Thymocyte regulatory variant alters transcription factor binding and protects from type 1 diabetes in infants.

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.

Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus.

The severe acute respiratory syndrome coronavirus 2 (SARS­CoV­2) disease (COVID-19) pandemic has caused millions of deaths worldwide. Genome-wide association studies identified the 3p21.31 region as conferring a twofold increased risk of respiratory failure. Here, using a combined multiomics and machine learning approach, we identify the gain-of-function risk A allele of an SNP, rs17713054G>A, as a probable causative variant. We show with chromosome conformation capture and gene-expression analysis that the rs17713054-affected enhancer upregulates the interacting gene, leucine zipper transcription factor like 1 (LZTFL1). Selective spatial transcriptomic analysis of lung biopsies from patients with COVID-19 shows the presence of signals associated with epithelial-mesenchymal transition (EMT), a viral response pathway that is regulated by LZTFL1. We conclude that pulmonary epithelial cells undergoing EMT, rather than immune cells, are likely responsible for the 3p21.31-associated risk. Since the 3p21.31 effect is conferred by a gain-of-function, LZTFL1 may represent a therapeutic target.

Using de novo assembly to identify structural variation of eight complex immune system gene regions.

Driven by the necessity to survive environmental pathogens, the human immune system has evolved exceptional diversity and plasticity, to which several factors contribute including inheritable structural polymorphism of the underlying genes. Characterizing this variation is challenging due to the complexity of these loci, which contain extensive regions of paralogy, segmental duplication and high copy-number repeats, but recent progress in long-read sequencing and optical mapping techniques suggests this problem may now be tractable. Here we assess this by using long-read sequencing platforms from PacBio and Oxford Nanopore, supplemented with short-read sequencing and Bionano optical mapping, to sequence DNA extracted from CD14+ monocytes and peripheral blood mononuclear cells from a single European individual identified as HV31. We use this data to build a de novo assembly of eight genomic regions encoding four key components of the immune system, namely the human leukocyte antigen, immunoglobulins, T cell receptors, and killer-cell immunoglobulin-like receptors. Validation of our assembly using k-mer based and alignment approaches suggests that it has high accuracy, with estimated base-level error rates below 1 in 10 kb, although we identify a small number of remaining structural errors. We use the assembly to identify heterozygous and homozygous structural variation in comparison to GRCh38. Despite analyzing only a single individual, we find multiple large structural variants affecting core genes at all three immunoglobulin regions and at two of the three T cell receptor regions. Several of these variants are not accurately callable using current algorithms, implying that further methodological improvements are needed. Our results demonstrate that assessing haplotype variation in these regions is possible given sufficiently accurate long-read and associated data. Continued reductions in the cost of these technologies will enable application of these methods to larger samples and provide a broader catalogue of germline structural variation at these loci, an important step toward making these regions accessible to large-scale genetic association studies.

Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes.

We report the largest and most diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 78 genome-wide-significant (P < 5 × 10-8) regions, including 36 that are new. We define credible sets of T1D-associated variants and show that they are enriched in immune-cell accessible chromatin, particularly CD4+ effector T cells. Using chromatin-accessibility profiling of CD4+ T cells from 115 individuals, we map chromatin-accessibility quantitative trait loci and identify five regions where T1D risk variants co-localize with chromatin-accessibility quantitative trait loci. We highlight rs72928038 in BACH2 as a candidate causal T1D variant leading to decreased enhancer accessibility and BACH2 expression in T cells. Finally, we prioritize potential drug targets by integrating genetic evidence, functional genomic maps and immune protein-protein interactions, identifying 12 genes implicated in T1D that have been targeted in clinical trials for autoimmune diseases. These findings provide an expanded genomic landscape for T1D.

Publisher Correction: Whole-genome sequencing of a sporadic primary immunodeficiency cohort.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Whole-genome sequencing of a sporadic primary immunodeficiency cohort.

Primary immunodeficiency (PID) is characterized by recurrent and often life-threatening infections, autoimmunity and cancer, and it poses major diagnostic and therapeutic challenges. Although the most severe forms of PID are identified in early childhood, most patients present in adulthood, typically with no apparent family history and a variable clinical phenotype of widespread immune dysregulation: about 25% of patients have autoimmune disease, allergy is prevalent and up to 10% develop lymphoid malignancies1-3. Consequently, in sporadic (or non-familial) PID genetic diagnosis is difficult and the role of genetics is not well defined. Here we address these challenges by performing whole-genome sequencing in a large PID cohort of 1,318 participants. An analysis of the coding regions of the genome in 886 index cases of PID found that disease-causing mutations in known genes that are implicated in monogenic PID occurred in 10.3% of these patients, and a Bayesian approach (BeviMed4) identified multiple new candidate PID-associated genes, including IVNS1ABP. We also examined the noncoding genome, and found deletions in regulatory regions that contribute to disease causation. In addition, we used a genome-wide association study to identify loci that are associated with PID, and found evidence for the colocalization of-and interplay between-novel high-penetrance monogenic variants and common variants (at the PTPN2 and SOCS1 loci). This begins to explain the contribution of common variants to the variable penetrance and phenotypic complexity that are observed in PID. Thus, using a cohort-based whole-genome-sequencing approach in the diagnosis of PID can increase diagnostic yield and further our understanding of the key pathways that influence immune responsiveness in humans.

Discovery of CD80 and CD86 as recent activation markers on regulatory T cells by protein-RNA single-cell analysis.

BACKGROUND: Traditionally, the transcriptomic and proteomic characterisation of CD4+ T cells at the single-cell level has been performed by two largely exclusive types of technologies: single-cell RNA sequencing (scRNA-seq) and antibody-based cytometry. Here, we present a multi-omics approach allowing the simultaneous targeted quantification of mRNA and protein expression in single cells and investigate its performance to dissect the heterogeneity of human immune cell populations. METHODS: We have quantified the single-cell expression of 397 genes at the mRNA level and up to 68 proteins using oligo-conjugated antibodies (AbSeq) in 43,656 primary CD4+ T cells isolated from the blood and 31,907 CD45+ cells isolated from the blood and matched duodenal biopsies. We explored the sensitivity of this targeted scRNA-seq approach to dissect the heterogeneity of human immune cell populations and identify trajectories of functional T cell differentiation. RESULTS: We provide a high-resolution map of human primary CD4+ T cells and identify precise trajectories of Th1, Th17 and regulatory T cell (Treg) differentiation in the blood and tissue. The sensitivity provided by this multi-omics approach identified the expression of the B7 molecules CD80 and CD86 on the surface of CD4+ Tregs, and we further demonstrated that B7 expression has the potential to identify recently activated T cells in circulation. Moreover, we identified a rare subset of CCR9+ T cells in the blood with tissue-homing properties and expression of several immune checkpoint molecules, suggestive of a regulatory function. CONCLUSIONS: The transcriptomic and proteomic hybrid technology described in this study provides a cost-effective solution to dissect the heterogeneity of immune cell populations at extremely high resolution. Unexpectedly, CD80 and CD86, normally expressed on antigen-presenting cells, were detected on a subset of activated Tregs, indicating a role for these co-stimulatory molecules in regulating the dynamics of CD4+ T cell responses.

Author Correction: Approaches and advances in the genetic causes of autoimmune disease and their implications.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genetic Variants Predisposing Most Strongly to Type 1 Diabetes Diagnosed Under Age 7 Years Lie Near Candidate Genes That Function in the Immune System and in Pancreatic ß-Cells.

OBJECTIVE: Immunohistological analyses of pancreata from patients with type 1 diabetes suggest distinct autoimmune islet ß-cell pathology between those diagnosed at <7 years (<7 group) and those diagnosed at age ≥13 years (≥13 group), with both B- and T-lymphocyte islet inflammation common in children in the <7 group, whereas B cells are rare in the ≥13 group. Based on these observations, we sought to identify differences in genetic susceptibility between these prespecified age-at-diagnosis groups to inform on the etiology of the most aggressive form of type 1 diabetes that initiates in the first years of life. RESEARCH DESIGN AND METHODS: Using multinomial logistic regression models, we tested if known type 1 diabetes loci (17 within the HLA and 55 non-HLA loci) had significantly stronger effect sizes in the <7 group compared with the ≥13 group, using genotype data from 27,071 individuals (18,485 control subjects and 3,121 case subjects diagnosed at <7 years, 3,757 at 7-13 years, and 1,708 at ≥13 years). RESULTS: Six HLA haplotypes/classical alleles and six non-HLA regions, one of which functions specifically in ß-cells (GLIS3) and the other five likely affecting key T-cell (IL2RA, IL10, IKZF3, and THEMIS), thymus (THEMIS), and B-cell development/functions (IKZF3 and IL10) or in both immune and ß-cells (CTSH), showed evidence for stronger effects in the <7 group. CONCLUSIONS: A subset of type 1 diabetes-associated variants are more prevalent in children diagnosed under the age of 7 years and are near candidate genes that act in both pancreatic ß- and immune cells.

Publisher Correction: Approaches and advances in the genetic causes of autoimmune disease and their implications.

In the version of this article initially published, the bibliographic information for reference 2 was incorrect in the reference list, and reference 2 was cited incorrectly at the end of the second sentence in the second paragraph ("...were identified2."). The correct reference 2 is as follows: "Kong, A. et al. The nature of nurture: Effects of parental genotypes. Science 359, 424-428 (2018)." The reference that should be cited at the end of the aforementioned sentence, which should be numbered '5' ("...were identified5."), is as follows: "Okada, Y. et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 506, 376-381 (2014)." All subsequent references (5-161) should be renumbered accordingly (6-162) in the list and text. Also, several of the gene symbols in Table 2 were formatted incorrectly (without commas); the correct gene symbols are as follows: column 3 row 13, RBM17, IL2RA; column 3 row 30, DEXI, CLEC16A; column 3 row 39, UBASH3A, ICOSLG; column 4 row 15, PTEN, KLLN; column 4 row 21, CLEC7A, CLEC9A; and column 5 rows 7-9, AL391559.1, ENSG00000238747, RP11-63K6.7, RP3-512E2.2. The errors have been corrected in the HTML and PDF version of the article.

Approaches and advances in the genetic causes of autoimmune disease and their implications.

Genome-wide association studies are transformative in revealing the polygenetic basis of common diseases, with autoimmune diseases leading the charge. Although the field is just over 10 years old, advances in understanding the underlying mechanistic pathways of these conditions, which result from a dense multifactorial blend of genetic, developmental and environmental factors, have already been informative, including insights into therapeutic possibilities. Nevertheless, the challenge of identifying the actual causal genes and pathways and their biological effects on altering disease risk remains for many identified susceptibility regions. It is this fundamental knowledge that will underpin the revolution in patient stratification, the discovery of therapeutic targets and clinical trial design in the next 20 years. Here we outline recent advances in analytical and phenotyping approaches and the emergence of large cohorts with standardized gene-expression data and other phenotypic data that are fueling a bounty of discovery and improved understanding of human physiology.

Chromosome contacts in activated T cells identify autoimmune disease candidate genes.

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.

Capturing the systemic immune signature of a norovirus infection: an n-of-1 case study within a clinical trial.

BACKGROUND: The infection of a participant with norovirus during the adaptive study of interleukin-2 dose on regulatory T cells in type 1 diabetes (DILT1D) allowed a detailed insight into the cellular and cytokine immune responses to this prevalent gastrointestinal pathogen. METHODS: Serial blood, serum and peripheral blood mononuclear cell (PBMC) samples were collected pre-, and post-development of the infection. To differentiate between the immune response to norovirus and to control for the administration of a single dose of aldesleukin (recombinant interleukin-2, rIL-2) alone, samples from five non-infected participants administered similar doses were analysed in parallel. RESULTS: Norovirus infection was self-limited and resolved within 24 hours, with the subsequent development of anti-norovirus antibodies. Serum pro- and anti-inflammatory cytokine levels, including IL-10, peaked during the symptomatic period of infection, coincident with increased frequencies of monocytes and neutrophils. At the same time, the frequency of regulatory CD4 + T cell (Treg), effector T cell (Teff) CD4 + and CD8 + subsets were dynamically reduced, rebounding to baseline levels or above at the next sampling point 24 hours later.  NK cells and NKT cells transiently increased CD69 expression and classical monocytes expressed increased levels of CD40, HLA-DR and SIGLEC-1, biomarkers of an interferon response. We also observed activation and mobilisation of Teffs, where increased frequencies of CD69 + and Ki-67 + effector memory Teffs were followed by the emergence of memory CD8 + Teff expressing the mucosal tissue homing markers CD103 and ß7 integrin. Treg responses were coincident with the innate cell, Teff and cytokine response. Key Treg molecules FOXP3, CTLA-4, and CD25 were upregulated following infection, alongside an increase in frequency of Tregs with the capacity to home to tissues. CONCLUSIONS: The results illustrate the innate, adaptive and counter-regulatory immune responses to norovirus infection. Low-dose IL-2 administration induces many of the Treg responses observed during infection.

Neonatal and adult recent thymic emigrants produce IL-8 and express complement receptors CR1 and CR2.

The maintenance of peripheral naive T lymphocytes in humans is dependent on their homeostatic division, not continuing emigration from the thymus, which undergoes involution with age. However, postthymic maintenance of naive T cells is still poorly understood. Previously we reported that recent thymic emigrants (RTEs) are contained in CD31+CD25- naive T cells as defined by their levels of signal joint T cell receptor rearrangement excision circles (sjTRECs). Here, by differential gene expression analysis followed by protein expression and functional studies, we define that the naive T cells having divided the least since thymic emigration express complement receptors (CR1 and CR2) known to bind complement C3b- and C3d-decorated microbial products and, following activation, produce IL-8 (CXCL8), a major chemoattractant for neutrophils in bacterial defense. We also observed an IL-8-producing memory T cell subpopulation coexpressing CR1 and CR2 and with a gene expression signature resembling that of RTEs. The functions of CR1 and CR2 on T cells remain to be determined, but we note that CR2 is the receptor for Epstein-Barr virus, which is a cause of T cell lymphomas and a candidate environmental factor in autoimmune disease.

Cells with Treg-specific FOXP3 demethylation but low CD25 are prevalent in autoimmunity.

Identification of alterations in the cellular composition of the human immune system is key to understanding the autoimmune process. Recently, a subset of FOXP3+ cells with low CD25 expression was found to be increased in peripheral blood from systemic lupus erythematosus (SLE) patients, although its functional significance remains controversial. Here we find in comparisons with healthy donors that the frequency of FOXP3+ cells within CD127lowCD25low CD4+ T cells (here defined as CD25lowFOXP3+ T cells) is increased in patients affected by autoimmune disease of varying severity, from combined immunodeficiency with active autoimmunity, SLE to type 1 diabetes. We show that CD25lowFOXP3+ T cells share phenotypic features resembling conventional CD127lowCD25highFOXP3+ Tregs, including demethylation of the Treg-specific epigenetic control region in FOXP3, HELIOS expression, and lack of IL-2 production. As compared to conventional Tregs, more CD25lowFOXP3+HELIOS+ T cells are in cell cycle (33.0% vs 20.7% Ki-67+; P = 1.3 × 10-9) and express the late-stage inhibitory receptor PD-1 (67.2% vs 35.5%; P = 4.0 × 10-18), while having reduced expression of the early-stage inhibitory receptor CTLA-4, as well as other Treg markers, such as FOXP3 and CD15s. The number of CD25lowFOXP3+ T cells is correlated (P = 3.1 × 10-7) with the proportion of CD25highFOXP3+ T cells in cell cycle (Ki-67+). These findings suggest that CD25lowFOXP3+ T cells represent a subset of Tregs that are derived from CD25highFOXP3+ T cells, and are a peripheral marker of recent Treg expansion in response to an autoimmune reaction in tissues.

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters.

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.

Regulatory T Cell Responses in Participants with Type 1 Diabetes after a Single Dose of Interleukin-2: A Non-Randomised, Open Label, Adaptive Dose-Finding Trial.

BACKGROUND: Interleukin-2 (IL-2) has an essential role in the expansion and function of CD4+ regulatory T cells (Tregs). Tregs reduce tissue damage by limiting the immune response following infection and regulate autoreactive CD4+ effector T cells (Teffs) to prevent autoimmune diseases, such as type 1 diabetes (T1D). Genetic susceptibility to T1D causes alterations in the IL-2 pathway, a finding that supports Tregs as a cellular therapeutic target. Aldesleukin (Proleukin; recombinant human IL-2), which is administered at high doses to activate the immune system in cancer immunotherapy, is now being repositioned to treat inflammatory and autoimmune disorders at lower doses by targeting Tregs. METHODS AND FINDINGS: To define the aldesleukin dose response for Tregs and to find doses that increase Tregs physiologically for treatment of T1D, a statistical and systematic approach was taken by analysing the pharmacokinetics and pharmacodynamics of single doses of subcutaneous aldesleukin in the Adaptive Study of IL-2 Dose on Regulatory T Cells in Type 1 Diabetes (DILT1D), a single centre, non-randomised, open label, adaptive dose-finding trial with 40 adult participants with recently diagnosed T1D. The primary endpoint was the maximum percentage increase in Tregs (defined as CD3+CD4+CD25highCD127low) from the baseline frequency in each participant measured over the 7 d following treatment. There was an initial learning phase with five pairs of participants, each pair receiving one of five pre-assigned single doses from 0.04 × 106 to 1.5 × 106 IU/m2, in order to model the dose-response curve. Results from each participant were then incorporated into interim statistical modelling to target the two doses most likely to induce 10% and 20% increases in Treg frequencies. Primary analysis of the evaluable population (n = 39) found that the optimal doses of aldesleukin to induce 10% and 20% increases in Tregs were 0.101 × 106 IU/m2 (standard error [SE] = 0.078, 95% CI = -0.052, 0.254) and 0.497 × 106 IU/m2 (SE = 0.092, 95% CI = 0.316, 0.678), respectively. On analysis of secondary outcomes, using a highly sensitive IL-2 assay, the observed plasma concentrations of the drug at 90 min exceeded the hypothetical Treg-specific therapeutic window determined in vitro (0.015-0.24 IU/ml), even at the lowest doses (0.040 × 106 and 0.045 × 106 IU/m2) administered. A rapid decrease in Treg frequency in the circulation was observed at 90 min and at day 1, which was dose dependent (mean decrease 11.6%, SE = 2.3%, range 10.0%-48.2%, n = 37), rebounding at day 2 and increasing to frequencies above baseline over 7 d. Teffs, natural killer cells, and eosinophils also responded, with their frequencies rapidly and dose-dependently decreased in the blood, then returning to, or exceeding, pretreatment levels. Furthermore, there was a dose-dependent down modulation of one of the two signalling subunits of the IL-2 receptor, the ß chain (CD122) (mean decrease = 58.0%, SE = 2.8%, range 9.8%-85.5%, n = 33), on Tregs and a reduction in their sensitivity to aldesleukin at 90 min and day 1 and 2 post-treatment. Due to blood volume requirements as well as ethical and practical considerations, the study was limited to adults and to analysis of peripheral blood only. CONCLUSIONS: The DILT1D trial results, most notably the early altered trafficking and desensitisation of Tregs induced by a single ultra-low dose of aldesleukin that resolves within 2-3 d, inform the design of the next trial to determine a repeat dosing regimen aimed at establishing a steady-state Treg frequency increase of 20%-50%, with the eventual goal of preventing T1D. TRIAL REGISTRATION: ISRCTN Registry ISRCTN27852285; ClinicalTrials.gov NCT01827735.

Natural Variation in Interleukin-2 Sensitivity Influences Regulatory T-Cell Frequency and Function in Individuals With Long-standing Type 1 Diabetes.

Defective immune homeostasis in the balance between FOXP3+ regulatory T cells (Tregs) and effector T cells is a likely contributing factor in the loss of self-tolerance observed in type 1 diabetes (T1D). Given the importance of interleukin-2 (IL-2) signaling in the generation and function of Tregs, observations that polymorphisms in genes in the IL-2 pathway associate with T1D and that some individuals with T1D exhibit reduced IL-2 signaling indicate that impairment of this pathway may play a role in Treg dysfunction and the pathogenesis of T1D. Here, we have examined IL-2 sensitivity in CD4+ T-cell subsets in 70 individuals with long-standing T1D, allowing us to investigate the effect of low IL-2 sensitivity on Treg frequency and function. IL-2 responsiveness, measured by STAT5a phosphorylation, was a very stable phenotype within individuals but exhibited considerable interindividual variation and was influenced by T1D-associated PTPN2 gene polymorphisms. Tregs from individuals with lower IL-2 signaling were reduced in frequency, were less able to maintain expression of FOXP3 under limiting concentrations of IL-2, and displayed reduced suppressor function. These results suggest that reduced IL-2 signaling may be used to identify patients with the highest Treg dysfunction and who may benefit most from IL-2 immunotherapy.

Dissection of a Complex Disease Susceptibility Region Using a Bayesian Stochastic Search Approach to Fine Mapping.

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.