AnnoPred risk prediction framework has three main stages (Methods). First, we estimate GWAS signal enrichment in 61 different annotation categories, including functional genome predicted by GenoCanyon scores [17], GenoSkyline tissue-specific functionality scores of 7 tissue types [14], and 53 baseline annotations for diverse genomic features [18] for each trait analyzed. Second, we propose an empirical prior of SNP effect size based on annotation assignment and signal enrichment. In general, SNPs located in annotation categories that are highly enriched for GWAS signals receive a higher effect size prior. Finally, the empirical prior is adopted in a Bayesian framework in which marginal summary statistics and LD matrix estimated from a reference panel are jointly modeled to infer the posterior effect size of each SNP. AnnoPred PRS is defined by PRS=∑j=1MXjEA(βj|β^,D^) where Xj and βj are the standardized genotype and effect size of the jth SNP, respectively, β^ is the marginal estimate of β, D^ is the sample LD matrix, and EA(βj|β^,D^) denotes the posterior expectation of effect sizes under an empirical prior based on annotation assignment for all SNPs when adjusting for LD matrix estimated from a reference panel (Methods).
