Development and evaluation of polygenic risk scores for prediction of endometrial cancer risk in European women

Cemsel Bafligil, Deborah J. Thompson, Artitaya Lophatananon, Neil Ryan, Miriam J Smith, Joe Dennis, Krisztina Mekli, Tracy A O'Mara, D Gareth Evans, Emma Crosbie

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose. Single nucleotide polymorphisms (SNPs) influence genetic predisposition to endometrial cancer. We hypothesized that a polygenic risk score (PRS) comprising multiple SNPs may improve endometrial cancer risk prediction for targeted screening and prevention.
Methods. We developed PRSs from SNPs identified from a systematic review of published studies and suggestive SNPs from the Endometrial Cancer Association Consortium. These were tested in an independent study of 555 surgically-confirmed endometrial cancer cases and 1,202 geographically-matched controls from Manchester/UK, and validated in 1,676 cases and 116,960 controls from the UK Biobank (UKBB).
Results. Age and BMI predicted endometrial cancer in both datasets (Manchester: AUC=0.77, 95%CI 0.74-0.80; UKBB:AUC=0.74, 95%CI 0.73-0.75). The AUC for PRS19, PRS24 and PRS72 was 0.58, 0.55 and 0.57 in the Manchester study and 0.56, 0.54 and 0.54 in UKBB, respectively. For PRS19, women in the third tertile had a 2.1-fold increased risk of endometrial cancer compared to those in the first tertile of the Manchester study (OR=2.08, 95%CI 1.61-2.68; Ptrend=5.75E-9). Combining PRS19 with age and BMI improved discriminatory power (Manchester study: AUC=0.79, 95%CI 0.76-0.82; UKBB: AUC=0.75, 95%CI 0.73-0.76).
Conclusion. An endometrial cancer risk prediction model incorporating a PRS derived from multiple SNPs may help stratify women for screening and prevention strategies.
Original languageEnglish
JournalGenetics in Medicine
Publication statusAccepted/In press - 24 May 2022

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