An Improved Understanding of the Aetiology and Diagnosis of Multisystem Inflammatory Syndrome in Children (MIS-C)

Introduction
The pathophysiology and biomarkers of multisystem inflammatory syndrome in children (MIS-C) remain inadequately defined. Typically, the syndrome develops 2-6 weeks post severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, is associated with fevers and hypotension and if left untreated can require intensive care admission. The clinical features of MIS-C overlap with other inflammatory and infectious syndromes, delaying time to appropriate treatment and often requiring unnecessary or prolonged use of broad-spectrum antibiotics.
Methods
We undertook a prospective serum peptide-based proteomic analysis and T cell receptor (TCR)-sequencing cohort study of 138 MIS-C patients and 36 febrile controls to identify a serum peptide-based proteomic signature and to improve our understanding of disease pathophysiology. Febrile controls were contemporaneously recruited patients with other active infectious or inflammatory diseases. Principal component analysis was used to examine the differences in peptide abundance between the groups. Lasso regression with 5-folds cross-validation was used to identify the top serum peptides associated with MIS-C and to evaluate the diagnostic performance of these peptide biomarkers. Raw T-cell receptor data of 50 patients with MIS-C versus 33 with SARS-CoV-2 and 11 healthy controls were aligned and categorised into TCR types. The interaction between our candidate peptide biomarkers, MHC allele, and the MIS-C T-Cell receptor was evaluated using deep learning models.
Results
We identified a set of 6 peptides in innate inflammatory and thrombotic pathways that distinguished acute cases of MIS-C (<14 day from onset) from other febrile controls with a sensitivity of 100% and specificity 94%. Treatment with immunomodulatory treatment and a period of convalescence was associated with a normalisation of the peptide-based proteomic signature, demonstrating that our signature is a consequence of MIS-C rather than reflecting an inherent proteomic predisposition to MIS-C. T-cell receptor (TCR) sequencing data demonstrated an increased frequency of TRBV 19 and 6-4 when compared to SARS-CoV-2 infected (p=0.024, 0.028) and healthy controls (<0.0001, <0.001). Finally, in silico structural modelling demonstrated that 4 peptides were predicted to strongly bind MIS-C specific pMHC-TCR complexes suggestive of antigen specific T-cell expansion.
Conclusion
We identified a highly sensitive and specific 6-peptide signature that can distinguish MIS-C from febrile controls. The peptides identified were predominantly associated with thrombotic and innate inflammatory pathways and were predicted in silico to bind MHC and differentially overexpressed T-Cell receptors in MIS-C, implicating these proteins in the pathophysiology of the disease.