Presented by Dr. Ting Qi, statistical geneticist at Westlake University, China Most variants identified from genome-wide association studies (G.W.A.S.) in humans are non-coding, suggesting their role in gene regulation. Prior studies have shown considerable links of G.W.A.S. signals to expression quantitative trait loci (eQTLs), but the links to other genetic regulatory mechanisms such as splicing QTLs (sQTLs) are under-explored. Here, we introduced a transcript-based sQTL method (named DISMISS) with improved power for sQTL detection. Applying DISMISS along with LeafCutter, an event-based sQTL method, to brain transcriptomic data, we identified 7491 genes with sQTLs with p value less than 0.00000005, 2598 of which did not have eQTLs. Integrating the eQTL and sQTL data into GWAS for nine neuropsychological traits, we identified 271 genes associated with the traits through sQTLs, 153 of which did not overlap the trait-associated genes identified through eQTLs. Our study demonstrates the use of brain sQTLs as an invaluable means to understand the role of genetic regulation of transcription in neuropsychological traits.