Background: Although circadian disruption has been implicated in gynecologic malignancies, genetic evidence for a causal relationship between insomnia and ovarian cysts remains lacking. The biological pathways linking sleep disturbance to ovarian pathology are therefore poorly understood, limiting mechanistic insights and therapeutic development. Methods: We employed a two-sample Mendelian Randomization (MR) framework using large-scale Genome-Wide Association Study (GWAS) datasets of European ancestry to examine the effects of seven sleep-related traits on five gynecologic outcome types. We further conducted transcriptomic analyses using Gene Expression Omnibus (GEO) datasets (GSE208668 and GSE7305) and performed molecular docking with 288 drug-like compounds to explore therapeutic targets. Results: MR identified a strong, unidirectional association between insomnia and increased ovarian cyst risk, with no evidence of reverse causality. Other sleep traits showed mixed effects across gynecologic outcomes. Single-nucleotide polymorphism (SNP)-mapped gene enrichment revealed involvement of neuronal signaling, circadian rhythm, and immune pathways. Three core genes (GFRA1, SORCS2, RASGRF2) were identified through overlap with ovarian cyst differentially expressed genes (DEGs) and were further supported by in silico docking with favorable predicted binding energies. Shared DEGs between insomnia and ovarian cyst samples were enriched in leukocyte activation, oxidative stress, and developmental processes. Conclusion: This multi-omics study provides genetic and molecular evidence that insomnia may contribute to ovarian cyst formation through circadian, synaptic, and immune mechanisms. The identified hub genes and druggable targets suggest circadian-aligned therapeutic strategies (chronotherapy), including sleep optimization, rhythm-timed pharmacotherapy, and melatonin-related modulation, as potential avenues for prevention and intervention. Keywords: insomnia, ovarian cyst, Mendelian randomization, circadian rhythm, transcriptomics, molecular docking, gynecologic outcomes
Geng et al. (2026) studied this question.
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