The autoimmune signature of hyperinflammatory multisystem inflammatory syndrome in children
Rebecca A. Porritt, … , Mascha Binder, Moshe Arditi
Rebecca A. Porritt, … , Mascha Binder, Moshe Arditi
Published August 26, 2021
Citation Information: J Clin Invest. 2021;131(20):e151520. https://doi.org/10.1172/JCI151520.
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Research Article Inflammation

The autoimmune signature of hyperinflammatory multisystem inflammatory syndrome in children

Abstract

Multisystem inflammatory syndrome in children (MIS-C) manifests as a severe and uncontrolled inflammatory response with multiorgan involvement, occurring weeks after SARS-CoV-2 infection. Here, we utilized proteomics, RNA sequencing, autoantibody arrays, and B cell receptor (BCR) repertoire analysis to characterize MIS-C immunopathogenesis and identify factors contributing to severe manifestations and intensive care unit admission. Inflammation markers, humoral immune responses, neutrophil activation, and complement and coagulation pathways were highly enriched in MIS-C patient serum, with a more hyperinflammatory profile in severe than in mild MIS-C cases. We identified a strong autoimmune signature in MIS-C, with autoantibodies targeted to both ubiquitously expressed and tissue-specific antigens, suggesting autoantigen release and excessive antigenic drive may result from systemic tissue damage. We further identified a cluster of patients with enhanced neutrophil responses as well as high anti-Spike IgG and autoantibody titers. BCR sequencing of these patients identified a strong imprint of antigenic drive with substantial BCR sequence connectivity and usage of autoimmunity-associated immunoglobulin heavy chain variable region (IGHV) genes. This cluster was linked to a TRBV11-2 expanded T cell receptor (TCR) repertoire, consistent with previous studies indicating a superantigen-driven pathogenic process. Overall, we identify a combination of pathogenic pathways that culminate in MIS-C and may inform treatment.

Authors

Rebecca A. Porritt, Aleksandra Binek, Lisa Paschold, Magali Noval Rivas, Angela McArdle, Lael M. Yonker, Galit Alter, Harsha K. Chandnani, Merrick Lopez, Alessio Fasano, Jennifer E. Van Eyk, Mascha Binder, Moshe Arditi

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Figure 2

Characterization of severe MIS-C.

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Characterization of severe MIS-C. Protein expression was compared betwee...
Protein expression was compared between severe MIS-C (n = 20) and healthy controls (n = 20). Proteins were considered significantly changed when FDR was less than 0.05, as determined by mapDIA statistical software for protein differential expression using MS/MS fragment-level quantitative data. (A) Top proteins enhanced in severe MIS-C, ranked by fold change. (B) Top proteins reduced in severe MIS-C, ranked by fold change. (C) ClueGO Ontology analysis via PINE visualized a network of pathways and functional annotation terms enriched in a set of proteins significantly increased in severe MIS-C population when compared with healthy controls. (D) Selected pathways and functional annotation terms from PINE analysis of proteins increased in severe MIS-C when compared with healthy controls. (E) Network plots visualized via PINE analysis of proteins reduced in severe MIS-C group when compared with healthy controls. (F) Selected pathways and functional annotation terms from protein functional enrichment analysis of proteins reduced in severe MIS-C group when compared with healthy controls.