An Integrative Network Analysis Framework for Identifying Altered Glycosylation Pathways Associated with Autism Spectrum Disorder.

Overview

1. Glycoscience Research Cluster (AGRC), University of Galway, Biomedical Sciences, H91 W2TY Galway, Ireland; (A.M.O.); (S.C.)
2. Institute for Health Discovery & Innovation, University of Galway, H91 TK33 Galway, Ireland
3. UMR 8576-UGSF-Unité de Glycobiologie Structurale et Fonctionnelle, Univ. Lille, CNRS, F-59000 Lille, France
4. School of Mathematical and Statistical Sciences, University of Galway, H91 TK33 Galway, Ireland

Abstract

Background: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition marked by heterogeneous behavioral symptoms and systemic comorbidities, including immune and gastrointestinal dysfunctions. Emerging studies suggest that glycosylation—a fundamental post-translational modification regulating cellular communication and immune responses—may play a role in ASD pathophysiology, yet its contribution remains underexplored. Methods: In this study, we developed an integrative transcriptomic and network analysis framework to investigate glycosylation-related gene expression changes and their functional associations in ASD. Using publicly available datasets from bulk and single-cell RNA sequencing of brain and blood tissues, we focused on four prior-knowledge gene subsets: glycogenes, extracellular matrix glycoproteins, immune response genes, and autism risk genes. Results: Differential expression and pathway enrichment analyses revealed consistent dysregulation of glycosylation pathways, including mucin-type O-glycan biosynthesis, glycosaminoglycan metabolism, GPI-anchor formation, and sialylation, across ASD tissues. These transcriptional changes were functionally linked to altered immune signaling (e.g., IL-17, Toll-like receptor, and complement pathways) and synaptic development pathways, forming a distinct glyco-immune axis. Network analysis identified key glycogenes such as GALNT10, NEU1, LMAN2L, and CHST1 as central molecular nodes, interacting with immune and neuronal regulators. Linkage disequilibrium analysis further revealed ASD-associated SNPs influencing the expression of these glycogenes in both blood and brain tissues. Conclusions: Together, these findings support a model in which disrupted glycosylation contributes to ASD pathophysiology by mediating immune dysregulation and altered neuronal connectivity. This study offers a systems-level framework to understand the molecular complexity of ASD and highlights glycogenes as potential biomarkers and targets for future therapeutic exploration.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data

Data links

• ncbi.nlm.nih.gov/geo, NCBI; found in the text, “2.1. Gene Expression Data Selection and…”

Data Availability Statement

1. The differentially expressed genes, identified from the full ASD differential gene expression meta-analysis results of brain samples published by Forés-Martos, J. et al. is available from the following published article [34]. 2. The differentially expressed genes, identified from the full ASD differential gene expression mega-analysis results of blood samples published by Tylee DS. et al. is available from the following published article [35]. 3. The gene expression datasets analyzed during the current study are available in the GEO repository under the following GEO accession numbers GSE18123; GSE26415; GSE89594; GSE42133. 4. All data generated or analyzed during this study are included in this published article and its Supplementary Information Files.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 5 authors, 10 keywords, 6 MeSH terms, 1 funder, 98 references.

Cite

This paper

Oommen, A. M., Morel, M., Cunningham, S., Seoighe, C., & Joshi, L. (2026). An Integrative Network Analysis Framework for Identifying Altered Glycosylation Pathways Associated with Autism Spectrum Disorder. Genes, 17(4), 486. https://doi.org/10.3390/genes17040486

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