Abstract

Background: Multisystemic inflammatory syndrome in children (MIS-C) is a life-threatening disease that occurs 2-5 weeks after severe acute respiratory syndrome coronavirus 2 exposure and is characterized by severe multisystemic inflammation. Early recognition of MIS-C is key to prognosis; therefore, establishing clinical and laboratory biomarkers that predict complications is urgently needed. Objective: We characterized the immune response and clinical features of patients with acute MIS-C and determined biomarkers of disease in a cohort of 42 Latin American patients. Methods: Immune characterization was performed using flow cytometry from peripheral mononuclear cells and severe acute respiratory syndrome coronavirus 2-specific humoral and cellular response was performed using flow cytometry, enzyme-linked immunospot, enzyme-linked immunosorbent assay, and neutralizing antibody assays. Results: MIS-C is characterized by robust T-cell activation and cytokine storm. We uncovered that while C-X-C motif chemokine ligand (CXCL) 9, IL-10, CXCL8, CXCL10, IL-6, and IL-18 are significantly elevated in patients with shock, while CCL5 was increased in milder disease. Monocyte dysregulation was specifically associated with KD-like MIS-C. Interestingly, MIS-C patients show a natural killer cell degranulation defect that is persistent after 6 months of disease presentation, suggesting it could underlie disease susceptibility. Most MIS-C had gastrointestinal involvement, and higher levels of neopterin were identified in their stools, potentially representing a biomarker of intestinal inflammation in MIS-C. Severe acute respiratory syndrome coronavirus 2-specific cellular response and neutralizing antibodies were identifiable in convalescent MIS-C patients, suggesting sustained immunity. Conclusion: Clinical characterization and comprehensive immunophenotyping of Chilean MIS-C cohort provide valuable insights in understanding immune dysregulation in MIS-C and identify relevant biomarkers of disease that could be used to predict severity and organ involvement.