined analyses. A number of these loci contain genes implicated in structure and function of skeletal muscle fibres ( ACTG1 ), neuronal maintenance and signal transduction ( PEX14, TGFA, SYT1 ), or monogenic syndromes with involvement of psychomotor impairment ( PEX14, LRPPRC and KANSL1 ). Mendelian randomization analyses are consistent with a causal effect of higher genetically predicted grip strength on lower fracture risk. In conclusion, our findings provide new biological insight into the mechanistic underpinnings of grip strength and the causal role of muscular strength in age-related morbidities and mortality.
F34. CHARACTERISING ANTIDEPRESSANT USAGE BASED ON ELECTRONIC PRESCRIPTION RECORDS IN THE AUSTRALIAN GENETICS OF DEPRESSION STUDY
Publisher: Elsevier BV
Date: 10-2023
Association of Schizophrenia Risk With Disordered Niacin Metabolism in an Indian Genome-wide Association Study
Publisher: American Medical Association (AMA)
Date: 10-2019
Understanding genetic risk factors for common side effects of antidepressant medications
Publisher: Cold Spring Harbor Laboratory
Date: 16-07-2021
DOI: 10.1101/2021.07.12.21260397
Abstract: Major depression is one of the most disabling health conditions internationally. In recent years, new generation antidepressant medicines have become very widely prescribed. While these medicines are efficacious, side effects are common and frequently result in discontinuation of treatment. Compared with specific pharmacological properties of the different medications, the relevance of in idual vulnerability is understudied. We used data from the Australian Genetics of Depression Study to gain insights into the aetiology and genetic risk factors to antidepressant side effects. As expected, the most commonly reported longer-term side effects were reduced sexual function and weight gain. Importantly, participants reporting a specific side effect for one antidepressant were more likely to report the same side effect for other antidepressants, suggesting the presence of shared in idual or pharmacological factors. Depression Polygenic Risk Scores (PRS) were associated with side effects that overlapped with depressive symptoms, including suicidality and anxiety. Body Mass Index PRS were strongly associated with weight gain from all medications. PRS for headaches were associated with headaches from sertraline. Insomnia PRS showed some evidence of predicting insomnia from amitriptyline and escitalopram. Our results suggest a set of common factors underlying the risk for antidepressant side effects. These factors seem to be, at least in part, explained by genetic liability related to depression severity and the nature of the side effect. Future studies on the genetic aetiology of side effects will enable insights into their underlying mechanisms and the possibility of risk stratification and prophylaxis strategies.
DNA Methylation Signatures of Depressive Symptoms in Middle-aged and Elderly Persons
Publisher: American Medical Association (AMA)
Date: 09-2018
The contribution of genetic variants to disease depends on the ruler
Publisher: Springer Science and Business Media LLC
Date: 16-09-2014
DOI: 10.1038/NRG3786
Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection
Publisher: Springer Science and Business Media LLC
Date: 26-02-2018
Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood
Publisher: Elsevier BV
Date: 06-2018
A parsimonious model for mass-univariate vertex-wise analysis
Publisher: Cold Spring Harbor Laboratory
Date: 22-01-2021
DOI: 10.1101/2021.01.22.427735
Abstract: 2. Covariance between grey-matter measurements can reflect structural or functional brain networks though it has also been shown to be influenced by confounding factors (e.g. age, head size, scanner), which could lead to lower mapping precision (increased size of associated clusters) and create distal false positives associations in mass-univariate vertex-wise analyses. We evaluated this concern by performing state-of-the-art mass-univariate analyses (general linear model, GLM) on traits simulated from real vertex-wise grey matter data (including cortical and subcortical thickness and surface area). We contrasted the results with those from linear mixed models (LMMs), which have been shown to overcome similar issues in omics association studies. We showed that when performed on a large s le (N=8,662, UK Biobank), GLMs yielded large spatial clusters of significant vertices and greatly inflated false positive rate (Family Wise Error Rate: FWER=1, cluster false discovery rate: FDR .6). We showed that LMMs resulted in more parsimonious results: smaller clusters and reduced false positive rate (yet FWER % after Bonferroni correction) but at a cost of increased computation. In practice, the parsimony of LMMs results from controlling for the joint effect of all vertices, which prevents local and distal redundant associations from reaching significance. Next, we performed mass-univariate association analyses on five real UKB traits (age, sex, BMI, fluid intelligence and smoking status) and LMM yielded fewer and more localised associations. We identified 19 significant clusters displaying small associations with age, sex and BMI, which suggest a complex architecture of at least dozens of associated areas with those phenotypes.
A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases
Publisher: Springer Science and Business Media LLC
Date: 16-05-2016
DOI: 10.1038/NG.3572
Risk of psychiatric illness from advanced paternal age is not predominantly from de novo mutations
Publisher: Springer Science and Business Media LLC
Date: 23-05-2016
DOI: 10.1038/NG.3577
Abstract: The offspring of older fathers have higher risk of psychiatric disorders such as schizophrenia and autism. Paternal-age-related de novo mutations are widely assumed to be the underlying causal mechanism, and, although such mutations must logically make some contribution, there are alternative explanations (for ex le, elevated liability to psychiatric illness may delay fatherhood). We used population genetic models based on empirical observations of key parameters (for ex le, mutation rate, prevalence, and heritability) to assess the genetic relationship between paternal age and risk of psychiatric illness. These models suggest that age-related mutations are unlikely to explain much of the increased risk of psychiatric disorders in children of older fathers. Conversely, a model incorporating a weak correlation between age at first child and liability to psychiatric illness matched epidemiological observations. Our results suggest that genetic risk factors shared by older fathers and their offspring are a credible alternative explanation to de novo mutations for risk to children of older fathers.
Assortative Mating in Autism Spectrum Disorder: Toward an Evidence Base From DNA Data, but Not There Yet
Publisher: Elsevier BV
Date: 08-2019
Genotype–covariate correlation and interaction disentangled by a whole-genome multivariate reaction norm model
Publisher: Springer Science and Business Media LLC
Date: 20-05-2019
DOI: 10.1038/S41467-019-10128-W
Abstract: The genomics era has brought useful tools to dissect the genetic architecture of complex traits. Here we propose a multivariate reaction norm model (MRNM) to tackle genotype–covariate (G–C) correlation and interaction problems. We apply MRNM to the UK Biobank data in analysis of body mass index using smoking quantity as a covariate, finding a highly significant G–C correlation, but only weak evidence for G–C interaction. In contrast, G–C interaction estimates are inflated in existing methods. It is also notable that there is significant heterogeneity in the estimated residual variances (i.e., variances not attributable to factors in the model) across different covariate levels, i.e., residual–covariate (R–C) interaction. We also show that the residual variances estimated by standard additive models can be inflated in the presence of G–C and/or R–C interactions. We conclude that it is essential to correctly account for both interaction and correlation in complex trait analyses.
Clinical, demographic, and genetic risk factors of treatment‐attributed suicidality in >10,000 Australian adults taking antidepressants
Publisher: Wiley
Date: 14-07-2022
DOI: 10.1002/AJMG.B.32913
Abstract: Emergence of suicidal symptoms has been reported as a potential antidepressant adverse drug reaction. Identifying risk factors associated could increase our understanding of this phenomenon and stratify in iduals at higher risk. Logistic regressions were used to identify risk factors of self‐reported treatment‐attributed suicidal ideation (TASI). We then employed classifiers to test the predictive ability of the variables identified. A TASI GWAS, as well as SNP‐based heritability estimation, were performed. GWAS replication was sought from an independent study. Significant associations were found for age and comorbid conditions, including bipolar and personality disorders. Participants reporting TASI from one antidepressant were more likely to report TASI from other antidepressants. No genetic loci associated with TAS I ( p 5e‐8) were identified. Of 32 independent variants with suggestive association ( p 1e‐5), 27 lead SNPs were available in a replication dataset from the GENDEP study. Only one variant showed a consistent effect and nominal association in the independent replication s le. Classifiers were able to stratify non‐TASI from TASI participants (AUC = 0.77) and those reporting treatment‐attributed suicide attempts (AUC = 0.85). The pattern of TASI co‐occurrence across participants suggest nonspecific factors underlying its etiology. These findings provide insights into the underpinnings of TASI and serve as a proof‐of‐concept of the use of classifiers for risk stratification.
P4‐459: Evidence for the involvement of the RSG2 gene in risk for anxiety and related phenotypes in an elderly population not selected for this trait
Publisher: Wiley
Date: 07-2011
Autism-related dietary preferences mediate autism-gut microbiome associations.
Publisher: Elsevier BV
Date: 11-2021
DOI: 10.1016/J.CELL.2021.10.015
Abstract: There is increasing interest in the potential contribution of the gut microbiome to autism spectrum disorder (ASD). However, previous studies have been underpowered and have not been designed to address potential confounding factors in a comprehensive way. We performed a large autism stool metagenomics study (n = 247) based on participants from the Australian Autism Biobank and the Queensland Twin Adolescent Brain project. We found negligible direct associations between ASD diagnosis and the gut microbiome. Instead, our data support a model whereby ASD-related restricted interests are associated with less- erse diet, and in turn reduced microbial taxonomic ersity and looser stool consistency. In contrast to ASD diagnosis, our dataset was well powered to detect microbiome associations with traits such as age, dietary intake, and stool consistency. Overall, microbiome differences in ASD may reflect dietary preferences that relate to diagnostic features, and we caution against claims that the microbiome has a driving role in ASD.
Estimation of non-additive genetic variance in human complex traits from a large sample of unrelated individuals
Publisher: Elsevier BV
Date: 05-2021
Glutamate cysteine ligase (GCL) and self reported depression: an association study from the HUNT
Publisher: Elsevier BV
Date: 06-2011
DOI: 10.1016/J.JAD.2010.12.019
Abstract: There is increasing evidence suggesting oxidative stress may play a role in the aetiology of depression. Glutathione is the brain's predominant free radical scavenger, and associated polymorphisms of the glutamate cysteine ligase (GCL) gene have been reported for related psychiatric disorders. The aim of the study was to investigate candidate polymorphisms of GCL validated in schizophrenia and their association with current state depression, as measured by the Hospital Anxiety and Depression Scale (HADS). Polymorphisms were genotyped on 983 cases and 967 controls selected from a population s le of adults participating in the Nord-Trøndelag Health Study. Cases were the top scoring in iduals (98.5th percentile) on the HADS depression subscale while the controls were randomly selected from below this cut-off. The polymorphisms comprised three SNPs from GCLM, the gene encoding the GCL modifier and 9 SNPs plus a trinucleotide repeat (TNTR) from intron 1 and the 5'UTR of GCLC, the gene encoding the GCL catalytic subunit. Using the linkage disequilibrium between the GCLC markers we also tested whether SNPs could represent the variation of the TNTR. The candidate polymorphisms showed no evidence for association with depression. The C allele of SNP rs9474592 is coupled with the 9 GAG repeats allele of the TNTR, r²=0.81. None of the other SNPs either in idually or as two or three-SNP haplotypes was associated with the TNTR alleles. Depression was self-reported and measured at one time point. This study provides no evidence to suggest that polymorphisms of GCL are associated with self-reported depression.
Exome Sequencing Reveals Common and Rare Variants in F5 Associated With ACE Inhibitor and Angiotensin Receptor Blocker–Induced Angioedema
Publisher: Wiley
Date: 18-07-2020
DOI: 10.1002/CPT.1927
Rare Variant Burden Analysis within Enhancers Identifies CAV1 as an ALS Risk Gene
Publisher: Elsevier BV
Date: 12-2020
Inference in Psychiatry via 2-Sample Mendelian Randomization—From Association to Causal Pathway?
Publisher: American Medical Association (AMA)
Date: 12-2017
Association study of candidate variants of COMT with neuroticism, anxiety and depression
Publisher: Wiley
Date: 02-04-2008
DOI: 10.1002/AJMG.B.30744
Abstract: The Val158Met polymorphism of the gene encoding catechol-O-methyltransferase (COMT) is one of the most widely tested variants for association with psychiatric disorders, but replication has been inconsistent including both sex limitation and heterogeneity of the associated allele. In this study we investigate the association between three SNPs from COMT and anxiety and depression disorders and neuroticism all measured within the same study s le. Participants were selected as sibling pairs (or multiples) that were either concordant or discordant for extreme neuroticism scores from a total s le of 18,742 Australian twin in iduals and their siblings. All participants completed the Composite International Diagnostic Interview (CIDI) from which diagnoses of DSM-IV depression and anxiety disorders were determined. Of the participants, 674 had a diagnosis of anxiety and/or depression from 492 families. Study participants (n = 2,045 from 987 families) plus, where possible, their parents were genotyped for rs737865, rs4680 (Val158Met), and rs165599. Using family based tests we looked for association between these variants and neuroticism, depression, anxiety, panic disorder and agarophobia (PDAG) and obsessive compulsive disorder. We found no convincing evidence for association either in allelic or genotypic tests for the total s le or when the s le was stratified by sex. Haplotype T-G-G showed weak association (P = 0.042) with PDAG before correction for multiple testing association between this haplotype and schizophrenia has been previously reported in an Australian s le.
Underestimated effect sizes in GWAS: fundamental limitations of single SNP analysis for dichotomous phenotypes.
Publisher: Public Library of Science (PLoS)
Date: 28-11-2011
Genetic comorbidity between major depression and cardio‐metabolic traits, stratified by age at onset of major depression
Publisher: Wiley
Date: 18-07-2020
DOI: 10.1002/AJMG.B.32807
Genotype-by-environment interactions inferred from genetic effects on phenotypic variability in the UK Biobank
Publisher: Cold Spring Harbor Laboratory
Date: 14-01-2019
DOI: 10.1101/519538
Abstract: Genotype-by-environment interaction (GEI) is a fundamental component in understanding complex trait variation. However, it remains challenging to identify genetic variants with GEI effects in humans largely because of the small effect sizes and the difficulty of monitoring environmental fluctuations. Here, we demonstrate that GEI can be inferred from genetic variants associated with phenotypic variability in a large s le without the need of measuring environmental factors. We performed a genome-wide variance quantitative trait locus (vQTL) analysis of ~5.6 million variants on 348,501 unrelated in iduals of European ancestry for 13 quantitative traits in the UK Biobank, and identified 75 significant vQTLs with P .0×10 −9 for 9 traits, especially for those related to obesity. Direct GEI analysis with five environmental factors showed that the vQTLs were strongly enriched with GEI effects. Our results indicate pervasive GEI effects for obesity-related traits and demonstrate the detection of GEI without environmental data.
Genome-wide association study of borderline personality disorder reveals genetic overlap with bipolar disorder, major depression and schizophrenia
Publisher: Springer Science and Business Media LLC
Date: 20-06-2017
DOI: 10.1038/TP.2017.115
Abstract: Borderline personality disorder (BOR) is determined by environmental and genetic factors, and characterized by affective instability and impulsivity, diagnostic symptoms also observed in manic phases of bipolar disorder (BIP). Up to 20% of BIP patients show comorbidity with BOR. This report describes the first case–control genome-wide association study (GWAS) of BOR, performed in one of the largest BOR patient s les worldwide. The focus of our analysis was (i) to detect genes and gene sets involved in BOR and (ii) to investigate the genetic overlap with BIP. As there is considerable genetic overlap between BIP, major depression (MDD) and schizophrenia (SCZ) and a high comorbidity of BOR and MDD, we also analyzed the genetic overlap of BOR with SCZ and MDD. GWAS, gene-based tests and gene-set analyses were performed in 998 BOR patients and 1545 controls. Linkage disequilibrium score regression was used to detect the genetic overlap between BOR and these disorders. Single marker analysis revealed no significant association after correction for multiple testing. Gene-based analysis yielded two significant genes: DPYD ( P =4.42 × 10 −7 ) and PKP4 ( P =8.67 × 10 −7 ) and gene-set analysis yielded a significant finding for exocytosis (GO:0006887, P FDR =0.019 FDR, false discovery rate). Prior studies have implicated DPYD , PKP4 and exocytosis in BIP and SCZ. The most notable finding of the present study was the genetic overlap of BOR with BIP ( r g =0.28 [ P =2.99 × 10 −3 ]), SCZ ( r g =0.34 [ P =4.37 × 10 −5 ]) and MDD ( r g =0.57 [ P =1.04 × 10 −3 ]). We believe our study is the first to demonstrate that BOR overlaps with BIP, MDD and SCZ on the genetic level. Whether this is confined to transdiagnostic clinical symptoms should be examined in future studies.
Risk of Early-Onset Depression Associated With Polygenic Liability, Parental Psychiatric History, and Socioeconomic Status
Publisher: American Medical Association (AMA)
Date: 04-2021
Assigning pedigree beef performance records to contemporary groups taking account of within-herd calving patterns
Publisher: Cambridge University Press (CUP)
Date: 10-1997
DOI: 10.1017/S1357729800016490
Abstract: A method is described for assigning beef cattle performance records to within-herd management effects (contemporary groups) retrospectively, using information on the recording date and herd. This method takes account of the within-herd calving pattern. The objective of developing a method of assigning records to contemporary groups was to maximize the contemporary group size while ensuring as far as possible that records in any contemporary group were subject to the same management. A simple method for assessing the effectiveness of different strategies for assigning records to contemporary groups is proposed, based on investigating the balance between the effects of contemporary group size upon the heritability and the accuracy of mass selection. The results of a study of different contemporary grouping strategies in the Simmental breed are reported.
Harnessing the information contained within genome-wide association studies to improve individual prediction of complex disease risk
Publisher: Oxford University Press (OUP)
Date: 24-06-2009
DOI: 10.1093/HMG/DDP295
Abstract: The current paradigm within genetic diagnostics is to test in iduals only at loci known to affect risk of complex disease-yet the technology exists to genotype an in idual at thousands of loci across the genome. We investigated whether information from genome-wide association studies could be harnessed to improve discrimination of complex disease affection status. We employed genome-wide data from the Wellcome Trust Case Control Consortium to test this hypothesis. Each disease cohort together with the same set of controls were split into two s les-a 'Training Set', where thousands of SNPs that might predispose to disease risk were identified and a 'Prediction Set', where the discriminatory ability of these SNPs was assessed. Genome-wide scores consisting of, for ex le, the total number of risk alleles an in idual carries was calculated for each in idual in the prediction set. Case-control status was regressed on this score and the area under the receiver operator characteristic curve (AUC) estimated. In most cases, a liberal inclusion of SNPs in the genome-wide score improved AUC compared with a more stringent selection of top SNPs, but did not perform as well as selection based upon established variants. The addition of genome-wide scores to known variant information produced only a limited increase in discriminative accuracy but was most effective for bipolar disorder, coronary heart disease and type II diabetes. We conclude that this small increase in discriminative accuracy is unlikely to be of diagnostic or predictive utility at the present time.
Accurately assessing the risk of schizophrenia conferred by rare copy-number variation affecting genes with brain function
Publisher: Public Library of Science (PLoS)
Date: 09-09-2010
Genetic and environmental exposures constrain epigenetic drift over the human life course
Publisher: Cold Spring Harbor Laboratory
Date: 23-09-2014
Abstract: Epigenetic mechanisms such as DNA methylation (DNAm) are essential for regulation of gene expression. DNAm is dynamic, influenced by both environmental and genetic factors. Epigenetic drift is the ergence of the epigenome as a function of age due to stochastic changes in methylation. Here we show that epigenetic drift may be constrained at many CpGs across the human genome by DNA sequence variation and by lifetime environmental exposures. We estimate repeatability of DNAm at 234,811 autosomal CpGs in whole blood using longitudinal data (2–3 repeated measurements) on 478 older people from two Scottish birth cohorts—the Lothian Birth Cohorts of 1921 and 1936. Median age was 79 yr and 70 yr, and the follow-up period was ∼10 yr and ∼6 yr, respectively. We compare this to methylation heritability estimated in the Brisbane Systems Genomics Study, a cross-sectional study of 117 families (offspring median age 13 yr parent median age 46 yr). CpG repeatability in older people was highly correlated (0.68) with heritability estimated in younger people. Highly heritable sites had strong underlying cis -genetic effects. Thirty-seven and 1687 autosomal CpGs were associated with smoking and sex, respectively. Both sets were strongly enriched for high repeatability. Sex-associated CpGs were also strongly enriched for high heritability. Our results show that a large number of CpGs across the genome, as a result of environmental and/or genetic constraints, have stable DNAm variation over the human lifetime. Moreover, at a number of CpGs, most variation in the population is due to genetic factors, despite some sites being highly modifiable by the environment.
Genome-Wide Linkage Analysis of Multiple Measures of Neuroticism of 2 Large Cohorts From Australia and the Netherlands
Publisher: American Medical Association (AMA)
Date: 02-06-2008
Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance-components analysis
Publisher: Springer Science and Business Media LLC
Date: 02-11-2015
DOI: 10.1038/NG.3431
Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses
Publisher: Springer Science and Business Media LLC
Date: 18-04-2016
DOI: 10.1038/NG.3552
Genome-wide gene-environment analyses of depression and reported lifetime traumatic experiences in UK Biobank
Publisher: Cold Spring Harbor Laboratory
Date: 12-01-2018
DOI: 10.1101/247353
Abstract: Depression is more frequently observed among in iduals exposed to traumatic events. The relationship between trauma exposure and depression, including the role of genetic variation, is complex and poorly understood. The UK Biobank concurrently assessed depression and reported trauma exposure in 126,522 genotyped in iduals of European ancestry. We compared the shared aetiology of depression and a range of phenotypes, contrasting in iduals reporting trauma exposure with those who did not (final s le size range: 24,094-92,957). Depression was heritable in participants reporting trauma exposure and in unexposed in iduals, and the genetic correlation between the groups was substantial and not significantly different from 1. Genetic correlations between depression and psychiatric traits were strong regardless of reported trauma exposure, whereas genetic correlations between depression and body mass index (and related phenotypes) were observed only in trauma exposed in iduals. The narrower range of genetic correlations in trauma unexposed depression and the lack of correlation with BMI echoes earlier ideas of endogenous depression.
A 3p26-3p25 Genetic Linkage Finding for DSM-IV Major Depression in Heavy Smoking Families
Publisher: American Psychiatric Association Publishing
Date: 08-2011
Genome-wide association for major depressive disorder: a possible role for the presynaptic protein piccolo
Publisher: Springer Science and Business Media LLC
Date: 09-12-2008
DOI: 10.1038/MP.2008.125
Genome-wide Meta-analysis Finds the ACSL5-ZDHHC6 Locus Is Associated with ALS and Links Weight Loss to the Disease Genetics
Publisher: Elsevier BV
Date: 10-2020
Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets
Publisher: Springer Science and Business Media LLC
Date: 28-03-2016
DOI: 10.1038/NG.3538
Abstract: Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with human complex traits. However, the genes or functional DNA elements through which these variants exert their effects on the traits are often unknown. We propose a method (called SMR) that integrates summary-level data from GWAS with data from expression quantitative trait locus (eQTL) studies to identify genes whose expression levels are associated with a complex trait because of pleiotropy. We apply the method to five human complex traits using GWAS data on up to 339,224 in iduals and eQTL data on 5,311 in iduals, and we prioritize 126 genes (for ex le, TRAF1 and ANKRD55 for rheumatoid arthritis and SNX19 and NMRAL1 for schizophrenia), of which 25 genes are new candidates 77 genes are not the nearest annotated gene to the top associated GWAS SNP. These genes provide important leads to design future functional studies to understand the mechanism whereby DNA variation leads to complex trait variation.
Genome-wide association analysis of coffee drinking suggests association with CYP1A1/CYP1A2 and NRCAM
Publisher: Springer Science and Business Media LLC
Date: 30-08-2011
DOI: 10.1038/MP.2011.101
Association of polygenic score for major depression with response to lithium in patients with bipolar disorder
Publisher: Springer Science and Business Media LLC
Date: 16-03-2200
DOI: 10.1038/S41380-020-0689-5
Abstract: Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi
Identification of common genetic risk variants for autism spectrum disorder
Publisher: Springer Science and Business Media LLC
Date: 25-02-2019
Improving genetic prediction by leveraging genetic correlations among human diseases and traits
Publisher: Springer Science and Business Media LLC
Date: 07-03-2018
DOI: 10.1038/S41467-017-02769-6
Abstract: Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7% for height to 47% for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait.
Pitfalls of predicting complex traits from SNPs
Publisher: Springer Science and Business Media LLC
Date: 18-06-2013
DOI: 10.1038/NRG3457
Erratum: Corrigendum to: Sporadic cases are the norm for complex disease
Publisher: Springer Science and Business Media LLC
Date: 19-08-2010
Cross-ethnic meta-analysis identifies association of the GPX3-TNIP1 locus with amyotrophic lateral sclerosis
Publisher: Springer Science and Business Media LLC
Date: 20-09-2017
DOI: 10.1038/S41467-017-00471-1
Abstract: Cross-ethnic genetic studies can leverage power from differences in disease epidemiology and population-specific genetic architecture. In particular, the differences in linkage disequilibrium and allele frequency patterns across ethnic groups may increase gene-mapping resolution. Here we use cross-ethnic genetic data in sporadic amyotrophic lateral sclerosis (ALS), an adult-onset, rapidly progressing neurodegenerative disease. We report analyses of novel genome-wide association study data of 1,234 ALS cases and 2,850 controls. We find a significant association of rs10463311 spanning GPX3-TNIP1 with ALS ( p = 1.3 × 10 −8 ), with replication support from two independent Australian s les (combined 576 cases and 683 controls, p = 1.7 × 10 −3 ). Both GPX3 and TNIP1 interact with other known ALS genes ( SOD1 and OPTN , respectively). In addition, GGNBP2 was identified using gene-based analysis and summary statistics-based Mendelian randomization analysis, although further replication is needed to confirm this result. Our results increase our understanding of genetic aetiology of ALS.
Genomewide Association Studies: History, Rationale, and Prospects for Psychiatric Disorders
Publisher: American Psychiatric Association Publishing
Date: 05-2009
Examining the impact of imputation errors on fine-mapping using DNA methylation QTL as a model trait
Publisher: Oxford University Press (OUP)
Date: 30-04-2019
DOI: 10.1534/GENETICS.118.301861
Abstract: This study highlights dangers in over-interpreting fine-mapping results. Chundru et al. show that genotype imputation accuracy has a large impact on fine-mapping accuracy. They used DNA methylation at CpG-sites with a variant... Genetic variants disrupting DNA methylation at CpG dinucleotides (CpG-SNP) provide a set of known causal variants to serve as models to test fine-mapping methodology. We use 1716 CpG-SNPs to test three fine-mapping approaches (Bayesian imputation-based association mapping, Bayesian sparse linear mixed model, and the J-test), assessing the impact of imputation errors and the choice of reference panel by using both whole-genome sequence (WGS), and genotype array data on the same in iduals (n = 1166). The choice of imputation reference panel had a strong effect on imputation accuracy, with the 1000 Genomes Project Phase 3 (1000G) reference panel (n = 2504 from 26 populations) giving a mean nonreference discordance rate between imputed and sequenced genotypes of 3.2% compared to 1.6% when using the Haplotype Reference Consortium (HRC) reference panel (n = 32,470 Europeans). These imputation errors had an impact on whether the CpG-SNP was included in the 95% credible set, with a difference of ∼23% and ∼7% between the WGS and the 1000G and HRC imputed datasets, respectively. All of the fine-mapping methods failed to reach the expected 95% coverage of the CpG-SNP. This is attributed to secondary cis genetic effects that are unable to be statistically separated from the CpG-SNP, and through a masking mechanism where the effect of the methylation disrupting allele at the CpG-SNP is hidden by the effect of a nearby SNP that has strong linkage disequilibrium with the CpG-SNP. The reduced accuracy in fine-mapping a known causal variant in a low-level biological trait with imputed genetic data has implications for the study of higher-order complex traits and disease.
Genetic Differences between Five European Populations
Publisher: S. Karger AG
Date: 2010
DOI: 10.1159/000313854
Abstract: i Aims: /i We sought to examine the magnitude of the differences in SNP allele frequencies between five European populations (Scotland, Ireland, Sweden, Bulgaria and Portugal) and to identify the loci with the greatest differences. i Methods: /i We performed a population-based genome-wide association analysis with Affymetrix 6.0 and 5.0 arrays. We used a 4 degrees of freedom χ sup /sup test to determine the magnitude of stratification for each SNP. We then examined the genes within the most stratified regions, using a highly conservative cutoff of p 10 sup –45 /sup . i Results: /i We found 40,593 SNPs which are genome-wide significantly (p ≤ 10 sup –8 /sup ) stratified between these populations. The largest differences clustered in gene ontology categories for immunity and pigmentation. Some of the top loci span genes that have already been reported as highly stratified: genes for hair color and pigmentation i (HERC2, EXOC2, IRF4) /i , the LCT gene, genes involved in NAD metabolism, and in immunity (HLA and the Toll-like receptor genes TLR10, TLR1, TLR6). However, several genes have not previously been reported as stratified within European populations, indicating that they might also have provided selective advantages: several zinc finger genes, two genes involved in glutathione synthesis or function, and most intriguingly, i FOXP2 /i , implicated in speech development. i Conclusion: /i Our analysis demonstrates that many SNPs show genome-wide significant differences within European populations and the magnitude of the differences correlate with the geographical distance. At least some of these differences are due to the selective advantage of polymorphisms within these loci.
LEVERAGING FUNCTIONAL GENOMIC ANNOTATIONS AND GENOME COVERAGE TO IMPROVE POLYGENIC PREDICTION OF COMPLEX TRAITS WITHIN AND BETWEEN ANCESTRIES
Publisher: Elsevier BV
Date: 10-2023
A resource-efficient tool for mixed model association analysis of large-scale data
Publisher: Cold Spring Harbor Laboratory
Date: 11-04-2019
DOI: 10.1101/598110
Abstract: The genome-wide association study (GWAS) has been widely used as an experimental design to detect associations between genetic variants and a phenotype. Two major confounding factors, population stratification and relatedness, could potentially lead to inflated GWAS test-statistics and thereby spurious associations. Mixed linear model (MLM)-based approaches can be used to account for s le structure. However, genome-wide association (GWA) analyses in biobank s les such as the UK Biobank (UKB) often exceed the capability of most existing MLM-based tools especially if the number of traits is large. Here, we developed an MLM-based tool (called fastGWA) that controls for population stratification by principal components and relatedness by a sparse genetic relationship matrix for GWA analyses of biobank-scale data. We demonstrated by extensive simulations that fastGWA is reliable, robust and highly resource-efficient. We then applied fastGWA to 2,173 traits on 456,422 array-genotyped and imputed in iduals and 2,048 traits on 46,191 whole-exome-sequenced in iduals in the UKB.
ADVANCES IN POLYGENIC SCORE METHODS AND APPLICATIONS IN PSYCHIATRIC GENETICS
Publisher: Elsevier BV
Date: 10-2023
Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs
Publisher: Springer Science and Business Media LLC
Date: 19-02-2012
DOI: 10.1038/NG.1108
Complement genes contribute sex-biased vulnerability in diverse disorders
Publisher: Springer Science and Business Media LLC
Date: 11-05-2020
Evidence for increased genetic risk load for major depression in patients assigned to electroconvulsive therapy
Publisher: Wiley
Date: 02-12-2019
DOI: 10.1002/AJMG.B.32700
Response to ‘Predicting the diagnosis of autism spectrum disorder using gene pathway analysis’
Publisher: Springer Science and Business Media LLC
Date: 22-10-2013
DOI: 10.1038/MP.2013.125
Genome-wide study of DNA methylation shows alterations in metabolic, inflammatory, and cholesterol pathways in ALS.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 23-02-2022
DOI: 10.1126/SCITRANSLMED.ABJ0264
Abstract: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with an estimated heritability between 40 and 50%. DNA methylation patterns can serve as proxies of (past) exposures and disease progression, as well as providing a potential mechanism that mediates genetic or environmental risk. Here, we present a blood-based epigenome-wide association study meta-analysis in 9706 s les passing stringent quality control (6763 patients, 2943 controls). We identified a total of 45 differentially methylated positions (DMPs) annotated to 42 genes, which are enriched for pathways and traits related to metabolism, cholesterol biosynthesis, and immunity. We then tested 39 DNA methylation-based proxies of putative ALS risk factors and found that high-density lipoprotein cholesterol, body mass index, white blood cell proportions, and alcohol intake were independently associated with ALS. Integration of these results with our latest genome-wide association study showed that cholesterol biosynthesis was potentially causally related to ALS. Last, DNA methylation at several DMPs and blood cell proportion estimates derived from DNA methylation data were associated with survival rate in patients, suggesting that they might represent indicators of underlying disease processes potentially amenable to therapeutic interventions.
Signatures of negative selection in the genetic architecture of human complex traits.
Publisher: Springer Science and Business Media LLC
Date: 16-04-2018
DOI: 10.1038/S41588-018-0101-4
Abstract: We develop a Bayesian mixed linear model that simultaneously estimates single-nucleotide polymorphism (SNP)-based heritability, polygenicity (proportion of SNPs with nonzero effects), and the relationship between SNP effect size and minor allele frequency for complex traits in conventionally unrelated in iduals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N = 126,752) and show that on average, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (P < 0.05/28) signatures of natural selection in the genetic architecture of 23 traits, including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. The significant estimates of the relationship between effect size and minor allele frequency in complex traits are consistent with a model of negative (or purifying) selection, as confirmed by forward simulation. We conclude that negative selection acts pervasively on the genetic variants associated with human complex traits.
Risk of psychiatric illness from advanced paternal age is not predominantly from de novo mutations
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 02-2017
GWAS of Suicide Attempt in Psychiatric Disorders and Association With Major Depression Polygenic Risk Scores
Publisher: American Psychiatric Association Publishing
Date: 08-2019
72. METHYLOME-WIDE ASSOCIATION STUDY OF ANTIDEPRESSANT EXPOSURE
Publisher: Elsevier BV
Date: 10-2023
Understanding genetic risk factors for common side effects of antidepressant medications
Publisher: Springer Science and Business Media LLC
Date: 09-11-2021
DOI: 10.1038/S43856-021-00046-8
Abstract: Major depression is one of the most disabling health conditions internationally. In recent years, new generation antidepressant medicines have become very widely prescribed. While these medicines are efficacious, side effects are common and frequently result in discontinuation of treatment. Compared with specific pharmacological properties of the different medications, the relevance of in idual vulnerability is understudied. We used data from the Australian Genetics of Depression Study to gain insights into the aetiology and genetic risk factors to antidepressant side effects. To this end, we employed structural equation modelling, polygenic risk scoring and regressions. Here we show that participants reporting a specific side effect for one antidepressant are more likely to report the same side effect for other antidepressants, suggesting the presence of shared in idual or pharmacological factors. Polygenic risk scores (PRS) for depression associated with side effects that overlapped with depressive symptoms, including suicidality and anxiety. Body Mass Index PRS are strongly associated with weight gain from all medications. PRS for headaches are associated with headaches from sertraline. Insomnia PRS show some evidence of predicting insomnia from amitriptyline and escitalopram. Our results suggest a set of common factors underlying the risk for antidepressant side effects. These factors seem to be partly explained by genetic liability related to depression severity and the nature of the side effect. Future studies on the genetic aetiology of side effects will enable insights into their underlying mechanisms and the possibility of risk stratification and prophylaxis strategies.
A phenome-wide association and Mendelian Randomisation study of polygenic risk for depression in UK Biobank
Publisher: Springer Science and Business Media LLC
Date: 08-05-2020
DOI: 10.1038/S41467-020-16022-0
Abstract: Depression is a leading cause of worldwide disability but there remains considerable uncertainty regarding its neural and behavioural associations. Here, using non-overlapping Psychiatric Genomics Consortium (PGC) datasets as a reference, we estimate polygenic risk scores for depression (depression-PRS) in a discovery ( N = 10,674) and replication ( N = 11,214) imaging s le from UK Biobank. We report 77 traits that are significantly associated with depression-PRS, in both discovery and replication analyses. Mendelian Randomisation analysis supports a potential causal effect of liability to depression on brain white matter microstructure ( β : 0.125 to 0.868, p FDR 0.043). Several behavioural traits are also associated with depression-PRS ( β : 0.014 to 0.180, p FDR : 0.049 to 1.28 × 10 −14 ) and we find a significant and positive interaction between depression-PRS and adverse environmental exposures on mental health outcomes. This study reveals replicable associations between depression-PRS and white matter microstructure. Our results indicate that white matter microstructure differences may be a causal consequence of liability to depression.
MiNDAUS partnership
Publisher: Informa UK Limited
Date: 30-09-2022
DOI: 10.1080/21678421.2021.1980889
Abstract: An innovative approach to patient management, evidence-based policy development, and clinical drug trials is required to provide personalized care and to improve the likelihood of finding an effective treatment for Motor Neurone Disease (MND). The MiNDAus Partnership builds on and extends existing national collaborations in a targeted approach to improve the standard and coordination of care for people living with MND in Australia, and to enhance the prospects of discovering a cure or treatment. Relationships have been developed between leading clinical and research groups as well as patient-centered organizations, care providers, and philanthropy with a shared vision. MiNDAus has established a corporate structure and meets at least biannually to decide on how best to progress research, drug development, and patient management. The key themes are (i) empowering patients and their family carers to engage in self-management and ensure personalized service provision, treatment, and policy development, (ii) integration of data collection so as to better inform policy development, (iii) unifying patients and carers with advocacy groups, funding bodies, clinicians and academic institutions so as to inform policy development and research, (iv) coordination of research efforts and development of standardized national infrastructure for conducting innovative clinical MND trials that can be harmonized within Australia and with international trials consortia. Such a collaborative approach is required across stakeholders in order to develop innovative management guidelines, underpinned by necessary and evidence-based policy change recommendations, which, will ensure the best patient care until a cure is discovered.
Significance tests for R2 of out-of-sample prediction using polygenic scores
Publisher: Cold Spring Harbor Laboratory
Date: 10-06-2022
DOI: 10.1101/2022.06.08.495250
Abstract: The coefficient of determination ( R 2 ) is a well-established measure to indicate the predictive ability of polygenic scores (PGS). However, the s ling variance of R 2 is rarely considered so that 95% confidence intervals (CI) are not usually reported. Moreover, when comparisons are made between PGS based on different discovery s les, the s ling covariance of R 2 is necessary to test the difference between them. Here, we show how to estimate the variance and covariance of R 2 values to assess the 95% CI and p-value of the R 2 difference. We apply this approach to real data to predict into 28,880 European participants using UK Biobank (UKBB) and Biobank Japan (BBJ) GWAS summary statistics for cholesterol and BMI. We quantify the significantly higher predictive ability of UKBB PGS compared to BBJ PGS (p-value 7.6e-31 for cholesterol and 1.4e-50 for BMI). A joint model of UKBB and BBJ PGS significantly improves the predictive ability, compared to a model of UKBB PGS only (p-value 3.5e-05 for cholesterol and 1.3e-28 for BMI). The proposed approach can also be applied to testing a significant difference between R 2 values across different p-value thresholds. We also show that the predictive ability of regulatory SNPs is significantly enriched than non-regulatory SNPs for cholesterol (p-value 2.6e-19 for UKBB and 8.7e-08 for BBJ). We suggest that the proposed approach (available in R package ‘r2redux’) should be used to test the statistical significance of difference between pairs of PGS, which may help to draw a correct conclusion about the predictive ability of PGS.
Novel Genetic Locus Influencing Retinal Venular Tortuosity Is Also Associated With Risk of Coronary Artery Disease
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 12-2019
Across-cohort QC analyses of GWAS summary statistics from complex traits
Publisher: Springer Science and Business Media LLC
Date: 24-08-2017
Shorter communications editor: Niels keiding: Accounting for mutation effects in the additive genetic variance-covariance matrix and its inverse
Publisher: JSTOR
Date: 03-1990
DOI: 10.2307/2531640
Genetic risk profiles for depression and anxiety in adult and elderly cohorts
Publisher: Springer Science and Business Media LLC
Date: 22-06-2010
DOI: 10.1038/MP.2010.65
Progression and survival of patients with motor neuron disease relative to their fecal microbiota
Publisher: Informa UK Limited
Date: 09-07-2020
Quantifying between-cohort and between-sex genetic heterogeneity in major depressive disorder
Publisher: Wiley
Date: 02-2019
DOI: 10.1002/AJMG.B.32713
The Australian Genetics of Depression Study: Study Description and Sample Characteristics
Publisher: Cold Spring Harbor Laboratory
Date: 03-05-2019
DOI: 10.1101/626762
Abstract: Depression is the most common psychiatric disorder and the largest contributor to global disability. The Australian Genetics of Depression study was established to recruit a large cohort of in iduals who have been diagnosed with depression, and to investigate genetic and environmental risk factors for depression and response to commonly prescribed antidepressants. This paper describes the recruitment and characteristics of the s le. Participants completed an online questionnaire that consisted of a compulsory module that assessed self-reported psychiatric history, clinical depression using the Composite Interview Diagnostic Interview Short Form, and experiences of using commonly prescribed antidepressants. Further voluntary modules assessed a wide range of traits of relevance to psychopathology. Participants who reported they were willing to provide a DNA s le were sent a saliva kit in the mail. A total of 20,689 participants, 75% of whom were female, enrolled in the study. The average age of participants was 43 years ± 15 years. 15,807 participants (76% of the participant group) returned saliva kits. The overwhelming majority of participants reported being given a diagnosis of depression by a medical practitioner and 88% met the criteria for a depressive episode. Rates of comorbidity with other psychiatric disorders were high. Two-thirds of the s le reported having taken more than one type of antidepressant during treatment for their depression. This study was effective in recruiting a large community s le of people with a history of clinical depression, highlighting the willingness of Australians to engage with medical research. A combination of recruitment through health records and media as well as use of an online questionnaire made it feasible to recruit the large s le needed for investigating the genetics of common diseases. It will be a valuable resource for investigating risk factors for depression, treatment response to antidepressants and susceptibility to side effects.
Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes
Publisher: Springer Science and Business Media LLC
Date: 12-01-2021
DOI: 10.1038/S41467-020-20237-6
Abstract: Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that in iduals with higher disease burden in the UK Biobank ( n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data.
Genome-wide gene expression changes in postpartum depression point towards an altered immune landscape
Publisher: Springer Science and Business Media LLC
Date: 04-03-2021
DOI: 10.1038/S41398-021-01270-5
Abstract: Maternal postpartum depression (PPD) is a significant public health concern due to the severe negative impact on maternal and child health and well-being. In this study, we aimed to identify genes associated with PPD. To do this, we investigated genome-wide gene expression profiles of pregnant women during their third trimester of pregnancy and tested the association of gene expression with perinatal depressive symptoms. A total of 137 women from a cohort from the University of North Carolina, USA were assessed. The main phenotypes analysed were Edinburgh Postnatal Depression Scale (EPDS) scores at 2 months postpartum and PPD (binary yes/no) based on an EPDS cutoff of 10. Illumina NextSeq500/550 transcriptomic sequencing from whole blood was analysed using the edgeR package. We identified 71 genes significantly associated with postpartum depression scores at 2 months, after correction for multiple testing at 5% FDR. These included several interesting candidates including TNFRSF17, previously reported to be significantly upregulated in women with PPD and MMP8, a matrix metalloproteinase gene, associated with depression in a genome-wide association study. Functional annotation of differentially expressed genes revealed an enrichment of immune response-related biological processes. Additional analysis of genes associated with changes in depressive symptoms from recruitment to 2 months postpartum identified 66 genes significant at an FDR of 5%. Of these genes, 33 genes were also associated with depressive symptoms at 2 months postpartum. Comparing the results with previous studies, we observed that 15.4% of genes associated with PPD in this study overlapped with 700 core maternal genes that showed significant gene expression changes across multiple brain regions ( P = 7.9e-05) and 29–53% of the genes were also associated with estradiol changes in a pharmacological model of depression ( P values range = 1.2e-4–2.1e-14). In conclusion, we identified novel genes and validated genes previously associated with oestrogen sensitivity in PPD. These results point towards the role of an altered immune transcriptomic landscape as a vulnerability factor for PPD.
Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression
Publisher: Springer Science and Business Media LLC
Date: 26-04-2018
A Common Genetic Factor Underlies Genetic Risk for Gynaecological and Reproductive Disorders and Is Correlated with Risk to Depression
Publisher: S. Karger AG
Date: 2023
DOI: 10.1159/000533413
What do we know about the variability in survival of patients with amyotrophic lateral sclerosis?
Publisher: Informa UK Limited
Date: 07-08-2020
Population‐based identity‐by‐descent mapping combined with exome sequencing to detect rare risk variants for schizophrenia
Publisher: Wiley
Date: 23-02-2019
DOI: 10.1002/AJMG.B.32716
Maternal depression and family adversity: Linked pathways to offspring depression?
Publisher: Elsevier BV
Date: 05-2017
DOI: 10.1016/J.JPSYCHIRES.2017.01.006
Abstract: There is conflicting evidence about the contribution of maternal depression and family adversity to depression experienced by offspring. Because maternal depression and family adversity are related, there is a need to determine how they independently contribute to offspring depression. Data are from a long-running prospective birth cohort study (Mater-University of Queensland Study of Pregnancy and its outcomes - MUSP). For this study some 2200 offspring were followed up at 30 years of age. We first examine the association between maternal depression and family adversity over the period from the pregnancy to the child reaching adulthood. Then we consider the extent to which maternal depression and family adversity trajectories over this period predict CIDI/DSM-IV episodes of depression in the offspring of these mothers at 30 years of age. We find a strong bi-directional association between maternal depression and family experiences of adverse life events over the entire period the child is at home. After adjustment, children reared in a family experiencing high levels of adverse life events are more likely to experience a lifetime ever DSM-IV diagnosis of depression, are more likely to have experienced multiple episodes of lifetime ever depression, and are more likely to report their first episode of depression was at a younger age. The findings suggest the association between maternal depression and offspring depression appears to be partly attributable to the higher levels of family adversity characteristic of depressed mothers.
Estimating missing heritability for disease from genome-wide association studies.
Publisher: Elsevier BV
Date: 03-2011
Sizing up whole-genome sequencing studies of common diseases
Publisher: Springer Science and Business Media LLC
Date: 26-04-2018
A resource-efficient tool for mixed model association analysis of large-scale data
Publisher: Springer Science and Business Media LLC
Date: 25-11-2019
DOI: 10.1038/S41588-019-0530-8
Abstract: The genome-wide association study (GWAS) has been widely used as an experimental design to detect associations between genetic variants and a phenotype. Two major confounding factors, population stratification and relatedness, could potentially lead to inflated GWAS test statistics and hence to spurious associations. Mixed linear model (MLM)-based approaches can be used to account for s le structure. However, genome-wide association (GWA) analyses in biobank s les such as the UK Biobank (UKB) often exceed the capability of most existing MLM-based tools especially if the number of traits is large. Here, we develop an MLM-based tool (fastGWA) that controls for population stratification by principal components and for relatedness by a sparse genetic relationship matrix for GWA analyses of biobank-scale data. We demonstrate by extensive simulations that fastGWA is reliable, robust and highly resource-efficient. We then apply fastGWA to 2,173 traits on array-genotyped and imputed s les from 456,422 in iduals and to 2,048 traits on whole-exome-sequenced s les from 46,191 in iduals in the UKB.
Genetic stratification of depression in UK Biobank
Publisher: Springer Science and Business Media LLC
Date: 24-05-2020
DOI: 10.1038/S41398-020-0848-0
Abstract: Depression is a common and clinically heterogeneous mental health disorder that is frequently comorbid with other diseases and conditions. Stratification of depression may align sub-diagnoses more closely with their underling aetiology and provide more tractable targets for research and effective treatment. In the current study, we investigated whether genetic data could be used to identify subgroups within people with depression using the UK Biobank. Examination of cross-locus correlations were used to test for evidence of subgroups using genetic data from seven other complex traits and disorders that were genetically correlated with depression and had sufficient power ( .6) for detection. We found no evidence for subgroups within depression for schizophrenia, bipolar disorder, attention deficit/hyperactivity disorder, autism spectrum disorder, anorexia nervosa, inflammatory bowel disease or obesity. This suggests that for these traits, genetic correlations with depression were driven by pleiotropic genetic variants carried by everyone rather than by a specific subgroup.
Association ofOPRD1polymorphisms with heroin dependence in a large case-control series
Publisher: Wiley
Date: 13-04-2012
EMX1 regulates NRP1-mediated wiring of the mouse anterior cingulate cortex
Publisher: The Company of Biologists
Date: 11-2015
DOI: 10.1242/DEV.119909
Abstract: Transcription factors act during cortical development as master regulatory genes that specify cortical arealization and cellular identities. Although numerous transcription factors have been identified as being crucial for cortical development, little is known about their downstream targets and how they mediate the emergence of specific neuronal connections via selective axon guidance. The EMX transcription factors are essential for early patterning of the cerebral cortex, but whether EMX1 mediates interhemispheric connectivity by controlling corpus callosum formation remains unclear. Here, we demonstrate that in mice on the C57Bl/6 background EMX1 plays an essential role in the midline crossing of an axonal subpopulation of the corpus callosum derived from the anterior cingulate cortex. In the absence of EMX1, cingulate axons display reduced expression of the axon guidance receptor NRP1 and form aberrant axonal bundles within the rostral corpus callosum. EMX1 also functions as a transcriptional activator of Nrp1 expression in vitro, and overexpression of this protein in Emx1 knockout mice rescues the midline-crossing phenotype. These findings reveal a novel role for the EMX1 transcription factor in establishing cortical connectivity by regulating the interhemispheric wiring of a subpopulation of neurons within the mouse anterior cingulate cortex.
Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle
Publisher: Elsevier BV
Date: 08-2023
Author Correction: From Mendel to quantitative genetics in the genome era: the scientific legacy of W. G. Hill
Publisher: Springer Science and Business Media LLC
Date: 22-07-2022
Interpreting the role of de novo protein-coding mutations in neuropsychiatric disease
Publisher: Springer Science and Business Media LLC
Date: 03-2013
DOI: 10.1038/NG.2555
Abstract: Pedigree, linkage and association studies are consistent with heritable variation for complex disease due to the segregation of genetic factors in families and in the population. In contrast, de novo mutations make only minor contributions to heritability estimates for complex traits. Nonetheless, some de novo variants are known to be important in disease etiology. The identification of risk-conferring de novo variants will contribute to the discovery of etiologically relevant genes and pathways and may help in genetic counseling. There is considerable interest in the role of such mutations in complex neuropsychiatric disease, largely driven by new genotyping and sequencing technologies. An important role for large de novo copy number variations has been established. Recently, whole-exome sequencing has been used to extend the investigation of de novo variation to point mutations in protein-coding regions. Here, we consider several challenges for the interpretation of such mutations in the context of their role in neuropsychiatric disease.
Lifetime prevalence and correlates of perinatal depression in a case-cohort study of depression
Publisher: BMJ
Date: 07-2022
DOI: 10.1136/BMJOPEN-2021-059300
Abstract: This study sought to evaluate the prevalence, timing of onset and duration of symptoms of depression in the perinatal period (PND) in women with depression, according to whether they had a history of depression prior to their first perinatal period. We further sought to identify biopsychosocial correlates of perinatal symptoms in women with depression. The Australian Genetics of Depression Study is an online case cohort study of the aetiology of depression. For a range of variables, women with depression who report significant perinatal depressive symptoms were compared with women with lifetime depression who did not experience perinatal symptoms. In a large s le of parous women with major depressive disorder (n=7182), we identified two subgroups of PND cases with and without prior depression history (n=2261 n=878, respectively). The primary outcome measure was a positive screen for PND on the lifetime version of the Edinburgh Postnatal Depression Scale. Descriptive measures reported lifetime prevalence, timing of onset and duration of PND symptoms. There were no secondary outcome measures. The prevalence of PND among parous women was 70%. The majority of women reported at least one perinatal episode with symptoms both antenatally and postnatally. Of women who experienced depression prior to first pregnancy, PND cases were significantly more likely to report more episodes of depression (OR=1.15 per additional depression episode, 95% CI 1.13 to 1.17, p .001), non-European ancestry (OR 1.5, 95% CI 1.0 to 2.1, p=0.03), severe nausea during pregnancy (OR 1.3, 95% CI 1.1 to 1.6, p=0.006) and emotional abuse (OR 1.4, 95% CI 1.1 to 1.7, p=0.005). The majority of parous women with lifetime depression in this study experienced PND, associated with more complex, severe depression. Results highlight the importance of perinatal assessments of depressive symptoms, particularly for women with a history of depression or childhood adverse experiences.
55. HIGHLIGHTING HUMAN BRAIN CELL TYPES AND REGIONS FOR THE GENETIC RISK OF SCHIZOPHRENIA AND OTHER PSYCHIATRIC DISORDERS
Publisher: Elsevier BV
Date: 10-2023
Cumulative influence of parity-related genomic changes in multiple sclerosis
Publisher: Elsevier BV
Date: 03-2019
DOI: 10.1016/J.JNEUROIM.2018.12.004
Abstract: Pregnancy reduces the frequency of relapses in Multiple Sclerosis (MS) and parity also has a beneficial long term effect on disease outcome. We aimed to uncover the biological mechanisms underlying the beneficial long-term effects of parity in MS. Genome-wide gene expression revealed 574 genes associated with parity 38.3% showed significant DNA methylation changes (enrichment p = 0.029). These genes overlapped with previous MS genes in humans and a rat MS model and were overrepresented within axon guidance (P = 1.6e-05), developmental biology (P = 0.0094) and cell-cell communication (P = 0.019) pathways. This gene regulation could provide a basis for a protective effect of parity on the long-term outcome of MS.
From Basic Science to Clinical Application of Polygenic Risk Scores
Publisher: American Medical Association (AMA)
Date: 2021
DOI: 10.1001/JAMAPSYCHIATRY.2020.3049
Abstract: Polygenic risk scores (PRS) are predictors of the genetic susceptibilities of in iduals to diseases. All in iduals have DNA risk variants for all common diseases, but genetic susceptibility differences between people reflect the cumulative burden of these. Polygenic risk scores for an in idual are calculated as weighted counts of thousands of risk variants that they carry, where the risk variants and their weights have been identified in genome-wide association studies. Here, we review the underlying basic science of PRS, providing a foundation for understanding the potential clinical utility and limitations of PRS. Polygenic risk scores can be calculated for a wide range of diseases from a saliva or blood s le using genotyping technologies that are inexpensive. While genotyping only needs to be done once for each in idual in their lifetime, the PRS can be recalculated as identification of risk variants improves. On their own, PRS will never be able to establish or definitively predict future diagnoses of common complex conditions because genetic factors only contribute part of the risk, and PRS will only ever capture part of the genetic contributions. Nonetheless, just as clinical medicine uses a multitude of other predictive measures, PRS either on their own or as part of multivariable predictive algorithms could play a role. Utility of PRS in clinical medicine and ethical issues related to their use should be evaluated in the context of realistic expectations of what PRS can and cannot deliver. For different diseases, PRS could have utility in community settings (stratification to better triage people into established screening programs) or could contribute to clinical decision-making for those presenting with symptoms but where formal diagnosis is unclear. In principle, PRS could contribute to treatment choices, but more data are needed to allow development of PRS in this context.
Meta-analyses of genome-wide linkage scans of anxiety-related phenotypes
Publisher: Springer Science and Business Media LLC
Date: 04-04-2012
DOI: 10.1038/EJHG.2012.47
Could Polygenic Risk Scores Be Useful in Psychiatry?
Publisher: American Medical Association (AMA)
Date: 02-2021
DOI: 10.1001/JAMAPSYCHIATRY.2020.3042
Abstract: Polygenic risk scores (PRS) are predictors of the genetic susceptibility to diseases, calculated for in iduals as weighted counts of thousands of risk variants in which the risk variants and their weights have been identified in genome-wide association studies. Polygenic risk scores show promise in aiding clinical decision-making in many areas of medical practice. This review evaluates the potential use of PRS in psychiatry. On their own, PRS will never be able to establish or definitively predict a diagnosis of common complex conditions (eg, mental health disorders), because genetic factors only contribute part of the risk and PRS will only ever capture part of the genetic contribution. Combining PRS with other risk factors has potential to improve outcome prediction and aid clinical decision-making (eg, determining follow-up options for in iduals seeking help who are at clinical risk of future illness). Prognostication of adverse physical health outcomes or response to treatment in clinical populations are of great interest for psychiatric practice, but data from larger s les are needed to develop and evaluate PRS. Polygenic risk scores will contribute to risk assessment in clinical psychiatry as it evolves to combine information from molecular, clinical, and lifestyle metrics. The genome-wide genotype data needed to calculate PRS are inexpensive to generate and could become available to psychiatrists as a by-product of practices in other medical specialties. The utility of PRS in clinical psychiatry, as well as ethical issues associated with their use, should be evaluated in the context of realistic expectations of what PRS can and cannot deliver. Clinical psychiatry has lagged behind other fields of health care in its use of new technologies and routine clinical data for research. Now is the time to catch up.
Discovery and implications of polygenicity of common diseases
Publisher: American Association for the Advancement of Science (AAAS)
Date: 24-09-2021
Abstract: The sequencing of the human genome has allowed the study of the genetic architecture of common diseases: the number of genomic variants that contribute to risk of disease and their joint frequency and effect size distribution. Common diseases are polygenic, with many loci contributing to phenotype, and the cumulative burden of risk alleles determines in idual risk in conjunction with environmental factors. Most risk loci occur in noncoding regions of the genome regulating cell- and context-specific gene expression. Although the effect sizes of most risk alleles are small, their cumulative effects in in iduals, quantified as a polygenic (risk) score, can identify people at increased risk of disease, thereby facilitating prevention or early intervention.
Complex Trait Prediction from Genome Data: Contrasting EBV in Livestock to PRS in Humans
Publisher: Oxford University Press (OUP)
Date: 15-02-2019
DOI: 10.1534/GENETICS.119.301859
Abstract: Genomic estimated breeding values (GEBVs) in livestock and polygenic risk scores (PRS) in humans are conceptually similar however, the between-species differences in linkage disequilibrium (LD) provide a fundamental point of distinction that impacts approaches to data analyses... In this Review, we focus on the similarity of the concepts underlying prediction of estimated breeding values (EBVs) in livestock and polygenic risk scores (PRS) in humans. Our research spans both fields and so we recognize factors that are very obvious for those in one field, but less so for those in the other. Differences in family size between species is the wedge that drives the different viewpoints and approaches. Large family size achievable in nonhuman species accompanied by selection generates a smaller effective population size, increased linkage disequilibrium and a higher average genetic relationship between in iduals within a population. In human genetic analyses, we select in iduals unrelated in the classical sense (coefficient of relationship & .05) to estimate heritability captured by common SNPs. In livestock data, all animals within a breed are to some extent “related,” and so it is not possible to select unrelated in iduals and retain a data set of sufficient size to analyze. These differences directly or indirectly impact the way data analyses are undertaken. In livestock, genetic segregation variance exposed through s lings of parental genomes within families is directly observable and taken for granted. In humans, this genomic variation is under-recognized for its contribution to variation in polygenic risk of common disease, in both those with and without family history of disease. We explore the equation that predicts the expected proportion of variance explained using PRS, and quantify how GWAS s le size is the key factor for maximizing accuracy of prediction in both humans and livestock. Last, we bring together the concepts discussed to address some frequently asked questions.
Bayesian analysis of GWAS summary data reveals differential signatures of natural selection across human complex traits and functional genomic categories
Publisher: Cold Spring Harbor Laboratory
Date: 09-2019
DOI: 10.1101/752527
Abstract: Understanding how natural selection has shaped the genetic architecture of complex traits and diseases is of importance in medical and evolutionary genetics. Bayesian methods have been developed using in idual-level data to estimate multiple features of genetic architecture, including signatures of natural selection. Here, we present an enhanced method (SBayesS) that only requires GWAS summary statistics and incorporates functional genomic annotations. We analysed GWAS data with large s le sizes for 155 complex traits and detected pervasive signatures of negative selection with erse estimates of SNP-based heritability and polygenicity. Projecting these estimates onto a map of genetic architecture obtained from evolutionary simulations revealed relatively strong natural selection on genetic variants associated with cardiorespiratory and cognitive traits and relatively small number of mutational targets for diseases. Averaging across traits, the joint distribution of SNP effect size and MAF varied across functional genomic regions (likely to be a consequence of natural selection), with enrichment in both the number of associated variants and the magnitude of effect sizes in regions such as transcriptional start sites, coding regions and 5’- and 3’-UTRs.
Estimating Effects and Making Predictions from Genome-Wide Marker Data
Publisher: Institute of Mathematical Statistics
Date: 11-2009
DOI: 10.1214/09-STS306
Aggregation of childhood leukemia in geographic areas of Greece.
Publisher: Springer Science and Business Media LLC
Date: 1997
Abstract: A total of 872 children aged up to 14 years, who were diagnosed with leukemia in Greece during the decade 1980-89, were allocated by place of residence to the 601 administrative districts of the country. Evaluation of spatial clustering was done using the Potthoff-Whittinghill method, which validly assesses heterogeneity of leukemia risk among districts with variable expected numbers of cases. There was highly significant evidence for spatial clustering occurring particularly among children living in urban and, to a lesser extent, semi-urban areas. The evidence was stronger for children younger than 10 years old, applied also to children in different five-year age groups, and persisted when cases of acute lymphoblastic leukemia were analyzed separately. These findings provide support to the hypothesis that localized environmental exposures could contribute to the etiology of childhood leukemia, but they cannot distinguish between exposures of physical or chemical nature, nor can they exclude socially conditioned patterns of exposure to infectious agents.
GWAS of epigenetic ageing rates in blood reveals a critical role forTERT
Publisher: Cold Spring Harbor Laboratory
Date: 30-06-2017
DOI: 10.1101/157776
Abstract: DNA methylation age is an accurate biomarker of chronological age and predicts lifespan, but its underlying molecular mechanisms are unknown. In this genome-wide association study of 9,907 in iduals, we found gene variants mapping to five loci associated with intrinsic epigenetic age acceleration (IEAA) and gene variants in 3 loci associated extrinsic epigenetic age acceleration (EEAA). Mendelian randomization analysis suggested causal influences of menarche and menopause on IEAA and lipid levels on IEAA and EEAA. Variants associated with longer leukocyte telomere length (LTL) in the telomerase reverse transcriptase gene ( TERT ) locus at 5p15.33 confer higher IEAA (P .7×10 -11 ). Causal modelling indicates TERT -specific and independent effects on LTL and IEAA. Experimental hTERT expression in primary human fibroblasts engenders a linear increase in DNA methylation age with cell population doubling number. Together, these findings indicate a critical role for hTERT in regulating the DNA methylation clock, in addition to its established role of compensating for cell replication-dependent telomere shortening.
Meta-analysis of genome-wide association studies of anxiety disorders
Publisher: Springer Science and Business Media LLC
Date: 12-01-2016
DOI: 10.1038/MP.2015.197
Prediction of rats of inbreeding in populations undergoing index selection.
Publisher: Springer Science and Business Media LLC
Date: 02-1994
DOI: 10.1007/BF00221142
Genome-wide interaction study of a proxy for stress-sensitivity and its prediction of major depressive disorder
Publisher: Public Library of Science (PLoS)
Date: 20-12-2018
R2ROC: An efficient method of comparing two or more correlated AUC from out-of-sample prediction using polygenic scores
Publisher: Cold Spring Harbor Laboratory
Date: 03-08-2023
DOI: 10.1101/2023.08.01.551571
Abstract: Polygenic risk scores (PRSs) enable early prediction of disease risk. Evaluating PRS performance for binary traits commonly relies on the area under the receiver operating characteristic curve (AUC). However, the widely used DeLong’s method for comparative significance tests suffer from limitations, including computational time and the lack of a one-to-one mapping between test statistics based on AUC and R 2 . To overcome these limitations, we propose a novel approach that leverages the Delta method to derive the variance and covariance of AUC values, enabling a comprehensive and efficient comparative significance test. Our approach offers notable advantages over DeLong’s method, including reduced computation time (up to 150-fold), making it suitable for large-scale analyses and ideal for integration into machine learning frameworks. Furthermore, our method allows for a direct one-to-one mapping between AUC and R 2 values for comparative significance tests, providing enhanced insights into the relationship between these measures and facilitating their interpretation. We validated our proposed approach through simulations and applied it to real data comparing PRSs for diabetes and coronary artery disease (CAD) prediction in a cohort of 28,880 European in iduals. The PRSs were derived using genome-wide association study summary statistics from two distinct sources. Our approach enabled a comprehensive and informative comparison of the PRSs, shedding light on their respective predictive abilities for diabetes and CAD. This advancement contributes to the assessment of genetic risk factors and personalized disease prediction, supporting better healthcare decision-making.
Using genotype data to distinguish pleiotropy from heterogeneity: deciphering coheritability in autoimmune and neuropsychiatric diseases
Publisher: Cold Spring Harbor Laboratory
Date: 06-11-2015
DOI: 10.1101/030783
Abstract: Shared genetic architecture between phenotypes may be driven by a common genetic basis (pleiotropy) or a subset of genetically similar in iduals (heterogeneity). We developed BUHMBOX, a well-powered statistical method to distinguish pleiotropy from heterogeneity using genotype data. We observed a shared genetic basis between 11 of 17 tested autoimmune diseases and type I diabetes (T1D, p 12) and 11 of 17 tested autoimmune diseases and rheumatoid arthritis (RA, p -7). This sharing could not be explained by heterogeneity (corrected pBUHMBOX .2 using 6,670 T1D cases and 7,279 RA cases), suggesting that shared genetic features in autoimmunity are due to pleiotropy. We observed a shared genetic basis between seronegative and seropostive RA (p -22), explained by heterogeneity (pBUHMBOX=0.008 in 2,406 seronegative RA cases). Consistent with previous observations, we observed genetic sharing between major depressive disorder (MDD) and schizophrenia (p 9). This sharing is not explained by heterogeneity (pBUHMBOX=0.28 in 9,238 MDD cases).
Comparing apples and oranges: equating the power of case-control and quantitative trait association studies.
Publisher: Wiley
Date: 2010
DOI: 10.1002/GEPI.20456
Abstract: Genome-wide association studies have achieved unprecedented success in the identification of novel genes and pathways implicated in complex traits. Typically, studies for disease use a case-control (CC) design and studies for quantitative traits (QT) are population based. The question that we address is what is the equivalence between CC and QT association studies in terms of detection power and s le size? We compare the binary and continuous traits by assuming a threshold model for disease and assuming that the effect size on disease liability has similar feature as on QT. We derive the approximate ratio of the non-centrality parameter (NCP) between CC and QT association studies, which is determined by s le size, disease prevalence (K) and the proportion of cases (v) in the CC study. For disease with prevalence <0.1, CC association study with equal numbers of cases and controls (v=0.5) needs smaller s le size than QT association study to achieve equivalent power, e.g. a CC association study of schizophrenia (K=0.01) needs only approximately 55% s le size required for association study of height. So a planned meta-analysis for height on approximately 120,000 in iduals has power equivalent to a CC study on 33,100 schizophrenia cases and 33,100 controls, a size not yet achievable for this disease. With equal s le size, when v=K, the power of CC association study is much less than that of QT association study because of the information lost by transforming a quantitative continuous trait to a binary trait.
Evaluating the Impact of Nonrandom Mating: Psychiatric Outcomes Among the Offspring of Pairs Diagnosed With Schizophrenia and Bipolar Disorder
Publisher: Elsevier BV
Date: 02-2020
Genetic Studies of Major Depressive Disorder: Why Are There No Genome-wide Association Study Findings and What Can We Do About It?
Publisher: Elsevier BV
Date: 10-2014
Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depressive disorder
Publisher: Cold Spring Harbor Laboratory
Date: 24-07-2017
DOI: 10.1101/167577
Abstract: Major depressive disorder (MDD) is a notably complex illness with a lifetime prevalence of 14%. 1 It is often chronic or recurrent and is thus accompanied by considerable morbidity, excess mortality, substantial costs, and heightened risk of suicide. 2-7 MDD is a major cause of disability worldwide. 8 We conducted a genome-wide association (GWA) meta-analysis in 130,664 MDD cases and 330,470 controls, and identified 44 independent loci that met criteria for statistical significance. We present extensive analyses of these results which provide new insights into the nature of MDD. The genetic findings were associated with clinical features of MDD, and implicated prefrontal and anterior cingulate cortex in the pathophysiology of MDD (regions exhibiting anatomical differences between MDD cases and controls). Genes that are targets of antidepressant medications were strongly enriched for MDD association signals (P=8.5×10 −10 ), suggesting the relevance of these findings for improved pharmacotherapy of MDD. Sets of genes involved in gene splicing and in creating isoforms were also enriched for smaller MDD GWA P-values, and these gene sets have also been implicated in schizophrenia and autism. Genetic risk for MDD was correlated with that for many adult and childhood onset psychiatric disorders. Our analyses suggested important relations of genetic risk for MDD with educational attainment, body mass, and schizophrenia: the genetic basis of lower educational attainment and higher body mass were putatively causal for MDD whereas MDD and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for MDD, and a continuous measure of risk underlies the observed clinical phenotype. MDD is not a distinct entity that neatly demarcates normalcy from pathology but rather a useful clinical construct associated with a range of adverse outcomes and the end result of a complex process of intertwined genetic and environmental effects. These findings help refine and define the fundamental basis of MDD.
Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis
Publisher: Oxford University Press (OUP)
Date: 28-11-2012
DOI: 10.1093/HMG/DDS491
Polygenic Risk Scores Derived from Varying Definitions of Depression and Risk of Depression
Publisher: American Medical Association (AMA)
Date: 10-2021
Comorbid chronic pain and depression: shared risk factors and differential antidepressant effectiveness
Publisher: Frontiers Media SA
Date: 12-04-2021
DOI: 10.3389/FPSYT.2021.643609
Abstract: The bidirectional relationship between depression and chronic pain is well-recognized, but their clinical management remains challenging. Here we characterize the shared risk factors and outcomes for their comorbidity in the Australian Genetics of Depression cohort study ( N = 13,839). Participants completed online questionnaires about chronic pain, psychiatric symptoms, comorbidities, treatment response and general health. Logistic regression models were used to examine the relationship between chronic pain and clinical and demographic factors. Cumulative linked logistic regressions assessed the effect of chronic pain on treatment response for 10 different antidepressants. Chronic pain was associated with an increased risk of depression (OR = 1.86 [1.37–2.54]), recent suicide attempt (OR = 1.88 [1.14–3.09]), higher use of tobacco (OR = 1.05 [1.02–1.09]) and misuse of painkillers (e.g., opioids OR = 1.31 [1.06–1.62]). Participants with comorbid chronic pain and depression reported fewer functional benefits from antidepressant use and lower benefits from sertraline (OR = 0.75 [0.68–0.83]), escitalopram (OR = 0.75 [0.67–0.85]) and venlafaxine (OR = 0.78 [0.68–0.88]) when compared to participants without chronic pain. Furthermore, participants taking sertraline (OR = 0.45 [0.30–0.67]), escitalopram (OR = 0.45 [0.27–0.74]) and citalopram (OR = 0.32 [0.15–0.67]) specifically for chronic pain (among other indications) reported lower benefits compared to other participants taking these same medications but not for chronic pain. These findings reveal novel insights into the complex relationship between chronic pain and depression. Treatment response analyses indicate differential effectiveness between particular antidepressants and poorer functional outcomes for these comorbid conditions. Further examination is warranted in targeted interventional clinical trials, which also include neuroimaging genetics and pharmacogenomics protocols. This work will advance the delineation of disease risk indicators and novel aetiological pathways for therapeutic intervention in comorbid pain and depression as well as other psychiatric comorbidities.
Polygenic risk scores and the prediction of onset of mood and psychotic disorders in adolescents and young adults
Publisher: Wiley
Date: 03-10-2023
DOI: 10.1111/EIP.13472
The role of critical immune genes in brain disorders: insights from neuroimaging immunogenetics
Publisher: Oxford University Press (OUP)
Date: 03-2022
DOI: 10.1093/BRAINCOMMS/FCAC078
Abstract: Genetic variants in the human leukocyte antigen and killer cell immunoglobulin-like receptor regions have been associated with many brain-related diseases, but how they shape brain structure and function remains unclear. To identify the genetic variants in HLA and KIR genes associated with human brain phenotypes, we performed a genetic association study of ∼30 000 European unrelated in iduals using brain MRI phenotypes generated by the UK Biobank (UKB). We identified 15 HLA alleles in HLA class I and class II genes significantly associated with at least one brain MRI-based phenotypes (P & 5 × 10−8). These associations converged on several main haplotypes within the HLA. In particular, the human leukocyte antigen alleles within an ancestral haplotype 8.1 were associated with multiple MRI measures, including grey matter volume, cortical thickness (TH) and diffusion MRI (dMRI) metrics. These alleles have been strongly associated with schizophrenia. Additionally, associations were identified between HLA-DRB1*04∼DQA1*03:01∼DQB1*03:02 and isotropic volume fraction of diffusion MRI in multiple white matter tracts. This haplotype has been reported to be associated with Parkinson’s disease. These findings suggest shared genetic associations between brain MRI biomarkers and brain-related diseases. Additionally, we identified 169 associations between the complement component 4 (C4) gene and imaging phenotypes. We found that C4 gene copy number was associated with cortical TH and dMRI metrics. No KIR gene copy numbers were associated with image-derived phenotypes at genome-wide threshold. To address the multiple testing burden in the phenome-wide association study, we performed a multi-trait association analysis using trait-based association test that uses extended Simes procedure and identified MRI image-specific associations. This study contributes to insight into how critical immune genes affect brain-related traits as well as the development of neurological and neuropsychiatric disorders.
GWAS on family history of Alzheimer’s disease
Publisher: Springer Science and Business Media LLC
Date: 18-05-2018
DOI: 10.1038/S41398-018-0150-6
Abstract: Alzheimer’s disease (AD) is a public health priority for the 21st century. Risk reduction currently revolves around lifestyle changes with much research trying to elucidate the biological underpinnings. We show that self-report of parental history of Alzheimer’s dementia for case ascertainment in a genome-wide association study of 314,278 participants from UK Biobank (27,696 maternal cases, 14,338 paternal cases) is a valid proxy for an AD genetic study. After meta-analysing with published consortium data ( n = 74,046 with 25,580 cases across the discovery and replication analyses), three new AD-associated loci ( P 5 × 10 −8 ) are identified. These contain genes relevant for AD and neurodegeneration: ADAM10 , BCKDK/KAT8 and ACE . Novel gene-based loci include drug targets such as VKORC1 (warfarin dose). We report evidence that the association of SNPs in the TOMM40 gene with AD is potentially mediated by both gene expression and DNA methylation in the prefrontal cortex. However, it is likely that multiple variants are affecting the trait and gene methylation/expression. Our discovered loci may help to elucidate the biological mechanisms underlying AD and, as they contain genes that are drug targets for other diseases and disorders, warrant further exploration for potential precision medicine applications.
Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration.
Publisher: Springer Science and Business Media LLC
Date: 02-04-2020
DOI: 10.1038/S41467-020-15421-7
Abstract: Vitamin D deficiency is a candidate risk factor for a range of adverse health outcomes. In a genome-wide association study of 25 hydroxyvitamin D (25OHD) concentration in 417,580 Europeans we identify 143 independent loci in 112 1-Mb regions, providing insights into the physiology of vitamin D and implicating genes involved in lipid and lipoprotein metabolism, dermal tissue properties, and the sulphonation and glucuronidation of 25OHD. Mendelian randomization models find no robust evidence that 25OHD concentration has causal effects on candidate phenotypes (e.g. BMI, psychiatric disorders), but many phenotypes have (direct or indirect) causal effects on 25OHD concentration, clarifying the epidemiological relationship between 25OHD status and the health outcomes examined in this study.
Evidence-based psychiatric genetics, AKA the false dichotomy between common and rare variant hypotheses
Publisher: Springer Science and Business Media LLC
Date: 14-06-2011
DOI: 10.1038/MP.2011.65
Abstract: In this article, we review some of the data that contribute to our understanding of the genetic architecture of psychiatric disorders. These include results from evolutionary modelling (hence no data), the observed recurrence risk to relatives and data from molecular markers. We briefly discuss the common-disease common-variant hypothesis, the success (or otherwise) of genome-wide association studies, the evidence for polygenic variance and the likely success of exome and whole-genome sequencing studies. We conclude that the perceived dichotomy between 'common' and 'rare' variants is not only false, but unhelpful in making progress towards increasing our understanding of the genetic basis of psychiatric disorders. Strong evidence has been accumulated that is consistent with the contribution of many genes to risk of disease, across a wide range of allele frequencies and with a substantial proportion of genetic variation in the population in linkage disequilibrium with single-nucleotide polymorphisms (SNPs) on commercial genotyping arrays. At the same time, most causal variants that segregate in the population are likely to be rare and in total these variants also explain a significant proportion of genetic variation. It is the combination of allele frequency, effect size and functional characteristics that will determine the success of new experimental paradigms such as whole exome/genome sequencing to detect such loci. Empirical results suggest that roughly half the genetic variance is tagged by SNPs on commercial genome-wide chips, but that in idual causal variants have a small effect size, on average. We conclude that larger experimental s le sizes are essential to further our understanding of the biology underlying psychiatric disorders.
Genome-wide association analyses identify new risk variants and the genetic architecture of amyotrophic lateral sclerosis
Publisher: Springer Science and Business Media LLC
Date: 25-07-2016
DOI: 10.1038/NG.3622
Identification of tag haplotypes for 5HTTLPR for different genome-wide SNP platforms
Publisher: Springer Science and Business Media LLC
Date: 14-06-2011
DOI: 10.1038/MP.2011.68
The neuroprogressive nature of major depressive disorder: pathways to disease evolution and resistance, and therapeutic implications
Publisher: Springer Science and Business Media LLC
Date: 24-04-2012
DOI: 10.1038/MP.2012.33
Abstract: In some patients with major depressive disorder (MDD), in idual illness characteristics appear consistent with those of a neuroprogressive illness. Features of neuroprogression include poorer symptomatic, treatment and functional outcomes in patients with earlier disease onset and increased number and length of depressive episodes. In such patients, longer and more frequent depressive episodes appear to increase vulnerability for further episodes, precipitating an accelerating and progressive illness course leading to functional decline. Evidence from clinical, biochemical and neuroimaging studies appear to support this model and are informing novel therapeutic approaches. This paper reviews current knowledge of the neuroprogressive processes that may occur in MDD, including structural brain consequences and potential molecular mechanisms including the role of neurotransmitter systems, inflammatory, oxidative and nitrosative stress pathways, neurotrophins and regulation of neurogenesis, cortisol and the hypothalamic-pituitary-adrenal axis modulation, mitochondrial dysfunction and epigenetic and dietary influences. Evidence-based novel treatments informed by this knowledge are discussed.
PPD ACT: an app-based genetic study of postpartum depression
Publisher: Springer Science and Business Media LLC
Date: 29-11-2018
DOI: 10.1038/S41398-018-0305-5
Abstract: Postpartum depression (PPD) is one of the most frequent complications of childbirth and particularly is suited to genetic investigation as it is more homogenous than major depression outside of the perinatal period. We developed an iOS app ( PPD ACT ) to recruit, consent, screen, and enable DNA collection from women with a lifetime history of PPD to sufficiently power genome-wide association studies. In 1 year, we recruited 7344 women with a history of PPD and have biobanked 2946 DNA s les from the US. This s le of PPD cases was notably severely affected and within 2 years of their worst episode of PPD. Clinical validation was performed within a hospital setting on a subset of participants and recall validity assessed 6–9 months after initial assessment to ensure reliability of screening tools. Here we detail the creation of the PPD ACT mobile app including design, ethical, security, and deployment considerations. We emphasize the importance of multidisciplinary collaboration to correctly implement such a research project. Additionally, we describe our ability to customize the PPD ACT platform to deploy internationally in order to collect a global s le of women with PPD.
Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects
Publisher: Springer Science and Business Media LLC
Date: 21-11-2016
DOI: 10.1038/NG.3725
A genome-wide association study of shared risk across psychiatric disorders implicates gene regulation during fetal neurodevelopment
Publisher: Springer Science and Business Media LLC
Date: 28-01-2019
The value of polygenic analyses in psychiatry
Publisher: Wiley
Date: 19-01-2018
DOI: 10.1002/WPS.20480
Parsimonious model for mass-univariate vertexwise analysis
Publisher: SPIE-Intl Soc Optical Eng
Date: 20-05-2022
DNA Modification Study of Major Depressive Disorder: Beyond Locus-by-Locus Comparisons
Publisher: Elsevier BV
Date: 02-2015
Examining sex-differentiated genetic effects across neuropsychiatric and behavioral traits
Publisher: Elsevier BV
Date: 06-2021
Purification of neural precursor cells reveals the presence of distinct, stimulus-specific subpopulations of quiescent precursors in the adult mouse hippocampus
Publisher: Society for Neuroscience
Date: 27-05-2015
DOI: 10.1523/JNEUROSCI.0504-15.2015
Abstract: The activity of neural precursor cells in the adult hippoc us is regulated by various stimuli however, whether these stimuli regulate the same or different precursor populations remains unknown. Here, we developed a novel cell-sorting protocol that allows the purification to homogeneity of neurosphere-forming neural precursors from the adult mouse hippoc us and examined the responsiveness of in idual precursors to various stimuli using a clonal assay. We show that within the Hes5-GFP + /Nestin-GFP + /EGFR + cell population, which comprises the majority of neurosphere-forming precursors, there are two distinct subpopulations of quiescent precursor cells, one directly activated by high-KCl depolarization, and the other activated by norepinephrine (NE). We then demonstrate that these two populations are differentially distributed along the septotemporal axis of the hippoc us, and show that the NE-responsive precursors are selectively regulated by GABA, whereas the KCl-responsive precursors are selectively modulated by corticosterone. Finally, based on RNAseq analysis by deep sequencing, we show that the progeny generated by activating NE-responsive versus KCl-responsive quiescent precursors are molecularly different. These results demonstrate that the adult hippoc us contains phenotypically similar but stimulus-specific populations of quiescent precursors, which may give rise to neural progeny with different functional capacity.
Polygenic Prediction of Molecular Traits using Large-Scale Meta-analysis Summary Statistics
Publisher: Cold Spring Harbor Laboratory
Date: 25-11-2022
DOI: 10.1101/2022.11.23.517213
Abstract: Transcriptome-wide association study (TWAS) integrates expression quantitative trait loci (eQTL) data with genome-wide association study (GWAS) results to infer differential expression. TWAS uses multi-variant models trained using in idual-level genotype-expression datasets, but methodological development is required for TWAS to utilise larger eQTL summary statistics. TWAS models predicting gene expression were derived using blood-based eQTL summary statistics from eQTLGen, the Young Finns Study (YFS), and MetaBrain. Summary statistic polygenic scoring methods were used to derive TWAS models, evaluating their predictive utility in GTEx v8. We investigated gene inclusion criteria and omnibus tests for aggregating TWAS associations for a given gene. We performed a schizophrenia TWAS using summary statistic-based TWAS models, comparing results to existing resources and methods. TWAS models derived using eQTL summary statistics performed comparably to models derived using in idual-level data. Multi-variant TWAS models significantly improved prediction over single variant models for 8.6% of genes. TWAS models derived using eQTLGen summary statistics significantly improved prediction over models derived using a smaller in idual-level dataset. The eQTLGen-based schizophrenia TWAS, using the ACAT omnibus test to aggregate associations for each gene, identified novel significant and colocalised associations compared to summary-based mendelian randomisation (SMR) and SMR-multi. Using multi-variant TWAS models and larger eQTL summary statistic datasets can improve power to detect differential expression associations. We provide TWAS models based on eQTLGen and MetaBrain summary statistics, and software to easily derive and apply summary statistic-based TWAS models based on eQTL and other molecular QTL datasets released in the future.
COPD education and cognitive behavioral therapy group treatment for clinically significant symptoms of depression and anxiety in COPD patients: a randomized controlled trial
Publisher: Cambridge University Press (CUP)
Date: 09-10-2007
DOI: 10.1017/S0033291707001687
Abstract: Chronic obstructive pulmonary disease (COPD) affects 14 to 20 million Americans and is associated with increased prevalence of affective disorders, contributing significantly to disability. This study compared cognitive behavioral therapy (CBT) group treatment for anxiety and depression with COPD education for COPD patients with moderate-to-severe anxiety and/or depressive symptoms. A randomized controlled trial (RCT) was conducted between 11 July 2002 and 30 April 2005 at the Michael E. DeBakey VA Medical Center, Houston, TX. Participants were 238 patients treated for COPD the year before, with forced expiratory value in 1 second (FEV) 1 /forced vital capacity (FVC) % and FEV 1 % predicted, and symptoms of moderate anxiety and/or moderate depression, who were being treated by a primary care provider or pulmonologist. Participants attended eight sessions of CBT or COPD education. Assessments were at baseline, at 4 and 8 weeks, and 4, 8 and 12 months. Primary outcomes were disease-specific and generic quality of life (QoL) [Chronic Respiratory Questionnaire (CRQ) and Medical Outcomes Survey Short Form-36 (SF-36) respectively]. Secondary outcomes were anxiety [Beck Anxiety Inventory (BAI)], depressive symptoms [Beck Depression Inventory-II (BDI-II)], 6-minute walk distance (6MWD) and use of health services. Both treatments significantly improved QoL, anxiety and depression ( p .005) over 8 weeks the rate of change did not differ between groups. Improvements were maintained with no significant change during follow-up. Ratios of post- to pretreatment use of health services were equal to 1 for both groups. CBT group treatment and COPD education can achieve sustainable improvements in QoL for COPD patients experiencing moderate-to-severe symptoms of depression or anxiety.
Explaining additional genetic variation in complex traits
Publisher: Elsevier BV
Date: 04-2014
Monozygotic twins affected with major depressive disorder have greater variance in methylation than their unaffected co-twin.
Publisher: Springer Science and Business Media LLC
Date: 11-06-2013
DOI: 10.1038/TP.2013.45
GCTA-GREML accounts for linkage disequilibrium when estimating genetic variance from genome-wide SNPs
Publisher: Proceedings of the National Academy of Sciences
Date: 25-07-2016
RNA-seq analysis of skeletal muscle in motor neurone disease cases and controls
Publisher: Cold Spring Harbor Laboratory
Date: 19-03-2023
DOI: 10.1101/2023.03.13.23287229
Abstract: Amyotrophic lateral sclerosis (ALS), the most predominant form of Motor Neuron Disease (MND), is a progressive and fatal neurodegenerative condition that spreads throughout the neuromotor system by afflicting upper and lower motor neurons. Lower motor neurons project from the central nervous system and innervate muscle fibres at motor endplates, which degrade over the course of the disease leading to muscle weakness. The direction of neurodegeration from or to the point of neuromuscular junctions and the role of muscle itself in pathogenesis has continued to be a topic of debate in ALS research. To assess the variation in gene expression between affected and nonaffected muscle tissue that might lead to this local degeneration of motor units, we generated RNA-seq skeletal muscle transcriptomes from 28 MND cases and 18 healthy controls and conducted differential expression analyses on gene-level counts, as well as an isoform switching analysis on isoform-level counts. We identified 52 differentially-expressed genes (Benjamini-Hochberg-adjusted p 0.05) within this comparison, including 38 protein coding, 9 long non-coding RNA, and 5 pseudogenes. Of protein-coding genes, 31 were upregulated in cases including with notable genes including the collagenic COL25A1 ( p = 3.1 × 10 −10 ), SAA1 which is released in response to tissue injury ( p = 3.6 × 10 −5 ) as well as others of the SAA family, and the actin-encoding ACTC1 ( p = 2.3 × 10 −5 ). Additionally, we identified 17 genes which exhibited a functional isoform switch with likely functional consequences between cases and controls. Our analyses provide evidence of increased tissue generation in MND cases, which likely serve to compensate for the degeneration of motor units and skeletal muscle.
A comparison of ten polygenic score methods for psychiatric disorders applied across multiple cohorts
Publisher: Cold Spring Harbor Laboratory
Date: 11-09-2020
DOI: 10.1101/2020.09.10.20192310
Abstract: Polygenic scores (PGSs), which assess the genetic risk of in iduals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies (GWASs). PGS methods differ in which DNA variants are included and the weights assigned to them some require an independent tuning s le to help inform these choices. PGSs are evaluated in independent target cohorts with known disease status. Variability between target cohorts is observed in applications to real data sets, which could reflect a number of factors, e.g., phenotype definition or technical factors. The Psychiatric Genomics Consortium working groups for schizophrenia (SCZ) and major depressive disorder (MDD) bring together many independently collected case- control cohorts. We used these resources (31K SCZ cases, 41K controls 248K MDD cases, 563K controls) in repeated application of leave-one-cohort-out meta-analyses, each used to calculate and evaluate PGS in the left-out (target) cohort. Ten PGS methods (the baseline PC+T method and nine methods that model genetic architecture more formally: SBLUP, LDpred2-Inf, LDpred-funct, LDpred2, Lassosum, PRS-CS, PRS-CS-auto, SBayesR, MegaPRS) are compared. Compared to PC+T, the other nine methods give higher prediction statistics, MegaPRS, LDPred2 and SBayesR significantly so, up to 9.2% variance in liability for SCZ across 30 target cohorts, an increase of 44%. For MDD across 26 target cohorts these statistics were 3.5% and 59%, respectively. Although the methods that more formally model genetic architecture have similar performance, MegaPRS, LDpred2, and SBayesR rank highest in most comparison and are recommended in applications to psychiatric disorders.
Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease
Publisher: Springer Science and Business Media LLC
Date: 06-06-2022
DOI: 10.1038/S41467-022-30875-7
Abstract: We integrated lipidomics and genomics to unravel the genetic architecture of lipid metabolism and identify genetic variants associated with lipid species putatively in the mechanistic pathway for coronary artery disease (CAD). We quantified 596 lipid species in serum from 4,492 in iduals from the Busselton Health Study. The discovery GWAS identified 3,361 independent lipid-loci associations, involving 667 genomic regions (479 previously unreported), with validation in two independent cohorts. A meta-analysis revealed an additional 70 independent genomic regions associated with lipid species. We identified 134 lipid endophenotypes for CAD associated with 186 genomic loci. Associations between independent lipid-loci with coronary atherosclerosis were assessed in ∼456,000 in iduals from the UK Biobank. Of the 53 lipid-loci that showed evidence of association ( P 1 × 10 −3 ), 43 loci were associated with at least one lipid endophenotype. These findings illustrate the value of integrative biology to investigate the aetiology of atherosclerosis and CAD, with implications for other complex diseases.
Improved polygenic prediction by Bayesian multiple regression on summary statistics
Publisher: Springer Science and Business Media LLC
Date: 08-11-2019
DOI: 10.1038/S41467-019-12653-0
Abstract: Accurate prediction of an in idual’s phenotype from their DNA sequence is one of the great promises of genomics and precision medicine. We extend a powerful in idual-level data Bayesian multiple regression model (BayesR) to one that utilises summary statistics from genome-wide association studies (GWAS), SBayesR. In simulation and cross-validation using 12 real traits and 1.1 million variants on 350,000 in iduals from the UK Biobank, SBayesR improves prediction accuracy relative to commonly used state-of-the-art summary statistics methods at a fraction of the computational resources. Furthermore, using summary statistics for variants from the largest GWAS meta-analysis ( n ≈ 700, 000) on height and BMI, we show that on average across traits and two independent data sets that SBayesR improves prediction R 2 by 5.2% relative to LDpred and by 26.5% relative to clumping and p value thresholding.
Leveraging both individual-level genetic data and GWAS summary statistics increases polygenic prediction
Publisher: Elsevier BV
Date: 06-2021
Large-scale genomics unveils the genetic architecture of psychiatric disorders
Publisher: Springer Science and Business Media LLC
Date: 27-05-2014
DOI: 10.1038/NN.3708
Methylome-wide association study of early life stressors and adult mental health reveals a relationship between birth date and cell type composition in blood
Publisher: Cold Spring Harbor Laboratory
Date: 12-03-0044
DOI: 10.1101/2021.03.10.21253201
Abstract: The environment and events that we are exposed to in utero, during birth and in early childhood influence our future physical and mental health. The underlying mechanisms that lead to these outcomes in adulthood are unclear, but long-term changes in epigenetic marks, such as DNA methylation, could act as a mediating factor or biomarker. DNA methylation data was assayed at 713,522 CpG sites from 9,537 participants of the Generation Scotland: Scottish Family Health Study, a family-based cohort with extensive data on genetic, medical, family history and lifestyle information. Methylome-wide association studies of eight early life environment phenotypes and two adult mental health phenotypes were conducted using DNA methylation data collected from adult whole blood s les. Two genes involved with different developmental pathways (PRICKLE2 and ABI1) were annotated to CpG sites associated with preterm birth (P 1.27 × 10 −9 ). A further two genes important to the development of sensory pathways (SOBP and RPGRIP1) were annotated to sites associated with low birth weight (P 4.35 × 10 −8 ). Genes and gene-sets annotated from associated CpGs sites and methylation profile scores were then used to quantify any overlap between the early life environment and mental health traits. However, there was no evidence of any overlap after applying a correction for multiple testing. Time of year of birth was found to be associated with a significant difference in estimated lymphocyte and neutrophil counts. Early life environments influence the risk of developing mental health disorders later in life however, this study provides no evidence that this is mediated by stable changes to the methylome detectable in peripheral blood.
Using summary data from the Danish National Registers to estimate heritabilities for schizophrenia, bipolar disorder, and major depressive disorder
Publisher: Frontiers Media SA
Date: 2012
Investigating Shared Genetic Basis Across Tourette Syndrome and Comorbid Neurodevelopmental Disorders Along the Impulsivity-Compulsivity Spectrum
Publisher: Elsevier BV
Date: 09-2021
DNA methylation-based measures of biological age: Meta-analysis predicting time to death
Publisher: Impact Journals, LLC
Date: 28-09-2016
Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood
Publisher: Springer Science and Business Media LLC
Date: 11-06-2018
DOI: 10.1038/S41467-018-04558-1
Abstract: Understanding the difference in genetic regulation of gene expression between brain and blood is important for discovering genes for brain-related traits and disorders. Here, we estimate the correlation of genetic effects at the top-associated cis -expression or -DNA methylation (DNAm) quantitative trait loci ( cis -eQTLs or cis -mQTLs) between brain and blood ( r b ). Using publicly available data, we find that genetic effects at the top cis -eQTLs or mQTLs are highly correlated between independent brain and blood s les ( $$\\hat r_b = 0.70$$ r ^ b = 0.70 for cis -eQTLs and $$\\hat r_ b = 0.78$$ r ^ b = 0.78 for cis -mQTLs). Using meta-analyzed brain cis -eQTL/mQTL data ( n = 526 to 1194), we identify 61 genes and 167 DNAm sites associated with four brain-related phenotypes, most of which are a subset of the discoveries (97 genes and 295 DNAm sites) using data from blood with larger s le sizes ( n = 1980 to 14,115). Our results demonstrate the gain of power in gene discovery for brain-related phenotypes using blood cis -eQTL/mQTL data with large s le sizes.
Brain age predicts mortality
Publisher: Springer Science and Business Media LLC
Date: 25-04-2017
DOI: 10.1038/MP.2017.62
Author Correction: Bayesian reassessment of the epigenetic architecture of complex traits
Publisher: Springer Science and Business Media LLC
Date: 09-10-2020
DOI: 10.1038/S41467-020-19099-9
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Predicting gene targets from integrative analyses of summary data from GWAS and eQTL studies for 28 human complex traits
Publisher: Springer Science and Business Media LLC
Date: 09-08-2016
RICOPILI: Rapid Imputation for COnsortias PIpeLIne
Publisher: Oxford University Press (OUP)
Date: 08-08-2020
DOI: 10.1093/BIOINFORMATICS/BTZ633
Abstract: Genome-wide association study (GWAS) analyses, at sufficient s le sizes and power, have successfully revealed biological insights for several complex traits. RICOPILI, an open-sourced Perl-based pipeline was developed to address the challenges of rapidly processing large-scale multi-cohort GWAS studies including quality control (QC), imputation and downstream analyses. The pipeline is computationally efficient with portability to a wide range of high-performance computing environments. RICOPILI was created as the Psychiatric Genomics Consortium pipeline for GWAS and adopted by other users. The pipeline features (i) technical and genomic QC in case-control and trio cohorts, (ii) genome-wide phasing and imputation, (iv) association analysis, (v) meta-analysis, (vi) polygenic risk scoring and (vii) replication analysis. Notably, a major differentiator from other GWAS pipelines, RICOPILI leverages on automated parallelization and cluster job management approaches for rapid production of imputed genome-wide data. A comprehensive meta-analysis of simulated GWAS data has been incorporated demonstrating each step of the pipeline. This includes all the associated visualization plots, to allow ease of data interpretation and manuscript preparation. Simulated GWAS datasets are also packaged with the pipeline for user training tutorials and developer work. RICOPILI has a flexible architecture to allow for ongoing development and incorporation of newer available algorithms and is adaptable to various HPC environments (QSUB, BSUB, SLURM and others). Specific links for genomic resources are either directly provided in this paper or via tutorials and external links. The central location hosting scripts and tutorials is found at this URL: /broadinstitute.org/RICOPILI/home Supplementary data are available at Bioinformatics online.
Trajectories of inflammatory biomarkers over the eighth decade and their associations with immune cell profiles and epigenetic ageing
Publisher: Springer Science and Business Media LLC
Date: 12-2018
Heritability of transforming growth factor-β1 and tumor necrosis factor-receptor type 1 expression and vitamin D levels in healthy adolescent twins
Publisher: Cambridge University Press (CUP)
Date: 03-12-2015
DOI: 10.1017/THG.2014.70
Abstract: Cytokines and vitamin D both have a role in modulating the immune system, and are also potentially useful biomarkers in mental illnesses such as major depressive disorder (MDD) and schizophrenia. Studying the variability of cytokines and vitamin D in a healthy population s le may add to understanding the association between these biomarkers and mental illness. To assess genetic and environmental contributions to variation in circulating levels of cytokines and vitamin D (25-hydroxy vitamin D: 25(OH)D3), we analyzed data from a healthy adolescent twin cohort (mean age 16.2 years standard deviation 0.25). Plasma cytokine measures were available for 400 in iduals (85 MZ, 115 DZ pairs), dried blood spot s le vitamin D measures were available for 378 in iduals (70 MZ, 118 DZ pairs). Heritability estimates were moderate but significant for the cytokines transforming growth factor-β1 (TGF-β1), 0.57 (95% CI 0.26–0.80) and tumor necrosis factor-receptor type 1 (TNFR1), 0.50 (95% CI 0.11–0.63) respectively. Measures of 25(OH)D3 were within normal range and heritability was estimated to be high (0.86, 95% CI 0.61–0.94). Assays of other cytokines did not generate meaningful results. These potential biomarkers may be useful in mental illness, with further research warranted in larger s le sizes. They may be particularly important in adolescents with mental illness where diagnostic uncertainty poses a significant clinical challenge.
Familiality of psychiatric disorders and risk of postpartum psychiatric episodes: a population-based cohort study
Publisher: American Psychiatric Association Publishing
Date: 08-2018
Conventional multipoint nonparametric linkage analysis is not necessarily inherently biased.
Publisher: Elsevier BV
Date: 10-2004
DOI: 10.1086/424755
Are Surgical Trials with Negative Results Being Interpreted Correctly?
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 2013
Conditional GWAS analysis identifies putative disorder-specific SNPs for psychiatric disorders
Publisher: Cold Spring Harbor Laboratory
Date: 30-03-2019
DOI: 10.1101/592899
Abstract: Substantial genetic liability is shared across psychiatric disorders but less is known about risk variants that are specific to a given disorder. We used multi-trait conditional and joint analysis (mtCOJO) to adjust GWAS summary statistics of one disorder for the effects of genetically correlated traits to identify putative disorder-specific SNP associations. We applied mtCOJO to summary statistics for five psychiatric disorders from the Psychiatric Genomics Consortium – schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit hyperactivity disorder (ADHD) and autism (AUT). Most genom-wide significant variants for these disorders had evidence of pleiotropy (i.e., impact on multiple psychiatric disorders) and hence have reduced mtCOJO conditional effect sizes. However, subsets of genome-wide significant variants had larger conditional effect sizes consistent with disorder-specific effects: 15 of 130 genome-wide significant variants for schizophrenia, 5 of 40 for major depression, 3 of 11 for ADHD and 1 of 2 for autism. In addition, we identified a number of variants that approached genome-wide significance in the original GWAS and have larger conditional effect sizes after conditioning on the other disorders. We show that decreased expression of VPS29 in the brain may increase risk to SCZ only and increased expression of CSE1L is associated with SCZ and MD, but not with BIP. Likewise, decreased expression of PCDHA7 in the brain is linked to increased risk of MD but decreased risk of SCZ and BIP.
Correction: Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank
Publisher: Springer Science and Business Media LLC
Date: 18-05-2020
Multi-locus genome-wide association analysis supports the role of glutamatergic synaptic transmission in the etiology of major depressive disorder.
Publisher: Springer Science and Business Media LLC
Date: 13-11-2012
DOI: 10.1038/TP.2012.95
Genetic risk for chronic pain is associated with lower antidepressant effectiveness: converging evidence for a depression subtype
Publisher: SAGE Publications
Date: 16-07-2021
DOI: 10.1177/00048674211031491
Abstract: Chronic pain and depression are highly comorbid and difficult-to-treat disorders. We previously showed this comorbidity is associated with higher depression severity, lower antidepressant treatment effectiveness and poorer prognosis in the Australian Genetics of Depression Study. The current study aimed to assess whether a genetic liability to chronic pain is associated with antidepressant effectiveness over and above the effect of genetic factors for depression in a s le of 12,863 Australian Genetics of Depression Study participants. Polygenic risk scores were calculated using summary statistics from genome-wide association studies of multisite chronic pain and major depression. Cumulative linked regressions were employed to assess the association between polygenic risk scores and antidepressant treatment effectiveness across 10 different medications. Mixed-effects logistic regressions showed that in idual genetic propensity for chronic pain, but not major depression, was significantly associated with patient-reported chronic pain (Pain PRS OR = 1.17 [1.12, 1.22] MD PRS OR = 1.01 [0.98, 1.06]). Significant associations were also found between lower antidepressant effectiveness and genetic risk for chronic pain or for major depression. However, a fully adjusted model showed the effect of Pain PRS (adjOR = 0.93 [0.90, 0.96]) was independent of MD PRS (adjOR = 0.96 [0.93, 0.99]). Sensitivity analyses were performed to assess the robustness of these results. After adjusting for depression severity measures (i.e. age of onset number of depressive episodes interval between age at study participation and at depression onset), the associations between Pain PRS and patient-reported chronic pain with lower antidepressant effectiveness remained significant (0.95 [0.92, 0.98] and 0.84 [0.78, 0.90], respectively). These results suggest genetic risk for chronic pain accounted for poorer antidepressant effectiveness, independent of the genetic risk for major depression. Our results, along with independent converging evidence from other studies, point towards a difficult-to-treat depression subtype characterised by comorbid chronic pain. This finding warrants further investigation into the implications for biologically based nosology frameworks in pain medicine and psychiatry.
Biological insights from 108 schizophrenia-associated genetic loci
Publisher: Springer Science and Business Media LLC
Date: 07-2014
DOI: 10.1038/NATURE13595
Negative Randomized Trials
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 07-2013
Genome-wide association analysis identifies 13 new risk loci for schizophrenia
Publisher: Springer Science and Business Media LLC
Date: 25-08-2013
DOI: 10.1038/NG.2742
Genome-wide association study of medication-use and associated disease in the UK Biobank
Publisher: Springer Science and Business Media LLC
Date: 23-04-2019
DOI: 10.1038/S41467-019-09572-5
Abstract: Genome-wide association studies (GWASs) of medication use may contribute to understanding of disease etiology, could generate new leads relevant for drug discovery and can be used to quantify future risk of medication taking. Here, we conduct GWASs of self-reported medication use from 23 medication categories in approximately 320,000 in iduals from the UK Biobank. A total of 505 independent genetic loci that meet stringent criteria ( P 10 −8 /23) for statistical significance are identified. We investigate the implications of these GWAS findings in relation to biological mechanism, potential drug target identification and genetic risk stratification of disease. Amongst the medication-associated genes are 16 known therapeutic-effect target genes for medications from 9 categories. Two of the medication classes studied are for disorders that have not previously been subject to large GWAS (hypothyroidism and gastro-oesophageal reflux disease).
Association and prediction of phenotypic traits from neuroimaging data using a multi-component mixed model excluding the target vertex
Publisher: SPIE
Date: 15-02-2021
DOI: 10.1117/12.2581022
Genome and epigenome wide studies of neurological protein biomarkers in the Lothian Birth Cohort 1936
Publisher: Springer Science and Business Media LLC
Date: 18-07-2019
DOI: 10.1038/S41467-019-11177-X
Abstract: Although plasma proteins may serve as markers of neurological disease risk, the molecular mechanisms responsible for inter-in idual variation in plasma protein levels are poorly understood. Therefore, we conduct genome- and epigenome-wide association studies on the levels of 92 neurological proteins to identify genetic and epigenetic loci associated with their plasma concentrations (n = 750 healthy older adults). We identify 41 independent genome-wide significant (P 5.4 × 10 −10 ) loci for 33 proteins and 26 epigenome-wide significant (P 3.9 × 10 −10 ) sites associated with the levels of 9 proteins. Using this information, we identify biological pathways in which putative neurological biomarkers are implicated (neurological, immunological and extracellular matrix metabolic pathways). We also observe causal relationships (by Mendelian randomisation analysis) between changes in gene expression (DRAXIN, MDGA1 and KYNU), or DNA methylation profiles (MATN3, MDGA1 and NEP), and altered plasma protein levels. Together, this may help inform causal relationships between biomarkers and neurological diseases.
Perinatal depression is associated with a higher polygenic risk for major depressive disorder than non-perinatal depression
Publisher: Hindawi Limited
Date: 05-01-2022
DOI: 10.1002/DA.23232
Abstract: Distinctions between major depressive disorder (MDD) and perinatal depression (PND) reflect varying views of PND, from a unique etiological subtype of MDD to an MDD episode that happens to coincide with childbirth. This case-control study investigated genetic differences between PND and MDD outside the perinatal period (non-perinatal depression or NPD). We conducted a genome-wide association study using PND cases (Edinburgh Postnatal Depression Scale score ≥ 13) from the Australian Genetics of Depression Study 2018 data (n = 3804) and screened controls (n = 6134). Results of gene-set enrichment analysis were compared with those of women with non-PND. For six psychiatric disorders/traits, genetic correlations with PND were evaluated, and logistic regression analysis reported polygenic score (PGS) association with both PND and NPD. Genes differentially expressed in ovarian tissue were significantly enriched (stdBeta = 0.07, p = 3.3e-04), but were not found to be associated with NPD. The genetic correlation between PND and MDD was 0.93 (SE = 0.07 p = 3.5e-38). Compared with controls, PGS for MDD are higher for PND cases (odds ratio [OR] = 1.8, confidence interval [CI] = [1.7-1.8], p = 9.5e-140) than for NPD cases (OR = 1.6, CI = [1.5-1.7], p = 1.2e-49). Highest risk is for those reporting both antenatal and postnatal depression, irrespective of prior MDD history. PND has a high genetic overlap with MDD, but points of distinction focus on differential expression in ovarian tissue and higher MDD PGS, particularly for women experiencing both antenatal and postpartum PND.
The nature and management of metastatic melanoma after progression on braf inhibitors: Effects of extended BRAF inhibition
Publisher: Wiley
Date: 07-2014
DOI: 10.1002/CNCR.28851
Abstract: The v-raf murine sarcoma viral oncogene homolog B (BRAF) inhibitor (BRAFi) drugs dabrafenib and vemurafenib have high response rates in BRAF-mutant, metastatic melanoma however, 50% of patients progress by 7 months. In this study, the authors examined the nature and management of disease progression (PD) on BRAFi treatment, including characteristics and outcomes of patients who received continued BRAFi treatment beyond disease progression (TBP). Clinicopathologic data at baseline and at the time of PD were collected for all patients with BRAF-mutant metastatic melanoma who received BRAFi monotherapy within clinical trials between July 2009 and September 2012. Management and survival after PD were examined, including continued BRAFi TBP (> 28 days beyond Response Evaluation Criteria in Solid Tumor [RECIST]-defined PD). Ninety-five of 114 BRAFi-treated patients had PD. Fifty-three of those 95 patients (56%) progressed in extracranial sites alone, 18% (17 of 95 patients) progressed in intracranial and extracranial sites simultaneously, and 16% (15 of 95 patients) progressed in intracranial sites alone. Twenty-nine of the 95 patients (31%) who had PD progressed in a single site or organ, 48% (46 of 95 patients) progressed in existing metastases only, and 18% (17 of 95 patients) had new metastases alone. At the time of PD, 35 of 95 patients (37%) received no subsequent systemic treatment, 20% (19 of 95 patients) changed systemic treatments, and 39% (37 of 95 patients) continued BRAFi TBP for a median of 97 days. BRAFi TBP and known prognostic factors (Eastern Cooperative Oncology Group performance status, lactate dehydrogenase, RECIST sum of the greatest dimensions of target lesions) were associated with overall survival (OS) from the time of PD however, in multivariable analysis, BRAFi TBP improved OS (hazard ratio, 0.50 95% confidence interval, 0.27-0.93 P = .029). Most BRAFi-treated patients progressed in existing extracranial sites, and 31% progressed in isolated sites. Compared with cessation, continued BRAFi TBP is associated with prolonged OS even after adjusting for potential prognostic factors at PD.
Shared temperament risk factors for anorexia nervosa: a twin study.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 02-2008
Response to Amar J. Klar: The chromosome 1;11 translocation provides the best evidence supporting genetic etiology for schizophrenia and bipolar affective disorders
Publisher: Oxford University Press (OUP)
Date: 02-2003
Concepts, estimation and interpretation of SNP-based heritability
Publisher: Springer Science and Business Media LLC
Date: 09-2017
DOI: 10.1038/NG.3941
Abstract: Narrow-sense heritability (h
A better coefficient of determination for genetic profile analysis.
Publisher: Wiley
Date: 04-2012
DOI: 10.1002/GEPI.21614
Abstract: Genome-wide association studies have facilitated the construction of risk predictors for disease from multiple Single Nucleotide Polymorphism markers. The ability of such "genetic profiles" to predict outcome is usually quantified in an independent data set. Coefficients of determination (R(2) ) have been a useful measure to quantify the goodness-of-fit of the genetic profile. Various pseudo-R(2) measures for binary responses have been proposed. However, there is no standard or consensus measure because the concept of residual variance is not easily defined on the observed probability scale. Unlike other nongenetic predictors such as environmental exposure, there is prior information on genetic predictors because for most traits there are estimates of the proportion of variation in risk in the population due to all genetic factors, the heritability. It is this useful ability to benchmark that makes the choice of a measure of goodness-of-fit in genetic profiling different from that of nongenetic predictors. In this study, we use a liability threshold model to establish the relationship between the observed probability scale and underlying liability scale in measuring R(2) for binary responses. We show that currently used R(2) measures are difficult to interpret, biased by ascertainment, and not comparable to heritability. We suggest a novel and globally standard measure of R(2) that is interpretable on the liability scale. Furthermore, even when using ascertained case-control studies that are typical in human disease studies, we can obtain an R(2) measure on the liability scale that can be compared directly to heritability.
Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders
Publisher: Elsevier BV
Date: 2022
Blood DNA methylation sites predict death risk in a longitudinal study of 12, 300 individuals
Publisher: Impact Journals, LLC
Date: 22-07-2020
Functional characterisation of the amyotrophic lateral sclerosis risk locus GPX3/TNIP1
Publisher: Springer Science and Business Media LLC
Date: 19-01-2022
DOI: 10.1186/S13073-021-01006-6
Abstract: Amyotrophic lateral sclerosis (ALS) is a complex, late-onset, neurodegenerative disease with a genetic contribution to disease liability. Genome-wide association studies (GWAS) have identified ten risk loci to date, including the TNIP1 / GPX3 locus on chromosome five. Given association analysis data alone cannot determine the most plausible risk gene for this locus, we undertook a comprehensive suite of in silico, in vivo and in vitro studies to address this. The Functional Mapping and Annotation (FUMA) pipeline and five tools (conditional and joint analysis (GCTA-COJO), Stratified Linkage Disequilibrium Score Regression (S-LDSC), Polygenic Priority Scoring (PoPS), Summary-based Mendelian Randomisation (SMR-HEIDI) and transcriptome-wide association study (TWAS) analyses) were used to perform bioinformatic integration of GWAS data ( N cases = 20,806, N controls = 59,804) with ‘omics reference datasets including the blood (eQTLgen consortium N = 31,684) and brain ( N = 2581). This was followed up by specific expression studies in ALS case-control cohorts (microarray N total = 942, protein N total = 300) and gene knockdown (KD) studies of human neuronal iPSC cells and zebrafish-morpholinos (MO). SMR analyses implicated both TNIP1 and GPX3 ( p 1.15 × 10 −6 ), but there was no simple SNP/expression relationship. Integrating multiple datasets using PoPS supported GPX3 but not TNIP1 . In vivo expression analyses from blood in ALS cases identified that lower GPX3 expression correlated with a more progressed disease (ALS functional rating score, p = 5.5 × 10 −3 , adjusted R 2 = 0.042, B effect = 27.4 ± 13.3 ng/ml/ALSFRS unit) with microarray and protein data suggesting lower expression with risk allele (recessive model p = 0.06, p = 0.02 respectively). Validation in vivo indicated gpx3 KD caused significant motor deficits in zebrafish-MO (mean difference vs. control ± 95% CI, vs. control, swim distance = 112 ± 28 mm, time = 1.29 ± 0.59 s, speed = 32.0 ± 2.53 mm/s, respectively, p for all 0.0001), which were rescued with gpx3 expression, with no phenotype identified with tnip1 KD or gpx3 overexpression. These results support GPX3 as a lead ALS risk gene in this locus, with more data needed to confirm/reject a role for TNIP1 . This has implications for understanding disease mechanisms ( GPX3 acts in the same pathway as SOD1 , a well-established ALS-associated gene) and identifying new therapeutic approaches. Few previous ex les of in-depth investigations of risk loci in ALS exist and a similar approach could be applied to investigate future expected GWAS findings.
Genetic variants associated with response to lithium treatment in bipolar disorder: a genome-wide association study
Publisher: Elsevier BV
Date: 03-2016
Anxiety and Comorbid Measures Associated With PLXNA2
Publisher: American Medical Association (AMA)
Date: 03-2007
DOI: 10.1001/ARCHPSYC.64.3.318
Abstract: Reduction in adult neurogenesis has been proposed as a mechanism for onset of depression. Semaphorins and their coreceptors, plexins, have been implicated in nervous system development and in adult neurogenesis. A recent genomewide association study of schizophrenia identified a variant of the gene encoding plexin A2 (PLXNA2) to be most consistently associated across study s les. Common genetic liabilities have been reported between psychiatric and psychological measures, but few ex les exist of common genetic variants. To perform a genetic association study between 6 single nucleotide polymorphisms from the PLXNA2 gene (rs3736963, rs2767565, rs752016, rs1327175, rs2478813, and rs716461) and anxiety, depression, neuroticism, and psychological distress. Extreme discordant and concordant siblings. Australia. Study participants were selected with respect to extreme neuroticism scores from a population cohort of 18 742 twin in iduals and their siblings. The participants and their parents (if blood or buccal s les were available) were genotyped, for a total of 2854 genotyped in iduals from 990 families. Of these, 624 in iduals with a diagnosis of anxiety or depression from 443 families were used in the association analysis. All the participants completed the Composite International Diagnostic Interview, the 23-item Neuroticism scale of the revised Eysenck Personality Questionnaire, and the 10-item Kessler Psychological Distress Scale. Diagnoses of DSM-IV depression and anxiety were determined from the Composite International Diagnostic Interview. There was evidence of an allelic association between rs2478813 (and other single nucleotide polymorphisms correlated with it) and anxiety, depression, neuroticism, and psychological distress the association with anxiety is significant after Bonferroni correction for multiple testing (empirical P<.001). The mouse ortholog of PLXNA2 is located in a highly significant linkage region previously reported for anxiety in mice. PLXNA2 is a candidate for causal variation in anxiety and in other psychiatric disorders through its comorbidity with anxiety.
Causal associations between risk factors and common diseases inferred from GWAS summary data
Publisher: Springer Science and Business Media LLC
Date: 15-01-2018
DOI: 10.1038/S41467-017-02317-2
Abstract: Health risk factors such as body mass index (BMI) and serum cholesterol are associated with many common diseases. It often remains unclear whether the risk factors are cause or consequence of disease, or whether the associations are the result of confounding. We develop and apply a method (called GSMR) that performs a multi-SNP Mendelian randomization analysis using summary-level data from genome-wide association studies to test the causal associations of BMI, waist-to-hip ratio, serum cholesterols, blood pressures, height, and years of schooling (EduYears) with common diseases (s le sizes of up to 405,072). We identify a number of causal associations including a protective effect of LDL-cholesterol against type-2 diabetes (T2D) that might explain the side effects of statins on T2D, a protective effect of EduYears against Alzheimer’s disease, and bidirectional associations with opposite effects (e.g., higher BMI increases the risk of T2D but the effect of T2D on BMI is negative).
ATXN1 repeat expansions confer risk for amyotrophic lateral sclerosis and contribute to TDP-43 mislocalization.
Publisher: Oxford University Press (OUP)
Date: 2020
DOI: 10.1093/BRAINCOMMS/FCAA064
Abstract: Increasingly, repeat expansions are being identified as part of the complex genetic architecture of amyotrophic lateral sclerosis. To date, several repeat expansions have been genetically associated with the disease: intronic repeat expansions in C9orf72, polyglutamine expansions in ATXN2 and polyalanine expansions in NIPA1. Together with previously published data, the identification of an amyotrophic lateral sclerosis patient with a family history of spinocerebellar ataxia type 1, caused by polyglutamine expansions in ATXN1, suggested a similar disease association for the repeat expansion in ATXN1. We, therefore, performed a large-scale international study in 11 700 in iduals, in which we showed a significant association between intermediate ATXN1 repeat expansions and amyotrophic lateral sclerosis (P = 3.33 × 10−7). Subsequent functional experiments have shown that ATXN1 reduces the nucleocytoplasmic ratio of TDP-43 and enhances amyotrophic lateral sclerosis phenotypes in Drosophila, further emphasizing the role of polyglutamine repeat expansions in the pathophysiology of amyotrophic lateral sclerosis.
Novel directions for G × E analysis in psychiatry
Publisher: Cambridge University Press (CUP)
Date: 08-10-2014
DOI: 10.1017/S2045796014000584
Abstract: G × E in psychiatry may explain why environmental risk factors have big impact in some in iduals but not in others, and conversely why relatives that are genetically at risk for disease do not all develop disease. Here we discuss two novel methods that use an aggregate genome-wide measure of genetic risk to detect G × E and estimate its effect in the population using data currently available and data we anticipate will be available in the near future. The first method exploits summary statistics from large-scale genome-wide association studies ignorant of the environmental conditions and detects G × E in an out-of-s le risk-profiling framework. The second method relies on larger s les and is based on a mixed linear model framework. It estimates variance explained directly from single nucleotide polymorphisms and environmental measures. Both methods have great potential to improve public health interventions focusing on risk-based screening that is informed by both genetic and environmental risk factors.
Estimation of SNP heritability from dense genotype data
Publisher: Elsevier BV
Date: 12-2013
Statistical power to detect genetic (co)variance of complex traits using SNP data in unrelated samples
Publisher: Public Library of Science (PLoS)
Date: 10-04-2014
Risk in Relatives, Heritability, SNP-Based Heritability, and Genetic Correlations in Psychiatric Disorders: A Review
Publisher: Elsevier BV
Date: 2021
DOI: 10.1016/J.BIOPSYCH.2020.05.034
Abstract: The genetic contribution to psychiatric disorders is observed through the increased rates of disorders in the relatives of those diagnosed with disorders. These increased rates are observed to be nonspecific for ex le, children of those with schizophrenia have increased rates of schizophrenia but also a broad range of other psychiatric diagnoses. While many factors contribute to risk, epidemiological evidence suggests that the genetic contribution carries the highest risk burden. The patterns of inheritance are consistent with a polygenic architecture of many contributing risk loci. The genetic studies of the past decade have provided empirical evidence identifying thousands of DNA variants associated with psychiatric disorders. Here, we describe how these latest results are consistent with observations from epidemiology. We provide an R tool (CHARRGe) to calculate genetic parameters from epidemiological parameters and vice versa. We discuss how the single nucleotide polymorphism-based estimates of heritability and genetic correlation relate to those estimated from family records.
Genetic correlates of vitamin D-binding protein and 25 hydroxyvitamin D in neonatal dried blood spots
Publisher: Cold Spring Harbor Laboratory
Date: 14-06-2022
DOI: 10.1101/2022.06.08.22276164
Abstract: The vitamin D binding protein (DBP), encoded by the group-specific component ( GC ) gene, is a much-studied component of the vitamin D system. In a genome-wide association study of DBP concentration in 65,589 neonates, we identified 26 independent loci, 17 of which were in or close to the GC gene, with fine-mapping identifying 2 loci on chromosomes 12 and 17 (missense variants within SH2B3 and GSDMA, respectively). When adjusted for key GC haplotypes, we found 15 independent loci distributed over 10 chromosomes. Mendelian randomization analyses found evidence consistent with a unidirectional, causal effect of higher DBP concentration and (a) higher 25 hydroxyvitamin D (25OHD) concentration, and (b) a reduced risk of multiple sclerosis and rheumatoid arthritis. A phenome-wide association study in an external dataset confirmed that higher DBP concentration was associated with higher 25OHD concentration and a reduced risk of vitamin D deficiency. Our study provides new insights into the influence of DBP on vitamin D status and a range of health outcomes.
Use of monozygotic twins to investigate the relationship between 5HTTLPR genotype, depression and stressful life events: an application of item response theory
Publisher: Wiley
Date: 30-05-2008
DOI: 10.1002/9780470696781.CH4
Abstract: We examine the interaction between stressful life events (SLE) and genotypes for the length polymorphism of the serotonin receptor gene (5HTTLPR) on risk of depression. We hypothesize that if the interaction is real, monozygotic twin pairs (MZT) homozygous for the short allele (SS) will have a greater within pair variance in depression measures than MZT homozygous for the long allele (LL), as a reflection of their increased sensitivity to unknown environmental risk factors. Telephone interviews were used to assess symptoms of depression and suicidality on 824 MZT. Rather than using the interview items to calculate sum scores or allocate diagnostic classes we use Item Response Theory to model the contribution of each item to each in idual's underlying liability to depression. SLE were also measured on the MZT assessed by mailed questionnaire on average 3.8 years previously, and these were used in follow-up analyses. We find no evidence for significant differences in within pair variance between 5HTTLPR genotypic classes and so can provide no support for interaction between these genotypes and the environment. The use of MZT provides a novel framework for examining genotype x environment interaction in the absence of measures on SLE.
Leveraging both individual-level genetic data and GWAS summary statistics increases polygenic prediction
Publisher: Cold Spring Harbor Laboratory
Date: 27-11-2020
DOI: 10.1101/2020.11.27.401141
Abstract: The accuracy of polygenic risk scores (PRSs) to predict complex diseases increases with the training s le size. PRSs are generally derived based on summary statistics from large meta-analyses of multiple genome-wide association studies (GWAS). However, it is now common for researchers to have access to large in idual-level data as well, such as the UK biobank data. To the best of our knowledge, it has not yet been explored how to best combine both types of data (summary statistics and in idual-level data) to optimize polygenic prediction. The most widely used approach to combine data is the meta-analysis of GWAS summary statistics (Meta-GWAS), but we show that it does not always provide the most accurate PRS. Through simulations and using twelve real case-control and quantitative traits from both iPSYCH and UK Biobank along with external GWAS summary statistics, we compare Meta-GWAS with two alternative data-combining approaches, stacked clumping and thresholding (SCT) and Meta-PRS. We find that, when large in idual-level data is available, the linear combination of PRSs (Meta-PRS) is both a simple alternative to Meta-GWAS and often more accurate.
Suggestive linkage on chromosome 2, 8, and 17 for lifetime major depression
Publisher: Wiley
Date: 05-04-2009
DOI: 10.1002/AJMG.B.30817
Study protocol for the Australian autism biobank: an international resource to advance autism discovery research
Publisher: Springer Science and Business Media LLC
Date: 27-08-2018
Extreme inbreeding in a European ancestry sample from the contemporary UK population
Publisher: Springer Science and Business Media LLC
Date: 03-09-2019
DOI: 10.1038/S41467-019-11724-6
Abstract: In most human societies, there are taboos and laws banning mating between first- and second-degree relatives, but actual prevalence and effects on health and fitness are poorly quantified. Here, we leverage a large observational study of ~450,000 participants of European ancestry from the UK Biobank (UKB) to quantify extreme inbreeding (EI) and its consequences. We use genotyped SNPs to detect large runs of homozygosity (ROH) and call EI when % of an in idual’s genome comprise ROHs. We estimate a prevalence of EI of ~0.03%, i.e., ~1/3652. EI cases have phenotypic means between 0.3 and 0.7 standard deviation below the population mean for 7 traits, including stature and cognitive ability, consistent with inbreeding depression estimated from in iduals with low levels of inbreeding. Our study provides DNA-based quantification of the prevalence of EI in a European ancestry s le from the UK and measures its effects on health and fitness traits.
Author Correction: Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology
Publisher: Springer Science and Business Media LLC
Date: 31-01-2022
Genome-wide association study of angioedema induced by angiotensin-converting enzyme inhibitor and angiotensin receptor blocker treatment
Publisher: Springer Science and Business Media LLC
Date: 21-02-2020
Genetic correlates of vitamin D-binding protein and 25-hydroxyvitamin D in neonatal dried blood spots
Publisher: Springer Science and Business Media LLC
Date: 15-02-2023
DOI: 10.1038/S41467-023-36392-5
Abstract: The vitamin D binding protein (DBP), encoded by the group-specific component ( GC ) gene, is a component of the vitamin D system. In a genome-wide association study of DBP concentration in 65,589 neonates we identify 26 independent loci, 17 of which are in or close to the GC gene, with fine-mapping identifying 2 missense variants on chromosomes 12 and 17 (within SH2B3 and GSDMA , respectively). When adjusted for GC haplotypes, we find 15 independent loci distributed over 10 chromosomes. Mendelian randomization analyses identify a unidirectional effect of higher DBP concentration and (a) higher 25-hydroxyvitamin D concentration, and (b) a reduced risk of multiple sclerosis and rheumatoid arthritis. A phenome-wide association study confirms that higher DBP concentration is associated with a reduced risk of vitamin D deficiency. Our findings provide valuable insights into the influence of DBP on vitamin D status and a range of health outcomes.
Genome-wide association study of gastrointestinal disorders reinforces the link between the digestive tract and the nervous system
Publisher: Cold Spring Harbor Laboratory
Date: 21-10-2019
DOI: 10.1101/811737
Abstract: Genetic factors are recognized to contribute to common gastrointestinal (GI) diseases such as gastro-oesophageal reflux disease (GORD), peptic ulcer disease (PUD), irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD). We conducted genome-wide association analyses based on 456,414 in iduals and identified 27 independent and significant loci for GORD, PUD and IBS, including SNPs associated with PUD at or near genes MUC1, FUT2, PSCA and CCKBR , for which there are previously established roles in Helicobacter pylori infection, response to counteract infection-related damage, gastric acid secretion and gastrointestinal motility. Post-GWAS analyses implicate putative functional links between the nervous system and gastrointestinal tract for GORD, PUD and IBS, including the central nervous system, the enteric nervous system and their connection. Mendelian Randomisation analyses imply potentially bi-directional causality (the risk of GORD in liability to major depression and the risk of major depression in liability to GORD) or pleiotropic effect between them. A stronger genetic similarity among GORD, PUD and IBS than between these disorders and IBD is reported. These findings advance understanding the role of genetic variants in the etiology of GORD, PUD and IBS and add biological insights into the link between the nervous system and the gastrointestinal tract.
Genetic correlation between amyotrophic lateral sclerosis and schizophrenia
Publisher: Springer Science and Business Media LLC
Date: 21-03-2017
DOI: 10.1038/NCOMMS14774
Abstract: We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique in iduals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05–21.6 P =1 × 10 −4 ) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS ( P =8.4 × 10 −7 ). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08–1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.
Association study of candidate variants from brain-derived neurotrophic factor and dystrobrevin-binding protein 1 with neuroticism, anxiety, and depression
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 10-2008
Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs
Publisher: Springer Science and Business Media LLC
Date: 11-08-2202
DOI: 10.1038/NG.2711
Refining Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Genetic Loci by Integrating Summary Data From Genome-wide Association, Gene Expression, and DNA Methylation Studies
Publisher: Elsevier BV
Date: 09-2020
Mapping common disease genes
Publisher: Cambridge University Press
Date: 02-08-2007
Translation elongation factor eEF1A2 is a potential oncoprotein that is overexpressed in two-thirds of breast tumours
Publisher: Springer Science and Business Media LLC
Date: 12-09-2005
Abstract: The tissue-specific translation elongation factor eEF1A2 was recently shown to be a potential oncogene that is overexpressed in ovarian cancer. Although there is no direct evidence for an involvement of eEF1A2 in breast cancer, the genomic region to which EEF1A2 maps, 20q13, is frequently lified in breast tumours. We therefore sought to establish whether eEF1A2 expression might be upregulated in breast cancer. eEF1A2 is highly similar (98%) to the near-ubiquitously expressed eEF1A1 (formerly known as EF1-α) making analysis with commercial antibodies difficult. We have developed specific anti-eEF1A2 antibodies and used them in immunohistochemical analyses of tumour s les. We report the novel finding that although eEF1A2 is barely detectable in normal breast it is moderately to strongly expressed in two-thirds of breast tumours. This overexpression is strongly associated with estrogen receptor positivity. eEF1A2 should be considered as a putative oncogene in breast cancer that may be a useful diagnostic marker and therapeutic target for a high proportion of breast tumours. The oncogenicity of eEF1A2 may be related to its role in protein synthesis or to its potential non-canonical functions in cytoskeletal remodelling or apoptosis.
The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls
Publisher: Elsevier BV
Date: 07-2020
No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study
Publisher: Public Library of Science (PLoS)
Date: 28-10-2016
Epigenetic Signatures of Cigarette Smoking
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 10-2016
DOI: 10.1161/CIRCGENETICS.116.001506
Abstract: DNA methylation leaves a long-term signature of smoking exposure and is one potential mechanism by which tobacco exposure predisposes to adverse health outcomes, such as cancers, osteoporosis, lung, and cardiovascular disorders. To comprehensively determine the association between cigarette smoking and DNA methylation, we conducted a meta-analysis of genome-wide DNA methylation assessed using the Illumina BeadChip 450K array on 15 907 blood-derived DNA s les from participants in 16 cohorts (including 2433 current, 6518 former, and 6956 never smokers). Comparing current versus never smokers, 2623 cytosine–phosphate–guanine sites (CpGs), annotated to 1405 genes, were statistically significantly differentially methylated at Bonferroni threshold of P ×10 −7 (18 760 CpGs at false discovery rate .05). Genes annotated to these CpGs were enriched for associations with several smoking-related traits in genome-wide studies including pulmonary function, cancers, inflammatory diseases, and heart disease. Comparing former versus never smokers, 185 of the CpGs that differed between current and never smokers were significant P ×10 −7 (2623 CpGs at false discovery rate .05), indicating a pattern of persistent altered methylation, with attenuation, after smoking cessation. Transcriptomic integration identified effects on gene expression at many differentially methylated CpGs. Cigarette smoking has a broad impact on genome-wide methylation that, at many loci, persists many years after smoking cessation. Many of the differentially methylated genes were novel genes with respect to biological effects of smoking and might represent therapeutic targets for prevention or treatment of tobacco-related diseases. Methylation at these sites could also serve as sensitive and stable biomarkers of lifetime exposure to tobacco smoke.
Examining sex-differentiated genetic effects across neuropsychiatric and behavioral traits
Publisher: Cold Spring Harbor Laboratory
Date: 05-05-2020
DOI: 10.1101/2020.05.04.076042
Abstract: The origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations across these traits, we tested for a sex-differentiated genetic architecture within and between traits. Using genome-wide association study (GWAS) summary statistics for 20 neuropsychiatric and behavioral traits, we tested for differences in SNP-based heritability (h 2 ) and genetic correlation (r g ) between sexes. For each trait, we computed z-scores from sex-stratified GWAS regression coefficients and identified genes with sex-differentiated effects. We calculated Pearson correlation coefficients between z-scores for each trait pair, to assess whether specific pairs share variants with sex-differentiated effects. Finally, we tested for sex differences in between-trait genetic correlations. With current s le sizes (and power), we found no significant, consistent sex differences in SNP-based h 2 . Between-sex, within-trait genetic correlations were consistently high, although significantly less than 1 for educational attainment and risk-taking behavior. We identified genome-wide significant genes with sex-differentiated effects for eight traits. Several trait pairs shared sex-differentiated effects. The top 0.1% of genes with sex-differentiated effects across traits overlapped with neuron- and synapse-related gene sets. Most between-trait genetic correlation estimates were similar across sex, with several exceptions (e.g. educational attainment & risk-taking behavior). Sex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic, requiring large s le sizes. Genes with sex-differentiated effects are enriched for neuron-related gene sets. This work motivates further investigation of genetic, as well as environmental, influences on sex differences.
Reply to Kardos et al.: estimation of inbreeding depression from SNP data
Publisher: Proceedings of the National Academy of Sciences
Date: 21-02-2018
A Genetic Investigation of Sex Bias in the Prevalence of Attention-Deficit/Hyperactivity Disorder
Publisher: Elsevier BV
Date: 06-2018
Seven short reflections on the notion of schizophrenia
Publisher: Elsevier BV
Date: 04-2022
Significance tests for R2 of out-of-sample prediction using polygenic scores
Publisher: Elsevier BV
Date: 02-2023
ANKK1, TTC12, and NCAM1 Polymorphisms and Heroin Dependence
Publisher: American Medical Association (AMA)
Date: 03-2013
Overlap of expression quantitative trait loci (eQTL) in human brain and blood.
Publisher: Springer Science and Business Media LLC
Date: 03-06-2014
Future Directions in Genetics of Psychiatric Disorders
Publisher: Springer New York
Date: 2014
Genome-wide association study of major depressive disorder: new results, meta-analysis, and lessons learned
Publisher: Springer Science and Business Media LLC
Date: 02-11-2010
DOI: 10.1038/MP.2010.109
The association between family history of mental disorders and general cognitive ability.
Publisher: Springer Science and Business Media LLC
Date: 22-07-2014
DOI: 10.1038/TP.2014.60
Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data
Publisher: Cold Spring Harbor Laboratory
Date: 18-03-2019
DOI: 10.1101/580993
Abstract: Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation. Current high-throughput technologies for detecting PAIs, such as promoter capture Hi-C, are not scalable to large cohorts. Here, we present an analytical approach that uses summary-level data from cohort-based DNA methylation (DNAm) quantitative trait locus (mQTL) studies to predict PAIs. Using mQTL data from human peripheral blood ( n =1,980), we predicted 34,797 PAIs which showed strong overlap with the chromatin contacts identified by previous experimental assays. The promoter-interacting DNAm sites were enriched in enhancers or near expression QTLs. Genes whose promoters were involved in PAIs were more actively expressed, and gene pairs with promoter-promoter interactions were enriched for co-expression. Integration of the predicted PAIs with GWAS data highlighted interactions among 601 DNAm sites associated with 15 complex traits. This study demonstrates the use of mQTL data to predict PAIs and provides insights into the role of PAIs in complex trait variation.
Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation
Publisher: Springer Science and Business Media LLC
Date: 09-2021
Cross-disorder GWAS meta-analysis for Attention Deficit/Hyperactivity Disorder, Autism Spectrum Disorder, Obsessive Compulsive Disorder, and Tourette Syndrome
Publisher: Cold Spring Harbor Laboratory
Date: 16-09-2019
DOI: 10.1101/770222
Abstract: Attention Deficit/Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), Obsessive-Compulsive Disorder (OCD), and Tourette Syndrome (TS) are among the most prevalent neurodevelopmental psychiatric disorders of childhood and adolescence. High comorbidity rates across these four disorders point toward a common etiological thread that could be connecting them across the repetitive behaviors-impulsivity-compulsivity continuum. Aiming to uncover the shared genetic basis across ADHD, ASD, OCD, and TS, we undertake a systematic cross-disorder meta-analysis, integrating summary statistics from all currently available genome-wide association studies (GWAS) for these disorders, as made available by the Psychiatric Genomics Consortium (PGC) and the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH). We present analysis of a combined dataset of 93,294 in iduals, across 6,788,510 markers and investigate associations on the single-nucleotide polymorphism (SNP), gene and pathway levels across all four disorders but also pairwise. In the ADHD-ASD-OCD-TS cross disorder GWAS meta-analysis, we uncover in total 297 genomewide significant variants from six LD (linkage disequilibrium) -independent genomic risk regions. Out of these genomewide significant association results, 199 SNPs, that map onto four genomic regions, show high posterior probability for association with at least three of the studied disorders (m-value .9). Gene-based GWAS meta-analysis across ADHD, ASD, OCD, and TS identified 21 genes significantly associated under Bonferroni correction. Out of those, 15 could not be identified as significantly associated based on the in idual disorder GWAS dataset, indicating increased power in the cross-disorder comparisons. Cross-disorder tissue-specificity analysis implicates the Hypothalamus-Pituitary-Adrenal axis (stress response) as possibly underlying shared pathophysiology across ADHD, ASD, OCD, and TS. Our work highlights genetic variants and genes that may contribute to overlapping neurobiology across the four studied disorders and highlights the value of re-defining the framework for the study across this spectrum of highly comorbid disorders, by using transdiagnostic approaches.
Allele frequencies and the r2 measure of linkage disequilibrium: impact on design and interpretation of association studies.
Publisher: Cambridge University Press (CUP)
Date: 04-2005
DOI: 10.1375/TWIN.8.2.87
Abstract: The design and interpretation of genetic association studies depends on the relationship between the genotyped variants and the underlying functional variant, often parameterized as the squared correlation or r 2 measure of linkage disequilibrium between two loci. While it has long been recognized that placing a constraint on the r 2 between two loci also places a constraint on the difference in frequencies between the coupled alleles, this constraint has not been quantified. Here, quantification of this severe constraint is presented. For ex le, for r 2 ≥ .8, the maximum difference in allele frequency is ± .06 which occurs when one locus has allele frequency .5. For r 2 ≥ .8 and allele frequency at one locus of .1, the maximum difference in allele frequency at the second locus is only ± .02. The impact on the design and interpretation of association studies is discussed.
Genetic stratification of depression in UK Biobank suggests a subgroup linked to age of natural menopause
Publisher: Cold Spring Harbor Laboratory
Date: 05-05-2017
DOI: 10.1101/134601
Abstract: Depression is a common and clinically heterogeneous mental health disorder that is frequently comorbid with other diseases and conditions. Stratification of depression may align sub-diagnoses more closely with their underling aetiology and provide more tractable targets for research and effective treatment. In the current study, we investigated whether genetic data could be used to identify subgroups within people with depression using the UK Biobank. Examination of cross-locus correlations was used to test for evidence of subgroups by examining whether there was clustering of independent genetic variants associated with eleven other complex traits and disorders in people with depression. We found evidence of a subgroup within depression using age of natural menopause variants ( P = 1.69 × 10 −3 ) and this effect remained significant in females ( P = 1.18 × 10 −3 ), but not males ( P = 0.186). However, no evidence for this subgroup ( P 0.05) was found in Generation Scotland, iPSYCH, a UK Biobank replication cohort or the GERA cohort. In the UK Biobank, having depression was also associated with a later age of menopause (beta = 0.34, standard error = 0.06, P = 9.92 × 10 −8 ). A potential age of natural menopause subgroup within depression and the association between depression and a later age of menopause suggests that they partially share a developmental pathway.
Hypermetabolism in ALS is associated with greater functional decline and shorter survival
Publisher: BMJ
Date: 29-04-2018
Abstract: To determine the prevalence of hypermetabolism, relative to body composition, in amyotrophic lateral sclerosis (ALS) and its relationship with clinical features of disease and survival. Fifty-eight patients with clinically definite or probable ALS as defined by El Escorial criteria, and 58 age and sex-matched control participants underwent assessment of energy expenditure. Our primary outcome was the prevalence of hypermetabolism in cases and controls. Longitudinal changes in clinical parameters between hypermetabolic and normometabolic patients with ALS were determined for up to 12 months following metabolic assessment. Survival was monitored over a 30-month period following metabolic assessment. Hypermetabolism was more prevalent in patients with ALS than controls (41% vs 12%, adjusted OR=5.4 p .01). Change in body weight, body mass index and fat mass (%) was similar between normometabolic and hypermetabolic patients with ALS. Mean lower motor neuron score (SD) was greater in hypermetabolic patients when compared with normometabolic patients (4 (0.3) vs 3 (0.7) p=0.04). In the 12 months following metabolic assessment, there was a greater change in Revised ALS Functional Rating Scale score in hypermetabolic patients when compared with normometabolic patients (−0.68 points/month vs −0.39 points/month p=0.01). Hypermetabolism was inversely associated with survival. Overall, hypermetabolism increased the risk of death during follow-up to 220% (HR 3.2, 95% CI 1.1 to 9.4, p=0.03). Hypermetabolic patients with ALS have a greater level of lower motor neuron involvement, faster rate of functional decline and shorter survival. The metabolic index could be important for informing prognosis in ALS.
mBAT-combo: a more powerful test to detect gene-trait associations from GWAS data
Publisher: Elsevier BV
Date: 2023
Cardiovascular disease, psychiatric diagnosis and sex differences in the multistep hypothesis of amyotrophic lateral sclerosis
Publisher: Wiley
Date: 25-10-2020
DOI: 10.1111/ENE.14554
Erratum: Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs
Publisher: Springer Science and Business Media LLC
Date: 27-06-2012
DOI: 10.1038/NG0712-831A
Common polygenic variation contributes to risk of schizophrenia and bipolar disorder
Publisher: Springer Science and Business Media LLC
Date: 07-2009
DOI: 10.1038/NATURE08185
Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis
Publisher: Springer Science and Business Media LLC
Date: 27-02-2020
DOI: 10.1038/S41525-020-0118-3
Abstract: We conducted DNA methylation association analyses using Illumina 450K data from whole blood for an Australian amyotrophic lateral sclerosis (ALS) case–control cohort (782 cases and 613 controls). Analyses used mixed linear models as implemented in the OSCA software. We found a significantly higher proportion of neutrophils in cases compared to controls which replicated in an independent cohort from the Netherlands (1159 cases and 637 controls). The OSCA MOMENT linear mixed model has been shown in simulations to best account for confounders. When combined in a methylation profile score, the 25 most-associated probes identified by MOMENT significantly classified case–control status in the Netherlands s le (area under the curve, AUC = 0.65, CI 95% = [0.62–0.68], p = 8.3 × 10 −22 ). The maximum AUC achieved was 0.69 (CI 95% = [0.66–0.71], p = 4.3 × 10 −34 ) when cell-type proportion was included in the predictor.
Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis
Publisher: Elsevier BV
Date: 03-2022
An overview of DNA methylation-derived trait score methods and applications
Publisher: Springer Science and Business Media LLC
Date: 16-02-2023
DOI: 10.1186/S13059-023-02855-7
Abstract: Microarray technology has been used to measure genome-wide DNA methylation in thousands of in iduals. These studies typically test the associations between in idual DNA methylation sites (“probes”) and complex traits or diseases. The results can be used to generate methylation profile scores (MPS) to predict outcomes in independent data sets. Although there are many parallels between MPS and polygenic (risk) scores (PGS), there are key differences. Here, we review motivations, methods, and applications of DNA methylation-based trait prediction, with a focus on common diseases. We contrast MPS with PGS, highlighting where assumptions made in genetic modeling may not hold in epigenetic data.
Comorbid chronic pain and depression: Shared risk factors and differential antidepressant effectiveness
Publisher: Cold Spring Harbor Laboratory
Date: 24-05-2020
DOI: 10.1101/2020.05.23.20110841
Abstract: The bidirectional relationship between depression and chronic pain is well recognized, but their clinical management remains challenging. Here we characterize the shared risk factors and outcomes for their comorbidity in the Australian Genetics of Depression cohort study (N=13,839). Participants completed online questionnaires about chronic pain, psychiatric symptoms, comorbidities, treatment response and general health. Logistic regression models were used to examine the relationship between chronic pain and clinical and demographic factors. Cumulative linked logistic regressions assessed the effect of chronic pain on treatment response for ten different antidepressants. Chronic pain was associated with an increased risk of depression (OR=1.86 [1.37–2.54]), recent suicide attempt (OR=1.88[1.14–3.09]), higher use of tobacco (OR=1.05 [1.02–1.09]) and misuse of painkillers (e.g., opioids OR=1.31 [1.06–1.62]). Participants with comorbid chronic pain and depression reported fewer functional benefits from antidepressant use and lower benefits from sertraline (OR=0.75[0.68–0.83]), escitalopram (OR=0.75[0.67–0.85]) and venlafaxine (OR=0.78[0.68–0.88]) when compared to participants without chronic pain. Furthermore, participants taking sertraline (OR=0.45[0.30–0.67]), escitalopram (OR=0.45[0.27–0.74]) and citalopram (OR=0.32[0.15–0.67]) specifically for chronic pain (among other indications) reported lower benefits compared to other participants taking these same medications but not for chronic pain. These findings reveal novel insights into the complex relationship between chronic pain and depression. Treatment response analyses indicate differential effectiveness between particular antidepressants and poorer functional outcomes for these comorbid conditions. Further examination is warranted in targeted interventional clinical trials, which also include neuroimaging genetics and pharmacogenomics protocols. This work will advance the delineation of disease risk indicators and novel aetiological pathways for therapeutic intervention in comorbid pain and depression as well as other psychiatric comorbidities.
A Comparison of Ten Polygenic Score Methods for Psychiatric Disorders Applied Across Multiple Cohorts
Publisher: Elsevier BV
Date: 11-2021
Testing the role of circadian genes in conferring risk for psychiatric disorders.
Publisher: Wiley
Date: 29-03-2014
DOI: 10.1002/AJMG.B.32230
Genome‐wide gene‐environment interaction in depression: A systematic evaluation of candidate genes
Publisher: Wiley
Date: 21-11-2017
DOI: 10.1002/AJMG.B.32593
Genome-wide Regional Heritability Mapping Identifies a Locus Within the TOX2 Gene Associated With Major Depressive Disorder
Publisher: Elsevier BV
Date: 09-2017
Genomic partitioning of inbreeding depression in humans
Publisher: Elsevier BV
Date: 08-2021
Association between DNA methylation variability and self-reported exposure to heavy metals
Publisher: Springer Science and Business Media LLC
Date: 22-06-2022
DOI: 10.1038/S41598-022-13892-W
Abstract: In iduals encounter varying environmental exposures throughout their lifetimes. Some exposures such as smoking are readily observed and have high personal recall others are more indirect or sporadic and might only be inferred from long occupational histories or lifestyles. We evaluated the utility of using lifetime-long self-reported exposures for identifying differential methylation in an amyotrophic lateral sclerosis cases-control cohort of 855 in iduals. In iduals submitted paper-based surveys on exposure and occupational histories as well as whole blood s les. Genome-wide DNA methylation levels were quantified using the Illumina Infinium Human Methylation450 array. We analyzed 15 environmental exposures using the OSCA software linear and MOA models, where we regressed exposures in idually by methylation adjusted for batch effects and disease status as well as predicted scores for age, sex, cell count, and smoking status. We also regressed on the first principal components on clustered environmental exposures to detect DNA methylation changes associated with a more generalised definition of environmental exposure. Five DNA methylation probes across three environmental exposures (cadmium, mercury and metalwork) were significantly associated using the MOA models and seven through the linear models, with one additionally across a principal component representing chemical exposures. Methylome-wide significance for four of these markers was driven by extreme hyper/hypo-methylation in small numbers of in iduals. The results indicate the potential for using self-reported exposure histories in detecting DNA methylation changes in response to the environment, but also highlight the confounded nature of environmental exposure in cohort studies.
A versatile gene-based test for genome-wide association studies
Publisher: Elsevier BV
Date: 07-2010
Analysis of the Influence of microRNAs in Lithium Response in Bipolar Disorder
Publisher: Frontiers Media SA
Date: 31-05-2018
Polygenic risk score, parental socioeconomic status, family history of psychiatric disorders, and the risk for schizophrenia: a Danish population-based study and meta-analysis
Publisher: American Medical Association (AMA)
Date: 07-2015
DOI: 10.1001/JAMAPSYCHIATRY.2015.0346
Abstract: Schizophrenia has a complex etiology influenced both by genetic and nongenetic factors but disentangling these factors is difficult. To estimate (1) how strongly the risk for schizophrenia relates to the mutual effect of the polygenic risk score, parental socioeconomic status, and family history of psychiatric disorders (2) the fraction of cases that could be prevented if no one was exposed to these factors (3) whether family background interacts with an in idual's genetic liability so that specific subgroups are particularly risk prone and (4) to what extent a proband's genetic makeup mediates the risk associated with familial background. We conducted a nested case-control study based on Danish population-based registers. The study consisted of 866 patients diagnosed as having schizophrenia between January 1, 1994, and December 31, 2006, and 871 matched control in iduals. Genome-wide data and family psychiatric and socioeconomic background information were obtained from neonatal biobanks and national registers. Results from a separate meta-analysis (34,600 cases and 45,968 control in iduals) were applied to calculate polygenic risk scores. Polygenic risk scores, parental socioeconomic status, and family psychiatric history. Odds ratios (ORs), attributable risks, liability R2 values, and proportions mediated. Schizophrenia was associated with the polygenic risk score (OR, 8.01 95% CI, 4.53-14.16 for highest vs lowest decile), socioeconomic status (OR, 8.10 95% CI, 3.24-20.3 for 6 vs no exposures), and a history of schizophrenia sychoses (OR, 4.18 95% CI, 2.57-6.79). The R2 values were 3.4% (95% CI, 2.1-4.6) for the polygenic risk score, 3.1% (95% CI, 1.9-4.3) for parental socioeconomic status, and 3.4% (95% CI, 2.1-4.6) for family history. Socioeconomic status and psychiatric history accounted for 45.8% (95% CI, 36.1-55.5) and 25.8% (95% CI, 21.2-30.5) of cases, respectively. There was an interaction between the polygenic risk score and family history (P = .03). A total of 17.4% (95% CI, 9.1-26.6) of the effect associated with family history of schizophrenia sychoses was mediated through the polygenic risk score. Schizophrenia was associated with the polygenic risk score, family psychiatric history, and socioeconomic status. Our study demonstrated that family history of schizophrenia sychoses is partly mediated through the in idual's genetic liability.
Performance of risk prediction for inflammatory bowel disease based on genotyping platform and genomic risk score method
Publisher: Springer Science and Business Media LLC
Date: 29-08-2017
Polygenic risk prediction: why and when out-of-sample prediction R2 can exceed SNP-based heritability
Publisher: Elsevier BV
Date: 07-2023
Age at first birth in women is genetically associated with increased risk of schizophrenia
Publisher: Springer Science and Business Media LLC
Date: 05-07-2018
DOI: 10.1038/S41598-018-28160-Z
Abstract: Previous studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is −0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank s le. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.
Trans-eQTLs identified in whole blood have limited influence on complex disease biology
Publisher: Springer Science and Business Media LLC
Date: 11-06-2018
Estimation and partitioning of (co)heritability of inflammatory bowel disease from GWAS and immunochip data
Publisher: Oxford University Press (OUP)
Date: 11-04-2014
DOI: 10.1093/HMG/DDU174
The association between neonatal vitamin D status and risk of schizophrenia
Publisher: Springer Science and Business Media LLC
Date: 06-12-2018
DOI: 10.1038/S41598-018-35418-Z
Abstract: Clues from the epidemiology of schizophrenia, such as the increased risk in those born in winter/spring, have led to the hypothesis that prenatal vitamin D deficiency may increase the risk of later schizophrenia. We wish to explore this hypothesis in a large Danish case-control study (n = 2602). The concentration of 25 hydroxyvitamin D (25OHD) was assessed from neonatal dried blood s les. Incidence rate ratios (IRR) were calculated when examined for quintiles of 25OHD concentration. In addition, we examined statistical models that combined 25OHD concentration and the schizophrenia polygenic risk score (PRS) in a s le that combined the new s le with a previous study (total n = 3464 s les assayed and genotyped between 2008-2013). Compared to the reference (fourth) quintile, those in the lowest quintile ( .4 nmol/L) had a significantly increased risk of schizophrenia (IRR = 1.44, 95%CI: 1.12–1.85). None of the other quintile comparisons were significantly different. There was no significant interaction between 25OHD and the PRS. Neonatal vitamin D deficiency was associated with an increased risk for schizophrenia in later life. These findings could have important public health implications related to the primary prevention of schizophrenia.
Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility
Publisher: Public Library of Science (PLoS)
Date: 11-08-2021
DOI: 10.1371/JOURNAL.PONE.0255402
Abstract: Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported disease-related symptoms. Here, we demonstrate that this COVID-19 prediction model has reasonable and consistent performance across multiple independent cohorts and that our attempt to improve upon this model did not result in improved predictions. Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. While we did not find any common, large-effect variants that reached genome-wide significance, we do observe suggestive genetic associations at two SNPs (rs11844522, p = 1.9x10-7 rs5798227, p = 2.2x10-7). Explorative analyses furthermore suggest that genetic variants associated with other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. This study represents a first effort that uses a symptom-based predicted phenotype as a proxy for COVID-19 in our pursuit of understanding the genetic susceptibility of the disease. We conclude that the inclusion of symptom-based predicted cases could be a useful strategy in a scenario of limited testing, either during the current COVID-19 pandemic or any future viral outbreak.
Misestimation of heritability and prediction accuracy of male-pattern baldness
Publisher: Springer Science and Business Media LLC
Date: 29-06-2018
Response to Browning and Browning
Publisher: Elsevier BV
Date: 07-2011
Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits
Publisher: Springer Science and Business Media LLC
Date: 02-03-2018
DOI: 10.1038/S41467-018-03371-0
Abstract: The identification of genes and regulatory elements underlying the associations discovered by GWAS is essential to understanding the aetiology of complex traits (including diseases). Here, we demonstrate an analytical paradigm of prioritizing genes and regulatory elements at GWAS loci for follow-up functional studies. We perform an integrative analysis that uses summary-level SNP data from multi-omics studies to detect DNA methylation (DNAm) sites associated with gene expression and phenotype through shared genetic effects (i.e., pleiotropy). We identify pleiotropic associations between 7858 DNAm sites and 2733 genes. These DNAm sites are enriched in enhancers and promoters, and % of them are mapped to distal genes. Further pleiotropic association analyses, which link both the methylome and transcriptome to 12 complex traits, identify 149 DNAm sites and 66 genes, indicating a plausible mechanism whereby the effect of a genetic variant on phenotype is mediated by genetic regulation of transcription through DNAm.
Evidence of CNIH3 involvement in opioid dependence
Publisher: Springer Science and Business Media LLC
Date: 04-08-2015
DOI: 10.1038/MP.2015.102
Narrowing the boundaries of the genetic architecture of schizophrenia.
Publisher: Oxford University Press (OUP)
Date: 08-12-2010
Estimation and implications of the genetic architecture of fasting and non-fasting blood glucose
Publisher: Springer Science and Business Media LLC
Date: 27-01-2023
DOI: 10.1038/S41467-023-36013-1
Abstract: The genetic regulation of post-prandial glucose levels is poorly understood. Here, we characterise the genetic architecture of blood glucose variably measured within 0 and 24 h of fasting in 368,000 European ancestry participants of the UK Biobank. We found a near-linear increase in the heritability of non-fasting glucose levels over time, which plateaus to its fasting state value after 5 h post meal ( h 2 = 11% standard error: 1%). The genetic correlation between different fasting times is 0.77, suggesting that the genetic control of glucose is largely constant across fasting durations. Accounting for heritability differences between fasting times leads to a ~16% improvement in the discovery of genetic variants associated with glucose. Newly detected variants improve the prediction of fasting glucose and type 2 diabetes in independent s les. Finally, we meta-analysed summary statistics from genome-wide association studies of random and fasting glucose ( N = 518,615) and identified 156 independent SNPs explaining 3% of fasting glucose variance. Altogether, our study demonstrates the utility of random glucose measures to improve the discovery of genetic variants associated with glucose homeostasis, even in fasting conditions.
Rare DNA variants in the brain-derived neurotrophic factor gene increase risk for attention-deficit hyperactivity disorder: a next-generation sequencing study
Publisher: Springer Science and Business Media LLC
Date: 26-07-2016
DOI: 10.1038/MP.2016.117
Abstract: Attention-deficit hyperactivity disorder (ADHD) is a prevalent and highly heritable disorder of childhood with negative lifetime outcomes. Although candidate gene and genome-wide association studies have identified promising common variant signals, these explain only a fraction of the heritability of ADHD. The observation that rare structural variants confer substantial risk to psychiatric disorders suggests that rare variants might explain a portion of the missing heritability for ADHD. Here we believe we performed the first large-scale next-generation targeted sequencing study of ADHD in 152 child and adolescent cases and 188 controls across an a priori set of 117 genes. A multi-marker gene-level analysis of rare (<1% frequency) single-nucleotide variants (SNVs) revealed that the gene encoding brain-derived neurotrophic factor (BDNF) was associated with ADHD at Bonferroni corrected levels. Sanger sequencing confirmed the existence of all novel rare BDNF variants. Our results implicate BDNF as a genetic risk factor for ADHD, potentially by virtue of its critical role in neurodevelopment and synaptic plasticity.
Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology
Publisher: Springer Science and Business Media LLC
Date: 17-05-2021
Impact of diagnostic misclassification on estimation of genetic correlations using genome-wide genotypes
Publisher: Springer Science and Business Media LLC
Date: 18-01-2012
Assumptions and properties of limiting pathway models for analysis of epistasis in complex traits
Publisher: Public Library of Science (PLoS)
Date: 30-07-2013
GWAS of epigenetic aging rates in blood reveals a critical role for TERT
Publisher: Springer Science and Business Media LLC
Date: 26-01-2018
DOI: 10.1038/S41467-017-02697-5
Abstract: DNA methylation age is an accurate biomarker of chronological age and predicts lifespan, but its underlying molecular mechanisms are unknown. In this genome-wide association study of 9907 in iduals, we find gene variants mapping to five loci associated with intrinsic epigenetic age acceleration (IEAA) and gene variants in three loci associated with extrinsic epigenetic age acceleration (EEAA). Mendelian randomization analysis suggests causal influences of menarche and menopause on IEAA and lipoproteins on IEAA and EEAA. Variants associated with longer leukocyte telomere length (LTL) in the telomerase reverse transcriptase gene ( TERT ) paradoxically confer higher IEAA ( P 2.7 × 10 −11 ). Causal modeling indicates TERT -specific and independent effects on LTL and IEAA. Experimental hTERT-expression in primary human fibroblasts engenders a linear increase in DNA methylation age with cell population doubling number. Together, these findings indicate a critical role for hTERT in regulating the epigenetic clock, in addition to its established role of compensating for cell replication-dependent telomere shortening.
Embracing polygenicity: a review of methods and tools for psychiatric genetics research
Publisher: Cambridge University Press (CUP)
Date: 29-08-2017
DOI: 10.1017/S0033291717002318
Abstract: The availability of genome-wide genetic data on hundreds of thousands of people has led to an equally rapid growth in methodologies available to analyse these data. While the motivation for undertaking genome-wide association studies (GWAS) is identification of genetic markers associated with complex traits, once generated these data can be used for many other analyses. GWAS have demonstrated that complex traits exhibit a highly polygenic genetic architecture, often with shared genetic risk factors across traits. New methods to analyse data from GWAS are increasingly being used to address a erse set of questions about the aetiology of complex traits and diseases, including psychiatric disorders. Here, we give an overview of some of these methods and present ex les of how they have contributed to our understanding of psychiatric disorders. We consider: (i) estimation of the extent of genetic influence on traits, (ii) uncovering of shared genetic control between traits, (iii) predictions of genetic risk for in iduals, (iv) uncovering of causal relationships between traits, (v) identifying causal single-nucleotide polymorphisms and genes or (vi) the detection of genetic heterogeneity. This classification helps organise the large number of recently developed methods, although some could be placed in more than one category. While some methods require GWAS data on in idual people, others simply use GWAS summary statistics data, allowing novel well-powered analyses to be conducted at a low computational burden.
The epigenetic clock and telomere length are independently associated with chronological age and mortality
Publisher: Oxford University Press (OUP)
Date: 04-2016
DOI: 10.1093/IJE/DYW041
Do 5HTTLPR and stress interact in risk for depression and suicidality? Item response analyses of a large sample.
Publisher: Wiley
Date: 2010
DOI: 10.1002/AJMG.B.31044
Leveraging functional genomic annotations and genome coverage to improve polygenic prediction of complex traits within and between ancestries
Publisher: Cold Spring Harbor Laboratory
Date: 14-10-2022
DOI: 10.1101/2022.10.12.510418
Abstract: We develop a new method, SBayesRC, that integrates GWAS summary statistics with functional genomic annotations to improve polygenic prediction of complex traits. Our method is scalable to whole-genome variant analysis and refines signals from functional annotations by allowing them to affect both causal variant probability and causal effect distribution. We analyse 28 traits in the UK Biobank using ∼7 million common SNPs and 96 annotations. SBayesRC improves prediction accuracy by 14% in European ancestry and by up to 33% in trans-ancestry prediction, compared to the baseline method SBayesR which does not use annotations, and outperforms state-of-the-art methods LDpred-funct, PolyPred-S and PRS-CSx by 12-15%. Investigation of factors affecting prediction accuracy identified a significant interaction between SNP density and annotation information, encouraging future use of whole-genome sequence variants for prediction. Functional partitioning analysis highlights a major contribution of evolutionary constrained regions to prediction accuracy and the largest per-SNP contribution from non-synonymous SNPs.
Genetic structure of major depression symptoms across clinical and community cohorts
Publisher: Cold Spring Harbor Laboratory
Date: 07-07-2023
DOI: 10.1101/2023.07.05.23292214
Abstract: Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and aetiological subtypes. There are several challenges to integrating symptom data from genetically-informative cohorts, such as s le size differences between clinical and community cohorts and various patterns of missing data. We conducted genome-wide association studies of major depressive symptoms in three clinical cohorts that were enriched for affected participants (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was s led and then compared alternative models with different symptom factors. The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for missing data patterns in the community cohorts (use of Depression and Anhedonia as gating symptoms). The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analysing genetic association data.
Improving Phenotypic Prediction by Combining Genetic and Epigenetic Associations
Publisher: Elsevier BV
Date: 07-2015
A Combined Pathway and Regional Heritability Analysis Indicates NETRIN1 Pathway Is Associated With Major Depressive Disorder
Publisher: Elsevier BV
Date: 02-2017
Is schizophrenia a risk factor for breast cancer?—evidence from genetic data
Publisher: Oxford University Press (OUP)
Date: 19-11-2018
Abstract: Observational epidemiological studies have found an association between schizophrenia and breast cancer, but it is not known if the relationship is a causal one. We used summary statistics from very large genome-wide association studies of schizophrenia (n = 40675 cases and 64643 controls) and breast cancer (n = 122977 cases and 105974 controls) to investigate whether there is evidence that the association is partly due to shared genetic risk factors and whether there is evidence of a causal relationship. Using LD-score regression, we found that there is a small but significant genetic correlation (rG) between the 2 disorders (rG = 0.14, SE = 0.03, P = 4.75 × 10–8), indicating shared genetic risk factors. Using 142 genetic variants associated with schizophrenia as instrumental variables that are a proxy for having schizophrenia, we estimated a causal effect of schizophrenia on breast cancer on the observed scale as bxy = 0.032 (SE = 0.009, P = 2.3 × 10–4). A 1 SD increase in liability to schizophrenia increases risk of breast cancer 1.09-fold. In contrast, the estimated causal effect of breast cancer on schizophrenia from 191 instruments was not significantly different from zero (bxy = −0.005, SE = 0.012, P = .67). No evidence for pleiotropy was found and adjusting for the effects of smoking or parity did not alter the results. These results provide evidence that the previously observed association is due to schizophrenia causally increasing risk for breast cancer. Genetic variants may provide an avenue to elucidating the mechanism underpinning this relationship.
Genetic co-morbidity between neuroticism, anxiety/depression and somatic distress in a population sample of adolescent and young adult twins
Publisher: Cambridge University Press (CUP)
Date: 04-11-2012
DOI: 10.1017/S0033291711002431
Abstract: Genetic studies in adults indicate that genes influencing the personality trait of neuroticism account for substantial genetic variance in anxiety and depression and in somatic health. Here, we examine for the first time the factors underlying the relationship between neuroticism and anxiety/depressive and somatic symptoms during adolescence. The Somatic and Psychological Health Report (SPHERE) assessed symptoms of anxiety/depression (PSYCH-14) and somatic distress (SOMA-10) in 2459 adolescent and young adult twins [1168 complete pairs (35.4% monozygotic, 53% female)] aged 12–25 years (mean=15.5±2.9). Differences between boys and girls across adolescence were explored for neuroticism, SPHERE-34, and the subscales PSYCH-14 and SOMA-10. Trivariate analyses partitioned sources of covariance in neuroticism, PSYCH-14 and SOMA-10. Girls scored higher than boys on both neuroticism and SPHERE, with SPHERE scores for girls increasing slightly over time, whereas scores for boys decreased or were unchanged. Neuroticism and SPHERE scores were strongly influenced by genetic factors [heritability (h 2 )=40–52%]. A common genetic source influenced neuroticism, PSYCH-14 and SOMA-10 (impacting PSYCH-14 more than SOMA-10). A further genetic source, independent of neuroticism, accounted for covariation specific to PSYCH-14 and SOMA-10. Environmental influences were largely specific to each measure. In adolescence, genetic risk factors indexed by neuroticism contribute substantially to anxiety/depression and, to a lesser extent, perceived somatic health. Additional genetic covariation between anxiety/depressive and somatic symptoms, independent of neuroticism, had greatest influence on somatic distress, where it was equal in influence to the factor shared with neuroticism.
Corrigendum: The epigenetic clock and telomere length are independently associated with chronological age and mortality [Int J Epidemiol., 45, 2, (424-432)(2016)] DOI: 10.1093/ije/dyw041
Publisher: Oxford University Press (OUP)
Date: 27-11-2016
DOI: 10.1093/IJE/DYX233
The genetic association between personality and major depression or bipolar disorder. A polygenic score analysis using genome-wide association data
Publisher: Springer Science and Business Media LLC
Date: 18-10-2011
DOI: 10.1038/TP.2011.45
Haplotype Analysis and a Novel Allele-Sharing Method Refines a Chromosome 4p Locus Linked to Bipolar Affective Disorder
Publisher: Elsevier BV
Date: 03-2007
DOI: 10.1016/J.BIOPSYCH.2006.06.029
Abstract: Bipolar affective disorder (BPAD) and schizophrenia (SCZ) are common conditions. Their causes are unknown, but they include a substantial genetic component. Previously, we described significant linkage of BPAD to a chromosome 4p locus within a large pedigree (F22). Others subsequently have found evidence for linkage of BPAD and SCZ to this region. We constructed high-resolution haplotypes for four linked families, calculated logarithm of the odds (LOD) scores, and developed a novel method to assess the extent of allele sharing within genes between the families. We describe an increase in the F22 LOD score for this region. Definition and comparison of the linked haplotypes allowed us to prioritize two subregions of 3.8 and 4.4 Mb. Analysis of the extent of allele sharing within these subregions identified 200 kb that shows increased allele sharing between families. Linkage of BPAD to chromosome 4p has been strengthened. Haplotype analysis in the additional linked families refined the 20-Mb linkage region. Development of a novel allele-sharing method allowed us to bridge the gap between conventional linkage and association studies. Description of a 200-kb region of increased allele sharing prioritizes this region, which contains two functional candidate genes for BPAD, SLC2A9, and WDR1, for subsequent studies.
Lithium carbonate in amyotrophic lateral sclerosis patients homozygous for the C-allele at SNP rs12608932 in UNC13A: protocol for a confirmatory, randomized, group-sequential, event-driven, double-bli
Publisher: Springer Science and Business Media LLC
Date: 05-12-2022
DOI: 10.1186/S13063-022-06906-5
Abstract: Given the large genetic heterogeneity in amyotrophic lateral sclerosis (ALS), it seems likely that genetic subgroups may benefit differently from treatment. An exploratory meta-analysis identified that patients homozygous for the C-allele at SNP rs12608932, a single nucleotide polymorphism in the gene UNC13A , had a statistically significant survival benefit when treated with lithium carbonate. We aim to confirm the efficacy of lithium carbonate on the time to death or respiratory insufficiency in patients with ALS homozygous for the C-allele at SNP rs12608932 in UNC13A . A randomized, group-sequential, event-driven, double-blind, placebo-controlled trial will be conducted in 15 sites across Europe and Australia. Patients will be genotyped for UNC13A those homozygous for the C-allele at SNP rs12608932 will be eligible. Patients must have a diagnosis of ALS according to the revised El Escorial criteria, and a TRICALS risk-profile score between −6.0 and −2.0. An expected number of 1200 patients will be screened in order to enroll a target s le size of 171 patients. Patients will be randomly allocated in a 2:1 ratio to lithium carbonate or matching placebo, and treated for a maximum duration of 24 months. The primary endpoint is the time to death or respiratory insufficiency, whichever occurs first. Key secondary endpoints include functional decline, respiratory function, quality of life, tolerability, and safety. An interim analysis for futility and efficacy will be conducted after the occurrence of 41 events. Lithium carbonate has been proven to be safe and well-tolerated in patients with ALS. Given the favorable safety profile, the potential benefits are considered to outweigh the burden and risks associated with study participation. This study may provide conclusive evidence about the life-prolonging potential of lithium carbonate in a genetic ALS subgroup. EudraCT number 2020-000579-19 . Registered on 29 March 2021.
Polygenic risk score analysis for amyotrophic lateral sclerosis leveraging cognitive performance, educational attainment and schizophrenia
Publisher: Springer Science and Business Media LLC
Date: 27-04-2022
Author reply to A commentary on Pitfalls of predicting complex traits from SNPs.
Publisher: Springer Science and Business Media LLC
Date: 18-11-2013
DOI: 10.1038/NRG3457-C2
mBAT-combo: a more powerful test to detect gene-trait associations from GWAS data
Publisher: Cold Spring Harbor Laboratory
Date: 29-06-2022
DOI: 10.1101/2022.06.27.497850
Abstract: Gene-based association tests aggregate multiple SNP-trait associations into sets defined by gene boundaries. Since genes have a direct biological link to downstream function, gene-based test results are widely used in post-GWAS analysis. A common approach for gene-based tests is to combine SNPs associations by computing the sum of χ 2 statistics. However, this strategy ignores the directions of SNP effects, which could result in a loss of power for SNPs with masking effects (e.g., when the product of the effects of two SNPs and their linkage disequilibrium (LD) correlation is negative). Here, we introduce “mBAT-combo”, a new set-based test that is better powered than other methods to detect multi-SNP associations in the context of masking effects. We validate the method through simulations and applications to real data. We find that of 35 blood and urine biomarker traits in the UK Biobank, 34 traits show evidence for masking effects in a total of 4,175 gene-trait pairs, indicating that masking effects in complex traits is common. We further validate the improved power of our method in height, body mass index and schizophrenia with different GWAS s le sizes and show that on average 95.7% of the genes detected only by mBAT-combo with smaller s le sizes can be identified by the single-SNP approach with larger s le sizes (average s le size increased by 1.7-fold). For instance, LRRC4B is significant only in our method for schizophrenia, which has been shown to play a role in presynaptic pathology using genetic fine-mapping and evidence-based synaptic annotations. As a more powerful gene-based method, mBAT-combo is expected to improve the downstream pathway analysis or tissue and cell-type enrichment analysis that takes genes identified from GWAS data as input to understand the biological mechanisms of the trait or disease. Despite our focus on genes in this study, the framework of mBAT-combo is general and can be applied to any set of SNPs to refine trait-association signals hidden in genomic regions with complex LD structures.
Extra-motor abnormalities in amyotrophic lateral sclerosis: another layer of heterogeneity
Publisher: Informa UK Limited
Date: 03-01-2017
DOI: 10.1080/14737175.2017.1273772
Abstract: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease defined by the presence of muscle weakness. The motor features of disease are heterogeneous in site of onset and progression. There are also extra-motor features in some patients. The genetic basis for extra-motor features is uncertain. The heterogeneity of ALS is an issue for clinical trials. Areas covered: This paper reviews the range and prevalence of extra-motor features associated with ALS, and highlights the current information about genetic associations with extra-motor features. Expert commentary: There are extra-motor features of ALS, but these are not found in all patients. The most common is cognitive abnormality. More data is required to ascertain whether extra-motor features arise with progression of disease. Extra-motor features are reported in patients with a range of causative genetic mutations, but are not found in all patients with these mutations. Further studies are required of the heterogeneity of ALS, and genotype henotype correlations are required, taking note of extra-motor features.
Assessment of Response to Lithium Maintenance Treatment in Bipolar Disorder: A Consortium on Lithium Genetics (ConLiGen) Report
Publisher: Public Library of Science (PLoS)
Date: 19-06-2013
GWAS of peptic ulcer disease implicates Helicobacter pylori infection, other gastrointestinal disorders and depression
Publisher: Springer Science and Business Media LLC
Date: 19-02-2021
DOI: 10.1038/S41467-021-21280-7
Abstract: Genetic factors are recognized to contribute to peptic ulcer disease (PUD) and other gastrointestinal diseases, such as gastro-oesophageal reflux disease (GORD), irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD). Here, genome-wide association study (GWAS) analyses based on 456,327 UK Biobank (UKB) in iduals identify 8 independent and significant loci for PUD at, or near, genes MUC1 , MUC6, FUT2 , PSCA , ABO , CDX2, GAST and CCKBR . There are previously established roles in susceptibility to Helicobacter pylori infection, response to counteract infection-related damage, gastric acid secretion or gastrointestinal motility for these genes. Only two associations have been previously reported for duodenal ulcer, here replicated trans-ancestrally. The results highlight the role of host genetic susceptibility to infection. Post-GWAS analyses for PUD, GORD, IBS and IBD add insights into relationships between these gastrointestinal diseases and their relationships with depression, a commonly comorbid disorder.
A polygenic resilience score moderates the genetic risk for schizophrenia
Publisher: Springer Science and Business Media LLC
Date: 06-09-2019
DOI: 10.1038/S41380-019-0463-8
Abstract: Based on the discovery by the Resilience Project (Chen R. et al. Nat Biotechnol 34:531–538, 2016) of rare variants that confer resistance to Mendelian disease, and protective alleles for some complex diseases, we posited the existence of genetic variants that promote resilience to highly heritable polygenic disorders1,0 such as schizophrenia. Resilience has been traditionally viewed as a psychological construct, although our use of the term resilience refers to a different construct that directly relates to the Resilience Project, namely: heritable variation that promotes resistance to disease by reducing the penetrance of risk loci, wherein resilience and risk loci operate orthogonal to one another. In this study, we established a procedure to identify unaffected in iduals with relatively high polygenic risk for schizophrenia, and contrasted them with risk-matched schizophrenia cases to generate the first known “polygenic resilience score” that represents the additive contributions to SZ resistance by variants that are distinct from risk loci. The resilience score was derived from data compiled by the Psychiatric Genomics Consortium, and replicated in three independent s les. This work establishes a generalizable framework for finding resilience variants for any complex, heritable disorder.
Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing
Publisher: Springer Science and Business Media LLC
Date: 23-08-2019
Sex-Specific Association Between Genetic Risk of Psychiatric Disorders and Cardiovascular Diseases
Publisher: Cold Spring Harbor Laboratory
Date: 10-10-2022
DOI: 10.1101/2022.10.08.22280805
Abstract: Epidemiological studies show increased cardiovascular disease (CVD) risk amongst in iduals with psychiatric disorders however, sex differences in comorbidity have been inconsistent. This study examined the sex-specific association between higher genetic risk of three psychiatric disorders [major depression (MD), schizophrenia and bipolar disorder] and the risk of three CVDs [coronary artery disease (CAD), heart failure (HF) and atrial fibrillation]. Sex-specific association between polygenic scores (PGS) for psychiatric disorders and CVD outcomes was assessed in 345,201 European-ancestry in iduals (UK Biobank) using logistic regression, with analyses replicated in an independent BioVU cohort (N = 62,641). In the UK Biobank cohort, a 1-standard-deviation increase in PGS MD was associated with a 1.11- (95% CI: 1.06 - 1.16 p = 5E-06) and 1.09-fold (95% CI: 1.04 - 1.14 p = 0.00038) higher risk of incident CAD and HF in females respectively, but only with a 1.04-fold (95% CI: 1.02 - 1.07 p = 0.0016) increased risk of incident CAD in males. These associations remained even in the absence of any psychiatric disorder diagnosis. The higher risk in females may potentially be mediated by greater BMI increase in females. The risk increase of HF was consistent between females who were pre-menopausal at baseline (mean age = 44.9 years) and post-menopausal at baseline (mean age = 60.8 years), while the risk increase of CAD was only observed in the baseline post- menopausal cohort. No significant association with CVD risks was observed for the genetic risk of schizophrenia or bipolar disorder. The greater increase in CAD risk in females was replicated in the BioVU cohort. Genetic predisposition to MD confers a greater risk of CAD and HF in females compared to males, even in the absence of any depression diagnosis. In addition to depression diagnosis, this study highlights the importance of considering predisposition to depression in heart health checks, especially in women.
Genotype-by-environment interactions inferred from genetic effects on phenotypic variability in the UK Biobank
Publisher: American Association for the Advancement of Science (AAAS)
Date: 02-08-2019
Abstract: We show that genotype-by-environment interaction can be inferred from an analysis without environmental data in a large s le.
Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia
Publisher: Elsevier BV
Date: 05-2023
The heritability of delusional‐like experiences
Publisher: Wiley
Date: 10-08-2012
DOI: 10.1111/J.1600-0447.2012.01905.X
Abstract: Delusional-like experiences (DLE) are common in the general community and are associated with a family history of mental illness. The aim of this study was to estimate the heritability of DLE. The Peter's Delusional Inventory (PDI) was administered to a population-based cohort of mothers (n = 2861, aged 35-67 years) and their adult offspring (n = 3079, aged 18-23 years). Heritability of DLE was estimated from the sum scores of the 21 item PDI under the assumption that the covariance between mother-offspring scores is attributable to shared additive genetic factors. The means (medians and standard deviations) for the total PDI scores for the mothers and their offspring were 3.6 (3.0, 3.0) and 5.0 (4.0, 3.5), respectively. The Pearson correlation coefficient between mother and offspring PDI scores was 0.17 (P < 0.001). The heritability was estimated to be 0.35 (standard error 0.04). Heritable factors contribute to over a third of the variance of PDI scores in this population. In light of the association between a family history of a wide range of mental disorders and DLE, these experiences may represent a useful quantitative endophenotype for genetic studies of common mental disorders in population settings.
Correction to: lifetime stress accelerates epigenetic aging in an urban, African American cohort: relevance of glucocorticoid signaling
Publisher: Springer Science and Business Media LLC
Date: 23-05-2018
Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors
Publisher: Elsevier BV
Date: 02-2022
Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders
Publisher: Elsevier BV
Date: 12-2019
Genome-wide association study of dietary intake in the UK biobank study and its associations with schizophrenia and other traits
Publisher: Springer Science and Business Media LLC
Date: 03-02-2020
DOI: 10.1038/S41398-020-0688-Y
Abstract: Motivated by observational studies that report associations between schizophrenia and traits, such as poor diet, increased body mass index and metabolic disease, we investigated the genetic contribution to dietary intake in a s le of 335,576 in iduals from the UK Biobank study. A principal component analysis applied to diet question item responses generated two components: Diet Component 1 (DC1) represented a meat-related diet and Diet Component 2 (DC2) a fish and plant-related diet. Genome-wide association analysis identified 29 independent single-nucleotide polymorphisms (SNPs) associated with DC1 and 63 SNPs with DC2. Estimated from over 35,000 3rd-degree relative pairs that are unlikely to share close family environments, heritabilities for both DC1 and DC2 were 0.16 (standard error (s.e.) = 0.05). SNP-based heritability was 0.06 (s.e. = 0.003) for DC1 and 0.08 (s.e = 0.004) for DC2. We estimated significant genetic correlations between both DCs and schizophrenia, and several other traits. Mendelian randomisation analyses indicated a negative uni-directional relationship between liability to schizophrenia and tendency towards selecting a meat-based diet (which could be direct or via unidentified correlated variables), but a bi-directional relationship between liability to schizophrenia and tendency towards selecting a fish and plant-based diet consistent with genetic pleiotropy.
A unified framework for association and prediction from vertex-wise grey-matter structure.
Publisher: Wiley
Date: 20-07-2020
DOI: 10.1002/HBM.25109
Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions
Publisher: Springer Science and Business Media LLC
Date: 04-02-2019
Genetic correlates of social stratification in Great Britain
Publisher: Springer Science and Business Media LLC
Date: 21-10-2019
DOI: 10.1038/S41562-019-0757-5
Abstract: Human DNA polymorphisms vary across geographic regions, with the most commonly observed variation reflecting distant ancestry differences. Here we investigate the geographic clustering of common genetic variants that influence complex traits in a s le of ~450,000 in iduals from Great Britain. Of 33 traits analysed, 21 showed significant geographic clustering at the genetic level after controlling for ancestry, probably reflecting migration driven by socioeconomic status (SES). Alleles associated with educational attainment (EA) showed the most clustering, with EA-decreasing alleles clustering in lower SES areas such as coal mining areas. In iduals who leave coal mining areas carry more EA-increasing alleles on average than those in the rest of Great Britain. The level of geographic clustering is correlated with genetic associations between complex traits and regional measures of SES, health and cultural outcomes. Our results are consistent with the hypothesis that social stratification leaves visible marks in geographic arrangements of common allele frequencies and gene-environment correlations.
A genome-wide meta-analysis of association studies of Cloninger's Temperament Scales.
Publisher: Springer Science and Business Media LLC
Date: 15-05-2012
DOI: 10.1038/TP.2012.37
Widespread signatures of natural selection across human complex traits and functional genomic categories
Publisher: Springer Science and Business Media LLC
Date: 19-02-2021
DOI: 10.1038/S41467-021-21446-3
Abstract: Understanding how natural selection has shaped genetic architecture of complex traits is of importance in medical and evolutionary genetics. Bayesian methods have been developed using in idual-level GWAS data to estimate multiple genetic architecture parameters including selection signature. Here, we present a method (SBayesS) that only requires GWAS summary statistics. We analyse data for 155 complex traits (n = 27k–547k) and project the estimates onto those obtained from evolutionary simulations. We estimate that, on average across traits, about 1% of human genome sequence are mutational targets with a mean selection coefficient of ~0.001. Common diseases, on average, show a smaller number of mutational targets and have been under stronger selection, compared to other traits. SBayesS analyses incorporating functional annotations reveal that selection signatures vary across genomic regions, among which coding regions have the strongest selection signature and are enriched for both the number of associated variants and the magnitude of effect sizes.
Molecular pathways involved in neuronal cell adhesion and membrane scaffolding contribute to schizophrenia and bipolar disorder susceptibility
Publisher: Springer Science and Business Media LLC
Date: 16-02-2010
DOI: 10.1038/MP.2010.7
Abstract: Susceptibility to schizophrenia and bipolar disorder may involve a substantial, shared contribution from thousands of common genetic variants, each of small effect. Identifying whether risk variants map to specific molecular pathways is potentially biologically informative. We report a molecular pathway analysis using the single-nucleotide polymorphism (SNP) ratio test, which compares the ratio of nominally significant (P<0.05) to nonsignificant SNPs in a given pathway to identify the 'enrichment' for association signals. We applied this approach to the discovery (the International Schizophrenia Consortium (n=6909)) and validation (Genetic Association Information Network (n=2729)) of schizophrenia genome-wide association study (GWAS) data sets. We investigated each of the 212 experimentally validated pathways described in the Kyoto Encyclopaedia of Genes and Genomes in the discovery s le. Nominally significant pathways were tested in the validation s le, and five pathways were found to be significant (P=0.03-0.001) only the cell adhesion molecule (CAM) pathway withstood conservative correction for multiple testing. Interestingly, this pathway was also significantly associated with bipolar disorder (Wellcome Trust Case Control Consortium (n=4847)) (P=0.01). At a gene level, CAM genes associated in all three s les (NRXN1 and CNTNAP2), which were previously implicated in specific language disorder, autism and schizophrenia. The CAM pathway functions in neuronal cell adhesion, which is critical for synaptic formation and normal cell signaling. Similar pathways have also emerged from a pathway analysis of autism, suggesting that mechanisms involved in neuronal cell adhesion may contribute broadly to neurodevelopmental psychiatric phenotypes.
Leveraging base-pair mammalian constraint to understand genetic variation and human disease
Publisher: American Association for the Advancement of Science (AAAS)
Date: 28-04-2023
Abstract: Thousands of genomic regions have been associated with heritable human diseases, but attempts to elucidate biological mechanisms are impeded by an inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function, agnostic to cell type or disease mechanism. Single-base phyloP scores from 240 mammals identified 3.3% of the human genome as significantly constrained and likely functional. We compared phyloP scores to genome annotation, association studies, copy-number variation, clinical genetics findings, and cancer data. Constrained positions are enriched for variants that explain common disease heritability more than other functional annotations. Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.
Association between the TRAX/DISC locus and both bipolar disorder and schizophrenia in the Scottish population.
Publisher: Springer Science and Business Media LLC
Date: 19-04-2005
Abstract: The Translin-associated factor X/Disrupted in Schizophrenia 1 (TRAX/DISC) region was first implicated as a susceptibility locus for schizophrenia by analysis of a large Scottish family in which a t(1 ) translocation cosegregates with schizophrenia, bipolar disorder and recurrent major depression. We now report evidence for association between bipolar disorder and schizophrenia and this locus in the general Scottish population. A systematic study of linkage disequilibrium in a representative s le of the Scottish population was undertaken across the 510 kb of TRAX and DISC1. SNPs representing each haplotype block were selected for case-control association studies of both schizophrenia and bipolar disorder. Significant association with bipolar disorder in women P=0.00026 (P=0.0016 in men and women combined) was detected in a region of DISC1. This same region also showed nominally significant association with schizophrenia in both men and women combined, P=0.0056. Two further regions, one in TRAX and the second in DISC1, showed weaker evidence for sex-specific associations of in idual haplotypes with bipolar disorder in men and women respectively, P<0.01. Only the association between bipolar women and DISC1 remained significant after correction for multiple testing. This result provides further supporting evidence for DISC1 as a susceptibility factor for both bipolar disorder and schizophrenia, consistent with the diagnoses in the original Scottish translocation family.
“Arte et Labore”—A Blackburn Rovers fan's legacy in human complex trait genetics
Publisher: Wiley
Date: 27-06-2019
DOI: 10.1111/JBG.12384
Abstract: Through his own research contributions on the modelling and genetic analysis of quantitative traits and through his former students and postdocs, Robin Thompson has indirectly left a major legacy in human genetics. In this short note, we highlight ex les of the long-lasting relevance and impact of Robin's work in human genetics. A lone early study of marker-assisted selection developed many of the tools and approaches later exploited (often after reinvention) by the human genetics community in GWAS studies and for prediction. Furthermore, a particularly clear ex le of the pervasive impact of Robin's work is that REML has become the default method to estimate variance components and that genetic predictions exploiting linkage disequilibrium in the population are starting to become used in precision medicine applications.
Use of MOET in Merino breeding programmes: a practical and economic appraisal
Publisher: Cambridge University Press (CUP)
Date: 04-1996
DOI: 10.1017/S1357729800014545
Abstract: Commercial application of multiple ovulation and embryo transfer (MOET) technology will be subject to practical constraints and economic rationalism. This study examines use of MOET in its most profitable arena: to breed stud rams which will disseminate genetic improvement widely through multiplier studs to commercial flocks. A deterministic prediction is used to evaluate schemes based on an open nucleus MOET group within a Merino parent stud, taking account of genetic merit and inbreeding. Selection is based on clean fleece weight with an assumed heritability of 0·4. Embryos are collected at a rate equivalent to 3·45 live lambs per donor. Benefits of MOET were calculated from the discounted expressions of rams sold, and compared with the costs incurred. As the proportion of the flock born from MOET increases, the rate of genetic gain increases rapidly at first, but diminishing returns are observed. The costs ofMOET increase linearly with the number of lambs produced, so the optimum proportion ofMOET lambs is for practical purposes always less than 100%. Some use of MOET was profitable provided the stud sells sufficient stud rams each year. Sensitivity tests found that other parameters had only a small impact on the optimum level ofMOET. In general however, changes which increased the rate of genetic gain (heritability, flock size) or increased its value (wool price, lower discount rate) increased the optimum number ofMOET lambs. The results should provide guidelines to optimum investment in MOET for the wool industry. An across flock genetic evaluation scheme is probably necessary to motivate this investment.
Association analysis of the chromosome 4p-located G protein-coupled receptor 78 (GPR78) gene in bipolar affective disorder and schizophrenia.
Publisher: Springer Science and Business Media LLC
Date: 03-01-2006
Abstract: The orphan G protein-coupled receptor 78 (GPR78) gene lies within a region of chromosome 4p where we have previously shown linkage to bipolar affective disorder (BPAD) in a large Scottish family. GPR78 was screened for single-nucleotide polymorphisms (SNPs) and a linkage disequilibrium map was constructed. Six tagging SNPs were selected and tested for association on a s le of 377 BPAD, 392 schizophrenia (SCZ) and 470 control in iduals. Using standard chi(2) statistics and a backwards logistic regression approach to adjust for the effect of sex, SNP rs1282, located approximately 3 kb upstream of the coding region, was identified as a potentially important variant in SCZ (chi(2) P=0.044 LRT P=0.065). When the analysis was restricted to females, the strength of association increased to an uncorrected allele P-value of 0.015 (odds ratios (OR)=1.688, 95% confidence intervals (CI): 1.104-2.581) and uncorrected genotype P-value of 0.015 (OR=5.991, 95% CI: 1.545-23.232). Under the recessive model, the genotype P-value improved further to 0.005 (OR=5.618, 95% CI: 1.460-21.617) and remained significant after correcting for multiple testing (P=0.017). No single-marker association was detected in the SCZ males, in the BPAD in iduals or with any other SNP. Haplotype analysis of the case-control s les revealed several global and in idual haplotypes, with P-values <0.05, all but one of which contained SNP rs1282. After correcting for multiple testing, two haplotypes remained significant in both the female BPAD in iduals (P=0.038 and 0.032) and in the full s le of affected female in iduals (P=0.044 and 0.033). Our results provide preliminary evidence for the involvement of GPR78 in susceptibility to BPAD and SCZ in the Scottish population.
A genome-wide association study of Cloninger's temperament scales: Implications for the evolutionary genetics of personality
Publisher: Elsevier BV
Date: 10-2010
Risk prediction of late-onset Alzheimer’s disease implies an oligogenic architecture
Publisher: Springer Science and Business Media LLC
Date: 23-09-2020
DOI: 10.1038/S41467-020-18534-1
Abstract: Genetic association studies have identified 44 common genome-wide significant risk loci for late-onset Alzheimer’s disease (LOAD). However, LOAD genetic architecture and prediction are unclear. Here we estimate the optimal P -threshold ( P optimal ) of a genetic risk score (GRS) for prediction of LOAD in three independent datasets comprising 676 cases and 35,675 family history proxy cases. We show that the discriminative ability of GRS in LOAD prediction is maximised when selecting a small number of SNPs. Both simulation results and direct estimation indicate that the number of causal common SNPs for LOAD may be less than 100, suggesting LOAD is more oligogenic than polygenic. The best GRS explains approximately 75% of SNP-heritability, and in iduals in the top decile of GRS have ten-fold increased odds when compared to those in the bottom decile. In addition, 14 variants are identified that contribute to both LOAD risk and age at onset of LOAD.
Attention deficit hyperactivity disorder symptoms as antecedents of later psychotic outcomes in 22q11.2 deletion syndrome
Publisher: Elsevier BV
Date: 02-2019
Calculation of Prediction Error Variances Using Sparse-Matrix Methods
Publisher: Wiley
Date: 12-01-1994
DOI: 10.1111/J.1439-0388.1994.TB00443.X
Abstract: The use of exact and approximate algorithms to calculate prediction error variances using sparse matrix methods are demonstrated for an in idual animal effect including maternal effects. One exact algorithm is substantially faster than two others. An approximation of the best exact method gave an acceptable level of reliabilities and reduced the computation by a factor of approximately fifty compared with the exact computation and is routine in national beef evaluation in Britain.
Gene action, genetic variation, and GWAS: A user-friendly web tool
Publisher: Public Library of Science (PLoS)
Date: 20-05-2021
DOI: 10.1371/JOURNAL.PGEN.1009548
Abstract: Fisher’s partitioning of genotypic values and genetic variance is highly relevant in the current era of genome-wide association studies (GWASs). However, despite being more than a century old, a number of persistent misconceptions related to nonadditive genetic effects remain. We developed a user-friendly web tool, the Falconer ShinyApp, to show how the combination of gene action and allele frequencies at causal loci translate to genetic variance and genetic variance components for a complex trait. The app can be used to demonstrate the relationship between a SNP effect size estimated from GWAS and the variation the SNP generates in the population, i.e., how locus-specific effects lead to in idual differences in traits. In addition, it can also be used to demonstrate how within and between locus interactions (dominance and epistasis, respectively) usually do not lead to a large amount of nonadditive variance relative to additive variance, and therefore, that these interactions usually do not explain in idual differences in a population.
Accurate, Large-Scale Genotyping of 5HTTLPR and Flanking Single Nucleotide Polymorphisms in an Association Study of Depression, Anxiety, and Personality Measures.
Publisher: Elsevier BV
Date: 09-2009
Analysis of DNA methylation associates the cystine–glutamate antiporter SLC7A11 with risk of Parkinson’s disease
Publisher: Springer Science and Business Media LLC
Date: 06-03-2020
DOI: 10.1038/S41467-020-15065-7
Abstract: An improved understanding of etiological mechanisms in Parkinson’s disease (PD) is urgently needed because the number of affected in iduals is projected to increase rapidly as populations age. We present results from a blood-based methylome-wide association study of PD involving meta-analysis of 229 K CpG probes in 1,132 cases and 999 controls from two independent cohorts. We identify two previously unreported epigenome-wide significant associations with PD, including cg06690548 on chromosome 4. We demonstrate that cg06690548 hypermethylation in PD is associated with down-regulation of the SLC7A11 gene and show this is consistent with an environmental exposure, as opposed to medications or genetic factors with effects on DNA methylation or gene expression. These findings are notable because SLC7A11 codes for a cysteine-glutamate anti-porter regulating levels of the antioxidant glutathione, and it is a known target of the environmental neurotoxin β-methylamino-L-alanine (BMAA). Our study identifies the SLC7A11 gene as a plausible biological target in PD.
Genetic Overlap Between Diagnostic Subtypes of Ischemic Stroke
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 03-2015
DOI: 10.1161/STROKEAHA.114.007930
Abstract: Despite moderate heritability, the phenotypic heterogeneity of ischemic stroke has h ered gene discovery, motivating analyses of diagnostic subtypes with reduced s le sizes. We assessed evidence for a shared genetic basis among the 3 major subtypes: large artery atherosclerosis (LAA), cardioembolism, and small vessel disease (SVD), to inform potential cross-subtype analyses. Analyses used genome-wide summary data for 12 389 ischemic stroke cases (including 2167 LAA, 2405 cardioembolism, and 1854 SVD) and 62 004 controls from the Metastroke consortium. For 4561 cases and 7094 controls, in idual-level genotype data were also available. Genetic correlations between subtypes were estimated using linear mixed models and polygenic profile scores. Meta-analysis of a combined LAA–SVD phenotype (4021 cases and 51 976 controls) was performed to identify shared risk alleles. High genetic correlation was identified between LAA and SVD using linear mixed models ( r g =0.96, SE=0.47, P =9×10 −4 ) and profile scores ( r g =0.72 95% confidence interval, 0.52–0.93). Between LAA and cardioembolism and SVD and cardioembolism, correlation was moderate using linear mixed models but not significantly different from zero for profile scoring. Joint meta-analysis of LAA and SVD identified strong association ( P =1×10 −7 ) for single nucleotide polymorphisms near the opioid receptor μ1 ( OPRM1 ) gene. Our results suggest that LAA and SVD, which have been hitherto treated as genetically distinct, may share a substantial genetic component. Combined analyses of LAA and SVD may increase power to identify small-effect alleles influencing shared pathophysiological processes.
A direct test of the diathesis–stress model for depression
Publisher: Springer Science and Business Media LLC
Date: 11-07-2018
DOI: 10.1038/MP.2017.130
Mapping genomic loci implicates genes and synaptic biology in schizophrenia
Publisher: Springer Science and Business Media LLC
Date: 08-04-2022
Common SNPs explain some of the variation in the personality dimensions of neuroticism and extraversion
Publisher: Springer Science and Business Media LLC
Date: 17-04-2012
DOI: 10.1038/TP.2012.27
A genome‐wide association study of sleep habits and insomnia
Publisher: Wiley
Date: 31-05-2013
DOI: 10.1002/AJMG.B.32168
Polygenic transmission and complex neuro developmental network for attention deficit hyperactivity disorder: Genome‐wide association study of both common and rare variants
Publisher: Wiley
Date: 31-05-2013
DOI: 10.1002/AJMG.B.32169
Association of mental disorder in childhood and adolescence with subsequent educational achievement
Publisher: American Medical Association (AMA)
Date: 08-2020
Quantitative genetics of disease traits
Publisher: Wiley
Date: 30-03-2015
DOI: 10.1111/JBG.12153
Abstract: John James authored two key papers on the theory of risk to relatives for binary disease traits and the relationship between parameters on the observed binary scale and an unobserved scale of liability (James Annals of Human Genetics, 1971 35: 47 Reich, James and Morris Annals of Human Genetics, 1972 36: 163). These two papers are John James' most cited papers (198 and 328 citations, November 2014). They have been influential in human genetics and have recently gained renewed popularity because of their relevance to the estimation of quantitative genetics parameters for disease traits using SNP data. In this review, we summarize the two early papers and put them into context. We show recent extensions of the theory for ascertained case-control data and review recent applications in human genetics.
Common schizophrenia alleles are enriched in mutation-intolerant genes and maintained by background selection
Publisher: Cold Spring Harbor Laboratory
Date: 09-08-2016
DOI: 10.1101/068593
Abstract: Schizophrenia is a debilitating psychiatric condition often associated with poor quality of life and decreased life expectancy. Lack of progress in improving treatment outcomes has been attributed to limited knowledge of the underlying biology, although large-scale genomic studies have begun to provide such insight. We report the largest single cohort genome-wide association study of schizophrenia (11,260 cases and 24,542 controls) and through meta-analysis with existing data we identify 50 novel GWAS loci. Using gene-wide association statistics we implicate an additional set of 22 novel associations that map onto a single gene. We show for the first time that the common variant association signal is highly enriched among genes that are intolerant to loss of function mutations and that variants in these genes persist in the population despite the low fecundity associated with the disorder through the process of background selection. Associations point to novel areas of biology (e.g. metabotropic GABA-B signalling and acetyl cholinesterase), reinforce those implicated in earlier GWAS studies (e.g. calcium channel function), converge with earlier rare variants studies (e.g. NRXN1, GABAergic signalling), identify novel overlaps with autism (e.g. RBFOX1, FOXP1, FOXG1), and support early controversial candidate gene hypotheses (e.g. ERBB4 implicating neuregulin signalling). We also demonstrate the involvement of six independent central nervous system functional gene sets in schizophrenia pathophysiology. These findings provide novel insights into the biology and genetic architecture of schizophrenia, highlight the importance of mutation intolerant genes and suggest a mechanism by which common risk variants are maintained in the population.
DNA methylation age of blood predicts all-cause mortality in later life
Publisher: Springer Science and Business Media LLC
Date: 30-01-2015
Interactions between the lipidome and genetic and environmental factors in autism
Publisher: Springer Science and Business Media LLC
Date: 04-2023
DOI: 10.1038/S41591-023-02271-1
Abstract: Autism omics research has historically been reductionist and diagnosis centric, with little attention paid to common co-occurring conditions (for ex le, sleep and feeding disorders) and the complex interplay between molecular profiles and neurodevelopment, genetics, environmental factors and health. Here we explored the plasma lipidome (783 lipid species) in 765 children (485 diagnosed with autism spectrum disorder (ASD)) within the Australian Autism Biobank. We identified lipids associated with ASD diagnosis ( n = 8), sleep disturbances ( n = 20) and cognitive function ( n = 8) and found that long-chain polyunsaturated fatty acids may causally contribute to sleep disturbances mediated by the FADS gene cluster. We explored the interplay of environmental factors with neurodevelopment and the lipidome, finding that sleep disturbances and unhealthy diet have a convergent lipidome profile (with potential mediation by the microbiome) that is also independently associated with poorer adaptive function. In contrast, ASD lipidome differences were accounted for by dietary differences and sleep disturbances. We identified a large chr19p13.2 copy number variant genetic deletion spanning the LDLR gene and two high-confidence ASD genes ( ELAVL3 and SMARCA4 ) in one child with an ASD diagnosis and widespread low-density lipoprotein-related lipidome derangements. Lipidomics captures the complexity of neurodevelopment, as well as the biological effects of conditions that commonly affect quality of life among autistic people.
Moving beyond neurons: the role of cell type-specific gene regulation in Parkinson’s disease heritability
Publisher: Springer Science and Business Media LLC
Date: 17-04-2019
DOI: 10.1038/S41531-019-0076-6
Abstract: Parkinson’s disease (PD), with its characteristic loss of nigrostriatal dopaminergic neurons and deposition of α-synuclein in neurons, is often considered a neuronal disorder. However, in recent years substantial evidence has emerged to implicate glial cell types, such as astrocytes and microglia. In this study, we used stratified LD score regression and expression-weighted cell-type enrichment together with several brain-related and cell-type-specific genomic annotations to connect human genomic PD findings to specific brain cell types. We found that PD heritability attributable to common variation does not enrich in global and regional brain annotations or brain-related cell-type-specific annotations. Likewise, we found no enrichment of PD susceptibility genes in brain-related cell types. In contrast, we demonstrated a significant enrichment of PD heritability in a curated lysosomal gene set highly expressed in astrocytic, microglial, and oligodendrocyte subtypes, and in LoF-intolerant genes, which were found highly expressed in almost all tested cellular subtypes. Our results suggest that PD risk loci do not lie in specific cell types or in idual brain regions, but rather in global cellular processes detectable across several cell types.
Phenotypic and genetic factors associated with differential consent to record linkage for prescription history in the Australian Genetics of Depression Study
Publisher: Cold Spring Harbor Laboratory
Date: 26-10-2021
DOI: 10.1101/2021.10.26.21265507
Abstract: S les can be prone to ascertainment and attrition biases.The Australian Genetics of Depression Study is a large publicly recruited cohort (n=20,689) established to increase the understanding of depression and antidepressant treatment response. As part of the recruitment, participants donated a saliva s le and were given the option to consent to linkage of prescription records for research purposes. This study investigates differences between participants who donated a saliva s le or agreed to linkage of their records compared to those who did not. We observed that older, male participants with a higher education were more likely to donate a saliva s le. Self-reported bipolar disorder, ADHD, panic disorder, PTSD, substance use disorder and social anxiety disorder were associated with lower odds of donating a saliva s le whereas anorexia was associated with higher odds of donation. Male and younger participants showed higher odds of agreeing to record linkage. Participants with higher neuroticism scores and those with a history of bipolar disorder were also more likely to agree to record linkage whereas participants with a diagnosis of anorexia were less likely to agree. Increased likelihood of consent was also associated with increased genetic susceptibility to anorexia and reduced genetic risk for depression, and schizophrenia whereas there was no significant genetic effect for neuroticism. Overall, our results show moderate differences among these subs les. Most current epidemiological studies do not adjust, nor search, for attrition biases at the genetic level. The possibility to do so is a strength of s les such as the AGDS. Our results suggest that analyses can be made more robust by identifying attrition biases both on the phenotypic and genetic level, and either contextualising them as a potential limitation or performing sensitivity analyses adjusting for them.
Bayesian reassessment of the epigenetic architecture of complex traits
Publisher: Springer Science and Business Media LLC
Date: 08-06-2020
DOI: 10.1038/S41467-020-16520-1
Abstract: Linking epigenetic marks to clinical outcomes improves insight into molecular processes, disease prediction, and therapeutic target identification. Here, a statistical approach is presented to infer the epigenetic architecture of complex disease, determine the variation captured by epigenetic effects, and estimate phenotype-epigenetic probe associations jointly. Implicitly adjusting for probe correlations, data structure (cell-count or relatedness), and single-nucleotide polymorphism (SNP) marker effects, improves association estimates and in 9,448 in iduals, 75.7% (95% CI 71.70–79.3) of body mass index (BMI) variation and 45.6% (95% CI 37.3–51.9) of cigarette consumption variation was captured by whole blood methylation array data. Pathway-linked probes of blood cholesterol, lipid transport and sterol metabolism for BMI, and xenobiotic stimuli response for smoking, showed .5 times larger associations with % posterior inclusion probability. Prediction accuracy improved by 28.7% for BMI and 10.2% for smoking over a LASSO model, with age-, and tissue-specificity, implying associations are a phenotypic consequence rather than causal.
Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns
Publisher: Springer Science and Business Media LLC
Date: 11-06-2019
DOI: 10.1038/S41467-019-10461-0
Abstract: Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike’s information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk.
Conditional GWAS analysis to identify disorder-specific SNPs for psychiatric disorders
Publisher: Springer Science and Business Media LLC
Date: 12-05-2020
A methylome-wide association study of major depression with out-of-sample case-control classification and trans-ancestry comparison
Publisher: Cold Spring Harbor Laboratory
Date: 28-10-2023
New data and an old puzzle: the negative association between schizophrenia and rheumatoid arthritis
Publisher: Oxford University Press (OUP)
Date: 18-08-2015
DOI: 10.1093/IJE/DYV136
The genetic interpretation of area under the ROC curve in genomic profiling.
Publisher: Public Library of Science (PLoS)
Date: 26-02-2010
Timing of antidepressant discontinuation during pregnancy and postpartum psychiatric outcomes in Denmark and Norway
Publisher: American Medical Association (AMA)
Date: 05-2023
DOI: 10.1001/JAMAPSYCHIATRY.2023.0041
Abstract: Approximately one-half of women treated for affective disorders discontinue antidepressant use during pregnancy, yet this discontinuation could lead to relapse post partum. To investigate the associations between longitudinal antidepressant fill trajectories during pregnancy and postpartum psychiatric outcomes. This cohort study used nationwide registers in Denmark and Norway. The s le included 41 475 live-born singleton pregnancies in Denmark (1997-2016) and 16 459 in Norway (2009-2018) for women who filled at least 1 antidepressant prescription within 6 months before pregnancy. Antidepressant prescription fills were obtained from the prescription registers. Antidepressant treatment during pregnancy was modeled using the k-means longitudinal method. Initiation of psycholeptics, psychiatric emergencies, or records of self-harm within 1 year post partum. Between April 1 and October 30, 2022, hazard ratios (HRs) for each psychiatric outcome were estimated using Cox proportional hazards regression models. Inverse probability of treatment weighting was used to control for confounding. Country-specific HRs were pooled using random-effects meta-analytic models. Among 57 934 pregnancies (mean [SD] maternal age, 30.7 [5.3] years in Denmark and 29.9 [5.5] years in Norway), 4 antidepressant fill trajectories were identified: early discontinuers (31.3% and 30.4% of the included pregnancies in Denmark and Norway, respectively), late discontinuers (previously stable users) (21.5% and 27.8%), late discontinuers (short-term users) (15.9% and 18.4%), and continuers (31.3% and 23.4%). Early discontinuers and late discontinuers (short-term users) had a lower probability of initiating psycholeptics and having postpartum psychiatric emergencies vs continuers. A moderately increased probability of initiation of psycholeptics was found among late discontinuers (previously stable users) vs continuers (HR, 1.13 95% CI, 1.03-1.24). This increase in late discontinuers (previously stable users) was more pronounced among women with previous affective disorders (HR, 1.28 95% CI, 1.12-1.46). No association between antidepressant fill trajectories and postpartum self-harm risk was found. Based on pooled data from Denmark and Norway, a moderately elevated probability of initiation of psycholeptics in late discontinuers (previously stable users) vs continuers was found. These findings suggest that women with severe mental illness who are currently on stable treatment may benefit from continuing antidepressant treatment and personalized treatment counseling during pregnancy.
Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder
Publisher: Springer Science and Business Media LLC
Date: 08-10-2018
DOI: 10.1038/S42003-018-0155-Y
Abstract: Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree ( n ~ 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected in iduals who married into the family, resulting in an increasing genetic risk over generations. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity increases over the generations of a family. Joint analyses of rare and common variation may be a powerful way to understand the familial genetics of psychiatric disorders.
Analysis of Gestation Length in American Simmental Cattle
Publisher: Oxford University Press (OUP)
Date: 10-1987
Abstract: Records of gestation length (71,461) for Simmental cattle were distributed with mean 284.3 d and standard deviation 5.52 d. Gestation length was found to increase with percent Simmental and was 1.9 d longer for calves born to mature dams than for those born to heifer dams. Bull calves experienced gestation lengths 1.5 d longer than heifer calves. Sire, maternal grandsire, residual and total variances were estimated to be 2.42, .58, 22.78 and 25.78 d2, respectively, by Henderson's Method III. Heritability of gestation length was calculated to be .374 from the sire variance and .09 from the maternal grandsire variance. Direct additive genetic variance was considered to be of greater importance than maternal additive genetic variance. Correlations between the evaluations of sires for gestation length and heifer calving ease, birth weight and weaning weight were .26, .26 and .13, respectively.
Analysis of shared heritability in common disorders of the brain
Publisher: American Association for the Advancement of Science (AAAS)
Date: 22-06-2018
Abstract: Consistent classification of neuropsychiatric diseases is problematic because it can lead to misunderstanding of etiology. The Brainstorm Consortium examined multiple genome-wide association studies drawn from more than 200,000 patients for 25 brain-associated disorders and 17 phenotypes. Broadly, it appears that psychiatric and neurologic disorders share relatively little common genetic risk. However, different and independent pathways can result in similar clinical manifestations (e.g., psychosis, which occurs in both schizophrenia and Alzheimer's disease). Schizophrenia correlated with many psychiatric disorders, whereas the immunopathological affliction Crohn's disease did not, and posttraumatic stress syndrome was also largely independent of underlying traits. Essentially, the earlier the onset of a disorder, the more inheritable it appeared to be. Science , this issue p. eaap8757
Prediction of individual genetic risk of complex disease
Publisher: Elsevier BV
Date: 06-2008
DOI: 10.1016/J.GDE.2008.07.006
Abstract: Most common diseases are caused by multiple genetic and environmental factors. In the last 2 years, genome-wide association studies (GWAS) have identified polymorphisms that are associated with risk to common disease, but the effect of any one risk allele is typically small. By combining information from many risk variants, will it be possible to predict accurately each in idual person's genetic risk for a disease? In this review we consider the lessons from GWAS and the implications for genetic risk prediction to common disease. We conclude that with larger GWAS s le sizes or by combining studies, accurate prediction of genetic risk will be possible, even if the causal mutations or the mechanisms by which they affect susceptibility are unknown.
Systematic review and meta-analysis of genetic risk factors for neuropathic pain
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 18-01-2018
Common SNPs explain some of the variation in the personality dimensions of neuroticism and extraversion (vol 2, e125, 2012)
Publisher: Springer Science and Business Media LLC
Date: 29-05-2012
DOI: 10.1038/TP.2012.49
A comparison of some simple methods to identify geographical areas with excess incidence of a rare disease such as childhood leukaemia
Publisher: Wiley
Date: 30-06-1999
DOI: 10.1002/(SICI)1097-0258(19990630)18:12<1501::AID-SIM135>3.0.CO;2-E
Abstract: Six statistics are compared in a simulation study for their ability to identify geographical areas with a known excess incidence of a rare disease. The statistics are the standardized incidence ratio, the empirical Bayes method of Clayton and Kaldor, Poisson probability, a statistic based on the 'Breslow T' test (BT) and two statistics based on the 'Potthoff-Whittinghill' test (PW) for extra-Poisson variance. Two alternative processes of clustering are simulated in which high-risk locations could be caused by environmental sources or could be sites of microepidemics of an infectious agent contributing to a rare disease such as childhood leukaemia. The simulation processes use two parameters (proportion of cases found in clusters and mean cluster size) which are varied to embrace a variety of situations. Real and artificial data sets of small area populations are considered. The most extreme of the artificial sets has all areas of equal population size. The other data sets use the small census areas (municipalities) in Finland since these have extremely heterogeneous population size distribution. Subset selection allows examination of this variability. Receiver operator curve methodology is used to compare the efficacy of the statistics in identifying the cluster areas statistics are compared for the proportion of true high-risk areas identified in the top 1 per cent and 10 per cent of ranked areas. One of the PW statistics performed consistently well under all circumstances, although the results for the BT statistic were marginally better when only the top 1 per cent of ranked areas was considered. The standardized incidence ratio performed consistently worst.
Genetic signatures of high-altitude adaptation in Tibetans
Publisher: Proceedings of the National Academy of Sciences
Date: 03-04-2017
Abstract: The origin of Tibetans and the mechanism of how they adapted to the high-altitude environment remain mostly unknown. We conduct the largest genome-wide study in Tibetans to date. We detect signatures of natural selection at nine gene loci, two of which are strongly associated with blood phenotypes in present day Tibetans. We further show the genetic relatedness of Tibetans with other ethnic groups in China and estimate the ergence time between Tibetans and Han. These findings provide important knowledge to understand the genetic ancestry of Tibetans and the genetic basis of high-altitude adaptation.
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