GWAS Meta-Analysis Reveals Shared Genes and Biological Pathways between Major Depressive Disorder and Insomnia.
Yi-Sian LinChia-Chun WangCho-Yi ChenPublished in: Genes (2021)
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 understanding 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.
Keyphrases
- major depressive disorder
- genome wide
- dna methylation
- sleep quality
- copy number
- bipolar disorder
- gene expression
- high resolution
- genome wide identification
- systematic review
- genome wide association
- end stage renal disease
- depressive symptoms
- ejection fraction
- randomized controlled trial
- bioinformatics analysis
- chronic kidney disease
- peritoneal dialysis
- newly diagnosed
- genome wide analysis
- case control
- cross sectional
- long non coding rna
- transcription factor
- mass spectrometry
- binding protein
- meta analyses
- amino acid
- hepatitis c virus