Gene Expression Profiling in Autism Spectrum Disorder: A Microarray Analysis Using Gse42133

Year : 2026 | Volume : 13 | Issue : 01 | Page : 37 48
    By

    Syed Nabeel,

  1. Research Scholar, Department of Biotechnology, Acharya Institute of Technology, Bengaluru, Karnataka, India

Abstract

Autism Spectrum Disorder (ASD) is a diverse neurodevelopmental disorder characterized by difficulties in social interaction, communication impairments, and restricted or repetitive patterns of behavior. Despite its increasing prevalence, the underlying molecular mechanisms remain poorly understood. Advances in transcriptomics offer opportunities to investigate the gene expression changes that may contribute to ASD pathophysiology. In this study, the microarray dataset GSE42133 was analyzed, which comprises gene expression profiles from peripheral blood samples of individuals diagnosed with ASD and age-matched neurotypical controls. Data preprocessing involved background correction, log2 transformation, and quantile normalization to maintain comparability among samples. Differential gene expressions were analyzed using the limma package in R, which identified significantly upregulated and downregulated genes based on adjusted p-values and log-fold change criteria. Functional enrichment analysis through Gene Ontology (GO) and KEGG pathway databases highlighted important biological processes and signaling pathways associated with immune response, cytokine signaling, neuroinflammation, and synaptic regulation. In particular, Erythropoietin (EPO) receptor signaling and Type I Interferon signaling pathways showed marked dysregulation, suggesting a connection between immune modulation and neurodevelopmental alterations in ASD. Visualization using volcano plots, heatmaps, and pathway maps further demonstrated clear expression differences between ASD and control groups. This integrative bioinformatics strategy confirms the role of immune-related genes in ASD and proposes potential therapeutic targets and diagnostic biomarkers. Overall, the findings enhance molecular-level understanding of ASD and support future research toward precision-based early diagnosis and intervention.

Keywords: Autism spectrum disorder, gene expression profiling, microarray analysis, differentially expressed genes (DEGs), limma, transcriptomics

[This article belongs to Research & Reviews: A Journal of Bioinformatics ]

How to cite this article:
Syed Nabeel. Gene Expression Profiling in Autism Spectrum Disorder: A Microarray Analysis Using Gse42133. Research & Reviews: A Journal of Bioinformatics. 2026; 13(01):37-48.
How to cite this URL:
Syed Nabeel. Gene Expression Profiling in Autism Spectrum Disorder: A Microarray Analysis Using Gse42133. Research & Reviews: A Journal of Bioinformatics. 2026; 13(01):37-48. Available from: https://journals.stmjournals.com/rrjobi/article=2026/view=239393


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Regular Issue Subscription Original Research
Volume 13
Issue 01
Received 12/11/2025
Accepted 10/02/2026
Published 27/03/2026
Publication Time 135 Days
49

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