In summary, the field standard approach to estimating SNP-based h2 for GWAS meta-analysis of binary traits results in a downward bias because it fails to account for variation in the proportion of cases (i.e., variable levels of ascertainment) across contributing cohorts. Our proposed solution of using ∑EffNk corrects for this bias and is applied at the stage of SNP-based h2 estimation such that it does not require rerunning the GWAS meta-analysis. For most psychiatric traits, ∑EffNk is already available in the GWAS summary statistics or can be straightforwardly computed from information provided in the original publication reporting the GWAS meta-analysis. In addition, we have shown that when ∑EffNk cannot be obtained, it can be straightforwardly approximated from the GWAS summary data. Thus, the use of ∑EffNk can be widely applied for the liability correction going forward so as to produce more accurate estimates of SNP-based heritability.
