A-G.50: Ancestry calibrated polygenic risk score for breast cancer risk stratification in an admixed Colombian cohort
Breast cancer (BC) polygenic risk scores (PRS) derived from European GWAS often lack transferability to admixed Latin Americans due to tri-ancestral genomic backgrounds, European (EUR), Native American (NAM), and African (AFR), which alter allele frequencies and linkage disequilibrium. Ancestry-unaware models risk systematic miscalibration, hindering equitable clinical implementation.
We enrolled 1,997 Colombian women (ages 40–65) in a translational precision medicine program at Biosciences unit Grupo SURA (2022–2024). Genotyping (Illumina GSA v3) was followed by phasing (Eagle v2.4.1) and imputation (TOPMed Freeze 8). Ancestry proportions were inferred via ADMIXTURE (K=3) using the HGDP panel. Risk modeling integrated: (i) a genome-wide PRS from established BC loci, (ii) principal components as calibration covariates, and (iii) modifiable clinical variables. To date, 32 incident BC cases have been identified among the cohort, with ~700 baseline controls under prospective follow-up.
Ancestry inference revealed a tri-ethnic profile (EUR: 0.59, NAM: 0.30, AFR: 0.11). The integrated genomic-clinical model achieved an AUC of 77.6% (OR per SD: 1.87; 95% CI: 1.68–2.07), with 72.6% accuracy, 67.7% sensitivity, and 74.3% specificity. Notably, the model yielded a Net Reclassification Improvement (NRI) of 48% and an NPV of 86.9%.
Integrating ancestry calibrated PRS with clinical factors substantially enhances BC risk discrimination in admixed populations. With 32 prospectively ascertained cases, this cohort serves as a critical resource for validating polygenic risk in Latin America, underscoring the necessity of diverse genomic data to achieve precision oncology.
Co-authors: Danny Styvens Cardona Pineda, Harvy Mauricio Velzco
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