<p>Cancer codes in the UK Biobank.</p>

Whether such shared polygenic risk exhibits structured convergence at regional or functional levels remains unclear. We investigated shared genetic risk across cancers by integrating local genetic correlation analyses with cross-cancer polygenic risk score (PRS) associations.</p> <p>Methods</p><p>We estimated pairwise local genetic correlations across 16 specific cancers and one pan-cancer phenotype using SUPERGNOVA.

Genome regions harboring multiple cancers with mutually correlated local genetic effects were annotated using genetic correlations with non-cancer phenotypes and associations from the GWAS Catalog. In parallel, cross-cancer PRS associations were evaluated, and significant cancer pairs were identified. Genome-wide PRSs for selected pairs were further decomposed into pleiotropy-informed and pathway-specific components to assess functional enrichment of shared polygenic risk.</p> <p>Results</p><p>Genome-wide genetic correlation analyses identified 20 significantly correlated cancer pairs, whereas local analyses revealed 82 regions with shared genetic signals across 66 cancer pairs.