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

Ho, Weang-Kee and Tai, Mei-Chee and Dennis, Joe and Shu, Xiang and Li, Jingmei and Ho, Peh Joo and Millwood, Iona Y. and Lin, Kuang and Jee, Yon-Ho and Lee, Su-Hyun and Mavaddat, Nasim and Bolla, Manjeet K. and Wang, Qin and Michailidou, Kyriaki and Long, Jirong and Wijaya, Eldarina Azfar and Hassan, Tiara and Rahmat, Kartini and Tan, Veronique Kiak Mien and Tan, Benita Kiat Tee and Tan, Su Ming and Tan, Ern Yu and Lim, Swee Ho and Gao, Yu-Tang and Zheng, Ying and Kang, Daehee and Choi, Ji-Yeob and Han, Wonshik and Lee, Han-Byoel and Kubo, Michiki and Okada, Yukinori and Namba, Shinichi and Park, Sue K. and Kim, Sung-Won and Shen, Chen-Yang and Wu, Pei-Ei and Park, Boyoung and Muir, Kenneth R. and Lophatananon, Artitaya and Wu, Anna H. and Tseng, Chiu-Chen and Matsuo, Keitaro and Ito, Hidemi and Kwong, Ava and Chan, Tsun L. and John, Esther M. and Kurian, Allison W. and Iwasaki, Motoki and Yamaji, Taiki and Kweon, Sun-Seog and Aronson, Kristan J. and Murphy, Rachel A. and Koh, Woon-Puay and Khor, Chiea-Chuen and Yuan, Jian-Min and Dorajoo, Rajkumar and Walters, Robin G. and Chen, Zhengming and Li, Liming and Lv, Jun and Jung, Keum-Ji and Kraft, Peter and Pharoah, Paul D. B. and Dunning, Alison M. and Simard, Jacques and Shu, Xiao-Ou and Yip, Cheng-Har and Taib, Nur Aishah Mohd and Antoniou, Antonis C. and Zheng, Wei and Hartman, Mikael and Easton, Douglas F. and Teo, Soo-Hwang and Project, BioBank Japan (2022) Polygenic risk scores for prediction of breast cancer risk in Asian populations. Genetics in Medicine, 24 (3). pp. 586-600. ISSN 1098-3600, DOI https://doi.org/10.1016/j.gim.2021.11.008.

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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.

Item Type: Article
Funders: None
Uncontrolled Keywords: Breast cancer; Genetic; Polygenic risk score; Risk prediction
Subjects: R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Divisions: Faculty of Medicine > Biomedical Imaging Department
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 11 Oct 2023 12:03
Last Modified: 11 Oct 2023 12:03
URI: http://eprints.um.edu.my/id/eprint/42333

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