Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects
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Published:2023-08-23
Issue:1
Volume:14
Page:
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ISSN:2041-1723
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Container-title:Nature Communications
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language:en
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Short-container-title:Nat Commun
Author:
Ito Shuji, Liu Xiaoxi, Ishikawa YukiORCID, Conti David D., Otomo Nao, Kote-Jarai Zsofia, Suetsugu Hiroyuki, Eeles Rosalind A.ORCID, Koike YoshinaoORCID, Hikino KeikoORCID, Yoshino Soichiro, Tomizuka Kohei, Horikoshi MomokoORCID, Ito KaoruORCID, Uchio Yuji, Momozawa YukihideORCID, Kubo Michiaki, Masumoto Akihide, Nagai Akiko, Obata Daisuke, Yamaguchi Hiroki, Muto Kaori, Takahashi Kazuhisa, Yamaji Ken, Yoshimori Kozo, Higashiyama Masahiko, Sinozaki Nobuaki, Asai Satoshi, Nagayama Satoshi, Murayama Shigeo, Minami Shiro, Suzuki Takao, Morisaki Takayuki, Obara Wataru, Takahashi Yasuo, Furukawa Yoichi, Murakami Yoshinori, Yamanashi Yuji, Koretsune Yukihiro, Kamatani YoichiroORCID, Matsuda KoichiORCID, Haiman Christopher A., Ikegawa Shiro, Nakagawa HidewakiORCID, Terao ChikashiORCID,
Abstract
AbstractProstate cancer (PrCa) is the second most common cancer worldwide in males. While strongly warranted, the prediction of mortality risk due to PrCa, especially before its development, is challenging. Here, we address this issue by maximizing the statistical power of genetic data with multi-ancestry meta-analysis and focusing on binding sites of the androgen receptor (AR), which has a critical role in PrCa. Taking advantage of large Japanese samples ever, a multi-ancestry meta-analysis comprising more than 300,000 subjects in total identifies 9 unreported loci including ZFHX3, a tumor suppressor gene, and successfully narrows down the statistically finemapped variants compared to European-only studies, and these variants strongly enrich in AR binding sites. A polygenic risk scores (PRS) analysis restricting to statistically finemapped variants in AR binding sites shows among cancer-free subjects, individuals with a PRS in the top 10% have a strongly higher risk of the future death of PrCa (HR: 5.57, P = 4.2 × 10−10). Our findings demonstrate the potential utility of leveraging large-scale genetic data and advanced analytical methods in predicting the mortality of PrCa.
Funder
MEXT | Japan Society for the Promotion of Science Japan Agency for Medical Research and Development
Publisher
Springer Science and Business Media LLC
Subject
General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry,Multidisciplinary
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