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

Authors
 Weang-Kee Ho  ;  Mei-Chee Tai  ;  Joe Dennis  ;  Xiang Shu  ;  Jingmei Li  ;  Peh Joo Ho  ;  Iona Y Millwood  ;  Kuang Lin  ;  Yon-Ho Jee  ;  Su-Hyun Lee  ;  Nasim Mavaddat  ;  Manjeet K Bolla  ;  Qin Wang  ;  Kyriaki Michailidou  ;  Jirong Long  ;  Eldarina Azfar Wijaya  ;  Tiara Hassan  ;  Kartini Rahmat  ;  Veronique Kiak Mien Tan  ;  Benita Kiat Tee Tan  ;  Su Ming Tan  ;  Ern Yu Tan  ;  Swee Ho Lim  ;  Yu-Tang Gao  ;  Ying Zheng  ;  Daehee Kang  ;  Ji-Yeob Choi  ;  Wonshik Han  ;  Han-Byoel Lee  ;  Michiki Kubo  ;  Yukinori Okada  ;  Shinichi Namba  ;  BioBank Japan Project  ;  Sue K Park  ;  Sung-Won Kim  ;  Chen-Yang Shen  ;  Pei-Ei Wu  ;  Boyoung Park  ;  Kenneth R Muir  ;  Artitaya Lophatananon  ;  Anna H Wu  ;  Chiu-Chen Tseng  ;  Keitaro Matsuo  ;  Hidemi Ito  ;  Ava Kwong  ;  Tsun L Chan  ;  Esther M John  ;  Allison W Kurian  ;  Motoki Iwasaki  ;  Taiki Yamaji  ;  Sun-Seog Kweon  ;  Kristan J Aronson  ;  Rachel A Murphy  ;  Woon-Puay Koh  ;  Chiea-Chuen Khor  ;  Jian-Min Yuan  ;  Rajkumar Dorajoo  ;  Robin G Walters  ;  Zhengming Chen  ;  Liming Li  ;  Jun Lv  ;  Keum-Ji Jung  ;  Peter Kraft  ;  Paul D B Pharoah  ;  Alison M Dunning  ;  Jacques Simard  ;  Xiao-Ou Shu  ;  Cheng-Har Yip  ;  Nur Aishah Mohd Taib  ;  Antonis C Antoniou  ;  Wei Zheng  ;  Mikael Hartman  ;  Douglas F Easton  ;  Soo-Hwang Teo 
Citation
 GENETICS IN MEDICINE, Vol.24(3) : 586-600, 2022-03 
Journal Title
GENETICS IN MEDICINE
ISSN
 1098-3600 
Issue Date
2022-03
MeSH
Bayes Theorem ; Breast Neoplasms* / epidemiology ; Breast Neoplasms* / genetics ; Female ; Genetic Predisposition to Disease ; Genome-Wide Association Study ; Humans ; Multifactorial Inheritance / genetics ; Polymorphism, Single Nucleotide / genetics ; Prospective Studies ; Risk Factors
Keywords
Breast cancer ; Genetic ; Polygenic risk score ; Risk prediction
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.
Files in This Item:
T202202993.pdf Download
DOI
10.1016/j.gim.2021.11.008
Appears in Collections:
4. Graduate School of Public Health (보건대학원) > Graduate School of Public Health (보건대학원) > 1. Journal Papers
Yonsei Authors
Jung, Keum Ji(정금지) ORCID logo https://orcid.org/0000-0003-4993-0666
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/189566
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