Early determinants of type 1 diabetes: experience from the BABYDIAB and BABYDIET studies

Maternal type 1 diabetes and relative protection against offspring transmission

Type 1 diabetes is around twice as common in the offspring of men with type 1 diabetes than in the offspring of women with type 1 diabetes, but the reasons for this difference are unclear. This Review summarises the evidence on the rate of transmission of type 1 diabetes to the offspring of affected fathers compared with affected mothers. The findings of nine major studies are presented, describing the magnitude of the effect observed and the relative strengths and weaknesses of these studies. This Review also explores possible underlying mechanisms for this effect, such as genetic mechanisms (eg, the selective loss of fetuses with high-risk genes in mothers with type 1 diabetes, preferential transmission of susceptibility genes from fathers, and parent-of-origin effects influencing gene expression), environmental exposures (eg, exposure to maternal hyperglycaemia, exogenous insulin exposure, and transplacental antibody transfer), and maternal microchimerism. Understanding why type 1 diabetes is more common in the offspring of men versus women with type 1 diabetes will help in the identification of individuals at high risk of the disease and can pave the way in the development of interventions that mimic the protective elements of maternal type 1 diabetes to reduce the risk of disease in individuals at high risk.

Type 1 diabetes mellitus: Inflammation, mitophagy, and mitochondrial function

Type 1 diabetes mellitus (T1DM) is a T-cell-mediated autoimmune disease characterized by the damage of insulin-secreting β-cells in the pancreatic islets of Langerhans. To date, its etiology is not fully understood, despite decades of active search for root causes, and that underlines the complexity of the disease pathogenesis. It was found that mitophagy plays a regulatory role in the development of autoimmune response during T1DM pathogenesis by preventing the accumulation of defective/dysfunctional mitochondria in pancreatic cells. Mitochondrial dysfunction due to impaired mitophagy with the release of mitochondrial reactive oxygen species (mtROS) and mitochondrial DNA (mtDNA) contributes to initiating an inflammatory response by elevating pro-inflammatory cytokines and interacting with receptors like those involved in the pathogen-associated response. Moreover, mtROS and mtDNA activate pathways leading to the development of chronic inflammation, which is tightly implicated in T1DM autoimmunity. In this review, we summarized the evidence highlighting the functional role of mitophagy and mitochondria in the development of immune response and chronic inflammation during T1DM pathogenesis. Several anti-inflammatory and mitophagy-related treatment options have been explored.

Stratifying risk for onset of type 1 diabetes using islet autoantibody trajectory clustering

AIMS/HYPOTHESIS

Islet autoantibodies can be detected prior to the onset of type 1 diabetes and are important tools for aetiologic studies, prevention trials and disease screening. Current risk stratification models rely on the positivity status of islet autoantibodies alone, but additional autoantibody characteristics may be important for understanding disease onset. This work aimed to determine if a data-driven model incorporating characteristics of islet autoantibody development, including timing, type and titre, could stratify risk for type 1 diabetes onset.

METHODS

Data on autoantibodies against GAD (GADA), tyrosine phosphatase islet antigen-2 (IA-2A) and insulin (IAA) were obtained for 1,415 children enrolled in The Environmental Determinants of Diabetes in the Young study with at least one positive autoantibody measurement from years 1 to 12 of life. Unsupervised machine learning algorithms were trained to identify clusters of autoantibody development based on islet autoantibody timing, type and titre. Risk for type 1 diabetes across each identified cluster was evaluated using time-to-event analysis.

RESULTS

We identified 2-4 clusters in each year cohort that differed by autoantibody timing, titre and type. During the first 3 years of life, risk for type 1 diabetes onset was driven by membership in clusters with high titres of all three autoantibodies (1-year risk: 20.87-56.25%, 5-year risk: 67.73-69.19%). Type 1 diabetes risk transitioned to type-specific titres during ages 4 to 8, as clusters with high titres of IA-2A (1-year risk: 20.88-28.93%, 5-year risk: 62.73-78.78%) showed faster progression to diabetes compared with high titres of GADA (1-year risk: 4.38-6.11%, 5-year risk: 25.06-31.44%). The importance of high GADA titres decreased during ages 9 to 12, with clusters containing high titres of IA-2A alone (1-year risk: 14.82-30.93%) or both GADA and IA-2A (1-year risk: 8.27-25.00%) demonstrating increased risk.

CONCLUSIONS/INTERPRETATION

This unsupervised machine learning approach provides a novel tool for stratifying risk for type 1 diabetes onset using multiple autoantibody characteristics. These findings suggest that age-dependent changes in IA-2A titres modulate risk for type 1 diabetes onset across 12 years of life. Overall, this work supports incorporation of islet autoantibody timing, type and titre in risk stratification models for aetiologic studies, prevention trials and disease screening.

Gut microbiome in type 1 diabetes: the immunological perspective

INTRODUCTION

Type 1 diabetes (T1D) is a prevalent, and yet uncurable, autoimmune disease targeting insulin-producing pancreatic β-cells. Despite a known genetic component in T1D onset, genetics alone cannot explain the alarming worldwide rise in T1D incidence, which is attributed to a growing impact of environmental factors, including perturbations of the gut microbiome.

AREAS COVERED

Intestinal commensal bacteria plays a crucial role in host physiology in health and disease by regulating endocrine and immune functions. An aberrant gut microbiome structure and metabolic function have been documented prior and during T1D onset. In this review, we summarize and discuss the current studies depicting the taxonomic profile and role of the gut microbial communities in murine models of T1D, diabetic patients and human interventional trials.

EXPERT OPINION

Compelling evidence have shown that the intestinal microbiota is instrumental in driving differentiation and functions of immune cells. Therefore, any alterations in the intestinal microbiome composition or microbial metabolite production, particularly early in life, may impact disease susceptibility and amplify inflammatory responses and hence accelerate the course of T1D pathogenesis.

Use of a glycomics array to establish the anti-carbohydrate antibody repertoire in type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune disease, characterized by the presence of autoantibodies to protein and non-protein antigens. Here we report the identification of specific anti-carbohydrate antibodies (ACAs) that are associated with pathogenesis and progression to T1D. We compare circulatory levels of ACAs against 202 glycans in a cross-sectional cohort of T1D patients (n = 278) and healthy controls (n = 298), as well as in a longitudinal cohort (n = 112). We identify 11 clusters of ACAs associated with glycan function class. Clusters enriched for aminoglycosides, blood group A and B antigens, glycolipids, ganglio-series, and O-linked glycans are associated with progression to T1D. ACAs against gentamicin and its related structures, G418 and sisomicin, are also associated with islet autoimmunity. ACAs improve discrimination of T1D status of individuals over a model with only clinical variables and are potential biomarkers for T1D.

Identifying the lungs as a susceptible site for allele-specific regulatory changes associated with type 1 diabetes risk

Type 1 diabetes (T1D) etiology is complex. We developed a machine learning approach that ranked the tissue-specific transcription regulatory effects for T1D SNPs and estimated their relative contributions to conversion to T1D by integrating case and control genotypes (Wellcome Trust Case Control Consortium and UK Biobank) with tissue-specific expression quantitative trait loci (eQTL) data. Here we show an eQTL (rs6679677) associated with changes to AP4B1-AS1 transcript levels in lung tissue makes the largest gene regulatory contribution to the risk of T1D development. Luciferase reporter assays confirmed allele-specific enhancer activity for the rs6679677 tagged locus in lung epithelial cells (i.e. A549 cells; C > A reduces expression, p = 0.005). Our results identify tissue-specific eQTLs for SNPs associated with T1D. The strongest tissue-specific eQTL effects were in the lung and may help explain associations between respiratory infections and risk of islet autoantibody seroconversion in young children.

The Multifactorial Progression from the Islet Autoimmunity to Type 1 Diabetes in Children

Type 1 Diabetes (T1D) results from autoimmune destruction of insulin producing pancreatic ß-cells. This disease, with a peak incidence in childhood, causes the lifelong need for insulin injections and necessitates careful monitoring of blood glucose levels. However, despite the current insulin therapies, it still shortens life expectancy due to complications affecting multiple organs. Recently, the incidence of T1D in childhood has increased by 3-5% per year in most developed Western countries. The heterogeneity of the disease process is supported by the findings of follow-up studies started early in infancy. The development of T1D is usually preceded by the appearance of autoantibodies targeted against antigens expressed in the pancreatic islets. The risk of T1D increases significantly with an increasing number of positive autoantibodies. The order of autoantibody appearance affects the disease risk. Genetic susceptibility, mainly defined by the human leukocyte antigen (HLA) class II gene region and environmental factors, is important in the development of islet autoimmunity and T1D. Environmental factors, mainly those linked to the changes in the gut microbiome as well as several pathogens, especially viruses, and diet are key modulators of T1D. The aim of this paper is to expand the understanding of the aetiology and pathogenesis of T1D in childhood by detailed description and comparison of factors affecting the progression from the islet autoimmunity to T1D in children.

Metabolic alterations in immune cells associate with progression to type 1 diabetes

AIMS/HYPOTHESIS

Previous metabolomics studies suggest that type 1 diabetes is preceded by specific metabolic disturbances. The aim of this study was to investigate whether distinct metabolic patterns occur in peripheral blood mononuclear cells (PBMCs) of children who later develop pancreatic beta cell autoimmunity or overt type 1 diabetes.

METHODS

In a longitudinal cohort setting, PBMC metabolomic analysis was applied in children who (1) progressed to type 1 diabetes (PT1D, n = 34), (2) seroconverted to ≥1 islet autoantibody without progressing to type 1 diabetes (P1Ab, n = 27) or (3) remained autoantibody negative during follow-up (CTRL, n = 10).

RESULTS

During the first year of life, levels of most lipids and polar metabolites were lower in the PT1D and P1Ab groups compared with the CTRL group. Pathway over-representation analysis suggested alanine, aspartate, glutamate, glycerophospholipid and sphingolipid metabolism were over-represented in PT1D. Genome-scale metabolic models of PBMCs during type 1 diabetes progression were developed by using publicly available transcriptomics data and constrained with metabolomics data from our study. Metabolic modelling confirmed altered ceramide pathways, known to play an important role in immune regulation, as specifically associated with type 1 diabetes progression.

CONCLUSIONS/INTERPRETATION

Our data suggest that systemic dysregulation of lipid metabolism, as observed in plasma, may impact the metabolism and function of immune cells during progression to overt type 1 diabetes.

DATA AVAILABILITY

The GEMs for PBMCs have been submitted to BioModels (www.ebi.ac.uk/biomodels/), under accession number MODEL1905270001. The metabolomics datasets and the clinical metadata generated in this study were submitted to MetaboLights (https://www.ebi.ac.uk/metabolights/), under accession number MTBLS1015.

The Challenges of Identifying Environmental Determinants of Type 1 Diabetes: In Search of the Holy Grail

Type 1 diabetes is the result of autoimmune-mediated destruction and inflammation of the insulin-producing β-cells of the pancreas. The excess morbidity and mortality from its complications coupled with its increasing incidence emphasize the importance to better understand the etiology of this condition. It has a strong genetic component, but a genetic predisposition is not the sole contributor to disease development as only 30% to 50% of identical twins both develop the disease. In addition, there are multiple lines of evidence to support that environmental factors contribute to the pathogenesis of type 1 diabetes. Environmental risk factors that have been proposed include infections, dietary factors, air pollution, vaccines, location of residence, childhood obesity, family environment and stress. Researchers have conducted many observational studies to identify and characterize these potential environmental factors, but findings have been inconsistent or inconclusive. Many studies have had inherent methodological issues in recruitment, participation, defining cases and exposures, and/or data analysis which may limit the interpretability of findings. Identifying and addressing these limitations may allow for greatly needed advances in our understanding of type 1 diabetes. As such, the purpose of this article is to review and discuss the limitations of observational studies that aim to determine environmental risk factors for type 1 diabetes and propose recommendations to overcome them.

Predicting progression to type 1 diabetes from ages 3 to 6 in islet autoantibody positive TEDDY children

OBJECTIVE

The capacity to precisely predict progression to type 1 diabetes (T1D) in young children over a short time span is an unmet need. We sought to develop a risk algorithm to predict progression in children with high-risk human leukocyte antigen (HLA) genes followed in The Environmental Determinants of Diabetes in the Young (TEDDY) study.

METHODS

Logistic regression and 4-fold cross-validation examined 38 candidate predictors of risk from clinical, immunologic, metabolic, and genetic data. TEDDY subjects with at least one persistent, confirmed autoantibody at age 3 were analyzed with progression to T1D by age 6 serving as the primary endpoint. The logistic regression prediction model was compared to two non-statistical predictors, multiple autoantibody status, and presence of insulinoma-associated-2 autoantibodies (IA-2A).

RESULTS

A total of 363 subjects had at least one autoantibody at age 3. Twenty-one percent of subjects developed T1D by age 6. Logistic regression modeling identified 5 significant predictors - IA-2A status, hemoglobin A1c, body mass index Z-score, single-nucleotide polymorphism rs12708716_G, and a combination marker of autoantibody number plus fasting insulin level. The logistic model yielded a receiver operating characteristic area under the curve (AUC) of 0.80, higher than the two other predictors; however, the differences in AUC, sensitivity, and specificity were small across models.

CONCLUSIONS

This study highlights the application of precision medicine techniques to predict progression to diabetes over a 3-year window in TEDDY subjects. This multifaceted model provides preliminary improvement in prediction over simpler prediction tools. Additional tools are needed to maximize the predictive value of these approaches.

Incidence and trend of type 1 diabetes and the underlying environmental determinants

A wealth of epidemiological studies concerning the distribution of type 1 diabetes (T1D) around the world have pointed to the appreciable variation in the incidence of T1D among disparate age groups, ethnicities, and geographical locations. On the whole, the incidence of childhood T1D has been on the rise, and a plausible inverse relationship between the initial incidence rate and the following annual increase in incidence has been raised. Countries that used to exhibit lower incidences tend to have steep annual increase whereas those with already-established high incidences are more likely to show a modest increase or even stabilization in T1D incidence. Environmental agents considered responsible for the current evolving pattern of T1D incidence will be detailed, mainly including the increasing prevalence of childhood obesity, viral infections in a chronic manner, maternal-child interaction such as breastfeeding, and latitude-ultraviolet B-vitamin D pathway. Certain rationale has been put forward in an attempt to explain the potential association between environmental agents and development of T1D. For instance, accelerator hypothesis regards insulin resistance as the promoter of earlier disease onset in obese children whereas the negative correlation of microbial infections in background populations with incidence of T1D represents the basic component of the hygiene hypothesis. Further investigations are still warranted to verify these theories across multiple ethnic groups and to identify additional contributors to the variation in T1D incidence.

Immune Mechanisms and Pathways Targeted in Type 1 Diabetes

PURPOSE OF REVIEW

The immunosuppressive agent cyclosporine was first reported to lower daily insulin dose and improve glycemic control in patients with new-onset type 1 diabetes (T1D) in 1984. While renal toxicity limited cyclosporine's extended use, this observation ignited collaborative efforts to identify immunotherapeutic agents capable of safely preserving β cells in patients with or at risk for T1D.

RECENT FINDINGS

Advances in T1D prediction and early diagnosis, together with expanded knowledge of the disease mechanisms, have facilitated trials targeting specific immune cell subsets, autoantigens, and pathways. In addition, clinical responder and non-responder subsets have been defined through the use of metabolic and immunological readouts. Herein, we review emerging T1D biomarkers within the context of recent and ongoing T1D immunotherapy trials. We also discuss responder/non-responder analyses in an effort to identify therapeutic mechanisms, define actionable pathways, and guide subject selection, drug dosing, and tailored combination drug therapy for future T1D trials.

Strength in Numbers: Opportunities for Enhancing the Development of Effective Treatments for Type 1 Diabetes-The TrialNet Experience

The early to mid-1980s were an inflection point in the history of type 1 diabetes research. Two landmark events occurred: the initiation of immune-based interventions seeking to prevent type 1 diabetes and the presentation of an innovative model describing the disorder's natural history. Both formed the basis for hundreds of subsequent studies designed to achieve a dramatic therapeutic goal-a means to prevent and/or reverse type 1 diabetes. However, the need to screen large numbers of individuals and prospectively monitor them using immunologic and metabolic tests for extended periods of time suggested such efforts would require a large collaborative network. Hence, the National Institutes of Health formed the landmark Diabetes Prevention Trial-Type 1 (DPT-1) in the mid-1990s, an effort that led to Type 1 Diabetes TrialNet. TrialNet studies have helped identify novel biomarkers; delineate type 1 diabetes progression, resulting in identification of highly predictable stages defined by the accumulation of autoantibodies (stage 1), dysglycemia (stage 2), and disease meeting clinical criteria for diagnosis (stage 3); and oversee numerous clinical trials aimed at preventing disease progression. Such efforts pave the way for stage-specific intervention trials with improved hope that a means to effectively disrupt the disorder's development will be identified.

A1 beta-casein milk protein and other environmental pre-disposing factors for type 1 diabetes

Globally type 1 diabetes incidence is increasing. It is widely accepted that the pathophysiology of type 1 diabetes is influenced by environmental factors in people with specific human leukocyte antigen haplotypes. We propose that a complex interplay between dietary triggers, permissive gut factors and potentially other influencing factors underpins disease progression. We present evidence that A1 β-casein cows’ milk protein is a primary causal trigger of type 1 diabetes in individuals with genetic risk factors. Permissive gut factors (for example, aberrant mucosal immunity), intervene by impacting the gut’s environment and the mucosal barrier. Various influencing factors (for example, breastfeeding duration, exposure to other dietary triggers and vitamin D) modify the impact of triggers and permissive gut factors on disease. The power of the dominant trigger and permissive gut factors on disease is influenced by timing, magnitude and/or duration of exposure. Within this framework, removal of a dominant dietary trigger may profoundly affect type 1 diabetes incidence. We present epidemiological, animal-based, in vitro and theoretical evidence for A1 β-casein and its β-casomorphin-7 derivative as dominant causal triggers of type 1 diabetes. The effects of ordinary milk containing A1 and A2 β-casein and milk containing only the A2 β-casein warrant comparison in prospective trials.

Role of DNA methylation at the placental RTL1 gene locus in type 1 diabetes

Genome-wide association studies (GWAS) have identified more than 40 T1D loci associated with type 1 diabetes (T1D). How these polymorphisms interact with environmental factors to trigger T1D is unknown, but recent evidence suggests that epigenetic mechanisms could play a role. To begin to explore the contribution of epigenetics to T1D, we have examined DNA methylation in a pilot study of whole blood cells DNA from 10 young T1D patients and 10 young controls. Through the study of >900 000 CG loci across a diverse set of functionally relevant genomic regions using a custom DNA methylation array, we identified 250 T1D-differentially methylated region (DMR) at p < 0.05 and 1 DMR using next a permutation-based multiple testing correction method. This DMR is located in an imprinted region previously associated with T1D on the chromosome 14 that encompasses RTL1 gene and 2 miRNAs (miR136 and miR432). Using pyrosequencing-based bisulfite PCR, we replicated this association in a different and larger set of T1D patients and controls. DNA methylation at this DMR was inversely correlated with RTL1 gene expression and positively correlated with miR136 expression in human placentas. The DMR identified in this study presents suggestive evidence for altered methylation site in T1D and provide a promising new candidate gene. RTL1 is essential for placental permeability function in the mid-to-late fetal stages. We suggest that hypo-methylation could increase the fetal exposure to environmental factors in T1D susceptibility.

Is there a role for gut microbiota in type 1 diabetes pathogenesis?

Type 1 diabetes mellitus (T1D) is an autoimmune disease characterized by insufficient insulin production due to the destruction of insulin secreting β-cells in the Langerhans islets. A variety of factors, including chemicals, viruses, commensal bacteria and diet have been proposed to contribute to the risk of developing the disorder. In the last years, gut microbiota has been proposed as a main factor in T1D pathogenesis. Several alterations of gut microbiota composition were described both in animal model and in humans. The decrease of Firmicutes/Bacteroides ratio was the most frequent pattern described, in particular, in human studies. Furthermore, Bacteroides, Clostridium cluster XIVa, Lactobacillus, Bifidobacterium, and Prevotella relative abundances were different in healthy and affected subjects. Dysbiosis would seem to increase intestinal permeability and thus promote the development of a pro-inflammatory niche that stimulates β-cell autoimmunity in predisposed subjects. Preliminary studies on animal models were realized to investigate the role of gut microbiota modulation as therapy or prevention approach in predisposed animals: promising and stimulating results have been reported. Key message Dietary antigens and microbiota-derived products might act as triggers of T1D by causing a pro-inflammatory and metabolic dysfunctional environment.

The progress and potential of proteomic biomarkers for type 1 diabetes in children

INTRODUCTION

Although it is possible to identify the genetic risk for type 1 diabetes (T1D), it is not possible to predict who will develop the disease. New biomarkers are needed that would help understand the mechanisms of disease onset and when to administer targeted therapies and interventions. Areas covered: An overview is presented of international study efforts towards understanding the cause of T1D, including the collection of several extensive temporal sample series that follow the development of T1D in at risk children. The results of the proteomics analysis of these materials are presented, which have included bodily fluids, such as serum or plasma and urine, as well as tissue samples from the pancreas. Expert commentary: Promising recent reports have indicated detection of early proteomic changes in the serum of patients prior to diagnosis, potentially providing new measures for risk assessment. Similarly, there has been evidence that post-translational modification (PTM) may result in the recognition of islet cell proteins as autoantigens; modified proteins could thus be used as targets for immunomodulation to overcome the threat of the autoimmune response.

Environmental trigger(s) of type 1 diabetes: why so difficult to identify?

Type 1 diabetes (T1D) is one of the most common chronic diseases with childhood onset, and the disease has increased two- to fivefold over the past half century by as yet unknown means. T1D occurs when the body's immune system turns against itself so that, in a very specific and targeted way, it destroys the pancreatic β-cells. T1D results from poorly defined interactions between susceptibility genes and environmental determinants. In contrast to the rapid progress in finding T1D genes, identification and confirmation of environmental determinants remain a formidable challenge. This review article will focus on factors which have to be evaluated and decision to take before starting a new prospective cohort study. Considering all the large ongoing prospective studies, new and more conclusive data than that obtained so far should instead come from international collaboration on the ongoing cohort studies.

Beyond genetics. Influence of dietary factors and gut microbiota on type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune disease ultimately leading to destruction of insulin secreting β-cells in the pancreas. Genetic susceptibility plays an important role in T1D etiology, but even mono-zygotic twins only have a concordance rate of around 50%, underlining that other factors than purely genetic are involved in disease development. Here we review the influence of dietary and environmental factors on T1D development in humans as well as animal models. Even though data are still inconclusive, there are strong indications that gut microbiota dysbiosis plays an important role in T1D development and evidence from animal models suggests that gut microbiota manipulation might prove valuable in future prevention of T1D in genetically susceptible individuals.

The multiple origins of Type 1 diabetes

It is widely accepted that Type 1 diabetes is a complex disease. Genetic predisposition and environmental factors favour the triggering of autoimmune responses against pancreatic β-cells, eventually leading to β-cell destruction. Over 40 susceptibility loci have been identified, many now mapped to known genes, largely supporting a dominant role for an immune-mediated pathogenesis. This role is also supported by the identification of several islet autoantigens and antigen-specific responses in patients with recent onset diabetes and subjects with pre-diabetes. Increasing evidence suggests certain viruses as a common environmental factor, together with diet and the gut microbiome. Inflammation and insulin resistance are emerging as additional cofactors, which might be interrelated with environmental factors. The heterogeneity of disease progression and clinical manifestations is likely a reflection of this multifactorial pathogenesis. So far, clinical trials have been mostly ineffective in delaying progression to overt diabetes in relatives at increased risk, or in reducing further loss of insulin secretion in patients with new-onset diabetes. This limited success may reflect, in part, our incomplete understanding of key pathogenic mechanisms, the lack of truly robust biomarkers of both disease activity and β-cell destruction, and the inability to assess the relative contributions of various pathogenic mechanisms at various time points during the course of the natural history of Type 1 diabetes. Emerging data and a re-evaluation of histopathological, immunological and metabolic findings suggest the hypothesis that unknown mechanisms of β-cell dysfunction may be present at diagnosis, and may contribute to the development of hyperglycaemia and clinical symptoms.

Early childhood infections and the risk of islet autoimmunity: the Diabetes Autoimmunity Study in the Young (DAISY)

OBJECTIVE

Type 1 diabetes is a common chronic childhood disease, and the incidence is increasing globally. Childhood infections are considered a potential environmental trigger of type 1 diabetes. Alternatively, improved hygiene and reduced childhood infections could explain the increase in type 1 diabetes in developed countries. The association of reported illnesses during infancy and later development of islet autoimmunity (IA) were examined in the Diabetes Autoimmunity Study in the Young.

RESEARCH DESIGN AND METHODS

Complete illness interviews through 9 months of age were collected for 1,729 children-1,174 without a family history of type 1 diabetes and 555 with a first-degree relative with type 1 diabetes. Persistent IA was defined as positive antibodies to insulin, glutamic acid decarboxylase, or tyrosine phosphatase on at least two consecutive study visits.

RESULTS

There were 109 children with persistent IA among the 1,729 children with illness records. A greater number of gastrointestinal illnesses were associated with an increased risk of IA, but only among children who were exposed to gluten-containing grains (wheat or barley) either <4 months of age (hazard ratio 1.37 [95% CI 1.22-1.55]; P < 0.0001) or ≥7 months of age (1.12 [1.05-1.19]; P = 0.0005) compared with 4-6 months of age (P for interaction = 0.02). There were no associations of upper respiratory symptoms, respiratory illnesses, or fevers with IA.

CONCLUSIONS

Specific pathogens such as enteroviruses or rotavirus may increase the risk of IA in the presence of existing inflammation induced by diet.

Animal models to study gluten sensitivity

The initial development and maintenance of tolerance to dietary antigens is a complex process that, when prevented or interrupted, can lead to human disease. Understanding the mechanisms by which tolerance to specific dietary antigens is attained and maintained is crucial to our understanding of the pathogenesis of diseases related to intolerance of specific dietary antigens. Two diseases that are the result of intolerance to a dietary antigen are celiac disease (CD) and dermatitis herpetiformis (DH). Both of these diseases are dependent upon the ingestion of gluten (the protein fraction of wheat, rye, and barley) and manifest in the gastrointestinal tract and skin, respectively. These gluten-sensitive diseases are two examples of how devastating abnormal immune responses to a ubiquitous food can be. The well-recognized risk genotype for both is conferred by either of the HLA class II molecules DQ2 or DQ8. However, only a minority of individuals who carry these molecules will develop either disease. Also of interest is that the age at diagnosis can range from infancy to 70-80 years of age. This would indicate that intolerance to gluten may potentially be the result of two different phenomena. The first would be that, for various reasons, tolerance to gluten never developed in certain individuals, but that for other individuals, prior tolerance to gluten was lost at some point after childhood. Of recent interest is the concept of non-celiac gluten sensitivity, which manifests as chronic digestive or neurologic symptoms due to gluten, but through mechanisms that remain to be elucidated. This review will address how animal models of gluten-sensitive disorders have substantially contributed to a better understanding of how gluten intolerance can arise and cause disease.