Gestational respiratory infections interacting with offspring HLA and CTLA-4 modifies incident β-cell autoantibodies

Gastrointestinal Infections Modulate the Risk for Insulin Autoantibodies as the First-Appearing Autoantibody in the TEDDY Study

OBJECTIVE

To investigate gastrointestinal infection episodes (GIEs) in relation to the appearance of islet autoantibodies in The Environmental Determinants of Diabetes in the Young (TEDDY) cohort.

RESEARCH DESIGN AND METHODS

GIEs on risk of autoantibodies against either insulin (IAA) or GAD (GADA) as the first-appearing autoantibody were assessed in a 10-year follow-up of 7,867 children. Stool virome was characterized in a nested case-control study.

RESULTS

GIE reports (odds ratio [OR] 2.17 [95% CI 1.39-3.39]) as well as Norwalk viruses found in stool (OR 5.69 [1.36-23.7]) at <1 year of age were associated with an increased IAA risk at 2-4 years of age. GIEs reported at age 1 to <2 years correlated with a lower risk of IAA up to 10 years of age (OR 0.48 [0.35-0.68]). GIE reports at any other age were associated with an increase in IAA risk (OR 2.04 for IAA when GIE was observed 12-23 months prior [1.41-2.96]). Impacts on GADA risk were limited to GIEs <6 months prior to autoantibody development in children <4 years of age (OR 2.16 [1.54-3.02]).

CONCLUSIONS

Bidirectional associations were observed. GIEs were associated with increased IAA risk when reported before 1 year of age or 12-23 months prior to IAA. Norwalk virus was identified as one possible candidate factor. GIEs reported during the 2nd year of life were associated with a decreased IAA risk.

Possible heterogeneity of initial pancreatic islet beta-cell autoimmunity heralding type 1 diabetes

The etiology of type 1 diabetes (T1D) foreshadows the pancreatic islet beta-cell autoimmune pathogenesis that heralds the clinical onset of T1D. Standardized and harmonized tests of autoantibodies against insulin (IAA), glutamic acid decarboxylase (GADA), islet antigen-2 (IA-2A), and ZnT8 transporter (ZnT8A) allowed children to be followed from birth until the appearance of a first islet autoantibody. In the Environmental Determinants of Diabetes in the Young (TEDDY) study, a multicenter (Finland, Germany, Sweden, and the United States) observational study, children were identified at birth for the T1D high-risk HLA haploid genotypes DQ2/DQ8, DQ2/DQ2, DQ8/DQ8, and DQ4/DQ8. The TEDDY study was preceded by smaller studies in Finland, Germany, Colorado, Washington, and Sweden. The aims were to follow children at increased genetic risk to identify environmental factors that trigger the first-appearing autoantibody (etiology) and progress to T1D (pathogenesis). The larger TEDDY study found that the incidence rate of the first-appearing autoantibody was split into two patterns. IAA first peaked already during the first year of life and tapered off by 3-4 years of age. GADA first appeared by 2-3 years of age to reach a plateau by about 4 years. Prior to the first-appearing autoantibody, genetic variants were either common or unique to either pattern. A split was also observed in whole blood transcriptomics, metabolomics, dietary factors, and exposures such as gestational life events and early infections associated with prolonged shedding of virus. An innate immune reaction prior to the adaptive response cannot be excluded. Clarifying the mechanisms by which autoimmunity is triggered to either insulin or GAD65 is key to uncovering the etiology of autoimmune T1D.

CTLA4, SH2B3, and CLEC16A diversely affect the progression of early islet autoimmunity in relatives of Type 1 diabetes patients

The HLA region is the major genetic risk determinant of Type 1 diabetes. How non-HLA loci contribute to the genetic risk is incompletely understood, but there are indications that at least some impact progression of asymptomatic autoimmunity. We examined whether SNPs in 7 susceptibility loci (INS, SH2B3, PTPN2, PTPN22, CTLA4, CLEC16A, and IL2RA) could improve prediction of the progression from single to multiple autoantibody positivity, and from there on to diagnosis. SNPs were genotyped in persistently autoantibody positive relatives by allelic discrimination qPCR and disease progression was studied by multivariate Cox regression analysis. In our cohort, only the CTLA4 GA genotype (rs3087243, P = 0.002) and the CLEC16A AA genotype (rs12708716, P = 0.021) were associated with accelerated progression from single to multiple autoantibody positivity, but their effects were restricted to presence of HLA-DQ2/DQ8, and IAA as first autoantibody, respectively. The interaction of CTLA4 and HLA-DQ2/DQ8 overruled the effect of DQ2/DQ8 alone. The HLA-DQ2/DQ8-mediated risk of progression to multiple autoantibodies nearly entirely depended on heterozygosity for CTLA4. The SH2B3 TT genotype (rs3184504) was protective for HLA-DQ8 positive subjects (P = 0.003). At the stage of multiple autoantibodies, only the CTLA4 GA genotype was a minor independent risk factor for progression towards clinical diabetes (P = 0.034). Our study shows that non-HLA polymorphisms impact progression of islet autoimmunity in a subgroup-, stage- and SNP-specific way, suggesting distinct mechanisms. If confirmed, these findings may help refine risk assessment, follow-up, and prevention trials in risk groups.

Respiratory infections and type 1 diabetes: Potential roles in pathogenesis

Among the environmental factors associated with type 1 diabetes (T1D), viral infections of the gut and pancreas has been investigated most intensely, identifying enterovirus infections as the prime candidate trigger of islet autoimmunity (IA) and T1D development. However, the association between respiratory tract infections (RTI) and IA/T1D is comparatively less known. While there are significant amounts of epidemiological evidence supporting the role of respiratory infections in T1D, there remains a paucity of data characterising infectious agents at the molecular level. This gap in the literature precludes the identification of the specific infectious agents driving the association between RTI and T1D. Furthermore, the effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections on the development of IA/T1D remains undeciphered. Here, we provide a comprehensive overview of the evidence to date, implicating RTIs (viral and non-viral) as potential risk factors for IA/T1D.

Progression of type 1 diabetes from latency to symptomatic disease is predicted by distinct autoimmune trajectories

Development of islet autoimmunity precedes the onset of type 1 diabetes in children, however, the presence of autoantibodies does not necessarily lead to manifest disease and the onset of clinical symptoms is hard to predict. Here we show, by longitudinal sampling of islet autoantibodies (IAb) to insulin, glutamic acid decarboxylase and islet antigen-2 that disease progression follows distinct trajectories. Of the combined Type 1 Data Intelligence cohort of 24662 participants, 2172 individuals fulfill the criteria of two or more follow-up visits and IAb positivity at least once, with 652 progressing to type 1 diabetes during the 15 years course of the study. Our Continuous-Time Hidden Markov Models, that are developed to discover and visualize latent states based on the collected data and clinical characteristics of the patients, show that the health state of participants progresses from 11 distinct latent states as per three trajectories (TR1, TR2 and TR3), with associated 5-year cumulative diabetes-free survival of 40% (95% confidence interval [CI], 35% to 47%), 62% (95% CI, 57% to 67%), and 88% (95% CI, 85% to 91%), respectively (p < 0.0001). Age, sex, and HLA-DR status further refine the progression rates within trajectories, enabling clinically useful prediction of disease onset.

Presence of islet autoantibodies precedes the onset of type 1 diabetes but it does not predict whether and how fast symptomatic disease appears. Here authors present a model to predict and visualize progression to diabetes by using a large longitudinal data set on autoantibodies and clinical parameters as input.

Frailty modeling under a selective sampling protocol: an application to type 1 diabetes related autoantibodies

In studies following selective sampling protocols for secondary outcomes, conventional analyses regarding their appearance could provide misguided information. In the large type 1 diabetes prevention and prediction (DIPP) cohort study monitoring type 1 diabetes-associated autoantibodies, we propose to model their appearance via a multivariate frailty model, which incorporates a correlation component that is important for unbiased estimation of the baseline hazards under the selective sampling mechanism. As further advantages, the frailty model allows for systematic evaluation of the association and the differences in regression parameters among the autoantibodies. We demonstrate the properties of the model by a simulation study and the analysis of the autoantibodies and their association with background factors in the DIPP study, in which we found that high genetic risk is associated with the appearance of all the autoantibodies, whereas the association with sex and urban municipality was evident for IA-2A and IAA autoantibodies.

Viruses and Type 1 Diabetes: From Enteroviruses to the Virome

For over a century, viruses have left a long trail of evidence implicating them as frequent suspects in the development of type 1 diabetes. Through vigorous interrogation of viral infections in individuals with islet autoimmunity and type 1 diabetes using serological and molecular virus detection methods, as well as mechanistic studies of virus-infected human pancreatic β-cells, the prime suspects have been narrowed down to predominantly human enteroviruses. Here, we provide a comprehensive overview of evidence supporting the hypothesised role of enteroviruses in the development of islet autoimmunity and type 1 diabetes. We also discuss concerns over the historical focus and investigation bias toward enteroviruses and summarise current unbiased efforts aimed at characterising the complete population of viruses (the “virome”) contributing early in life to the development of islet autoimmunity and type 1 diabetes. Finally, we review the range of vaccine and antiviral drug candidates currently being evaluated in clinical trials for the prevention and potential treatment of type 1 diabetes.

Maternal food consumption during late pregnancy and offspring risk of islet autoimmunity and type 1 diabetes

AIMS/HYPOTHESIS

We aimed to investigate the association between maternal consumption of gluten-containing foods and other selected foods during late pregnancy and offspring risk of islet autoimmunity (IA) and type 1 diabetes in The Environmental Determinants of Diabetes in the Young (TEDDY) study.

METHODS

The TEDDY study recruited children at high genetic risk for type 1 diabetes at birth, and prospectively follows them for the development of IA and type 1 diabetes (n = 8556). A questionnaire on the mother's diet in late pregnancy was completed by 3-4 months postpartum. The maternal daily intake was estimated from a food frequency questionnaire for eight food groups: gluten-containing foods, non-gluten cereals, fresh milk, sour milk, cheese products, soy products, lean/medium-fat fish and fatty fish. For each food, we described the distribution of maternal intake among the four participating countries in the TEDDY study and tested the association of tertile of maternal food consumption with risk of IA and type 1 diabetes using forward selection time-to-event Cox regression.

RESULTS

By 28 February 2019, 791 cases of IA and 328 cases of type 1 diabetes developed in TEDDY. There was no association between maternal late-pregnancy consumption of gluten-containing foods or any of the other selected foods and risk of IA, type 1 diabetes, insulin autoantibody-first IA or GAD autoantibody-first IA (all p ≥ 0.01). Maternal gluten-containing food consumption in late pregnancy was higher in Sweden (242 g/day), Germany (247 g/day) and Finland (221 g/day) than in the USA (199 g/day) (pairwise p < 0.05).

CONCLUSIONS/INTERPRETATION

Maternal food consumption during late pregnancy was not associated with offspring risk for IA or type 1 diabetes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00279318.

Etiology of Autoimmune Islet Disease: Timing Is Everything

Life is about timing. -Carl LewisThe understanding of autoimmune type 1 diabetes is increasing, and examining etiology separate from pathogenesis has become crucial. The components to explain type 1 diabetes development have been known for some time. The strong association with HLA has been researched for nearly 50 years. Genome-wide association studies added another 60+ non-HLA genetic factors with minor contribution to risk. Insulitis has long been known to be present close to clinical diagnosis. T and B cells recognizing β-cell autoantigens are detectable prior to diagnosis and in newly diagnosed patients. Islet autoantibody tests against four major autoantigens have been standardized and used as biomarkers of islet autoimmunity. However, to clarify the etiology would require attention to time. Etiology may be defined as the cause of a disease (i.e., type 1 diabetes) or abnormal condition (i.e., islet autoimmunity). Timing is everything, as neither the prodrome of islet autoimmunity nor the clinical onset of type 1 diabetes tells us much about the etiology. Rather, the islet autoantibody that appears first and persists would mark the diagnosis of an autoimmune islet disease (AID). Events after the diagnosis of AID would represent the pathogenesis. Several islet autoantibodies without (stage 1) or with impaired glucose tolerance (stage 2) or with symptoms (stage 3) would define the pathogenesis culminating in clinical type 1 diabetes. Etiology would be about the timing of events that take place before the first-appearing islet autoantibody.

First-appearing islet autoantibodies for type 1 diabetes in young children: maternal life events during pregnancy and the child's genetic risk

AIMS/HYPOTHESIS

Psychological stress has long been considered a possible trigger of type 1 diabetes, although prospective studies examining the link between psychological stress or life events during pregnancy and the child's type 1 diabetes risk are rare. The objective of this study was to examine the association between life events during pregnancy and first-appearing islet autoantibodies (IA) in young children, conditioned by the child's type 1 diabetes-related genetic risk.

METHODS

The IA status of 7317 genetically at-risk The Environmental Determinants of Diabetes in the Young (TEDDY) participants was assessed every 3 months from 3 months to 4 years, and bi-annually thereafter. Reports of major life events during pregnancy were collected at study inception when the child was 3 months of age and placed into one of six categories. Life events during pregnancy were examined for association with first-appearing insulin (IAA) (N = 222) or GAD (GADA) (N = 209) autoantibodies in the child until 6 years of age using proportional hazard models. Relative excess risk due to interaction (RERI) by the child's HLA-DR and SNP profile was estimated.

RESULTS

Overall, 65% of mothers reported a life event during pregnancy; disease/injury (25%), serious interpersonal (28%) and job-related (25%) life events were most common. The association of life events during pregnancy differed between IAA and GADA as the first-appearing autoantibody. Serious interpersonal life events correlated with increased risk of GADA-first only in HLA-DR3 children with the BACH2-T allele (HR 2.28, p < 0.0001), an additive interaction (RERI 1.87, p = 0.0004). Job-related life events were also associated with increased risk of GADA-first among HLA-DR3/4 children (HR 1.53, p = 0.04) independent of serious interpersonal life events (HR 1.90, p = 0.002), an additive interaction (RERI 1.19, p = 0.004). Job-related life events correlated with reduced risk of IAA-first (HR 0.55, p = 0.004), particularly in children with the BTNL2-GG allele (HR 0.48; 95% CI 0.31, 0.76).

CONCLUSIONS/INTERPRETATION

Specific life events during pregnancy are differentially related to IAA vs GADA as first-appearing IA and interact with different HLA and non-HLA genetic factors, supporting the concept of different endotypes underlying type 1 diabetes. However, the mechanisms underlying these associations remain to be discovered. Life events may be markers for other yet-to-be-identified factors important to the development of first-appearing IA.

The clinical consequences of heterogeneity within and between different diabetes types

Advances in molecular methods and the ability to share large population-based datasets are uncovering heterogeneity within diabetes types, and some commonalities between types. Within type 1 diabetes, endotypes have been discovered based on demographic (e.g. age at diagnosis, race/ethnicity), genetic, immunological, histopathological, metabolic and/or clinical course characteristics, with implications for disease prediction, prevention, diagnosis and treatment. In type 2 diabetes, the relative contributions of insulin resistance and beta cell dysfunction are heterogeneous and relate to demographics, genetics and clinical characteristics, with substantial interaction from environmental exposures. Investigators have proposed approaches that vary from simple to complex in combining these data to identify type 2 diabetes clusters relevant to prognosis and treatment. Advances in pharmacogenetics and pharmacodynamics are also improving treatment. Monogenic diabetes is a prime example of how understanding heterogeneity within diabetes types can lead to precision medicine, since phenotype and treatment are affected by which gene is mutated. Heterogeneity also blurs the classic distinctions between diabetes types, and has led to the definition of additional categories, such as latent autoimmune diabetes in adults, type 1.5 diabetes and ketosis-prone diabetes. Furthermore, monogenic diabetes shares many features with type 1 and type 2 diabetes, which make diagnosis difficult. These challenges to the current classification framework in adult and paediatric diabetes require new approaches. The 'palette model' and the 'threshold hypothesis' can be combined to help explain the heterogeneity within and between diabetes types. Leveraging such approaches for therapeutic benefit will be an important next step for precision medicine in diabetes. Graphical abstract.

Hierarchical Order of Distinct Autoantibody Spreading and Progression to Type 1 Diabetes in the TEDDY Study

OBJECTIVE

The first-appearing β-cell autoantibody has been shown to influence risk of type 1 diabetes (T1D). Here, we assessed the risk of autoantibody spreading to the second-appearing autoantibody and further progression to clinical disease in The Environmental Determinants of Diabetes in the Young (TEDDY) study.

RESEARCH DESIGN AND METHODS

Eligible children with increased HLA-DR-DQ genetic risk for T1D were followed quarterly from age 3 months up to 15 years for development of a single first-appearing autoantibody (GAD antibody [GADA], insulin autoantibody [IAA], or insulinoma antigen-2 autoantibody [IA-2A]) and subsequent development of a single second-appearing autoantibody and progression to T1D. Autoantibody positivity was defined as positivity for a specific autoantibody at two consecutive visits confirmed in two laboratories. Zinc transporter 8 autoantibody (ZnT8A) was measured in children who developed another autoantibody.

RESULTS

There were 608 children who developed a single first-appearing autoantibody (IAA, n = 282, or GADA, n = 326) with a median follow-up of 12.5 years from birth. The risk of a second-appearing autoantibody was independent of GADA versus IAA as a first-appearing autoantibody (adjusted hazard ratio [HR] 1.12; 95% CI 0.88-1.42; P = 0.36). Second-appearing GADA, IAA, IA-2A, or ZnT8A conferred an increased risk of T1D compared with children who remained positive for a single autoantibody, e.g., IAA or GADA second (adjusted HR 6.44; 95% CI 3.78-10.98), IA-2A second (adjusted HR 16.33; 95% CI 9.10-29.29; P < 0.0001), or ZnT8A second (adjusted HR 5.35; 95% CI 2.61-10.95; P < 0.0001). In children who developed a distinct second autoantibody, IA-2A (adjusted HR 3.08; 95% CI 2.04-4.65; P < 0.0001) conferred a greater risk of progression to T1D as compared with GADA or IAA. Additionally, both a younger initial age at seroconversion and shorter time to the development of the second-appearing autoantibody increased the risk for T1D.

CONCLUSIONS

The hierarchical order of distinct autoantibody spreading was independent of the first-appearing autoantibody type and was age-dependent and augmented the risk of progression to T1D.

Plasma ascorbic acid and the risk of islet autoimmunity and type 1 diabetes: the TEDDY study

AIMS/HYPOTHESIS

We studied the association of plasma ascorbic acid with the risk of developing islet autoimmunity and type 1 diabetes and examined whether SNPs in vitamin C transport genes modify these associations. Furthermore, we aimed to determine whether the SNPs themselves are associated with the risk of islet autoimmunity or type 1 diabetes.

METHODS

We used a risk set sampled nested case-control design within an ongoing international multicentre observational study: The Environmental Determinants of Diabetes in the Young (TEDDY). The TEDDY study followed children with increased genetic risk from birth to endpoints of islet autoantibodies (350 cases, 974 controls) and type 1 diabetes (102 cases, 282 controls) in six clinical centres. Control participants were matched for family history of type 1 diabetes, clinical centre and sex. Plasma ascorbic acid concentration was measured at ages 6 and 12 months and then annually up to age 6 years. SNPs in vitamin C transport genes were genotyped using the ImmunoChip custom microarray. Comparisons were adjusted for HLA genotypes and for background population stratification.

RESULTS

Childhood plasma ascorbic acid (mean ± SD 10.76 ± 3.54 mg/l in controls) was inversely associated with islet autoimmunity risk (adjusted OR 0.96 [95% CI 0.92, 0.99] per +1 mg/l), particularly islet autoimmunity, starting with insulin autoantibodies (OR 0.94 [95% CI 0.88, 0.99]), but not with type 1 diabetes risk (OR 0.93 [95% Cl 0.86, 1.02]). The SLC2A2 rs5400 SNP was associated with increased risk of type 1 diabetes (OR 1.77 [95% CI 1.12, 2.80]), independent of plasma ascorbic acid (OR 0.92 [95% CI 0.84, 1.00]).

CONCLUSIONS/INTERPRETATION

Higher plasma ascorbic acid levels may protect against islet autoimmunity in children genetically at risk for type 1 diabetes. Further studies are warranted to confirm these findings.

DATA AVAILABILITY

The datasets generated and analysed during the current study will be made available in the NIDDK Central Repository at https://www.niddkrepository.org/studies/teddy.

Early-life factors contributing to type 1 diabetes

The incidence of type 1 diabetes has increased since the mid-twentieth century at a rate that is too rapid to be attributed to genetic predisposition alone. While the disease can occur at any age, mounting evidence from longitudinal cohort studies of at-risk children indicate that type 1 diabetes associated autoantibodies can be present from the first year of life, and that those who develop type 1 diabetes at a young age have a more aggressive form of the disease. This corroborates the hypothesis that environmental exposures in early life contribute to type 1 diabetes risk, whether related to maternal influences on the fetus during pregnancy, neonatal factors or later effects during infancy and early childhood. Studies to date show a range of environmental triggers acting at different time points, suggesting a multifactorial model of genetic and environmental factors in the pathogenesis of type 1 diabetes, which integrally involves a dialogue between the immune system and pancreatic beta cells. For example, breastfeeding may have a weak protective effect on type 1 diabetes risk, while use of an extensively hydrolysed formula does not. Additionally, exposure to being overweight pre-conception, both in utero and postnatally, is associated with increased risk of type 1 diabetes. Epidemiological, clinical and pathological studies in humans support a role for viral infections, particularly enteroviruses, in type 1 diabetes, but definitive proof is lacking. The role of the early microbiome and its perturbations in islet autoimmunity and type 1 diabetes is the subject of investigation in ongoing cohort studies. Understanding the interactions between environmental exposures and the human genome and metagenome, particularly across ethnically diverse populations, will be critical for the development of future strategies for primary prevention of type 1 diabetes.

Maternal dietary supplement use and development of islet autoimmunity in the offspring: TEDDY study

OBJECTIVE

We investigated the association between maternal use of vitamin D and omega-3 fatty acids (n-3 FAs) supplements during pregnancy and risk of islet autoimmunity (IA) in the offspring.

METHODS

The Environmental Determinants of Diabetes in the Young (TEDDY) Study is prospectively following 8676 children with increased genetic risk for type 1 diabetes in Finland, Germany, Sweden, and the United States. Blood samples were collected every 3 months between 3 and 48 months of age then every 6 months thereafter to determine persistent IA. Duration, frequency, and supplement dose during pregnancy were recalled by mothers at 3 to 4 months postpartum. Cumulative intakes of supplemental vitamin D and n-3 FAs were analyzed as continuous or binary variables. We applied time-to-event analysis to study the association between maternal supplement use and IA, adjusting for country, human leukocyte antigen-DR-DQ genotype, family history of type 1 diabetes and sex. Secondary outcomes included insulin autoantibodies (IAA) or glutamic acid decarboxylase (GADA) as the first appearing autoantibody.

RESULTS

As of February 2018, there were 747 (9.0%) children with IA. Vitamin D supplement intake during pregnancy (any vs none) was not associated with risk for IA (hazard ratio [HR] 1.11; 95% confidence interval [CI] 0.94, 1.31); neither was cumulative vitamin D supplement intake. Supplemental n-3 FA intake was similarly not associated with IA risk (HR: 1.19, 95% CI 0.98, 1.45). Similar lack of association was observed for either IAA or GADA as the first appearing autoantibody.

CONCLUSIONS

The TEDDY cohort showed no evidence of benefit regarding IA risk for vitamin D or n-3 FA supplementation during pregnancy.

Time-Resolved Autoantibody Profiling Facilitates Stratification of Preclinical Type 1 Diabetes in Children

Progression to clinical type 1 diabetes varies among children who develop β-cell autoantibodies. Differences in autoantibody patterns could relate to disease progression and etiology. Here we modeled complex longitudinal autoantibody profiles by using a novel wavelet-based algorithm. We identified clusters of similar profiles associated with various types of progression among 600 children from The Environmental Determinants of Diabetes in the Young (TEDDY) birth cohort study; these children developed persistent insulin autoantibodies (IAA), GAD autoantibodies (GADA), insulinoma-associated antigen 2 autoantibodies (IA-2A), or a combination of these, and they were followed up prospectively at 3- to 6-month intervals (median follow-up 6.5 years). Children who developed multiple autoantibody types (n = 370) were clustered, and progression from seroconversion to clinical diabetes within 5 years ranged between clusters from 6% (95% CI 0, 17.4) to 84% (59.2, 93.6). Children who seroconverted early in life (median age <2 years) and developed IAA and IA-2A that were stable-positive on follow-up had the highest risk of diabetes, and this risk was unaffected by GADA status. Clusters of children who lacked stable-positive GADA responses contained more boys and lower frequencies of the HLA-DR3 allele. Our novel algorithm allows refined grouping of β-cell autoantibody-positive children who distinctly progressed to clinical type 1 diabetes, and it provides new opportunities in searching for etiological factors and elucidating complex disease mechanisms.

The Environmental Determinants of Diabetes in the Young (TEDDY) Study: 2018 Update

PURPOSE OF REVIEW

The environmental triggers of islet autoimmunity leading to type 1 diabetes (T1D) need to be elucidated to inform primary prevention. The Environmental Determinants of Diabetes in the Young (TEDDY) Study follows from birth 8676 children with T1D risk HLA-DR-DQ genotypes in the USA, Finland, Germany, and Sweden. Most study participants (89%) have no first-degree relative with T1D. The primary outcomes include the appearance of one or more persistent islet autoantibodies (islet autoimmunity, IA) and clinical T1D.

RECENT FINDINGS

As of February 28, 2018, 769 children had developed IA and 310 have progressed to T1D. Secondary outcomes include celiac disease and autoimmune thyroid disease. While the follow-up continues, TEDDY has already evaluated a number of candidate environmental triggers, including infections, probiotics, micronutrient, and microbiome. TEDDY results suggest that there are multiple pathways leading to the destruction of pancreatic beta-cells. Ongoing measurements of further specific exposures, gene variants, and gene-environment interactions and detailed "omics" studies will provide novel information on the pathogenesis of T1D.

Maternal infection during pregnancy and type 1 diabetes mellitus in offspring: a systematic review and meta-analysis

Previous studies have demonstrated that type 1 diabetes mellitus (T1DM) could be triggered by an early childhood infection. Whether maternal infection during pregnancy is associated with T1DM in offspring is unknown. Therefore, we aimed to study the association using a systematic review and meta-analysis. Eighteen studies including 4304 cases and 25 846 participants were enrolled in this meta-analysis. Odds ratios (ORs) and 95% confidence intervals (CIs) were synthesised using random-effects models. Subgroup analyses and sensitivity analyses were conducted to assess the robustness of associations. Overall, the pooled analysis yielded a statistically significant association between maternal infection during pregnancy and childhood T1DM (OR 1.31, 95% CI 1.07-1.62). Furthermore, six studies that tested maternal enterovirus infection showed a pooled OR of 1.54 (95% CI 1.05-2.27). Heterogeneity from different studies was evident (I2 = 70.1%, P < 0.001) and was mainly attributable to the different study designs, ascertaining methods and sample size among different studies. This study provides evidence for an association between maternal infection during pregnancy and childhood T1DM.

Identification of non-HLA genes associated with development of islet autoimmunity and type 1 diabetes in the prospective TEDDY cohort

Traditional linkage analysis and genome-wide association studies have identified HLA and a number of non-HLA genes as genetic factors for islet autoimmunity (IA) and type 1 diabetes (T1D). However, the relative risk associated with previously identified non-HLA genes is usually very small as measured in cases/controls from mixed populations. Genetic associations for IA and T1D may be more accurately assessed in prospective cohorts. In this study, 5806 subjects from the TEDDY (The Environmental Determinants of Diabetes in the Young) study, an international prospective cohort study, were genotyped for 176,586 SNPs on the ImmunoChip. Cox proportional hazards analyses were performed to discover the SNPs associated with the risk for IA, T1D, or both. Three regions were associated with the risk of developing any persistent confirmed islet autoantibody: one known region near SH2B3 (HR = 1.35, p = 3.58 × 10-7) with Bonferroni-corrected significance and another known region near PTPN22 (HR = 1.46, p = 2.17 × 10-6) and one novel region near PPIL2 (HR = 2.47, p = 9.64 × 10-7) with suggestive evidence (p < 10-5). Two known regions (PTPN22: p = 2.25 × 10-6, INS; p = 1.32 × 10-7) and one novel region (PXK/PDHB: p = 8.99 × 10-6) were associated with the risk for multiple islet autoantibodies. First appearing islet autoantibodies differ with respect to association. Two regions (INS: p = 5.67 × 10-6 and TTC34/PRDM16: 6.45 × 10-6) were associated if the fist appearing autoantibody was IAA and one region (RBFOX1: p = 8.02 × 10-6) was associated if the first appearing autoantibody was GADA. The analysis of T1D identified one region already known to be associated with T1D (INS: p = 3.13 × 10-7) and three novel regions (RNASET2, PLEKHA1, and PPIL2; 5.42 × 10-6 > p > 2.31 × 10-6). These results suggest that a number of low frequency variants influence the risk of developing IA and/or T1D and these variants can be identified by large prospective cohort studies using a survival analysis approach.