Bioinformatics analysis of genomic and immune infiltration patterns in autism spectrum disorder

BACKGROUND: Autism spectrum disorder (ASD) is a specific type of pervasive developmental disorder, and most studies suggest that the onset of autism may be related to genetic and immune factors. The etiology of autism and the underlying molecular events need to be further addressed. METHODS: The ASD...

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Autores principales: Wei, Ru-Qiong, Guo, Wen-Liang, Wu, Yin-Teng, Alarcòn Rodrìguez, Raquel, Requena Mullor, Marìa del Mar, Gui, Yu-Chang, Xu, Jian-Wen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577768/
https://www.ncbi.nlm.nih.gov/pubmed/36267781
http://dx.doi.org/10.21037/atm-22-4108
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author Wei, Ru-Qiong
Guo, Wen-Liang
Wu, Yin-Teng
Alarcòn Rodrìguez, Raquel
Requena Mullor, Marìa del Mar
Gui, Yu-Chang
Xu, Jian-Wen
author_facet Wei, Ru-Qiong
Guo, Wen-Liang
Wu, Yin-Teng
Alarcòn Rodrìguez, Raquel
Requena Mullor, Marìa del Mar
Gui, Yu-Chang
Xu, Jian-Wen
author_sort Wei, Ru-Qiong
collection PubMed
description BACKGROUND: Autism spectrum disorder (ASD) is a specific type of pervasive developmental disorder, and most studies suggest that the onset of autism may be related to genetic and immune factors. The etiology of autism and the underlying molecular events need to be further addressed. METHODS: The ASD-related dataset GSE18123 was downloaded from the Gene Expression Omnibus (GEO) database. Gene set enrichment analysis (GSEA) was used to screen for Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that may be associated with autism. The top 5,000 genes with an absolute median difference were obtained, and a co-expression network was constructed using weighted correlation network analysis (WGCNA). In addition, GO and KEGG enrichment analyses were performed for genes in the modules most closely related to ASD. Hub genes were found in the significant modules, and the expression values and receiver operating characteristic (ROC) curves of the hub genes were analyzed and validated. Immune cell infiltration in ASD was calculated using the CIBERSORT algorithm, and the relationship between hub genes and immune cells was analyzed. Finally, GSEA was used to explore the potential pathways of hub genes affecting ASD. RESULTS: The 5,000 DEGs were divided into eight significant modules by WGCNA. The green module was most significantly associated with ASD, and two hub genes [fatty acid-binding protein 2 (FABP2) and Janus kinase 2 (JAK2)] were found. Immune cell infiltration showed that resting dendritic cells and monocytes differed significantly in ASD and healthy individuals. FABP2 was significantly associated with memory B cells and CD8 T cells. JAK2 was significantly associated with monocytes, CD4 activated memory T cells, CD4 resting memory T cells, activated dendritic cells, gamma delta T cells, regulatory T cells (Tregs), CD8 T cells, and naïve CD4 T cells. FABP2 and JAK2 were found to affect multiple pathways of immunity. CONCLUSIONS: FABP2 and JAK2 may influence the immune microenvironment of ASD by regulating immune cells and immune-related pathways and are candidate molecular markers for the development of ASD.
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spelling pubmed-95777682022-10-19 Bioinformatics analysis of genomic and immune infiltration patterns in autism spectrum disorder Wei, Ru-Qiong Guo, Wen-Liang Wu, Yin-Teng Alarcòn Rodrìguez, Raquel Requena Mullor, Marìa del Mar Gui, Yu-Chang Xu, Jian-Wen Ann Transl Med Original Article BACKGROUND: Autism spectrum disorder (ASD) is a specific type of pervasive developmental disorder, and most studies suggest that the onset of autism may be related to genetic and immune factors. The etiology of autism and the underlying molecular events need to be further addressed. METHODS: The ASD-related dataset GSE18123 was downloaded from the Gene Expression Omnibus (GEO) database. Gene set enrichment analysis (GSEA) was used to screen for Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that may be associated with autism. The top 5,000 genes with an absolute median difference were obtained, and a co-expression network was constructed using weighted correlation network analysis (WGCNA). In addition, GO and KEGG enrichment analyses were performed for genes in the modules most closely related to ASD. Hub genes were found in the significant modules, and the expression values and receiver operating characteristic (ROC) curves of the hub genes were analyzed and validated. Immune cell infiltration in ASD was calculated using the CIBERSORT algorithm, and the relationship between hub genes and immune cells was analyzed. Finally, GSEA was used to explore the potential pathways of hub genes affecting ASD. RESULTS: The 5,000 DEGs were divided into eight significant modules by WGCNA. The green module was most significantly associated with ASD, and two hub genes [fatty acid-binding protein 2 (FABP2) and Janus kinase 2 (JAK2)] were found. Immune cell infiltration showed that resting dendritic cells and monocytes differed significantly in ASD and healthy individuals. FABP2 was significantly associated with memory B cells and CD8 T cells. JAK2 was significantly associated with monocytes, CD4 activated memory T cells, CD4 resting memory T cells, activated dendritic cells, gamma delta T cells, regulatory T cells (Tregs), CD8 T cells, and naïve CD4 T cells. FABP2 and JAK2 were found to affect multiple pathways of immunity. CONCLUSIONS: FABP2 and JAK2 may influence the immune microenvironment of ASD by regulating immune cells and immune-related pathways and are candidate molecular markers for the development of ASD. AME Publishing Company 2022-09 /pmc/articles/PMC9577768/ /pubmed/36267781 http://dx.doi.org/10.21037/atm-22-4108 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Wei, Ru-Qiong
Guo, Wen-Liang
Wu, Yin-Teng
Alarcòn Rodrìguez, Raquel
Requena Mullor, Marìa del Mar
Gui, Yu-Chang
Xu, Jian-Wen
Bioinformatics analysis of genomic and immune infiltration patterns in autism spectrum disorder
title Bioinformatics analysis of genomic and immune infiltration patterns in autism spectrum disorder
title_full Bioinformatics analysis of genomic and immune infiltration patterns in autism spectrum disorder
title_fullStr Bioinformatics analysis of genomic and immune infiltration patterns in autism spectrum disorder
title_full_unstemmed Bioinformatics analysis of genomic and immune infiltration patterns in autism spectrum disorder
title_short Bioinformatics analysis of genomic and immune infiltration patterns in autism spectrum disorder
title_sort bioinformatics analysis of genomic and immune infiltration patterns in autism spectrum disorder
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577768/
https://www.ncbi.nlm.nih.gov/pubmed/36267781
http://dx.doi.org/10.21037/atm-22-4108
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