Related Genes and Potential Biomarkers for Early Diagnosis of Alzheimer’s Disease

Abstract

Aim: The aim of this study is to extend our understanding of the molecular mechanism of Alzheimer’s disease (AD). Methods: We downloaded the gene expression profile GSE18309 from Gene Expression Omnibus database, which includes 3 genechips from patients with mild cognitive impairment (MCI), 3 genechips from patients with AD, and 3 genechips from normal controls (NC). Linear Models for Microarray Data package was used to identify differentially expressed genes (DEGs) in MCI versus NC group and AD versus NC group. Then, we extracted the overlapping DEGs of 2 groups for functional and pathway enrichment analysis using FuncAssociate software accompanied by gene ontology and expressing analysis systematic explorer, respectively. Further, AutoDock4 (http://autodock.scripps.edu/) was used to predict the docking site between small molecule ligands and proteins of a key DEG. Results: A total of 60 DEGs were identified. Biological processes associated with nutrient response and muscle development were significantly dysregulated in AD and MCI. In addition, we identified 2 active binding sites (A5 and L30) on protein structure of cholecystokinin A receptor (CCKAR) for drug design. Conclusion: The DEGs including CCKAR might be used as biomarkers for early diagnosis of AD. However, further experimental studies are needed to confirm our results.