Introduction: The molecular pathogenesis of Alzheimer’s disease (AD) is still not clear, and the relationship between gene expression profile for different brain regions has not been studied. Objective: Bioinformatic analysis at the genetic level has become the best way for the pathogenesis research of AD, which can analyze the abovementioned relationship. Methods: In this study, the datasets of AD were obtained from the Gene Expression Omnibus (GEO), and Qlucore Omics Explorer (QOE) software was used to screen differentially expressed genes of GSE36980 and GSE9770 and verify gene expression of GSE63060. The Gene Ontology (GO) function enrichment analysis of these selected genes was conducted by Database for Annotation, Visualization, and Integrated Discovery (DAVID), and then the gene/protein interaction network was established by STRING to find the related proteins. R language was used for drafting maps and plots. Results: There were 20 differentially expressed genes related to AD selected from GSE36980 (p = 6.2e−6, q = 2.9422e−4) and GSE9770 (p = 3.3e−4, q = 0.016606). Their expression levels of the AD group were lower than those in the control group and varied among different brain regions. Cellular morphogenesis and establishment or maintenance of cell polarity were enriched, and LRRTM1 and RASAL1 were identified by the integration network. Moreover, the analysis of GSE63060 verified the expression level of LRRTM1 and RASAL1 in Alzheimer’s patients, which was much lower than that in normal people aged >65 years. Conclusions: The pathogenesis of AD at molecular levels may link to cell membrane structures and signal transduction; hence, a list of 20 genes, including LRRTM1 and RASAL1, potentially are important for the discovery of treatment target or molecular marker of AD.