tetano
Editor, Senior Moderator
Heliyon
. 2024 Jul 23;10(15):e34694.
doi: 10.1016/j.heliyon.2024.e34694. eCollection 2024 Aug 15. Early inflammatory profiles predict maximal disease severity in COVID-19: An unsupervised cluster analysis
Grace Kenny[SUP] 1 2 [/SUP], Gurvin Saini[SUP] 1 [/SUP], Colette Marie Gaillard[SUP] 1 [/SUP], Riya Negi[SUP] 1 [/SUP], Dana Alalwan[SUP] 1 [/SUP], Alejandro Garcia Leon[SUP] 1 [/SUP], Kathleen McCann[SUP] 2 [/SUP], Willard Tinago[SUP] 1 [/SUP], Christine Kelly[SUP] 1 3 [/SUP], Aoife G Cotter[SUP] 1 3 [/SUP], Eoghan de Barra[SUP] 4 [/SUP], Mary Horgan[SUP] 5 [/SUP], Obada Yousif[SUP] 6 [/SUP], Virginie Gautier[SUP] 1 [/SUP], Alan Landay[SUP] 7 [/SUP], Danny McAuley[SUP] 8 [/SUP], Eoin R Feeney[SUP] 1 2 [/SUP], Cecilia O'Kane[SUP] 8 [/SUP], Patrick Wg Mallon[SUP] 1 2 [/SUP]
Affiliations
Background: The inflammatory changes that underlie the heterogeneous presentations of COVID-19 remain incompletely understood. In this study we aimed to identify inflammatory profiles that precede the development of severe COVID-19, that could serve as targets for optimised delivery of immunomodulatory therapies and provide insights for the development of new therapies.
Methods: We included individuals sampled <10 days from COVID-19 symptom onset, recruited from both inpatient and outpatient settings. We measured 61 biomarkers in plasma, including markers of innate immune and T cell activation, coagulation, tissue repair and lung injury. We used principal component analysis and hierarchical clustering to derive biomarker clusters, and ordinal logistic regression to explore associations between cluster membership and maximal disease severity, adjusting for known risk factors for severe COVID-19.
Results: In 312 individuals, median (IQR) 7 (4-9) days from symptom onset, we found four clusters. Cluster 1 was characterised by low overall inflammation, cluster 2 was characterised by higher levels of growth factors and markers of endothelial activation (EGF, VEGF, PDGF, TGFα, PAI-1 and p-selectin). Cluster 3 and 4 both had higher overall inflammation. Cluster 4 had the highest levels of most markers including markers of innate immune activation (IL6, procalcitonin, CRP, TNFα), and coagulation (D-dimer, TPO), in contrast cluster 3 had the highest levels of alveolar epithelial injury markers (RAGE, ST2), but relative downregulation of growth factors and endothelial activation markers, suggesting a dysfunctional inflammatory pattern. In unadjusted and adjusted analysis, compared to cluster 1, cluster 3 had the highest odds of progressing to more severe disease (unadjusted OR (95%CI) 9.02 (4.53-17.96), adjusted OR (95%CI) 6.02 (2.70-13.39)).
Conclusion: Early inflammatory profiles predicted subsequent maximal disease severity independent of risk factors for severe COVID-19. A cluster with downregulation of growth factors and endothelial activation markers, and early evidence of alveolar epithelial injury, had the highest risk of severe COVID-19.
Keywords: Biomarkers; Immune phenotypes; Principal component analysis; Severe acute coronavirus 2.
. 2024 Jul 23;10(15):e34694.
doi: 10.1016/j.heliyon.2024.e34694. eCollection 2024 Aug 15. Early inflammatory profiles predict maximal disease severity in COVID-19: An unsupervised cluster analysis
Grace Kenny[SUP] 1 2 [/SUP], Gurvin Saini[SUP] 1 [/SUP], Colette Marie Gaillard[SUP] 1 [/SUP], Riya Negi[SUP] 1 [/SUP], Dana Alalwan[SUP] 1 [/SUP], Alejandro Garcia Leon[SUP] 1 [/SUP], Kathleen McCann[SUP] 2 [/SUP], Willard Tinago[SUP] 1 [/SUP], Christine Kelly[SUP] 1 3 [/SUP], Aoife G Cotter[SUP] 1 3 [/SUP], Eoghan de Barra[SUP] 4 [/SUP], Mary Horgan[SUP] 5 [/SUP], Obada Yousif[SUP] 6 [/SUP], Virginie Gautier[SUP] 1 [/SUP], Alan Landay[SUP] 7 [/SUP], Danny McAuley[SUP] 8 [/SUP], Eoin R Feeney[SUP] 1 2 [/SUP], Cecilia O'Kane[SUP] 8 [/SUP], Patrick Wg Mallon[SUP] 1 2 [/SUP]
Affiliations
- PMID: 39144942
- PMCID: PMC11320140
- DOI: 10.1016/j.heliyon.2024.e34694
Background: The inflammatory changes that underlie the heterogeneous presentations of COVID-19 remain incompletely understood. In this study we aimed to identify inflammatory profiles that precede the development of severe COVID-19, that could serve as targets for optimised delivery of immunomodulatory therapies and provide insights for the development of new therapies.
Methods: We included individuals sampled <10 days from COVID-19 symptom onset, recruited from both inpatient and outpatient settings. We measured 61 biomarkers in plasma, including markers of innate immune and T cell activation, coagulation, tissue repair and lung injury. We used principal component analysis and hierarchical clustering to derive biomarker clusters, and ordinal logistic regression to explore associations between cluster membership and maximal disease severity, adjusting for known risk factors for severe COVID-19.
Results: In 312 individuals, median (IQR) 7 (4-9) days from symptom onset, we found four clusters. Cluster 1 was characterised by low overall inflammation, cluster 2 was characterised by higher levels of growth factors and markers of endothelial activation (EGF, VEGF, PDGF, TGFα, PAI-1 and p-selectin). Cluster 3 and 4 both had higher overall inflammation. Cluster 4 had the highest levels of most markers including markers of innate immune activation (IL6, procalcitonin, CRP, TNFα), and coagulation (D-dimer, TPO), in contrast cluster 3 had the highest levels of alveolar epithelial injury markers (RAGE, ST2), but relative downregulation of growth factors and endothelial activation markers, suggesting a dysfunctional inflammatory pattern. In unadjusted and adjusted analysis, compared to cluster 1, cluster 3 had the highest odds of progressing to more severe disease (unadjusted OR (95%CI) 9.02 (4.53-17.96), adjusted OR (95%CI) 6.02 (2.70-13.39)).
Conclusion: Early inflammatory profiles predicted subsequent maximal disease severity independent of risk factors for severe COVID-19. A cluster with downregulation of growth factors and endothelial activation markers, and early evidence of alveolar epithelial injury, had the highest risk of severe COVID-19.
Keywords: Biomarkers; Immune phenotypes; Principal component analysis; Severe acute coronavirus 2.