Over 100 genetic loci harbor schizophrenia associated variants, yet how these variants confer liability is uncertain. The CommonMind Consortium sequenced RNA from dorsolateral prefrontal cortex of schizophrenia cases (N = 258) and control subjects (N = 279), creating a resource of gene expression and its genetic regulation. Using this resource, ~20% of schizophrenia loci have variants that could contribute to altered gene expression and liability. In five loci, only a single gene was involved: FURIN, TSNARE1, CNTN4, CLCN3, or SNAP91. Altering expression of FURIN, TSNARE1, or CNTN4 changes neurodevelopment in zebrafish; knockdown of FURIN in human neural progenitor cells yields abnormal migration. Of 693 genes showing significant case/control differential expression, their fold changes are ≤ 1.33, and an independent cohort yields similar results. Gene co-expression implicates a network relevant for schizophrenia. Our findings show schizophrenia is polygenic and highlight the utility of this resource for mechanistic interpretations of genetic liability for brain diseases.

73Over 100 genetic loci harbor schizophrenia associated variants, yet how these common 74 variants confer risk is uncertain. The CommonMind Consortium has sequenced dorsolateral 75 prefrontal cortex RNA from schizophrenia cases (n=258) and control subjects (n=279), creating 76 the largest publicly available resource to date of gene expression and its genetic regulation; ~5 77 times larger than the latest release of GTEx. Using this resource, we find that ~20% of the 78 schizophrenia risk loci have common variants that could explain regulation of brain gene 79 expression. In five loci, these variants modulate expression of a single gene: FURIN, TSNARE1, 80 CNTN4, CLCN3 or SNAP91. Experimentally altered expression of three of them, FURIN, 81 TSNARE1, and CNTN4, perturbs the proliferation and apoptotic index of neural progenitors and 82 leads to neuroanatomical deficits in zebrafish. Furthermore, shRNA mediated knock-down of 83 FURIN in neural progenitor cells derived from human induced pluripotent stem cells produces 84 abnormal neural migration. Although 4.2% of genes (N = 693) display significant differential 85 expression between cases and controls, 44% show some evidence for differential expression. 86All fold changes are ≤ 1.33, and an independent cohort yields similar differential expression for 87 these 693 genes (r = 0.58). These findings are consistent with schizophrenia being highly 88 polygenic, as has been reported in investigations of common and rare genetic variation. Co-89 expression analyses identify a gene module that shows enrichment for genetic associations and 90 is thus relevant for schizophrenia. Taken together, these results pave the way for mechanistic 91 interpretations of genetic liability for schizophrenia and other brain diseases. 4The human brain is complicated and not well understood. Seemingly straightforward 93 fundamental information such as which genes are expressed therein and what functions they 94 perform are only partially characterized. To overcome these obstacles, we established the 95 CommonMind Consortium (CMC; www.synpase.org/CMC), a public-private partnership to 96 generate functional genomic data in brain samples obtained from autopsies of cases with and 97 without severe psychiatric disorders. The CMC is the largest existing collection of collaborating 98 brain banks and includes over 1,150 samples. A wide spectrum of data is being generated on 99 these samples including regional gene expression, epigenomics (cell-type specific histone 100 modifications and open chromatin), whole genome sequencing, and somatic mosaicism. 101 102 Schizophrenia (SCZ), affecting roughly 0.7% of adults, is a severe psychiatric disorder 103 characterized by abnormalities in thought and cognition (1). Despite a century of evidence 104 establishing its genetic basis, only recently have specific genetic risk factors been conclusively 105identified, including rare copy number variants (2) and >100 common variants (3). However, 106 there is not a one-to-one Mendelian mapping between these SCZ ris...

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Schizophrenia and bipolar disorder are serious mental illnesses that affect more than 2% of adults. While large-scale genetics studies have identified genomic regions associated with disease risk, less is known about the molecular mechanisms by which risk alleles with small effects lead to schizophrenia and bipolar disorder. In order to fill this gap between genetics and disease phenotype, we have undertaken a multi-cohort genomics study of postmortem brains from controls, individuals with schizophrenia and bipolar disorder. Here we present a public resource of functional genomic data from the dorsolateral prefrontal cortex (DLPFC; Brodmann areas 9 and 46) of 986 individuals from 4 separate brain banks, including 353 diagnosed with schizophrenia and 120 with bipolar disorder. The genomic data include RNA-seq and SNP genotypes on 980 individuals, and ATAC-seq on 269 individuals, of which 264 are a subset of individuals with RNA-seq. We have performed extensive preprocessing and quality control on these data so that the research community can take advantage of this public resource available on the Synapse platform at http://CommonMind.org.

Causal genes and variants within genome-wide association study (GWAS) loci can be identified by integrating GWAS statistics with expression quantitative trait loci (eQTL) and determining which variants underlie both GWAS and eQTL signals. Most analyses, however, consider only the marginal eQTL signal, rather than dissect this signal into multiple conditionally independent signals for each gene. Here we show that analyzing conditional eQTL signatures, which could be important under specific cellular or temporal contexts, leads to improved fine mapping of GWAS associations. Using genotypes and gene expression levels from post-mortem human brain samples (n = 467) reported by the CommonMind Consortium (CMC), we find that conditional eQTL are widespread; 63% of genes with primary eQTL also have conditional eQTL. In addition, genomic features associated with conditional eQTL are consistent with context-specific (e.g., tissue-, cell type-, or developmental time point-specific) regulation of gene expression. Integrating the 2014 Psychiatric Genomics Consortium schizophrenia (SCZ) GWAS and CMC primary and conditional eQTL data reveals 40 loci with strong evidence for co-localization (posterior probability > 0.8), including six loci with co-localization of conditional eQTL. Our co-localization analyses support previously reported genes, identify novel genes associated with schizophrenia risk, and provide specific hypotheses for their functional follow-up.