An epigenome-wide methylation study of healthy individuals with or without depressive symptoms

J Hum Genet. 2018 Mar;63(3):319-326. doi: 10.1038/s10038-017-0382-y. Epub 2018 Jan 5.

Abstract

Major depressive disorder is a common psychiatric disorder that is thought to be triggered by both genetic and environmental factors. Depressive symptoms are an important public health problem and contribute to vulnerability to major depression. Although a substantial number of genetic and epigenetic studies have been performed to date, the detailed etiology of depression remains unclear and there are no validated biomarkers. DNA methylation is one of the major epigenetic modifications that play diverse roles in the etiology of complex diseases. In this study, we performed an epigenome-wide association study (EWAS) of DNA methylation on subjects with (N = 20) or without (N = 27) depressive symptoms in order to examine whether different levels of DNA methylation were associated with depressive tendencies. Employing methylation-array technology, a total of 363,887 methylation sites across the genomes were investigated and several candidate CpG sites associated with depressive symptoms were identified, especially annotated to genes linked to a G-protein coupled receptor protein signaling pathway. These data provide a strong impetus for validation studies using a larger cohort and support the possibility that G-protein coupled receptor protein signaling pathways are involved in the pathogenesis of depression.

MeSH terms

  • Computational Biology / methods
  • CpG Islands
  • DNA Methylation*
  • Depression / epidemiology*
  • Depression / genetics*
  • Depressive Disorder, Major / epidemiology
  • Depressive Disorder, Major / genetics
  • Epigenesis, Genetic*
  • Epigenomics* / methods
  • Female
  • Gene Expression Profiling
  • Gene Ontology
  • Gene Regulatory Networks
  • Genetic Association Studies*
  • Genetic Predisposition to Disease*
  • Genome-Wide Association Study
  • Healthy Volunteers
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Male
  • Molecular Sequence Annotation
  • Phenotype
  • Population Surveillance