Cargando…

Genetic Insights of Schizophrenia via Single Cell RNA-Sequencing Analyses

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....

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Yong, Zhang, Chu-Yi, Wang, Lu, Li, Yi, Xiao, Xiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10318862/
https://www.ncbi.nlm.nih.gov/pubmed/36805283
http://dx.doi.org/10.1093/schbul/sbad002
_version_ 1785068132521476096
author Wu, Yong
Zhang, Chu-Yi
Wang, Lu
Li, Yi
Xiao, Xiao
author_facet Wu, Yong
Zhang, Chu-Yi
Wang, Lu
Li, Yi
Xiao, Xiao
author_sort Wu, Yong
collection PubMed
description 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.
format Online
Article
Text
id pubmed-10318862
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-103188622023-07-05 Genetic Insights of Schizophrenia via Single Cell RNA-Sequencing Analyses Wu, Yong Zhang, Chu-Yi Wang, Lu Li, Yi Xiao, Xiao Schizophr Bull Regular Articles 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. Oxford University Press 2023-02-20 /pmc/articles/PMC10318862/ /pubmed/36805283 http://dx.doi.org/10.1093/schbul/sbad002 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Regular Articles
Wu, Yong
Zhang, Chu-Yi
Wang, Lu
Li, Yi
Xiao, Xiao
Genetic Insights of Schizophrenia via Single Cell RNA-Sequencing Analyses
title Genetic Insights of Schizophrenia via Single Cell RNA-Sequencing Analyses
title_full Genetic Insights of Schizophrenia via Single Cell RNA-Sequencing Analyses
title_fullStr Genetic Insights of Schizophrenia via Single Cell RNA-Sequencing Analyses
title_full_unstemmed Genetic Insights of Schizophrenia via Single Cell RNA-Sequencing Analyses
title_short Genetic Insights of Schizophrenia via Single Cell RNA-Sequencing Analyses
title_sort genetic insights of schizophrenia via single cell rna-sequencing analyses
topic Regular Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10318862/
https://www.ncbi.nlm.nih.gov/pubmed/36805283
http://dx.doi.org/10.1093/schbul/sbad002
work_keys_str_mv AT wuyong geneticinsightsofschizophreniaviasinglecellrnasequencinganalyses
AT zhangchuyi geneticinsightsofschizophreniaviasinglecellrnasequencinganalyses
AT wanglu geneticinsightsofschizophreniaviasinglecellrnasequencinganalyses
AT liyi geneticinsightsofschizophreniaviasinglecellrnasequencinganalyses
AT xiaoxiao geneticinsightsofschizophreniaviasinglecellrnasequencinganalyses