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通过对192个风险区域进行多血统精细定位分析来优化乳腺癌遗传风险与生物学特性

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

作者信息

Jia Guochong, Chen Zhishan, Ping Jie, Cai Qiuyin, Tao Ran, Li Chao, Bauer Joshua A, Xie Yuhan, Ambs Stefan, Barnard Mollie E, Chen Yu, Choi Ji-Yeob, Gao Yu-Tang, Garcia-Closas Montserrat, Gu Jian, Hu Jennifer J, Iwasaki Motoki, John Esther M, Kweon Sun-Seog, Li Christopher I, Matsuda Koichi, Matsuo Keitaro, Nathanson Katherine L, Nemesure Barbara, Olopade Olufunmilayo I, Pal Tuya, Park Sue K, Park Boyoung, Press Michael F, Sanderson Maureen, Sandler Dale P, Shen Chen-Yang, Troester Melissa A, Yao Song, Zheng Ying, Ahearn Thomas, Brewster Abenaa M, Falusi Adeyinka, Hennis Anselm J M, Ito Hidemi, Kubo Michiaki, Lee Eun-Sook, Makumbi Timothy, Ndom Paul, Noh Dong-Young, O'Brien Katie M, Ojengbede Oladosu, Olshan Andrew F, Park Min-Ho, Reid Sonya, Yamaji Taiki, Zirpoli Gary, Butler Ebonee N, Huang Maosheng, Low Siew-Kee, Obafunwa John, Weinberg Clarice R, Zhang Haoyu, Zhao Hongyu, Cote Michelle L, Ambrosone Christine B, Huo Dezheng, Li Bingshan, Kang Daehee, Palmer Julie R, Shu Xiao-Ou, Haiman Christopher A, Guo Xingyi, Long Jirong, Zheng Wei

机构信息

Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA.

Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.

出版信息

Nat Genet. 2025 Jan;57(1):80-87. doi: 10.1038/s41588-024-02031-y. Epub 2025 Jan 3.

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.

摘要

全基因组关联研究已经确定了大约200个乳腺癌的遗传风险位点,但其中的因果变异和靶基因大多未知。我们试图利用来自172737例女性乳腺癌病例以及242009例非洲、亚洲和欧洲血统对照的全基因组关联研究数据,对所有已知的乳腺癌风险位点进行精细定位。我们确定了332个独立的乳腺癌风险关联信号,其中包括131个此前未报告的信号,并且对于其中50个信号,我们将可信的因果变异缩小到了单个变异。整合功能基因组学数据的分析确定了195个推定的易感基因,这些基因在PI3K/AKT、TNF/NF-κB、p53和Wnt/β-连环蛋白通路中富集。单细胞RNA测序或体外实验数据为105个基因提供了额外的功能证据。我们的研究揭示了大量的乳腺癌关联信号和候选易感基因,揭示了乳腺癌的遗传学和生物学特征,并支持了在精细定位分析中纳入多血统数据的价值。

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