{"doi":"10.1002/ijc.70041","title":"Integrating multi‐ancestry genomic and proteomic data to identify blood risk biomarkers and target proteins for breast cancer genetic risk loci","abstract":"Abstract Genome‐wide association studies (GWAS) have identified more than 200 risk loci for breast cancer. However, target genes and their encoded proteins in these loci remain largely unknown. In this study, we utilized genetic prediction models for 1349 circulating proteins derived from individuals of African ( n = 1871) and European ( n = 7213) ancestry to investigate genetically predicted protein levels in association with breast cancer risk among females of African ( n = 40,138), Asian ( n = 137,677), and European ( n = 247,173) ancestry. We identified 51 blood protein biomarkers associated with breast cancer risk, overall or by subtypes, at a false discovery rate (FDR) < 0.05, including 27 proteins encoded by genes located at least 1 Mb away from any of the known risk loci identified in GWAS. Of them, 32 proteins showed significant associations with breast cancer risk at the Bonferroni‐corrected significance level ( p < 2.45 × 10 −4 ). Of the 24 proteins located at GWAS‐identified risk loci, associations for 14 proteins were significantly attenuated after adjustment for the index risk variant of each respective locus, suggesting that these proteins may be target proteins for the risk loci. Encoding gene expression levels in normal breast tissue could be genetically predicted for 23 of the 51 identified proteins, and 13 encoding genes were associated with breast cancer risk in the same direction ( p < .05). Our study identified potential protein targets of GWAS risk loci and biomarkers for breast cancer risk and provided additional insights into breast cancer genetics and etiology.","journal":"International Journal of Cancer","year":2025,"id":570218,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7355,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":385972,"name":"Jie Ping","orcid":"0000-0001-9907-5819","position":1,"is_corresponding":false},{"id":1184167,"name":"Ran Tao","orcid":"0000-0001-5461-5930","position":2,"is_corresponding":false},{"id":240075,"name":"Jirong Long","orcid":"0000-0002-7433-9766","position":3,"is_corresponding":false},{"id":1475596,"name":"Lili Liu","orcid":"0000-0002-6035-3583","position":4,"is_corresponding":false},{"id":827173,"name":"Shuai Xu","orcid":"0000-0002-7798-5720","position":5,"is_corresponding":false},{"id":407005,"name":"Heather M. 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