Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

GWAS Meta-Analysis Reveals Shared Genes and Biological Pathways Between Major Depressive Disorder and Insomnia

Version 1 : Received: 6 September 2021 / Approved: 7 September 2021 / Online: 7 September 2021 (08:07:18 CEST)

A peer-reviewed article of this Preprint also exists.

Lin, Y.-S.; Wang, C.-C.; Chen, C.-Y. GWAS Meta-Analysis Reveals Shared Genes and Biological Pathways between Major Depressive Disorder and Insomnia. Genes 2021, 12, 1506. Lin, Y.-S.; Wang, C.-C.; Chen, C.-Y. GWAS Meta-Analysis Reveals Shared Genes and Biological Pathways between Major Depressive Disorder and Insomnia. Genes 2021, 12, 1506.

Abstract

Major depressive disorder (MDD) is one of the most prevalent and disabling mental disorders worldwide. Among the symptoms of MDD, sleep disturbance such as insomnia is prominent and the first reason patients may seek professional help. However, the underlying pathophysiology of this comorbidity is still elusive. Recently, genome-wide association studies (GWAS) have begun to unveil the genetic background of several psychiatric disorders, including MDD and insomnia. Identifying the shared genomic risk loci between comorbid psychiatric disorders could be a valuable strategy to understand their comorbidity. This study seeks to identify the shared genes and biological pathways between MDD and insomnia based on their shared genetic variants. First, we performed a meta-analysis based on the GWAS summary statistics of MDD and insomnia obtained from Psychiatric Genomics Consortium and UK Biobank, respectively. Next, we associated shared genetic variants to genes using two gene mapping strategies: (a) positional mapping based on genomic proximity and (b) expression quantitative trait loci (eQTL) mapping based on gene expression linkage across multiple tissues. As a result, a total of 719 shared genes were identified. Over half (51%) of them are protein-coding genes. Functional enrichment analysis shows that the most enriched biological pathways are related to epigenetic modification, sensory perception, and immunologic signatures. We also identified druggable targets using a network approach. Together these results may provide insights into understanding the genetic predisposition and underlying biological pathways of comorbid MDD and insomnia symptoms.

Keywords

GWAS; MDD; Insomnia; eQTL; comorbidity; STRING; gene network; meta-analysis

Subject

Biology and Life Sciences, Biology and Biotechnology

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