Investigating the molecular mechanisms of glutamine metabolism and mitochondria-related biomarkers in Alzheimer's disease through transcriptomics and experimental validation.

Journal: European journal of medical research
Published Date: Jan 15, 2026

Abstract

BACKGROUND: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder. This study aims to identify biomarkers associated with glutamine metabolism-related genes (GRGs) and mitochondria-related genes (MRGs) in AD through bioinformatics analysis, offering insights for prevention and treatment strategies. METHODS: Candidate genes were first picked out through differential gene expression profiling, construction of weighted gene co-expression network analysis (WGCNA), and interaction network analysis. Biomarkers were then filtered using machine learning algorithms. For these biomarkers, expression verification and receiver operating characteristic (ROC) curve analysis were carried out. These biomarkers underwent GeneMANIA analysis, subcellular and chromosomal localization, enrichment analysis, along with immune infiltration assessment, establishment of a multi-layered molecular regulatory network, and prediction of potential therapeutic agents by leveraging drug-gene interaction databases. Finally, the consistency was validated by reverse transcription quantitative polymerase chain reaction (RT-qPCR). RESULTS: Initially, 10 candidate genes were identified through bioinformatics analysis. Machine learning, expression validation, and ROC analysis pinpointed SNCA and PPP2R1A as biomarkers (AUC > 0.7). These biomarkers were associated with 20 functionally similar genes and were active in the nucleus and cytoplasm. SNCA was located on chromosome 4, and PPP2R1A on chromosome 19. Enrichment analysis unveiled their involvement in pathways such as olfactory transduction. Additionally, these biomarkers influenced immune cells; for instance, there was a positive correlation between PPP2R1A and type 2 T helper cells (cor = 0.66, P = 1.03 × 10-5). A molecular regulatory network demonstrated that these biomarkers were regulated by 134 miRNAs, and 72 potential drugs targeting these biomarkers were identified. RT-qPCR confirmed the expression consistency with bioinformatics results. CONCLUSION: This study ultimately identified SNCA and PPP2R1A as biomarkers for AD, providing a theoretical foundation and potential targets for the diagnosis and treatment of AD.

Authors

  • Xiaying Si
    Department of Psychological Health, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China.
  • Shihan Tian
    School of Life Sciences, Xiamen University, Xiamen, 361102, Fujian, China.
  • Yudong Chen
    College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China; The National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen 518060, China.
  • Xin Li
    Veterinary Diagnostic Center, Shanghai Animal Disease Control Center, Shanghai, China.
  • Guode Wu
    Department of Neurology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China.
  • Yuan Yao
    Department of Food Science, Purdue University, West Lafayette, IN, 47907, USA. Electronic address: [email protected].
  • Manxia Wang
    Lanzhou University Second Hospital, The Second Medical College of Lanzhou University, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, China. [email protected].

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