Integrative Gene-Centric Analysis of Breast Cancer: High-Confidence Germline Predisposition Genes from Population-Scale Cohorts

Background Heritable breast cancer (BC) predisposition is shaped by high-penetrance genes such as BRCA1 and BRCA2, but many moderate- and low-penetrance genes remain uncharacterized. While over 100 independent loci have been reported, their causal genes are often mixed with spurious identifications. Methods Using large-scale, multi-ethnic genomic data from cohorts including the UK Biobank (UKB) and FinnGen (FG), we refined the catalog of BC predisposition genes by requiring consistency across multiple GWAS in Open Targets (OT) and excluding likely false positives, thereby reaffirming the contribution of established genes such as BRCA1, BRCA2, PALB2, CHEK2, and other DNA repair genes. Results Our multi-cohort design enabled replication across European ancestry, although transferability to other populations was limited, as shown in the Million Veteran Program (MVP) cohort. By integrating genome, transcriptome-, and proteome-wide association studies (GWAS, TWAS, and PWAS), we identified 38 high-confidence BC predisposition genes, including eight previously reported drivers, 13 genes supported by multiple lines of evidence, and a set of candidates (e.g., APOBEC3A, TNS1, PEX14) that currently lack supporting evidence in the context of heritable BC. PWAS, a gene-based association approach that assess the aggregated effect of coding variants on protein function was applied for the entire UKB population. A dozen candidate genes were identified, most of them were considered within the core gene set, and additional two genes that match recessive inheritance. Overlap with FG data and additional gene-based models further supported the involvement of moderate- and high-penetrance genes such as DNMT3A and ATM. Conclusions These findings refine the genetic architecture of BC susceptibility, define a core set of predisposition genes, and highlight novel candidates for functional follow-up. The core list of BC susceptibility genes provides biological insights and a framework for gene-based targeted prevention and clinical risk prediction.