A consideration of publication-derived immune-related associations in Coronavirus and related lung damaging diseases.
Betacoronavirus
COVID-19
Cluster Analysis
Comorbidity
Coronavirus Infections
/ immunology
Cytokine Release Syndrome
/ virology
Cytokines
/ immunology
Hematopoietic Stem Cells
/ cytology
Humans
Immune System
Influenza A Virus, H5N1 Subtype
Influenza, Human
/ immunology
Lung Diseases
/ immunology
Pandemics
Pneumonia, Viral
/ immunology
PubMed
Publications
SARS-CoV-2
Severe Acute Respiratory Syndrome
/ immunology
COVID-19
Coronavirus
Cytokines
H5N1 influenza
Haematopoietic cells
SARS
Journal
Journal of translational medicine
ISSN: 1479-5876
Titre abrégé: J Transl Med
Pays: England
ID NLM: 101190741
Informations de publication
Date de publication:
03 08 2020
03 08 2020
Historique:
received:
11
05
2020
accepted:
28
07
2020
entrez:
5
8
2020
pubmed:
5
8
2020
medline:
15
8
2020
Statut:
epublish
Résumé
The severe acute respiratory syndrome virus SARS-CoV-2, a close relative of the SARS-CoV virus, is the cause of the recent COVID-19 pandemic affecting, to date, over 14 million individuals across the globe and demonstrating relatively high rates of infection and mortality. A third virus, the H5N1, responsible for avian influenza, has caused infection with some clinical similarities to those in COVID-19 infections. Cytokines, small proteins that modulate immune responses, have been directly implicated in some of the severe responses seen in COVID-19 patients, e.g. cytokine storms. Understanding the immune processes related to COVID-19, and other similar infections, could help identify diagnostic markers and therapeutic targets. Here we examine data of cytokine, immune cell types, and disease associations captured from biomedical literature associated with COVID-19, Coronavirus in general, SARS, and H5N1 influenza, with the objective of identifying potentially useful relationships and areas for future research. Cytokine and cell-type associations captured from Medical Subject Heading (MeSH) terms linked to thousands of PubMed records, has identified differing patterns of associations between the four corpuses of publications (COVID-19, Coronavirus, SARS, or H5N1 influenza). Clustering of cytokine-disease co-occurrences in the context of Coronavirus has identified compelling clusters of co-morbidities and symptoms, some of which already known to be linked to COVID-19. Finally, network analysis identified sub-networks of cytokines and immune cell types associated with different manifestations, co-morbidities and symptoms of Coronavirus, SARS, and H5N1. Systematic review of research in medicine is essential to facilitate evidence-based choices about health interventions. In a fast moving pandemic the approach taken here will identify trends and enable rapid comparison to the literature of related diseases.
Sections du résumé
BACKGROUND
The severe acute respiratory syndrome virus SARS-CoV-2, a close relative of the SARS-CoV virus, is the cause of the recent COVID-19 pandemic affecting, to date, over 14 million individuals across the globe and demonstrating relatively high rates of infection and mortality. A third virus, the H5N1, responsible for avian influenza, has caused infection with some clinical similarities to those in COVID-19 infections. Cytokines, small proteins that modulate immune responses, have been directly implicated in some of the severe responses seen in COVID-19 patients, e.g. cytokine storms. Understanding the immune processes related to COVID-19, and other similar infections, could help identify diagnostic markers and therapeutic targets.
METHODS
Here we examine data of cytokine, immune cell types, and disease associations captured from biomedical literature associated with COVID-19, Coronavirus in general, SARS, and H5N1 influenza, with the objective of identifying potentially useful relationships and areas for future research.
RESULTS
Cytokine and cell-type associations captured from Medical Subject Heading (MeSH) terms linked to thousands of PubMed records, has identified differing patterns of associations between the four corpuses of publications (COVID-19, Coronavirus, SARS, or H5N1 influenza). Clustering of cytokine-disease co-occurrences in the context of Coronavirus has identified compelling clusters of co-morbidities and symptoms, some of which already known to be linked to COVID-19. Finally, network analysis identified sub-networks of cytokines and immune cell types associated with different manifestations, co-morbidities and symptoms of Coronavirus, SARS, and H5N1.
CONCLUSION
Systematic review of research in medicine is essential to facilitate evidence-based choices about health interventions. In a fast moving pandemic the approach taken here will identify trends and enable rapid comparison to the literature of related diseases.
Identifiants
pubmed: 32746922
doi: 10.1186/s12967-020-02472-z
pii: 10.1186/s12967-020-02472-z
pmc: PMC7397454
doi:
Substances chimiques
Cytokines
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
297Subventions
Organisme : Medical Research Council
ID : MR/M008959/1
Pays : United Kingdom
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