Copper metabolism-related Genes in entorhinal cortex for Alzheimer's disease

Abstract

The pathological features of Alzheimer's disease are the formation of amyloid plaques and entanglement of nerve fibers. Studies have shown that Cu may be involved in the formation of amyloid plaques. However, their role has been controversial. The aim of this study was to explore the role of Cu in AD. We applied the "R" software for our differential analysis. Differentially expressed genes were screened using the limma package. Copper metabolism-related genes and the intersection set of differential genes with GSE5281 were searched; functional annotation was performed. The protein-protein interaction network was constructed using several modules to analyse the most significant hub genes. The hub genes were then qualified, and a database was used to screen for small-molecule AD drugs. We identified 87 DEGs. gene ontology analysis focused on homeostatic processes, response to toxic substances, positive regulation of transport, and secretion. The enriched molecular functions are mainly related to copper ion binding, molecular function regulators, protein-containing complex binding, identical protein binding and signalling receptor binding. The KEGG database is mainly involved in central carbon metabolism in various cancers, Parkinson's disease and melanoma. We identified five hub genes, FGF2, B2M, PTPRC, CD44 and SPP1, and identified the corresponding small molecule drugs. Our study identified key genes possibly related to energy metabolism in the pathological mechanism of AD and explored potential targets for AD treatment by establishing interaction networks.

Figure 1

Volcano plot illustrating DEGs. (A) The volcano plot shows the DEGs between the control group and AD, red represents up-regulated genes, blue represents down-regulated genes, and gray represents genes with little fold change. (B) Venn plots show common genes associated with copper metabolism in GSE5281. DEGs, differentially expressed genes.

Figure 2

The visual flow-process diagram of this study. AD: Alzheimer's disease, CM-genes: Copper metabolism-related genes, DEGs: Differentially expressed genes, GO: Gene Ontology, KEGG: Kyoto Encyclopedia of Genes and Genome.

Figure 3

Gene Ontology analysis. Biological process (BP, A); cellular component (CC, B); molecular function (MF, C); and analysis results of 87 DEGs with copper metabolism.

Figure 4

Network of enriched terms. (A) colored by cluster ID, where nodes that share the same cluster ID are typically close to one another; (B) colored by p-value, where terms containing more genes tend to have a more significant p-value.

Figure 5

g:Profiler performs functional enrichment analysis, also known as over-representation analysis (ORA) or gene set enrichment analysis, on DEGs list. In addition to Gene Ontology, it includes pathways from KEGG Reactome and WikiPathways. Red represents MF, orange represents BP, green represents CC, pink represents KEGG, blue represents REAC.

Figure 6

The two most prominent modules in the PPI network. (A) is module 1, (B) is module 2.

Figure 7

GO analysis of two modules. Bar graph of enriched terms across modules gene lists, colored by p-values. (A) module 1. (B) module 2.

Figure 8

Molecular docking pattern of the compounds identified in the DrugBank database with the corresponding targets (B2M and F2F). (A) B2M-3-indolebutyric acid [affinity (kcal/mol): − 5.4]; (B) B2M-doxycycline [affinity (kcal/mol): − 7.3]; (C) B2M-n-formylmethionine [affinity (kcal/mol): − 3.8]; (D) F2F-sirolimus [affinity (kcal/mol): − 8.2]; (E) F2F-pentosan polysulfate [affinity (kcal/mol): − 6.9]; (F) F2F-ABT-510 [affinity (kcal/mol): − 6.4]; (G) F2F-1,4-dideoxy-O2-sulfo-glucuronic acid [affinity (kcal/mol): − 8.3]; (H) F2F-1,4-dideoxy-5-dehydro-O2-sulfo -glucuronic acid [affinity (kcal/mol): − 6.0].