medRxivGenetic & Genomic MedicinePreprint
Deciphering the Genomic architecture of three major Cancers in African-Ancestry Populations
David EnomaiD, Anthony Micheal Idedia, Christogonus Chichebe EkenwanezeiD, Omoremime Elizabeth DaniaiD, Olubanke Olujoke OgunlanaiD
Abstract
Genomic studies of cancer risk have disproportionately focused on populations of European ancestry, limiting biological insight and risk prediction in African-ancestry populations that experience a high burden of disease. Here, we analysed breast, colorectal, and prostate cancers in African-ancestry participants from the UK Biobank using ancestry-aware genome-wide association studies (GWAS), SNP-based heritability estimation, fine-mapping, transcriptome-wide association studies (TWAS), and polygenic risk scoring (PRS). SNP-based heritability analyses revealed a comparatively high point estimate of common-variant heritability for colorectal cancer risk in African-ancestry individuals, alongside more modest estimates for breast and prostate cancer. Five loci reached genome-wide significance (p < 5x10-{square}), including four colorectal cancer loci (notably rs111448231 in RYR2) and one novel breast cancer locus (rs78768133). Gene-based burden testing identified eight prostate cancer-associated genes (MRPL45, PSMD8, GGN, SPRED3, FAM98C, BCLAF1, MTFR2, and NELL2) with FDR-significant associations, clustering within biologically plausible chromosomal regions on chr19q13 and chr6q23. Transcriptome-wide association analysis identified CYTH2 (ENSG00000105443.13) as a significant gene for prostate cancer. Polygenic risk scores incorporating African-ancestry linkage disequilibrium demonstrated heterogeneous predictive performance across cancers, with modest discrimination for colorectal and breast cancer and substantially stronger performance for prostate cancer (AUC = 0.89). Together, these findings delineate ancestry-relevant cancer genetic architectures and demonstrate the importance of population-matched genomic approaches for equitable precision oncology.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- research focus: fine-mapping
- research focus: polygenic risk
- approach: statistical model
- Citations
- 0
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