Screening of signaling pathways and hub genes in Guillain-Barré syndrome based on bioinformatics and machine learning

Guillain-Barré syndrome (GBS) is a acute immune-mediated peripheral neuropathy with scarce incidence, yet its molecular mechanisms remain incompletely elucidated. This study aims to systematically identify key hub genes and signaling pathways in GBS to uncover novel insights into its immunopathology and potential therapeutic targets. The transcriptomic dataset GSE31014, comprising peripheral blood leukocytes from 7 GBS patients and 7 healthy controls, was analyzed. Differentially expressed genes (DEGs) were identified using the Limma package. Functional enrichment was assessed via Gene Set Enrichment Analysis (GSEA). A protein-protein interaction (PPI) network was constructed to identify core modules, from which hub genes were pinpointed through the cross-validation of two machine learning algorithms: the Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE). Immune cell infiltration was evaluated using single-sample GSEA (ssGSEA). Furthermore, upstream regulatory networks and potential therapeutic small molecules were predicted. The hub gene upreguation was validated by laboratory qRT-PCR and independent public datasets. We identified 885 DEGs in GBS, which were significantly enriched in immune-related pathways such as chemokine signaling, B/T cell receptor signaling, and oxidative phosphorylation. PPI network and machine learning algorithms converged on two robust hub genes: HSP90AA1 and CAMP. Immune infiltration analysis revealed widespread activation of both innate and adaptive immune cells in GBS. HSP90AA1 expression correlated with B-cell and type 2 immune responses, while CAMP displayed a dual role, associated with both innate immune killing and the regulation of specific T-cell and NK-cell subsets. Both genes were co-enriched in the chemokine signaling pathway. FOXC1 was predicted as a common upstream transcriptional regulator. Additionally, five promising small-molecule therapeutics were screened. The significant upregulation of HSP90AA1 and CAMP in GBS was consistently validated. This integrated bioinformatics study identifies HSP90AA1 and CAMP as key hub genes in GBS, potentially driving neuroinflammation through the dysregulation of chemokine-mediated immune recruitment and activation. The findings offer novel insights into the immunopathogenesis of GBS and propose candidate molecules for future therapeutic development.

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Publication Details

Journal
BMC Neurology
Published
2026-03-13
DOI
https://doi.org/10.1186/s12883-026-04766-z
Primary Topic
Peripheral Neuropathies and Disorders
Type
article
Field-Weighted Citation Impact
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article

Screening of signaling pathways and hub genes in Guillain-Barré syndrome based on bioinformatics and machine learning

Denger Zhang, Wei Ma, Zhenhai Wang, Zhao Wang
BMC Neurology
Peripheral Neuropathies and Disorders
article

Screening of signaling pathways and hub genes in Guillain-Barré syndrome based on bioinformatics and machine learning

Denger Zhang, Wei Ma, Zhenhai Wang, Zhao Wang
article en

Abstract

Guillain-Barré syndrome (GBS) is a acute immune-mediated peripheral neuropathy with scarce incidence, yet its molecular mechanisms remain incompletely elucidated. This study aims to systematically identify key hub genes and signaling pathways in GBS to uncover novel insights into its immunopathology and potential therapeutic targets. The transcriptomic dataset GSE31014, comprising peripheral blood leukocytes from 7 GBS patients and 7 healthy controls, was analyzed. Differentially expressed genes (DEGs) were identified using the Limma package. Functional enrichment was assessed via Gene Set Enrichment Analysis (GSEA). A protein-protein interaction (PPI) network was constructed to identify core modules, from which hub genes were pinpointed through the cross-validation of two machine learning algorithms: the Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE). Immune cell infiltration was evaluated using single-sample GSEA (ssGSEA). Furthermore, upstream regulatory networks and potential therapeutic small molecules were predicted. The hub gene upreguation was validated by laboratory qRT-PCR and independent public datasets. We identified 885 DEGs in GBS, which were significantly enriched in immune-related pathways such as chemokine signaling, B/T cell receptor signaling, and oxidative phosphorylation. PPI network and machine learning algorithms converged on two robust hub genes: HSP90AA1 and CAMP. Immune infiltration analysis revealed widespread activation of both innate and adaptive immune cells in GBS. HSP90AA1 expression correlated with B-cell and type 2 immune responses, while CAMP displayed a dual role, associated with both innate immune killing and the regulation of specific T-cell and NK-cell subsets. Both genes were co-enriched in the chemokine signaling pathway. FOXC1 was predicted as a common upstream transcriptional regulator. Additionally, five promising small-molecule therapeutics were screened. The significant upregulation of HSP90AA1 and CAMP in GBS was consistently validated. This integrated bioinformatics study identifies HSP90AA1 and CAMP as key hub genes in GBS, potentially driving neuroinflammation through the dysregulation of chemokine-mediated immune recruitment and activation. The findings offer novel insights into the immunopathogenesis of GBS and propose candidate molecules for future therapeutic development.

BMC Neurology
Ningxia Medical University (CN), Ningxia Medical University General Hospital (CN), Shanxi Academy of Medical Sciences (CN), Ningxia Center for Diseases Prevention and Control (CN)
Openalex Percentile: Top 30%
Peripheral Neuropathies and Disorders
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