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Polygenic risk scores for prediction of breast cancer risk in Asian populations.

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Ho, Weang-Kee 
Tai, Mei-Chee 
Shu, Xiang 
Li, Jingmei 

Abstract

PURPOSE: Non-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups. METHODS: The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases). RESULTS: The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk. CONCLUSION: PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.

Description

Keywords

Breast cancer, Genetic, Polygenic risk score, Risk prediction, Bayes Theorem, Breast Neoplasms, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Prospective Studies, Risk Factors

Journal Title

Genet Med

Conference Name

Journal ISSN

1098-3600
1530-0366

Volume Title

Publisher

Elsevier BV
Sponsorship
National Cancer Institute (U19CA148065)
European Commission Horizon 2020 (H2020) Societal Challenges (634935)
European Commission Horizon 2020 (H2020) Societal Challenges (633784)
Cancer Research UK (16563)
Cancer Research UK (10118)
Cancer Research UK (20861)
Wellcome Trust (203477/B/16/Z)
National Cancer Institute (U19CA148537)
National Cancer Institute (R01CA128978)
Medical Research Council (MR/P012930/1)
European Commission (223175)
Wellcome Trust (203477/Z/16/Z)
Cancer Research UK (10710)
Cancer Research UK (12014)
Medical Research Council (MC_PC_12026)
Cancer Research Uk (None)
Cancer Research UK (16565)
Cancer Research UK (SEBINT-20100002)