Abstract:

Recent clinical evidence suggests that dapagliflozin may confer protective effects against Alzheimer’s disease (AD); however, its precise molecular mechanisms and specific targets remain largely undefined. In the present study, we employed bioinformatics approaches to systematically screen potential molecular targets of dapagliflozin in the context of AD, followed by in vitro validation, aiming to establish a theoretical foundation for its preventive and therapeutic applications. To identify differentially expressed genes (DEGs), three gene expression microarray datasets (GSE118553, GSE122063, and GSE132903) were retrieved from the GEO database, encompassing a total of 242 normal human brain tissue samples and 320 AD brain tissue samples. Functional enrichment analyses were subsequently conducted to elucidate the biological significance of the identified DEGs. A protein-protein interaction (PPI) network was constructed using Cytoscape software to pinpoint the top five core targets. Molecular docking simulations between dapagliflozin and these core targets were performed using AutoDockTools and Vina. Finally, an AD cellular model was established by treating HT-22 cells with amyloid β-protein 1-42 (Aβ_1-42), and the modulatory effects of dapagliflozin on the core targets were experimentally validated in vitro. A total of 77 DEGs were identified. Subsequent PPI network analysis highlighted five central targets: Glial fibrillary acidic protein (GFAP), Synaptophysin, Synaptotagmin-1 (SYT1), Somatostatin (SST), and Glutamate decarboxylase 2 (GAD2). Molecular docking results demonstrated that all five targets exhibited favorable binding interactions with dapagliflozin, with SYT1 displaying the highest binding affinity (i.e., the lowest binding energy). In vitro experiments further confirmed that dapagliflozin significantly upregulated SYT1 expression at both mRNA and protein levels in the AD model.

Key words: Alzheimer disease, Dapagliflozin, Synaptotagmin-1, Molecular docking, HT-22 cells