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.

Potential of TCR sequencing in graft-versus-host disease.

Graft-versus-host disease (GvHD) remains one of the major complications following allogeneic haematopoietic stem cell transplantation (allo-HSCT). GvHD can occur in almost every tissue, with the skin, liver, and intestines being the mainly affected organs. T cells are implicated in initiating GvHD. T cells identify a broad range of antigens and mediate the immune response through receptors on their surfaces (T cell receptors, TCRs). The composition of TCRs within a T cell population defines the TCR repertoire of an individual, and this repertoire represents exposure to self and non-self proteins. Monitoring the changes in the TCR repertoire using TCR sequencing can provide an indication of the dynamics of a T cell population. Monitoring the frequency and specificities of specific TCR clonotypes longitudinally in different conditions and specimens (peripheral blood, GvHD-affected tissue samples) can provide insights into factors modulating immune reactions following allogeneic transplantation and will help to understand the underlying mechanisms mediating GvHD. This review provides insights into current studies of the TCR repertoire in GvHD and potential future clinical implications of TCR sequencing.

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.

Autoantibodies against ATP4A are a feature of the abundant autoimmunity that develops in first-degree relatives of patients with type 1 diabetes.

OBJECTIVE: Type 1 diabetes is associated with autoantibodies to different organs that include the gut. The objective of the study was to determine the risk of developing gastric parietal cell autoimmunity in relation to other autoimmunity in individuals with a family history of type 1 diabetes. METHODS: Autoantibodies to the parietal cell autoantigen, H+ /K+ ATPase subunit A (ATP4A) was measured in 2218 first-degree relatives of patients with type 1 diabetes, who were prospectively followed from birth for a median of 14.5 years. All were also tested regularly for the development of islet autoantibodies, transglutaminase autoantibodies, and thyroid peroxidase autoantibodies. RESULTS: The cumulative risk to develop ATP4A autoantibodies was 8.1% (95% CI, 6.6-9.6) by age 20 years with a maximum incidence observed at age 2 years. Risk was increased in females (HR, 1.9; 95% CI, 1.3-2.8; p = 0.0004), relatives with the HLA DR4-DQ8/DR4-DQ8 genotype (HR, 3.4; 95% CI, 1.9-5.9; p < 0.0001) and in participants who also had thyroid peroxidase autoantibodies (HR, 3.7; 95% CI, 2.5-5.5; p < 0.0001). Risk for at least one of ATP4A-, islet-, transglutaminase-, or thyroid peroxidase-autoantibodies was 24.7% (95% CI, 22.6-26.7) by age 20 years and was 47.3% (95% CI, 41.3-53.3) in relatives who had an HLA DR3/DR4-DQ8, DR4-DQ8/DR4-DQ8, or DR3/DR3 genotype (p < 0.0001 vs. other genotypes). CONCLUSIONS: Relatives of patients with type 1 diabetes who have risk genotypes are at very high risk for the development of autoimmunity against gastric and other organs.

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.

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.

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.

Trained innate immunity, long-lasting epigenetic modulation, and skewed myelopoiesis by heme.

Trained immunity defines long-lasting adaptations of innate immunity based on transcriptional and epigenetic modifications of myeloid cells and their bone marrow progenitors [M. Divangahi et al., Nat. Immunol. 22, 2-6 (2021)]. Innate immune cells, however, do not exclusively differentiate between foreign and self but also react to host-derived molecules referred to as alarmins. Extracellular "labile" heme, released during infections, is a bona fide alarmin promoting myeloid cell activation [M. P. Soares, M. T. Bozza, Curr. Opin. Immunol. 38, 94-100 (2016)]. Here, we report that labile heme is a previously unrecognized inducer of trained immunity that confers long-term regulation of lineage specification of hematopoietic stem cells and progenitor cells. In contrast to previous reports on trained immunity, essentially mediated by pathogen-associated molecular patterns, heme training depends on spleen tyrosine kinase signal transduction pathway acting upstream of c-Jun N-terminal kinases. Heme training promotes resistance to sepsis, is associated with the expansion of self-renewing hematopoetic stem cells primed toward myelopoiesis and to the occurrence of a specific myeloid cell population. This is potentially evoked by sustained activity of Nfix, Runx1, and Nfe2l2 and dissociation of the transcriptional repressor Bach2. Previously reported trained immunity inducers are, however, infrequently present in the host, whereas heme abundantly occurs during noninfectious and infectious disease. This difference might explain the vanishing protection exerted by heme training in sepsis over time with sustained long-term myeloid adaptations. Hence, we propose that trained immunity is an integral component of innate immunity with distinct functional differences on infectious disease outcome depending on its induction by pathogenic or endogenous molecules.

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.

Oral insulin immunotherapy in children at risk for type 1 diabetes in a randomised controlled trial.

AIMS/HYPOTHESIS: Oral administration of antigen can induce immunological tolerance. Insulin is a key autoantigen in childhood type 1 diabetes. Here, oral insulin was given as antigen-specific immunotherapy before the onset of autoimmunity in children from age 6 months to assess its safety and immune response actions on immunity and the gut microbiome. METHODS: A phase I/II randomised controlled trial was performed in a single clinical study centre in Germany. Participants were 44 islet autoantibody-negative children aged 6 months to 2.99 years who had a first-degree relative with type 1 diabetes and a susceptible HLA DR4-DQ8-containing genotype. Children were randomised 1:1 to daily oral insulin (7.5 mg with dose escalation to 67.5 mg) or placebo for 12 months using a web-based computer system. The primary outcome was immune efficacy pre-specified as induction of antibody or T cell responses to insulin and measured in a central treatment-blinded laboratory. RESULTS: Randomisation was performed in 44 children. One child in the placebo group was withdrawn after the first study visit and data from 22 insulin-treated and 21 placebo-treated children were analysed. Oral insulin was well tolerated with no changes in metabolic variables. Immune responses to insulin were observed in children who received both insulin (54.5%) and placebo (66.7%), and the trial did not demonstrate an effect on its primary outcome (p = 0.54). In exploratory analyses, there was preliminary evidence that the immune response and gut microbiome were modified by the INS genotype Among children with the type 1 diabetes-susceptible INS genotype (n = 22), antibody responses to insulin were more frequent in insulin-treated (72.7%) as compared with placebo-treated children (18.2%; p = 0.03). T cell responses to insulin were modified by treatment-independent inflammatory episodes. CONCLUSIONS/INTERPRETATION: The study demonstrated that oral insulin immunotherapy in young genetically at-risk children was safe, but was not associated with an immune response as predefined in the trial primary outcome. Exploratory analyses suggested that antibody responses to oral insulin may occur in children with a susceptible INS genotype, and that inflammatory episodes may promote the activation of insulin-responsive T cells. TRIAL REGISTRATION: Clinicaltrials.gov NCT02547519 FUNDING: The main funding source was the German Center for Diabetes Research (DZD e.V.).

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.

Antigen-reactive regulatory T cells can be expanded in vitro with monocytes and anti-CD28 and anti-CD154 antibodies.

BACKGROUND: In recent years, therapies with CD4+CD25highFoxP3+ regulatory T cells (Tregs) have been successfully tested in many clinical trials. The important issue regarding the use of this treatment in autoimmune conditions remains the specificity toward particular antigen, as because of epitope spread, there are usually multiple causative autoantigens to be regulated in such conditions. METHODS: Here we show a method of generation of Tregs enriched with antigen-reactive clones that potentially covers the majority of such autoantigens. In our research, Tregs were expanded with anti-CD28 and anti-CD154 antibodies and autologous monocytes and loaded with a model peptide, such as whole insulin or insulin ß chain peptide 9-23. The cells were then sorted into cells recognizing the presented antigen. The reactivity was verified with functional assays in which Tregs suppressed proliferation or interferon gamma production of autologous effector T cells (polyclonal and antigen-specific) used as responders challenged with the model peptide. Finally, we analyzed clonotype distribution and TRAV gene usage in the specific Tregs. RESULTS: Altogether, the applied technique had a good yield and allowed us to obtain a Treg product enriched with a specific subset, as confirmed in the functional tests. The product consisted of many clones; nevertheless, the content of these clones was different from that found in polyclonal or unspecific Tregs. CONCLUSIONS: The presented technique might be used to generate populations of Tregs enriched with cells reactive to any given peptide, which can be used as a cellular therapy medicinal product in antigen-targeted therapies.

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.

Cytoplasmic ends of tetraspanin 7 harbour epitopes recognised by autoantibodies in type 1 diabetes.

AIMS/HYPOTHESIS: The beta cell protein tetraspanin 7 is a target of autoantibodies in individuals with type 1 diabetes. The aim of this study was to identify autoantibody epitope-containing regions and key residues for autoantibody binding. METHODS: Autoantibody epitope regions were identified by immunoprecipitation of luciferase-tagged single or multiple tetraspanin 7 domains using tetraspanin 7 antibody-positive sera. Subsequently, amino acids (AAs) relevant for autoantibody binding were identified by single AA mutations. RESULTS: In tetraspanin 7 antibody-positive sera, antibody binding was most frequent to tetraspanin 7 proteins that contained the NH2-terminal cytoplasmic domain 1 (C1; up to 39%) or COOH-terminal C3 (up to 22%). Binding to C3 was more frequent when the domain was expressed along with the flanking transmembrane domain, suggesting that conformation is likely to be important. Binding to external domains was not observed. Single AA mutations of C3 identified residues Y246, E247 and R239 as critical for COOH-terminal binding of 9/10, 10/10 and 8/10 sera tested, respectively. Mutation of cysteines adjacent to the transmembrane domain at either residues C235 or C236 resulted in both decreased (8/178 and 15/178 individuals, respectively; >twofold decrease) and increased (30/178 and 13/178 individuals, respectively; >twofold increase) binding in participant sera vs wild-type protein. CONCLUSIONS/INTERPRETATION: We hypothesise that conformation and, potentially, modification of protein terminal ends of tetraspanin 7 may be important for autoantibody binding in type 1 diabetes.

Tonic Signaling and Its Effects on Lymphopoiesis of CAR-Armed Hematopoietic Stem and Progenitor Cells.

Long-term survival of adoptively transferred chimeric Ag receptor (CAR) T cells is often limited. Transplantation of hematopoietic stem cells (HSCs) transduced to express CARs could help to overcome this problem as CAR-armed HSCs can continuously deliver CAR+ multicell lineages (e.g., T cells, NK cells). In dependence on the CAR construct, a variable extent of tonic signaling in CAR T cells was reported; thus, effects of CAR-mediated tonic signaling on the hematopoiesis of CAR-armed HSCs is unclear. To assess the effects of tonic signaling, two CAR constructs were established and analyzed 1) a signaling CAR inducing a solid Ag-independent tonic signaling termed CAR-28/ζ and 2) a nonstimulating control CAR construct lacking intracellular signaling domains termed CAR-Stop. Bone marrow cells from immunocompetent mice were isolated, purified for HSC-containing Lin-cKit+ cells or the Lin-cKit+ Sca-1+ subpopulation (Lin-Sca-1+cKit+), and transduced with both CAR constructs. Subsequently, modified bone marrow cells were transferred into irradiated mice, in which they successfully engrafted and differentiated into hematopoietic progenitors. HSCs expressing the CAR-Stop sustained normal hematopoiesis. In contrast, expression of the CAR-28/ζ led to elimination of mature CAR+ T and B cells, suggesting that the CAR-mediated tonic signaling mimics autorecognition via the newly recombined immune receptors in the developing lymphocytes.

T-cell receptor-α repertoire of CD8+ T cells following allogeneic stem cell transplantation using next-generation sequencing.

Alloreactivity or opportunistic infections following allogeneic stem cell transplantation are difficult to predict and contribute to post-transplantation mortality. How these immune reactions result in changes to the T-cell receptor repertoire remains largely unknown. Using next-generation sequencing, the T-cell receptor alpha (TRα) repertoire of naïve and memory CD8+ T cells from 25 patients who had received different forms of allogeneic transplantation was analyzed. In parallel, reconstitution of the CD8+/CD4+ T-cell subsets was mapped using flow cytometry. When comparing the influence of anti-T-cell therapy, a delay in the reconstitution of the naïve CD8+ T-cell repertoire was observed in patients who received in vivo T-cell depletion using antithymocyte globulin or post-transplantation cyclophosphamide in case of haploidentical transplantation. Sequencing of the TRα identified a repertoire consisting of more dominant clonotypes (>1% of reads) in these patients at 6 and 18 months post transplantation. When comparing donor and recipient, approximately 50% and approximately 80% of the donors' memory repertoire were later retrieved in the naïve and memory CD8+ T-cell receptor repertoire of the recipients, respectively. Although there was a remarkable expansion of single clones observed in the recipients' memory CD8+ TRα repertoire, no clear association between graft-versus-host disease or cytomegalovirus infection and T-cell receptor diversity was identified. A lower TRα diversity was observed in recipients of a cytomegalovirus-seropositive donor (P=0.014). These findings suggest that CD8+ T-cell reconstitution in transplanted patients is influenced by the use of T-cell depletion or immunosuppression and the donor repertoire.

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.

Machine learning based classification of cells into chronological stages using single-cell transcriptomics.

Age-associated deterioration of cellular physiology leads to pathological conditions. The ability to detect premature aging could provide a window for preventive therapies against age-related diseases. However, the techniques for determining cellular age are limited, as they rely on a limited set of histological markers and lack predictive power. Here, we implement GERAS (GEnetic Reference for Age of Single-cell), a machine learning based framework capable of assigning individual cells to chronological stages based on their transcriptomes. GERAS displays greater than 90% accuracy in classifying the chronological stage of zebrafish and human pancreatic cells. The framework demonstrates robustness against biological and technical noise, as evaluated by its performance on independent samplings of single-cells. Additionally, GERAS determines the impact of differences in calorie intake and BMI on the aging of zebrafish and human pancreatic cells, respectively. We further harness the classification ability of GERAS to identify molecular factors that are potentially associated with the aging of beta-cells. We show that one of these factors, junba, is necessary to maintain the proliferative state of juvenile beta-cells. Our results showcase the applicability of a machine learning framework to classify the chronological stage of heterogeneous cell populations, while enabling detection of candidate genes associated with aging.