SynthesisGenes2021
GWAS Meta-Analysis Reveals Shared Genes and Biological Pathways between Major Depressive Disorder and Insomnia.
Synthesis in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Identification of therapeutic targets for insomnia through genetic and plasma proteomic approaches.Medicine · 2025Pooled it
- Optimization of potential targets for antidepressant Chinese medicines: AI and multi-omics methods.Chinese medicine · 2026Review
- The genetic risk of mental health disorders in children from diverse population-based cohorts is modulated by poverty.Research square · 2026Article
- Article
- Elucidating the susceptibility genes between insomnia and migraine by integrating genetic data and transcriptomes.The journal of headache and pain · 2026Article
- Large-scale composite hypothesis testing procedure for omics data analyses.NAR genomics and bioinformatics · 2025Article
- Molecular mechanisms explaining sex-specific functional connectivity changes in chronic insomnia disorder.BMC medicine · 2025Article
- Correlation between psychological stress and depressive symptoms among Japanese university students: a cross-sectional analysis.Journal of physical therapy science · 2024Article
- The association between epilepsy and sleep disturbance in US adults: the mediating effect of depression.BMC public health · 2024Article
- Bidirectional mechanism of comorbidity of depression and insomnia based on synaptic plasticity.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2023Article
- Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings.Translational psychiatry · 2023Review
- Integrative Functional Genomic Analysis in Multiplex Autism Families from Kazakhstan.Disease markers · 2022Article
- Shared Genetics and Causality Between Decaffeinated Coffee Consumption and Neuropsychiatric Diseases: A Large-Scale Genome-Wide Cross-Trait Analysis and Mendelian Randomization Analysis.Frontiers in psychiatry · 2022Article
- The Function and Structure of Precuneus Is Associated With Subjective Sleep Quality in Major Depression.Frontiers in psychiatry · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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 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.
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