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Refining breast cancer genetic risk and biology through multi-ancestry fine-mapping analyses of 192 risk regions

Authors
Jia, GuochongChen, ZhishanPing, JieCai, QiuyinTao, RanLi, ChaoBauer, Joshua A.Xie, YuhanPark, BoyoungZheng, WeiAmbs, StefanBarnard, Mollie E.Chen, YuChoi, Ji-YeobGao, Yu-TangGarcia-Closas, MontserratGu, JianHu, Jennifer J.Iwasaki, MotokiJohn, Esther M.Kweon, Sun-SeogLi, Christopher I.Matsuda, KoichiMatsuo, KeitaroNathanson, Katherine L.Nemesure, BarbaraOlopade, Olufunmilayo I.Pal, TuyaPark, Sue K.Press, Michael F.Sanderson, MaureenSandler, Dale P.Shen, Chen-YangTroester, Melissa A.Yao, SongZheng, YingAhearn, ThomasBrewster, Abenaa M.Falusi, AdeyinkaHennis, Anselm J. M.Ito, HidemiKubo, MichiakiLee, Eun-SookMakumbi, TimothyNdom, PaulNoh, Dong-YoungO’Brien, Katie M.Ojengbede, OladosuOlshan, Andrew F.Park, Min-HoReid, SonyaYamaji, TaikiZirpoli, GaryButler, Ebonee N.Huang, MaoshengLow, Siew-KeeObafunwa, JohnWeinberg, Clarice R.Zhang, HaoyuZhao, HongyuCote, Michelle L.Ambrosone, Christine B.Huo, DezhengLi, BingshanKang, DaeheePalmer, Julie R.Shu, Xiao-OuHaiman, Christopher A.Guo, XingyiLong, Jirong
Issue Date
Jan-2025
Publisher
Nature Publishing Group
Citation
Nature Genetics, v.57, no.1, pp 80 - 87
Pages
8
Indexed
SCIE
SCOPUS
Journal Title
Nature Genetics
Volume
57
Number
1
Start Page
80
End Page
87
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/207179
DOI
10.1038/s41588-024-02031-y
ISSN
1061-4036
1546-1718
Abstract
Genome-wide association studies have identified approximately 200 genetic risk loci for breast cancer, but the causal variants and target genes are mostly unknown. We sought to fine-map all known breast cancer risk loci using genome-wide association study data from 172,737 female breast cancer cases and 242,009 controls of African, Asian and European ancestry. We identified 332 independent association signals for breast cancer risk, including 131 signals not reported previously, and for 50 of them, we narrowed the credible causal variants down to a single variant. Analyses integrating functional genomics data identified 195 putative susceptibility genes, enriched in PI3K/AKT, TNF/NF-κB, p53 and Wnt/β-catenin pathways. Single-cell RNA sequencing or in vitro experiment data provided additional functional evidence for 105 genes. Our study uncovered large numbers of association signals and candidate susceptibility genes for breast cancer, uncovered breast cancer genetics and biology, and supported the value of including multi-ancestry data in fine-mapping analyses.
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