Identification and Verification of Key Genes Underlying Methamphetamine Sensitization Using Network-Based Analysis

Methamphetamine (METH) is a highly addictive psychostimulant that alters gene expression in brain reward circuits. This study aimed to identify METH-associated transcriptional changes in the nucleus accumbens (NAc) and explore potential pharmacological interventions.

We conducted an in silico analysis of publicly available microarray data (GSE46717) from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified using limma and analyzed for functional enrichment via EnrichR. Protein-protein interaction (PPI) networks were constructed using STRING to identify hub genes, validated in silico with jackknife resampling. Adult male Wistar rats were injected with METH (10 mg/ kg, followed by 2.5 mg/kg after one month), and expression of selected hub genes was measured in NAc tissue using quantitative polymerase chain reaction (qPCR). Connectivity mapping was applied to identify candidate drugs reversing METH-induced transcriptional changes.

We identified 280 DEGs (210 upregulated, 70 downregulated). Upregulated pathways included caffeine metabolism, long-term potentiation, and cocaine addiction, whereas GABAergic and glutamatergic synapse genes were downregulated. Network analysis highlighted Fos, Crh, Oprl1, and Slc17a6 as hub genes, validated both computationally and experimentally. Connectivity mapping identified D-64131 and Mebendazole as potential therapeutics.

METH induces substantial transcriptional alterations in the NAc, affecting synaptic signaling and addiction pathways. Integrating in silico network analysis with experimental validation identified robust hub genes and suggested candidate compounds for therapeutic intervention.