Early Inflammatory Profiles Predict Maximal Disease Severity in Covid-19
Topics in Antiviral Medicine
; 31(2):109, 2023.
Article
in English
| EMBASE | ID: covidwho-2315997
ABSTRACT
Background:
Better understanding of host inflammatory changes that precede development of severe COVID-19 could improve delivery of available antiviral and immunomodulatory therapies, and provide insights for the development of new therapies. Method(s) In plasma from individuals with COVID-19, sampled <=10 days from symptom onset from the All-Ireland Infectious Diseases Cohort study, we measured 61 biomarkers, including markers of innate immune and T cell activation, coagulation, tissue repair, lung injury, and immune regulation. We used principal component analysis (PCA) and k-means clustering to derive biomarker clusters, and univariate and multivariate ordinal logistic regression to explore association between cluster membership and maximal disease severity, adjusting for risk factors for severe COVID-19, including age, sex, ethnicity, BMI, hypertension and diabetes. Result(s) From March 2020-April 2021, we included 312 individuals, (median (IQR) age 62 (48-77) years, 7 (4-9) days from symptom onset, 54% male) in the analysis. PCA and clustering derived 4 clusters. Compared to cluster 1, clusters 2-4 were significantly older and of higher BMI but there were no significant differences in sex or ethnicity. Cluster 1 had low levels of inflammation, cluster 2 had higher levels of markers of tissue repair and endothelial activation (EGF, VEGF, PDGF, TGFalpha, serpin E1 and p-selectin). Cluster 3 and 4 were both characterised by higher overall inflammation, but compared to cluster 4, cluster 3 had downregulation of growth factors, markers of endothelial activation, and immune regulation (IL10, PDL1), but higher alveolar epithelial injury markers (RAGE, ST2). In univariate analysis, compared to cluster 1, cluster 3 had the highest odds of severe disease (OR (95% CI) 9.02 (4.62-18.31), followed by cluster 4 5.59 (2.75-11.72) then cluster 2 4.5 (2.38-8.81), all p < 0.05). Cluster 3 remained most strongly associated with severe disease in fully adjusted analyses;cluster 3 OR(95% CI) 5.99 (2.69-13.35), cluster 2 3.14 (1.54-6.42), cluster 4 3.13 (1.36-7.19), all p< 0.05). Conclusion(s) Distinct early inflammatory profiles predicted maximal disease severity independent of known risk factors for severe COVID-19. A cluster characterised by downregulation of growth factor and endothelial markers and early evidence of alveolar injury was associated with highest risk of developing severe COVID19. Whether this reflects a dysregulated inflammatory response that could improve targeted treatment requires further study. Heatmap of biomarker derived clusters and forest plot of association between clusters and disease severity. A Heatmap demonstrating differences in biomarkers between clusters B Forest plot demonstrating odds ratio of specific clusters for progressing to moderate or severe disease (reference Cluster 1), calculated using ordinal logistic regression. Odds ratio (95% CI) presented as unadjusted and fully adjusted (for age, sex, ethnicity, BMI, hypertension, diabetes, immunosuppression, smoking and baseline anticoagulant use). Maximal disease severity graded per the WHO severity scale.
adult; body mass; cohort analysis; communicable disease; conference abstract; controlled study; coronavirus disease 2019; diabetes mellitus; down regulation; endothelium; epithelium lesion; ethnicity; female; forest; human; human tissue; hypertension; immunoregulation; immunostimulation; immunosuppressive treatment; inflammation; Ireland; k means clustering; lung alveolus; lung injury; major clinical study; male; middle aged; principal component analysis; risk factor; smoking; T lymphocyte; T lymphocyte activation; tissue repair; univariate analysis; anticoagulant agent; biological marker; endogenous compound; epidermal growth factor; growth factor; interleukin 10; PADGEM protein; plasminogen activator inhibitor 1; platelet derived growth factor; transforming growth factor alpha; vasculotropin
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Collection:
Databases of international organizations
Database:
EMBASE
Type of study:
Prognostic study
Language:
English
Journal:
Topics in Antiviral Medicine
Year:
2023
Document Type:
Article
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