bioRxiv ScienceSearch

Biology subjects

Hall, L. S.

Publications and source records attributed to Hall, L. S..

5 recordsLinked to original sources

A Transcriptome Wide Association Study implicates specific pre- and post-synaptic abnormalities in Schizophrenia

Schizophrenia is a complex highly heritable disorder. Genome-wide association studies have identified multiple loci that influence the risk of developing schizophrenia, although the causal variants driving these associations and their impacts on specific genes are largely unknown. Here we link genetic findings to gene expression in the human brain by performing a transcriptome-wide association study (TWAS) in which we integrate the largest published genome-wide association dataset of schizophrenia, with publically available post mortem expression data from the dorsolateral prefrontal cortex (DLPFC). We identify a significant correlation between schizophrenia risk and expression at eighty-nine genes in DLPFC, including forty-two genes not identified in earlier TWAS of this transcriptomic resource. Genes whose expression correlate with schizophrenia were enriched for those involved in nervous system development, abnormal synaptic transmission, reduced long term potentiation, and calcium-dependent cell-cell adhesion. Previous genetic studies have implicated post-synaptic glutamatergic and gabaergic processes in schizophrenia; here we extend this to include molecules that regulate presynaptic transmitter release. We identify specific candidate genes to which we assign predicted directions of effect in terms of expression level, facilitating downstream experimental studies geared towards a better mechanistic understanding of schizophrenia pathogenesis.

genetics

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

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

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

Applying polygenic risk scoring for psychiatric disorders within a family context

We aim to investigate the application of polygenic risk scoring within a family context. Polygenic risk profiles could aid in unraveling the role that common variation confers on disease risk within a pedigree that would have traditionally been viewed through the prism of monogenic inheritance only. We illustrate our discussion by analyzing polygenic risk scores for schizophrenia, major depressive disorder and bipolar disorder in a large pedigree (n~260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. We apply polygenic risk scores to study patterns of assortative mating and anticipation, whereby it appears increased polygenic risk for psychiatric disorders is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generations in the family. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity of a disease increases over the generations of a family. Joint analyses of both rare and common variation may be the most powerful way to understand the familial genetics of mood and psychiatric disorders.

genetics