Small RNA-Seq and real time rt-qPCR reveal islet miRNA released under stress conditions.

Replacement of beta cells through transplantation is a potential therapeutic approach for individuals with pancreas removal or poorly controllable type 1 diabetes. However, stress and death of beta cells pose significant challenges. Circulating miRNA has emerged as potential biomarkers reflecting early beta cell stress and death, allowing for timely intervention. The aim of this study was to identify miRNAs as potential biomarkers for beta cell health. Literature review combined with small RNA sequencing was employed to select islet-enriched miRNA. The release of those miRNA was assessed by RT-qPCR in vivo, using a streptozotocin induced diabetes mouse model and in vitro, through mouse and human islets exposed to varying degrees of hypoxic and cytokine stressors. Utilizing the streptozotocin induced model, we identified 18 miRNAs out of 39 candidate islet-enriched miRNA to be released upon islet stress in vivo. In vitro analysis of culture supernatants from cytokine and/or hypoxia stressed islets identified the release of 45 miRNAs from mouse and 8 miRNAs from human islets. Investigation into the biological pathways targeted by the cytokine- and/or hypoxia-induced miRNA suggested the involvement of MAPK and PI3K-Akt signaling pathways in both mouse and human islets. We have identified miRNAs associated with beta cell health and stress. The findings allowed us to propose a panel of 47 islet-related human miRNA that is potentially valuable for application in clinical contexts of beta cell transplantation and presymptomatic early-stage type 1 diabetes.

SARS-CoV-2 Infection and Development of Islet Autoimmunity in Early Childhood.

Importance: The incidence of diabetes in childhood has increased during the COVID-19 pandemic. Elucidating whether SARS-CoV-2 infection is associated with islet autoimmunity, which precedes type 1 diabetes onset, is relevant to disease etiology and future childhood diabetes trends. Objective: To determine whether there is a temporal relationship between SARS-CoV-2 infection and the development of islet autoimmunity in early childhood. Design, Setting, and Participants: Between February 2018 and March 2021, the Primary Oral Insulin Trial, a European multicenter study, enrolled 1050 infants (517 girls) aged 4 to 7 months with a more than 10% genetically defined risk of type 1 diabetes. Children were followed up through September 2022. Exposure: SARS-CoV-2 infection identified by SARS-CoV-2 antibody development in follow-up visits conducted at 2- to 6-month intervals until age 2 years from April 2018 through June 2022. Main Outcomes and Measures: The development of multiple (≥2) islet autoantibodies in follow-up in consecutive samples or single islet antibodies and type 1 diabetes. Antibody incidence rates and risk of developing islet autoantibodies were analyzed. Results: Consent was obtained for 885 (441 girls) children who were included in follow-up antibody measurements from age 6 months. SARS-CoV-2 antibodies developed in 170 children at a median age of 18 months (range, 6-25 months). Islet autoantibodies developed in 60 children. Six of these children tested positive for islet autoantibodies at the same time as they tested positive for SARS-CoV-2 antibodies and 6 at the visit after having tested positive for SARS-CoV-2 antibodies. The sex-, age-, and country-adjusted hazard ratio for developing islet autoantibodies when the children tested positive for SARS-CoV-2 antibodies was 3.5 (95% CI, 1.6-7.7; P = .002). The incidence rate of islet autoantibodies was 3.5 (95% CI, 2.2-5.1) per 100 person-years in children without SARS-CoV-2 antibodies and 7.8 (95% CI, 5.3-19.0) per 100 person-years in children with SARS-CoV-2 antibodies (P = .02). Islet autoantibody risk in children with SARS-CoV-2 antibodies was associated with younger age (<18 months) of SARS-CoV-2 antibody development (HR, 5.3; 95% CI, 1.5-18.3; P = .009). Conclusion and relevance: In young children with high genetic risk of type 1 diabetes, SARS-CoV-2 infection was temporally associated with the development of islet autoantibodies.

Corrigendum: A novel type I interferon primed dendritic cell subpopulation in TREX1 mutant chilblain lupus patients.

[This corrects the article DOI: 10.3389/fimmu.2022.897500.].

A Novel Type I Interferon Primed Dendritic Cell Subpopulation in TREX1 Mutant Chilblain Lupus Patients.

Heterozygous TREX1 mutations are associated with monogenic familial chilblain lupus and represent a risk factor for developing systemic lupus erythematosus. These interferonopathies originate from chronic type I interferon stimulation due to sensing of inadequately accumulating nucleic acids. We here analysed the composition of dendritic cell (DC) subsets, central stimulators of immune responses, in patients with TREX1 deficiency. We performed single-cell RNA-sequencing of peripheral blood DCs and monocytes from two patients with familial chilblain lupus and heterozygous mutations in TREX1 and from controls. Type I interferon pathway genes were strongly upregulated in patients. Cell frequencies of the myeloid and plasmacytoid DC and of monocyte populations in patients and controls were similar, but we describe a novel DC subpopulation highly enriched in patients: a myeloid DC CD1C+ subpopulation characterized by the expression of LMNA, EMP1 and a type I interferon- stimulated gene profile. The presence of this defined subpopulation was confirmed in a second cohort of patients and controls by flow cytometry, also revealing that an increased percentage of patient's cells in the subcluster express costimulatory molecules. We identified a novel type I interferon responsive myeloid DC subpopulation, that might be important for the perpetuation of TREX1-induced chilblain lupus and other type I interferonopathies.

Distinguishing activated T regulatory cell and T conventional cells by single-cell technologies.

Resting conventional T cells (Tconv) can be distinguished from T regulatory cells (Treg) by the canonical markers FOXP3, CD25 and CD127. However, the expression of these proteins alters after T-cell activation leading to overlap between Tconv and Treg. The objective of this study was to distinguish resting and antigen-responsive T effector (Tconv) and Treg using single-cell technologies. CD4+ Treg and Tconv cells were stimulated with antigen and responsive and non-responsive populations processed for targeted and non-targeted single-cell RNAseq. Machine learning was used to generate a limited set of genes that could distinguish responding and non-responding Treg and Tconv cells and which was used for single-cell multiplex qPCR and to design a flow cytometry panel. Targeted scRNAseq clearly distinguished the four-cell populations. A minimal set of 27 genes was identified by machine learning algorithms to provide discrimination of the four populations at >95% accuracy. In all, 15 of the genes were validated to be differentially expressed by single-cell multiplex qPCR. Discrimination of responding Treg from responding Tconv could be achieved by a flow cytometry strategy that included staining for CD25, CD127, FOXP3, IKZF2, ITGA4, and the novel marker TRIM which was strongly expressed in Tconv and weakly expressed in both responding and non-responding Treg. A minimal set of genes was identified that discriminates responding and non-responding CD4+ Treg and Tconv cells and, which have identified TRIM as a marker to distinguish Treg by flow cytometry.

Maternal Type 1 Diabetes Reduces Autoantigen-Responsive CD4+ T Cells in Offspring.

Autoimmunity against pancreatic ß-cell autoantigens is a characteristic of childhood type 1 diabetes (T1D). Autoimmunity usually appears in genetically susceptible children with the development of autoantibodies against (pro)insulin in early childhood. The offspring of mothers with T1D are protected from this process. The aim of this study was to determine whether the protection conferred by maternal T1D is associated with improved neonatal tolerance against (pro)insulin. Consistent with improved neonatal tolerance, the offspring of mothers with T1D had reduced cord blood CD4+ T-cell responses to proinsulin and insulin, a reduction in the inflammatory profile of their proinsulin-responsive CD4+ T cells, and improved regulation of CD4+ T cell responses to proinsulin at 9 months of age, as compared with offspring with a father or sibling with T1D. Maternal T1D was also associated with a modest reduction in CpG methylation of the INS gene in cord blood mononuclear cells from offspring with a susceptible INS genotype. Our findings support the concept that a maternal T1D environment improves neonatal immune tolerance against the autoantigen (pro)insulin.

Gene Expression-Based Identification of Antigen-Responsive CD8+ T Cells on a Single-Cell Level.

CD8+ T cells are important effectors of adaptive immunity against pathogens, tumors, and self antigens. Here, we asked how human cognate antigen-responsive CD8+ T cells and their receptors could be identified in unselected single-cell gene expression data. Single-cell RNA sequencing and qPCR of dye-labeled antigen-specific cells identified large gene sets that were congruently up- or downregulated in virus-responsive CD8+ T cells under different antigen presentation conditions. Combined expression of TNFRSF9, XCL1, XCL2, and CRTAM was the most distinct marker of virus-responsive cells on a single-cell level. Using transcriptomic data, we developed a machine learning-based classifier that provides sensitive and specific detection of virus-responsive CD8+ T cells from unselected populations. Gene response profiles of CD8+ T cells specific for the autoantigen islet-specific glucose-6-phosphatase catalytic subunit-related protein differed markedly from virus-specific cells. These findings provide single-cell gene expression parameters for comprehensive identification of rare antigen-responsive cells and T cell receptors.

Association of Dendritic Cell Signatures With Autoimmune Inflammation Revealed by Single-Cell Profiling.

OBJECTIVE: To identify single-cell transcriptional signatures of dendritic cells (DCs) that are associated with autoimmunity, and determine whether those DC signatures are correlated with the clinical heterogeneity of autoimmune disease. METHODS: Blood-derived DCs were single-cell sorted from the peripheral blood of patients with rheumatoid arthritis, systemic lupus erythematosus, or type 1 diabetes as well as healthy individuals. DCs were analyzed using single-cell gene expression assays, performed immediately after isolation or after in vitro stimulation of the cells. In addition, protein expression was measured using fluorescence-activated cell sorting. RESULTS: CD1c+ conventional DCs and plasmacytoid DCs from healthy individuals exhibited diverse transcriptional signatures, while the DC transcriptional signatures in patients with autoimmune disease were altered. In particular, distinct DC clusters, characterized by up-regulation of TAP1, IRF7, and IFNAR1, were abundant in patients with systemic autoimmune disease, whereas DCs from patients with type 1 diabetes had decreased expression of the regulatory genes PTPN6, TGFB, and TYROBP. The frequency of CD1c+ conventional DCs that expressed a systemic autoimmune profile directly correlated with the extent of disease activity in patients with rheumatoid arthritis (Spearman's r = 0.60, P = 0.03). CONCLUSION: DC transcriptional signatures are altered in patients with autoimmune disease and are associated with the level of disease activity, suggesting that immune cell transcriptional profiling could improve our ability to detect and understand the heterogeneity of these diseases, and could guide treatment choices in patients with a complex autoimmune disease.

CD8+ T cells specific for the islet autoantigen IGRP are restricted in their T cell receptor chain usage.

CD8+ T cells directed against beta cell autoantigens are considered relevant for the pathogenesis of type 1 diabetes. Using single cell T cell receptor sequencing of CD8+ T cells specific for the IGRP265-273 epitope, we examined whether there was expansion of clonotypes and sharing of T cell receptor chains in autoreactive CD8+ T cell repertoires. HLA-A*0201 positive type 1 diabetes patients (n = 19) and controls (n = 18) were analysed. TCR α- and ß-chain sequences of 418 patient-derived IGRP265-273-multimer+ CD8+ T cells representing 48 clonotypes were obtained. Expanded populations of IGRP265-273-specific CD8+ T cells with dominant clonotypes that had TCR α-chains shared across patients were observed. The SGGSNYKLTF motif corresponding to TRAJ53 was contained in 384 (91.9%) cells, and in 20 (41.7%) patient-derived clonotypes. TRAJ53 together with TRAV29/DV5 was found in 15 (31.3%) clonotypes. Using next generation TCR α-chain sequencing, we found enrichment of one of these TCR α-chains in the memory CD8+ T cells of patients as compared to healthy controls. CD8+ T cell clones bearing the enriched motifs mediated antigen-specific target cell lysis. We provide the first evidence for restriction of T cell receptor motifs in the alpha chain of human CD8+ T cells with specificity to a beta cell antigen.

A divergent population of autoantigen-responsive CD4+ T cells in infants prior to ß cell autoimmunity.

Autoimmune diabetes is marked by sensitization to ß cell self-antigens in childhood. We longitudinally followed at-risk children from infancy and performed single-cell gene expression in ß cell antigen-responsive CD4+ T cells through pre- and established autoimmune phases. A striking divergence in the gene signature of ß cell antigen-responsive naïve CD4+ T cells from children who developed ß cell autoimmunity was found in infancy, well before the appearance of ß cell antigen-specific memory T cells or autoantibodies. The signature resembled a pre-T helper 1 (TH1)/TH17/T follicular helper cell response with expression of CCR6, IL21, TBX21, TNF, RORC, EGR2, TGFB1, and ICOS, in the absence of FOXP3, IL17, and other cytokines. The cells transitioned to an IFNG-TH1 memory phenotype with the emergence of autoantibodies. We suggest that the divergent naïve T cell response is a consequence of genetic or environmental priming during unfavorable perinatal exposures and that the signature will guide future efforts to detect and prevent ß cell autoimmunity.

High diversity in the TCR repertoire of GAD65 autoantigen-specific human CD4+ T cells.

Autoreactive CD4(+) T cells are an essential feature of type 1 diabetes mellitus. We applied single-cell TCR α- and ß-chain sequencing to peripheral blood GAD65-specific CD4(+) T cells, and TCR α-chain next-generation sequencing to bulk memory CD4(+) T cells to provide insight into TCR diversity in autoimmune diabetes mellitus. TCRs obtained for 1650 GAD65-specific CD4(+) T cells isolated from GAD65 proliferation assays and/or GAD65 557I tetramer staining in 6 patients and 10 islet autoantibody-positive children showed large diversity with 1003 different TCRs identified. TRAV and TRBV gene usage was broad, and the TRBV5.1 gene was most prominent within the GAD65 557I tetramer(+) cells. Limited overlap (<5%) was observed between TCRs of GAD65-proliferating and GAD65 557I tetramer(+) CD4(+) T cells. Few TCRs were repeatedly found in GAD65-specific cells at different time points from individual patients, and none was seen in more than one subject. However, single chains were often shared between patients and used in combination with different second chains. Next-generation sequencing revealed a wide frequency range (<0.00001-1.62%) of TCR α-chains corresponding to GAD65-specific T cells. The findings support minor selection of genes and TCRs for GAD65-specific T cells, but fail to provide strong support for TCR-targeted therapies.

Measuring T cell receptor and T cell gene expression diversity in antigen-responsive human CD4+ T cells.

T cells have diversity in TCR, epitope recognition, and cytokine production, and can be used for immune monitoring. Furthermore, clonal expansion of TCR families in disease may provide opportunities for TCR-directed therapies. We developed methodology for sequencing expressed genes of TCR alpha and beta chains from single cells and applied this to vaccine (tetanus-toxoid)-responsive CD4(+) T cells. TCR alpha and beta chains were both successfully sequenced in 1309 (43%) of 3038 CD4(+) T cells yielding 677 different receptors. TRAV and TRBV gene usage differed between tetanus-toxoid-responsive and non-responsive cells (p=0.004 and 0.0002), and there was extensive TCR diversity in tetanus-toxoid-responsive cells within individuals. Identical TCRs could be recovered in different samples from the same subject: TCRs identified after booster vaccination were frequent in pre-booster memory T cells (31% of pre-booster TCR), and also identified in pre-booster vaccination naïve cells (6.5%). No TCR was shared between subjects, but tetanus toxoid-responsive cells sharing one of their TCR chains were observed within and between subjects. Coupling single-cell gene expression profiling to TCR sequencing revealed examples of distinct cytokine profiles in cells bearing identical TCR. Novel molecular methodology demonstrates extensive diversity of Ag-responsive CD4(+) T cells within and between individuals.