新冠肺炎康复患者潜在机制和健康影响的整合转录组学和网络分析。

IF 2.3 Q3 BIOCHEMICAL RESEARCH METHODS
Bioinformatics and Biology Insights Pub Date : 2023-10-24 eCollection Date: 2023-01-01 DOI:10.1177/11779322231206684
Suthipong Chujan, Watanyoo Nakareangrit, Tawit Suriyo, Jutamaad Satayavivad
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引用次数: 0

摘要

2019冠状病毒病(新冠肺炎)是一种由严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引起的近期流行性疾病。目前,世界各地仍有新冠肺炎病例出院后可能发展为持续症状。被称为长期新冠肺炎的一系列症状会持续数月,并可能导致肺部炎症和心血管疾病等各种疾病,这可能会给人类健康带来巨大的经济负担和风险。此外,新冠肺炎大流行后综合征的分子机制尚不清楚。在这项研究中,我们旨在探索新冠肺炎康复者的分子机制、疾病关联和可能的健康风险。将人类恢复期新冠肺炎数据集的基因表达数据与健康正常个体的数据集进行比较,以鉴定差异表达基因(DEG)。为了确定生物功能和潜在的途径改变,使用GO和KEGG数据库来分析DEG。疾病相关性、组织和器官特异性分析用于确定可能的健康影响。在健康和恢复期新冠肺炎受试者之间共鉴定出250个DEG。所鉴定的生物功能改变揭示了细胞因子相互作用,并通过NF-κB1、RELA、JUN、STAT3和SP1增加炎症。有趣的是,最重要的途径是细胞因子-细胞因子受体相互作用、脂质代谢改变和动脉粥样硬化,它们在恢复期新冠肺炎中起着至关重要的作用。此外,我们还发现了肺炎、皮炎和自身免疫性疾病。根据我们的研究,恢复期新冠肺炎与多种器官的炎症有关,这些炎症可能导致自身免疫性和炎症性疾病以及动脉粥样硬化。这些发现是深入全面探索疾病机制以了解COVID-19后感染与潜在健康风险之间关系的第一步。这对于制定预防和治疗长期新冠肺炎的适当策略是必要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Integrated Transcriptomics and Network Analysis of Potential Mechanisms and Health Effects of Convalescent COVID-19 Patients.

Integrated Transcriptomics and Network Analysis of Potential Mechanisms and Health Effects of Convalescent COVID-19 Patients.

Integrated Transcriptomics and Network Analysis of Potential Mechanisms and Health Effects of Convalescent COVID-19 Patients.

Integrated Transcriptomics and Network Analysis of Potential Mechanisms and Health Effects of Convalescent COVID-19 Patients.

Coronaviral disease 2019 (COVID-19) is a recent pandemic disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, there are still cases of COVID-19 around the world that can develop into persistent symptoms after discharge. The constellation of symptoms, termed long COVID, persists for months and can lead to various diseases such as lung inflammation and cardiovascular disease, which may lead to considerable financial burden and possible risk to human health. Moreover, the molecular mechanisms underlying the post-pandemic syndrome of COVID-19 remain unclear. In this study, we aimed to explore the molecular mechanism, disease association, and possible health risks in convalescent COVID-19 patients. Gene expression data from a human convalescent COVID-19 data set was compared with a data set from healthy normal individuals in order to identify differentially expressed genes (DEGs). To determine biological function and potential pathway alterations, the GO and KEGG databases were used to analyze the DEGs. Disease association, tissue, and organ-specific analyses were used to identify possible health effects. A total of 250 DEGs were identified between healthy and convalescent COVID-19 subjects. The biological function alterations identified revealed cytokine interactions and increased inflammation through NF-κB1, RELA, JUN, STAT3, and SP1. Interestingly, the most significant pathways were cytokine-cytokine receptor interaction, altered lipid metabolism, and atherosclerosis that play a crucial role in convalescent COVID-19. In addition, we also found pneumonitis, dermatitis, and autoimmune diseases. Based on our study, convalescent COVID-19 is associated with inflammation in a variety of organs that could lead to autoimmune and inflammatory diseases, as well as atherosclerosis. These findings are a first step toward fully exploring the disease mechanisms in depth to understand the relationship between post-COVID-19 infection and potential health risks. This is necessary for the development of appropriate strategies for the prevention and treatment of long COVID.

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来源期刊
Bioinformatics and Biology Insights
Bioinformatics and Biology Insights BIOCHEMICAL RESEARCH METHODS-
CiteScore
6.80
自引率
1.70%
发文量
36
审稿时长
8 weeks
期刊介绍: Bioinformatics and Biology Insights is an open access, peer-reviewed journal that considers articles on bioinformatics methods and their applications which must pertain to biological insights. All papers should be easily amenable to biologists and as such help bridge the gap between theories and applications.
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