Breast cancer genomic studies have been conducted primarily in European-ancestry populations, limiting diversity and statistical power. To address this, this study increases representation of African- and Asian-ancestry women and expands the European-ancestry sample size to better define inherited susceptibility to breast cancer overall and by subtypes. Genetic association summary data were harmonized for 237,817 breast cancer cases and 1,679,059 controls of African, Asian and European ancestry. Fixed-effect meta-analyses were conducted within and across ancestries for overall breast cancer and subtypes. Transcriptome-wide analyses were carried out in European-ancestry populations to identify candidate susceptibility genes. Candidate genes were assessed for pathway enrichment. We identified 415 risk loci and 196 genes associated with breast cancer risk overall or by subtypes. Of these, 207 loci and 81 genes have not been reported previously. Subtype analyses identify 198 loci and 135 genes for estrogen receptor-positive breast cancer, 69 loci and 35 genes for estrogen receptor-negative breast cancer, and 22 loci and eight genes exclusively associated with triple-negative breast cancer, including 11 loci and four genes not reported previously. Associations for 230 loci and 132 genes differ by estrogen receptor status. Risk genes are enriched in pathways related to transcriptional regulation, estrogen response, mitotic spindle processes and repair of genetic damage. These findings expand the landscape of breast cancer susceptibility and subtype-specific genetic architecture, provide insights into breast cancer biology and genetics. Breast cancer is a the most common malignancy diagnosed among women, and genetic factors can affect a woman’s risk. We conducted a large genetic studies including 237,817 women with breast cancer and 1,679,059 women without breast cancer across African, Asian and European ancestry groups. We found 415 genetic regions and 196 genes linked to breast cancer risk, many of which were not reported before. These results provide insights into breast cancer biology and genetics and enhance risk prediction to identify high-risk women for breast cancer prevention.
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