tetano
Editor, Senior Moderator
Front Immunol
. 2025 Jan 8:15:1452638.
doi: 10.3389/fimmu.2024.1452638. eCollection 2024. Investigating the relationship between the immune response and the severity of COVID-19: a large-cohort retrospective study
Riccardo Giuseppe Margiotta[SUP] #[/SUP][SUP] 1 [/SUP], Emanuela Sozio[SUP] #[/SUP][SUP] 2 [/SUP], Fabio Del Ben[SUP] 3 4 [/SUP], Antonio Paolo Beltrami[SUP] 3 4 [/SUP], Daniela Cesselli[SUP] 3 4 [/SUP], Marco Comar[SUP] 3 [/SUP], Alessandra Devito[SUP] 3 [/SUP], Martina Fabris[SUP] 3 4 [/SUP], Francesco Curcio[SUP] 3 4 [/SUP], Carlo Tascini[SUP] 2 3 [/SUP], Guido Sanguinetti[SUP] 1 [/SUP]
Affiliations
The COVID-19 pandemic has left an indelible mark globally, presenting numerous challenges to public health. This crisis, while disruptive and impactful, has provided a unique opportunity to gather precious clinical data extensively. In this observational, case-control study, we utilized data collected at the Azienda Sanitaria Universitaria Friuli Centrale, Italy, to comprehensively characterize the immuno-inflammatory features in COVID-19 patients. Specifically, we employed multicolor flow cytometry, cytokine assays, and inflammatory biomarkers to elucidate the interplay between the infectious agent and the host's immune status. We characterized immuno-inflammatory profiles within the first 72 hours of hospital admission, stratified by age, disease severity, and time elapsed since symptom onset. Our findings indicate that patients admitted to the hospital shortly after symptom onset exhibit a distinct pattern compared to those who arrive later, characterized by a more active immune response and heightened cytokine activity, but lower markers of tissue damage. We used univariate and multivariate logistic regression models to identify informative markers for outcome severity. Predictors incorporating the immuno-inflammatory features significantly outperformed standard baselines, identifying up to 59% of patients with positive outcomes while maintaining a false omission rate as low as 4%. Overall, our study sheds light on the immuno-inflammatory aspects observed in COVID-19 patients prior to vaccination, providing insights for guiding the clinical management of first-time infections by a novel virus.
Keywords: COVID-19; cytokines; flow cytometry; immune system; immunology; inflammation; predictive modeling.
. 2025 Jan 8:15:1452638.
doi: 10.3389/fimmu.2024.1452638. eCollection 2024. Investigating the relationship between the immune response and the severity of COVID-19: a large-cohort retrospective study
Riccardo Giuseppe Margiotta[SUP] #[/SUP][SUP] 1 [/SUP], Emanuela Sozio[SUP] #[/SUP][SUP] 2 [/SUP], Fabio Del Ben[SUP] 3 4 [/SUP], Antonio Paolo Beltrami[SUP] 3 4 [/SUP], Daniela Cesselli[SUP] 3 4 [/SUP], Marco Comar[SUP] 3 [/SUP], Alessandra Devito[SUP] 3 [/SUP], Martina Fabris[SUP] 3 4 [/SUP], Francesco Curcio[SUP] 3 4 [/SUP], Carlo Tascini[SUP] 2 3 [/SUP], Guido Sanguinetti[SUP] 1 [/SUP]
Affiliations
- PMID: 39845955
- PMCID: PMC11750771
- DOI: 10.3389/fimmu.2024.1452638
The COVID-19 pandemic has left an indelible mark globally, presenting numerous challenges to public health. This crisis, while disruptive and impactful, has provided a unique opportunity to gather precious clinical data extensively. In this observational, case-control study, we utilized data collected at the Azienda Sanitaria Universitaria Friuli Centrale, Italy, to comprehensively characterize the immuno-inflammatory features in COVID-19 patients. Specifically, we employed multicolor flow cytometry, cytokine assays, and inflammatory biomarkers to elucidate the interplay between the infectious agent and the host's immune status. We characterized immuno-inflammatory profiles within the first 72 hours of hospital admission, stratified by age, disease severity, and time elapsed since symptom onset. Our findings indicate that patients admitted to the hospital shortly after symptom onset exhibit a distinct pattern compared to those who arrive later, characterized by a more active immune response and heightened cytokine activity, but lower markers of tissue damage. We used univariate and multivariate logistic regression models to identify informative markers for outcome severity. Predictors incorporating the immuno-inflammatory features significantly outperformed standard baselines, identifying up to 59% of patients with positive outcomes while maintaining a false omission rate as low as 4%. Overall, our study sheds light on the immuno-inflammatory aspects observed in COVID-19 patients prior to vaccination, providing insights for guiding the clinical management of first-time infections by a novel virus.
Keywords: COVID-19; cytokines; flow cytometry; immune system; immunology; inflammation; predictive modeling.