ArticleFrontiers in neurology2026
Integrating multi-omics and machine learning to explore the role of amino acid metabolism in intervertebral disk degeneration.
Article in Frontiers in neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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9 authors.
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Abstract
Objective: Intervertebral disk degeneration (IDD) is the leading cause of chronic low back pain, yet its link to amino acid metabolic reprogramming remains unclear. Methods: Three GEO transcriptomes were integrated; amino-acid-metabolism genes were intersected with differentially expressed genes. Core genes were selected by LASSO, SVM and random forest, incorporated into an SHAP-interpretable nomogram, and tested by single-cell analysis, Results: Forty-three altered amino acid metabolism-related genes were identified, from which five core genes were screened: CETP, AIFM1, and GM2A were up-regulated; PNPLA2 and AGK were down-regulated. The constructed nomogram prediction model achieved an AUC value of 0.812. Degenerated intervertebral disks exhibited increased immune infiltration; the core genes either suppressed protective matrix genes or impaired stress defense capability. Molecular docking results showed that NVP-AEW541 and EGCG could bind to the AIFM1 protein with a binding free energy of -10.7 kcal/mol; WB confirmed protein trends. Conclusion: The five-core-gene signature is strongly associated with IDD and may represent a key regulatory pathway, offering a promising diagnostic model and potential therapeutic targets.
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