Evidence map›Paper›PMID 36072597›Full record

ArticleFrontiers in immunology2022

Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data.

Zehua Dong, Qiyu Yan, Wenxiu Cao, Zhixian Liu, Xiaosheng Wang

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 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.6field-weighted citation impact, top 15% 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

13 citing papers in PubMed, 18 citations in OpenAlex.

  1. Exploration of shared gene signatures and molecular mechanisms between psoriasis and COVID-19: evidence from transcriptome data.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
    Article
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  7. UnravelingFrontiers in oncology · 2024
    Review
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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

5 authors at 2 institutions in 1 country.

Zehua DongBiomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.
Qiyu YanBiomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.
Wenxiu CaoBiomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.
Zhixian LiuJiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Xiaosheng WangBiomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.
China Pharmaceutical University · CNNanjing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Although several key molecules have been identified to modulate SARS-CoV-2 invasion of human host cells, the molecules correlated with outcomes in COVID-19 caused by SARS-CoV-2 infection remain insufficiently explored. Methods: This study analyzed three RNA-Seq gene expression profiling datasets for COVID-19 and identified differentially expressed genes (DEGs) between COVID-19 patients and normal people, commonly in the three datasets. Furthermore, this study explored the correlation between the expression of these genes and clinical features in COVID-19 patients. Results: This analysis identified 13 genes significantly upregulated in COVID-19 patients' leukocyte and SARS-CoV-2-infected nasopharyngeal tissue compared to normal tissue. These genes included Conclusions: A strong antiviral immune response is essential in reducing severity of COVID-19.

Indexed as

COVID-19TranscriptomeAntiviral AgentsGene Expression ProfilingHumansSARS-CoV-2Antiviral Agentsantiviral immune responsesCOVID-19COVID-19 clustersintensive care unitmechanical ventilatory supportviral loads

Identifiers

PMID36072597
PMCPMC9441550
OpenAlexW4292566765

What OpenQuestion 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 OpenQuestion graph.