Evidence map›Paper›PMID 36119022›Full record

ArticleFrontiers in immunology2022

Discovering common pathogenetic processes between COVID-19 and sepsis by bioinformatics and system biology approach.

Lu Lu, Le-Ping Liu, Rong Gui, Hang Dong, Yan-Rong Su, Xiong-Hui Zhou, Feng-Xia Liu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
4.1field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 41 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Lu LuDepartment of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China.
Le-Ping LiuDepartment of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China.
Rong GuiDepartment of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China.
Hang DongDepartment of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China.
Yan-Rong SuDepartment of Laboratory Medicine, The Third Xiangya Hospital of Central South University, Changsha, China.
Xiong-Hui ZhouDepartment of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China.
Feng-Xia LiuDepartment of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China.
Third Xiangya Hospital · CNCentral South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Corona Virus Disease 2019 (COVID-19), an acute respiratory infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread rapidly worldwide, resulting in a pandemic with a high mortality rate. In clinical practice, we have noted that many critically ill or critically ill patients with COVID-19 present with typical sepsis-related clinical manifestations, including multiple organ dysfunction syndrome, coagulopathy, and septic shock. In addition, it has been demonstrated that severe COVID-19 has some pathological similarities with sepsis, such as cytokine storm, hypercoagulable state after blood balance is disrupted and neutrophil dysfunction. Considering the parallels between COVID-19 and non-SARS-CoV-2 induced sepsis (hereafter referred to as sepsis), the aim of this study was to analyze the underlying molecular mechanisms between these two diseases by bioinformatics and a systems biology approach, providing new insights into the pathogenesis of COVID-19 and the development of new treatments. Specifically, the gene expression profiles of COVID-19 and sepsis patients were obtained from the Gene Expression Omnibus (GEO) database and compared to extract common differentially expressed genes (DEGs). Subsequently, common DEGs were used to investigate the genetic links between COVID-19 and sepsis. Based on enrichment analysis of common DEGs, many pathways closely related to inflammatory response were observed, such as Cytokine-cytokine receptor interaction pathway and NF-kappa B signaling pathway. In addition, protein-protein interaction networks and gene regulatory networks of common DEGs were constructed, and the analysis results showed that

Indexed as

COVID-19SepsisBiomarkersComputational BiologyCritical IllnessCytokinesEmetineGene Expression ProfilingHumansMolecular Docking SimulationNF-kappa BProgesteroneReceptors, CytokineSARS-CoV-2BiomarkersCytokinesEmetineNF-kappa BProgesteroneReceptors, CytokineCOVID-19differentially expressed gene (DEG)drug moleculefunctional enrichmentgene ontologyhub geneprotein–protein interaction (PPI)sepsis

Identifiers

PMID36119022
PMCPMC9471316
OpenAlexW4293767725

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.