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


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-01-05

AUTHORS

Mihoko Shimada, Takeshi Otowa, Taku Miyagawa, Tadashi Umekage, Yoshiya Kawamura, Miki Bundo, Kazuya Iwamoto, Tempei Ikegame, Mamoru Tochigi, Kiyoto Kasai, Hisanobu Kaiya, Hisashi Tanii, Yuji Okazaki, Katsushi Tokunaga, Tsukasa Sasaki

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. More... »

PAGES

319-326

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  • Journal

    TITLE

    Journal of Human Genetics

    ISSUE

    3

    VOLUME

    63

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s10038-017-0382-y

    DOI

    http://dx.doi.org/10.1038/s10038-017-0382-y

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1100198453

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/29305581


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