Abstract
Schizophrenia is a complex highly heritable disorder. Genome-wide association studies (GWAS) have identified multiple loci that influence the risk of developing schizophrenia, although the causal variants driving these associations and their impacts on specific genes are largely unknown. We identify a significant correlation between schizophrenia risk and expression at 89 genes in the dorsolateral prefrontal cortex (P ≤ 9.43 × 10−6), including 20 novel genes. Genes whose expression correlate with schizophrenia were enriched for those involved in abnormal CNS synaptic transmission (PFDR = 0.02) and antigen processing and presentation of peptide antigen via MHC class I (PFDR = 0.02). Within the CNS synaptic transmission set, we identify individual significant candidate genes to which we assign direction of expression changes in schizophrenia. The findings provide strong candidates for experimentally probing the molecular basis of synaptic pathology in schizophrenia.
Highlights
Schizophrenia [OMIM: 181500] is a severe psychiatric disorder which typically manifests in late adolescence or early adulthood [1]
We identify a significant correlation between schizophrenia risk and expression at 89 genes in the dorsolateral prefrontal cortex (P ≤ 9.43 × 10−6), including 20 novel genes
Of the 5301 genes modeled in our data with significant cisheritable expression in the dorsolateral prefrontal cortex (DLPFC), 89 returned a significant transcriptome-wide association studies (TWAS) association signal (P ≤ 9.43 × 10−6)
Summary
Schizophrenia [OMIM: 181500] is a severe psychiatric disorder which typically manifests in late adolescence or early adulthood [1]. Genetic studies have shown that schizophrenia is multifactorial but highly heritable. The genetic contribution is polygenic, involving large numbers of risk alleles spanning the full spectrum of possible allele frequencies [2,3,4]. The most recent genome-wide association study (GWAS) reported 174 independent association signals representing 145 distinct associated loci [2]. Each genetic locus identified by GWAS provides an opportunity to expose a biological mechanism bridging statistical association and disease. The imprecision inherent in GWAS makes extracting biological information from these studies challenging.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
