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BACKGROUND: Of the 108 Schizophrenia (SZ) risk-loci discovered through genome-wide association studies (GWAS), 96 are not altering the sequence of any protein. Evidence linking non-coding risk-SNPs and genes may be established using expression quantitative trait loci (eQTL). However, other approaches such allelic expression quantitative trait loci (aeQTL) also may be of use.METHODS: We applied both the eQTL and aeQTL analysis to a biobank of deeply sequenced RNA from 680 dorso-lateral pre-frontal cortex (DLPFC) samples. For each of 340 genes proximal to the SZ risk-SNPs, we asked how much SNP-genotype affected total expression (eQTL), as well as how much the expression ratio between the two alleles differed from 1:1 as a consequence of the risk-SNP genotype (aeQTL).RESULTS: We analyzed overlap with comparable eQTL-findings: 16 of the 30 risk-SNPs known to have gene-level eQTL also had gene-level aeQTL effects. 6 of 21 risk-SNPs with known splice-eQTL had exon-aeQTL effects. 12 novel potential risk genes were identified with the aeQTL approach, while 55 tested SNP-pairs were found as eQTL but not aeQTL. Of the tested 108 loci we could find at least one gene to be associated with 21 of the risk-SNPs using gene-level aeQTL, and with an additional 18 risk-SNPs using exon-level aeQTL.CONCLUSION: Our results suggest that the aeQTL strategy complements the eQTL approach to susceptibility gene identification.

Background Genome-Wide Association Studies (GWAS) have identified many genomic loci associated with risk for schizophrenia, but unambiguous identification of specific risk genes has proved difficult. We investigated the 2 megabase genomic region flanking index SNP rs10791097, the 16th ranked SNP in the 2014 publication from the Psychiatric Genomics Consortium (PGC) GWAS for schizophrenia. Methods We performed RNA sequencing (RNAseq) on samples from human postmortem DLPFC, hippocampus, and caudate from the Lieber Institute Human Brain Repository (N=~495, of which 175 were patients diagnosed with schizophrenia). To detect expression quantitative trait loci (eQTLs), we tested for association between genotypes at regional GWAS schizophrenia risk variants and expressed features at the gene, exon, and junction levels under a simple additive genetic model. Results Dozens of PGC GWAS-significant markers in the region were strongly associated with expressed features in SNX19, with eQTL p values ranging from 3.06E-07 to 1.58E-44. In contrast, eleven other genes in the region produced much weaker results. A junction between exons 8 and 9 defined a canonical class of “full length” SNX19 transcripts (junc8.9 at hg19 position chr11:130750702-130773149) which was only weakly associated with genetic risk. In contrast, the PGC index SNP rs10791097 was associated with expression of a rarer class of transcripts, defined by a junction between exons 8 and 10 (junc8.10, chr11:130749607-130773149), in DLPFC (eQTL p= 5.98E-26), hippocampus (p=1.04E-19), and caudate (p=6.87E-19), with the clinical risk allele (T) predicting greater expression. Many of the junc8.10 eQTLs were confirmed in both GTEx (multiple brain regions) and in the CommonMind Consortium (DLPFC) datasets. Of note, only 46% of the 495 postmortem DLPFC samples had junc8.10 read counts > 0. Discussion In addition, we found highly significant eQTLs across multiple brain regions involving 4 other expressed features: 1) a novel junction at position chr11:130765052-130773149, 2) a novel junction at chr11:130750702-130764497), 3) a known exon at chr11:130762646-130762954, and 4) a known exon at chr11:130763659-130763769. These 4 features defined 4 more independent classes of transcripts, each with the clinical risk alleles predicting greater expression. Across 3 different brain regions, PGC GWAS risk genotypes were associated with expression levels of 5 classes of SNX19 protein coding transcripts. We suggest that a critical element of the molecular mechanism(s) of schizophrenia risk from this GWAS locus is likely to be over-expression in multiple brain regions of multiple SNX19 transcripts and proteins of diverse structure and function.