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Integrated analysis of endoplasmic reticulum stress regulators’ expression identifies distinct subtypes of autism spectrum disorder

Endoplasmic reticulum (ER) stress has been demonstrated to play important roles in a variety of human diseases. However, their relevance to autism spectrum disorder (ASD) remains largely unknown. Herein, we aimed to investigate the expression patterns and potential roles of the ER stress regulators...

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Autores principales: Li, Yanjun, Gao, Songyin, Meng, Yuelan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10149679/
https://www.ncbi.nlm.nih.gov/pubmed/37139330
http://dx.doi.org/10.3389/fpsyt.2023.1136154
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author Li, Yanjun
Gao, Songyin
Meng, Yuelan
author_facet Li, Yanjun
Gao, Songyin
Meng, Yuelan
author_sort Li, Yanjun
collection PubMed
description Endoplasmic reticulum (ER) stress has been demonstrated to play important roles in a variety of human diseases. However, their relevance to autism spectrum disorder (ASD) remains largely unknown. Herein, we aimed to investigate the expression patterns and potential roles of the ER stress regulators in ASD. The ASD expression profiles GSE111176 and GSE77103 were compiled from the Gene Expression Omnibus (GEO) database. ER stress score determined by the single sample gene set enrichment analysis (ssGSEA) was significantly higher in ASD patients. Differential analysis revealed that there were 37 ER stress regulators dysregulated in ASD. Based on their expression profile, the random forest and artificial neuron network techniques were applied to build a classifier that can effectively distinguish ASD from control samples among independent datasets. Weighted gene co-expression network analysis (WGCNA) screened out the turquoise module with 774 genes was closely related to the ER stress score. Through the overlapping results of the turquoise module and differential expression ER stress genes, hub regulators were gathered. The TF/miRNA-hub gene interaction networks were created. Furthermore, the consensus clustering algorithm was performed to cluster the ASD patients, and there were two ASD subclusters. Each subcluster has unique expression profiles, biological functions, and immunological characteristics. In ASD subcluster 1, the FAS pathway was more enriched, while subcluster 2 had a higher level of plasma cell infiltration as well as the BCR signaling pathway and interleukin receptor reaction reactivity. Finally, the Connectivity map (CMap) database was used to find prospective compounds that target various ASD subclusters. A total of 136 compounds were significantly enriched. In addition to some specific drugs which can effectively reverse the differential gene expression of each subcluster, we found that the PKC inhibitor BRD-K09991945 that targets Glycogen synthase kinase 3β (GSK3B) might have a therapeutic effect on both ASD subtypes that worth of the experimental validation. Our finding proved that ER stress plays a crucial role in the diversity and complexity of ASD, which may inform both mechanistic and therapeutic assessments of the disorder.
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spelling pubmed-101496792023-05-02 Integrated analysis of endoplasmic reticulum stress regulators’ expression identifies distinct subtypes of autism spectrum disorder Li, Yanjun Gao, Songyin Meng, Yuelan Front Psychiatry Psychiatry Endoplasmic reticulum (ER) stress has been demonstrated to play important roles in a variety of human diseases. However, their relevance to autism spectrum disorder (ASD) remains largely unknown. Herein, we aimed to investigate the expression patterns and potential roles of the ER stress regulators in ASD. The ASD expression profiles GSE111176 and GSE77103 were compiled from the Gene Expression Omnibus (GEO) database. ER stress score determined by the single sample gene set enrichment analysis (ssGSEA) was significantly higher in ASD patients. Differential analysis revealed that there were 37 ER stress regulators dysregulated in ASD. Based on their expression profile, the random forest and artificial neuron network techniques were applied to build a classifier that can effectively distinguish ASD from control samples among independent datasets. Weighted gene co-expression network analysis (WGCNA) screened out the turquoise module with 774 genes was closely related to the ER stress score. Through the overlapping results of the turquoise module and differential expression ER stress genes, hub regulators were gathered. The TF/miRNA-hub gene interaction networks were created. Furthermore, the consensus clustering algorithm was performed to cluster the ASD patients, and there were two ASD subclusters. Each subcluster has unique expression profiles, biological functions, and immunological characteristics. In ASD subcluster 1, the FAS pathway was more enriched, while subcluster 2 had a higher level of plasma cell infiltration as well as the BCR signaling pathway and interleukin receptor reaction reactivity. Finally, the Connectivity map (CMap) database was used to find prospective compounds that target various ASD subclusters. A total of 136 compounds were significantly enriched. In addition to some specific drugs which can effectively reverse the differential gene expression of each subcluster, we found that the PKC inhibitor BRD-K09991945 that targets Glycogen synthase kinase 3β (GSK3B) might have a therapeutic effect on both ASD subtypes that worth of the experimental validation. Our finding proved that ER stress plays a crucial role in the diversity and complexity of ASD, which may inform both mechanistic and therapeutic assessments of the disorder. Frontiers Media S.A. 2023-04-17 /pmc/articles/PMC10149679/ /pubmed/37139330 http://dx.doi.org/10.3389/fpsyt.2023.1136154 Text en Copyright © 2023 Li, Gao and Meng. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychiatry
Li, Yanjun
Gao, Songyin
Meng, Yuelan
Integrated analysis of endoplasmic reticulum stress regulators’ expression identifies distinct subtypes of autism spectrum disorder
title Integrated analysis of endoplasmic reticulum stress regulators’ expression identifies distinct subtypes of autism spectrum disorder
title_full Integrated analysis of endoplasmic reticulum stress regulators’ expression identifies distinct subtypes of autism spectrum disorder
title_fullStr Integrated analysis of endoplasmic reticulum stress regulators’ expression identifies distinct subtypes of autism spectrum disorder
title_full_unstemmed Integrated analysis of endoplasmic reticulum stress regulators’ expression identifies distinct subtypes of autism spectrum disorder
title_short Integrated analysis of endoplasmic reticulum stress regulators’ expression identifies distinct subtypes of autism spectrum disorder
title_sort integrated analysis of endoplasmic reticulum stress regulators’ expression identifies distinct subtypes of autism spectrum disorder
topic Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10149679/
https://www.ncbi.nlm.nih.gov/pubmed/37139330
http://dx.doi.org/10.3389/fpsyt.2023.1136154
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AT gaosongyin integratedanalysisofendoplasmicreticulumstressregulatorsexpressionidentifiesdistinctsubtypesofautismspectrumdisorder
AT mengyuelan integratedanalysisofendoplasmicreticulumstressregulatorsexpressionidentifiesdistinctsubtypesofautismspectrumdisorder