Breast cancer genome-wide association studies (GWAS) have identified over 200 independent genome-wide significant susceptibility markers. However, most studies have focused on one or two ancestral groups. We examined breast cancer genetic architecture using GWAS summary statistics from African (AFR), East Asian (EAS), European (EUR) and Hispanic/Latina (H/L) samples, totaling 159, 297 cases and 212, 102 controls, comprising the largest multi-ancestry study of breast cancer to date. The logit-scale heritability of breast cancer ranged from h²=0. 47 (SE = 0. 07) in EAS to AFR h²=0. 61 (SE = 0. 10), with no significant differences across ancestries (p=0. 63). The estimated number of susceptibility markers in a sparse normal-mixture effects model also varied from 4, 446 (SE = 3, 100) in EAS to 8, 308 (SE = 2, 751) in AFR, but differences were not significant across ancestries (p=0. 55). Cross-sample genetic correlations varied, with the strongest correlation between EUR and EAS (ρ=0. 79, SE = 0. 08) and weakest between AFR and H/L (ρ=0. 26, SE = 0. 24). Common variants in regulatory elements were enriched for genetic association across samples. By integrating the GWAS summary statistics with the Tabula Sapiens scRNA-seq atlas, we identified ancestry-shared associations between breast cancer and specific cell types, including innate immune cells, secretory epithelial cells and stromal cells. Collectively, these results support a largely shared polygenic architecture of breast cancer across ancestries, with consistent enrichment of common regulatory variants and convergent cellular signatures identified through single-cell analyses.
Li et al. (Sun,) studied this question.