Our results provide several opportunities for future work. First, the fine-mapped SNPs that we have identified can be prioritized for functional follow-up. Second, fine-mapping results (posterior mean effect sizes) can be used to compute trans-ethnic polygenic risk scores48 which may be less sensitive to LD differences between populations than existing methods49,50. Third, the proximal pairs of coding and non-coding fine-mapped SNPs that we identified (Supplementary Table 25) may aid efforts to link SNPs to genes51–53. Fourth, SNPs that were fine-mapped for multiple genetically uncorrelated traits may shed light on shared biological pathways54. Fifth, sets of SNPs causally explaining 50% of common SNP heritability can potentially be used for gene and pathway enrichment analysis55,56. Finally, PolyFun can incorporate additional functional annotations at negligible additional computational cost, motivating further efforts to identify conditionally informative annotations.
