Polygenic risk scores for prediction of breast cancer risk in Asian populations.
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Authors
Ho, Weang-Kee
Tai, Mei-Chee
Shu, Xiang
Li, Jingmei
Ho, Peh Joo
Millwood, Iona Y
Lin, Kuang
Jee, Yon-Ho
Lee, Su-Hyun
Bolla, Manjeet K
Wang, Qin
Michailidou, Kyriaki
Long, Jirong
Wijaya, Eldarina Azfar
Hassan, Tiara
Rahmat, Kartini
Tan, Veronique Kiak Mien
Tan, Benita Kiat Tee
Tan, Su Ming
Tan, Ern Yu
Lim, Swee Ho
Gao, Yu-Tang
Zheng, Ying
Kang, Daehee
Choi, Ji-Yeob
Han, Wonshik
Lee, Han-Byoel
Kubo, Michiki
Okada, Yukinori
Namba, Shinichi
BioBank Japan Project
Park, Sue K
Kim, Sung-Won
Shen, Chen-Yang
Wu, Pei-Ei
Park, Boyoung
Muir, Kenneth R
Lophatananon, Artitaya
Wu, Anna H
Tseng, Chiu-Chen
Matsuo, Keitaro
Ito, Hidemi
Kwong, Ava
Chan, Tsun L
John, Esther M
Kurian, Allison W
Iwasaki, Motoki
Yamaji, Taiki
Kweon, Sun-Seog
Aronson, Kristan J
Murphy, Rachel A
Koh, Woon-Puay
Khor, Chiea-Chuen
Yuan, Jian-Min
Dorajoo, Rajkumar
Walters, Robin G
Chen, Zhengming
Li, Liming
Lv, Jun
Jung, Keum-Ji
Kraft, Peter
Dunning, Alison M
Simard, Jacques
Shu, Xiao-Ou
Yip, Cheng-Har
Taib, Nur Aishah Mohd
Zheng, Wei
Hartman, Mikael
Teo, Soo-Hwang
Publication Date
2022-03Journal Title
Genet Med
ISSN
1098-3600
Publisher
Elsevier BV
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Ho, W., Tai, M., Dennis, J., Shu, X., Li, J., Ho, P. J., Millwood, I. Y., et al. (2022). Polygenic risk scores for prediction of breast cancer risk in Asian populations.. Genet Med https://doi.org/10.1016/j.gim.2021.11.008
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.
Keywords
Breast cancer, Genetic, Polygenic risk score, Risk prediction
Sponsorship
National Cancer Institute (U19CA148065)
European Commission Horizon 2020 (H2020) Societal Challenges (634935)
European Commission Horizon 2020 (H2020) Societal Challenges (633784)
Cancer Research UK (CRUK-A16563)
Cancer Research UK (CRUK-A10118)
Cancer Research UK (20861)
Wellcome Trust (203477/B/16/Z)
National Cancer Institute (U19CA148537)
National Cancer Institute (R01CA128978)
Medical Research Council (MR/P012930/1)
Identifiers
External DOI: https://doi.org/10.1016/j.gim.2021.11.008
This record's URL: https://www.repository.cam.ac.uk/handle/1810/331659
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