Integrated Bioinformatics Analysis of Screen Mitochondrial Autophagy-Related Core Genes and Construct Diagnostic Model for Alzheimer's Disease.

Identify mitochondrial autophagy genes associated with Alzheimer's disease (AD) and elucidate its underlying pathogenesis and explore potential therapeutic targets. Alzheimer's disease related gene expression data were obtained from the Gene Expression Omnibus database. Mitochondrial autophagy-related genes with a relevance score > 1 were screened based on the GeneCards database. We identified differentially expressed genes using R, followed by functional enrichment and immune cell infiltration analyses. A protein-protein interaction network was constructed based on the STRING database, and key genes were identified by Cytoscape software. A diagnostic model for Alzheimer's disease was subsequently developed based on these key genes. Nine key genes were identified for Alzheimer's disease. Gene Ontology enrichment analysis revealed that the differentially expressed genes (DEGs) were primarily involved in mitochondrial function and nucleotide metabolism. Immune infiltration analysis showed negative correlations between YWHAG and VPS35 expression and M1 macrophage abundance, while RTN4 expression positively correlated with follicular helper T cell abundance. Using logistic regression analysis, a diagnostic model for AD was constructed based on three of the key genes. The model was validated by independent external samples, where area under the curve (AUC) demonstrated its robust and excellent diagnostic performance. The nine key genes identified in this study provide new insights and potential therapeutic targets for elucidating how mitochondrial autophagy influences Alzheimer's disease. The established diagnostic model provides a theoretical basis for personalized diagnosis and treatment of Alzheimer's disease.