AUTHOR=Castro-Castro Ana Cristina , Figueroa-Protti Lucia , Molina-Mora Jose Arturo , Rojas-Salas María Paula , Villafuerte-Mena Danae , Suarez-Sánchez María José , Sanabría-Castro Alfredo , Boza-Calvo Carolina , Calvo-Flores Leonardo , Solano-Vargas Mariela , Madrigal-Sánchez Juan José , Sibaja-Campos Mario , Silesky-Jiménez Juan Ignacio , Chaverri-Fernández José Miguel , Soto-Rodríguez Andrés , Echeverri-McCandless Ann , Rojas-Chaves Sebastián , Landaverde-Recinos Denis , Weigert Andreas , Mora Javier TITLE=Difference in mortality rates in hospitalized COVID-19 patients identified by cytokine profile clustering using a machine learning approach: An outcome prediction alternative JOURNAL=Frontiers in Medicine VOLUME=9 YEAR=2022 URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2022.987182 DOI=10.3389/fmed.2022.987182 ISSN=2296-858X ABSTRACT=

COVID-19 is a disease caused by the novel Coronavirus SARS-CoV-2 causing an acute respiratory disease that can eventually lead to severe acute respiratory syndrome (SARS). An exacerbated inflammatory response is characteristic of SARS-CoV-2 infection, which leads to a cytokine release syndrome also known as cytokine storm associated with the severity of the disease. Considering the importance of this event in the immunopathology of COVID-19, this study analyses cytokine levels of hospitalized patients to identify cytokine profiles associated with severity and mortality. Using a machine learning approach, 3 clusters of COVID-19 hospitalized patients were created based on their cytokine profile. Significant differences in the mortality rate were found among the clusters, associated to different CXCL10/IL-38 ratio. The balance of a CXCL10 induced inflammation with an appropriate immune regulation mediated by the anti-inflammatory cytokine IL-38 appears to generate the adequate immune context to overrule SARS-CoV-2 infection without creating a harmful inflammatory reaction. This study supports the concept that analyzing a single cytokine is insufficient to determine the outcome of a complex disease such as COVID-19, and different strategies incorporating bioinformatic analyses considering a broader immune profile represent a more robust alternative to predict the outcome of hospitalized patients with SARS-CoV-2 infection.