Biology subjects

Adams, M. J.

Publications and source records attributed to Adams, M. J..

11 recordsLinked to original sources

bioRxiv2018

Genome-wide meta-analysis of depression in 807,553 individuals identifies 102 independent variants with replication in a further 1,507,153 individuals

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 sample sizes due to the polygenic nature of the disorder. To maximise sample size, we meta-analysed data on 807,553 individuals (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 sample of 1,306,354 individuals (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.

genetics↗

bioRxiv2018

Association of whole-genome and NETRIN1 signaling pathway-derived polygenic risk scores for Major Depressive Disorder and thalamic radiation white matter microstructure in UK Biobank

BackgroundMajor Depressive Disorder (MDD) is a clinically heterogeneous psychiatric disorder with a polygenic architecture. Genome-wide association studies have identified a number of risk-associated variants across the genome, and growing evidence of NETRIN1 pathway involvement. Stratifying disease risk by genetic variation within the NETRIN1 pathway may provide an important route for identification of disease mechanisms by focusing on a specific process excluding heterogeneous risk-associated variation in other pathways. Here, we sought to investigate whether MDD polygenic risk scores derived from the NETRIN1 signaling pathway (NETRIN1-PRS) and the whole genome excluding NETRIN1 pathway genes (genomic-PRS) were associated with white matter integrity.\n\nMethodsWe used two diffusion tensor imaging measures, fractional anisotropy (FA) and mean diffusivity (MD), in the most up-to-date UK Biobank neuroimaging data release (FA: N = 6,401; MD: N = 6,390).\n\nResultsWe found significantly lower FA in the superior longitudinal fasciculus ({beta} = -0.035, pcorrected = 0.029) and significantly higher MD in a global measure of thalamic radiations ({beta} = 0.029, pcorrected = 0.021), as well as higher MD in the superior ({beta} = 0.034, pcorrected = 0.039) and inferior ({beta} = 0.029, pcorrected = 0.043) longitudinal fasciculus and in the anterior ({beta} = 0.025, pcorrected = 0.046) and superior ({beta} = 0.027, pcorrected = 0.043) thalamic radiation associated with NETRIN1-PRS. Genomic-PRS was also associated with lower FA and higher MD in several tracts.\n\nConclusionsOur findings indicate that variation in the NETRIN1 signaling pathway may confer risk for MDD through effects on thalamic radiation white matter microstructure.

genetics↗

bioRxiv2018

Trans-ancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders

Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest GWAS to date of DSM - IV diagnosed AD. Genome - wide data on 14,904 individuals with AD and 37,944 controls from 28 case / control and family - based studies were meta - analyzed, stratified by genetic ancestry (European, N = 46,568; African; N = 6,280). Independent, genome - wide significant effects of different ADH1B variants were identified in European (rs1229984; p = 9.8E - 13) and African ancestries (rs2066702; p = 2.2E - 9). Significant genetic correlations were observed with schizophrenia, ADHD, depression, and use of cigarettes and cannabis. There was only modest genetic correlation with alcohol consumption and inconsistent associations with problem drinking. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and non - pathological drinking behaviors.

genetics↗

bioRxiv2018

Genome-wide association study meta-analysis of the Alcohol Use Disorder Identification Test (AUDIT) in two population-based cohorts (N=141,958)

Alcohol use disorders (AUD) are common conditions that have enormous social and economic consequences. We obtained quantitative measures using the Alcohol Use Disorder Identification Test (AUDIT) from two population-based cohorts of European ancestry: UK Biobank (UKB; N=121,604) and 23andMe (N=20,328) and performed a genome-wide association study (GWAS) meta-analysis. We also performed GWAS for AUDIT items 1-3, which focus on consumption (AUDIT-C), and for items 4-10, which focus on the problematic consequences of drinking (AUDIT-P). The GWAS meta-analysis of AUDIT total score identified 10 associated risk loci. Novel associations localized to genes including JCAD and SLC39A13; we also replicated previously identified signals in the genes ADH1B, ADH1C, KLB, and GCKR. The dimensions of AUDIT showed positive genetic correlations with alcohol consumption (rg=0.76-0.92) and Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) alcohol dependence (rg=0.33-0.63). AUDIT-P and AUDIT-C showed significantly different patterns of association across a number of traits, including psychiatric disorders. AUDIT-P was positively genetically correlated with schizophrenia (rg=0.22, p=3.0x10-10), major depressive disorder (rg=0.26, p=5.6x10-3), and attention-deficit/hyperactivity disorder (ADHD; rg=0.23, p=1.1x10-5), whereas AUDIT-C was negatively genetically correlated with major depressive disorder (rg=-0.24, p=3.7x10-3) and ADHD (rg=-0.10, p=1.8x10-2). We also used the AUDIT data in the UKB to identify thresholds for dichotomizing AUDIT total score that optimize genetic correlations with DSM-IV alcohol dependence. Coding individuals with AUDIT total score of [≤]4 as controls and [≥]12 as cases produced a high genetic correlation with DSM-IV alcohol dependence (rg=0.82, p=3.2x10-6) while retaining most subjects. We conclude that AUDIT scores ascertained in population-based cohorts can be used to explore the genetic basis of both alcohol consumption and AUD.

genetics↗

bioRxiv2017

Accelerated Epigenetic Ageing in Major Depressive Disorder

BackgroundMajor depressive disorder (MDD) is a severe, heritable psychiatric disorder associated with shortened lifespan and comorbidities of advancing age. It is unknown however whether MDD is associated with accelerated biological ageing relative to chronological age. This hypothesis was tested using the epigenetic clock as a measure of biological age.\n\nMethodsTo address the main hypothesis, using peripheral blood, we derived measures of Epigenetic Age Acceleration (EAA) in 3,833 controls and 1,219 MDD cases based on Hannum and Horvath epigenetic clocks in Generation Scotland (GS:SFHS, mean age 48 years, std dev 14.5). Models controlled for relatedness, sex, cell counts, and processing batch (basic model), as well as additional covariates of smoking and drinking status, and body mass index (BMI) (full models).\n\nResultsAccelerated epigenetic ageing was found in MDD cases versus controls using the Horvath clock ({beta}=0.0804, p=0.012 equivalent to 0.20 years) in both the basic and full models. Significant MDD*age interactions indicated greatest effects at younger age ranges. No significant differences were observed for the Hannum clock. BMI was the only additional covariate found to attenuate the relationship between EAAHorvath and MDD. Further, genetic correlation analysis indicated significant overlap in the genetic aetiology of EAAHorvath with BMI (rG=0.20, p=0.03), between MDD with BMI (rG=0.10, p=9.86x10-6), but not between EAAHorvath and MDD (rG=0.14, p=0.125). Mediation analysis indicated partial mediation of the relationship between EAAHorvath and depression status through BMI ({beta} =0.0028; p=0.0248, ~13%).\n\nConclusionThese data imply that accelerated biological ageing is associated with MDD and partially mediated through BMI.

genomics↗

bioRxiv2017

116 independent genetic variants influence the neuroticism personality trait in over 329,000 UK Biobank individuals.

Neuroticism is a stable personality trait 1; twin studies report heritability between 30% and 50% 2, and SNP-based heritability is about 15% 3. Higher levels of neuroticism are associated with poorer mental and physical health 4,5, and the economic burden of neuroticism for societies is high 6. To date, genome-wide association (GWA) studies of neuroticism have identified up to 11 genetic loci 3,7. Here we report 116 significant independent genetic loci from a GWA of neuroticism in 329,821 UK Biobank participants, with replication available in a GWA meta-analysis of neuroticism in 122,867 individuals. Genetic signals for neuroticism were enriched in neuronal genesis and differentiation pathways, and substantial genetic correlations were found between neuroticism and depressive symptoms (rg = .82, SE=.03), major depressive disorder (rg = .69, SE=.07) and subjective wellbeing (rg = -.68, SE=.03) alongside other mental health traits. These discoveries significantly advance our understanding of neuroticism and its association with major depressive disorder.

genetics↗

bioRxiv2017

Genome-wide association study of depression phenotypes in UK Biobank (n = 322,580) identifies the enrichment of variants in excitatory synaptic pathways

Depression is a polygenic trait that causes extensive periods of disability and increases the risk of suicide, a leading cause of death in young people. Previous genetic studies have identified a number of common risk variants which have increased in number in line with increasing sample sizes. We conducted a genome-wide association study (GWAS) in the largest single population-based cohort to date, UK Biobank. This allowed us to estimate the effects of {approx} 8 million genetic variants in 320,000 people for three depression phenotypes: broad depression, probable major depressive disorder (MDD), and International Classification of Diseases (ICD, version 9 or 10)-coded MDD. Each phenotype was found to be significantly genetically correlated with the results from a previous independent study of clinically defined MDD. We identified 14 independent loci that were significantly associated (P < 5 x 10-8) with broad depression, two independent variants for probable MDD, and one independent variant for ICD-coded MDD. Gene-based analysis of our GWAS results with MAGMA revealed 46 regions significantly associated (P < 2.77 x 10-6) with broad depression, two significant regions for probable MDD and one significant region for ICD-coded MDD. Gene region-based analysis of our GWAS results with MAGMA revealed 59 regions significantly associated (P < 6.02 x 10-6) with broad depression, of which 27 were also detected by gene-based analysis. Variants for broad depression were enriched in pathways for excitatory neurotransmission, mechanosensory behavior, postsynapse, neuron spine and dendrite. This study provides a number of novel genetic risk variants that can be leveraged to elucidate the mechanisms of MDD and low mood.

genetics↗

bioRxiv2017

Resting-state connectivity and its association with cognitive performance, educational attainment, and household income in UK Biobank (N = 3,950)

Cognitive ability is an important predictor of lifelong physical and mental well-being and its impairments are associated with many psychiatric disorders. Higher cognitive ability is also associated with greater educational attainment and increased household income. Understanding neural mechanisms underlying cognitive ability is therefore of crucial importance for determining the nature of these associations. In the current study, we examined the spontaneous activity of the brain at rest to investigate its relationships with not only cognitive ability, but also educational attainment and household income. We used a large sample of resting-state neuroimaging data from UK Biobank (N=3,950). Firstly, analysis at the whole-brain level showed that connections involving the default mode network (DMN), fronto-parietal network (FPN) and cingulo-opercular network (CON) were significantly positively associated with levels of cognitive performance assessed by a verbal-numerical reasoning test (standardised {beta} ranged from 0.054 to 0.097). Connections associated with higher levels of cognitive performance were also significantly positively associated with educational attainment (r=0.48, N=4,160) and household income (r=0.38, N=3,793). Further, analysis on the coupling of functional networks showed that better cognitive performance was associated with more positive DMN-CON connections, decreased cross-hemisphere connections between homotopic network in CON and FPN, and stronger CON-FPN connections (absolute {beta} ranged from 0.034 to 0.063). The present study finds that variation in brain resting state functional connectivity associated with individual differences in cognitive ability, largely involving DMN and lateral prefrontal networks. Additionally, we provide further evidence of shared neural associations of cognitive ability, educational attainment, and household income.

neuroscience↗

bioRxiv2017

The Stratification Of Major Depressive Disorder Into Genetic Subgroups

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 x 10-3) and this effect remained significant in females (P = 1.18 x 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 x 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.

genetics↗

bioRxiv2017

Genome-Wide Meta-Analyses Of Stratified Depression In Generation Scotland And UK Biobank

Few replicable genetic associations for Major Depressive Disorder (MDD) have been identified. However recent studies of depression have identified common risk variants by using either a broader phenotype definition in very large samples, or by reducing the phenotypic and ancestral heterogeneity of MDD cases. Here, a range of genetic analyses were applied to data from two large British cohorts, Generation Scotland and UK Biobank, to ascertain whether it is more informative to maximize the sample size by using data from all available cases and controls, or to use a refined subset of the data - stratifying by MDD recurrence or sex. Meta-analysis of GWAS data in males from these two studies yielded one genome-wide significant locus on 3p22.3. Three associated genes within this region (CRTAP, GLB1, and TMPPE) were significantly associated in subsequent gene-based tests. Meta-analyzed MDD, recurrent MDD and female MDD were each genetically correlated with 6 of 200 health-correlated traits, namely neuroticism, depressive symptoms, subjective well-being, MDD, a cross-disorder phenotype and Bipolar Disorder. Meta-analyzed male MDD showed no statistically significant correlations with these traits after correction for multiple testing. Whilst stratified GWAS analysis revealed a genome-wide significant locus for male MDD, the lack of independent replication, the equivalent SNP-based heritability estimates and the consistent pattern of genetic correlation with other health-related traits suggests that phenotypic stratification in currently available sample sizes is currently weakly justified. Based upon existing studies and our findings, the strategy of maximizing sample sizes is likely to provide the greater gain.

genetics↗

bioRxiv2017

Genome-wide association study of alcohol consumption and genetic overlap with other health-related traits in UK Biobank (N=112,117).

Alcohol consumption has been linked to over 200 diseases and is responsible for over 5% of the global disease burden. Well known genetic variants in alcohol metabolizing genes, e.g. ALDH2, ADH1B, are strongly associated with alcohol consumption but have limited impact in European populations where they are found at low frequency. We performed a genome-wide association study (GWAS) of self-reported alcohol consumption in 112,117 individuals in the UK Biobank (UKB) sample of white British individuals. We report significant genome-wide associations at 8 independent loci. These include SNPs in alcohol metabolizing genes (ADH1B/ADH1C/ADH5) and 2 loci in KLB, a gene recently associated with alcohol consumption. We also identify SNPs at novel loci including GCKR, PXDN, CADM2 and TNFRSF11A. Gene-based analyses found significant associations with genes implicated in the neurobiology of substance use (CRHR1, DRD2), and genes previously associated with alcohol consumption (AUTS2). GCTA-GREML analyses found a significant SNP-based heritability of self-reported alcohol consumption of 13% (S.E.=0.01). Sex-specific analyses found largely overlapping GWAS loci and the genetic correlation between male and female alcohol consumption was 0.73 (S.E.=0.09, p-value = 1.37 x 10-16). Using LD score regression, genetic overlap was found between alcohol consumption and schizophrenia (rG=0.13, S.E=0.04), HDL cholesterol (rG=0.21, S.E=0.05), smoking (rG=0.49, S.E=0.06) and various anthropometric traits (e.g. Overweight, rG=-0.19, S.E.=0.05). This study replicates the association between alcohol consumption and alcohol metabolizing genes and KLB, and identifies 4 novel gene associations that should be the focus of future studies investigating the neurobiology of alcohol consumption.

genetics↗