Such approaches could also be implemented without one’s own independent data using available databases of basal gene expression (e.g., GTEx (Consortium, 2013), Braineac (Hardy et al., 2009), CommonMind (Fromer et al., 2016)) and methylation to prioritize variants across the entire genome. Similar approaches have been used to functionally partition SNP-h2 using functional annotation. (Gusev et al., 2014, Finucane et al., 2015). Such integration may enhance the biological plausibility of disease associated variants and potentially enhance their power. However, such an approach becomes clearly dependent on the quality of data in both contributing datasets and currently available databases of biological phenotypes such as mRNA expression, which are typically composed of small samples with restricted age ranges and tissue types, as well as a lack of detailed phenotypic and exposure characterization. For instance, many psychiatric disorders are precipitated by stress. Given that stress responsive systems can have direct effects on gene transcription it may be important to consider stress-related gene transcription for such phenotypes (Arloth et al., 2015) and basal expression may not be as informative. Consistent with this notion, glucocorticoid-related gene
