The relationship between case-control differential gene expression from brain tissue and genetic associations in schizophrenia

Clifton, Nicholas ORCID: https://orcid.org/0000-0003-2597-5253, Schulmann, Anton, Schizophrenia Working Group of the Psychiatric Genomics Consorti, Holmans, Peter ORCID: https://orcid.org/0000-0003-0870-9412, O'Donovan, Michael ORCID: https://orcid.org/0000-0001-7073-2379 and Vawter, Marquis 2023. The relationship between case-control differential gene expression from brain tissue and genetic associations in schizophrenia. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 192 (5-6) , pp. 85-92. 10.1002/ajmg.b.32931

Preview

PDF - Published Version Available under License Creative Commons Attribution. Download (1MB) | Preview

Abstract

Large numbers of genetic loci have been identified that are known to contain common risk alleles for schizophrenia, but linking associated alleles to specific risk genes remains challenging. Given that most alleles that influence liability to schizophrenia are thought to do so by altered gene expression, intuitively, case–control differential gene expression studies should highlight genes with a higher probability of being associated with schizophrenia and could help identify the most likely causal genes within associated loci. Here, we test this hypothesis by comparing transcriptome analysis of the dorsolateral prefrontal cortex from 563 schizophrenia cases and 802 controls with genome-wide association study (GWAS) data from the third wave study of the Psychiatric Genomics Consortium. Genes differentially expressed in schizophrenia were not enriched for common allelic association statistics compared with other brain-expressed genes, nor were they enriched for genes within associated loci previously reported to be prioritized by genetic fine-mapping. Genes prioritized by Summary-based Mendelian Randomization were underexpressed in cases compared to other genes in the same GWAS loci. However, the overall strength and direction of expression change predicted by SMR were not related to that observed in the differential expression data. Overall, this study does not support the hypothesis that genes identified as differentially expressed from RNA sequencing of bulk brain tissue are enriched for those that show evidence for genetic associations. Such data have limited utility for prioritizing genes in currently associated loci in schizophrenia.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Advanced Research Computing @ Cardiff (ARCCA) MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG) Medicine
Publisher:	Wiley
ISSN:	1552-4841
Funders:	MRC
Date of First Compliant Deposit:	10 January 2023
Date of Acceptance:	5 January 2023
Last Modified:	16 Jul 2024 10:21
URI:	https://orca.cardiff.ac.uk/id/eprint/155631

Actions (repository staff only)

Edit Item