1. Cross-ancestry GWAS meta-analysis identifies six breast cancer loci in African and European ancestry women.
- Author
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Adedokun B, Du Z, Gao G, Ahearn TU, Lunetta KL, Zirpoli G, Figueroa J, John EM, Bernstein L, Zheng W, Hu JJ, Ziegler RG, Nyante S, Bandera EV, Ingles SA, Press MF, Deming-Halverson SL, Rodriguez-Gil JL, Yao S, Ogundiran TO, Ojengbede O, Blot W, Troester MA, Nathanson KL, Hennis A, Nemesure B, Ambs S, Fiorica PN, Sucheston-Campbell LE, Bensen JT, Kushi LH, Torres-Mejia G, Hu D, Fejerman L, Bolla MK, Dennis J, Dunning AM, Easton DF, Michailidou K, Pharoah PDP, Wang Q, Sandler DP, Taylor JA, O'Brien KM, Kitahara CM, Falusi AG, Babalola C, Yarney J, Awuah B, Addai-Wiafe B, Chanock SJ, Olshan AF, Ambrosone CB, Conti DV, Ziv E, Olopade OI, Garcia-Closas M, Palmer JR, Haiman CA, and Huo D
- Subjects
- Female, Genome-Wide Association Study, Humans, Introns, Polymorphism, Single Nucleotide, Black People genetics, Breast Neoplasms genetics, Genetic Predisposition to Disease, Quantitative Trait Loci, White People genetics
- 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.
- Published
- 2021
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