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Type 1 diabetes (T1D) is caused by a T-cell-mediated destruction of insulin-secreting pancreatic islet β cells. The T1D-predisposing human leukocyte antigen (HLA) class II molecule, DQ8, binds and presents insulin B chain peptides in the thymus producing autoreactive CD4+ T cells1–12. Here, we show that this process is driven by negatively-charged T cell receptor (TCR) complementarity-determining region 3β (CDR3β) sequences interacting with alanine at position 57 of the DQ8 β chain. Since T1D aetiology is linked to gut microbiota dysbiosis13–18, we hypothesized that the commensal proteome contains mimics of the primary insulin B:9-23 epitope that control TCR selection and tolerance. We identified a large set of bacterial proteins with significant similarity to insulin B:9-25, particularly from the transketolase (TKT) superfamily. We isolated a CD4+ TCR with a negatively-charged CDR3β from the pancreas of a DQ8-positive patient that was cross-reactive with one of these TKT peptides and insulin B:9-23. The T1D-protective molecule, DQ6, with the negatively-charged aspartic acid (D) at DQβ57(12,19), showed strong TKT mimotope binding, supporting a role for TKT-specific regulatory T cells in resistance to T1D. We propose that in a DQ8+DQ6− child with a proinflammatory dysbiotic gut microbiota, cross-reactive TKT-insulin B chain peptide T effector cells escape from the thymus and initiate T1D. TKT is a strong candidate because it is highly upregulated during weaning, a key period in T1D aetiology, and hence a prominent target for an autoimmune-prone immune system. Inhibiting gut dysbiosis and improving immune tolerance to TKT and other mimotopes, especially before and during weaning, could be a route to primary prevention of T1D and other common diseases.

We recently mapped a genetic susceptibility locus on chromosome 6q22.33 for type 1 diabetes diagnosed below age of 7 years near the gene Protein tyrosine phosphatase receptor type K (PTPRK) and the thymocyte selection associated gene (THEMIS). As the thymus plays a central role in shaping the T cell repertoire, we aimed to identify the most likely causal genetic factors behind the association using thymocyte genomic data. In four thymocyte populations we identified 253 DNA sequence motifs underlying histone modifications. The G insertion allele of rs138300818, associated with protection from diabetes, created thymocyte motifs for multiple histone modifications and thymocyte types. The insertion also disrupted a predicted RFX5/7 transcription factor binding site. RFX7 is abundantly expressed in thymus. Chromatin state and RNA sequencing data suggested strong transcription overlapping rs138300818 in fetal thymus, while eQTL and chromatin conformation data indicated that the rs138300818 insertion is associated with lower THEMIS expression. Taken together, our results support a role for thymic THEMIS gene expression and the rs138300818 variant in promoting the development and diagnosis of type 1 diabetes at an earlier age.

Type 1 diabetes (T1D) is a common autoimmune disorder characterized by the destruction of insulin-secreting pancreatic β cells [1], in which polymorphism of the human leukocyte antigen (HLA) class II region is the major genetic risk factor [2, 3, 4]. However, how variation in class II molecules alters T1D risk remains a longstanding question. Here we show how T1D risk due to HLA class II haplotype combinations [5] correlates with the frequency of negatively charged sequences in the CDR3β region of CD4+ T cell receptor (TCR) repertoires purified from peripheral blood. These sequences are known to be common in receptors that bind insulin B:9–23 [6], the primary autoantigen in T1D. We also show the same effect in circulating activated CD4+ T cells from newly-diagnosed T1D cases, and in islet-infiltrating T cells from patients with active T1D. Furthermore, we demonstrate that the proportion of insulin-reactive CD4+ T cells present in islets is predicted by the frequency of these negatively charged CDR3β amino acid sequences. Our results suggest diagnostic uses of T cell repertoire profiling in early detection of insulin autoimmunity, and inform ongoing efforts to improve tolerance induction to insulin and prevention of T1D [7].

How organisms achieve sustained peripheral tolerance throughout their lifetime, a correct immune discrimination between self and non-self, remains poorly understood. Host-microbiome interactions carry fundamental information that facilitates this process. We hypothesize that commensal microbes are under evolutionary pressure to develop epitopes that, when presented along with other antigens from their own bacterial community, lead to an overall tolerogenic self classification by the host immune system. Hosts, which have co-evolved with commensals, may rely on mimotopes, bacterial epitopes that are indistinguishable from key self epitopes, as a homeostatic feedback mechanism to establish and maintain tolerance. Using a probabilistic sequence model of peptide mimicry, we show that the gut microbiome contains a set of genes that are likely to trigger identical immune responses to insulin B 9–25, a widely distributed self epitope across tissues and the primary autoantigen in type 1 diabetes. Similarities in the antigen receptor sequences determined from CD4 T cells reacting to insulin epitopes and mimotopes provide experimental evidence for mimicry. All predicted high posterior probability mimotopes belong to the transketolase superfamily, an enzyme that allows efficient harvest of commensal-derived sugar polymers and dietary fibre, an advantage during host colonisation. Microbial transketolase upregulation during infant weaning coincides in time with the peak in autoantibody development against insulin. Abundance changes in bacterial genera that carry these mimotopes have also been observed to precede disease diagnosis. Our findings suggest gut dysbiosis followed by immune response to insulin mimotopes as a primary cause of type 1 diabetes, and may contribute towards unraveling similar causal patterns in a wide variety of disorders.

The molecular heterogeneity of autoimmune and inflammatory diseases has been one of the main obstacles to the development of safe and specific therapeutic options. Here we have evaluated the diagnostic and clinical value of a robust, inexpensive, immunoassay detecting the circulating soluble form of the monocyte-specific surface receptor sialic acid binding Ig-like lectin 1 (sSIGLEC-1).We developed an immunoassay to measure sSIGLEC-1 in small volumes of plasma/serum from systemic lupus erythematosus (SLE) patients and healthy donors. Plasma concentrations of sSIGLEC-1 strongly correlated with expression of SIGLEC-1 on the surface of blood monocytes and with type I interferon (IFN)-regulated gene (IRG) expression in SLE patients. In addition, we identified marked ancestry-related differences in sSIGLEC-1 concentrations in SLE patients, with patients of non-European ancestry showing higher levels compared to patients of European ancestry. Higher sSIGLEC-1 concentrations were associated with lower serum complement component 3 and increased frequency of renal complications in European patients, but not with the SLEDAI clinical score.Our sSIGLEC-1 immunoassay provides a specific and easily-assayed marker for monocyte-macrophage activation, and interferonopathy in SLE and other diseases. Further studies can extend its clinical associations and its potential use to stratify patients and as a secondary endpoint in trials.

BackgroundAutoimmune disease-associated variants are preferentially found in regulatory regions in immune cells, particularly CD4+ T cells. Linking such regulatory regions to gene promoters in disease-relevant cell contexts facilitates identification of candidate disease genes.ResultsWithin four hours, activation of CD4+ T cells invokes changes in histone modifications and enhancer RNA transcription that correspond to altered expression of the interacting genes identified by promoter capture Hi-C. By integrating promoter capture Hi-C data with genetic associations for five autoimmune diseases we prioritised 245 candidate genes with a median distance from peak signal to prioritised gene of 153 kb. Just under half (108/245) prioritised genes related to activation-sensitive interactions. This included IL2RA, where allele-specific expression analyses were consistent with its interaction-mediated regulation, illustrating the utility of the approach.ConclusionsOur systematic experimental framework offers an alternative approach to candidate causal gene identification for variants with cell state-specific functional effects, with achievable sample sizes.

The adaptive immune system utilizes multiple mechanisms linked to innate immune cell functions to respond appropriately to pathogens and commensals. Here we discover further aspects of this connectivity by demonstrating that naïve T cells as they emerge from the thymus (recent thymic emigrants, RTEs) express complement receptors (CR1 and CR2), the bacterial pathogen recognition receptor TLR1 and an enzyme that deactivates bacterial lipopolysaccharide (AOAH) and following activation secrete the anti-microbial cytokine IL-8. CR2+ naïve T cells also express a selection of genes associated with tissue migration, consistent with the hypothesis that following emigration from the thymus RTEs seed peripheral compartments where some pursue their anti-microbial potential by becoming IL-8-producing CR2+ memory cells while others undergo homeostatic expansion. CR2+ naïve and memory cells are abundant in children but decrease with age, coinciding with the involution of the thymus. The ability of CR2, which is also a receptor for Epstein-Barr Virus (EBV), to identify recent thymic emigrants will facilitate assessment of thymic function during aging and aid investigations of multiple clinical areas including the occurrence of T cell lymphomas caused by EBV.

Identification of candidate causal variants in regions associated with risk of common diseases is complicated by linkage disequilibrium (LD) and multiple association signals. Nonetheless, accurate maps of these variants are needed, both to fully exploit detailed cell specific chromatin annotation data to highlight disease causal mechanisms and cells, and for design of the functional studies that will ultimately be required to confirm causal mechanisms. We adapted a Bayesian evolutionary stochastic search algorithm to the fine mapping problem, and demonstrated its improved performance over conventional stepwise and regularised regression through simulation studies. We then applied it to fine map the established multiple sclerosis (MS) and type 1 diabetes (T1D) associations in the IL-2RA (CD25) gene region. For T1D, both stepwise and stochastic search approaches identified four T1D association signals, with the major effect tagged by the single nucleotide polymorphism, rs12722496. In contrast, for MS, the stochastic search found two distinct competing models: a single candidate causal variant, tagged by rs2104286 and reported previously using stepwise analysis; and a more complex model with two association signals, one of which was tagged by the major T1D associated rs12722496 and the other by rs56382813. There is low to moderate LD between rs2104286 and both rs12722496 and rs56382813 (r2 ≃ 0:3) and our two SNP model could not be recovered through a forward stepwise search after conditioning on rs2104286. Both signals in the two variant model for MS affect CD25 expression on distinct subpopulations of CD4+ T cells, which are key cells in the autoimmune process. The results support a shared causal variant for T1D and MS. Our study illustrates the benefit of using a purposely designed model search strategy for fine mapping and the advantage of combining disease and protein expression data., Author Summary Genetic association studies have identified many DNA sequence variants that associate with disease risk. By exploiting the known correlation that exists between neighbouring variants in the genome, inference can be extended beyond those individual variants tested to identify sets within which a causal variant is likely to reside. However, this correlation, particularly in the presence of multiple disease causing variants in relative proximity, makes disentangling the specific causal variants difficult. Statistical approaches to this fine mapping problem have traditionally taken a stepwise search approach, beginning with the most associated variant in a region, then iteratively attempting to find additional associated variants. We adapted a stochastic search approach that avoids this stepwise process and is explicitly designed for dealing with highly correlated predictors to the fine mapping problem. We showed in simulated data that it outperforms its stepwise counterpart and other variable selection strategies such as the lasso. We applied our approach to understand the association of two immune-mediated diseases to a region on chromosome 10p15. We identified a model for multiple sclerosis containing two variants, neither of which was found through a stepwise search, and functionally linked both of these to the neighbouring candidate gene, IL2RA, in independent data. Our approach can be used to aid fine mapping of other disease-associated regions, which is critical for design of functional follow-up studies required to understand the mechanisms through which genetic variants influence disease.