SARS-CoV-2 感染患者宿主脂质代谢的基因表达谱:系统评价和综合生物信息学分析。
Gene expression profiling of host lipid metabolism in SARS-CoV-2 infected patients: a systematic review and integrated bioinformatics analysis.
机构信息
Faculty of Medicine and Health Sciences, Universiti Sains Islam Malaysia, Nilai, Malaysia.
Tropical Infectious Diseases Research and Education Centre (TIDREC), Universiti Malaya, Kuala Lumpur, Malaysia.
出版信息
BMC Infect Dis. 2024 Jan 23;24(1):124. doi: 10.1186/s12879-024-08983-0.
BACKGROUND
The Coronavirus disease 2019 (COVID-19) pandemic occurred due to the dispersion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Severe symptoms can be observed in COVID-19 patients with lipid-related comorbidities such as obesity and diabetes. Yet, the extensive molecular mechanisms of how SARS-CoV-2 causes dysregulation of lipid metabolism remain unknown.
METHODS
Here, an advanced search of articles was conducted using PubMed, Scopus, EBSCOhost, and Web of Science databases using terms from Medical Subject Heading (MeSH) like SARS-CoV-2, lipid metabolism and transcriptomic as the keywords. From 428 retrieved studies, only clinical studies using next-generation sequencing as a gene expression method in COVID-19 patients were accepted. Study design, study population, sample type, the method for gene expression and differentially expressed genes (DEGs) were extracted from the five included studies. The DEGs obtained from the studies were pooled and analyzed using the bioinformatics software package, DAVID, to determine the enriched pathways. The DEGs involved in lipid metabolic pathways were selected and further analyzed using STRING and Cytoscape through visualization by protein-protein interaction (PPI) network complex.
RESULTS
The analysis identified nine remarkable clusters from the PPI complex, where cluster 1 showed the highest molecular interaction score. Three potential candidate genes (PPARG, IFITM3 and APOBEC3G) were pointed out from the integrated bioinformatics analysis in this systematic review and were chosen due to their significant role in regulating lipid metabolism. These candidate genes were significantly involved in enriched lipid metabolic pathways, mainly in regulating lipid homeostasis affecting the pathogenicity of SARS-CoV-2, specifically in mechanisms of viral entry and viral replication in COVID-19 patients.
CONCLUSIONS
Taken together, our findings in this systematic review highlight the affected lipid-metabolic pathways along with the affected genes upon SARS-CoV-2 invasion, which could be a potential target for new therapeutic strategies study in the future.
背景
2019 年冠状病毒病(COVID-19)是由严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)传播引起的。COVID-19 患者伴有肥胖和糖尿病等脂质相关合并症时,可能会出现严重症状。然而,SARS-CoV-2 如何导致脂质代谢失调的广泛分子机制尚不清楚。
方法
在此,通过使用 PubMed、Scopus、EBSCOhost 和 Web of Science 数据库,使用医学主题词(MeSH)中的术语(如 SARS-CoV-2、脂质代谢和转录组)作为关键字,对文章进行了高级搜索。从 428 篇检索到的研究中,仅接受了使用下一代测序作为 COVID-19 患者基因表达方法的临床研究。从 5 项纳入研究中提取研究设计、研究人群、样本类型、基因表达方法和差异表达基因(DEGs)。使用生物信息学软件包 DAVID 对获得的 DEGs 进行汇集和分析,以确定富集途径。选择涉及脂质代谢途径的 DEGs,并通过 STRING 和 Cytoscape 通过蛋白质-蛋白质相互作用(PPI)网络复合物的可视化进一步分析。
结果
该分析从 PPI 复合物中确定了 9 个显著的簇,其中簇 1 显示出最高的分子相互作用评分。从本系统评价的综合生物信息学分析中指出了 3 个潜在的候选基因(PPARG、IFITM3 和 APOBEC3G),由于它们在调节脂质代谢中的重要作用而被选中。这些候选基因显著参与了富含脂质代谢途径的富集,主要在调节脂质稳态方面,影响 SARS-CoV-2 的致病性,特别是在 COVID-19 患者中病毒进入和病毒复制的机制。
结论
总之,本系统评价中的发现强调了 SARS-CoV-2 入侵时受影响的脂质代谢途径以及受影响的基因,这可能是未来新治疗策略研究的潜在靶点。