Impact of Age and Antibody Type on Progression From Single to Multiple Autoantibodies in Type 1 Diabetes Relatives

Recommendations for Screening and Monitoring the Stages of Type 1 Diabetes in the Immune Therapy Era

Type 1 diabetes (T1D) is a complex, chronic autoimmune disease that affects over 1.6 million people in the United States. It is now understood that T1D may be undetected for many years while the disease progresses quietly without producing symptoms. T1D can be identified through diabetes-related autoantibody screening and staged accordingly, enabling healthcare providers to identify high-risk individuals in the early stages of the disease and either provide a stage-specific intervention or offer clinical trial opportunities to preserve beta cell function and anticipate the onset of clinical T1D. Evidence-based clinical practice guidelines currently do not exist for routine diabetes-related autoantibody screening of individuals at risk of developing T1D or of the general population. The purpose of this article is to help clinicians acquire an understanding of the rationale and protocols recommended for identifying patients at risk of developing T1D and monitoring such patients for autoimmune markers and progression of disease from Stage 1 to Stage 3 (clinical disease).

Consensus guidance for monitoring individuals with islet autoantibody-positive pre-stage 3 type 1 diabetes

Given the proven benefits of screening to reduce diabetic ketoacidosis (DKA) likelihood at the time of stage 3 type 1 diabetes diagnosis, and emerging availability of therapy to delay disease progression, type 1 diabetes screening programmes are being increasingly emphasised. Once broadly implemented, screening initiatives will identify significant numbers of islet autoantibody-positive (IAb+) children and adults who are at risk of (confirmed single IAb+) or living with (multiple IAb+) early-stage (stage 1 and stage 2) type 1 diabetes. These individuals will need monitoring for disease progression; much of this care will happen in non-specialised settings. To inform this monitoring, JDRF in conjunction with international experts and societies developed consensus guidance. Broad advice from this guidance includes the following: (1) partnerships should be fostered between endocrinologists and primary-care providers to care for people who are IAb+; (2) when people who are IAb+ are initially identified there is a need for confirmation using a second sample; (3) single IAb+ individuals are at lower risk of progression than multiple IAb+ individuals; (4) individuals with early-stage type 1 diabetes should have periodic medical monitoring, including regular assessments of glucose levels, regular education about symptoms of diabetes and DKA, and psychosocial support; (5) interested people with stage 2 type 1 diabetes should be offered trial participation or approved therapies; and (6) all health professionals involved in monitoring and care of individuals with type 1 diabetes have a responsibility to provide education. The guidance also emphasises significant unmet needs for further research on early-stage type 1 diabetes to increase the rigour of future recommendations and inform clinical care.

Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review

BACKGROUND

Islet autoantibodies form the foundation for type 1 diabetes (T1D) diagnosis and staging, but heterogeneity exists in T1D development and presentation. We hypothesized that autoantibodies can identify heterogeneity before, at, and after T1D diagnosis, and in response to disease-modifying therapies.

METHODS

We systematically reviewed PubMed and EMBASE databases (6/14/2022) assessing 10 years of original research examining relationships between autoantibodies and heterogeneity before, at, after diagnosis, and in response to disease-modifying therapies in individuals at-risk or within 1 year of T1D diagnosis. A critical appraisal checklist tool for cohort studies was modified and used for risk of bias assessment.

RESULTS

Here we show that 152 studies that met extraction criteria most commonly characterized heterogeneity before diagnosis (91/152). Autoantibody type/target was most frequently examined, followed by autoantibody number. Recurring themes included correlations of autoantibody number, type, and titers with progression, differing phenotypes based on order of autoantibody seroconversion, and interactions with age and genetics. Only 44% specifically described autoantibody assay standardization program participation.

CONCLUSIONS

Current evidence most strongly supports the application of autoantibody features to more precisely define T1D before diagnosis. Our findings support continued use of pre-clinical staging paradigms based on autoantibody number and suggest that additional autoantibody features, particularly in relation to age and genetic risk, could offer more precise stratification. To improve reproducibility and applicability of autoantibody-based precision medicine in T1D, we propose a methods checklist for islet autoantibody-based manuscripts which includes use of precision medicine MeSH terms and participation in autoantibody standardization workshops.

Screening and Prevention of Type 1 Diabetes: Where Are We?

A diagnosis of type 1 diabetes (T1D) and the subsequent requirement for exogenous insulin treatment is associated with considerable acute and chronic morbidity and a substantial effect on patient quality of life. Importantly, a large body of work suggests that early identification of presymptomatic T1D can accurately predict clinical disease, and when paired with education and monitoring, can yield improved health outcomes. Furthermore, a growing cadre of effective disease-modifying therapies provides the potential to alter the natural history of early stages of T1D. In this mini review, we highlight prior work that has led to the current landscape of T1D screening and prevention, as well as challenges and next steps moving into the future of these rapidly evolving areas of patient care.

Risk Modeling to Reduce Monitoring of an Autoantibody-Positive Population to Prevent DKA at Type 1 Diabetes Diagnosis

CONTEXT

The presence of islet autoimmunity identifies individuals likely to progress to clinical type 1 diabetes (T1D). In clinical research studies, autoantibody screening followed by regular metabolic monitoring every 6 months reduces incidence of diabetic ketoacidosis (DKA) at diagnosis.

OBJECTIVE

We hypothesized that DKA reduction can be achieved on a population basis with a reduced frequency of metabolic monitoring visits. We reasoned that prolonged time between the development of T1D and the time of clinical diagnosis ("undiagnosed time") would more commonly result in DKA and thus that limiting undiagnosed time would decrease DKA.

METHODS

An analysis was conducted of data from TrialNet's Pathway to Prevention (PTP), a cross-sectional longitudinal study that identifies and follows at-risk relatives of people with T1D. PTP is a population-based study enrolling across multiple countries. A total of 6193 autoantibody (AAB)-positive individuals participated in PTP from March 2004 to April 2019. We developed models of progression to clinical diagnosis for pediatric and adult populations with single or multiple AAB, and summarized results using estimated hazard rate. An optimal monitoring visit schedule was determined for each model to achieve a minimum average level of undiagnosed time for each population.

RESULTS

Halving the number of monitoring visits usually conducted in research studies is likely to substantially lower the population incidence of DKA at diagnosis of T1D.

CONCLUSION

Our study has clinical implications for the metabolic monitoring of at-risk individuals. Fewer monitoring visits would reduce the clinical burden, suggesting a path toward transitioning monitoring beyond the research setting.

Evaluating T cell responses prior to the onset of type 1 diabetes

AIMS

In the current study we aimed to evaluat T cell phenotypes and metabolic profiles in high-risk individuals who progressed to type 1 diabetes compared to those remaining disease free.

METHODS

A Fluorspot assay was used to examine T cell responses to a panel of islet autoantigen peptides in samples obtained 6- and 30-months preceding disease onset and at the same timepoints in non-progressors.

RESULTS

We noted a significant increase in the magnitude of the proinflammatory interferon-γ response to proinsulin and insulin peptides in individuals who progressed to type 1 diabetes. In contrast, in the non-progressors, we observed an increase in the regulatory IL-10 response to proinsulin peptides. Furthermore, the T cell responses to the islet peptide panel predisposed towards a proinflammatory interferon-γ bias in the progressors.

CONCLUSIONS

Collectively, these data suggest that a proinflammatory T cell response is prevalent in high-risk individuals who progress to type 1 diabetes and can be detected up to 6 months prior to onset of disease. This observation, albeit in a small cohort, can potentially be harnessed in disease staging, particularly in identifying autoantibody-positive individuals transitioning from stage 2 (dysglycemia present and pre-symptomatic) to stage 3 (dysglycemia present and symptomatic). The detection of these different T cell phenotypes in progressors and non-progressors suggests the presence of disease endotypes.

Preclinical Autoimmune Disease: a Comparison of Rheumatoid Arthritis, Systemic Lupus Erythematosus, Multiple Sclerosis and Type 1 Diabetes

The preclinical phase of autoimmune disorders is characterized by an initial asymptomatic phase of varying length followed by nonspecific signs and symptoms. A variety of autoimmune and inflammatory manifestations can be present and tend to increase in the last months to years before a clinical diagnosis can be made. The phenotype of an autoimmune disease depends on the involved organs, the underlying genetic susceptibility and pathophysiological processes. There are different as well as shared genetic or environmental risk factors and pathophysiological mechanisms between separate diseases. To shed more light on this, in this narrative review we compare the preclinical disease course of four important autoimmune diseases with distinct phenotypes: rheumatoid arthritis (RA), Systemic Lupus Erythematosus (SLE), multiple sclerosis (MS) and type 1 diabetes (T1D). In general, we observed some notable similarities such as a North-South gradient of decreasing prevalence, a female preponderance (except for T1D), major genetic risk factors at the HLA level, partly overlapping cytokine profiles and lifestyle risk factors such as obesity, smoking and stress. The latter risk factors are known to produce a state of chronic systemic low grade inflammation. A central characteristic of all four diseases is an on average lengthy prodromal phase with no or minor symptoms which can last many years, suggesting a gradually evolving interaction between the genetic profile and the environment. Part of the abnormalities may be present in unaffected family members, and autoimmune diseases can also cluster in families. In conclusion, a promising strategy for prevention of autoimmune diseases might be to address adverse life style factors by public health measures at the population level.

Characterising the age-dependent effects of risk factors on type 1 diabetes progression

AIMS/HYPOTHESIS

Age is known to be one of the most important stratifiers of disease progression in type 1 diabetes. However, what drives the difference in rate of progression between adults and children is poorly understood. Evidence suggests that many type 1 diabetes disease predictors do not have the same effect across the age spectrum. Without a comprehensive analysis describing the varying risk profiles of predictors over the age continuum, researchers and clinicians are susceptible to inappropriate assessment of risk when examining populations of differing ages. We aimed to systematically assess and characterise how the effect of key type 1 diabetes risk predictors changes with age.

METHODS

Using longitudinal data from single- and multiple-autoantibody-positive at-risk individuals recruited between the ages of 1 and 45 years in TrialNet's Pathway to Prevention Study, we assessed and visually characterised the age-varying effect of key demographic, immune and metabolic predictors of type 1 diabetes by employing a flexible spline model. Two progression outcomes were defined: participants with single autoantibodies (n=4893) were analysed for progression to multiple autoantibodies or type 1 diabetes, and participants with multiple autoantibodies were analysed (n=3856) for progression to type 1 diabetes.

RESULTS

Several predictors exhibited significant age-varying effects on disease progression. Amongst single-autoantibody participants, HLA-DR3 (p=0.007), GAD65 autoantibody positivity (p=0.008), elevated BMI (p=0.007) and HOMA-IR (p=0.002) showed a significant increase in effect on disease progression with increasing age. Insulin autoantibody positivity had a diminishing effect with older age in single-autoantibody-positive participants (p<0.001). Amongst multiple-autoantibody-positive participants, male sex (p=0.002) was associated with an increase in risk for progression, and HLA DR3/4 (p=0.05) showed a decreased effect on disease progression with older age. In both single- and multiple-autoantibody-positive individuals, significant changes in HR with age were seen for multiple measures of islet function. Risk estimation using prediction risk score Index60 was found to be better at a younger age for both single- and multiple-autoantibody-positive individuals (p=0.007 and p<0.001, respectively). No age-varying effect was seen for prediction risk score DPTRS (p=0.861 and p=0.178, respectively). Multivariable analyses suggested that incorporating the age-varying effect of the individual components of these validated risk scores has the potential to enhance the risk estimate.

CONCLUSIONS/INTERPRETATION

Analysing the age-varying effect of disease predictors improves understanding and prediction of type 1 diabetes disease progression, and should be leveraged to refine prediction models and guide mechanistic studies.

Immunotherapy for type 1 diabetes

INTRODUCTION

Despite advances in technology including the development of more sophisticated methods of monitoring blood glucose and delivering insulin, many individuals with type 1 diabetes continue to experience significant challenges in optimizing glycaemic control. Alternative treatment approaches to insulin are required. Increasing efforts have focused on developing treatments aimed at targeting the underlying disease process to modulate the immune system, maximize beta cell function and enhance endogenous insulin production and action.

SOURCES OF DATA

Literature searches with keywords 'Type 1 diabetes and immunotherapy', publications relating to clinical trials of immunotherapy in type 1 diabetes.

AREAS OF AGREEMENT

Insulin therapy is insufficient to achieve optimal glycaemic control in many individuals with type 1 diabetes, and new treatment approaches are required. Studies have showed promising results for the use of immunotherapy as a means of delaying disease onset and progression.

AREAS OF CONTROVERSY

The optimal way of identifying individuals most likely to benefit from immunotherapies.

GROWING POINTS

A better understanding of the natural history of type 1 diabetes has made it possible to identify individuals who have developed autoimmunity but have not yet progressed to clinical diabetes, offering opportunities not only to develop treatments that delay disease progression, but prevent its development in the first place. A consensus on how to identify individuals who may benefit from immunotherapy to prevent disease onset is needed.

AREAS TIMELY FOR DEVELOPING RESEARCH

The development of optimal strategies for preventing and delaying progression of type 1 diabetes, and monitoring the response to immunointervention.

Persistence of islet autoantibodies after diagnosis in type 1 diabetes

The presence of islet autoantibodies remains a reliable biomarker to identify individuals at high risk of developing type 1 diabetes. As such, these autoantibodies play a pivotal role in understanding the prodrome of diabetes and selecting individuals for both prevention and intervention clinical trials. Over the last few decades, studies have sought to investigate autoantibody prevalence after diabetes onset to better understand ongoing islet autoimmunity; however, many findings are contradictory, and little is known about factors that may influence autoantibody persistence. Generally, glutamate decarboxylase autoantibodies (GADAs) are the most prevalent autoantibodies after diagnosis, particularly in adults, whilst zinc transporter 8 autoantibodies (ZnT8A) prevalence declines more rapidly. However, when studies with islet autoantibody data at diagnosis are considered, it becomes clear that overall islet antigen-2 autoantibodies (IA-2A) tend to persist for longer than GADA or ZnT8A. In this review, we assess the major studies that have contributed to our understanding of autoantibody persistence after diabetes onset and what factors affect this. Islet autoantibodies may provide biomarkers for long-term β-cell function and insights into how to prevent ongoing islet autoimmunity but larger studies collecting samples at and decades after diabetes onset are required to leverage the information they could provide.

Diagnostic Capabilities of Islet Autoantibodies in Children with New-Onset Type 1 Diabetes Mellitus and Healthy Siblings

The aim of the study is to determine the diagnostic utility of several islet autoantibodies and their combinations in order to identify individuals susceptible to type 1 diabetes mellitus (T1DM) among healthy siblings in the pediatric population within the scope of the development of a screening program.

Ten years follow up of first degree relatives of type 1 diabetes patients: presence of autoimmune biomarkers and the progression to diabetes in a retrospective cohort

OBJECTIVE

The aim of the study was to assess the autoimmunity in first degrees relatives (FDR) of patients with type 1 diabetes (T1DM) and the progression to T1DM after 10 years of follow up in the Brazilian population.

METHODS

Non-diabetic FDR of T1DM patients were interviewed and blood was drawn for autoantibodies measurement (GADA, IA-2A, IAA, ZnT8A). Serum samples were analyzed by standard radioligand binding assays performed at the Federal University of Rio de Janeiro (GADA, IAA and IA2A), and at the Skäne University Hospital, Sweden (ZnT8A). The FDR were interviewed by phone after 10 years to determine if they had developed T1DM. Descriptive statistical analysis was performed and results were described as means and standard deviation (SD).

RESULTS

81 individuals were analyzed. Thirteen subjects had positive autoantibodies associated with T1DM.10 were positive for 1 autoantibody and 3 subjects were positive for multiple autoantibodies (1 of them showed positivity for 2 autoantibodies - GADA, ZnT8A - and the other two were positive for 3 autoantibodies - GADA, IA2A, ZnT8A). The 3 subjects with multiple positive autoantibodies developed T1DM within 10 years.

CONCLUSION

In Brazilian FDR of T1DM patients, the positivity for multiple autoantibodies indicate a greater chance of progression to T1DM, similar to observed in Caucasians. ZnT8A was helpful in the risk assessment for T1DM development.

Advances in Type 1 Diabetes Prediction Using Islet Autoantibodies: Beyond a Simple Count

Islet autoantibodies are key markers for the diagnosis of type 1 diabetes. Since their discovery, they have also been recognized for their potential to identify at-risk individuals prior to symptoms. To date, risk prediction using autoantibodies has been based on autoantibody number; it has been robustly shown that nearly all multiple-autoantibody-positive individuals will progress to clinical disease. However, longitudinal studies have demonstrated that the rate of progression among multiple-autoantibody-positive individuals is highly heterogenous. Accurate prediction of the most rapidly progressing individuals is crucial for efficient and informative clinical trials and for identification of candidates most likely to benefit from disease modification. This is increasingly relevant with the recent success in delaying clinical disease in presymptomatic subjects using immunotherapy, and as the field moves toward population-based screening. There have been many studies investigating islet autoantibody characteristics for their predictive potential, beyond a simple categorical count. Predictive features that have emerged include molecular specifics, such as epitope targets and affinity; longitudinal patterns, such as changes in titer and autoantibody reversion; and sequence-dependent risk profiles specific to the autoantibody and the subject's age. These insights are the outworking of decades of prospective cohort studies and international assay standardization efforts and will contribute to the granularity needed for more sensitive and specific preclinical staging. The aim of this review is to identify the dynamic and nuanced manifestations of autoantibodies in type 1 diabetes, and to highlight how these autoantibody features have the potential to improve study design of trials aiming to predict and prevent disease.

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.

An Age-Related Exponential Decline in the Risk of Multiple Islet Autoantibody Seroconversion During Childhood

OBJECTIVE

Islet autoimmunity develops before clinical type 1 diabetes and includes multiple and single autoantibody phenotypes. The objective was to determine age-related risks of islet autoantibodies that reflect etiology and improve screening for presymptomatic type 1 diabetes.

RESEARCH DESIGN AND METHODS

The Environmental Determinants of Diabetes in the Young study prospectively monitored 8,556 genetically at-risk children at 3- to 6-month intervals from birth for the development of islet autoantibodies and type 1 diabetes. The age-related change in the risk of developing islet autoantibodies was determined using landmark and regression models.

RESULTS

The 5-year risk of developing multiple islet autoantibodies was 4.3% (95% CI 3.8-4.7) at 7.5 months of age and declined to 1.1% (95% CI 0.8-1.3) at a landmark age of 6.25 years (P < 0.0001). Risk decline was slight or absent in single insulin and GAD autoantibody phenotypes. The influence of sex, HLA, and other susceptibility genes on risk subsided with increasing age and was abrogated by age 6 years. Highest sensitivity and positive predictive value of multiple islet autoantibody phenotypes for type 1 diabetes was achieved by autoantibody screening at 2 years and again at 5-7 years of age.

CONCLUSIONS

The risk of developing islet autoimmunity declines exponentially with age, and the influence of major genetic factors on this risk is limited to the first few years of life.

The risk of progression to type 1 diabetes is highly variable in individuals with multiple autoantibodies following screening

AIMS/HYPOTHESIS

Young children who develop multiple autoantibodies (mAbs) are at very high risk for type 1 diabetes. We assessed whether a population with mAbs detected by screening is also at very high risk, and how risk varies according to age, type of autoantibodies and metabolic status.

METHODS

Type 1 Diabetes TrialNet Pathway to Prevention participants with mAbs (n = 1815; age, 12.35 ± 9.39 years; range, 1-49 years) were analysed. Type 1 diabetes risk was assessed according to age, autoantibody type/number (insulin autoantibodies [IAA], glutamic acid decarboxylase autoantibodies [GADA], insulinoma-associated antigen-2 autoantibodies [IA-2A] or zinc transporter 8 autoantibodies [ZnT8A]) and Index60 (composite measure of fasting C-peptide, 60 min glucose and 60 min C-peptide). Cox regression and cumulative incidence curves were utilised in this cohort study.

RESULTS

Age was inversely related to type 1 diabetes risk in those with mAbs (HR 0.97 [95% CI 0.96, 0.99]). Among participants with 2 autoantibodies, those with GADA had less risk (HR 0.35 [95% CI 0.22, 0.57]) and those with IA-2A had higher risk (HR 2.82 [95% CI 1.76, 4.51]) of type 1 diabetes. Those with IAA and GADA had only a 17% 5 year risk of type 1 diabetes. The risk was significantly lower for those with Index60 <1.0 (HR 0.23 [95% CI 0.19, 0.30]) vs those with Index60 values ≥1.0. Among the 12% (225/1815) ≥12.0 years of age with GADA positivity, IA-2A negativity and Index60 <1.0, the 5 year risk of type 1 diabetes was 8%.

CONCLUSIONS/INTERPRETATION

Type 1 diabetes risk varies substantially according to age, autoantibody type and metabolic status in individuals screened for mAbs. An appreciable proportion of older children and adults with mAbs appear to have a low risk of progressing to type 1 diabetes at 5 years. With this knowledge, clinical trials of type 1 diabetes prevention can better target those most likely to progress.

The heterogeneous pathogenesis of type 1 diabetes mellitus

Type 1 diabetes mellitus (T1DM) results from the destruction of pancreatic β-cells that is mediated by the immune system. Multiple genetic and environmental factors found in variable combinations in individual patients are involved in the development of T1DM. Genetic risk is defined by the presence of particular allele combinations, which in the major susceptibility locus (the HLA region) affect T cell recognition and tolerance to foreign and autologous molecules. Multiple other loci also regulate and affect features of specific immune responses and modify the vulnerability of β-cells to inflammatory mediators. Compared with the genetic factors, environmental factors that affect the development of T1DM are less well characterized but contact with particular microorganisms is emerging as an important factor. Certain infections might affect immune regulation, and the role of commensal microorganisms, such as the gut microbiota, are important in the education of the developing immune system. Some evidence also suggests that nutritional factors are important. Multiple islet-specific autoantibodies are found in the circulation from a few weeks to up to 20 years before the onset of clinical disease and this prediabetic phase provides a potential opportunity to manipulate the islet-specific immune response to prevent or postpone β-cell loss. The latest developments in understanding the heterogeneity of T1DM and characterization of major disease subtypes might help in the development of preventive treatments.

Age at Seroconversion, HLA Genotype, and Specificity of Autoantibodies in Progression of Islet Autoimmunity in Childhood

CONTEXT

Children with initial autoantibodies to either insulin (IAA) or glutamic acid decarboxylase (GADA) differ in peak age of seroconversion and have different type 1 diabetes (T1D) risk gene associations, suggesting heterogeneity in the disease process.

OBJECTIVE

To compare the associations of age at seroconversion, HLA risk, and specificity of secondary autoantibodies with the progression of islet autoimmunity between children with either IAA or GADA as their first autoantibody.

DESIGN AND METHODS

A cohort of 15,253 children with HLA-associated increased risk of T1D participated in a follow-up program in which islet autoantibodies were regularly measured. The median follow-up time was 6.7 years. Spearman correlation, Kaplan-Meier survival plots, and Cox proportional-hazard models were used for statistical analyses.

RESULTS

Persistent positivity for at least one of the tested autoantibodies was detected in 998 children; 388 of children progressed to clinical T1D. Young age at initial seroconversion was associated with a high probability of expansion of IAA-initiated autoimmunity and progression to clinical diabetes, whereas expansion of GADA-initiated autoimmunity and progression to diabetes were not dependent on initial seroconversion age. The strength of HLA risk affected the progression of both IAA- and GADA-initiated autoimmunity. The simultaneous appearance of two other autoantibodies increased the rate of progression to diabetes compared with that of a single secondary autoantibody among subjects with GADA-initiated autoimmunity but not among those with IAA as the first autoantibody.

CONCLUSIONS

Findings emphasize the differences in the course of islet autoimmunity initiated by either IAA or GADA supporting heterogeneity in the pathogenic process.

New Insights into Immunotherapy Strategies for Treating Autoimmune Diabetes

Type 1 diabetes mellitus (T1D) is an autoimmune illness that affects millions of patients worldwide. The main characteristic of this disease is the destruction of pancreatic insulin-producing beta cells that occurs due to the aberrant activation of different immune effector cells. Currently, T1D is treated by lifelong administration of novel versions of insulin that have been developed recently; however, new approaches that could address the underlying mechanisms responsible for beta cell destruction have been extensively investigated. The strategies based on immunotherapies have recently been incorporated into a panel of existing treatments for T1D, in order to block T-cell responses against beta cell antigens that are very common during the onset and development of T1D. However, a complete preservation of beta cell mass as well as insulin independency is still elusive. As a result, there is no existing T1D targeted immunotherapy able to replace standard insulin administration. Presently, a number of novel therapy strategies are pursuing the goals of beta cell protection and normoglycemia. In the present review we explore the current state of immunotherapy in T1D by highlighting the most important studies in this field, and envision novel strategies that could be used to treat T1D in the future.

Disease-Modifying Therapies in Type 1 Diabetes: A Look into the Future of Diabetes Practice

The novel understanding that the presence of multiple islet autoantibodies, indicating islet autoimmunity, inevitably leads to type 1 diabetes mellitus (T1DM) has necessitated the development of a new staging classification system for the condition. Coupled with an improved understanding of the disease course, the realization that T1DM appears to be more heterogeneous than previously thought has led to unique opportunities to develop more targeted therapies that may be applied even before the onset of dysglycemia or symptoms. To date, several therapies have been trialed to delay or halt disease progression in both presymptomatic and clinical T1DM, each demonstrating varying degrees of effectiveness, toxicity, and utility. Key research supports the eventual implementation of immunotherapy in autoimmune diabetes, potentially calling for a paradigm shift among care providers. It will likely be necessary to develop new approaches to trial design and to address potential barriers to progress before an effective treatment for the disease may be achieved.

Shared and unique immune alterations in pre-clinical autoimmunity

Progression from health to a classified autoimmune disease is an evolving process that can happen rapidly in some diseases, but usually takes years to develop. Specific immune alterations predate pathogenic autoimmunity and can be used as disease biomarkers to identify high-risk individuals for prevention studies applied in the pre-clinical state. Here we discuss recent findings that illuminate specific immune pathways that are altered in the earliest phases of pre-clinical autoimmunity as well as those mediators more closely associated with later clinically apparent and classified disease onset.

Birth and coming of age of islet autoantibodies

This review takes the reader through 45 years of islet autoantibody research, from the discovery of islet‐cell antibodies in 1974 to today’s population‐based screening for presymptomatic early‐stage type 1 diabetes. The review emphasizes the current practical value of, and factors to be considered in, the measurement of islet autoantibodies.

Autoantibodies Directed Toward a Novel IA-2 Variant Protein Enhance Prediction of Type 1 Diabetes

We identified autoantibodies (AAb) reacting with a variant IA-2 molecule (IA-2var) that has three amino acid substitutions (Cys27, Gly608, and Pro671) within the full-length molecule. We examined IA-2var AAb in first-degree relatives of type 1 diabetes (T1D) probands from the TrialNet Pathway to Prevention Study. The presence of IA-2var-specific AAb in relatives was associated with accelerated progression to T1D in those positive for AAb to GAD65 and/or insulin but negative in the standard test for IA-2 AAb. Furthermore, relatives with single islet AAb (by traditional assays) and carrying both IA-2var AAb and the high-risk HLA-DRB1*04-DQB1*03:02 haplotype progress rapidly to onset of T1D. Molecular modeling of IA-2var predicts that the genomic variation that alters the three amino acids induces changes in the three-dimensional structure of the molecule, which may lead to epitope unmasking in the IA-2 extracellular domain. Our observations suggest that the presence of AAb to IA-2var would identify high-risk subjects who would benefit from participation in prevention trials who have one islet antibody by traditional testing and otherwise would be misclassified as "low risk" relatives.

Prediction and prevention of type 1 diabetes in children

Type 1 diabetes (T1D) is a chronic T-cell mediated autoimmune disease characterized by destruction of beta cells. Although new data have better defined the complex etiology underling the interrelation of genetic and environmental factors in the natural history of T1D, relevant pieces of the puzzle still are missing. Genetic predisposition is mainly associated to some histocompatibility leukocyte antigen (HLA) alleles; however, recent data suggest that new as well as still unknown genes might better define the complex multigenetic risk of the disease. In addition to the genetic effects, the concordance in familial aggregation in T1D indicates a pivotal role of environmental factors in the course of the disease, facilitating autoantibodies production. JDRF has recently proposed a new early stage of T1D according to which the detection of two or more autoantibodies in the blood, might describe those children at increased risk of developing T1D during the following years. In contrast to the improvements reached by prediction models, to date primary, secondary and tertiary prevention have still failed to achieve a safe and efficacious intervention strategies. Anyway, the most recent progresses in this field pave the way for future studies, with the aim of preventing T1D in children.

Identical and Nonidentical Twins: Risk and Factors Involved in Development of Islet Autoimmunity and Type 1 Diabetes

OBJECTIVE

There are variable reports of risk of concordance for progression to islet autoantibodies and type 1 diabetes in identical twins after one twin is diagnosed. We examined development of positive autoantibodies and type 1 diabetes and the effects of genetic factors and common environment on autoantibody positivity in identical twins, nonidentical twins, and full siblings.

RESEARCH DESIGN AND METHODS

Subjects from the TrialNet Pathway to Prevention Study (N = 48,026) were screened from 2004 to 2015 for islet autoantibodies (GAD antibody [GADA], insulinoma-associated antigen 2 [IA-2A], and autoantibodies against insulin [IAA]). Of these subjects, 17,226 (157 identical twins, 283 nonidentical twins, and 16,786 full siblings) were followed for autoantibody positivity or type 1 diabetes for a median of 2.1 years.

RESULTS

At screening, identical twins were more likely to have positive GADA, IA-2A, and IAA than nonidentical twins or full siblings (all P < 0.0001). Younger age, male sex, and genetic factors were significant factors for expression of IA-2A, IAA, one or more positive autoantibodies, and two or more positive autoantibodies (all P ≤ 0.03). Initially autoantibody-positive identical twins had a 69% risk of diabetes by 3 years compared with 1.5% for initially autoantibody-negative identical twins. In nonidentical twins, type 1 diabetes risk by 3 years was 72% for initially multiple autoantibody-positive, 13% for single autoantibody-positive, and 0% for initially autoantibody-negative nonidentical twins. Full siblings had a 3-year type 1 diabetes risk of 47% for multiple autoantibody-positive, 12% for single autoantibody-positive, and 0.5% for initially autoantibody-negative subjects.

CONCLUSIONS

Risk of type 1 diabetes at 3 years is high for initially multiple and single autoantibody-positive identical twins and multiple autoantibody-positive nonidentical twins. Genetic predisposition, age, and male sex are significant risk factors for development of positive autoantibodies in twins.

Relative Pancreas Volume Is Reduced in First-Degree Relatives of Patients With Type 1 Diabetes

OBJECTIVE

Pancreas size is reduced in patients at type 1 diabetes onset and in autoantibody (AAB)-positive donors without diabetes. We sought to determine whether pancreas volume (PV) imaging could improve understanding of the loss of pancreas size in first-degree relatives (FDRs) of patients with type 1 diabetes. We also examined relationships among PV, AAB status, and endocrine and exocrine functions.

RESEARCH DESIGN AND METHODS

We conducted a cross-sectional study that included five groups: AAB^- control subjects (no diabetes and no first- or second-degree relatives with type 1 diabetes) (N = 49), AAB^- FDRs (N = 61), AAB⁺ FDRs (N = 67 total: n = 31 with a single positive AAB [AAB⁺ single] and n = 36 with multiple positive AABs [AAB⁺ multiple]), and patients with recent-onset type 1 diabetes (<1 year) (N = 52). Fasting subjects underwent 1.5T pancreatic MRI, and PV and relative PV (RPV) (PV-to-BMI ratio) were analyzed between groups and for correlations with HbA_1c, C-peptide, glucose, and trypsinogen.

RESULTS

All FDR groups had significantly lower RPV adjusted for BMI (RPV_BMI) than control subjects (all P < 0.05). Patients with type 1 diabetes had lower RPV_BMI than AAB^- FDR (P < 0.0001) and AAB⁺ multiple (P ≤ 0.013) subjects. Transformed data indicated that trypsinogen levels were lowest in patients with type 1 diabetes.

CONCLUSIONS

This study demonstrates, for the first time, all FDRs having significantly smaller RPV_BMI compared with AAB^- control subjects. Furthermore, RPV_BMI was significantly lower in patients with recent-onset type 1 diabetes than in the AAB^- FDR and AAB⁺ multiple groups. As such, RPV_BMI may be a novel noninvasive biomarker for predicting progression through stages of type 1 diabetes risk. This study highlights the potential paracrine relationships between the exocrine and endocrine pancreas in progression to type 1 diabetes in subjects at risk.

Type 1 Diabetes-related Autoantibodies in Different Forms of Diabetes

Autoantibodies against Glutamic Acid Decarboxylase (GADA), insulinoma antigen-2 (IA- 2A), insulin (IAA) and the most recently Zinc Transporter 8 (ZnT8A) are one of the most reliable biomarkers for autoimmune diabetes in both children and adults. They are today the only biomarkers that can distinguish Latent Autoimmune Diabetes in Adults (LADA) from phenotypically type 2 diabetes. As the frequency of autoantibodies at diagnosis in childhood type 1 diabetes depends on age, GADA is by far the most common in adult onset autoimmune diabetes, especially LADA. Being multiple autoantibody positive have also shown to be more common in childhood diabetes compared to adult onset diabetes, and multiple autoantibody positivity have a high predictive value of childhood type 1 diabetes. Autoantibodies have shown inconsistent results to predict diabetes in adults. Levels of autoantibodies are reported to cause heterogeneity in LADA. Reports indicate that individuals with high levels of autoantibodies have a more type 1 diabetes like phenotype and individuals with low levels of autoantibody positivity have a more type 2 diabetes like phenotype. It is also well known that autoantibody levels can fluctuate and transient autoantibody positivity in adult onset autoimmune diabetes have been reported to affect the phenotype.

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Manley L, Nemery R, Charlton W, Smith P, Kerr L, Steindel-Kopp B, Alamaguer M, Tabisola-Nuesca E, Pendersen A, Larson N, Cooper-Olviver H, Chan D, Fitz-Patrick D, Carreira T, Park Y, Ruhaak R, Liljenquist D. A Type 1 Diabetes Genetic Risk Score Predicts Progression of Islet Autoimmunity and Development of Type 1 Diabetes in Individuals at Risk

OBJECTIVE

We tested the ability of a type 1 diabetes (T1D) genetic risk score (GRS) to predict progression of islet autoimmunity and T1D in at-risk individuals.

RESEARCH DESIGN AND METHODS

We studied the 1,244 TrialNet Pathway to Prevention study participants (T1D patients' relatives without diabetes and with one or more positive autoantibodies) who were genotyped with Illumina ImmunoChip (median [range] age at initial autoantibody determination 11.1 years [1.2-51.8], 48% male, 80.5% non-Hispanic white, median follow-up 5.4 years). Of 291 participants with a single positive autoantibody at screening, 157 converted to multiple autoantibody positivity and 55 developed diabetes. Of 953 participants with multiple positive autoantibodies at screening, 419 developed diabetes. We calculated the T1D GRS from 30 T1D-associated single nucleotide polymorphisms. We used multivariable Cox regression models, time-dependent receiver operating characteristic curves, and area under the curve (AUC) measures to evaluate prognostic utility of T1D GRS, age, sex, Diabetes Prevention Trial-Type 1 (DPT-1) Risk Score, positive autoantibody number or type, HLA DR3/DR4-DQ8 status, and race/ethnicity. We used recursive partitioning analyses to identify cut points in continuous variables.

RESULTS

Higher T1D GRS significantly increased the rate of progression to T1D adjusting for DPT-1 Risk Score, age, number of positive autoantibodies, sex, and ethnicity (hazard ratio [HR] 1.29 for a 0.05 increase, 95% CI 1.06-1.6; P = 0.011). Progression to T1D was best predicted by a combined model with GRS, number of positive autoantibodies, DPT-1 Risk Score, and age (7-year time-integrated AUC = 0.79, 5-year AUC = 0.73). Higher GRS was significantly associated with increased progression rate from single to multiple positive autoantibodies after adjusting for age, autoantibody type, ethnicity, and sex (HR 2.27 for GRS >0.295, 95% CI 1.47-3.51; P = 0.0002).

CONCLUSIONS

The T1D GRS independently predicts progression to T1D and improves prediction along T1D stages in autoantibody-positive relatives.

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.

Accelerated Progression to Type 1 Diabetes in the Presence of HLA-A*24 and -B*18 Is Restricted to Multiple Islet Autoantibody-Positive Individuals With Distinct HLA-DQ and Autoantibody Risk Profiles

OBJECTIVE

We investigated the effect of HLA class I risk alleles on disease progression in various phases of subclinical islet autoimmunity in first-degree relatives of patients with type 1 diabetes.

RESEARCH DESIGN AND METHODS

A registry-based group of siblings/offspring (aged 0-39 years) was monitored from single- to multiple-autoantibody positivity (n = 267) and from multiple-autoantibody positivity to clinical onset (n = 252) according to HLA-DQ, -A*24, -B*18, and -B*39 status. Genetic markers were determined by PCR sequence-specific oligotyping.

RESULTS

Unlike HLA-B*18 or -B*39, HLA-A*24 was associated with delayed progression from single- to multiple-autoantibody positivity (P = 0.009) but not to type 1 diabetes. This occurred independently from older age (P < 0.001) and absence of HLA-DQ2/DQ8 or -DQ8 (P < 0.001 and P = 0.003, respectively), and only in the presence of GAD autoantibodies. In contrast, HLA-A*24 was associated with accelerated progression from multiple-autoantibody positivity to clinical onset (P = 0.006), but its effects were restricted to HLA-DQ8⁺ relatives with IA-2 or zinc transporter 8 autoantibodies (P = 0.002). HLA-B*18, but not -B*39, was also associated with more rapid progression, but only in HLA-DQ2 carriers with double positivity for GAD and insulin autoantibodies (P = 0.004).

CONCLUSIONS

HLA-A*24 predisposes to a delayed antigen spreading of humoral autoimmunity, whereas HLA-A*24 and -B*18 are associated with accelerated progression of advanced subclinical autoimmunity in distinct risk groups. The relation of these alleles to the underlying disease process requires further investigation. Their typing should be relevant for the preparation and interpretation of observational and interventional studies in asymptomatic type 1 diabetes.

Relationship between islet autoantibody status and the clinical characteristics of children and adults with incident type 1 diabetes in a UK cohort

OBJECTIVES

To describe the characteristics of children and adults with incident type 1 diabetes in contemporary, multiethnic UK, focusing on differences between the islet autoantibody negative and positive.

DESIGN

Observational cohort study.

SETTING

146 mainly secondary care centres across England and Wales.

PARTICIPANTS

3312 people aged ≥5 years were recruited within 6 months of a clinical diagnosis of type 1 diabetes via the National Institute for Health Research Clinical Research Network. 3021 were of white European ethnicity and 291 (9%) were non-white. There was a small male predominance (57%). Young people <17 years comprised 59%.

MAIN OUTCOME MEASURES

Autoantibody status and characteristics at presentation.

RESULTS

The majority presented with classical osmotic symptoms, weight loss and fatigue. Ketoacidosis was common (42%), especially in adults, and irrespective of ethnicity. 35% were overweight or obese. Of the 1778 participants who donated a blood sample, 85% were positive for one or more autoantibodies against glutamate decarboxylase, islet antigen-2 and zinc transporter 8. Presenting symptoms were similar in the autoantibody-positive and autoantibody-negative participants, as was the frequency of ketoacidosis (43%vs40%, P=0.3). Autoantibody positivity was less common with increasing age (P=0.0001), in males compared with females (82%vs90%, P<0.0001) and in people of non-white compared with white ethnicity (73%vs86%, P<0.0001). Body mass index was higher in autoantibody-negative adults than autoantibody-positive adults (median, IQR 25.5, 23.1-29.2vs23.9, 21.4-26.7 kg/m²; P=0.0001). Autoantibody-negative participants were more likely to have a parent with diabetes (28%vs16%, P<0.0001) and less likely to have another autoimmune disease (4%vs8%, P=0.01).

CONCLUSIONS

Most people assigned a diagnosis of type 1 diabetes presented with classical clinical features and islet autoantibodies. Although indistinguishable at an individual level, autoantibody-negative participants as a group demonstrated features more typically associated with other diabetes subtypes.

TRIAL REGISTRATION NUMBER

ISRCTN66496918; Pre-results.

Type 1 Diabetes TrialNet: A Multifaceted Approach to Bringing Disease-Modifying Therapy to Clinical Use in Type 1 Diabetes

What will it take to bring disease-modifying therapy to clinical use in type 1 diabetes? Coordinated efforts of investigators involved in discovery, translational, and clinical research operating in partnership with funders and industry and in sync with regulatory agencies are needed. This Perspective describes one such effort, Type 1 Diabetes TrialNet, a National Institutes of Health-funded and JDRF-supported international clinical trials network that emerged from the Diabetes Prevention Trial-Type 1 (DPT-1). Through longitudinal natural history studies, as well as trials before and after clinical onset of disease combined with mechanistic and ancillary investigations to enhance scientific understanding and translation to clinical use, TrialNet is working to bring disease-modifying therapies to individuals with type 1 diabetes. Moreover, TrialNet uses its expertise and experience in clinical studies to increase efficiencies in the conduct of trials and to reduce the burden of participation on individuals and families. Herein, we highlight key contributions made by TrialNet toward a revised understanding of the natural history of disease and approaches to alter disease course and outline the consortium's plans for the future.