ArticleBMC pharmacology & toxicology2025
Alzheimer's disease: an integrative bioinformatics and machine learning analysis reveals glutamine metabolism-associated gene biomarkers.
Article in BMC pharmacology & toxicology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Spatial Changes in Hippocampal Transcriptomic Profiles Following Limbic Non-convulsive Status Epilepticus: Insights into Long-Term Inflammation and Cognitive Deficits.Molecular neurobiology · 2026Article
- Asparaginase-like protein 1 and human endogenous retroviruses link immune and gene dysregulation in dementia.Frontiers in cellular and infection microbiology · 2026Article
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7 authors.
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Abstract
backgroundAlzheimer's disease (AD), a hallmark of age-related cognitive decline, is defined by its unique neuropathology. Metabolic dysregulation, particularly involving glutamine (Gln) metabolism, has emerged as a critical but underexplored aspect of AD pathophysiology, representing a significant gap in our current understanding of the disease.
methodsTo investigate the involvement of GlnMgs in AD, we conducted a comprehensive bioinformatic analysis. We began by identifying differentially expressed GlnMgs from a curated list of 34 candidate genes. Subsequently, we employed GSEA and GSVA to assess the biological significance of these GlnMgs. Advanced techniques such as Lasso regression and SVM-RFE were utilized to identify key hub genes and evaluate the diagnostic potential of 14 central GlnMgs in AD. Additionally, we examined their correlations with clinical parameters and validated their expression across multiple independent AD cohorts (GSE5281, GSE37263, GSE106241, GSE132903, GSE63060).
resultsOur rigorous analysis identified 14 GlnMgs-GLS2, GLS, GLUD2, GLUL, GOT1, HAL, AADAT, PFAS, ASNSD1, PPAT, NIT2, ALDH5A1, ASRGL1, and ATCAY-as potential contributors to AD pathogenesis. These genes were implicated in vital biological processes, including lipid transport and the metabolism of purine-containing compounds, in response to nutrient availability. Notably, these GlnMgs demonstrated significant diagnostic potential, highlighting their utility as both diagnostic and prognostic biomarkers for AD.
conclusionsOur study uncovers 14 GlnMgs with potential links to AD, expanding our understanding of the disease's molecular underpinnings and offering promising avenues for biomarker development. These findings not only enhance the molecular landscape of AD but also pave the way for future diagnostic and therapeutic innovations, potentially reshaping AD diagnostics and patient care.
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