TY - JOUR
T1 - Early inflammatory profiles predict maximal disease severity in COVID-19
T2 - An unsupervised cluster analysis
AU - Kenny, Grace
AU - Saini, Gurvin
AU - Gaillard, Colette Marie
AU - Negi, Riya
AU - Alalwan, Dana
AU - Garcia Leon, Alejandro
AU - McCann, Kathleen
AU - Tinago, Willard
AU - Kelly, Christine
AU - Cotter, Aoife G.
AU - de Barra, Eoghan
AU - Horgan, Mary
AU - Yousif, Obada
AU - Gautier, Virginie
AU - Landay, Alan
AU - McAuley, Danny
AU - Feeney, Eoin R.
AU - O'Kane, Cecilia
AU - Mallon, Patrick WG
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2024/8/15
Y1 - 2024/8/15
N2 - 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.
AB - 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.
KW - Biomarkers
KW - Immune phenotypes
KW - Principal component analysis
KW - Severe acute coronavirus 2
UR - http://www.scopus.com/inward/record.url?scp=85199283000&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85199283000&partnerID=8YFLogxK
U2 - 10.1016/j.heliyon.2024.e34694
DO - 10.1016/j.heliyon.2024.e34694
M3 - Article
C2 - 39144942
AN - SCOPUS:85199283000
SN - 2405-8440
VL - 10
JO - Heliyon
JF - Heliyon
IS - 15
M1 - e34694
ER -