ArticleFunctional & integrative genomics2024
Whole blood transcriptome signature predicts severe forms of COVID-19: Results from the COVIDeF cohort study.
Article in Functional & integrative genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Article
- ETS Homologous Factor (EHF) and Gamma Linolenic Acid (GLA): novel strategies for early diagnosis and treatment of endometriosis.Functional & integrative genomics · 2026Article
- Immune monitoring, immune phenotyping, and precision intervention in severe pneumonia: current evidence and translational challenges.Frontiers in immunology · 2026Review
- Minimalistic transcriptomic signatures permit accurate early prediction of COVID-19 mortality.JCI insight · 2025Article
- Immune transcriptomic differences in paediatric patients with SARS-CoV-2 compared to other lower respiratory tract infections.bioRxiv : the preprint server for biology · 2025Article
- Integrated multi-sample transcriptomic analysis of COVID-19 patients against controls using a bioinformatics pipeline.Scientific reports · 2025Article
- mirrorCheck: an R package facilitating informed use of DESeq2's lfcShrink() function for differential gene expression analysis of clinical samples.Bioinformatics advances · 2025Article
- SARS-CoV-2 variants induce increased inflammatory gene expression but reduced interferon responses and heme synthesis as compared with wild type strains.Scientific reports · 2024Article
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Authors and funding
16 authors.
Funding
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Abstract
COVID-19 is associated with heterogeneous outcome. Early identification of a severe progression of the disease is essential to properly manage the patients and improve their outcome. Biomarkers reflecting an increased inflammatory response, as well as individual features including advanced age, male gender, and pre-existing comorbidities, are risk factors of severe COVID-19. Yet, these features show limited accuracy for outcome prediction. The aim was to evaluate the prognostic value of whole blood transcriptome at an early stage of the disease. Blood transcriptome of patients with mild pneumonia was profiled. Patients with subsequent severe COVID-19 were compared to those with favourable outcome, and a molecular predictor based on gene expression was built. Unsupervised classification discriminated patients who would later develop a COVID-19-related severe pneumonia. The corresponding gene expression signature reflected the immune response to the viral infection dominated by a prominent type I interferon, with IFI27 among the most over-expressed genes. A 48-genes transcriptome signature predicting the risk of severe COVID-19 was built on a training cohort, then validated on an external independent cohort, showing an accuracy of 81% for predicting severe outcome. These results identify an early transcriptome signature of severe COVID-19 pneumonia, with a possible relevance to improve COVID-19 patient management.
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