Sagulkoo Pakorn, Chuntakaruk Hathaichanok, Rungrotmongkol Thanyada, Suratanee Apichat, Plaimas Kitiporn
Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok 10330, Thailand.
Center of Biomedical Informatics, Department of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand.
J Pers Med. 2022 Jun 23;12(7):1030. doi: 10.3390/jpm12071030.
The coronavirus disease 2019 (COVID-19) pandemic causes many morbidity and mortality cases. Despite several developed vaccines and antiviral therapies, some patients experience severe conditions that need intensive care units (ICU); therefore, precision medicine is necessary to predict and treat these patients using novel biomarkers and targeted drugs. In this study, we proposed a multi-level biological network analysis framework to identify key genes via protein-protein interaction (PPI) network analysis as well as survival analysis based on differentially expressed genes (DEGs) in leukocyte transcriptomic profiles, discover novel biomarkers using microRNAs (miRNA) from regulatory network analysis, and provide candidate drugs targeting the key genes using drug-gene interaction network and structural analysis. The results show that upregulated DEGs were mainly enriched in cell division, cell cycle, and innate immune signaling pathways. Downregulated DEGs were primarily concentrated in the cellular response to stress, lysosome, glycosaminoglycan catabolic process, and mature B cell differentiation. Regulatory network analysis revealed that hsa-miR-6792-5p, hsa-let-7b-5p, hsa-miR-34a-5p, hsa-miR-92a-3p, and hsa-miR-146a-5p were predicted biomarkers. , , , and were identified as key genes in severe COVID-19. In addition, drug repurposing from drug-gene and drug-protein database searching and molecular docking showed that camptothecin and doxorubicin were candidate drugs interacting with the key genes. In conclusion, multi-level systems biology analysis plays an important role in precision medicine by finding novel biomarkers and targeted drugs based on key gene identification.
2019年冠状病毒病（COVID-19）大流行导致了许多发病和死亡病例。尽管有几种已研发的疫苗和抗病毒疗法，但一些患者仍会出现需要重症监护病房（ICU）治疗的严重病情；因此，精准医学对于使用新型生物标志物和靶向药物来预测和治疗这些患者而言是必要的。在本研究中，我们提出了一个多层次生物网络分析框架，通过蛋白质-蛋白质相互作用（PPI）网络分析以及基于白细胞转录组谱中差异表达基因（DEG）的生存分析来识别关键基因，通过调控网络分析利用 microRNA（miRNA）发现新型生物标志物，并利用药物-基因相互作用网络和结构分析提供靶向关键基因的候选药物。结果表明，上调的DEG主要富集在细胞分裂、细胞周期和先天免疫信号通路中。下调的DEG主要集中在细胞对应激的反应、溶酶体、糖胺聚糖分解代谢过程以及成熟B细胞分化中。调控网络分析显示，hsa-miR-6792-5p、hsa-let-7b-5p、hsa-miR-34a-5p、hsa-miR-92a-3p和hsa-miR-146a-5p是预测的生物标志物。 、 、 和 被确定为重症COVID-19中的关键基因。此外，从药物-基因和药物-蛋白质数据库搜索以及分子对接进行的药物重新利用表明，喜树碱和阿霉素是与关键基因相互作用的候选药物。总之，多层次系统生物学分析通过基于关键基因识别发现新型生物标志物和靶向药物，在精准医学中发挥着重要作用。
