Biology subjects

Thomson, P. A.

Publications and source records attributed to Thomson, P. A..

3 recordsLinked to original sources

bioRxiv2023

Methylome-wide association studies of traumatic physical injury identifies differential DNA methylation of synaptic plasticity and GABAergic-signalling.

Traumatic physical injury is often associated with psychological trauma and is a risk factor for major depressive disorder (MDD). In Generation Scotland traumatic injury was significantly associated with recurrent major depression (OR = 2.10, 95% CI 1.33-3.33, PLJ=LJ0.0016). and schizotypal symptoms, particularly disorganised thought ({beta}LJ=LJ0.111, 95% CI 0.049-0.177, PLJ=LJ0.0004). We performed methylome-wide analyses of traumatic injury in individuals with MDD and controls separately to investigate the link between traumatic injury and MDD. Nominally significant differences in differential DNA methylation between MDD and control groups were identified at 40 003 CpG sites (p < 0.05). Individuals with recurrent MDD showed significantly higher levels of DNA methylation associated with traumatic injury at CpG sites at the first exon and lower levels at exon boundaries, this was significant different to the association pattern at these sites in controls (mean difference in M-value = 0.0083, P = 21.1x10-10, and -0.0125, P = 2.1x10-174, respectively). Analyses at the level of CpG site, genes and gene ontologies implicated dysregulation of processes related to synaptic plasticity, including dendrite development, excitatory synapse and GABAergic signalling (normalised enrichment values > 2, FDR q-values < 0.01). Enrichment analyses for regional brain-expression in the recurrent MDD group highlight the limbic lobe and supraoptic nuclei (recurrent MDD FWER = 0.028 and 0.034, respectively). These results suggest that traumatic injury is associated with patterns of DNA methylation differentially in individuals with MDD compared to controls, highlighting the need for novel analysis approaches.

genomics↗

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↗