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Early inflammatory profiles predict maximal disease severity in COVID-19: An unsupervised cluster analysis.
Kenny, Grace; Saini, Gurvin; Gaillard, Colette Marie; Negi, Riya; Alalwan, Dana; Garcia Leon, Alejandro; McCann, Kathleen; Tinago, Willard; Kelly, Christine; Cotter, Aoife G; de Barra, Eoghan; Horgan, Mary; Yousif, Obada; Gautier, Virginie; Landay, Alan; McAuley, Danny; Feeney, Eoin R; O'Kane, Cecilia; Mallon, Patrick Wg.
Afiliação
  • Kenny G; Centre for Experimental Pathogen Host Research, University College Dublin, Dublin, Ireland.
  • Saini G; Department of Infectious Diseases, St Vincent's University Hospital, Dublin, Ireland.
  • Gaillard CM; Centre for Experimental Pathogen Host Research, University College Dublin, Dublin, Ireland.
  • Negi R; Centre for Experimental Pathogen Host Research, University College Dublin, Dublin, Ireland.
  • Alalwan D; Centre for Experimental Pathogen Host Research, University College Dublin, Dublin, Ireland.
  • Garcia Leon A; Centre for Experimental Pathogen Host Research, University College Dublin, Dublin, Ireland.
  • McCann K; Centre for Experimental Pathogen Host Research, University College Dublin, Dublin, Ireland.
  • Tinago W; Department of Infectious Diseases, St Vincent's University Hospital, Dublin, Ireland.
  • Kelly C; Centre for Experimental Pathogen Host Research, University College Dublin, Dublin, Ireland.
  • Cotter AG; Centre for Experimental Pathogen Host Research, University College Dublin, Dublin, Ireland.
  • de Barra E; Department of Infectious Diseases, Mater Misericordiae University Hospital, Dublin, Ireland.
  • Horgan M; Centre for Experimental Pathogen Host Research, University College Dublin, Dublin, Ireland.
  • Yousif O; Department of Infectious Diseases, Mater Misericordiae University Hospital, Dublin, Ireland.
  • Gautier V; Department of International Health and Tropical Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland.
  • Landay A; Department of Infectious Diseases, Cork University Hospital, Wilton, Cork, Ireland.
  • McAuley D; Department of Endocrinology, Wexford General Hospital, Wexford, Ireland.
  • Feeney ER; Centre for Experimental Pathogen Host Research, University College Dublin, Dublin, Ireland.
  • O'Kane C; Department of Internal Medicine, Rush University, Chicago, IL, USA.
  • Mallon PW; Queen's University Belfast, Belfast, United Kingdom.
Heliyon ; 10(15): e34694, 2024 Aug 15.
Article em En | MEDLINE | ID: mdl-39144942
ABSTRACT

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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article