Exploring T Cell Receptor Repertoires in Myocardial Diseases.

Mounting experimental and clinical evidence has revealed that adaptive immune mechanisms targeting myocardial antigens are triggered by different forms of cardiac injury and impact disease progression. B and T lymphocytes recognize specific antigens via unique adaptive immune receptors generated through a somatic rearrangement process that generates a potential repertoire of 1019 unique receptors. While the adaptive immune receptor repertoire diversity provides the basis for immunologic specificity, making sense of it can be a challenging task. In the present review, we discuss key aspects underlying the generation of TCRs (T cell receptors) and emerging tools for their study in the context of myocardial diseases. Moreover, we outline how exploring TCR repertoires could lead to a deeper understanding of myocardial pathophysiological principles and potentially serve as diagnostic tools.

Myocardial Milieu Favors Local Differentiation of Regulatory T Cells.

BACKGROUND: In the past years, several studies investigated how distinct immune cell subsets affects post-myocardial infarction repair. However, whether and how the tissue environment controls these local immune responses has remained poorly understood. We sought to investigate how antigen-specific T-helper cells differentiate under myocardial milieu's influence. METHODS: We used a transgenic T cell receptor (TCR-M) model and major histocompatibility complex-II tetramers, both myosin-specific, combined with single-cell transcriptomics (single-cell RNA sequencing [scRNA-seq]) and functional phenotyping to elucidate how the antigen-specific CD4+ T cells differentiate in the murine infarcted myocardium and influence tissue repair. Additionally, we transferred proinflammatory versus regulatory predifferentiated TCR-M-cells to dissect how they specially contribute to post-myocardial infarction inflammation. RESULTS: Flow cytometry and scRNA-/TCR-seq analyses revealed that transferred TCR-M cells acquired an induced regulatory phenotype (induced regulatory T cell) in the infarcted myocardium and blunted local inflammation. Myocardial TCR-M cells differentiated into 2 main lineages enriched with either cell activation and profibrotic transcripts (eg, Tgfb1) or suppressor immune checkpoints (eg, Pdcd1), which we also found in human myocardial tissue. These cells produced high levels of LAP (latency-associated peptide) and inhibited IL-17 (interleukin-17) responses. Endogenous myosin-specific T-helper cells, identified using genetically barcoded tetramers, also accumulated in infarcted hearts and exhibited a regulatory phenotype. Notably, TCR-M cells that were predifferentiated toward a regulatory phenotype in vitro maintained stable in vivo FOXP3 (Forkhead box P3) expression and anti-inflammatory activity whereas TH17 partially converted toward a regulatory phenotype in the injured myocardium. Overall, the myosin-specific Tregs dampened post-myocardial infarction inflammation, suppressed neighboring T cells, and were associated with improved cardiac function. CONCLUSIONS: These findings provide novel evidence that the heart and its draining lymph nodes actively shape local immune responses by promoting the differentiation of antigen-specific Tregs poised with suppressive function.

Deep immunophenotyping reveals that autoimmune and autoinflammatory disorders are spread along two immunological axes capturing disease inflammation levels and types.

OBJECTIVES: Based on genetic associations, McGonagle and McDermott suggested a classification of autoimmune and autoinflammatory diseases as a continuum ranging from purely autoimmune to purely autoinflammatory diseases and comprising diseases with both components. We used deep immunophenotyping to identify immune cell populations and molecular targets characterising this continuum. METHODS: We collected blood from 443 patients with one of 15 autoimmune or autoinflammatory diseases and 71 healthy volunteers. Deep phenotyping was performed using 13 flow cytometry panels characterising over 600 innate and adaptive cell populations. Unsupervised and supervised analyses were conducted to identify disease clusters with their common and specific cell parameters. RESULTS: Unsupervised clustering categorised these diseases into five clusters. Principal component analysis deconvoluted this clustering into two immunological axes. The first axis was driven by the ratio of LAG3+ to ICOS+ in regulatory T lymphocytes (Tregs), and segregated diseases based on their inflammation levels. The second axis was driven by activated Tregs and type 3 innate lymphoid cells (ILC3s), and segregated diseases based on their types of affected tissues. We identified a signature of 23 cell populations that accurately characterised the five disease clusters. CONCLUSIONS: We have refined the monodimensional continuum of autoimmune and autoinflammatory diseases as a continuum characterised by both disease inflammation levels and targeted tissues. Such classification should be helpful for defining therapies. Our results call for further investigations into the role of the LAG3+/ICOS+ balance in Tregs and the contribution of ILC3s in autoimmune and autoinflammatory diseases. TRIAL REGISTRATION NUMBER: NCT02466217.

Clinical correlates of lifetime and current comorbidity patterns in autoimmune and inflammatory diseases.

BACKGROUND: Autoimmune and inflammatory diseases (AIDs) are a heterogeneous group of disorders with diverse etiopathogenic mechanisms. This study explores the potential utility of family history, together with present and past comorbidities, in identifying distinct etiopathogenic subgroups. This approach may facilitate more accurate diagnosis, prognosis and personalized therapy. METHODS: We performed a multiple correspondence analysis on patients' comorbidities, followed by hierarchical principal component clustering of clinical data from 48 healthy volunteers and 327 patients with at least one of 19 selected AIDs included in the TRANSIMMUNOM cross-sectional study. RESULTS: We identified three distinct clusters characterized by: 1) the absence of comorbidities, 2) polyautoimmunity, and 3) polyinflammation. These clusters were further distinguished by specific comorbidities and biological parameters. Autoantibodies, allergies, and viral infections characterized the polyautoimmunity cluster, while older age, BMI, depression, cancer, hypertension, periodontal disease, and dyslipidemia characterized the polyinflammation cluster. Rheumatoid arthritis patients were distributed across all three clusters. They had higher DAS28 and prevalence of extra-articular manifestations when belonging to the polyinflammation and polyautoimmunity clusters, and also lower ACPA and RF seropositivity and higher pain scores within the polyinflammation cluster. We developed a model allowing to classify AID patients into comorbidity clusters. CONCLUSIONS: In this study, we have uncovered three distinct comorbidity profiles among AID patients. These profiles suggest the presence of distinct etiopathogenic mechanisms underlying these subgroups. Validation, longitudinal stability assessment, and exploration of their impact on therapy efficacy are needed for a comprehensive understanding of their potential role in personalized medicine.

Clonotypic IgH Response against Systemic Viral infection in Pronephros and Spleen of a Teleost Fish.

Upon infection, B lymphocytes develop clonal responses. In teleost fish, which lack lymph nodes, the kinetics and location of B cell responses remain poorly characterized. Fish pronephros is the site of B cell differentiation and the main niche for persistence of plasma cells. In this study, we undertook the analysis of the rainbow trout IgHµ repertoire in this critical tissue for humoral adaptive immunity after primary immunization and boost with a rhabdovirus, the viral hemorrhagic septicemia virus (VHSV). We used a barcoded 5' RACE-cDNA sequencing approach to characterize modifications of the IgHµ repertoire, including VH usage in expressed V(D)J rearrangements, clonal diversity, and clonotype sharing between individual fish and treatments. In the pronephros, our approach quantified the clonotype frequency across the whole IgH repertoire (i.e., with all VH), measuring the frequency of Ag-responding clonotypes. Viral infection led to extensive modifications of the pronephros B cell repertoire, implicating several VH subgroups after primary infection. In contrast, only modest changes in repertoire persisted 5 mo later, including VHSV-specific public expansions. The IgM public response implicating IgHV1-18 and JH5, previously described in spleen, was confirmed in pronephros in all infected fish, strongly correlated to the response. However, the distribution of top clonotypes showed that pronephros and spleen B cells constitute distinct compartments with different IgH repertoires. Unexpectedly, after boost, the frequency of anti-VHSV clonotypes decreased both in pronephros and spleen, raising questions about B cell circulation. A better monitoring of B cell response kinetics in lymphoid tissues will be an essential step to understand B memory and plasmocyte formation mechanisms in fish.

High-resolution repertoire analysis reveals a major bystander activation of Tfh and Tfr cells.

T follicular helper (Tfh) and regulatory (Tfr) cells are terminally differentiated cells found in germinal centers (GCs), specialized secondary lymphoid organ structures dedicated to antibody production. As such, follicular T (Tfol) cells are supposed to be specific for immunizing antigens, which has been reported for Tfh cells but is debated for Tfr cells. Here, we used high-throughput T cell receptor (TCR) sequencing to analyze the repertoires of Tfh and Tfr cells, at homeostasis and after immunization with self- or foreign antigens. We observed that, whatever the conditions, Tfh and Tfr cell repertoires are less diverse than those of effector T cells and Treg cells of the same tissues; surprisingly, these repertoires still represent thousands of different sequences, even after immunization with a single antigen that induces a 10-fold increase in Tfol cell numbers. Thorough analysis of the sharing and network of TCR sequences revealed that a specific response to the immunizing antigen can only, but hardly, be detected in Tfh cells immunized with a foreign antigen and Tfr cells immunized with a self-antigen. These antigen-specific responses are obscured by a global stimulation of Tfh and Tfr cells that appears to be antigen-independent. Altogether, our results suggest a major bystander Tfol cell activation during the immune response in the GCs.

TCR sequences and tissue distribution discriminate the subsets of naïve and activated/memory Treg cells in mice.

Analyses of the regulatory T (Treg) cell TCR repertoire should help elucidate the nature and diversity of their cognate antigens and thus how Treg cells protect us from autoimmune diseases. We earlier identified CD44(hi) CD62L(low) activated/memory (am) Treg cells as a Treg-cell subset with a high turnover and possible self-specificity. We now report that amTreg cells are predominantly distributed in lymph nodes (LNs) draining deep tissues. Multivariate analyses of CDR3 spectratyping first revealed that amTreg TCR repertoire is different from that of naïve Treg cells (nTreg cells) and effector T (Teff) cells. Furthermore, in deep- versus superficial LNs, TCR-ß deep sequencing further revealed diversified nTreg-cell and amTreg-cell repertoires, although twofold less diverse than that of Teff cells, and with repertoire richness significantly lower in deep-LN versus superficial-LN Treg cells. Importantly, expanded clonotypes were mostly detected in deep-LN amTreg cells, some accounting for 20% of the repertoire. Strikingly, these clonotypes were absent from nTreg cells, but found at low frequency in Teff cells. Our results, obtained in nonmanipulated mice, indicate different antigenic targets for naïve and amTreg cells and that amTreg cells are self-specific. The data we present are consistent with an instructive component in Treg-cell differentiation.

Enhancing comparative T cell receptor repertoire analysis in small biological samples through pooling homologous cell samples from multiple mice.

Accurate characterization and comparison of T cell receptor (TCR) repertoires from small biological samples present significant challenges. The main challenge is the low material input, which compromises the quality of bulk sequencing and hinders the recovery of sufficient TCR sequences for robust analyses. We aimed to address this limitation by implementing a strategic approach to pool homologous biological samples. Our findings demonstrate that such pooling indeed enhances the TCR repertoire coverage, particularly for cell subsets of constrained sizes, and enables accurate comparisons of TCR repertoires at different levels of complexity across T cell subsets with different sizes. This methodology holds promise for advancing our understanding of T cell repertoires in scenarios where sample size constraints are a prevailing concern.

Single-cell RNA-Seq analysis reveals cell subsets and gene signatures associated with rheumatoid arthritis disease activity.

Rheumatoid arthritis (RA) management leans toward achieving remission or low disease activity. In this study, we conducted single-cell RNA sequencing (scRNA-Seq) of peripheral blood mononuclear cells (PBMCs) from 36 individuals (18 patients with RA and 18 matched controls, accounting for age, sex, race, and ethnicity), to identify disease-relevant cell subsets and cell type-specific signatures associated with disease activity. Our analysis revealed 18 distinct PBMC subsets, including an IFN-induced transmembrane 3-overexpressing (IFITM3-overexpressing) IFN-activated monocyte subset. We observed an increase in CD4+ T effector memory cells in patients with moderate-high disease activity (DAS28-CRP ≥ 3.2) and a decrease in nonclassical monocytes in patients with low disease activity or remission (DAS28-CRP < 3.2). Pseudobulk analysis by cell type identified 168 differentially expressed genes between RA and matched controls, with a downregulation of proinflammatory genes in the γδ T cell subset, alteration of genes associated with RA predisposition in the IFN-activated subset, and nonclassical monocytes. Additionally, we identified a gene signature associated with moderate-high disease activity, characterized by upregulation of proinflammatory genes such as TNF, JUN, EGR1, IFIT2, MAFB, and G0S2 and downregulation of genes including HLA-DQB1, HLA-DRB5, and TNFSF13B. Notably, cell-cell communication analysis revealed an upregulation of signaling pathways, including VISTA, in both moderate-high and remission-low disease activity contexts. Our findings provide valuable insights into the systemic cellular and molecular mechanisms underlying RA disease activity.

Identification of Symptom Phenotypes of Hand Osteoarthritis Using Hierarchical Clustering: Results From the DIGICOD Cohort.

OBJECTIVE: We aimed to delineate phenotypes in hand osteoarthritis (HOA) based on cardinal symptoms (pain, functional limitation, stiffness, and aesthetic discomfort). METHODS: With data from the Digital Cohort Design (DIGICOD), we performed a hierarchical agglomerative clustering analysis based on Australian/Canadian Osteoarthritis Hand Index (AUSCAN) subscores for pain, physical function, stiffness, and visual analog scale for aesthetic discomfort. Kruskal-Wallis and post hoc analyses were used to assess differences between clusters. RESULTS: Among 389 patients, we identified 5 clusters: cluster 1 (n = 88) and cluster 2 (n = 91) featured low and mild symptoms; cluster 3 (n = 80) featured isolated aesthetic discomfort; cluster 4 (n = 42) featured a high level of pain, stiffness, and functional limitation; and cluster 5 (n = 88) had the same features as cluster 4 but with high aesthetic discomfort. For clusters 4 and 5, AUSCAN pain score was >41 of 100, representing only one-third of our patients. Aesthetic discomfort (clusters 3 and 5) was significantly associated with erosive HOA and a higher number of nodes. The highly symptomatic cluster 5 was associated but not significantly with metabolic syndrome, and body mass index and C-reactive protein level did not differ among clusters. Symptom intensity was significantly associated with joint destruction as well as with physical and psychological burden. Patients' main expectations differed among clusters, and function improvement was the most frequent expectation overall. CONCLUSION: The identification of distinct clinical clusters based on HOA cardinal symptoms suggests previously undescribed subtypes of this condition, warranting further study of biological characteristics of such clusters, and opening a path toward phenotype-based personalized medicine in HOA.

Human thymopoiesis produces polyspecific CD8+ α/ß T cells responding to multiple viral antigens.

T-cell receptors (TCRs) are formed by stochastic gene rearrangements, theoretically generating >1019 sequences. They are selected during thymopoiesis, which releases a repertoire of about 108 unique TCRs per individual. How evolution shaped a process that produces TCRs that can effectively handle a countless and evolving set of infectious agents is a central question of immunology. The paradigm is that a diverse enough repertoire of TCRs should always provide a proper, though rare, specificity for any given need. Expansion of such rare T cells would provide enough fighters for an effective immune response and enough antigen-experienced cells for memory. We show here that human thymopoiesis releases a large population of clustered CD8+ T cells harboring α/ß paired TCRs that (i) have high generation probabilities and (ii) a preferential usage of some V and J genes, (iii) which CDR3 are shared between individuals, and (iv) can each bind and be activated by multiple unrelated viral peptides, notably from EBV, CMV, and influenza. These polyspecific T cells may represent a first line of defense that is mobilized in response to infections before a more specific response subsequently ensures viral elimination. Our results support an evolutionary selection of polyspecific α/ß TCRs for broad antiviral responses and heterologous immunity.

Single-Cell Analysis and Tracking of Antigen-Specific T Cells: Integrating Paired Chain AIRR-Seq and Transcriptome Sequencing: A Method by the AIRR Community.

Single-cell adaptive immune receptor repertoire sequencing (scAIRR-seq) offers the possibility to access the nucleotide sequences of paired receptor chains from T-cell receptors (TCR) or B-cell receptors (BCR ). Here we describe two protocols and the downstream bioinformatic approaches that facilitate the integrated analysis of paired T-cell receptor (TR ) alpha/beta (TRA /TRB ) AIRR-seq, RNA sequencing (RNAseq), immunophenotyping, and antigen-binding information. To illustrate the methodologies with a use case, we describe how to identify, characterize, and track SARS-CoV-2-specific T cells over multiple time points following infection with the virus. The first method allows the analysis of pools of memory CD8+ cells, identifying expansions and contractions of clones of interest. The second method allows the study of rare or antigen-specific cells and allows studying their changes over time.

Use of machine learning in osteoarthritis research: a systematic literature review.

OBJECTIVE: The aim of this systematic literature review was to provide a comprehensive and exhaustive overview of the use of machine learning (ML) in the clinical care of osteoarthritis (OA). METHODS: A systematic literature review was performed in July 2021 using MEDLINE PubMed with key words and MeSH terms. For each selected article, the number of patients, ML algorithms used, type of data analysed, validation methods and data availability were collected. RESULTS: From 1148 screened articles, 46 were selected and analysed; most were published after 2017. Twelve articles were related to diagnosis, 7 to prediction, 4 to phenotyping, 12 to severity and 11 to progression. The number of patients included ranged from 18 to 5749. Overall, 35% of the articles described the use of deep learning And 74% imaging analyses. A total of 85% of the articles involved knee OA and 15% hip OA. No study investigated hand OA. Most of the studies involved the same cohort, with data from the OA initiative described in 46% of the articles and the MOST and Cohort Hip and Cohort Knee cohorts in 11% and 7%. Data and source codes were described as publicly available respectively in 54% and 22% of the articles. External validation was provided in only 7% of the articles. CONCLUSION: This review proposes an up-to-date overview of ML approaches used in clinical OA research and will help to enhance its application in this field.

AIRR Community Guide to Planning and Performing AIRR-Seq Experiments.

The development of high-throughput sequencing of adaptive immune receptor repertoires (AIRR-seq of IG and TR rearrangements) has provided a new frontier for in-depth analysis of the immune system. The last decade has witnessed an explosion in protocols, experimental methodologies, and computational tools. In this chapter, we discuss the major considerations in planning a successful AIRR-seq experiment together with basic strategies for controlling and evaluating the outcome of the experiment. Members of the AIRR Community have authored several chapters in this edition, which cover step-by-step instructions to successfully conduct, analyze, and share an AIRR-seq project.

Regulatory T lymphocytes/Th17 lymphocytes imbalance in autism spectrum disorders: evidence from a meta-analysis.

BACKGROUND: Immune system dysfunction has been proposed to play a critical role in the pathophysiology of autism spectrum disorders (ASD). Conflicting reports of lymphocyte subpopulation abnormalities have been described in numerous studies of patients with ASD. To better define lymphocytes abnormalities in ASD, we performed a meta-analysis of the lymphocyte profiles from subjects with ASD. METHODS: We used the PRISMA recommendations to query PubMed, Embase, PsychoINFO, BIOSIS, Science Direct, Cochrane CENTRAL, and Clinicaltrials.gov for terms related to clinical diagnosis of ASD and to lymphocytes' populations. We selected studies exploring lymphocyte subpopulations in children with ASD. The search protocol has been registered in the international Prospective Register of Systematic Reviews (CRD42019121473). RESULTS: We selected 13 studies gathering 388 ASD patients and 326 healthy controls. A significant decrease in the CD4+ lymphocyte was found in ASD patients compared to controls [- 1.51 (95% CI - 2.99; - 0.04) p = 0.04] (I2 = 96% [95% CI 94.6, 97.7], p < 0.01). No significant difference was found for the CD8+ T, B and natural killer lymphocytes. Considering the CD4+ subpopulation, there was a significant decrease in regulatory T lymphocytes (Tregs) in ASD patients (n = 114) compared to controls (n = 107) [- 3.09 (95% CI - 4.41; - 1.76) p = 0.0001]; (I2 = 90.9%, [95% CI 76.2, 96.5], p < 0.0001) associated with an increase oin the Th17 lymphocytes (ASD; n = 147 controls; n = 128) [2.23 (95% CI 0.79; 3.66) p = 0,002] (I2 = 95.1% [95% CI 90.4, 97.5], p < 0.0001). LIMITATIONS: Several factors inducing heterogeneity should be considered. First, differences in the staining method may be responsible for a part in the heterogeneity of results. Second, ASD population is also by itself heterogeneous, underlying the need of studying sub-groups that are more homogeneous. CONCLUSION: Our meta-analysis indicates defects in CD4+ lymphocytes, specifically decrease oin Tregs and increase in Th17 in ASD patients and supports the development of targeted immunotherapies in the field of ASD.

Biological controls for standardization and interpretation of adaptive immune receptor repertoire profiling.

Use of adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread, providing new insights into the immune system with potential broad clinical and diagnostic applications. However, like many high-throughput technologies, it comes with several problems, and the AIRR Community was established to understand and help solve them. We, the AIRR Community's Biological Resources Working Group, have surveyed scientists about the need for standards and controls in generating and annotating AIRR-seq data. Here, we review the current status of AIRR-seq, provide the results of our survey, and based on them, offer recommendations for developing AIRR-seq standards and controls, including future work.

Impaired Activated/Memory Regulatory T Cell Clonal Expansion Instigates Diabetes in NOD Mice.

Regulatory T cell (Treg) insufficiency licenses the destruction of insulin-producing pancreatic ß-cells by autoreactive effector T cells (Teffs), causing spontaneous autoimmune diabetes in NOD mice. We investigated the contribution to diabetes of the T-cell receptor (TCR) repertoires of naive regulatory T cells (nTregs), activated/memory Tregs (amTregs), and CD4+ Teffs from prediabetic NOD mice and normal C57BL/6 (B6) mice. NOD mice amTreg and Teff repertoire diversity was unexpectedly higher than that of B6 mice. This was due to the presence of highly expanded clonotypes in B6 amTregs and Teffs that were largely lost in their NOD counterparts. Interleukin-2 (IL-2) administration to NOD mice restored such amTreg clonotype expansions and prevented diabetes development. In contrast, IL-2 administration only led to few or no clonotype expansions in nTregs and Teffs, respectively. Noteworthily, IL-2-expanded amTreg and nTreg clonotypes were markedly enriched in islet-antigen specific TCRs. Altogether, our results highlight the link between a reduced clonotype expansion within the activated Treg repertoire and the development of an autoimmune disease. They also indicate that the repertoire of amTregs is amenable to rejuvenation by IL-2.

Benchmarking of T cell receptor repertoire profiling methods reveals large systematic biases.

Monitoring the T cell receptor (TCR) repertoire in health and disease can provide key insights into adaptive immune responses, but the accuracy of current TCR sequencing (TCRseq) methods is unclear. In this study, we systematically compared the results of nine commercial and academic TCRseq methods, including six rapid amplification of complementary DNA ends (RACE)-polymerase chain reaction (PCR) and three multiplex-PCR approaches, when applied to the same T cell sample. We found marked differences in accuracy and intra- and inter-method reproducibility for T cell receptor α (TRA) and T cell receptor ß (TRB) TCR chains. Most methods showed a lower ability to capture TRA than TRB diversity. Low RNA input generated non-representative repertoires. Results from the 5' RACE-PCR methods were consistent among themselves but differed from the RNA-based multiplex-PCR results. Using an in silico meta-repertoire generated from 108 replicates, we found that one genomic DNA-based method and two non-unique molecular identifier (UMI) RNA-based methods were more sensitive than UMI methods in detecting rare clonotypes, despite the better clonotype quantification accuracy of the latter.

Polyclonal expansion of TCR Vbeta 21.3+ CD4+ and CD8+ T cells is a hallmark of Multisystem Inflammatory Syndrome in Children.

Multiple Inflammatory Syndrome in Children (MIS-C) is a delayed and severe complication of SARS-CoV-2 infection that strikes previously healthy children. As MIS-C combines clinical features of Kawasaki disease and Toxic Shock Syndrome (TSS), we aimed to compare the immunological profile of pediatric patients with these different conditions. We analyzed blood cytokine expression, and the T cell repertoire and phenotype in 36 MIS-C cases, which were compared to 16 KD, 58 TSS, and 42 COVID-19 cases. We observed an increase of serum inflammatory cytokines (IL-6, IL-10, IL-18, TNF-α, IFNγ, CD25s, MCP1, IL-1RA) in MIS-C, TSS and KD, contrasting with low expression of HLA-DR in monocytes. We detected a specific expansion of activated T cells expressing the Vß21.3 T cell receptor ß chain variable region in both CD4 and CD8 subsets in 75% of MIS-C patients and not in any patient with TSS, KD, or acute COVID-19; this correlated with the cytokine storm detected. The T cell repertoire returned to baseline within weeks after MIS-C resolution. Vß21.3+ T cells from MIS-C patients expressed high levels of HLA-DR, CD38 and CX3CR1 but had weak responses to SARS-CoV-2 peptides in vitro. Consistently, the T cell expansion was not associated with specific classical HLA alleles. Thus, our data suggested that MIS-C is characterized by a polyclonal Vß21.3 T cell expansion not directed against SARS-CoV-2 antigenic peptides, which is not seen in KD, TSS and acute COVID-19.