Abstract
To date, genome-wide association studies (GWAS) have revealed over 200 genetic risk loci associated with prostate cancer; yet, true disease-causing variants remain elusive. Identification of causal variants and their targets from association signals is complicated by high linkage disequilibrium and limited availability of functional genomics data for specific tissue/cell types. Here, we integrated statistical fine-mapping and functional annotation from prostate-specific epigenomic profiles, 3D genome features, and quantitative trait loci data to distinguish causal variants from associations and identify target genes. Our fine-mapping analysis yielded 3,395 likely causal variants, and multiscale functional annotation linked them to 487 target genes. We prioritized rs10486567 as a genome-wide top-ranked SNP and predicted HOTTIP as its target. Deletion of the rs10486567-associated enhancer in prostate cancer cells decreased their capacity for invasive migration. HOTTIP overexpression in enhancer-KO cell lines rescued defective invasive migration. Furthermore, we found that rs10486567 regulates HOTTIP through allele-specific long-range chromatin interaction.