dc.contributor.author | Sadanandam, A | |
dc.contributor.author | Bopp, T | |
dc.contributor.author | Dixit, S | |
dc.contributor.author | Knapp, DJHF | |
dc.contributor.author | Emperumal, CP | |
dc.contributor.author | Vergidis, P | |
dc.contributor.author | Rajalingam, K | |
dc.contributor.author | Melcher, A | |
dc.contributor.author | Kannan, N | |
dc.date.accessioned | 2021-03-02T16:07:29Z | |
dc.date.available | 2021-03-02T16:07:29Z | |
dc.date.issued | 2020-12-08 | |
dc.identifier.citation | Cell death discovery, 2020, 6 (1), pp. 141 - ? | |
dc.identifier.issn | 2058-7716 | |
dc.identifier.uri | https://repository.icr.ac.uk/handle/internal/4387 | |
dc.identifier.eissn | 2058-7716 | |
dc.identifier.doi | 10.1038/s41420-020-00376-x | |
dc.description.abstract | COVID-19 patients show heterogeneity in clinical presentation and outcomes that makes pandemic control and strategy difficult; optimizing management requires a systems biology approach of understanding the disease. Here we sought to potentially understand and infer complex disease progression, immune regulation, and symptoms in patients infected with coronaviruses (35 SARS-CoV and 3 SARS-CoV-2 patients and 57 samples) at two different disease progression stages. Further, we compared coronavirus data with healthy individuals (n = 16) and patients with other infections (n = 144; all publicly available data). We applied inferential statistics (the COVID-engine platform) to RNA profiles (from limited number of samples) derived from peripheral blood mononuclear cells (PBMCs). Compared to healthy individuals, a subset of integrated blood-based gene profiles (signatures) distinguished acute-like (mimicking coronavirus-infected patients with prolonged hospitalization) from recovering-like patients. These signatures also hierarchically represented multiple (at the system level) parameters associated with PBMC including dysregulated cytokines, genes, pathways, networks of pathways/concepts, immune status, and cell types. Proof-of-principle observations included PBMC-based increases in cytokine storm-associated IL6, enhanced innate immunity (macrophages and neutrophils), and lower adaptive T and B cell immunity in patients with acute-like disease compared to those with recovery-like disease. Patients in the recovery-like stage showed significantly enhanced TNF, IFN-γ, anti-viral, HLA-DQA1, and HLA-F gene expression and cytolytic activity, and reduced pro-viral gene expression compared to those in the acute-like stage in PBMC. Besides, our analysis revealed overlapping genes associated with potential comorbidities (associated diabetes) and disease-like conditions (associated with thromboembolism, pneumonia, lung disease, and septicemia). Overall, our COVID-engine inferential statistics platform and study involving PBMC-based RNA profiling may help understand complex and variable system-wide responses displayed by coronavirus-infected patients with further validation. | |
dc.format | Electronic | |
dc.format.extent | 141 - ? | |
dc.language | eng | |
dc.language.iso | eng | |
dc.publisher | SPRINGERNATURE | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0 | |
dc.title | A blood transcriptome-based analysis of disease progression, immune regulation, and symptoms in coronavirus-infected patients. | |
dc.type | Journal Article | |
dcterms.dateAccepted | 2020-11-13 | |
rioxxterms.version | VoR | |
rioxxterms.versionofrecord | 10.1038/s41420-020-00376-x | |
rioxxterms.licenseref.uri | https://creativecommons.org/licenses/by/4.0 | |
rioxxterms.licenseref.startdate | 2020-12-08 | |
rioxxterms.type | Journal Article/Review | |
dc.relation.isPartOf | Cell death discovery | |
pubs.issue | 1 | |
pubs.notes | Not known | |
pubs.organisational-group | /ICR | |
pubs.organisational-group | /ICR/Primary Group | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Molecular Pathology | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Molecular Pathology/Systems and Precision Cancer Medicine | |
pubs.organisational-group | /ICR | |
pubs.organisational-group | /ICR/Primary Group | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Molecular Pathology | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Molecular Pathology/Systems and Precision Cancer Medicine | |
pubs.publication-status | Published | |
pubs.volume | 6 | |
pubs.embargo.terms | Not known | |
icr.researchteam | Systems and Precision Cancer Medicine | |
icr.researchteam | Systems and Precision Cancer Medicine | |
dc.contributor.icrauthor | Melcher, Alan | |