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Methylomic Profiling of Cortex Samples from Completed Suicide Cases Implicates a Role for PSORS1C3 in Major Depression and Suicide

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Date 2017 Jan 4
PMID 28045465
Citations 44
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Abstract

Major depressive disorder (MDD) represents a major social and economic health issue and constitutes a major risk factor for suicide. The molecular pathology of suicidal depression remains poorly understood, although it has been hypothesised that regulatory genomic processes are involved in the pathology of both MDD and suicidality. In this study, genome-wide patterns of DNA methylation were assessed in depressed suicide completers (n=20) and compared with non-psychiatric, sudden-death controls (n=20) using tissue from two cortical brain regions (Brodmann Area 11 (BA11) and Brodmann Area 25 (BA25)). Analyses focused on identifying differentially methylated regions (DMRs) associated with suicidal depression and epigenetic variation were explored in the context of polygenic risk scores for major depression and suicide. Weighted gene co-methylation network analysis was used to identify modules of co-methylated loci associated with depressed suicide completers and polygenic burden for MDD and suicide attempt. We identified a DMR upstream of the PSORS1C3 gene, subsequently validated using bisulfite pyrosequencing and replicated in a second set of suicide samples, which is characterised by significant hypomethylation in both cortical brain regions in MDD suicide cases. We also identified discrete modules of co-methylated loci associated with polygenic risk burden for suicide attempt, but not major depression. Suicide-associated co-methylation modules were enriched among gene networks implicating biological processes relevant to depression and suicidality, including nervous system development and mitochondria function. Our data suggest that there are coordinated changes in DNA methylation associated with suicide that may offer novel insights into the molecular pathology associated with depressed suicide completers.

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References
1.
Chibnik L, Yu L, Eaton M, Srivastava G, Schneider J, Kellis M . Alzheimer's loci: epigenetic associations and interaction with genetic factors. Ann Clin Transl Neurol. 2015; 2(6):636-47. PMC: 4479524. DOI: 10.1002/acn3.201. View

2.
Hannon E, Dempster E, Viana J, Burrage J, Smith A, Macdonald R . An integrated genetic-epigenetic analysis of schizophrenia: evidence for co-localization of genetic associations and differential DNA methylation. Genome Biol. 2016; 17(1):176. PMC: 5004279. DOI: 10.1186/s13059-016-1041-x. View

3.
Birney E, Davey Smith G, Greally J . Epigenome-wide Association Studies and the Interpretation of Disease -Omics. PLoS Genet. 2016; 12(6):e1006105. PMC: 4919098. DOI: 10.1371/journal.pgen.1006105. View

4.
Pedersen B, Schwartz D, Yang I, Kechris K . Comb-p: software for combining, analyzing, grouping and correcting spatially correlated P-values. Bioinformatics. 2012; 28(22):2986-8. PMC: 3496335. DOI: 10.1093/bioinformatics/bts545. View

5.
Feil R, Fraga M . Epigenetics and the environment: emerging patterns and implications. Nat Rev Genet. 2012; 13(2):97-109. DOI: 10.1038/nrg3142. View