Re-evaluating genetic variants identified in candidate gene studies of breast cancer risk using data from nearly 280,000 women of Asian and European ancestry
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Re-evaluating genetic variants identified in candidate gene studies of breast cancer risk using data from nearly 280,000 women of Asian and European ancestry
Re-evaluating genetic variants identified in candidate gene studies of breast cancer risk using data from nearly 280,000 women of Asian and European ancestry
Re-evaluating genetic variants identified in candidate gene studies of breast cancer risk using data from nearly 280,000 women of Asian and European ancestry Yang, Yaohua et al. EBioMedicine, Volume 48, 203 - 211
Abstract:
Background:
We previously conducted a systematic field synopsis of 1059 breast cancer candidate gene studies and investigated 279 genetic variants, 51 of which showed associations. The major limitation of this work was the small sample size, even pooling data from all 1059 studies. Thereafter, genome-wide association studies (GWAS) have accumulated data for hundreds of thousands of subjects. It's necessary to re-evaluate these variants in large GWAS datasets.
Methods:
Of these 279 variants, data were obtained for 228 from GWAS conducted within the Asian Breast Cancer Consortium (24,206 cases and 24,775 controls) and the Breast Cancer Association Consortium (122,977 cases and 105,974 controls of European ancestry). Meta-analyses were conducted to combine the results from these two datasets.
Findings:
Of those 228 variants, an association was observed for 12 variants in 10 genes at a Bonferroni-corrected threshold of P
License type:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Funding Info:
This project was supported in part by grants R01CA158473 and R01CA148677 from the U.S. National Institutes of Health , as well as funds from the Anne Potter Wilson endowment. This project was also supported by development funds from the Department of Medicine at the Vanderbilt University Medical Center . Kenneth Muir and Artitaya Lophatananon are supported by the NIHR Manchester Biomedical Research Centre and by the ICEP, which is supported by CRUK ( C18281/A19169 ). Jingmei Li is supported by a National Research Foundation Singapore Fellowship (NRF- NRFF2017-02 ).