Current mid-pipeline translational studies use either a “best guess” approach or a “top hits” approach to select genetic markers to include in GRSs. The “best guess” approach selects markers identified in association studies that are located in or near genes with plausible biological relationships to the pathophysiology of a phenotype or that demonstrate strong and replicable association signals 24–26. The “top hits” approach selects markers with the strongest association signals in a single GWAS, independent of their biological plausibility 27,28. Early studies have illustrated the promise of translational research with GWAS markers, but as the field moves forward, more systematic approaches are needed that can better integrate new information from the latest studies. Neither the top-hits nor the best-guess approach provides a systematic and replicable means of integrating results from multiple GWAS. Meta-analysis can accomplish this, but comprehensive meta-analyses are not always available. Moreover, the top-hits and best-guess approaches do not provide a means to select specific SNPs for follow-up, and this problem is not solved by meta-analysis. The approach of selecting the “lead” SNP at a locus, usually the
