Identification of Novel Biomarkers Related to Vesicle Trafficking in Alzheimer's Disease Using Bioinformatics Approaches.

Alzheimer's disease (AD) is a neurodegenerative disorder with complex pathogenesis. Vesicle trafficking abnormalities are closely associated with AD, making the identification of related biomarkers crucial. Chip data of AD were downloaded from the GEO database as training and test sets. Differentially expressed vesicle trafficking-related genes were analyzed, followed by construction of protein-protein interaction (PPI) networks, machine learning for important biomarkers identification, and various analyses including ROC curve analysis, and construction of regulatory networks. A total of 149 differentially expressed vesicle trafficking-related genes were identified. Through multiple analyses, 5 key genes (KIF22, ACTR10, TUBB2A, TUBA3C, and DCTN1) were obtained. Additionally, potential miRNA regulatory networks and candidate drugs were predicted, and AD subtypes were characterized.This study successfully identified novel biomarkers related to vesicle trafficking in AD, and these findings provide new insights into the role of intracellular transport dysfunction in AD pathogenesis.