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Abstract We recently mapped a genetic susceptibility locus on chromosome 6q22.33 for type 1 diabetes (T1D) diagnosed below the age of 7 years between the PTPRK and thymocyte-selection-associated (THEMIS) genes. As the thymus plays a central role in shaping the T cell repertoire, we aimed to identify the most likely causal genetic factors behind this 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. In a parallel approach to identifying variants that alter transcription factor binding motifs, the same variant disrupted a predicted motif for Rfx7, which is abundantly expressed in the thymus. Chromatin state and RNA sequencing data suggested strong transcription overlapping rs138300818 in fetal thymus, while expression quantitative trait locus and chromatin conformation data associate the insertion with lower THEMIS expression. Extending the analysis to other T1D loci further highlighted rs66733041 affecting the GATA3 transcription factor binding in the AFF3 locus. Taken together, our results support a role for thymic THEMIS gene expression and the rs138300818 variant in promoting the development of early-onset T1D.

Abstract Background 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 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). Methods We developed an immunoassay to measure sSIGLEC-1 in small volumes of plasma/serum from systemic lupus erythematosus (SLE) patients (n = 75) and healthy donors (n = 504). Samples from systemic sclerosis patients (n = 99) were studied as an autoimmune control. We investigated the correlation between sSIGLEC-1 and both monocyte surface SIGLEC-1 and type I interferon-regulated gene (IRG) expression. Associations of sSIGLEC-1 with clinical features were evaluated in an independent cohort of SLE patients (n = 656). Results Plasma concentrations of sSIGLEC-1 strongly correlated with expression of SIGLEC-1 on the surface of blood monocytes and with IRG expression in SLE patients. We found 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 SLE Disease Activity Index clinical score. Conclusions 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 clinical trials.

Abstract Background Autoimmune 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. Results Within 4 h, 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. Conclusions Our systematic experimental framework offers an alternative approach to candidate causal gene identification for variants with cell state-specific functional effects, with achievable sample sizes.

We provide in this paper a detailed characterization of the human peripheral CD4+ CD127lowCD25+ regulatory T cell (Treg) compartment, with a particular emphasis in defining the population expressing higher levels of the IL-6 receptor (IL-6R). We provide a description of the phenotype of this population by assessing both the surface expression by flow cytometry as well as their transcriptional profile and functional features. In addition, we also present functional data describing the responsiveness of these subsets to IL-6 signalling in vitro and to IL-2 in vivo. The data presented in this paper support the research article “Human IL-6RhiTIGIT− CD4+CD127lowCD25+ T cells display potent in vitro suppressive capacity and a distinct Th17 profile” (Ferreira RC et al., 2017; doi: 10.1016/j.clim.2017.03.002) [1].

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.