Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
23 08 2023
23 08 2023
Historique:
received:
05
09
2022
accepted:
27
06
2023
medline:
25
8
2023
pubmed:
24
8
2023
entrez:
23
8
2023
Statut:
epublish
Résumé
Prostate 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
Identifiants
pubmed: 37612283
doi: 10.1038/s41467-023-39858-8
pii: 10.1038/s41467-023-39858-8
pmc: PMC10447511
doi:
Substances chimiques
Androgens
0
Receptors, Androgen
0
AR protein, human
0
Types de publication
Meta-Analysis
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4863Investigateurs
Akihide Masumoto
(A)
Akiko Nagai
(A)
Daisuke Obata
(D)
Hiroki Yamaguchi
(H)
Kaori Muto
(K)
Kazuhisa Takahashi
(K)
Ken Yamaji
(K)
Kozo Yoshimori
(K)
Masahiko Higashiyama
(M)
Nobuaki Sinozaki
(N)
Satoshi Asai
(S)
Satoshi Nagayama
(S)
Shigeo Murayama
(S)
Shiro Minami
(S)
Takao Suzuki
(T)
Takayuki Morisaki
(T)
Wataru Obara
(W)
Yasuo Takahashi
(Y)
Yoichi Furukawa
(Y)
Yoshinori Murakami
(Y)
Yuji Yamanashi
(Y)
Yukihiro Koretsune
(Y)
Informations de copyright
© 2023. Springer Nature Limited.
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