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Genome-wide gene-environment interaction in depression: A systematic evaluation of candidate genes: The childhood trauma working-group of PGC-MDD. | LitMetric

AI Article Synopsis

  • This study examined how specific genes and variants linked to major depressive disorder (MDD) interact with childhood trauma in influencing the development of MDD in a large group of subjects.* -
  • Researchers identified 27 genes and 268 SNPs related to MDD, using data from 3,944 individuals of European ancestry, but found no significant associations or consistent results across different methods.* -
  • The findings suggest that the impact of known genetic candidates on gene-environment interactions in MDD may be uncertain, highlighting the need for larger studies and improved methods to understand these complex relationships.*

Article Abstract

Gene by environment (GxE) interaction studies have investigated the influence of a number of candidate genes and variants for major depressive disorder (MDD) on the association between childhood trauma and MDD. Most of these studies are hypothesis driven and investigate only a limited number of SNPs in relevant pathways using differing methodological approaches. Here (1) we identified 27 genes and 268 SNPs previously associated with MDD or with GxE interaction in MDD and (2) analyzed their impact on GxE in MDD using a common approach in 3944 subjects of European ancestry from the Psychiatric Genomics Consortium who had completed the Childhood Trauma Questionnaire. (3) We subsequently used the genome-wide SNP data for a genome-wide case-control GxE model and GxE case-only analyses testing for an enrichment of associated SNPs. No genome-wide significant hits and no consistency among the signals of the different analytic approaches could be observed. This is the largest study for systematic GxE interaction analysis in MDD in subjects of European ancestry to date. Most of the known candidate genes/variants could not be supported. Thus, their impact on GxE interaction in MDD may be questionable. Our results underscore the need for larger samples, more extensive assessment of environmental exposures, and greater efforts to investigate new methodological approaches in GxE models for MDD.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5726923PMC
http://dx.doi.org/10.1002/ajmg.b.32593DOI Listing

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