ORCID Profile
0000-0002-7940-0335
Current Organisation
University of Adelaide
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
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.
Ageing and Older People | Expanding Knowledge in the Medical and Health Sciences |
Publisher: Elsevier BV
Date: 11-2017
Publisher: Elsevier BV
Date: 09-2017
Publisher: Elsevier BV
Date: 09-2018
Publisher: Elsevier BV
Date: 05-2017
Publisher: Elsevier BV
Date: 04-2019
Publisher: Elsevier BV
Date: 09-2014
Publisher: Elsevier BV
Date: 10-2017
Publisher: Elsevier BV
Date: 11-2018
Publisher: Elsevier BV
Date: 2015
Publisher: SAGE Publications
Date: 11-01-2018
Abstract: Timely and accurate assessments of disease burden are essential for developing effective national health policies. We used the Global Burden of Disease Study 2015 to examine burden due to mental and substance use disorders in Australia. For each of the 20 mental and substance use disorders included in Global Burden of Disease Study 2015, systematic reviews of epidemiological data were conducted, and data modelled using a Bayesian meta-regression tool to produce prevalence estimates by age, sex, geography and year. Prevalence for each disorder was then combined with a disorder-specific disability weight to give years lived with disability, as a measure of non-fatal burden. Fatal burden was measured as years of life lost due to premature mortality which were calculated by combining the number of deaths due to a disorder with the life expectancy remaining at the time of death. Disability-adjusted life years were calculated by summing years lived with disability and years of life lost to give a measure of total burden. Uncertainty was calculated around all burden estimates. Mental and substance use disorders were the leading cause of non-fatal burden in Australia in 2015, explaining 24.3% of total years lived with disability, and were the second leading cause of total burden, accounting for 14.6% of total disability-adjusted life years. There was no significant change in the age-standardised disability-adjusted life year rates for mental and substance use disorders from 1990 to 2015. Global Burden of Disease Study 2015 found that mental and substance use disorders were leading contributors to disease burden in Australia. Despite several decades of national reform, the burden of mental and substance use disorders remained largely unchanged between 1990 and 2015. To reduce this burden, effective population-level preventions strategies are required in addition to effective interventions of sufficient duration and coverage.
Publisher: Wiley
Date: 23-09-2019
DOI: 10.1111/BDI.12829
Abstract: The Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale) is the most widely used clinical measure of lithium response phenotypes. We assess its performance against recommended psychometric and clinimetric standards. We used data from the Consortium for Lithium Genetics and a French study of lithium response phenotypes (combined s le >2500) to assess reproducibility, responsiveness, validity, and interpretability of the A scale (assessing change in illness activity), the B scale, and its items (assessing confounders of response) and the previously established response categories derived from the Total Score for the Alda scale. The key findings are that the B scale is vulnerable to error measurement. For ex le, some items contribute little to overall performance of the Alda scale (eg, B2) and that the B scale does not reliably assess a single construct (uncertainty in response). Machine learning models indicate that it may be more useful to employ an algorithm for combining the ratings of in idual B items in a sequence that clarifies the noise to signal ratio instead of using a composite score. This study highlights three important topics. First, empirical approaches can help determine which aspects of the performance of any scale can be improved. Second, the B scale of the Alda is best applied as a multidimensional index (identifying several independent confounders of the assessment of response). Third, an integrated science approach to precision psychiatry is vital, otherwise phenotypic misclassifications will undermine the reliability and validity of findings from genetics and biomarker studies.
Publisher: Wiley
Date: 23-01-2020
DOI: 10.1111/AJAG.12760
Publisher: Elsevier BV
Date: 2017
Publisher: Springer Science and Business Media LLC
Date: 04-07-2017
Publisher: Springer Science and Business Media LLC
Date: 09-2017
DOI: 10.1007/S13167-017-0112-8
Abstract: Personalized medicine (personalized psychiatry in a specific setting) is a new model towards in idualized care, in which knowledge from genomics and other omic pillars (microbiome, epigenomes, proteome, and metabolome) will be combined with clinical data to guide efforts to new drug development and targeted prescription of the existing treatment options. In this review, we summarize pharmacogenomic studies in mood disorders that may lay the foundation towards personalized psychiatry. In addition, we have discussed the possible strategies to integrate data from omic pillars as a future path to personalized psychiatry. So far, the progress of uncovering single nucleotide polymorphisms (SNPs) underpinning treatment efficacy in mood disorders (e.g., SNPs associated with selective serotonin re-uptake inhibitors or lithium treatment response in patients with bipolar disorder and major depressive disorder) are encouraging, but not adequate. Genetic studies have pointed to a number of SNPs located at candidate genes that possibly influence response to (a) antidepressants COMT , HTR2A , HTR1A , CNR1 , SLC6A4, NPY , MAOA , IL1B , GRIK4 , BDNF , GNB3 , FKBP5 , CYP2D6 , CYP2C19 , and ABCB1 and (b) mood stabilizers (lithium) 5 - HTT , TPH , DRD1 , FYN , INPP1 , CREB1 , BDNF , GSK3β , ARNTL , TIM , DPB , NR3C1 , BCR , XBP1 , and CACNG2 . We suggest three alternative and complementary strategies to implement knowledge gained from pharmacogenomic studies. The first strategy can be to implement diagnostic, therapeutic, or prognostic genetic testing based on candidate genes or gene products. The second alternative is an integrative analysis (systems genomics approach) to combine omics data obtained from the different pillars of omics investigation, including genomics, epigenomes, proteomics, metabolomics and microbiomes. The main goal of system genomics is an identification and understanding of biological pathways, networks, and modules underlying drug-response. The third strategy aims to the development of multivariable diagnostic or prognostic algorithms (tools) combining in idual’s genomic information (polygenic score) with other predictors (e.g., omics pillars, neuroimaging, and clinical characteristics) to finally predict therapeutic outcomes. An integration of molecular science with that of traditional clinical practice is the way forward to drug discoveries and novel therapeutic approaches and to characterize psychiatric disorders leading to a better predictive, preventive, and personalized medicine (PPPM) in psychiatry. With future advances in the omics technology and methodological developments for data integration, the goal of PPPM in psychiatry is promising.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 2017
Publisher: Oxford University Press (OUP)
Date: 02-07-2021
Abstract: (i) to describe the general practitioner utilisation of health assessments, management plans, coordination of team care arrangements and medication review item numbers within 6 months of an aged care eligibility assessment for home care packages (HCP) and (ii) investigate the impact of health assessments on the risk of mortality and entry into permanent residential aged care (PRAC) of in iduals accessing HCP. retrospective cohort study utilising data from the Registry of Senior Australians (ROSA) was conducted. 75,172 in iduals aged ≥75 years who received HCP between 2011 and 2015. for objective 1: the use of comprehensive assessments (Medicare Benefits Schedule (MBS) items 705 or 707), management plans (MBS 721), coordination of team care arrangements (MBS 723), and medication reviews (MBS 900). For objective 2: time to death and entry into PRAC. of the 75,172 in iduals, 28.2% (95% confidence interval (CI): 27.8–8.5%) had comprehensive assessments, 36.7% (95% CI: 36.3–37.0%) had management plans, 33.0% (95% CI: 32.7–33.3%) received coordination of team care arrangements and 5.4% (95% CI: 5.2–5.5%) had medication reviews. In iduals with a comprehensive assessment had a 5% lower risk of mortality (adjusted hazard ratio (aHR), 95% CI = 0.95, 0.92–0.98) but 5% higher risk of transition to PRAC (adjusted subdistribution HRs, 95% CI = 1.05, 1.02–1.08) compared to those who did not have these services. the utilisation of health assessments was associated with a lower risk of mortality. There is an opportunity for increased use of item numbers in frailer in iduals.
Publisher: Elsevier BV
Date: 2020
Publisher: Springer Science and Business Media LLC
Date: 29-11-2021
DOI: 10.1038/S41398-021-01702-2
Abstract: Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between in iduals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium’s therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi + Gen www.ConLiGen.org ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.
Publisher: Cold Spring Harbor Laboratory
Date: 22-10-2018
DOI: 10.1101/449363
Abstract: Lithium is a first-line medication for bipolar disorder (BD), but only ~30% of patients respond optimally to the drug. Since genetic factors are known to mediate lithium treatment response, we hypothesized whether polygenic susceptibility to the spectrum of depression traits is associated with treatment outcomes in patients with BD. In addition, we explored the potential molecular underpinnings of this relationship. Weighted polygenic scores (PGSs) were computed for major depressive disorder (MDD) and depressive symptoms (DS) in BD patients from the Consortium on Lithium Genetics (ConLi + Gen n=2,586) who received lithium treatment. Lithium treatment outcome was assessed using the ALDA scale. Summary statistics from genome-wide association studies (GWAS) in MDD (130,664 cases and 330,470 controls) and DS (n=161,460) were used for PGS weighting. Associations between PGSs of depression traits and lithium treatment response were assessed by binary logistic regression. We also performed a cross-trait meta-GWAS, followed by Ingenuity ® Pathway Analysis. BD patients with a low polygenic load for depressive traits were more likely to respond well to lithium, compared to patients with high polygenic load (MDD: OR =1.64 [95%CI: 1.26-2.15], lowest vs highest PGS quartiles DS: OR=1.53 [95%CI: 1.18-2.00]). Associations were significant for type 1, but not type 2 BD. Cross-trait GWAS and functional characterization implicated voltage-gated potassium channels, insulin-related pathways, mitogen-activated protein-kinase (MAPK) signaling, and miRNA expression. Genetic loading to depression traits in BD patients lower their odds of responding optimally to lithium. Our findings support the emerging concept of a lithium-responsive biotype in BD. See attached details
Publisher: Springer Science and Business Media LLC
Date: 09-01-2019
Publisher: Research Square Platform LLC
Date: 03-10-2023
Publisher: Elsevier BV
Date: 11-2018
Publisher: Springer Science and Business Media LLC
Date: 24-01-2017
DOI: 10.1038/TP.2016.261
Abstract: Meta-analyses of genome-wide association studies (meta-GWASs) and candidate gene studies have identified genetic variants associated with cardiovascular diseases, metabolic diseases and mood disorders. Although previous efforts were successful for in idual disease conditions (single disease), limited information exists on shared genetic risk between these disorders. This article presents a detailed review and analysis of cardiometabolic diseases risk (CMD-R) genes that are also associated with mood disorders. First, we reviewed meta-GWASs published until January 2016, for the diseases ‘type 2 diabetes, coronary artery disease, hypertension’ and/or for the risk factors ‘blood pressure, obesity, plasma lipid levels, insulin and glucose related traits’. We then searched the literature for published associations of these CMD-R genes with mood disorders. We considered studies that reported a significant association of at least one of the CMD-R genes and ‘depression’ or ‘depressive disorder’ or ‘depressive symptoms’ or ‘bipolar disorder’ or ‘lithium treatment response in bipolar disorder’, or ‘serotonin reuptake inhibitors treatment response in major depression’. Our review revealed 24 potential pleiotropic genes that are likely to be shared between mood disorders and CMD-Rs. These genes include MTHFR , CACNA1D , CACNB2 , GNAS , ADRB1 , NCAN , REST , FTO , POMC , BDNF , CREB , ITIH4 , LEP , GSK3B , SLC18A1 , TLR4 , PPP1R1B , APOE , CRY2 , HTR1A , ADRA2A , TCF7L2 , MTNR1B and IGF1 . A pathway analysis of these genes revealed significant pathways: corticotrophin-releasing hormone signaling , AMPK signaling , cAMP-mediated or G-protein coupled receptor signaling , axonal guidance signaling , serotonin or dopamine receptors signaling , d opamine-DARPP32 feedback in cAMP signaling , circadian rhythm signaling and leptin signaling . Our review provides insights into the shared biological mechanisms of mood disorders and cardiometabolic diseases.
Publisher: American Medical Association (AMA)
Date: 04-2017
Publisher: Royal College of Psychiatrists
Date: 28-02-2022
DOI: 10.1192/BJP.2022.28
Abstract: Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment. To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder. This study utilised genetic and clinical data ( n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi + Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework. The best performing linear model explained 5.1% ( P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% ( P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% ( P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data. Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
Publisher: Elsevier BV
Date: 09-2014
Publisher: AMPCo
Date: 09-08-2020
DOI: 10.5694/MJA2.50720
Publisher: Research Square Platform LLC
Date: 14-02-2023
DOI: 10.21203/RS.3.RS-2580252/V1
Abstract: Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2,367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response — defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P ����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������
Publisher: Springer Science and Business Media LLC
Date: 05-09-2018
DOI: 10.1038/S41380-018-0236-9
Abstract: Neuroticism has been shown to act as an important risk factor for major depressive disorder (MDD). Genetic and neuroimaging research has independently revealed biological correlates of neurotic personality including cortical alterations in brain regions of high relevance for affective disorders. Here we investigated the influence of a polygenic score for neuroticism (PGS) on cortical brain structure in a joint discovery s le of n = 746 healthy controls (HC) and n = 268 MDD patients. Findings were validated in an independent replication s le (n = 341 HC and n = 263 MDD). Subgroup analyses stratified for case-control status and analyses of associations between neurotic phenotype and cortical measures were carried out. PGS for neuroticism was significantly associated with a decreased cortical surface area of the inferior parietal cortex, the precuneus, the rostral cingulate cortex and the inferior frontal gyrus in the discovery s le. Similar associations between PGS and surface area of the inferior parietal cortex and the precuneus were demonstrated in the replication s le. Subgroup analyses revealed negative associations in the latter regions between PGS and surface area in both HC and MDD subjects. Neurotic phenotype was negatively correlated with surface area in similar cortical regions including the inferior parietal cortex and the precuneus. No significant associations between PGS and cortical thickness were detected. The morphometric overlap of associations between both PGS and neurotic phenotype in similar cortical regions closely related to internally focused cognition points to the potential relevance of genetically shaped cortical alterations in the development of neuroticism.
Publisher: Springer Science and Business Media LLC
Date: 09-04-2009
Publisher: Elsevier BV
Date: 09-2017
Publisher: Elsevier BV
Date: 09-1992
Publisher: Elsevier BV
Date: 09-2014
Publisher: Springer Science and Business Media LLC
Date: 21-07-2017
Publisher: American Medical Association (AMA)
Date: 09-11-2017
Publisher: Research Square Platform LLC
Date: 26-06-2023
DOI: 10.21203/RS.3.RS-3068352/V1
Abstract: The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we investigated the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4,925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi + Gen, N = 2,374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. We found several genes associated with Li response at p 1x10 − 4 values, including HAS3 , CNTNAP5 and NFIB . Network and functional enrichment analyses uncovered an overrepresentation of pathways involved in cell adhesion and intercellular communication, which appear to converge on the well-known Li-induced inhibition of GSK-3β. We also found various genes associated with BP’s age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation at the exploratory threshold. These included RTN4 , XKR4 , NRXN1 , NRG1/3 and GRK5 . Additionally, PGS analyses suggested serum FAS, ECP, TRANCE and cytokine ligands, amongst others, might represent potential circulating biomarkers of Li response and clinical presentation. Taken together, our results support the notion of a relatively weak association between immunity and clinically relevant features of BP at the genetic level.
Publisher: American Medical Association (AMA)
Date: 03-2016
Publisher: Springer Science and Business Media LLC
Date: 02-08-2017
DOI: 10.1038/NCOMMS16140
Abstract: Nature Communications 8: Article number: 15805 (2017) Published: 14 June 2017 Updated: 2 August 2017 In Supplementary Fig. 10 of this Article, images for panels a and b were inadvertently omitted. The correct version of Supplementary Fig. 10 is provided as Supplementary Information associated withthis Erratum.
Publisher: Elsevier BV
Date: 11-2018
Publisher: Cold Spring Harbor Laboratory
Date: 11-11-2017
DOI: 10.1101/209270
Abstract: Lithium is a first-line mood stabilizer for the maintenance treatment of Bipolar Disorder (BPD). However, the efficacy of lithium varies widely, with a non-response rate of up to 30%. Biological response markers and predictors are lacking. Genetic factors are thought to mediate lithium treatment response, and the previously reported genetic overlap between BPD and schizophrenia (SCZ) led us to test whether a polygenic score (PGS) for SCZ could predict lithium treatment response in BPD. Further, we explored the potential molecular underpinnings of this association. Weighted SCZ PGSs were computed at ten p-value thresholds (P T ) using summary statistics from a genome-wide association study (GWAS) of 36,989 SCZ cases, and genotype data for BPD patients from the Consortium on Lithium Genetics (ConLi + Gen). For functional exploration, we performed a cross-trait meta-GWAS and pathway analysis, combining GWAS summary statistics on SCZ and lithium treatment response. International multicenter GWAS. Patients with BPD who had undergone lithium treatment were genotyped and retrospectively assessed for long-term treatment response (n=2,586). Clinical treatment response to lithium was defined on both the categorical and continuous scales using the ALDA score. The effect measures include odds ratios (ORs) and the proportion of variance explained (R 2 ), and a significant association was determined at p .05. The PGS for SCZ was inversely associated with lithium treatment response in the categorical outcome (p=8×10 −5 ), at P T ×10 −2 . Patients with BPD who had low polygenic load for SCZ responded better to lithium, with ORs for lithium response ranging from 3.46 [95%CI: 1.42-8.41 at 1 st decile] to 2.03 [95%CI: 0.86-4.81 at the 9th decile], compared to the patients in the 10 th decile of SCZ risk. In the cross-trait meta-GWAS, 15 genetic loci that may have overlapping effects on lithium treatment response and susceptibility to SCZ were identified. Functional pathway and network analysis of these loci point to the HLA complex and inflammatory cytokines (TNFα, IL-4, IFNγ) as molecular contributors to lithium treatment response in BPD. The study provides, for the first-time, evidence for a negative association between high genetic loading for SCZ and poor response to lithium in patients with BPD. These results suggest the potential for translational research aimed at personalized prescribing of lithium. Does a polygenic score for Schizophrenia (SCZ) predict response to lithium in patients with Bipolar Disorder (BPD)? What are the molecular drivers of the association between SCZ and lithium treatment response? We found an inverse association between genetic loading for SCZ risk variants and response to lithium in patients with BPD. Genetic variants in the HLA region on chromosome 6, the antigen presentation pathway and markers of inflammation (TNFα, IL-4, IFNγ) point to molecular underpinnings of lithium treatment response in BPD. In patients with BPD, an assessment of a polygenic load for SCZ risk variants may assist in conjunction with clinical data to predict whether they would respond to lithium treatment.
Publisher: American Medical Association (AMA)
Date: 07-2015
Publisher: Springer Science and Business Media LLC
Date: 20-04-2020
DOI: 10.1038/S41591-020-0807-6
Abstract: A double burden of malnutrition occurs when in iduals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of % in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic.
Publisher: Springer Science and Business Media LLC
Date: 14-06-2017
DOI: 10.1038/NCOMMS15805
Abstract: Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 in iduals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755 ), expression quantitative trait loci (eQTLs) (influencing GNG11 , RGS6 and NEO1 ), or are located in genes preferentially expressed in the sinoatrial node ( GNG11 , RGS6 and HCN4) . Genetic risk scores account for 0.9 to 2.6% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (−0.74 r g −0.55) and blood pressure (−0.35 r g −0.20). These findings provide clinically relevant biological insight into heritable variation in vagal heart rhythm regulation, with a key role for genetic variants ( GNG11 , RGS6) that influence G-protein heterotrimer action in GIRK-channel induced pacemaker membrane hyperpolarization.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 04-2018
DOI: 10.1097/PSY.0000000000000555
Abstract: Shared genetic background may explain phenotypic associations between depression and Type 2 diabetes (T2D). We aimed to study, on a genome-wide level, if genetic correlation and pleiotropic loci exist between depressive symptoms and T2D or glycemic traits. We estimated single-nucleotide polymorphism (SNP)–based heritability and analyzed genetic correlation between depressive symptoms and T2D and glycemic traits with the linkage disequilibrium score regression by combining summary statistics of previously conducted meta-analyses for depressive symptoms by CHARGE consortium ( N = 51,258), T2D by DIAGRAM consortium ( N = 34,840 patients and 114,981 controls), fasting glucose, fasting insulin, and homeostatic model assessment of β-cell function and insulin resistance by MAGIC consortium ( N = 58,074). Finally, we investigated pleiotropic loci using a bivariate genome-wide association study approach with summary statistics from genome-wide association study meta-analyses and reported loci with genome-wide significant bivariate association p value ( p 5 × 10 −8 ). Biological annotation and function of significant pleiotropic SNPs were assessed in several databases. The SNP-based heritability ranged from 0.04 to 0.10 in each in idual trait. In the linkage disequilibrium score regression analyses, depressive symptoms showed no significant genetic correlation with T2D or glycemic traits ( p 0.37). However, we identified pleiotropic genetic variations for depressive symptoms and T2D (in the IGF2BP2 , CDKAL1 , CDKN2B-AS , and PLEKHA1 genes), and fasting glucose (in the MADD , CDKN2B-AS , PEX16 , and MTNR1B genes). We found no significant overall genetic correlations between depressive symptoms, T2D, or glycemic traits suggesting major differences in underlying biology of these traits. However, several potential pleiotropic loci were identified between depressive symptoms, T2D, and fasting glucose, suggesting that previously established phenotypic associations may be partly explained by genetic variation in these specific loci.
Publisher: Elsevier BV
Date: 2017
Publisher: Springer Science and Business Media LLC
Date: 24-05-2018
Publisher: Elsevier BV
Date: 03-2022
Publisher: Springer Science and Business Media LLC
Date: 14-11-2016
Publisher: Springer Science and Business Media LLC
Date: 25-04-2018
Publisher: Springer Science and Business Media LLC
Date: 08-07-2019
Publisher: Elsevier BV
Date: 06-2020
Publisher: S. Karger AG
Date: 2021
DOI: 10.1159/000519707
Abstract: Response to lithium varies widely between in iduals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients ( i N /i = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using i lassosum /i and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = −0.14 95% confidence interval [CI]: −0.24 to −0.03 i /i value = 0.010) and MDD (β = −0.16 95% CI: −0.27 to −0.04 i /i value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61 95% CI: 1.34–1.93 i /i value = 2e−7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD.
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
Publisher: Springer Science and Business Media LLC
Date: 2019
DOI: 10.1007/S00702-018-01966-X
Abstract: Selective serotonin reuptake inhibitors (SSRIs) are first-line antidepressants for the treatment of major depressive disorder (MDD). However, treatment response during an initial therapeutic trial is often poor and is difficult to predict. Heterogeneity of response to SSRIs in depressed patients is partly driven by co-occurring somatic disorders such as coronary artery disease (CAD) and obesity. CAD and obesity may also be associated with metabolic side effects of SSRIs. In this study, we assessed the association of CAD and obesity with treatment response to SSRIs in patients with MDD using a polygenic score (PGS) approach. Additionally, we performed cross-trait meta-analyses to pinpoint genetic variants underpinnings the relationship of CAD and obesity with SSRIs treatment response. First, PGSs were calculated at different p value thresholds (P
Publisher: Springer Science and Business Media LLC
Date: 11-07-2022
Publisher: Springer International Publishing
Date: 2016
Publisher: SAGE Publications
Date: 03-08-2020
Abstract: Mental health disorders are a major health concern in older people and are associated with a higher risk of disability, frailty and early mortality. This study aimed to conduct a contemporary population-based assessment of the prevalence, trends and factors associated with mental health disorders in in iduals who are living in permanent residential aged care (PRAC) in Australia. A retrospective cross-sectional study was conducted using national data from the Registry of Senior Australians, a national cohort of older Australians who had aged care eligibility assessment and entered PRAC between 2008 and 2016. Stepwise multivariate logistic regression modeling was applied to identify factors associated with mental health disorders. Of 430,862 in iduals included in this study, 57.8% had at least one mental health disorder. The prevalence of depression, phobia/anxiety and psychosis were as follows: 46.2% (95% confidence interval = [46.0%, 46.3%]), 14.9% (95% confidence interval = [14.8%, 15.0%]) and 9.7% (95% confidence interval = [9.6%, 9.8%]), respectively. The likelihood of having a mental health disorder was higher for those who were (adjusted odds ratio [95% confidence interval]) relatively younger, specifically for every 10-year increment in age, the odds of having mental health disorders was 44.0% lower (0.56, [0.55, 0.56]) female (1.33 [1.32, 1.35]) having increasing numbers of physical health comorbidities, 6–10 (1.26 [1.24, 1.29]) or 11–15 (1.48 [1.45, 1.51]) or more than 15 (1.64 [1.58, 1.71]) compared to people having less than five comorbidities having limitations related to health care tasks (1.05 [1.04, 1.07]), meals (1.04 [1.02, 1.05]) or social and community participation (1.10 [1.08, 1.12]). The burden of mental health disorders in older Australians living in PRAC was high and in iduals with these conditions tend to be younger, with several physical comorbidities and/or functional limitations. Understanding the profile of in iduals with mental health disorders at entry into PRAC can be used as evidence for baseline resource allocation for this population and evaluation of future needs of mental health services.
Publisher: Springer Science and Business Media LLC
Date: 11-03-2019
DOI: 10.1038/S41598-019-40834-W
Abstract: Before implementing therapeutic genomic interventions for optimizing health in early life, comprehensive understanding of their effect on several traits across the life course is warranted. Abnorml birthweight is associated with cardiometabolic disease risk in adulthood however, the extent of genetic pleiotropy in the association has not been comprehensively investigated. We tested for pleiotropy and enrichment of functional loci between birthweight and 15 cardiometabolic disease traits (CMD). We found significantly abundant genetic pleiotropy ( P 3.3 × 10 −3 ) and enrichment of functional annotations ( P 3.3 × 10 −3 ) in loci influencing both birthweight and CMD. We did not observe consistent effect directions of pleiotropic loci on the traits. A total of 67 genetic loci, of which 65 loci have been reported in previous genome-wide association studies, were associated with both birthweight and CMD at a false discovery rate of 5%. Two novel loci were associated with birthweight and adult coronary artery disease (rs2870463 in CTRB1 ) and with birthweight and adult waist circumference (rs12704673 in CALCR ). Both loci are known to have regulatory effects on expression of nearby genes. In all, our findings revealed pervasive genetic pleiotropy in early growth and adulthood cardiometabolic diseases, implying the need for caution when considering genetic loci as therapeutic targets.
Publisher: Elsevier BV
Date: 10-2016
Publisher: Springer Science and Business Media LLC
Date: 02-02-2017
Publisher: Springer Science and Business Media LLC
Date: 05-09-2018
DOI: 10.1038/S41398-018-0237-0
Abstract: Lithium is the first-line treatment for bipolar affective disorder (BPAD) but two-thirds of patients respond only partially or not at all. The reasons for this high variability in lithium response are not well understood. Transcriptome-wide profiling, which tests the interface between genes and the environment, represents a viable means of exploring the molecular mechanisms underlying lithium response variability. Thus, in the present study we performed co-expression network analyses of whole-blood-derived RNA-seq data from n = 50 lithium-treated BPAD patients. Lithium response was assessed using the well-validated ALDA scale, which we used to define both a continuous and a dichotomous measure. We identified a nominally significant correlation between a co-expression module comprising 46 genes and lithium response represented as a continuous (i.e., scale ranging 0–10) phenotype (cor = −0.299, p = 0.035). Forty-three of these 46 genes had reduced mRNA expression levels in better lithium responders relative to poorer responders, and the central regulators of this module were all mitochondrially-encoded ( MT-ND1 , MT-ATP6 , MT-CYB ). Accordingly, enrichment analyses indicated that genes involved in mitochondrial functioning were heavily over-represented in this module, specifically highlighting the electron transport chain (ETC) and oxidative phosphorylation (OXPHOS) as affected processes. Disrupted ETC and OXPHOS activity have previously been implicated in the pathophysiology of BPAD. Our data adds to previous evidence suggesting that a normalisation of these processes could be central to lithium’s mode of action, and could underlie a favourable therapeutic response.
Publisher: Springer Science and Business Media LLC
Date: 21-07-2017
Publisher: Massachusetts Medical Society
Date: 06-07-2017
Publisher: Springer Science and Business Media LLC
Date: 11-07-2023
DOI: 10.1038/S41380-023-02149-1
Abstract: Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li + PGS ) in patients with BD. To gain further insights into lithium’s possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li + PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi + Gen: N = 2367) and replicated in the combined PsyCourse ( N = 89) and BipoLife ( N = 102) studies. The associations of Li + PGS and lithium treatment response — defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P 0.05. Li + PGS was positively associated with lithium treatment response in the ConLi + Gen cohort, in both the categorical ( P = 9.8 × 10 − 12 , R 2 = 1.9%) and continuous ( P = 6.4 × 10 − 9 , R 2 = 2.6%) outcomes. Compared to bipolar patients in the 1 st decile of the risk distribution, in iduals in the 10 th decile had 3.47-fold (95%CI: 2.22–5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome ( P = 3.9 × 10 − 4 , R 2 = 0.9%), but not for the continuous outcome ( P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li + PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.
Publisher: Springer Science and Business Media LLC
Date: 02-07-2020
DOI: 10.1038/S41591-020-0972-7
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Publisher: Frontiers Media SA
Date: 06-03-2018
Location: Australia
Start Date: 2022
End Date: 02-2022
Amount: $365,000.00
Funder: Australian Research Council
View Funded Activity