Some of the SNPs selected through data integration had ranks up to 25 000 in the meta-analysis. Although these SNPs would never have been selected on the basis of their P value, they replicated as well as SNPs selected on the basis of having the top-ranked P values in the meta-analysis without data integration. This demonstrates the value of considering existing data sources. This conclusion also emerges from a study by Ayalew et al,46 who identified and prioritized genes involved in SCZ by gene-level integration of GWAS data with other genetic and gene expression studies. Some of the top findings in their study were the previously reported SCZ candidate gene TCF4 and the pathways involved in synaptic connectivity and glutamate signaling. Following the same concept but using a more statistical approach, we also identified SNPs in TCF4 and identified pathways related to cellular connectivity and signaling. Given that the number of (publicly) available databases and the tools to curate these data are increasing rapidly, future studies should be able to capitalize even more on data integration.
