Dataset Information

Mechanistic Insight Into the Regulation of Immune-Related Genes Expression in Autism Spectrum Disorder

ABSTRACT: Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder featuring impairment in verbal and non-verbal interactions, defects in social interactions, stereotypic behaviors as well as restricted interests. In recent times, the incidence of ASD is growing at a rapid pace. In spite of great endeavors devoted to explaining ASD pathophysiology, its precise etiology remains unresolved. ASD pathogenesis is related to different phenomena associated with the immune system; however, the mechanisms behind these immune phenomena as well as the potential contributing genes remain unclear. In the current work, we used a bioinformatics approach to describe the role of long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) in the peripheral blood (PB) samples to figure out the molecular regulatory procedures involved in ASD better. The Gene Expression Omnibus database was used to obtain the PB microarray dataset (GSE89594) from the subjects suffering from ASD and control subjects, containing the data related to both mRNAs and lncRNAs. The list of immune-related genes was obtained from the ImmPort database. In order to determine the immune-related differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs), the limma package of R software was used. A protein-protein interaction network was developed for the immune-related DEmRNAs. By employing the Human MicroRNA Disease Database, DIANA-LncBase, and DIANA-TarBase databases, the RNA interaction pairs were determined. We used the Pearson correlation coefficient to discover the positive correlations between DElncRNAs and DEmRNAs within the ceRNA network. Finally, the lncRNA-associated ceRNA network was created based on DElncRNA-miRNA-DEmRNA interactions and co-expression interactions. In addition, the KEGG enrichment analysis was conducted for immune-related DEmRNAs found within the constructed network. This work found four potential DElncRNA-miRNA-DEmRNA axes in ASD pathogenesis, including, LINC00472/hsa-miR-221-3p/PTPN11, ANP32A-IT1/hsa-miR-182-5p/S100A2, LINC00472/hsa-miR-132-3p/S100A2, and RBM26-AS1/hsa-miR-182-5p/S100A2. According to pathway enrichment analysis, the immune-related DEmRNAs were enriched in the “JAK-STAT signaling pathway” and “Adipocytokine signaling pathway.” An understanding of regulatory mechanisms of ASD-related immune genes would provide novel insights into the molecular mechanisms behind ASD pathogenesis.

SUBMITTER: Sabaie H

PROVIDER: S-EPMC8568055 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Introduction: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with clinical presentation and prognostic heterogeneity. Ferroptosis is a regulated non-apoptotic cell death program implicated in the occurrence and progression of various diseases. Therefore, we aimed to explore ferroptosis-related molecular subtypes in ASD and further illustrate the potential mechanism. Methods: A total of 201 normal samples and 293 ASD samples were obtained from the Gene Expression Omnibus (GEO) database. We used the unsupervised clustering analysis to identify the molecular subtypes based on ferroptosis-related genes (FRGs) and evaluate the immune characteristics between ferroptosis subtypes. Ferroptosis signatures were identified using the least absolute shrinkage and selection operator regression (LASSO) and recursive feature elimination for support vector machines (SVM-RFE) machine learning algorithms. The ferroptosis scores based on seven selected genes were constructed to evaluate the ferroptosis characteristics of ASD. Results: We identified 16 differentially expressed FRGs in ASD children compared with controls. Two distinct molecular clusters associated with ferroptosis were identified in ASD. Analysis of immune infiltration revealed immune heterogeneity between the two clusters. Cluster2, characterized by a higher immune score and a larger number of infiltrated immune cells, exhibited a stronger immune response and was markedly enriched in immune response-related signaling pathways. Additionally, the ferroptosis scores model was capable of predicting ASD subtypes and immunity. Higher levels of ferroptosis scores were associated with immune activation, as seen in Cluster2. Lower ferroptosis scores were accompanied by relative immune downregulation, as seen in Cluster1. Conclusion: Our study systematically elucidated the intricate correlation between ferroptosis and ASD and provided a promising ferroptosis score model to predict the molecular clusters and immune infiltration cell profiles of children with ASD.

Dataset Information

Mechanistic Insight Into the Regulation of Immune-Related Genes Expression in Autism Spectrum Disorder

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets