bioRxivGenomics
Gene Expression Elucidates Functional Impact of Polygenic Risk for Schizophrenia
Menachem FromeriD, Panos RoussosiD, Solveig K Sieberts, Jessica S Johnson, David H Kavanagh, Thanneer M Perumal, Douglas M Ruderfer, Edwin C Oh, Aaron Topol, Hardik R Shah, Lambertus L Klei, Robin KrameriD, Dalila PintoiD, Zeynep H Gumus, A. Ercument Cicek, Kristen Dang, Andrew Browne, Cong Lu, Li Xie, Ben ReadheadiD, Eli A Stahl, Mahsa Parvisi, Tymor Hamamsy, John F Fullard, Ying-Chih Wang, , Lara M Mangravit
Abstract
Over 100 genetic loci harbor schizophrenia associated variants, yet how these common variants confer risk is uncertain. The CommonMind Consortium has sequenced dorsolateral prefrontal cortex RNA from schizophrenia cases (n=258) and control subjects (n=279), creating the largest publicly available resource to date of gene expression and its genetic regulation; [~]5 times larger than the latest release of GTEx. Using this resource, we find that [~]20% of the schizophrenia risk loci have common variants that could explain regulation of brain gene expression. In five loci, these variants modulate expression of a single gene: FURIN, TSNARE1, CNTN4, CLCN3 or SNAP91. Experimentally altered expression of three of them, FURIN, TSNARE1, and CNTN4, perturbs the proliferation and apoptotic index of neural progenitors and leads to neuroanatomical deficits in zebrafish. Furthermore, shRNA mediated knock-down of FURIN1 in neural progenitor cells derived from human induced pluripotent stem cells produces abnormal neural migration. Although 4.2% of genes (N = 693) display significant differential expression between cases and controls, 44% show some evidence for differential expression. All fold changes are [≤] 1.33, and an independent cohort yields similar differential expression for these 693 genes (r = 0.58). These findings are consistent with schizophrenia being highly polygenic, as has been reported in investigations of common and rare genetic variation. Co-expression analyses identify a gene module that shows enrichment for genetic associations and is thus relevant for schizophrenia. Taken together, these results pave the way for mechanistic interpretations of genetic liability for schizophrenia and other brain diseases.
- organism: human
- organism: zebrafish
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
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