As sample sizes in GWAS continue to grow, we will begin to uncover thousands of variants associated with psychiatric risk. If we consider each variant an individual brushstroke, mechanistic studies look to zoom out to understand the biological picture being painted (Gandal, Leppa, Won, Parikshak, & Geschwind, 2016). This is achieved by grouping variants together based on functional characteristics, such as the specific tissue types (e.g., certain areas of the brain) or when in development the genes are expressed. These characteristics are typically identified using collateral gene expression data, such as single-cell RNA sequencing. Mechanistic approaches thereby offer a means of distilling the thousands of constituent parts (genetic risk variants) down to a handful of cohesive, biological targets (Figure 1b). Within the PGC, a number of exciting results have already emerged. In the first major cross-disorder effort (Cross Disorder Working Group of the Psychiatric Genomics Consortium, 2013), genes involved in calcium channel signaling were found to be associated with ASD, ADHD, SCZ, major depressive disorder (MDD), and bipolar disorder (BIP). In follow-up work from the PGC Network and Pathways Analysis
