Downwardly biased estimates of SNP-based heritability will propagate to produce downwardly biased estimates of genetic covariance, which may in turn bias methods that rely on these estimates [e.g., MTAG (6), GenomicSEM (5)]. Importantly, genetic correlations are expected to be unaffected by this bias because they standardize genetic covariance estimates relative to heritability estimates, thereby canceling out the bias. Another issue that merits further investigation is the presence of ascertainment differences that stratify by meaningful covariates across cohorts. For example, it is currently unknown how estimates may be biased when ascertainment varies across GWAS cohorts more for one sex than the other. In addition, it will be important to examine the effect of ascertainment differences when cohorts systematically vary with respect to the severity of cases, as may be observed for meta-analyses of inpatient and community samples.
