Zhang Xiuning, Yu Hailei, Bai Rui, Ma Chunling
Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang, China.
Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology, Chinese Academy of Medical Sciences, Shijiazhuang, China.
Front Neurosci. 2020 Nov 27;14:608349. doi: 10.3389/fnins.2020.608349. eCollection 2020.
Although numerous studies have confirmed that the mechanisms of opiate addiction include genetic and epigenetic aspects, the results of such studies are inconsistent. Here, we downloaded gene expression profiling information, GSE87823, from the Gene Expression Omnibus database. Samples from males between ages 19 and 35 were selected for analysis of differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses were used to analyze the pathways associated with the DEGs. We further constructed protein-protein interaction (PPI) networks using the STRING database and used 10 different calculation methods to validate the hub genes. Finally, we utilized the Basic Local Alignment Search Tool (BLAST) to identify the DEG with the highest sequence similarity in mouse and detected the change in expression of the hub genes in this animal model using RT-qPCR. We identified three key genes, , , and . expression decreased in the nucleus accumbens of opioid-addicted mice compared with control mice, which was consistent with the change seen in humans. The importance and originality of this study are provided by two aspects. Firstly, we used a variety of calculation methods to obtain hub genes; secondly, we exploited homology analysis to solve the difficult challenge that addiction-related experiments cannot be carried out in patients or healthy individuals. In short, this study not only explores potential biomarkers and therapeutic targets of opioid addiction but also provides new ideas for subsequent research on opioid addiction.
尽管众多研究已证实阿片类药物成瘾机制包括遗传和表观遗传方面，但此类研究结果并不一致。在此，我们从基因表达综合数据库下载了基因表达谱信息GSE87823。选取19至35岁男性的样本用于分析差异表达基因（DEG）。使用京都基因与基因组百科全书（KEGG）通路和基因本体论（GO）富集分析来分析与DEG相关的通路。我们进一步使用STRING数据库构建蛋白质-蛋白质相互作用（PPI）网络，并使用10种不同计算方法来验证枢纽基因。最后，我们利用基本局部比对搜索工具（BLAST）在小鼠中鉴定出序列相似性最高的DEG，并使用逆转录定量聚合酶链反应（RT-qPCR）检测该动物模型中枢纽基因的表达变化。我们鉴定出三个关键基因， 、 和 。与对照小鼠相比，阿片类药物成瘾小鼠伏隔核中的 表达下降，这与在人类中观察到的变化一致。本研究的重要性和创新性体现在两个方面。首先，我们使用多种计算方法来获得枢纽基因；其次，我们利用同源性分析来解决无法在患者或健康个体中进行成瘾相关实验这一难题。简而言之，本研究不仅探索了阿片类药物成瘾的潜在生物标志物和治疗靶点，还为后续阿片类药物成瘾研究提供了新思路。
