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

Autor: Ru-Qiong, Wei, Wen-Liang, Guo, Yin-Teng, Wu, Raquel, Alarcòn Rodrìguez, Marìa Del Mar, Requena Mullor, Yu-Chang, Gui, Jian-Wen, Xu
Rok vydání: 2022
Předmět:
Zdroj: Annals of Translational Medicine. 10:1013-1013
ISSN: 2305-5847
2305-5839
DOI: 10.21037/atm-22-4108
Popis: 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.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.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 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.
Databáze: OpenAIRE
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