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无症状和重症新冠肺炎患者的计算机转录分析揭示了重症患者对其他合并症和非病毒病理状况的易感性。

In silico transcriptional analysis of asymptomatic and severe COVID-19 patients reveals the susceptibility of severe patients to other comorbidities and non-viral pathological conditions.

作者信息

Sen Poonam, Kaur Harpreet

机构信息

Pine Biotech, New Orleans, United States.

出版信息

Hum Gene (Amst). 2023 Feb;35:201135. doi: 10.1016/j.humgen.2022.201135. Epub 2022 Dec 16.

Abstract

COVID-19 is a severe respiratory disease caused by SARS-CoV-2, a novel human coronavirus. Patients infected with SARS-CoV-2 exhibit heterogeneous symptoms that pose pragmatic hurdles for implementing appropriate therapy and management of the COVID-19 patients and their post-COVID complications. Thus, understanding the impact of infection severity at the molecular level in the host is vital to understand the host response and accordingly it's precise management. In the current study, we performed a comparative transcriptomics analysis of publicly available seven asymptomatic and eight severe COVID-19 patients. Exploratory data analysis employing Principal Component Analysis (PCA) showed the distinct clusters of asymptomatic and severe patients. Subsequently, the differential gene expression analysis using DESeq2 identified 1224 significantly upregulated genes (logFC≥ 1.5, p-adjusted value <0.05) and 268 significantly downregulated genes (logFC≤ -1.5, p-adjusted value <0.05) in severe samples in comparison to asymptomatic samples. Eventually, Gene Set Enrichment Analysis (GSEA) revealed the upregulation of anti-viral and anti-inflammatory pathways, secondary infections, Iron homeostasis, anemia, cardiac-related, etc.; while, downregulation of lipid metabolism, adaptive immune response, translation, recurrent respiratory infections, heme-biosynthetic pathways, etc. Conclusively, these findings provide insight into the enhanced susceptibility of severe COVID-19 patients to other health comorbidities including non-viral pathogenic infections, atherosclerosis, autoinflammatory diseases, anemia, male infertility, etc. owing to the activation of biological processes, pathways and molecular functions associated with them. We anticipate this study will facilitate the researchers in finding efficient therapeutic targets and eventually the clinicians in management of COVID-19 patients and post-COVID-19 effects in them.

摘要

新冠病毒病(COVID-19)是由一种新型人类冠状病毒严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引起的严重呼吸道疾病。感染SARS-CoV-2的患者表现出异质性症状,这给实施对COVID-19患者及其新冠后并发症的适当治疗和管理带来了实际障碍。因此,在分子水平上了解感染严重程度对宿主的影响对于理解宿主反应及其精确管理至关重要。在本研究中,我们对公开可得的7例无症状和8例重症COVID-19患者进行了比较转录组学分析。采用主成分分析(PCA)的探索性数据分析显示了无症状和重症患者的不同聚类。随后,使用DESeq2进行的差异基因表达分析确定,与无症状样本相比,重症样本中有1224个基因显著上调(logFC≥1.5,校正p值<0.05),268个基因显著下调(logFC≤ -1.5,校正p值<0.05)。最终,基因集富集分析(GSEA)揭示了抗病毒和抗炎途径、继发感染、铁稳态、贫血、心脏相关等途径的上调;而脂质代谢、适应性免疫反应、翻译、反复呼吸道感染、血红素生物合成途径等下调。总之,这些发现揭示了重症COVID-19患者由于与其他健康合并症相关的生物过程、途径和分子功能的激活,对包括非病毒病原体感染、动脉粥样硬化、自身炎症性疾病、贫血、男性不育等其他健康合并症的易感性增加。我们预计这项研究将有助于研究人员找到有效的治疗靶点,并最终帮助临床医生管理COVID-19患者及其新冠后影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/525d/9754755/9d3343180719/ga1_lrg.jpg

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