Human Molecular GeneticsGeneticsPeer-reviewed journal article
A Transcriptome Wide Association Study implicates specific pre- and post-synaptic abnormalities in Schizophrenia
Lynsey S. HalliD, Christopher William Medway, Oliver PainiD, Antonio F. PardiñasiD, Elliott ReesiD, Valentina Escott‐PriceiD, Andrew J. PocklingtoniD, Nicholas J. BrayiD, Peter HolmansiD, James WaltersiD, Michael John OweniD, Michael C. O’DonovaniD
Abstract
Schizophrenia is a complex highly heritable disorder. Genome-wide association studies 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. Here we link genetic findings to gene expression in the human brain by performing a transcriptome-wide association study (TWAS) in which we integrate the largest published genome-wide association dataset of schizophrenia, with publically available post mortem expression data from the dorsolateral prefrontal cortex (DLPFC). We identify a significant correlation between schizophrenia risk and expression at eighty-nine genes in DLPFC, including forty-two genes not identified in earlier TWAS of this transcriptomic resource. Genes whose expression correlate with schizophrenia were enriched for those involved in nervous system development, abnormal synaptic transmission, reduced long term potentiation, and calcium-dependent cell-cell adhesion. Previous genetic studies have implicated post-synaptic glutamatergic and gabaergic processes in schizophrenia; here we extend this to include molecules that regulate presynaptic transmitter release. We identify specific candidate genes to which we assign predicted directions of effect in terms of expression level, facilitating downstream experimental studies geared towards a better mechanistic understanding of schizophrenia pathogenesis.
- organism: human
- assay: bulk RNA-seq
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 73
- FWCI
- 7.95
- Field percentile
- top 2%
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