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J Med Genet. 2018 Aug;55(8):546-554. doi: 10.1136/jmedgenet-2018-105313. Epub 2018 May 5.

Evaluation of polygenic risk scores for ovarian cancer risk prediction in a prospective cohort study.

Author information

1
Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
2
Department of Women's Cancer, Institute for Women's Health, University College London, London, UK.
3
School of Women's and Children's Health, University of New South Wales, Sydney, New South Wales, Australia.
4
Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK.
5
Centre for Experimental Cancer Medicine, Barts Cancer Institute, Queen Mary University of London, London, UK.
6
Department of Gynaecological Oncology, Barts Health NHS Trust, Royal London Hospital, London, UK.
7
Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
8
Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA.
9
The Kinghorn Cancer Centre, Garvan Institute of Medical Research, Sydney, New South Wales, Australia.
10
University of New South Wales, Sydney, New South Wales, Australia.
11
University of Manchester, Manchester, UK.

Abstract

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.

KEYWORDS:

evaluation; ovarian cancer; polygenic risk scores; prospective cohort study; risk prediction

PMID:
29730597
PMCID:
PMC6073911
DOI:
10.1136/jmedgenet-2018-105313
[Indexed for MEDLINE]
Free PMC Article

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