Frontiers in neurology · 2026
Integrating multi-omics and machine learning to explore the role of amino acid metabolism in intervertebral disk degeneration.
СтатьяНазвание и аннотация: Перевод в очереди
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Li Xusheng, Shuid Ahmad Nazrun, Miswan Mohd Fairudz Mohd, Zhang Xiao, Gu Wenbo, Cao Donghui, Wang Jungang, Jiang Ziyang, Yuan Haifeng
Аннотация
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, in silico knockout, docking and WB.
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.
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, in silico knockout, docking and WB.
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.