tetano
Editor, Senior Moderator
Front Immunol
. 2024 Sep 23:15:1464480.
doi: 10.3389/fimmu.2024.1464480. eCollection 2024. Distinct soluble immune checkpoint profiles characterize COVID-19 severity, mortality and SARS-CoV-2 variant infections
Tudorita Gabriela Paranga[SUP] 1 2 [/SUP], Mariana Pavel-Tanasa[SUP] 3 4 [/SUP], Daniela Constantinescu[SUP] 3 4 [/SUP], Elena Iftimi[SUP] 3 [/SUP], Claudia Elena Plesca[SUP] 1 2 [/SUP], Ionela-Larisa Miftode[SUP] 1 2 [/SUP], Petru Cianga[SUP] 3 4 [/SUP], Egidia Miftode[SUP] 1 2 [/SUP]
Affiliations
Introduction: Over the past four years, the COVID-19 pandemic has posed serious global health challenges. The severe form of disease and death resulted from the failure of immune regulatory mechanisms, closely highlighted by the dual proinflammatory cytokine and soluble immune checkpoint (sICP) storm. Identifying the individual factors impacting on disease severity, evolution and outcome, as well as any additional interconnections, have become of high scientific interest.
Methods: In this study, we evaluated a novel panel composed of ten sICPs for the predictive values of COVID-19 disease severity, mortality and Delta vs. Omicron variant infections in relation to hyperinflammatory biomarkers. The serum levels of sICPs from confirmed SARS-CoV-2 infected patients at hospital admission were determined by Luminex, and artificial neural network analysis was applied for defining the distinct patterns of molecular associations with each form of disease: mild, moderate, and severe.
Results: Notably, distinct sICP profiles characterized various stages of disease and Delta infections: while sCD40 played a central role in all defined diagrams, the differences emerged from the distribution levels of four molecules recently found and relatively less investigated (sCD30, s4-1BB, sTIM-1, sB7-H3), and their associations with various hematological and biochemical inflammatory biomarkers. The artificial neural network analysis revealed the prominent role of serum sTIM-1 and Galectin-9 levels at hospital admission in discriminating between survivors and non-survivors, as well as the role of specific anti-interleukin therapy (Tocilizumab, Anakinra) in improving survival for patients with initially high sTIM-1 levels. Furthermore, strong associations between sCD40 and Galectin-9 with suPAR defined the Omicron variant infections, while the positive match of sCD40 with sTREM-1 serum levels characterized the Delta-infected patients.
Conclusions: Of importance, this study provides a comprehensive analysis of circulatory immune factors governing the COVID-19 pathology, and identifies key roles of sCD40, sTIM-1, and Galectin-9 in predicting mortality.
Keywords: COVID-19; STIM-1; galectin-9; mortality; neural network; sCD40; soluble immune checkpoints.
. 2024 Sep 23:15:1464480.
doi: 10.3389/fimmu.2024.1464480. eCollection 2024. Distinct soluble immune checkpoint profiles characterize COVID-19 severity, mortality and SARS-CoV-2 variant infections
Tudorita Gabriela Paranga[SUP] 1 2 [/SUP], Mariana Pavel-Tanasa[SUP] 3 4 [/SUP], Daniela Constantinescu[SUP] 3 4 [/SUP], Elena Iftimi[SUP] 3 [/SUP], Claudia Elena Plesca[SUP] 1 2 [/SUP], Ionela-Larisa Miftode[SUP] 1 2 [/SUP], Petru Cianga[SUP] 3 4 [/SUP], Egidia Miftode[SUP] 1 2 [/SUP]
Affiliations
- PMID: 39376569
- PMCID: PMC11456479
- DOI: 10.3389/fimmu.2024.1464480
Introduction: Over the past four years, the COVID-19 pandemic has posed serious global health challenges. The severe form of disease and death resulted from the failure of immune regulatory mechanisms, closely highlighted by the dual proinflammatory cytokine and soluble immune checkpoint (sICP) storm. Identifying the individual factors impacting on disease severity, evolution and outcome, as well as any additional interconnections, have become of high scientific interest.
Methods: In this study, we evaluated a novel panel composed of ten sICPs for the predictive values of COVID-19 disease severity, mortality and Delta vs. Omicron variant infections in relation to hyperinflammatory biomarkers. The serum levels of sICPs from confirmed SARS-CoV-2 infected patients at hospital admission were determined by Luminex, and artificial neural network analysis was applied for defining the distinct patterns of molecular associations with each form of disease: mild, moderate, and severe.
Results: Notably, distinct sICP profiles characterized various stages of disease and Delta infections: while sCD40 played a central role in all defined diagrams, the differences emerged from the distribution levels of four molecules recently found and relatively less investigated (sCD30, s4-1BB, sTIM-1, sB7-H3), and their associations with various hematological and biochemical inflammatory biomarkers. The artificial neural network analysis revealed the prominent role of serum sTIM-1 and Galectin-9 levels at hospital admission in discriminating between survivors and non-survivors, as well as the role of specific anti-interleukin therapy (Tocilizumab, Anakinra) in improving survival for patients with initially high sTIM-1 levels. Furthermore, strong associations between sCD40 and Galectin-9 with suPAR defined the Omicron variant infections, while the positive match of sCD40 with sTREM-1 serum levels characterized the Delta-infected patients.
Conclusions: Of importance, this study provides a comprehensive analysis of circulatory immune factors governing the COVID-19 pathology, and identifies key roles of sCD40, sTIM-1, and Galectin-9 in predicting mortality.
Keywords: COVID-19; STIM-1; galectin-9; mortality; neural network; sCD40; soluble immune checkpoints.