Identification and Verification of Potential Hub Genes in Amphetamine-Type Stimulant (ATS) and Opioid Dependence by Bioinformatic Analysis

Abstract

Objective: Amphetamine-type stimulant (ATS) and opioid dependencies are chronic inflammatory diseases with similar symptoms and common genomics. However, their coexpressive genes have not been thoroughly investigated. We aimed to identify and verify the coexpressive hub genes and pathway involved in the pathogenesis of ATS and opioid dependencies. Methods: The microarray of ATS- and opioid-treatment mouse models was obtained from the Gene Expression Omnibus database. GEO2R and Venn diagram were performed to identify differentially expressed genes (DEGs) and coexpressive DEGs (CDEGs). Functional annotation and protein-protein interaction network detected the potential functions. The hub genes were screened using the CytoHubba and MCODE plugin with different algorithms, and further validated by receiver operating characteristic analysis in the GSE15774 database. We also validated the hub genes mRNA levels in BV2 cells using qPCR. Result: Forty-four CDEGs were identified between ATS and opioid databases, which were prominently enriched in the PI3K/Akt signaling pathway. The top 10 hub genes were mainly enriched in apoptotic process (CD44, Dusp1, Sgk1, and Hspa1b), neuron differentiation, migration, and proliferation (Nr4a2 and Ddit4), response to external stimulation (Fos and Cdkn1a), and transcriptional regulation (Nr4a2 and Npas4). Receiver operating characteristic (ROC) analysis found that six hub genes (Fos, Dusp1, Sgk1, Ddit4, Cdkn1a, and Nr4a2) have an area under the curve (AUC) of more than 0.70 in GSE15774. The mRNA levels of Fos, Dusp1, Sgk1, Ddit4, Cdkn1a, PI3K, and Akt in BV2 cells and GSE15774 with METH and heroin treatments were higher than those of controls. However, the Nr4a2 mRNA levels increased in BV2 cells and decreased in the bioinformatic analysis. Conclusions: The identification of hub genes was associated with ATS and opioid dependencies, which were involved in apoptosis, neuron differentiation, migration, and proliferation. The PI3K/Akt signaling pathway might play a critical role in the pathogenesis of substance dependence.

Keywords: PI3K/Akt pathway; amphetamine-type stimulants (ATS); apoptosis; differentially expressed genes (DEGs); hub gene; opioids.

FIGURE 1

Flow diagram of the study design.

FIGURE 2

METH) and heroin increased the mRNA levels of CD11b and inflammatory cytokine in immortalized mouse microglia cells (BV2) cells. The relative mRNA levels of CD11b by qPCR and cell viability by CCK-8 assay at varied concentrations (A, B) and various timepoints (C, D) between METH and heroin, respectively. The relative mRNA levels of CD11b, IL-6, and TNF-α treated with 1,000 μM METH and 200 μM heroin after 24 h (E–G), respectively. (*p < 0.05, **p < 0.01, ***p < 0.001 compared with the controls).

FIGURE 3

The coexpressive differentially expressed genes (CDEGs) in ATS- and opioid-treatment databases by Venn diagram.

FIGURE 4

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. GO analysis of DEGs with opioid (A) and ATS treatments (B). KEGG pathway enrichment analysis for DEGs in opioid (C) and ATS treatments (D). GO and KEGG pathway analysis for CDEGs (E).

FIGURE 5

The hub genes screened by the CytoHubba plugin and predicted by receiver operating characteristic (ROC) curve. The protein–protein interaction (PPI) network of CDEGs (A). Venn diagram of the top 10 hub genes by MCC, DMNC, MNC, and degree algorithms (B). The PPI network of TF-target genes by the iRegulon plugin (C). The ROC curve-predicted hub genes in GSE15774 (D). Red indicates the hub genes. Pink indicates the other DEGs. Blue indicates TF-target genes.

FIGURE 6

The relative mRNA levels of Fos (A), Dusp1 (B), Sgk1 (C), Nr4a2 (D), Ddit4 (E), Cdkn1a (F), PI3K (G), and Akt (H) in BV2 cells treated with 1,000 μM METH and 200 μM heroin after 24 h, respectively (^* p ＜ 0.05, ^** p ＜ 0.01, ^*** p ＜ 0.001 compared with the controls).