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A Syngeneic Murine Model of Endometriosis using Naturally Cycling Mice
Published on: November 24, 2020
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Polygenic Risk Score Prediction for Endometriosis.
Kirstine Kloeve-Mogensen1,2, Palle Duun Rohde1,3, Simone Twisttmann4
1Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.
Frontiers in Reproductive Health
|October 28, 2022
Summary
A new polygenic risk score (PRS) shows genetic links to endometriosis, aiding in early detection. This PRS may help identify women at higher risk, improving diagnosis and management of endometriosis.
Area of Science:
- Reproductive medicine and genetics.
- Clinical diagnostics and risk assessment.
Background:
- Endometriosis diagnosis is often delayed, leading to pain sensitization.
- Genetics plays a significant role in endometriosis development.
- Improved clinical tools are needed for early identification of at-risk individuals.
Purpose of the Study:
- To evaluate the discriminative ability of a polygenic risk score (PRS) for endometriosis.
- To assess the PRS's association with different endometriosis subtypes and adenomyosis.
- To explore the potential of PRS in clinical risk assessment for endometriosis.
Main Methods:
- Developed a PRS using 14 genetic variants from a large genome-wide association study.
- Validated the PRS in three cohorts: Danish referral center, Danish Twin Registry (DTR), and UK Biobank.
- Included patients with adenomyosis for comparative analysis.
Main Results:
- The PRS was significantly associated with endometriosis in both Danish cohorts (OR=1.57, p=2.5x10^-11) and the UK Biobank (OR=1.28, p<2.2x10^-16).
- PRS showed association with ovarian, infiltrating, and peritoneal endometriosis subtypes.
- No association was found between PRS and adenomyosis, suggesting distinct genetic underpinnings.
Conclusions:
- A PRS can identify individuals with an increased risk for endometriosis across various subtypes.
- While not sufficient alone, PRS offers significant discriminatory value when combined with clinical factors.
- PRS holds promise as a component of a novel endometriosis risk stratification tool.
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