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Cross-ancestry GWAS meta-analysis identifies six breast cancer loci in African and European ancestry women

  • The GBHS Study Team
  • The University of Chicago
  • University of Southern California
  • National Institutes of Health
  • Boston University
  • University of Edinburgh
  • Stanford University
  • City of Hope National Med Center
  • Vanderbilt University
  • University of Miami
  • University of North Carolina at Chapel Hill
  • Rutgers - The State University of New Jersey, New Brunswick
  • Roswell Park Cancer Institute
  • University of Ibadan
  • University of Pennsylvania
  • University of the West Indies
  • Stony Brook University
  • Ohio State University
  • Kaiser Permanente
  • Instituto Nacional de Salud Publica
  • University of California at San Francisco
  • University of Cambridge
  • Cyprus Institute of Neurology and Genetics
  • Korle Bu Teaching Hospital
  • Komfo Anokye Teaching Hospital
  • Peace and Love Hospital

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

Our study describes breast cancer risk loci using a cross-ancestry GWAS approach. We first identify variants that are associated with breast cancer at P < 0.05 from African ancestry GWAS meta-analysis (9241 cases and 10193 controls), then meta-analyze with European ancestry GWAS data (122977 cases and 105974 controls) from the Breast Cancer Association Consortium. The approach identifies four loci for overall breast cancer risk [1p13.3, 5q31.1, 15q24 (two independent signals), and 15q26.3] and two loci for estrogen receptor-negative disease (1q41 and 7q11.23) at genome-wide significance. Four of the index single nucleotide polymorphisms (SNPs) lie within introns of genes (KCNK2, C5orf56, SCAMP2, and SIN3A) and the other index SNPs are located close to GSTM4, AMPD2, CASTOR2, and RP11-168G16.2. Here we present risk loci with consistent direction of associations in African and European descendants. The study suggests that replication across multiple ancestry populations can help improve the understanding of breast cancer genetics and identify causal variants.

Original languageEnglish
Article number4198
JournalNature Communications
Volume12
Issue number1
DOIs
StatePublished - Dec 1 2021

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