ArticleScientific reports2023
Predicting severity in COVID-19 disease using sepsis blood gene expression signatures.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Identification of potential characteristic genes in sepsis utilizing RNA sequencing and gene silence.BMC immunology · 2025Article
- Longitudinal gene expression analysis in COVID-19 sepsis highlights dynamic immune, cellular, and metabolic dysfunction in high severity patients.Scientific reports · 2025Article
- Minimalistic transcriptomic signatures permit accurate early prediction of COVID-19 mortality.JCI insight · 2025Article
- Biomarkers to guide sepsis management.Annals of intensive care · 2025Review
- A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis.Nature communications · 2025Article
- Colon cancer versus colitis: a microRNA and gene expression analysis via system biology tools.Gastroenterology and hepatology from bed to bench · 2025Article
- Reducing the burden of preventable deaths from sepsis in Canada: A need for a national sepsis action plan.Healthcare management forum · 2024Article
- COVID-19-Associated Sepsis: Potential Role of Phytochemicals as Functional Foods and Nutraceuticals.International journal of molecular sciences · 2024Review
- A single workflow for multi-species blood transcriptomics.BMC genomics · 2024Article
- Antibiotic failure: Beyond antimicrobial resistance.Drug resistance updates : reviews and commentaries in antimicrobial and anticancer chemotherapy · 2023Review
- The Impact of COVID-19 on Sepsis-Related Mortality in the United States.Journal of clinical medicine research · 2023Article
- Persistence is key: unresolved immune dysfunction is lethal in both COVID-19 and non-COVID-19 sepsis.Frontiers in immunology · 2023Article
- Re-Addressing Dementia by Network Medicine and Mechanism-Based Molecular Endotypes.Journal of Alzheimer's disease : JAD · 2023Article
- Post-COVID symptoms are associated with endotypes reflecting poor inflammatory and hemostatic modulation.Frontiers in immunology · 2023Article
- Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets.Frontiers in immunology · 2023Article
- Severe COVID-19 and non-COVID-19 severe sepsis converge transcriptionally after a week in the intensive care unit, indicating common disease mechanisms.Frontiers in immunology · 2023Observational
- Dysregulated early transcriptional signatures linked to mast cell and interferon responses are implicated in COVID-19 severity.Frontiers in immunology · 2023Article
- Implementation and impact of the global access principles at the University of British Columbia: current successes and future challenges.Frontiers in pharmacology · 2023Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Severely-afflicted COVID-19 patients can exhibit disease manifestations representative of sepsis, including acute respiratory distress syndrome and multiple organ failure. We hypothesized that diagnostic tools used in managing all-cause sepsis, such as clinical criteria, biomarkers, and gene expression signatures, should extend to COVID-19 patients. Here we analyzed the whole blood transcriptome of 124 early (1-5 days post-hospital admission) and late (6-20 days post-admission) sampled patients with confirmed COVID-19 infections from hospitals in Quebec, Canada. Mechanisms associated with COVID-19 severity were identified between severity groups (ranging from mild disease to the requirement for mechanical ventilation and mortality), and established sepsis signatures were assessed for dysregulation. Specifically, gene expression signatures representing pathophysiological events, namely cellular reprogramming, organ dysfunction, and mortality, were significantly enriched and predictive of severity and lethality in COVID-19 patients. Mechanistic endotypes reflective of distinct sepsis aetiologies and therapeutic opportunities were also identified in subsets of patients, enabling prediction of potentially-effective repurposed drugs. The expression of sepsis gene expression signatures in severely-afflicted COVID-19 patients indicates that these patients should be classified as having severe sepsis. Accordingly, in severe COVID-19 patients, these signatures should be strongly considered for the mechanistic characterization, diagnosis, and guidance of treatment using repurposed drugs.
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