ArticleFrontiers in immunology2022
COVID-19 patients exhibit unique transcriptional signatures indicative of disease severity.
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 10 papers.
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Who cites it
10 citing papers in PubMed.
- Article
- Evolution of SARS-CoV-2 T cell responses as a function of multiple COVID-19 boosters.Cell reports · 2025Article
- Immune transcriptomic analysis on COVID-19 patients with varying clinical presentations identifies severity markers.Scientific reports · 2025Article
- Unlocking the Potential of RNA Sequencing in COVID-19: Toward Accurate Diagnosis and Personalized Medicine.Diagnostics (Basel, Switzerland) · 2025Review
- Whole blood transcriptome signature predicts severe forms of COVID-19: Results from the COVIDeF cohort study.Functional & integrative genomics · 2024Article
- Integrated analysis of RNA-seq datasets reveals novel targets and regulators of COVID-19 severity.Life science alliance · 2024Article
- Analysis of transcriptomics data from COVID-19 patients: a pilot research.Folia microbiologica · 2024Article
- Classification of COVID-19 Patients into Clinically Relevant Subsets by a Novel Machine Learning Pipeline Using Transcriptomic Features.International journal of molecular sciences · 2023Article
- Article
- Dysregulated early transcriptional signatures linked to mast cell and interferon responses are implicated in COVID-19 severity.Frontiers in immunology · 2023Article
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8 authors.
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Abstract
COVID-19 manifests a spectrum of respiratory symptoms, with the more severe often requiring hospitalization. To identify markers for disease progression, we analyzed longitudinal gene expression data from patients with confirmed SARS-CoV-2 infection admitted to the intensive care unit (ICU) for acute hypoxic respiratory failure (AHRF) as well as other ICU patients with or without AHRF and correlated results of gene set enrichment analysis with clinical features. The results were then compared with a second dataset of COVID-19 patients separated by disease stage and severity. Transcriptomic analysis revealed that enrichment of plasma cells (PCs) was characteristic of all COVID-19 patients whereas enrichment of interferon (IFN) and neutrophil gene signatures was specific to patients requiring hospitalization. Furthermore, gene expression results were used to divide AHRF COVID-19 patients into 2 groups with differences in immune profiles and clinical features indicative of severe disease. Thus, transcriptomic analysis reveals gene signatures unique to COVID-19 patients and provides opportunities for identification of the most at-risk individuals.
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