The relationship between case-control differential gene expression from brain tissue and genetic associations in schizophrenia.
Nicholas E CliftonAnton Schulmannnull nullPeter A HolmansMichael C O'DonovanMarquis P VawterPublished in: American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics (2023)
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.
Keyphrases
- genome wide
- dna methylation
- gene expression
- bipolar disorder
- genome wide association study
- bioinformatics analysis
- case control
- genome wide identification
- copy number
- prefrontal cortex
- white matter
- big data
- mental health
- working memory
- poor prognosis
- multiple sclerosis
- transcription factor
- genome wide analysis
- brain injury
- binding protein
- subarachnoid hemorrhage