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

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.

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Journal
Human Molecular Genetics
Published
2026-01-01
DOI
https://doi.org/10.1093/hmg/ddag015
Primary Topic
Genetic Associations and Epidemiology
Type
article
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article

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

Shivaani Mariapun, Marc Naven, E. K. O. John, John S. Dennis et al.
Human Molecular Genetics
Genetic Associations and Epidemiology
article

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

Shivaani Mariapun, Marc Naven, E. K. O. John, John S. Dennis, Taiki Yamaji, Rachel A. Murphy, Ern Yu Tan, Alexis Jiaying Khng, A. S. H. Wu, Peh Joo Ho, Xuling Chang, Geok Hoon Lim, S C Teo, Sungwon Kim, Wei Zheng, Veronique Kiak‐Mien Tan, Manjeet K. Bolla, MyBrCa Investigators, A. Kwong, Cheng-Har Yip, Chun Hang Au, Daniel O Stram, Artitaya Lophatananon, Mikael Hartman, Ji-Yeob Choi, Alison M Dunning, Weang-Kee Ho, Qin Wang, Kristan J Aronson, Motoki Iwasaki, Kenneth R Muir, Jingmei Li, Douglas F Easton, Nur Aishah Mohd Tai, Mengyu Li, Daehee Kang, Rajkumar s/o Dorajoo, Sue K Park, Ling Wang, Xiao-Ou Shu, Allison W Kurian
article en

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.

Human Molecular GeneticsVol. 35(6)
Agency for Science, Technology and Research (SG), University of Southern California (US), BC Cancer Agency (CA), Seoul National University (KR), University of British Columbia (CA), Mandalay Technological University (MM), University of Nottingham Malaysia Campus (MY), SingHealth (SG), National University of Singapore (SG), Cancer Research Institute (US), Nanyang Technological University (SG), Vanderbilt University (US), Queen's University (CA), Singapore General Hospital (SG), University of Cambridge (GB), Manchester Academic Health Science Centre (GB), Queen Mary Hospital (CN), Tung Wah Hospital (CN), Tan Tock Seng Hospital (SG), New Generation University College (ET), Seoul National University Hospital (KR), University of Malaya (MY), Kyung Hee University (KR), Cancer Research Malaysia (MY), Hong Kong Sanatorium and Hospital (HK), Stanford Health Care (US), Peter Doherty Institute (AU), KK Women's and Children's Hospital (SG), Institute of Molecular and Cell Biology (RU), USC Norris Comprehensive Cancer Center (US), National Cancer Centre Singapore (SG), Subang Jaya Medical Centre (MY), National University Health System (SG), MRC Epidemiology Unit (GB), National Cancer Research Institute (GB), Genome Institute of Singapore (SG), Institute of Molecular and Cell Biology (SG), University of Hong Kong (HK), SEGi University (MY), Stanford University (US)
Good health and well-being
Openalex Percentile: Top 12%
Genetic Associations and Epidemiology
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