TY - JOUR T1 - Evaluation of polygenic risk scores for ovarian cancer risk prediction in a prospective cohort study JF - Journal of Medical Genetics JO - J Med Genet SP - 546 LP - 554 DO - 10.1136/jmedgenet-2018-105313 VL - 55 IS - 8 AU - Xin Yang AU - Goska Leslie AU - Aleksandra Gentry-Maharaj AU - Andy Ryan AU - Maria Intermaggio AU - Andrew Lee AU - Jatinderpal K Kalsi AU - Jonathan Tyrer AU - Faiza Gaba AU - Ranjit Manchanda AU - Paul D P Pharoah AU - Simon A Gayther AU - Susan J Ramus AU - Ian Jacobs AU - Usha Menon AU - Antonis C Antoniou Y1 - 2018/08/01 UR - http://jmg.bmj.com/content/55/8/546.abstract N2 - Background Genome-wide association studies have identified >30 common SNPs associated with epithelial ovarian cancer (EOC). We evaluated the combined effects of EOC susceptibility SNPs on predicting EOC risk in an independent prospective cohort study.Methods We genotyped ovarian cancer susceptibility single nucleotide polymorphisms (SNPs) in a nested case–control study (750 cases and 1428 controls) from the UK Collaborative Trial of Ovarian Cancer Screening trial. Polygenic risk scores (PRSs) were constructed and their associations with EOC risk were evaluated using logistic regression. The absolute risk of developing ovarian cancer by PRS percentiles was calculated.Results The association between serous PRS and serous EOC (OR 1.43, 95% CI 1.29 to 1.58, p=1.3×10–11) was stronger than the association between overall PRS and overall EOC risk (OR 1.32, 95% CI 1.21 to 1.45, p=5.4×10–10). Women in the top fifth percentile of the PRS had a 3.4-fold increased EOC risk compared with women in the bottom 5% of the PRS, with the absolute EOC risk by age 80 being 2.9% and 0.9%, respectively, for the two groups of women in the population.Conclusion PRSs can be used to predict future risk of developing ovarian cancer for women in the general population. Incorporation of PRSs into risk prediction models for EOC could inform clinical decision-making and health management. ER -