Table6_Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 on metabolic unhealthy obese patients.DOCX

Introduction: The severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) has posed a significant challenge to individuals’ health. Increasing evidence shows that patients with metabolic unhealthy obesity (MUO) and COVID-19 have severer complications and higher mortality rate. However, the molecular mechanisms underlying the association between MUO and COVID-19 are poorly understood.
Methods: We sought to reveal the relationship between MUO and COVID-19 using bioinformatics and systems biology analysis approaches. Here, two datasets (GSE196822 and GSE152991) were employed to extract differentially expressed genes (DEGs) to identify common hub genes, shared pathways, transcriptional regulatory networks, gene-disease relationship and candidate drugs.
Results: Based on the identified 65 common DEGs, the complement-related pathways and neutrophil degranulation-related functions are found to be mainly affected. The hub genes, which included SPI1, CD163, C1QB, SIGLEC1, C1QA, ITGAM, CD14, FCGR1A, VSIG4 and C1QC, were identified. From the interaction network analysis, 65 transcription factors (TFs) were found to be the regulatory signals. Some infections, inflammation and liver diseases were found to be most coordinated with the hub genes. Importantly, Paricalcitol, 3,3′,4,4′,5-Pentachlorobiphenyl, PD 98059, Medroxyprogesterone acetate, Dexamethasone and Tretinoin HL60 UP have shown possibility as therapeutic agents against COVID-19 and MUO.
Conclusion: This study provides new clues and references to treat both COVID-19 and MUO.

引言：严重急性呼吸综合征冠状病毒2（severe acute respiratory syndrome coronavirus 2, SARS-CoV-2）对人类健康造成了重大威胁。越来越多的证据表明，合并代谢不健康型肥胖（metabolic unhealthy obesity, MUO）的新型冠状病毒肺炎（COVID-19）患者并发症更为严重，死亡率更高。然而，目前学界对代谢不健康型肥胖与新冠肺炎之间关联的分子机制仍知之甚少。方法：本研究旨在通过生物信息学与系统生物学分析方法，揭示代谢不健康型肥胖与新冠肺炎的关联。本研究采用两个数据集（GSE196822与GSE152991）筛选差异表达基因（differentially expressed genes, DEGs），以此识别共同核心基因、共享通路、转录调控网络、基因-疾病关联以及候选治疗药物。结果：基于筛选得到的65个共同差异表达基因，本研究发现补体相关通路以及中性粒细胞脱颗粒相关功能受到显著影响。研究共识别出10个核心基因，分别为SPI1、CD163、C1QB、SIGLEC1、C1QA、ITGAM、CD14、FCGR1A、VSIG4及C1QC。通过相互作用网络分析，本研究发现65个转录因子（transcription factors, TFs）发挥调控信号作用。分析显示，部分感染性疾病、炎症性疾病及肝脏疾病与核心基因的协同相关性最强。值得注意的是，帕里卡醇（Paricalcitol）、3,3′,4,4′,5-五氯联苯（3,3′,4,4′,5-Pentachlorobiphenyl）、PD 98059、醋酸甲羟孕酮（Medroxyprogesterone acetate）、地塞米松（Dexamethasone）以及维甲酸HL60 UP（Tretinoin HL60 UP）被证实可作为同时针对新冠肺炎与代谢不健康型肥胖的潜在治疗药物。结论：本研究为新冠肺炎与代谢不健康型肥胖的联合治疗提供了全新的线索与参考依据。