Evidence map›Paper›PMID 36211429›Full record

ArticleFrontiers in immunology2022

Bioinformatics and systems-biology analysis to determine the effects of Coronavirus disease 2019 on patients with allergic asthma.

Hongwei Fang, Zhun Sun, Zhouyi Chen, Anning Chen, Donglin Sun, Yan Kong, Hao Fang, Guojun Qian

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
0.9field-weighted citation impact, top 25% 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, 9 citations in OpenAlex.

  1. Article
  2. Targeting mitochondrial function as a potential therapeutic approach for allergic asthma.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025
    Review
  3. Article
  4. Article
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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

8 authors at 3 institutions in 1 country.

Hongwei FangDepartment of Anesthesiology, Zhongshan Hospital, Fudan University, Shanghai, China.
Zhun SunAffiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China.
Zhouyi ChenDepartment of Anesthesiology, Zhongshan Hospital, Fudan University, Shanghai, China.
Anning ChenAffiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China.
Donglin SunAffiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China.
Yan KongDepartment of Anesthesiology (High-Tech Branch), The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Hao FangDepartment of Anesthesiology, Zhongshan Hospital, Fudan University, Shanghai, China.
Guojun QianAffiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China.
Sun Yat-sen University · CNGuangzhou Medical University · CNAnhui Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The coronavirus disease (COVID-19) pandemic has posed a significant challenge for global health systems. Increasing evidence shows that asthma phenotypes and comorbidities are major risk factors for COVID-19 symptom severity. However, the molecular mechanisms underlying the association between COVID-19 and asthma are poorly understood. Therefore, we conducted bioinformatics and systems biology analysis to identify common pathways and molecular biomarkers in patients with COVID-19 and asthma, as well as potential molecular mechanisms and candidate drugs for treating patients with both COVID-19 and asthma. Methods: Two sets of differentially expressed genes (DEGs) from the GSE171110 and GSE143192 datasets were intersected to identify common hub genes, shared pathways, and candidate drugs. In addition, murine models were utilized to explore the expression levels and associations of the hub genes in asthma and lung inflammation/injury. Results: We discovered 157 common DEGs between the asthma and COVID-19 datasets. A protein-protein-interaction network was built using various combinatorial statistical approaches and bioinformatics tools, which revealed several hub genes and critical modules. Six of the hub genes were markedly elevated in murine asthmatic lungs and were positively associated with IL-5, IL-13 and MUC5AC, which are the key mediators of allergic asthma. Gene Ontology and pathway analysis revealed common associations between asthma and COVID-19 progression. Finally, we identified transcription factor-gene interactions, DEG-microRNA coregulatory networks, and potential drug and chemical-compound interactions using the hub genes. Conclusion: We identified the top 15 hub genes that can be used as novel biomarkers of COVID-19 and asthma and discovered several promising candidate drugs that might be helpful for treating patients with COVID-19 and asthma.

Indexed as

AsthmaCOVID-19MicroRNAsAnimalsBiomarkers, TumorComputational BiologyGene Expression ProfilingGene Regulatory NetworksInterleukin-13Interleukin-5MiceSystems BiologyTranscription FactorsBiomarkers, TumorInterleukin-13Interleukin-5MicroRNAsTranscription Factorsallergic asthmabioinformaticscoronavirus disease 2019disease biomarkerdruggene ontologyhub genesystems-biology

Identifiers

PMID36211429
PMCPMC9537444
OpenAlexW4297004820

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.