Biology subjects

Todd, J. A.

Publications and source records attributed to Todd, J. A..

7 recordsLinked to original sources

bioRxiv2018

Dexi disruption depletes gut microbial metabolites and accelerates autoimmune diabetes

Non-coding genetic variants in the CLEC16A gene on human chromosome 16p13.13 are associated with risk of autoimmune diseases, including type 1 diabetes and multiple sclerosis. In this region, we previously identified DEXI, a candidate causal gene of unknown function, which alters the risk of type 1 diabetes, where the T1D predisposing allele is associated with lower DEXI expression. Here, we demonstrate by CRISPR mutagenesis in vivo and deep phenotyping that disrupted Dexi expression accelerates diabetes in the non-obese diabetic (NOD) mouse, a spontaneous model of autoimmune pancreatic beta-cell destruction. Mutant mice have increased serum IgM and IgA concentrations compared to wild-type NOD mice, as well as changes in both the gut microbiome and molecular metabolites associated with microbial metabolism. These findings suggest that the mechanism by which DEXI alters diabetes risk involves the composition and function of the microbiome and its impact on host metabolites. Such metabolites, including short chain fatty acids such as butyrate, have been shown to alter the activity of the immune cells involved in beta-cell destruction and susceptibility of the beta cells to autoimmune attack.\n\nOne Sentence Summary: Disruption of the Dexi gene leads to accelerated diabetes in the non-obese diabetic (NOD) mouse, accompanied by changes in serum immunoglobulins, gut microbiome and microbial metabolites.

genetics↗

bioRxiv2017

Targeting regulatory T cells with Interleukin-2 treatment in type 1 diabetes: a response-adaptive, non-randomised, open-label trial of repeat doses of Aldesleukin (DILfrequency)

BackgroundType 1 diabetes (T1D) results from loss of immune regulation leading to the development of autoimmunity to pancreatic beta-cells, involving autoreactive T effector cells (Teffs). Regulatory T cells (Tregs), that prevent autoimmunity, require Interleukin-2 (IL-2) for maintenance of immunosuppressive functions and, alterations in the IL-2 pathway predispose to T1D. Using an adaptive trial design we aimed to determine the optimal regimen of aldesleukin (recombinant human IL-2) to physiologically enhance Tregs while limiting expansion of autoreactive Teffs.\n\nMethodsDILfrequency is a single-center, non-randomised, open-label, response-adaptive study of participants aged 18 to 70 years with T1D. The initial learning phase allocated 12 participants to six different predefined dose-frequency regimens. Then, three cohorts of 8 participants were sequentially allocated dose-frequencies, based on repeated interim analyses of all accumulated trial data. The co-primary endpoints were percentage change in Tregs, Teffs and, CD25 ( subunit of the IL-2 receptor) expression by Tregs, from baseline to steady state. Trial registration ISRCTN40319192 and ClinicalTrials.gov (NCT02265809).\n\nFindings115 participants were assessed between November 17th 2014 and May 22nd 2016, 38 participants were enrolled with 36 completing treatment. The optimal regimen to maintain a steady state increase in Tregs of 30% and CD25 expression of 25% without Teff expansion is 0.26 x 106 IU/m2 (95% CI (-0.007 to 0.485)) every 3 days (1.3 to 4.4). Tregs and CD25 were dose-frequency responsive, while Teffs were not. The commonest adverse event was injection site reaction (464/694 events), with a single participant developing transient eosinophilia at the highest dose (0.47 x 106 IU/m2).\n\nInterpretationThis response-adaptive trial defined a well-tolerated aldesleukin regimen that specifically induces Treg expansion that can now be trialled to treat T1D.\n\nFundingSir Jules Thorn Trust, Wellcome, JDRF, SNSF, NIHR

clinical trials↗

bioRxiv2017

Fine-mapping identifies causal variants for RA and T1D in DNASE1L3, SIRPG, MEG3, TNFAIP3 and CD28/CTLA4 loci

We fine-mapped 76 rheumatoid arthritis (RA) and type 1 diabetes (T1D) loci outside of the MHC. After sequencing 799 1kb regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89% of common variants. We fine-mapped1,2 these loci in RA (11,475 cases, 15,870 controls)3, T1D (9,334 cases and 11,111 controls) 4 and combined datasets. We reduced the number of potential causal variants to [≤]5 in 8 RA and 11 T1D loci. We identified causal missense variants in five loci (DNASE1L3, SIRPG, PTPN22, SH2B3 and TYK2) and likely causal non-coding variants in six loci (MEG3, TNFAIP3, CD28/CTLA4, ANKRD55, IL2RA, REL/PUS10). Functional analysis confirmed allele specific binding and differential enhancer activity for three variants: the CD28/CTLA4 rs117701653 SNP, the TNFAIP3 rs35926684 indel, and the MEG3 rs34552516 indel. This study demonstrates the potential for dense genotyping and imputation to pinpoint missense and non-coding causal alleles.

genetics↗

bioRxiv2017

Consequences Of Natural Perturbations In The Human Plasma Proteome

Proteins are the primary functional units of biology and the direct targets of most drugs, yet there is limited knowledge of the genetic factors determining inter-individual variation in protein levels. Here we reveal the genetic architecture of the human plasma proteome, testing 10.6 million DNA variants against levels of 2,994 proteins in 3,301 individuals. We identify 1,927 genetic associations with 1,478 proteins, a 4-fold increase on existing knowledge, including trans associations for 1,104 proteins. To understand consequences of perturbations in plasma protein levels, we introduce an approach that links naturally occurring genetic variation with biological, disease, and drug databases. We provide insights into pathogenesis by uncovering the molecular effects of disease-associated variants. We identify causal roles for protein biomarkers in disease through Mendelian randomization analysis. Our results reveal new drug targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.

genomics↗

bioRxiv2017

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 that is highly enriched in HELIOS+ cells, 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 x 10-9) and express the late-stage inhibitory receptor PD-1 (67.2% vs 35.5%; P = 4.0 x 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 are highly correlated (P = 1.2 x 10-19) 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.\n\nHighlights- FOXP3+ compartment within CD127lowCD25low T cells is expanded in autoimmune patients.\n\n- Increased numbers of CD25lowFOXP3+ T cells are a circulating marker of autoimmunity.\n\n- CD25lowFOXP3+ HELIOS+ T cells are fully demethylated at the FOXP3 TSDR.\n\n- CD25lowFOXP3+ T cells could represent a terminal stage of regulatory T cells.

immunology↗

bioRxiv2017

Type 1 diabetes genome-wide association analysis with imputation identifies five new risk regions

Type 1 diabetes genotype datasets have undergone several well powered genome wide analysis studies (GWAS), identifying 57 associated regions at the time of analysis. There are still many regions of smaller effect size or low frequency left to discover, and better exploitation of existing type 1 diabetes cohorts with meta analysis and imputation can precede the acquisition of new or larger cohorts. An existing dataset of 5,913 case and 8,829 control samples was analysed using genome-wide microarrays (Affymetrix GeneChip 500K and Illumina Infinium 550K) with imputation via IMPUTE2 with the 1000 Genomes Project (phase 3) reference panel. Genotyping coverage was doubled in known association regions, and increased by four fold in other regions compared to previous studies. Our analysis resulted in new index variants for 17/57 regions, an expanded set of plausible candidate SNPs for 17 regions, and five novel type 1 diabetes association regions at 1p31.3, 1q24.3, 1q31.2, 2q11.2 and 11q12.2. Candidate genes for the new loci included ITGB3BP, FASLG, RGS1, AFF3 and CD5/CD6. Further prioritisation of causal genes and causal variants will require detailed RNA and protein expression studies, in conjunction with genome annotation studies including analysis of physical promoter-enhancer interactions.

genomics↗

bioRxiv2017

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

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.\n\nResultsWithin 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.\n\nConclusionsOur systematic experimental framework offers an alternative approach to candidate causal gene identification for variants with cell state-specific functional effects, with achievable sample sizes.

genomics↗