been proposed for the purpose of fine-mapping functional variants [16, 20, 21]. Whether these models could be adapted to benefit risk prediction accuracy remains to be investigated in the future. Importantly, the rich collection of publicly available integrative annotation data, in conjunction with the increasing accessibility of GWAS summary statistics, makes AnnoPred a customizable and powerful tool. As GWAS sample size continues to grow, AnnoPred has the potential to achieve even better prediction accuracy and become widely adopted as a summary of genetic contribution in clinical applications of risk prediction.
