Real-world Effectiveness and Safety of Vedolizumab for the Treatment of Inflammatory Bowel Disease: The Scottish Vedolizumab Cohort.

BACKGROUND & AIMS: Vedolizumab is an anti-a4b7 monoclonal antibody that is licensed for the treatment of moderate to severe Crohn's disease and ulcerative colitis. The aims of this study were to establish the real-world effectiveness and safety of vedolizumab for the treatment of inflammatory bowel disease. METHODS: This was a retrospective study involving seven NHS health boards in Scotland between June 2015 and November 2017. Inclusion criteria included: a diagnosis of ulcerative colitis or Crohn's disease with objective evidence of active inflammation at baseline (Harvey-Bradshaw Index[HBI] ≥5/Partial Mayo ≥2 plus C-reactive protein [CRP] >5 mg/L or faecal calprotectin ≥250 µg/g or inflammation on endoscopy/magnetic resonance imaging [MRI]); completion of induction; and at least one clinical follow-up by 12 months. Kaplan-Meier survival analysis was used to establish 12-month cumulative rates of clinical remission, mucosal healing, and deep remission [clinical remission plus mucosal healing]. Rates of serious adverse events were described quantitatively. RESULTS: Our cohort consisted of 180 patients with ulcerative colitis and 260 with Crohn's disease. Combined median follow-up was 52 weeks (interquartile range [IQR] 26-52 weeks). In ulcerative colitis, 12-month cumulative rates of clinical remission, mucosal healing, and deep remission were 57.4%, 47.3%, and 38.5%, respectively. In Crohn's disease, 12-month cumulative rates of clinical remission, mucosal healing, and deep remission were 58.4%, 38.9%, and 28.3% respectively. The serious adverse event rate was 15.6 per 100 patient-years of follow-up. CONCLUSIONS: Vedolizumab is a safe and effective treatment for achieving both clinical remission and mucosal healing in ulcerative colitis and Crohn's disease.

ß-cell specific T-lymphocyte response has a distinct inflammatory phenotype in children with Type 1 diabetes compared with adults.

AIM: To examine the hypothesis that the quality, magnitude and breadth of helper T-lymphocyte responses to ß cells differ in Type 1 diabetes according to diagnosis in childhood or adulthood. METHODS: We studied helper T-lymphocyte reactivity against ß-cell autoantigens by measuring production of the pro-inflammatory cytokine interferon-γ and the anti-inflammatory cytokine interleukin-10, using enzyme-linked immunospot assays in 61 people with Type 1 diabetes (within 3 months of diagnosis, positive for HLA DRB1*0301 and/or *0401), of whom 33 were children/adolescents, and a further 91 were unaffected siblings. RESULTS: Interferon-γ responses were significantly more frequent in children with Type 1 diabetes compared with adults (85 vs 61%; P = 0.04). Insulin and proinsulin peptides were preferentially targeted in children (P = 0.0001 and P = 0.04, respectively) and the breadth of the interferon-γ response was also greater, with 70% of children having an interferon-γ response to three or more peptides compared with 14% of adults (P < 0.0001). Islet ß-cell antigen-specific interleukin-10 responses were similar in children and adults in terms of frequency, breadth and magnitude, with the exception of responses to glutamic acid decarboxylase 65, which were significantly less frequent in adults. CONCLUSIONS: At diagnosis of Type 1 diabetes, pro-inflammatory autoreactivity is significantly more prevalent, focuses on a wider range of targets, and is more focused on insulin/proinsulin in children than adults. We interpret this as indicating a more aggressive immunological response in the younger age group that is especially characterized by loss of tolerance to proinsulin. These findings highlight the existence of age-related heterogeneity in Type 1 diabetes pathogenesis that could have relevance to the development of immune-based therapies.

CHiCP: a web-based tool for the integrative and interactive visualization of promoter capture Hi-C datasets.

UNLABELLED: Promoter capture Hi-C (PCHi-C) allows the genome-wide interrogation of physical interactions between distal DNA regulatory elements and gene promoters in multiple tissue contexts. Visual integration of the resultant chromosome interaction maps with other sources of genomic annotations can provide insight into underlying regulatory mechanisms. We have developed Capture HiC Plotter (CHiCP), a web-based tool that allows interactive exploration of PCHi-C interaction maps and integration with both public and user-defined genomic datasets. AVAILABILITY AND IMPLEMENTATION: CHiCP is freely accessible from www.chicp.org and supports most major HTML5 compliant web browsers. Full source code and installation instructions are available from http://github.com/D-I-L/django-chicp CONTACT: ob219@cam.ac.uk.

Primary prevention of beta-cell autoimmunity and type 1 diabetes - The Global Platform for the Prevention of Autoimmune Diabetes (GPPAD) perspectives.

OBJECTIVE: Type 1 diabetes can be identified by the presence of beta-cell autoantibodies that often arise in the first few years of life. The purpose of this perspective is to present the case for primary prevention of beta-cell autoimmunity and to provide a study design for its implementation in Europe. METHODS: We examined and summarized recruitment strategies, enrollment rates, and outcomes in published TRIGR, FINDIA and BABYDIET primary prevention trials, and the TEDDY intensive observational study. A proposal for a recruitment and implementation strategy to perform a phase II/III primary prevention randomized controlled trial in infants with genetic risk for developing beta-cell autoimmunity is outlined. RESULTS: Infants with a family history of type 1 diabetes (TRIGR, BABYDIET, TEDDY) and infants younger than age 3 months from the general population (FINDIA, TEDDY) were enrolled into these studies. All studies used HLA genotyping as part of their eligibility criteria. Predicted beta-cell autoimmunity risk in the eligible infants ranged from 3% (FINDIA, TEDDY general population) up to 12% (TRIGR, BABYDIET). Amongst eligible infants, participation was between 38% (TEDDY general population) and 97% (FINDIA). Outcomes, defined as multiple beta-cell autoantibodies, were consistent with predicted risks. We subsequently modeled recruitment into a randomized controlled trial (RCT) that could assess the efficacy of oral insulin treatment as adapted from the Pre-POINT pilot trial. The RCT would recruit infants with and without a first-degree family history of type 1 diabetes and be based on general population genetic risk testing. HLA genotyping and, for the general population, genotyping at additional type 1 diabetes susceptibility SNPs would be used to identify children with around 10% risk of beta-cell autoimmunity. The proposed RCT would have 80% power to detect a 50% reduction in multiple beta-cell autoantibodies by age 4 years at a two-tailed alpha of 0.05, and would randomize around 1160 infants to oral insulin or placebo arms in order to fulfill this. It is estimated that recruitment would require testing of between 400,000 and 500,000 newborns or infants. CONCLUSION: It is timely and feasible to establish a platform for primary prevention trials for type 1 diabetes in Europe. This multi-site European infrastructure would perform RCTs, supply data coordination and biorepository, provide cohorts for mechanistic and observational studies, and increase awareness for autoimmune diabetes.

Multi-parametric flow cytometric and genetic investigation of the peripheral B cell compartment in human type 1 diabetes.

The appearance of circulating islet-specific autoantibodies before disease diagnosis is a hallmark of human type 1 diabetes (T1D), and suggests a role for B cells in the pathogenesis of the disease. Alterations in the peripheral B cell compartment have been reported in T1D patients; however, to date, such studies have produced conflicting results and have been limited by sample size. In this study, we have performed a detailed characterization of the B cell compartment in T1D patients (n = 45) and healthy controls (n = 46), and assessed the secretion of the anti-inflammatory cytokine interleukin (IL)-10 in purified B cells from the same donors. Overall, we found no evidence for a profound alteration of the B cell compartment or in the production of IL-10 in peripheral blood of T1D patients. We also investigated age-related changes in peripheral B cell subsets and confirmed the sharp decrease with age of transitional CD19(+) CD27(-) CD24(hi) CD38(hi) B cells, a subset that has recently been ascribed a putative regulatory function. Genetic analysis of the B cell compartment revealed evidence for association of the IL2-IL21 T1D locus with IL-10 production by both memory B cells (P = 6·4 × 10(-4) ) and islet-specific CD4(+) T cells (P = 2·9 × 10(-3) ). In contrast to previous reports, we found no evidence for an alteration of the B cell compartment in healthy individuals homozygous for the non-synonymous PTPN22 Trp(620) T1D risk allele (rs2476601; Arg(620) Trp). The IL2-IL21 association we have identified, if confirmed, suggests a novel role for B cells in T1D pathogenesis through the production of IL-10, and reinforces the importance of IL-10 production by autoreactive CD4(+) T cells.

HLA class II gene associations in African American type 1 diabetes reveal a protective HLA-DRB1*03 haplotype.

AIMS: Owing to strong linkage disequilibrium between markers, pinpointing disease associations within genetic regions is difficult in European ancestral populations, most notably the very strong association of the HLA-DRB1*03-DQA1*05:01-DQB1*02:01 haplotype with Type 1 diabetes risk, which is assumed to be because of a combination of HLA-DRB1 and HLA-DQB1. In contrast, populations of African ancestry have greater haplotype diversity, offering the possibility of narrowing down regions and strengthening support for a particular gene in a region being causal. We aimed to study the human leukocyte antigen (HLA) region in African American Type 1 diabetes. METHODS: Two hundred and twenty-seven African American patients with Type 1 diabetes and 471 African American control subjects were tested for association at the HLA class II genes, HLA-DRB1, HLA-DQA1, HLA-DQB1 and 5147 single nucleotide polymorphisms across the major histocompatibility complex region using logistic regression models. Population admixture was accounted for with principal components analysis. RESULTS: Single nucleotide polymorphism marker associations were explained by the HLA associations, with the major peak over the class II loci. The HLA association overall was extremely strong, as expected for Type 1 diabetes, even in African Americans in whom diabetes diagnosis is heterogeneous. In addition, there were unique features: the HLA-DRB1*03 haplotype was split into HLA-DRB1*03:01, which confers greatest susceptibility in these samples (odds ratio 3.17, 95% CI 1.72-5.83) and HLA-DRB1*03:02, an allele rarely observed in Europeans, which confers the greatest protection in these African American samples (odds ratio 0.22, 95% CI 0.09-0.55). CONCLUSIONS: The unique diversity of the African HLA region we have uncovered supports a specific and major role for HLA-DRB1 in HLA-DRB1*03 haplotype-associated Type 1 diabetes risk.

Genetic association of zinc transporter 8 (ZnT8) autoantibodies in type 1 diabetes cases.

AIMS/HYPOTHESIS: Autoantibodies to zinc transporter 8 (ZnT8A) are associated with risk of type 1 diabetes. Apart from the SLC30A8 gene itself, little is known about the genetic basis of ZnT8A. We hypothesise that other loci in addition to SLC30A8 are associated with ZnT8A. METHODS: The levels of ZnT8A were measured in 2,239 British type 1 diabetic individuals diagnosed before age 17 years, with a median duration of diabetes of 4 years. Cases were tested at over 775,000 loci genome wide (including 53 type 1 diabetes associated regions) for association with positivity for ZnT8A. ZnT8A were also measured in an independent dataset of 855 family members with type 1 diabetes. RESULTS: Only FCRL3 on chromosome 1q23.1 and the HLA class I region were associated with positivity for ZnT8A. rs7522061T>C was the most associated single nucleotide polymorphism (SNP) in the FCRL3 region (p = 1.13 × 10(-16)). The association was confirmed in the family dataset (p ≤ 9.20 × 10(-4)). rs9258750A>G was the most associated variant in the HLA region (p = 2.06 × 10(-9) and p = 0.0014 in family cases). The presence of ZnT8A was not associated with HLA-DRB1, HLA-DQB1, HLA-A, HLA-B or HLA-C (p > 0.05). Unexpectedly, the two loci associated with the presence of ZnT8A did not alter risk of having type 1 diabetes, and the 53 type 1 diabetes risk loci did not influence positivity for ZnT8A, despite them being disease specific. CONCLUSIONS/INTERPRETATION: ZnT8A are not primary pathogenic factors in type 1 diabetes. Nevertheless, ZnT8A testing in combination with other autoantibodies facilitates disease prediction, despite the biomarker not being under the same genetic control as the disease.

Confirmation of novel type 1 diabetes risk loci in families.

AIMS/HYPOTHESIS: Over 50 regions of the genome have been associated with type 1 diabetes risk, mainly using large case/control collections. In a recent genome-wide association (GWA) study, 18 novel susceptibility loci were identified and replicated, including replication evidence from 2,319 families. Here, we, the Type 1 Diabetes Genetics Consortium (T1DGC), aimed to exclude the possibility that any of the 18 loci were false-positives due to population stratification by significantly increasing the statistical power of our family study. METHODS: We genotyped the most disease-predicting single-nucleotide polymorphisms at the 18 susceptibility loci in 3,108 families and used existing genotype data for 2,319 families from the original study, providing 7,013 parent-child trios for analysis. We tested for association using the transmission disequilibrium test. RESULTS: Seventeen of the 18 susceptibility loci reached nominal levels of significance (p < 0.05) in the expanded family collection, with 14q24.1 just falling short (p = 0.055). When we allowed for multiple testing, ten of the 17 nominally significant loci reached the required level of significance (p < 2.8 × 10(-3)). All susceptibility loci had consistent direction of effects with the original study. CONCLUSIONS/INTERPRETATION: The results for the novel GWA study-identified loci are genuine and not due to population stratification. The next step, namely correlation of the most disease-associated genotypes with phenotypes, such as RNA and protein expression analyses for the candidate genes within or near each of the susceptibility regions, can now proceed.

Strategies for the prevention of autoimmune type 1 diabetes.

European experts on autoimmune Type 1 diabetes met for 2 days in October 2010 in Cambridge, to review the state-of-the-art and to discuss strategies for prevention of Type 1 diabetes (http://www-gene.cimr.cam.ac.uk/todd/sub_pages/T1D_prevention_Cambridge_workshop_20_21Oct2010.pdf). Meeting sessions examined the epidemiology of Type 1 diabetes; possible underlying causes of the continuing and rapid increase in Type 1 diabetes incidence at younger ages; and lessons learned from previous prevention trials. Consensus recommendations from the meeting were: 1. Resources such as national diabetes registries and natural history studies play an essential role in developing and refining assays to be used in screening for risk factors for Type 1 diabetes. 2. It is crucial to dissect out the earliest physiological events after birth, which are controlled by the susceptibility genes now identified in Type 1 diabetes, and the environmental factors that might affect these phenotypes, in order to bring forward a mechanistic approach to designing future prevention trials. 3. Current interventions at later stages of disease, such as in newly diagnosed Type 1 diabetes, have relied mainly on non-antigen-specific mechanisms. For primary prevention-preventing the onset of autoimmunity-interventions must be based on knowledge of the actual disease process such that: participants in a trial would be stratified according the disease-associated molecular phenotypes; the autoantigen(s) and immune responses to them; and the manipulation of the environment, as early as possible in life. Combinations of interventions should be considered as they may allow targeting different components of disease, thus lowering side effects while increasing efficacy.

Overview of the Type I Diabetes Genetics Consortium.

The Type I Diabetes Genetics Consortium (T1DGC) is an international, multicenter research program with two primary goals. The first goal is to identify genomic regions and candidate genes whose variants modify an individual's risk of type I diabetes (T1D) and help explain the clustering of the disease in families. The second goal is to make research data available to the research community and to establish resources that can be used by, and that are fully accessible to, the research community. To facilitate the access to these resources, the T1DGC has developed a Consortium Agreement (http://www.t1dgc.org) that specifies the rights and responsibilities of investigators who participate in Consortium activities. The T1DGC has assembled a resource of affected sib-pair families, parent-child trios, and case-control collections with banks of DNA, serum, plasma, and EBV-transformed cell lines. In addition, both candidate gene and genome-wide (linkage and association) studies have been performed and displayed in T1DBase (http://www.t1dbase.org) for all researchers to use in their own investigations. In this supplement, a subset of the T1DGC collection has been used to investigate earlier published candidate genes for T1D, to confirm the results from a genome-wide association scan for T1D, and to determine associations with candidate genes for other autoimmune diseases or with type II diabetes that may be involved with beta-cell function.

Current status and the future for the genetics of type I diabetes.

The Type I Diabetes Genetics Consortium (T1DGC) is an international collaboration whose primary goal is to identify genes whose variants modify an individual's risk of type I diabetes (T1D). An integral part of the T1DGC's mission is the establishment of clinical and data resources that can be used by, and that are fully accessible to, the T1D research community (http://www.t1dgc.org). The T1DGC has organized the collection and analyses of study samples and conducted several major research projects focused on T1D gene discovery: a genome-wide linkage scan, an intensive evaluation of the human major histocompatibility complex, a detailed examination of published candidate genes, and a genome-wide association scan. These studies have provided important information to the scientific community regarding the function of specific genes or chromosomal regions on T1D risk. The results are continually being updated and displayed (http://www.t1dbase.org). The T1DGC welcomes all investigators interested in using these data for scientific endeavors on T1D. The T1DGC resources provide a framework for future research projects, including examination of structural variation, re-sequencing of candidate regions in a search for T1D-associated genes and causal variants, correlation of T1D risk genotypes with biomarkers obtained from T1DGC serum and plasma samples, and in-depth bioinformatics analyses.

Association analyses of the vitamin D receptor gene in 1654 families with type I diabetes.

Type I diabetes (T1D) results from interactions between environmental exposures and genetic susceptibility leading to immune dysfunction and destruction of the insulin-producing beta cells of the pancreas. Vitamin D deficiency is likely to be one of the many environmental factors influencing T1D development and diagnosis, and, hence, the hormone receptor gene, VDR, was examined for association with T1D risk. The Type I Diabetes Genetics Consortium genotyped 38 single nucleotide polymorphisms (SNPs) in 1654 T1D nuclear families (6707 individuals, 3399 affected). Genotypes for 38 SNPs were assigned using the Illumina (ILMN) and Sequenom (SQN) technology. The analysis of data release as of July 2008 is reported for both platforms. No evidence of association of VDR SNPs with T1D at P<0.01 was obtained in the overall sample set, nor in subgroups analyses of the parent-of-origin, sex of offspring and HLA risk once adjusted for multiple testing.

Analysis of 19 genes for association with type I diabetes in the Type I Diabetes Genetics Consortium families.

In recent years the pace of discovery of genetic associations with type I diabetes (T1D) has accelerated, with the total number of confirmed loci, including the major histocompatibility complex (MHC) region, reaching 43. However, much of the deciphering of the associations at these, and the established T1D loci, has yet to be performed in sufficient numbers of samples or with sufficient markers. Here, 257 single-nucleotide polymorphisms (SNPs) have been genotyped in 19 candidate genes (INS, PTPN22, IL2RA, CTLA4, IFIH1, SUMO4, VDR, PAX4, OAS1, IRS1, IL4, IL4R, IL13, IL12B, CEACAM21, CAPSL, Q7Z4c4(5Q), FOXP3, EFHB) in 2300 affected sib-pair families and tested for association with T1D as part of the Type I Diabetes Genetics Consortium's candidate gene study. The study had approximately 80% power at alpha=0.002 and a minor allele frequency of 0.2 to detect an effect with a relative risk (RR) of 1.20, which drops to just 40% power for a RR of 1.15. At the INS gene, rs689 (-23 HphI) was the most associated SNP (P=3.8 x 10(-31)), with the estimated RR=0.57 (95% confidence interval, 0.52-0.63). In addition, rs689 was associated with age-at-diagnosis of T1D (P=0.001), with homozygosity for the T1D protective T allele, delaying the onset of T1D by approximately 2 years in these families. At PTPN22, rs2476601 (R620W), in agreement with previous reports, was the most significantly associated SNP (P=6.9 x 10(-17)), with RR=1.55 (1.40-1.72). Evidence for association with T1D was observed for the IFIH1 SNP, rs1990760 (P=7.0 x 10(-4)), with RR=0.88 (0.82-0.95) and the CTLA4 SNP rs1427676 (P=0.0005), with RR=1.14 (1.06-1.23). In contrast, no convincing evidence of association was obtained for SUMO4, VDR, PAX4, OAS1, IRS1, IL4, IL4R, IL13, IL12B, CEACAM21 or CAPSL gene regions (http://www.T1DBase.org).

Follow-up of 1715 SNPs from the Wellcome Trust Case Control Consortium genome-wide association study in type I diabetes families.

The advent of genome-wide association (GWA) studies has revolutionized the detection of disease loci and provided abundant evidence for previously undetected disease loci that can be pooled together in meta-analysis studies or used to design follow-up studies. A total of 1715 SNPs from the Wellcome Trust Case Control Consortium GWA study of type I diabetes (T1D) were selected and a follow-up study was conducted in 1410 affected sib-pair families assembled by the Type I Diabetes Genetics Consortium. In addition to the support for previously identified loci (PTPN22/1p13; ERBB3/12q13; SH2B3/12q24; CLEC16A/16p13; UBASH3A/21q22), evidence supporting two new and distinct chromosome locations associated with T1D was observed: FHOD3/18q12 (rs2644261, P=5.9 x 10(-4)) and Xp22 (rs5979785, P=6.8 x 10(-3); http://www.T1DBase.org). There was independent support for both SNPs in a GWA meta-analysis of 7514 cases and 9045 controls (P values=5.0 x 10(-3) and 6.7 x 10(-6), respectively). The chromosome 18q12 region contains four genes, none of which are obvious functional candidate genes. In contrast, the Xp22 SNP is located 30 kb centromeric of the functional candidate genes TLR8 and TLR7 genes. Both TLR8 and TLR7 are functional candidate genes owing to their key roles as pathogen recognition receptors and, in the case of TLR7, overexpression has been associated directly with murine autoimmune disease.

Analysis of 55 autoimmune disease and type II diabetes loci: further confirmation of chromosomes 4q27, 12q13.2 and 12q24.13 as type I diabetes loci, and support for a new locus, 12q13.3-q14.1.

A candidate gene study was conducted on 10 established type II diabetes genes and 45 genes associated with autoimmune diseases, including type I diabetes (T1D), in a maximum of 1410 affected sib-pair families assembled by the Type I Diabetes Genetics Consortium. Associations at P values <10(-3) were found for three known T1D regions at chromosomes 4q27, 12q13.2 and 12q24.13 (http://www.T1DBase.org). Support was obtained for a newly identified T1D candidate locus on chromosome 12q13.3-12q14.1 (rs1678536/KIF5A: P=8.1 x 10(-3); relative risk (RR) for minor allele=0.89, 95% CI=0.82-0.97), which has a separate association from the previously reported T1D candidate locus ERBB3/12q13.2-q13.3. Our new evidence adds to that previously published for the same gene region in a T1D case-control study (rs1678542; P=3.0 x 10(-4); odds ratio (OR)=0.92, 95% CI=0.88-0.96). This region, which contains many genes, has also been associated with rheumatoid arthritis.

No association of multiple type 2 diabetes loci with type 1 diabetes.

AIMS/HYPOTHESIS: We used recently confirmed type 2 diabetes gene regions to investigate the genetic relationship between type 1 and type 2 diabetes, in an average of 7,606 type 1 diabetic individuals and 8,218 controls, providing >80% power to detect effects as small as an OR of 1.11 at a false-positive rate of 0.003. METHODS: The single nucleotide polymorphisms (SNPs) with the most convincing evidence of association in 12 type 2 diabetes-associated gene regions, PPARG, CDKAL1, HNF1B, WFS1, SLC30A8, CDKN2A-CDKN2B, IGF2BP2, KCNJ11, TCF7L2, FTO, HHEX-IDE and THADA, were analysed in type 1 diabetes cases and controls. PPARG and HHEX-IDE were additionally tested for association in 3,851 type 1 diabetes families. Tests for interaction with HLA class II genotypes, autoantibody status, sex, and age-at-diagnosis of type 1 diabetes were performed with all 12 gene regions. RESULTS: Only PPARG and HHEX-IDE showed any evidence of association with type 1 diabetes cases and controls (p = 0.004 and p = 0.003, respectively; p > 0.05 for other SNPs). The potential association of PPARG was supported by family analyses (p = 0.003; p (combined) = 1.0 x 10(-4)). No SNPs showed evidence of interaction with any covariate (p > 0.05). CONCLUSIONS/INTERPRETATION: We found no convincing genetic link between type 1 and type 2 diabetes. An association of PPARG (rs1801282/Pro12Ala) could be consistent with its known function in inflammation. Hence, our results reinforce evidence suggesting that type 1 diabetes is a disease of the immune system, rather than being due to inherited defects in beta cell function or regeneration or insulin resistance.

Ambulatory blood pressure measurements are related to albumin excretion and are predictive for risk of microalbuminuria in young people with type 1 diabetes.

AIMS/HYPOTHESIS: The relationship between BP and microalbuminuria in young people with type 1 diabetes is not completely clear. As microalbuminuria is preceded by a gradual rise in albumin excretion within the normal range, we hypothesised that ambulatory BP (ABP) may be closely related to albumin excretion and progression to microalbuminuria. METHODS: ABP monitoring (ABPM) was performed in 509 young people with type 1 diabetes (age median [range]: 15.7 [10.7-22.6] years) followed with annual assessments of three early morning urinary albumin:creatinine ratios (ACRs) and HbA(1c). Systolic BP (SBP) and diastolic BP (DBP) and the nocturnal fall in BP were analysed in relation to ACR. RESULTS: All ABPM variables were significantly related to baseline log(10) ACR (p < 0.001). After the ABPM evaluation, 287 patients were followed for a median of 2.2 (1.0-5.5) years. ABP at baseline was independently related to mean ACR during follow-up. Nineteen initially normoalbuminuric patients developed microalbuminuria after 2.0 (0.2-4.0) years and their baseline daytime DBP was higher than in normoalbuminuric patients (p < 0.001). After adjusting for baseline ACR and HbA(1c), there was an 11% increased risk of microalbuminuria for each 1 mmHg increase in daytime DBP. Forty-eight per cent of patients were non-dippers for SBP and 60% for DBP; however, ACR was not different between dippers and non-dippers and there were no differences in the nocturnal fall in BP between normoalbuminuric and future microalbuminuric patients. CONCLUSIONS/INTERPRETATION: In this cohort of young people with type 1 diabetes, ABP was significantly related to ACR, and daytime DBP was independently associated with progression to microalbuminuria. Increasing albumin excretion, even in the normal range, may be associated with parallel rises in BP.

Confirmation of HLA class II independent type 1 diabetes associations in the major histocompatibility complex including HLA-B and HLA-A.

AIM: Until recently, human leucocyte antigen (HLA) class II-independent associations with type 1 diabetes (T1D) in the Major Histocompatibility Complex (MHC) region were not adequately characterized owing to insufficient map coverage, inadequate statistical approaches and strong linkage disequilibrium spanning the entire MHC. Here we test for HLA class II-independent associations in the MHC using fine mapping data generated by the Type 1 Diabetes Genetics Consortium (T1DGC). METHODS: We have applied recursive partitioning to the modelling of the class II loci and used stepwise conditional logistic regression to test approximately 1534 loci between 29 and 34 Mb on chromosome 6p21, typed in 2240 affected sibpair (ASP) families. RESULTS: Preliminary analyses confirm that HLA-B (at 31.4 Mb), HLA-A (at 30.0 Mb) are associated with T1D independently of the class II genes HLA-DRB1 and HLA-DQB1 (P = 6.0 x 10(-17) and 8.8 x 10(-13), respectively). In addition, a second class II region of association containing the single-nucleotide polymorphism (SNP), rs439121, and the class II locus HLA-DPB1, was identified as a T1D susceptibility effect which is independent of HLA-DRB1, HLA-DQB1 and HLA-B (P = 9.2 x 10(-8)). A younger age-at-diagnosis of T1D was found for HLA-B*39 (P = 7.6 x 10(-6)), and HLA-B*38 was protective for T1D. CONCLUSIONS: These analyses in the T1DGC families replicate our results obtained previously in approximately 2000 cases and controls and 850 families. Taking both studies together, there is evidence for four T1D-associated regions at 30.0 Mb (HLA-A), 31.4 Mb (HLA-B), 32.5 Mb (rs9268831/HLA-DRA) and 33.2 Mb (rs439121/HLA-DPB1) that are independent of HLA-DRB1/HLA-DQB1. Neither study found evidence of independent associations at HLA-C, HLA-DQA1 loci nor in the UBD/MAS1L or ITPR3 gene regions. These studies show that to find true class II-independent effects, large, well-powered sample collections are required and be genotyped with a dense map of markers. In addition, a robust statistical methodology that fully models the class II effects is necessary. Recursive partitioning is a useful tool for modelling these multiallelic systems.

Analysis of 17 autoimmune disease-associated variants in type 1 diabetes identifies 6q23/TNFAIP3 as a susceptibility locus.

As a result of genome-wide association studies in larger sample sets, there has been an increase in identifying genes that influence susceptibility to individual immune-mediated diseases, as well as evidence that some genes are associated with more than one disease. In this study, we tested 17 single nucleotide polymorphisms (SNP) from 16 gene regions that have been reported in several autoimmune diseases including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), multiple sclerosis (MS), ankylosing spondylitis (AS) and Crohn's disease (CD) to determine whether the variants are also associated with type 1 diabetes (T1D). In up to 8010 cases and 9733 controls we found some evidence for an association with T1D in the regions containing genes: 2q32/STAT4, 17q21/STAT3, 5p15/ERAP1 (ARTS1), 6q23/TNFAIP3 and 12q13/KIF5A/PIP4K2C with allelic P-values ranging from 3.70 x 10(-3) to 3.20 x 10(-5). These findings extend our knowledge of susceptibility locus sharing across different autoimmune diseases, and provide convincing evidence that the RA/SLE locus 6q23/TNFAIP3 is a newly identified T1D locus.