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A reanalysis of a genome-wide association study on breast cancer in Asian populations using the SG10K_Health reference panel for imputation: a multi-Centre case-control analysis.

Human molecular genetics 2026 Vol.35(6)

Chang X, Mariapun S, Li M, Wang L, Ho PJ, Khng AJ, Muir KR, Lophatananon A, Aronson KJ, Murphy RA, Kwong A, Au CH, Kim SW, Park SK, Stram DO, Wu AH, Teo SH, Yip CH, Tai NAM, John EM, Kurian AW, Iwasaki M, Yamaji T, Choi JY, Kang D, Shu XO, Zheng W, Hartman M, Tan EY, Tan VK, Lim GH, Bolla MK, Dunning AM, Dennis J, Wang Q, Naven M, Easton DF, Dorajoo RS, Ho WK, Li J

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Genome-wide association studies (GWAS) have identified numerous genetic variants linked to breast cancer risk, but most discoveries come from European populations, limiting their applicability to othe

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BibTeX ↓ RIS ↓
APA Chang X, Mariapun S, et al. (2026). A reanalysis of a genome-wide association study on breast cancer in Asian populations using the SG10K_Health reference panel for imputation: a multi-Centre case-control analysis.. Human molecular genetics, 35(6). https://doi.org/10.1093/hmg/ddag015
MLA Chang X, et al.. "A reanalysis of a genome-wide association study on breast cancer in Asian populations using the SG10K_Health reference panel for imputation: a multi-Centre case-control analysis.." Human molecular genetics, vol. 35, no. 6, 2026.
PMID 41871294
DOI 10.1093/hmg/ddag015

Abstract

Genome-wide association studies (GWAS) have identified numerous genetic variants linked to breast cancer risk, but most discoveries come from European populations, limiting their applicability to other populations. Here, we show that the choice of genotype imputation reference panel, an essential step for GWAS, affects variant detection in Asian populations. Using two large breast cancer datasets from the Breast Cancer Association Consortium (n = 38 954 Asian samples), we compared the 1000 Genomes (1KG) reference panel with SG10K_Health (SG10K), an Asian-specific panel. SG10K imputed more rare variants and achieved higher accuracy for rare alleles (MAF < 0.001), while 1KG performed better for common variants in some contexts. Differences in panel performance influenced association signals, including breast cancer candidate loci such as FGFR2, TOX3, and ESR1. Together, these findings support the use of population-specific imputation panels as a means to improve variant discovery in underrepresented populations.

MeSH Terms

Humans; Breast Neoplasms; Genome-Wide Association Study; Female; Asian People; Case-Control Studies; Genetic Predisposition to Disease; Polymorphism, Single Nucleotide; Receptor, Fibroblast Growth Factor, Type 2; Estrogen Receptor alpha; Alleles; Genotype; Receptors, Progesterone; Trans-Activators; Apoptosis Regulatory Proteins

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