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.
Genetic risk factors for type 1 diabetes Pociot, Flemming, Prof; Lernmark, Åke, Prof
The Lancet (British edition),
06/2016, Letnik:
387, Številka:
10035
Journal Article
Recenzirano
Summary Type 1 diabetes is diagnosed at the end of a prodrome of β-cell autoimmunity. The disease is most likely triggered at an early age by autoantibodies primarily directed against insulin or ...glutamic acid decarboxylase, or both, but rarely against islet antigen-2. After the initial appearance of one of these autoantibody biomarkers, a second, third, or fourth autoantibody against either islet antigen-2 or the ZnT8 transporter might also appear. The larger the number of β-cell autoantibody types, the greater the risk of rapid progression to clinical onset of diabetes. This association does not necessarily mean that the β-cell autoantibodies are pathogenic, but rather that they represent reproducible biomarkers of the pathogenesis. The primary risk factor for β-cell autoimmunity is genetic, mainly occurring in individuals with either HLA-DR3-DQ2 or HLA-DR4-DQ8 haplotypes, or both, but a trigger from the environment is generally needed. The pathogenesis can be divided into three stages: 1, appearance of β-cell autoimmunity, normoglycaemia, and no symptoms; 2, β-cell autoimmunity, dysglycaemia, and no symptoms; and 3, β-cell autoimmunity, dysglycaemia, and symptoms of diabetes. The genetic association with each one of the three stages can differ. Type 1 diabetes could serve as a disease model for organ-specific autoimmune disorders such as coeliac disease, thyroiditis, and Addison's disease, which show similar early markers of a prolonged disease process before clinical diagnosis.
Underlying type 1 diabetes is a genetic aetiology dominated by the influence of specific HLA haplotypes involving primarily the class II
DR-DQ
region. In genetically predisposed children with the
...DR4-DQ8
haplotype, exogenous factors, yet to be identified, are thought to trigger an autoimmune reaction against insulin, signalled by insulin autoantibodies as the first autoantibody to appear. In children with the
DR3-DQ2
haplotype, the triggering reaction is primarily against GAD signalled by GAD autoantibodies (GADA) as the first-appearing autoantibody. The incidence rate of insulin autoantibodies as the first-appearing autoantibody peaks during the first years of life and declines thereafter. The incidence rate of GADA as the first-appearing autoantibody peaks later but does not decline. The first autoantibody may variably be followed, in an apparently non-HLA-associated pathogenesis, by a second, third or fourth autoantibody. Although not all persons with a single type of autoantibody progress to diabetes, the presence of multiple autoantibodies seems invariably to be followed by loss of functional beta cell mass and eventually by dysglycaemia and symptoms. Infiltration of mononuclear cells in and around the islets appears to be a late phenomenon appearing in the multiple-autoantibody-positive with dysglycaemia. As our understanding of the aetiology and pathogenesis of type 1 diabetes advances, the improved capability for early prediction should guide new strategies for the prevention of type 1 diabetes.
Diabetes is not a single homogeneous disease but composed of many diseases with hyperglycaemia as a common feature. Four factors have, historically, been used to identify this diversity: the age at ...onset; the severity of the disease, i.e. degree of loss of beta cell function; the degree of insulin resistance and the presence of diabetes-associated autoantibodies. Our broad understanding of the distinction between the two major types, type 1 diabetes mellitus and type 2 diabetes mellitus, are based on these factors, but it has become apparent that they do not precisely capture the different disease forms. Indeed, both major types of diabetes have common features, encapsulated by adult-onset autoimmune diabetes and maturity-onset diabetes of the young. As a result, there has been a repositioning of our understanding of diabetes. In this review, drawing on recent literature, we discuss the evidence that autoimmune type 1 diabetes has a broad clinical phenotype with diverse therapeutic options, while the term non-autoimmune type 2 diabetes obscures the optimal management strategy because it encompasses substantial heterogeneity. Underlying these developments is a general progression towards precision medicine with the need for precise patient characterisation, currently based on clinical phenotypes but in future augmented by laboratory-based tests.
Key points
• The need to clarify diabetes classification, which is currently imprecise in distinguishing major disease types, using laboratory tests
• The importance of predictors of disease progression, including genetic, immune and metabolic features
• The potential for predicting therapeutic responses to provide a more personalised approach to therapy
Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by insulin deficiency and resultant hyperglycemia. Complex interactions of genetic and environmental factors trigger the onset of ...autoimmune mechanisms responsible for development of autoimmunity to β cell antigens and subsequent development of T1D. A potential role of virus infections has long been hypothesized, and growing evidence continues to implicate enteroviruses as the most probable triggering viruses. Recent studies have strengthened the association between enteroviruses and development of autoimmunity in T1D patients, potentially through persistent infections. Enterovirus infections may contribute to different stages of disease development. We review data from both human cohort studies and experimental research exploring the potential roles and molecular mechanisms by which enterovirus infections can impact disease outcome.
Type 1 diabetes (T1D) is an autoimmune disease that targets pancreatic islet beta cells and incorporates genetic and environmental factors
, including complex genetic elements
, patient exposures
and ...the gut microbiome
. Viral infections
and broader gut dysbioses
have been identified as potential causes or contributing factors; however, human studies have not yet identified microbial compositional or functional triggers that are predictive of islet autoimmunity or T1D. Here we analyse 10,913 metagenomes in stool samples from 783 mostly white, non-Hispanic children. The samples were collected monthly from three months of age until the clinical end point (islet autoimmunity or T1D) in the The Environmental Determinants of Diabetes in the Young (TEDDY) study, to characterize the natural history of the early gut microbiome in connection to islet autoimmunity, T1D diagnosis, and other common early life events such as antibiotic treatments and probiotics. The microbiomes of control children contained more genes that were related to fermentation and the biosynthesis of short-chain fatty acids, but these were not consistently associated with particular taxa across geographically diverse clinical centres, suggesting that microbial factors associated with T1D are taxonomically diffuse but functionally more coherent. When we investigated the broader establishment and development of the infant microbiome, both taxonomic and functional profiles were dynamic and highly individualized, and dominated in the first year of life by one of three largely exclusive Bifidobacterium species (B. bifidum, B. breve or B. longum) or by the phylum Proteobacteria. In particular, the strain-specific carriage of genes for the utilization of human milk oligosaccharide within a subset of B. longum was present specifically in breast-fed infants. These analyses of TEDDY gut metagenomes provide, to our knowledge, the largest and most detailed longitudinal functional profile of the developing gut microbiome in relation to islet autoimmunity, T1D and other early childhood events. Together with existing evidence from human cohorts
and a T1D mouse model
, these data support the protective effects of short-chain fatty acids in early-onset human T1D.
The development of the microbiome from infancy to childhood is dependent on a range of factors, with microbial-immune crosstalk during this time thought to be involved in the pathobiology of later ...life diseases
such as persistent islet autoimmunity and type 1 diabetes
. However, to our knowledge, no studies have performed extensive characterization of the microbiome in early life in a large, multi-centre population. Here we analyse longitudinal stool samples from 903 children between 3 and 46 months of age by 16S rRNA gene sequencing (n = 12,005) and metagenomic sequencing (n = 10,867), as part of the The Environmental Determinants of Diabetes in the Young (TEDDY) study. We show that the developing gut microbiome undergoes three distinct phases of microbiome progression: a developmental phase (months 3-14), a transitional phase (months 15-30), and a stable phase (months 31-46). Receipt of breast milk, either exclusive or partial, was the most significant factor associated with the microbiome structure. Breastfeeding was associated with higher levels of Bifidobacterium species (B. breve and B. bifidum), and the cessation of breast milk resulted in faster maturation of the gut microbiome, as marked by the phylum Firmicutes. Birth mode was also significantly associated with the microbiome during the developmental phase, driven by higher levels of Bacteroides species (particularly B. fragilis) in infants delivered vaginally. Bacteroides was also associated with increased gut diversity and faster maturation, regardless of the birth mode. Environmental factors including geographical location and household exposures (such as siblings and furry pets) also represented important covariates. A nested case-control analysis revealed subtle associations between microbial taxonomy and the development of islet autoimmunity or type 1 diabetes. These data determine the structural and functional assembly of the microbiome in early life and provide a foundation for targeted mechanistic investigation into the consequences of microbial-immune crosstalk for long-term health.
Type 1 diabetes mellitus (T1DM) is an autoimmune disorder directed against the β cells of the pancreatic islets. The genetic risk of the disease is linked to HLA-DQ risk alleles and unknown ...environmental triggers. In most countries, only 10-15% of children or young adults newly diagnosed with T1DM have a first-degree relative with the disease. Autoantibodies against insulin, GAD65, IA-2 or the ZnT8 transporter mark islet autoimmunity. These islet autoantibodies may already have developed in children of 1-3 years of age. Immune therapy in T1DM is approached at three different stages. Primary prevention is treatment of individuals at increased genetic risk. For example, one trial is testing if hydrolyzed casein milk formula reduces T1DM incidence in genetically predisposed infants. Secondary prevention is targeted at individuals with persistent islet autoantibodies. Ongoing trials involve nonautoantigen-specific therapies, such as Bacillus Calmette-Guérin vaccine or anti-CD3 monoclonal antibodies, or autoantigen-specific therapies, including oral and nasal insulin or alum-formulated recombinant human GAD65. Trial interventions at onset of T1DM have also included nonautoantigen-specific approaches, and autoantigen-specific therapies, such as proinsulin peptides. Although long-term preservation of β-cell function has been difficult to achieve in many studies, considerable progress is being made through controlled clinical trials and animal investigations towards uncovering mechanisms of β-cell destruction. Novel therapies that prevent islet autoimmunity or halt progressive β-cell destruction are needed.
Multiple laboratory tests are used to diagnose and manage patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these tests varies substantially.
An expert ...committee compiled evidence-based recommendations for the use of laboratory testing for patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. Draft guidelines were posted on the Internet and presented at the 2007 Arnold O. Beckman Conference. The document was modified in response to oral and written comments, and a revised draft was posted in 2010 and again modified in response to written comments. The National Academy of Clinical Biochemistry and the Evidence Based Laboratory Medicine Committee of the AACC jointly reviewed the guidelines, which were accepted after revisions by the Professional Practice Committee and subsequently approved by the Executive Committee of the American Diabetes Association.
In addition to long-standing criteria based on measurement of plasma glucose, diabetes can be diagnosed by demonstrating increased blood hemoglobin A(1c) (Hb A(1c)) concentrations. Monitoring of glycemic control is performed by self-monitoring of plasma or blood glucose with meters and by laboratory analysis of Hb A(1c). The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed.
The guidelines provide specific recommendations that are based on published data or derived from expert consensus. Several analytes have minimal clinical value at present, and their measurement is not recommended.
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