Ilse Weets

Trends in childhood type 1 diabetes incidence in Europe during 1989–2008: evidence of non-uniformity over time in rates of increase

Aims/hypothesisThe aim of the study was to describe 20-year incidence trends for childhood type 1 diabetes in 23 EURODIAB centres and compare rates of increase in the first (1989–1998) and second (1999–2008) halves of the period.MethodsAll registers operate in geographically defined regions and are based on a clinical diagnosis. Completeness of registration is assessed by capture–recapture methodology. Twenty-three centres in 19 countries registered 49,969 new cases of type 1 diabetes in individuals diagnosed before their 15th birthday during the period studied.ResultsAscertainment exceeded 90% in most registers. During the 20-year period, all but one register showed statistically significant changes in incidence, with rates universally increasing. When estimated separately for the first and second halves of the period, the median rates of increase were similar: 3.4% per annum and 3.3% per annum, respectively. However, rates of increase differed significantly between the first half and the second half for nine of the 21 registers with adequate coverage of both periods; five registers showed significantly higher rates of increase in the first half, and four significantly higher rates in the second half.Conclusions/interpretationThe incidence rate of childhood type 1 diabetes continues to rise across Europe by an average of approximately 3–4% per annum, but the increase is not necessarily uniform, showing periods of less rapid and more rapid increase in incidence in some registers. This pattern of change suggests that important risk exposures differ over time in different European countries. Further time trend analysis and comparison of the patterns in defined regions is warranted.

β-Cell Replication Is Increased in Donor Organs From Young Patients After Prolonged Life Support

OBJECTIVE This study assesses β-cell replication in human donor organs and examines possible influences of the preterminal clinical conditions. RESEARCH DESIGN AND METHODS β-Cell replication was quantified in a consecutive series of n = 363 human organ donors using double immunohistochemistry for Ki67 and insulin. Uni- and multivariate analysis was used to correlate replication levels to clinical donor characteristics and histopathologic findings. RESULTS β-Cell replication was virtually absent in most donors, with ≤0.1% Ki67-positive β-cells in 72% of donors. A subpopulation of donors, however, showed markedly elevated levels of replication of up to 7.0% Ki67-positive β-cells. β-Cell replication was accompanied by the increased replication of glucagon-, somatostatin-, and CA19.9-positive cells. Prolonged life support, kidney dysfunction, relatively young donor age, inflammatory infiltration, and prolonged brain death before organ retrieval were all found to be significantly associated with an increased level (≥90th percentile) of β-cell replication, with the first three risk factors being independent predictors. Increased β-cell replication was most often noted in relatively young donors (≤25 years) who received prolonged (≥3 days) life support (68%); in contrast, it was rare in donors with a short duration of life support regardless of age (1%). Prolonged life support was accompanied by increased levels of CD68+ and LCA/CD45+ infiltration in the pancreatic parenchyma. CONCLUSION These results indicate that preterminal clinical conditions in (young) organ donors can lead to increased inflammatory infiltration of the pancreas and to increased β-cell replication.

Contribution of Antibodies Against IA-2β and Zinc Transporter 8 to Classification of Diabetes Diagnosed Under 40 Years of Age

OBJECTIVE We investigated whether measuring autoantibodies against zinc transporter 8 (ZnT8A) and IA-2β (IA-2βA) may improve classification of new-onset type 1 diabetic patients based on detection of autoantibodies against insulin (IAA), GAD (GADA), and IA-2 (IA-2A). In addition, we studied the correlation of IA-2βA and ZnT8A with other biological and demographic variables. RESEARCH DESIGN AND METHODS Circulating autoantibodies were determined by liquid-phase radiobinding assays from 761 healthy control subjects and 655 new-onset (<1 week insulin) diabetic patients (aged 0–39 years) with clinical type 1 diabetes phenotype consecutively recruited by the Belgian Diabetes Registry. RESULTS At diagnosis, IA-2βA and ZnT8A prevalences were 41 and 58%, respectively. In IAA-negative, GADA-negative, and IA-2A–negative patients, one IA-2βA–positive and eleven ZnT8A-positive individuals were identified at the expense of eight and seven additional positive control subjects (1%), respectively, for each test. ZnT8A or IA-2βA screening increased (P < 0.001; McNemar) the number of patients with ≥2 antibodies both under (from 78 to 87% for ZnT8A and 82% for IA-2βA) and above age 15 (from 51 to 63% for ZnT8A and 56% for IA-2βA) versus 0% in control subjects. IA-2βA and ZnT8A were preferentially associated with IA-2A, and with younger age at diagnosis. Unlike ZnT8A, IA-2βA levels were positively correlated with HLA-DQ8 and negatively with HLA-DQ2. ZnT8A could replace IAA for classification of patients above age 10 without loss of sensitivity or specificity. CONCLUSIONS ZnT8A, and to a lesser degree IA-2βA, may usefully complement GADA, IA-2A, and IAA for classifying insulin-treated diabetes under age 40 years.

Proinsulin levels and the proinsulin:c-peptide ratio complement autoantibody measurement for predicting type 1 diabetes

Aims/hypothesisWe investigated whether random proinsulin levels and proinsulin:C-peptide ratio (PI:C) complement immune and genetic markers for identifying relatives at high risk of type 1 diabetes.Materials and methodsDuring an initial sampling, random glycaemia, proinsulin, PI:C and HLA DQ genotype were determined in 561 non-diabetic first-degree relatives who had been positive for islet autoantibodies on one or more occasions and in 561 age- and sex-matched persistently antibody-negative relatives.ResultsDuring follow-up (median 62 months), 46 relatives with antibodies at entry developed type 1 diabetes. At baseline, antibody-positive relatives (n=338) had higher PI:C values (p<0.001) than antibody-negative subjects with (n=223) or subjects without (n=561) later seroconversion. Proinsulin and PI:C were graded according to risk of diabetes as expressed by positivity for (multiple) antibodies or IA-2 antibodies, especially in persons carrying the high-risk HLA DQ2/DQ8 genotype and in prediabetic relatives. In the presence of multiple or IA-2 antibodies, a PI:C ratio exceeding percentile 66 of all antibody-negative relatives at entry (n=784) conferred a 5-year diabetes risk of 50% and 68%, respectively (p<0.001 vs 13% for same antibody status with PI:C<percentile 66). Cox regression analysis confirmed random PI:C as an independent predictor of the risk of diabetes (p≤0.001).Conclusions/interpretationRandom proinsulin and PI:C represent dynamic markers of the state of beta cell function that complement immune markers in identifying relatives who are at homogeneously high risk of contracting type 1 diabetes and are therefore eligible for secondary prevention trials.

Seasonality in clinical onset of Type 1 diabetes in Belgian patients above the age of 10 is restricted to HLA-DQ2/DQ8-negative males, which explains the male to female excess in incidence

Aims/hypothesisType 1 diabetes arises from an interplay between environmental and genetic factors. The reported seasonality at diagnosis supports the hypothesis that currently unknown external triggers play a role in the onset of the disease. We investigated whether a seasonal pattern is observed at diagnosis in Belgian Type 1 diabetic patients, and if so whether seasonality varies according to age, sex and genetic risk, all known to affect the incidence of Type 1 diabetes.MethodsThe seasonal pattern at clinical diagnosis was assessed in 2176 islet antibody-positive diabetic patients aged 0 to 39 years diagnosed between 1989 and 2000. Additional stratification was performed for age, sex and HLA-DQ genotype.ResultsOverall, a significant seasonal pattern at clinical diagnosis of diabetes was observed (p<0.001). More subjects were diagnosed in the period of November to February (n=829) than during the period of June to September (n=619) characterised by higher averages of maximal daily temperature and daily hours of sunshine. However, the seasonal pattern was restricted to patients diagnosed above the age of 10 (0–9 years: p=0.398; 10–19 years: p<0.001; 20–29 years: p=0.003; 30–39 years: p=0.015). Since older age at diagnosis is associated with a male to female excess and a lower prevalence of the genetic accelerator HLA-DQ2/DQ8, we further stratified the patients aged 10 to 39 years (n=1675) according to HLA-DQ genotype and sex, and we found that the seasonal pattern was largely restricted to male subjects lacking DQ2/DQ8 (n=748; p<0.001 vs all others: n=927; p=0.031).Conclusions/interpretationIn a subgroup of male patients diagnosed over the age of 10, the later stages of the subclinical disease process may be more driven by sex- and season-dependent external factors than in younger, female and genetically more susceptible subjects. These factors may explain the male to female excess in diabetes diagnosed in early adulthood.

Combined positivity for HLA DQ2/DQ8 and IA-2 antibodies defines population at high risk of developing type 1 diabetes

Aims/hypothesisPrevention trials in first-degree relatives of type 1 diabetic patients are hampered by large interindividual differences in progression rate to diabetes. We investigated whether specific combinations of immune and genetic markers can identify subgroups with more homogeneous progression to clinical onset.MethodsAntibodies against islet cell cytoplasm (ICA), insulin (IAA), glutamate decarboxylase (GADA) and IA-2 protein (IA-2A) were measured in 790 non-diabetic control subjects and 4,589 first-degree relatives under age 40.ResultsOn first sampling, 11.1% of the siblings presented at least one antibody type (p<0.001 vs other relatives). During follow-up (median 52 months) 43 subjects developed type 1 diabetes (31 siblings, ten offspring of a diabetic father, two offspring of a diabetic mother). Using Kaplan–Meier survival analysis and Cox regression, IA-2A conferred the highest 5-year diabetes risk (>50%) irrespective of the number of antibodies present. In initially IA-2A-positive relatives (n=58) progression to hyperglycaemia depended more on HLA DQ status than on type of kinship (84% progression in the presence of DQ2/DQ8 vs 32% in its absence; p<0.003). In IA-2A-negative relatives (n=4,531) 5-year progression to diabetes increased with the number of other antibodies (ICA, GADA and/or IAA) (p<0.001) but overall did not exceed 10% even for two or more antibodies. Among relatives initially positive for one or more antibody type other than IA-2A (n=315), there was significantly more progression to diabetes (overall still <10%) in carriers of DQ2 (p<0.001 vs no DQ2), regardless of DQ8 status.Conclusions/interpretationThese observations suggest that the HLA-DQ-inferred risk of diabetes can proceed through two distinct pathways distinguished by IA-2A status. Combined positivity for DQ2/DQ8 and IA-2A defines a more homogeneous high-risk population for prevention trials than those used so far.

Relative and absolute HLA-DQA1-DQB1 linked risk for developing type I diabetes before 40 years of age in the Belgian population: implications for future prevention studies

HLA-DQ genotyping remains the cornerstone of genetic risk stratification in type I diabetes prediction and prevention studies. We developed a genetic screening strategy for predisposition to type I diabetes in the Belgian population based upon HLA-DQA1-DQB1 typing and taking into account the age at clinical onset. A group of 1866 autoantibody-positive type I patients below age 40 years recruited by the Belgian Diabetes Registry and a group of 750 control subjects were DQA1-DQB1 genotyped. In the total study population 16 different DQA1-DQB1 haplotypes were revealed, allowing the stratification of 81 genotypes in ten different genotype groups. Apart from the highest risk DQA1*-DQB1* genotype 0301-0302/0501-0201 (odds ratio 21; absolute risk 6%), three other genotype groups conferred a highly significant disease risk (p < 10(-6)). Altogether, these susceptibility genotypes were carried by 9% of the control subjects versus 60% of the patients diagnosed before age 40 years and up to 70% of those under age 5 years. All other genotypes were protective, neutral, infrequent or associated with a moderate protection or susceptibility. A strong, although not absolute protection was conferred by DQB1*0602-positive haplotypes (odds ratio = 0.03). This study in a large cohort of autoantibody-positive patients shows that a DQA1-DQB1-based genotyping strategy allows the identification of a subgroup representing less than 10% of the Belgian population but harbouring the majority of future type I patients arising in childhood or early adulthood. Future prediction and prevention studies should take into account the age dependency of this HLA-DQ associated risk.

BMI is an important driver of β-cell loss in type 1 diabetes upon diagnosis in 10 to 18-year-old children

OBJECTIVE Body weight-related insulin resistance probably plays a role in progression to type 1 diabetes, but has an uncertain impact following diagnosis. In this study, we investigated whether BMI measured at diagnosis was an independent predictor of C-peptide decline 1-year post-diagnosis. DESIGN Multicentre longitudinal study carried out at diagnosis and up to 1-year follow-up. METHODS Data on C-peptide were collected from seven diabetes centres in Europe. Patients were grouped according to age at diagnosis (<5 years, n=126; >5 years <10 years, n=295; >10 years <18 years, n=421; >18 years, n=410). Linear regression was used to investigate whether BMI was an independent predictor of change in fasting C-peptide over 1 year. Models were additionally adjusted for baseline insulin dose and HbA1c. RESULTS In individuals diagnosed between 0 and 5 years, 5 and 10 years and those diagnosed >18 years, we found no association between BMI and C-peptide decline. In patients aged 10-18 years, higher BMI at baseline was associated with a greater decline in fasting C-peptide over 1 year with a decrease (β 95% CI; P value) of 0.025 (0.010, 0.041) nM/kg per m(2) higher baseline BMI (P=0.001). This association remained significant after adjusting for gender and differences in HbA1c and insulin dose (β=0.026, 95% CI=0.0097, 0.042; P=0.002). CONCLUSIONS These observations indicate that increased body weight and increased insulin demand are associated with more rapid disease progression after diagnosis of type 1 diabetes in an age group 10-18 years. This should be considered in studies of β-cell function in type 1 diabetes.

IFIH1 gene polymorphisms in type 1 diabetes: Genetic association analysis and genotype–phenotype correlation in the Belgian population

The evaluation of susceptibility loci in a registry-based setting could be an important addition to the current predictive and screening models in T1D. Therefore, the aim of this study was to evaluate the importance of one of these loci, IFIH1. T1D patients (n=1981), control subjects (n=2092) and 430 families were genotyped for HLA-DQ and IFIH1 nsSNP rs1990760 (Ala946Thr). In the association analysis, the allelic frequencies, A (62.4% vs. 61.3%) and G (37.6% vs. 38.7%) were similar in cases and controls (chi(2) = 0.98, p = 0.32), the genotypic frequencies reveals a weak association with T1D (chi(2) = 6.79, p = 0.03), no significant transmission distortions in families (%T; A = 51.4%, G = 48.0 %, chi(2) = 1.76, p = 0.19) and no interaction with HLA-DQ-linked risk. Furthermore, no genotype-phenotype correlation was observed. In conclusion, IFIH1 has no important role in T1D risk assessment in a registry-based Belgian population.

Seasonal variation in month of diagnosis in children with type 1 diabetes registered in 23 European centers during 1989-2008: little short-term influence of sunshine hours or average temperature

The month of diagnosis in childhood type 1 diabetes shows seasonal variation.