ArticleScientific reports2024
Disease progression associated cytokines in COVID-19 patients with deteriorating and recovering health conditions.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed.
- Vascular Immune Crosstalk in COVID-19: RAAS Biomarker Signature Linking Angiotensin II to Respiratory Compromise and Soluble ACE2 to IL-13 and FGF, Revealing Therapeutic Targets.International journal of molecular sciences · 2026Article
- Serum cytokine profiling reveals CXCL10 (IP-10) as a major predictor of severe COVID-19 outcomes in hospitalized patients during the first pandemic wave in Italy.Frontiers in immunology · 2026Article
- Transforming cytokine diagnostics: AI, multiplexing, and point-of-care biosensing technologies.Mikrochimica acta · 2025Review
- Multiplex Targeted Proteomic Analysis of Cytokine Ratios for ICU Mortality in Severe COVID-19.Proteomes · 2025Article
- NK Cells: A Powerful Squad Versus SARS-CoV-2.International journal of molecular sciences · 2025Review
- Early Immunological and Inflammation Proteomic Changes in Elderly COVID-19 Patients Predict Severe Disease Progression.Biomedicines · 2025Article
- Cytokines dynamics and biological sex differences in SARS-CoV-2 infected people in Cameroon.Clinical and experimental immunology · 2025Article
- Advances in understanding the role of pentraxin-3 in lung infections.Frontiers in immunology · 2025Review
- Article
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Authors and funding
6 authors.
Funding
Abstract
Understanding the immune response to COVID-19 is challenging due to its high variability among individuals. To identify differentially expressed cytokines between the deteriorating and recovering phases, we analyzed the Electronic Health Records (EHR) and cytokine profile data in a COVID-19 cohort of 444 infected patients and 145 non-infected healthy individuals. We categorized each patient's progression into Deterioration Phase (DP) and Recovery Phase (RP) using longitudinal neutrophil, lymphocyte and lactate dehydrogenase levels. A random forest model was built using healthy and severe patients to compute the contribution of each cytokine toward disease progression using Shapley Additive Explanations (SHAP). SHAP values were used for supervised clustering to identify DP and RP-related samples and their associated cytokines. The identified clusters effectively discriminated DP and RP samples, suggesting that the cytokine profiles differed between deteriorating and recovering health conditions. Especially, CXCL10, GDF15, PTX3, and TNFSF10 were differentially expressed between the DP and RP samples, which are involved in the JAK-STAT, NF-
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