TY - JOUR
T1 - Evaluation of polygenic risk scores for ovarian cancer risk prediction in a prospective cohort study
AU - Yang, Xin
AU - Leslie, Goska
AU - Gentry-Maharaj, Aleksandra
AU - Ryan, Andy
AU - Intermaggio, Maria
AU - Lee, Andrew
AU - Kalsi, Jatinderpal K.
AU - Tyrer, Jonathan
AU - Gaba, Faiza
AU - Manchanda, Ranjit
AU - Pharoah, Paul D.P.
AU - Gayther, Simon A.
AU - Ramus, Susan J.
AU - Jacobs, Ian
AU - Menon, Usha
AU - Antoniou, Antonis C.
N1 - Publisher Copyright:
© 2018 Article author(s) (or their employer(s) unless otherwise stated in the text of the article). All rights reserved.
PY - 2018/8/1
Y1 - 2018/8/1
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.
AB - 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.
KW - evaluation
KW - ovarian cancer
KW - polygenic risk scores
KW - prospective cohort study
KW - risk prediction
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U2 - 10.1136/jmedgenet-2018-105313
DO - 10.1136/jmedgenet-2018-105313
M3 - Article
C2 - 29730597
AN - SCOPUS:85049089219
SN - 0022-2593
VL - 55
SP - 546
EP - 554
JO - Journal of medical genetics
JF - Journal of medical genetics
IS - 8
ER -