LAUSR

Genome-wide association studies (GWAS) have successfully identified 145 loci implicated in schizophrenia (SCZ). However, the underlying mechanisms remain largely unknown. Here, we analyze 1497 RNA-seq data in combination with their genotype data and identify SNPs that are associated with expression throughout the genome by dissecting expression features to genes (eGene) and exon–exon junctions (eJunction). Then, we colocalize eGene and eJunction with SCZ GWAS using SMR and fine mapping. Multiple ChIP-seq data and DNA methylation data generated from brain were used for identifying the causal variants. Finally, we used a hypothesis-free (no SCZ risk loci considered) enrichment analysis to determine implicated pathways. We identified 171 genes and eight splicing junctions located within four genes ( SNX19 , ARL6IP4 , APOPT1 , and CYP2D6 ) that potentially contribute to SCZ susceptibility. Among the genes, CYP2D6 is significantly associated with SCZ SNPs in eGene and eJunction. In-depth examination of the CYP2D6 region revealed that a nonsynonymous single nucleotide variant rs16947 is strongly associated with a higher abundance of CYP2D6 exon 3 skipping junctions. While we found rs133377 and other functional SNPs in high linkage disequilibrium with rs16947 ( r 2  = 0.9539), histone acetylation analysis showed they are located within active transcription start sites. Furthermore, our data-driven enrichment analysis showed that CYP2D6 is significantly involved in drug metabolism of codeine, tamoxifen, and citalopram. Our study facilitates an understanding of the genetic architecture of SCZ and provides new drug targets.