ORCID Profile
0000-0002-3947-441X
Current Organisations
Johns Hopkins School of Medicine
,
Brigham and Women's Hospital
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Publisher: Elsevier BV
Date: 02-2015
Publisher: Elsevier BV
Date: 2022
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.
Publisher: American Psychiatric Association Publishing
Date: 11-2009
Publisher: Oxford University Press (OUP)
Date: 21-06-2016
DOI: 10.1093/HMG/DDW181
Publisher: Springer Science and Business Media LLC
Date: 05-2019
Publisher: Frontiers Media SA
Date: 13-03-2019
Publisher: Springer Science and Business Media LLC
Date: 18-12-2019
DOI: 10.1038/S41467-019-13544-0
Abstract: Body composition is often altered in psychiatric disorders. Using genome-wide common genetic variation data, we calculate sex-specific genetic correlations amongst body fat %, fat mass, fat-free mass, physical activity, glycemic traits and 17 psychiatric traits (up to N = 217,568). Two patterns emerge: (1) anorexia nervosa, schizophrenia, obsessive-compulsive disorder, and education years are negatively genetically correlated with body fat % and fat-free mass, whereas (2) attention-deficit/hyperactivity disorder (ADHD), alcohol dependence, insomnia, and heavy smoking are positively correlated. Anorexia nervosa shows a stronger genetic correlation with body fat % in females, whereas education years is more strongly correlated with fat mass in males. Education years and ADHD show genetic overlap with childhood obesity. Mendelian randomization identifies schizophrenia, anorexia nervosa, and higher education as causal for decreased fat mass, with higher body fat % possibly being a causal risk factor for ADHD and heavy smoking. These results suggest new possibilities for targeted preventive strategies.
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.
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.
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.
Publisher: Public Library of Science (PLoS)
Date: 25-01-2016
Publisher: Elsevier BV
Date: 07-2015
Publisher: Elsevier BV
Date: 07-2020
Publisher: American Psychiatric Association Publishing
Date: 08-2019
Publisher: American Medical Association (AMA)
Date: 05-2019
Publisher: Elsevier BV
Date: 06-2018
Publisher: Cambridge University Press (CUP)
Date: 17-09-2018
DOI: 10.1017/S0033291718002039
Abstract: Most studies underline the contribution of heritable factors for psychiatric disorders. However, heritability estimates depend on the population under study, diagnostic instruments, and study designs that each has its inherent assumptions, strengths, and biases. We aim to test the homogeneity in heritability estimates between two powerful, and state of the art study designs for eight psychiatric disorders. We assessed heritability based on data of Swedish siblings ( N = 4 408 646 full and maternal half-siblings), and based on summary data of eight s les with measured genotypes ( N = 125 533 cases and 208 215 controls). All data were based on standard diagnostic criteria. Eight psychiatric disorders were studied: (1) alcohol dependence (AD), (2) anorexia nervosa, (3) attention deficit/hyperactivity disorder (ADHD), (4) autism spectrum disorder, (5) bipolar disorder, (6) major depressive disorder, (7) obsessive-compulsive disorder (OCD), and (8) schizophrenia. Heritability estimates from sibling data varied from 0.30 for Major Depression to 0.80 for ADHD. The estimates based on the measured genotypes were lower, ranging from 0.10 for AD to 0.28 for OCD, but were significant, and correlated positively (0.19) with national sibling-based estimates. When removing OCD from the data the correlation increased to 0.50. Given the unique character of each study design, the convergent findings for these eight psychiatric conditions suggest that heritability estimates are robust across different methods. The findings also highlight large differences in genetic and environmental influences between psychiatric disorders, providing future directions for etiological psychiatric research.
Publisher: Springer Science and Business Media LLC
Date: 28-01-2014
DOI: 10.1038/MP.2013.195
Publisher: Wiley
Date: 16-07-2015
DOI: 10.1002/AJMG.B.32344
Publisher: Springer Science and Business Media LLC
Date: 11-08-2202
DOI: 10.1038/NG.2711
No related grants have been discovered for Pamela Mahon.