medRxivGenetic & Genomic MedicinePreprint
Genetic liability for endometriosis associates with pain, inflammatory, and metabolic traits: a polygenic score analysis
Juliane Lyng Beauchamp, Karina BanasikiD, Lisette J. A. KogelmaniD, David WestergaardiD, Dea Froeding Skipper, Olafur B. DavidssoniD, Sisse Rye OstrowskiiD, Christina MikkelseniD, Christian ErikstrupiD, Mie Topholm BruuniD, Bitten AagaardiD, Ole Birger PederseniD, Erik Soerensen, Henrik UllumiD, DBDS Genomic Cosnoritum, Palle Duun RohdeiD, Mette NyegaardiD, Thomas Folkmann HanseniD, Henriette Svarre NielseniD
Abstract
PurposeEndometriosis is associated with pain, cardiometabolic, psychiatric, and immune comorbidities. We tested whether the genetic liability captured by an endometriosis polygenic risk score (PRS) extends to these comorbidities through shared pathways or operates independently of the disease. MethodsIn 168,238 women and 155,304 men of European ancestry from two Danish genetic studies linked to national health registers, we constructed an endometriosis PRS using LDpred2 from an independent GWAS meta-analysis (23,112 cases, 429,677 controls). Entropy balancing with doubly robust adjustment addressed selection bias. Comorbidity analyses were performed in both sexes to distinguish shared from endometriosis-specific pathways. ResultsThe PRS was associated with endometriosis (OR 1.55 per SD, 95% CI 1.50-1.61; AUC 0.73) and with 20 of 29 comorbidities in women. Pain conditions (fibromyalgia, migraine, chronic back pain) and cardiometabolic conditions replicated in men, indicating shared pathways, whereas immune-mediated conditions associated in women only. Seventeen associations persisted in women without diagnosed endometriosis. High genetic risk was associated with increased healthcare utilisation and all-cause mortality (HR 1.05, 95% CI 1.01-1.10). ConclusionThe endometriosis PRS captures a pain-inflammatory-metabolic genetic axis operating in both sexes, indicating that the genetic liability extends beyond the uterine disease and providing a rationale for targeted investigation and risk stratification.
- organism: human
- assay: GWAS summary statistics
- research focus: polygenic risk
- approach: statistical model
- Citations
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