Predict Key Biomarkers of Alcohol Dependence in Nucleus Accumbens by Weighted Gene Co-Expression Network Analysis

Abstract

Alcohol dependence (AD) is a complication behavioral disease interacted by a number of genes and environmental factors with high heritability. The main point of the study was to identify the regulatory mechanism exerted by the nucleus accumbens (NAc) in AD. We not only performed DEGs analysis but also carried WGCNA analysis in GSE62699 dataset, and then we used online tools for gene enrichment analysis of the DEGs and hub genes, and explored possible transcription factors. We conducted DEG analysis first, and then opted the top 25% of genes with the maximum variance to perform WGCNA analysis. Finally, through GO and KEGG analysis, we found that acute inflammation is the most important biological pathway in DEGs. Then signal transduction and cell communication are the main results of BP in WGCNA. We used the hub gene to explore the transcription factor (TF) which may have a key role using the web tool--miRNet, and found that TP53 and NFKB1 are the important TFs in NAc. From the result, the miRNAs and TFs may serve as potential biomarkers and treatment targets of AD, and all these findings may be a theoretical basis to explore the regulatory mechanisms of AD.