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Updated: Jun 15, 2025

Establishment of an Experimental Mouse Model of Endometrioma to Study its Related Infertility
Published on: April 5, 2024
Interaction between genetic risk and comorbid conditions in endometriosis
Isabelle M McGrath1, Valentina Rukins2, Triin Laisk2
1The Institute for Molecular Bioscience, The University of Queensland, Brisbane, 4072 QLD, Australia; Department of Psychiatry, University of Oxford, Oxford, UK.
None:
Endometriosis is a complex disease, and many genetic and environmental risk factors contribute to disease risk. The genetic risk of endometriosis has been well characterized in genome-wide association studies. While few physiological risk factors are known, endometriosis is associated with many comorbid disorders. This study examines the interplay between genetic risk factors, comorbid disorders, and endometriosis. Genetic and health record data from the UK Biobank (5,432 cases; 92,344 controls) and Estonian Biobank (3,824 cases; 15,296 controls) was used to estimate the correlation between comorbidity burden, endometriosis and genetic risk, and to estimate the interactive effects between endometriosis polygenic risk score (PRS) and diagnosis of prevalent comorbidities (uterine fibroids, heavy menstrual bleeding, dysmenorrhea, irritable bowel syndrome, diverticular disease, and asthma) on endometriosis prevalence. The comorbidity burden was significantly higher in endometriosis cases and was positively correlated with endometriosis PRS in women without endometriosis but negatively correlated in women with endometriosis. The absolute increase in endometriosis prevalence conveyed by the presence of several comorbidities (uterine fibroids, heavy menstrual bleeding, dysmenorrhea) was greater in individuals with a high endometriosis PRS compared to a low endometriosis PRS. These findings, consistent across two biobanks, highlight significant interactions between polygenic risk for endometriosis and the diagnosed comorbidities in endometriosis susceptibility that have implications for understanding the underlying mechanisms contributing to disease risk.
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