Psychiatric disorders are widespread throughout the world. Large-scale genome-wide association studies (GWAS) have revealed numerous SNPs associated with a risk for psychiatric disorders. However, the biological mechanisms by which the SNPs contribute to the development of the disease are unknown. Systematical evaluation of the association between the SNPs and various quantitative phenotypes such as levels of gene expression and pathological markers can be a useful approach to identifying the underlying mechanisms. To facilitate this approach, we developed a database named Stanley Integrated Neurogenomic Pathology Database, SNEP-DB, that includes 4,070 neuropathology marker data, gene expression data, and SNPs from samples of the Stanley Medical Research Institute (SMRI) brain collections. Moreover, the database allows users to explore association analysis results from the SMRI brain data integrated with the GWAS results from recent large-scale studies. By exploiting the database, we have identified 43,417 associations between SNPs and levels of neuropathology markers, so-called markerQTLs. We have also identified 77,410 gene-level eQTLs and 129,980 transcript-level eQTLs. We expect SNEP-DB will enable users to explore the mechanisms underlying major psychiatric disorders by identifying significant associations between disease-associated SNPs and various quantitative phenotypes. (Database URL: http://bidas.kaist.ac.kr/snep/)