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Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes

  • Jie Ping
  • , Guochong Jia
  • , Qiuyin Cai
  • , Xingyi Guo
  • , Ran Tao
  • , Christine Ambrosone
  • , Dezheng Huo
  • , Stefan Ambs
  • , Mollie E. Barnard
  • , Yu Chen
  • , Montserrat Garcia-Closas
  • , Jian Gu
  • , Jennifer J. Hu
  • , Esther M. John
  • , Christopher I. Li
  • , Katherine Nathanson
  • , Barbara Nemesure
  • , Olufunmilayo I. Olopade
  • , Tuya Pal
  • , Michael F. Press
  • Maureen Sanderson, Dale P. Sandler, Toshio Yoshimatsu, Prisca O. Adejumo, Thomas Ahearn, Abenaa M. Brewster, Anselm J.M. Hennis, Timothy Makumbi, Paul Ndom, Katie M. O’Brien, Andrew F. Olshan, Mojisola M. Oluwasanu, Sonya Reid, Song Yao, Ebonee N. Butler, Maosheng Huang, Atara Ntekim, Bingshan Li, Melissa A. Troester, Julie R. Palmer, Christopher A. Haiman, Jirong Long, Wei Zheng
  • Vanderbilt University
  • Roswell Park Cancer Institute
  • The University of Chicago
  • National Institutes of Health
  • Boston University
  • New York University
  • University of Texas MD Anderson Cancer Center
  • University of Miami
  • Stanford University
  • Fred Hutchinson Cancer Research Center
  • University of Pennsylvania
  • University of Southern California
  • Meharry Medical College
  • University of Ibadan
  • The University of the West Indies
  • Stony Brook University
  • Uganda Ministry of Health
  • Yaoundé General Hospital
  • University of North Carolina at Chapel Hill

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

African-ancestry (AA) participants are underrepresented in genetics research. Here, we conducted a transcriptome-wide association study (TWAS) in AA female participants to identify putative breast cancer susceptibility genes. We built genetic models to predict levels of gene expression, exon junction, and 3′ UTR alternative polyadenylation using genomic and transcriptomic data generated in normal breast tissues from 150 AA participants and then used these models to perform association analyses using genomic data from 18,034 cases and 22,104 controls. At Bonferroni-corrected P < 0.05, we identified six genes associated with breast cancer risk, including four genes not previously reported (CTD-3080P12.3, EN1, LINC01956 and NUP210L). Most of these genes showed a stronger association with risk of estrogen-receptor (ER) negative or triple-negative than ER-positive breast cancer. We also replicated the associations with 29 genes reported in previous TWAS at P < 0.05 (one-sided), providing further support for an association of these genes with breast cancer risk. Our study sheds new light on the genetic basis of breast cancer and highlights the value of conducting research in AA populations.

Original languageEnglish
Article number3718
JournalNature Communications
Volume15
Issue number1
DOIs
StatePublished - Dec 2024

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