Genetic Insights of Schizophrenia via Single Cell RNA-Sequencing Analyses

Abstract

Background Schizophrenia is a complex and heterogeneous disorder involving multiple regions and types of cells in the brain. Despite rapid progress made by genome-wide association studies (GWAS) of schizophrenia, the mechanisms of the illness underlying the GWAS significant loci remain less clear. Study Design We investigated schizophrenia risk genes using summary-data-based Mendelian randomization based on single-cell sequencing data, and explored the types of brain cells involved in schizophrenia through the expression weighted cell-type enrichment analysis. Results We identified 54 schizophrenia risk genes (two-thirds of these genes were not identified using sequencing data of bulk tissues) using single-cell RNA-sequencing data. Further cell type enrichment analysis showed that schizophrenia risk genes were highly expressed in excitatory neurons and caudal ganglionic eminence interneurons, suggesting putative roles of these cells in the pathogenesis of schizophrenia. We also found that these risk genes identified using single-cell sequencing results could form a large protein-protein interaction network with genes affected by disease-causing rare variants. Conclusions Through integrative analyses using expression data at single-cell levels, we identified 54 risk genes associated with schizophrenia. Notably, many of these genes were only identified using single-cell RNA-sequencing data, and their altered expression levels in particular types of cells, rather than in the bulk tissues, were related to the increased risk of schizophrenia. Our results provide novel insight into the biological mechanisms of schizophrenia, and future single-cell studies are necessary to further facilitate the understanding of the disorder.

xWAS analysis in neuropsychiatric disorders by integrating multi-molecular phenotype quantitative trait loci and GWAS summary data

“…Firstly, it solely focused on five kinds of molecular phenotypes, while there exist numerous other molecular features that warrant our attention, which may modulate the variants through distinct mechanisms. Moreover, the regulation of many genes is related to spatial context, so QTL effects of a particular cell type in a given developmental stage might be shadowed in this analyses based on bulk tissue [ 19 , 72 ]. Additionally, QTL data tend to be obtained from specific cohorts of individuals, it may influence the genes and gene functional enrichment results observed.…”

Potential marker genes for chronic obstructive pulmonary disease revealed based on single-cell sequencing and Mendelian randomization analysis

“…The exploration of the pathogenesis of COPD through genetic However, with the development of gene sequencing technology, it has been recognized that the regulation of numerous genes is specific to certain cells. Previous sequencing results based on a wide range of tissues may have resulted in the omission of information regarding expression quantitative trait loci (eQTLs) specific to certain cell subtypes [21]. Therefore, the utilization of scRNA-seq technology has become invaluable in the search for crucial COPD genes.…”

“…Thus, the combination of MR analysis with scRNA-seq results may provide greater insight into the mechanisms of development of certain diseases. For example, Wu et al identified in their study that risk genes for schizophrenia were highly expressed in specific neuronal cells and clarified the causal relationship [ 21 ]. Indeed, expression quantitative trait loci (eQTLs) in lung tissues have gained some degree of discovery in the pathogenesis of COPD [ 22 , 23 ].…”

Increasing Ambient GABA Levels in the Hippocampus to Improve Cognition in a Mouse Model of Schizophrenia: A Research Protocol

“…Understanding gene expression changes is crucial because of their impact on neurotransmitter systems, synaptic formation, and neural circuitry, directly affecting behaviour and cognitive functions [59]. Techniques such as RNA sequencing can identify key genes and pathways that are dysregulated, offering insights into the genetic underpinnings of schizophrenia [60]. Simultaneously, examining synaptic plasticity, which encompasses the structural and functional changes in synapses responsible for learning and memory, is essential [17,25].…”