The Notch1/CD22 signaling axis disrupts Treg function in SARS-CoV-2–associated multisystem inflammatory syndrome in children
Mehdi Benamar, … , Lauren A. Henderson, Talal A. Chatila
Mehdi Benamar, … , Lauren A. Henderson, Talal A. Chatila
Published October 25, 2022
Citation Information: J Clin Invest. 2023;133(1):e163235. https://doi.org/10.1172/JCI163235.
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Research Article COVID-19 Immunology

The Notch1/CD22 signaling axis disrupts Treg function in SARS-CoV-2–associated multisystem inflammatory syndrome in children

Abstract

Multisystem inflammatory syndrome in children (MIS-C) evolves in some pediatric patients following acute infection with SARS-CoV-2 by hitherto unknown mechanisms. Whereas acute-COVID-19 severity and outcomes were previously correlated with Notch4 expression on Tregs, here, we show that Tregs in MIS-C were destabilized through a Notch1-dependent mechanism. Genetic analysis revealed that patients with MIS-C had enrichment of rare deleterious variants affecting inflammation and autoimmunity pathways, including dominant-negative mutations in the Notch1 regulators NUMB and NUMBL leading to Notch1 upregulation. Notch1 signaling in Tregs induced CD22, leading to their destabilization in a mTORC1-dependent manner and to the promotion of systemic inflammation. These results identify a Notch1/CD22 signaling axis that disrupts Treg function in MIS-C and point to distinct immune checkpoints controlled by individual Treg Notch receptors that shape the inflammatory outcome in SARS-CoV-2 infection.

Authors

Mehdi Benamar, Qian Chen, Janet Chou, Amélie M. Julé, Rafik Boudra, Paola Contini, Elena Crestani, Peggy S. Lai, Muyun Wang, Jason Fong, Shira Rockwitz, Pui Lee, Tsz Man Fion Chan, Ekin Zeynep Altun, Eda Kepenekli, Elif Karakoc-Aydiner, Ahmet Ozen, Perran Boran, Fatih Aygun, Pinar Onal, Ayse Ayzit Kilinc Sakalli, Haluk Cokugras, Metin Yusuf Gelmez, Fatma Betul Oktelik, Esin Aktas Cetin, Yuelin Zhong, Maria Lucia Taylor, Katherine Irby, Natasha B. Halasa, Elizabeth H. Mack, Overcoming COVID-19 Investigators, Sara Signa, Ignazia Prigione, Marco Gattorno, Nicola Cotugno, Donato Amodio, Raif S. Geha, Mary Beth Son, Jane Newburger, Pankaj B. Agrawal, Stefano Volpi, Paolo Palma, Ayca Kiykim, Adrienne G. Randolph, Gunnur Deniz, Safa Baris, Raffaele De Palma, Klaus Schmitz-Abe, Louis-Marie Charbonnier, Lauren A. Henderson, Talal A. Chatila

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Figure 1

Increased CD4+ T cell activation and Treg destabilization in MIS-C.

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Increased CD4+ T cell activation and Treg destabilization in MIS-C. Circ...
Circulating CD4+ T cells from control and pre- and post-treatment MIS-C individuals were studied with 10x Genomics. (A) Uniform manifold approximation and projection (UMAP) of normalized and harmonized data set, split by disease group and color coded by cell type. Cell identities were defined by mapping the data to a reference human PBMC data set with Azimuth. (B) Frequencies (percentage) of each cell type among total CD4+ T cells for each patient, as determined with scRNA-Seq. (C and D) Data on log2 fold change (LFC) in gene expression derived from independent pseudobulk DEA of pretreatment MIS-C patients versus healthy controls (x axis) and of pretreatment MIS-C versus post-treatment MIS-C patients (y axis) in Tregs (C) and activated Tconv cells (D). For each cell type, genes differentially expressed (P < 0.2) in pretreatment MIS-C versus both control and post-treatment individuals are highlighted (blue: LFC <0, red: LFC >0). (E and F) Heatmaps of all genes found to be significantly (P < 0.05) differentially expressed in Tregs (E) and Tconv cells (F) according to pseudobulk DEA comparing results for pretreatment MIS-C versus control and pretreatment MIC-C versus post-treatment individuals. (G and H) LFC distributions of genes belonging to each of the corresponding enriched hallmarks. GSEA was run against the MSigDB hallmark database using ranked LFCs derived from pseudobulk DEAs of Tregs from pretreatment MIS-C patients versus controls. adj, adjusted; tx, treatment.