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DNA methylation and inflammation marker profiles associated with a history of depression.

gse113725

Description

Depression is a common and disabling disorder, representing a major social and economic health issue. Moreover, depression is associated with the progression of diseases with an inflammatory etiology including many inflammatory-related disorders. At the molecular level, the mechanisms by which depression might promote the onset of these diseases and associated immune-dysfunction are not well understood. In this study we assessed genome-wide patterns of DNA methylation in whole blood-derived DNA obtained from individuals with a self-reported history of depression (n=100) and individuals without a history of depression (n=100) using the Illumina 450K microarray. Our analysis identified 6 significant (Sidak corrected P < 0.05) depression-associated differentially methylated regions (DMRs); the top-ranked DMR was located in exon 1 of the LTB4R2 gene (Sidak corrected P = 1.27 x 10-14). Polygenic risk scores (PRS) for depression were generated and known biological markers of inflammation, telomere length (TL) and IL-6, were measured in DNA and serum samples respectively. Next, we employed a systems-level approach to identify networks of co-methylated loci associated with a history of depression, in addition to depression PRS, TL and IL-6 levels. Our analysis identified one depression-associated co-methylation module (P = 0.04). Interestingly, the depression-associated module was highly enriched for pathways related to immune function and was also associated with TL and IL-6 cytokine levels. In summary, our genome-wide DNA methylation analysis of individuals with and without a self-reported history of depression identified several candidate DMRs of potential relevance to the pathogenesis of depression and its associated immune-dysfunction phenotype.

Overall Design

DNA from whole blood from 194 individuals

Histogram

Data and Resources

Raw Files [194]

Additional Info

Field Value
Source https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE113725
Type of Data

Methylation profiling by genome tiling array

Technology

Methylation Array

GSE Submission Date 26/04/2018
GSE Authors Bethany,,Crawford; Zoe Craig; Georgina Mansell; Isobel White; Adam Smith; Steve Spaull; Jennifer Imm; Eilis Hannon; Andrew Wood; Hanieh Yaghootkar; Yingjie Ji; Niamh Mullins; Cathryn,M,Lewis; Jonathan Mill; Therese,M,Murphy
Dataset Last Updated November 29, 2019, 16:44 (UTC)
Dataset Created November 29, 2019, 13:01 (UTC)