Genome-Wide Association Study of Breast Cancer in the Japanese Population

Siew Kee Low, Atsushi Takahashi, Kyota Ashikawa, Johji Inazawa, Yoshio Miki, Michiaki Kubo, Yusuke Nakamura, Toyomasa Katagiri

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34 Citations (Scopus)


Breast cancer is the most common malignancy among women in worldwide including Japan. Several studies have identified common genetic variants to be associated with the risk of breast cancer. Due to the complex linkage disequilibrium structure and various environmental exposures in different populations, it is essential to identify variants associated with breast cancer in each population, which subsequently facilitate the better understanding of mammary carcinogenesis. In this study, we conducted a genome-wide association study (GWAS) as well as whole-genome imputation with 2,642 cases and 2,099 unaffected female controls. We further examined 13 suggestive loci (P<1.0×10-5) using an independent sample set of 2,885 cases and 3,395 controls and successfully validated two previously-reported loci, rs2981578 (combined P-value of 1.31×10-12, OR = 1.23; 95% CI = 1.16-.30) on chromosome 10q26 (FGFR2), rs3803662 (combined P-value of 2.79×10-11, OR = 1.21; 95% CI = 1.15-.28) and rs12922061 (combined P-value of 3.97×10-10, OR = 1.23; 95% CI = 1.15-.31) on chromosome 16q12 (TOX3-LOC643714). Weighted genetic risk score on the basis of three significantly associated variants and two previously reported breast cancer associated loci in East Asian population revealed that individuals who carry the most risk alleles in category 5 have 2.2 times higher risk of developing breast cancer in the Japanese population than those who carry the least risk alleles in reference category 1. Although we could not identify additional loci associated with breast cancer, our study utilized one of the largest sample sizes reported to date, and provided genetic status that represent the Japanese population. Further local and international collaborative study is essential to identify additional genetic variants that could lead to a better, accurate prediction for breast cancer.

Original languageEnglish
Article numbere76463
JournalPloS one
Issue number10
Publication statusPublished - 15-10-2013
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General


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