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

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 subgroup...

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Main Authors: Ho, Weang-Kee, Tai, Mei-Chee, Dennis, Joe, Shu, Xiang, Li, Jingmei, Ho, Peh Joo, Millwood, Iona Y., Lin, Kuang, Jee, Yon-Ho, Lee, Su-Hyun, Mavaddat, Nasim, 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, 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, Pharoah, Paul D. B., Dunning, Alison M., Simard, Jacques, Shu, Xiao-Ou, Yip, Cheng-Har, Taib, Nur Aishah Mohd, Antoniou, Antonis C., Zheng, Wei, Hartman, Mikael, Easton, Douglas F., Teo, Soo-Hwang, Project, BioBank Japan
Format: Article
Published: Elsevier Sci Inc 2022
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Online Access:http://eprints.um.edu.my/42333/
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Summary: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. (C) 2021 by American College of Medical Genetics and Genomics. Published by Elsevier Inc.