Evidence map›Paper›PMID 36052061›Full record

ArticleFrontiers in immunology2022

Bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation-promoted renal injury in severe COVID-19.

Zhimin Chen, Caiming Chen, Fengbin Chen, Ruilong Lan, Guo Lin, Yanfang Xu

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 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 21% 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

7 citing papers in PubMed, 11 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

6 authors at 2 institutions in 1 country.

Zhimin ChenDepartment of Nephrology, Blood Purification Research Center, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Caiming ChenDepartment of Nephrology, Blood Purification Research Center, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Fengbin ChenDepartment of Traditional Chinese Medicine, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Ruilong LanCentral Laboratory, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Guo LinDepartment of Intensive Care Unit, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Yanfang XuDepartment of Nephrology, Blood Purification Research Center, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
First Affiliated Hospital of Fujian Medical University · CNFujian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Renal injury secondary to COVID-19 is an important factor for the poor prognosis of COVID-19 patients. The pathogenesis of renal injury caused by aberrant immune inflammatory of COVID-19 remains unclear. In this study, a total of 166 samples from 4 peripheral blood transcriptomic datasets of COVID-19 patients were integrated. By using the weighted gene co-expression network (WGCNA) algorithm, we identified key genes for mild, moderate, and severe COVID-19. Subsequently, taking these genes as input genes, we performed Short Time-series Expression Miner (STEM) analysis in a time consecutive ischemia-reperfusion injury (IRI) -kidney dataset to identify genes associated with renal injury in COVID-19. The results showed that only in severe COVID-19 there exist a small group of genes associated with the progression of renal injury. Gene enrichment analysis revealed that these genes are involved in extensive immune inflammation and cell death-related pathways. A further protein-protein interaction (PPI) network analysis screened 15 PPI-hub genes:

Indexed as

Computational BiologyCOVID-19Biomarkers, TumorHumansKidneyLigandsBiomarkers, TumorLigandsbioinformaticsCOVID-19nomogramrenal injurySTEMWGCNA

Identifiers

PMID36052061
PMCPMC9424635
OpenAlexW4291820622

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.