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.
View: Text | PDF
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

×

Figure 4

RNA-seq analysis of MIS-C.

Options: View larger image (or click on image) Download as PowerPoint
RNA-seq analysis of MIS-C. RNA-seq was performed using whole-blood RNA i...
RNA-seq was performed using whole-blood RNA isolated from febrile controls (n = 13), mild MIS-C (n = 4), and severe MIS-C (n = 8) patients. (A) Experimental design of RNA-seq analysis and patient groups. (B) PCA of RNA-seq profiles. (C) Genes up- or downregulated in cluster 1 vs. cluster 2 MIS-C patients (FDR < 0.05). (D) Selected pathways and functional annotation terms from gene functional enrichment analysis performed with PINE software using significantly up- and downregulated (FDR < 0.01, log2[FC] > 1.5 and < –1.25) genes in cluster 1 vs. cluster 2 MIS-C patients. (E) Cell deconvolution analysis of RNA-seq data by CIBERSORT. (F) Top proteins increased in cluster 1 vs. cluster 2, based on proteomics data. (G) Enriched pathways and functional annotation terms based on protein expression changes significantly (FDR < 0.05) upregulated in cluster 1 with respect to cluster 2. (H) TRBV11-2 expansion of RNA-seq samples (17). (I) IgG titers against Spike protein receptor binding domain (RBD). Data are presented as mean ± SEM. Statistical significance was determined by Mann-Whitney test (H and I).