Single Islet Autoantibody at Diagnosis of Clinical Type 1 Diabetes is Associated With Older Age and Insulin Resistance

Islet autoantibodies in Thai individuals individuals diagnosed with type 1 diabetes before 30 years of age: a large multicentre nationwide study

AIMS/HYPOTHESIS

Type 1 diabetes is categorised into autoantibody positive and autoantibody negative. Most type 1 diabetes research has focused on European populations, leaving a gap in understanding in relation to other ethnic groups, including Thai populations. This lack of data is significant given Thailand's poor prevention and therapeutic management strategies. We aimed to investigate the frequency and distribution of islet autoantibodies among Thai individuals with long-standing type 1 diabetes diagnosed before the age of 30 years.

METHODS

We conducted a nationwide population-based study involving 48 hospitals in Thailand from May 2020 to September 2023, enrolling 953 participants. Demographic and clinical characteristics of individuals with autoantibody-positive and -negative type 1 diabetes were analysed. The autoantibodies GAD65, IA-2 and ZnT8 were measured using ELISA. A random C-peptide level was detected by electrochemiluminescence immunoassay.

RESULTS

Thai individuals with autoantibody-negative type 1 diabetes comprised 34.2% of the population. Among all individuals, the frequency of GAD65, IA-2 and ZnT8 was 56%, 37% and 33%, respectively. Autoantibody-negative individuals with type 1 diabetes were older at diagnosis, had higher BMI and had higher random C-peptide levels compared with autoantibody-positive individuals with type 1 diabetes. Female individuals had a higher prevalence of type 1 diabetes than male individuals (58% vs 42%; p=1.531 × 10-5). The southern region of Thailand exhibited a distinct pattern of autoantibody frequency compared with other regions (p=0.0001561).

CONCLUSIONS/INTERPRETATION

The frequency, distribution and characteristics of autoantibody-positive and -negative long-standing type 1 diabetes in Thailand showed uniqueness from other populations. This provides insight into the disease that may have implications for type 1 diabetes prediction, treatment and pathogenesis, especially in the Southeast Asian population.

Time to reframe the disease staging system for type 1 diabetes

In 2015, introduction of a disease staging system offered a framework for benchmarking progression to clinical type 1 diabetes. This model, based on islet autoantibodies (stage 1) and dysglycaemia (stage 2) before type 1 diabetes diagnosis (stage 3), has facilitated screening and identification of people at risk. Yet, there are many limitations to this model as the stages combine a very heterogeneous group of individuals; do not have high specificity for type 1 diabetes; can occur without persistence (ie, reversion to an earlier risk stage); and exclude age and other influential risk factors. The current staging system also infers that individuals at risk of type 1 diabetes progress linearly from stage 1 to stage 2 and subsequently stage 3, whereas such movements are often more complex. With the approval of teplizumab by the US Food and Drug Administration in 2022 to delay type 1 diabetes in people at stage 2, there is a need to refine the definition and accuracy of type 1 diabetes staging. Theoretically, we propose that a type 1 diabetes risk calculator should incorporate any available demographic, genetic, autoantibody, metabolic, and immune data that could be continuously updated. Additionally, we call to action for the field to increase the breadth of knowledge regarding type 1 diabetes risk in non-relatives, adults, and individuals from minority populations.

Characterisation of islet antibody-negative type 1 diabetes mellitus in Indian children

AIMS

Islet antibody-negative type 1 diabetes mellitus (T1DM) has not been well characterised. We determined the frequency of antibody-negative T1DM and compared it with antibody-positive T1DM in a cohort of north Indian children.

METHODS

In a multi-centre, prospective, observational study, 176 Indian children (age 1-18 years) were assessed within 2 weeks of diagnosis of T1DM. Antibodies against GAD65 (GADA), islet antigen-2 (IA-2A) and zinc transporter 8 (ZnT8A), were estimated using validated ELISA. HLA-DRB1, DQA1 and DQB1 alleles were studied by Luminex-based typing. Monogenic diabetes was determined by targeted next-generation sequencing using the Illumina platform.

RESULTS

After excluding 12 children with monogenic diabetes, GADA, IA-2A and ZnT8A were present in 124 (76%), 60 (37%) and 62 (38%) o children, respectively, while 24 (15%) were negative for all antibodies. A single antibody (most frequently GADA) was present in 68 (41%) of children, while all three antibodies were found in 34 (21%). Islet antibody-negative T1DM (n = 24, 15%) did not differ from antibody-positive children in their clinical features, HbA1c or plasma C-peptide, both at onset or after 1 year follow-up (available in 62 children). The frequency of other organ-specific antibodies or high-risk HLA-DR and DQ alleles were also similar. Children with a single islet antibody did not differ from those with multiple antibodies.

CONCLUSIONS

The frequency of various islet-antibodies, in isolation and combination, differed considerably from studies among children of European descent with T1DM. Children with T1DM who were islet antibody-negative were indistinguishable from those who were antibody-positive.

Understanding diabetes heterogeneity: key steps towards precision medicine in diabetes

Diabetes is a highly heterogeneous condition; yet, it is diagnosed by measuring a single blood-borne metabolite, glucose, irrespective of aetiology. Although pragmatically helpful, disease classification can become complex and limit advances in research and medical care. Here, we describe diabetes heterogeneity, highlighting recent approaches that could facilitate management by integrating three disease models across all forms of diabetes, namely, the palette model, the threshold model and the gradient model. Once diabetes has developed, further worsening of established diabetes and the subsequent emergence of diabetes complications are kept in check by multiple processes designed to prevent or circumvent metabolic dysfunction. The impact of any given disease risk factor will vary from person-to-person depending on their background, diabetes-related propensity, and environmental exposures. Defining the consequent heterogeneity within diabetes through precision medicine, both in terms of diabetes risk and risk of complications, could improve health outcomes today and shine a light on avenues for novel therapy in the future.

Prevalence, clinical characteristics and HLA genotypes of idiopathic type 1 diabetes: A cross-sectional study

AIMS

Idiopathic type 1 diabetes (T1D) is a neglected subtype of T1D. Our aim was to investigate the frequency, clinical characteristics, and human leucocyte antigen (HLA) genotypes of idiopathic T1D.

METHODS

We enrolled 1205 newly diagnosed T1D patients in our analysis. To exclude monogenic diabetes in autoantibody-negative patients, we utilised a custom monogenic diabetes gene panel. Individuals negative for autoantibodies and subsequently excluded for monogenic diabetes were diagnosed with idiopathic T1D. We collected clinical characteristics, measured islet autoantibodies by radioligand assay and obtained HLA data.

RESULTS

After excluding 11 patients with monogenic diabetes, 284 cases were diagnosed with idiopathic T1D, accounting for 23.8% (284/1194) of all newly diagnosed T1D cases. When compared with autoimmune T1D, idiopathic T1D patients showed an older onset age, higher body mass index among adults, lower haemoglobin A1c, higher levels of fasting C-peptide and 2-h postprandial C-peptide, and were likely to have type 2 diabetes (T2D) family history and carry 0 susceptible HLA haplotype (all p < 0.01). A lower proportion of individuals carrying 2 susceptible HLA haplotypes in idiopathic T1D was observed in the adult-onset subgroup (15.7% vs. 38.0% in child-onset subgroup, p < 0.001) and in subgroup with preserved beta-cell function (11.0% vs. 30.1% in subgroup with poor beta-cell function, p < 0.001). Multivariable correlation analyses indicated that being overweight, having T2D family history and lacking susceptible HLA haplotypes were associated with negative autoantibodies.

CONCLUSIONS

Idiopathic T1D represents about 1/4 of newly diagnosed T1D, with adult-onset and preserved beta-cell function patients showing lower HLA susceptibility and more insulin resistance.

Heterogeneity and endotypes in type 1 diabetes mellitus

Despite major advances over the past decade, prevention and treatment of type 1 diabetes mellitus (T1DM) remain suboptimal, with large and unexplained variations in individual responses to interventions. The current classification schema for diabetes mellitus does not capture the complexity of this disease or guide clinical management effectively. One of the approaches to achieve the goal of applying precision medicine in diabetes mellitus is to identify endotypes (that is, well-defined subtypes) of the disease each of which has a distinct aetiopathogenesis that might be amenable to specific interventions. Here, we describe epidemiological, clinical, genetic, immunological, histological and metabolic differences within T1DM that, together, suggest heterogeneity in its aetiology and pathogenesis. We then present the emerging endotypes and their impact on T1DM prediction, prevention and treatment.

The relationship between islet autoantibody status and the genetic risk of type 1 diabetes in adult-onset type 1 diabetes

AIMS/HYPOTHESIS

The reason for the observed lower rate of islet autoantibody positivity in clinician-diagnosed adult-onset vs childhood-onset type 1 diabetes is not known. We aimed to explore this by assessing the genetic risk of type 1 diabetes in autoantibody-negative and -positive children and adults.

METHODS

We analysed GAD autoantibodies, insulinoma-2 antigen autoantibodies and zinc transporter-8 autoantibodies (ZnT8A) and measured type 1 diabetes genetic risk by genotyping 30 type 1 diabetes-associated variants at diagnosis in 1814 individuals with clinician-diagnosed type 1 diabetes (1112 adult-onset, 702 childhood-onset). We compared the overall type 1 diabetes genetic risk score (T1DGRS) and non-HLA and HLA (DR3-DQ2, DR4-DQ8 and DR15-DQ6) components with autoantibody status in those with adult-onset and childhood-onset diabetes. We also measured the T1DGRS in 1924 individuals with type 2 diabetes from the Wellcome Trust Case Control Consortium to represent non-autoimmune diabetes control participants.

RESULTS

The T1DGRS was similar in autoantibody-negative and autoantibody-positive clinician-diagnosed childhood-onset type 1 diabetes (mean [SD] 0.274 [0.034] vs 0.277 [0.026], p=0.4). In contrast, the T1DGRS in autoantibody-negative adult-onset type 1 diabetes was lower than that in autoantibody-positive adult-onset type 1 diabetes (mean [SD] 0.243 [0.036] vs 0.271 [0.026], p<0.0001) but higher than that in type 2 diabetes (mean [SD] 0.229 [0.034], p<0.0001). Autoantibody-negative adults were more likely to have the more protective HLA DR15-DQ6 genotype (15% vs 3%, p<0.0001), were less likely to have the high-risk HLA DR3-DQ2/DR4-DQ8 genotype (6% vs 19%, p<0.0001) and had a lower non-HLA T1DGRS (p<0.0001) than autoantibody-positive adults. In contrast to children, autoantibody-negative adults were more likely to be male (75% vs 59%), had a higher BMI (27 vs 24 kg/m²) and were less likely to have other autoimmune conditions (2% vs 10%) than autoantibody-positive adults (all p<0.0001). In both adults and children, type 1 diabetes genetic risk was unaffected by the number of autoantibodies (p>0.3). These findings, along with the identification of seven misclassified adults with monogenic diabetes among autoantibody-negative adults and the results of a sensitivity analysis with and without measurement of ZnT8A, suggest that the intermediate type 1 diabetes genetic risk in autoantibody-negative adults is more likely to be explained by the inclusion of misclassified non-autoimmune diabetes (estimated to represent 67% of all antibody-negative adults, 95% CI 61%, 73%) than by the presence of unmeasured autoantibodies or by a discrete form of diabetes. When these estimated individuals with non-autoimmune diabetes were adjusted for, the prevalence of autoantibody positivity in adult-onset type 1 diabetes was similar to that in children (93% vs 91%, p=0.4).

CONCLUSIONS/INTERPRETATION

The inclusion of non-autoimmune diabetes is the most likely explanation for the observed lower rate of autoantibody positivity in clinician-diagnosed adult-onset type 1 diabetes. Our data support the utility of islet autoantibody measurement in clinician-suspected adult-onset type 1 diabetes in routine clinical practice.

Combined detection of islet autoantibodies for clinical diagnosis of type 1 diabetes in the low-prevalence population

CONTEXT

Single positive islet autoantibodies (IAbs), sometimes detected in healthy individuals and low risk type 1 diabetes (T1D) patients, are considered to be irrelevant to the development of diabetes, making it difficult to diagnose and classify adult-onset diabetics.

OBJECTIVE

To determine the significance and clinical value of IAbs in T1D diagnosis in the low-prevalence population; and to explore whether electrochemiluminescence (ECL)-IAb detection assay can improve the clinical utility of IAbs in the immunodiagnosis of T1D in the low-prevalence population.

PARTICIPANTS AND METHODS

A total of 633 newly-diagnosed adult-onset diabetic patients (≥18 years old) were divided into two groups according to their clinical phenotypes: 575 patients with age at diagnosis ≥35 years and body mass index (BMI) ≥ 24 kg/m2 were considered a low-prevalence population (population with a low prevalence of T1D) and the other 58 patients were considered a high-prevalence population. All the samples from 633 participants were tested with IAbs using standard radiobinding assays (RBA) and electrochemiluminescence (ECL) assay, in parallel.

RESULTS

Compared with the high-prevalence population, fewer positive IAbs (94/575, 16.3% vs. 28/58, 48.3%) were detected in the low-prevalence population, and more of which (69/94, 73.4% vs. 9/28, 32.2%) were positive for a single IAb, with GADA being the most prevalent single-IAb. Single-IAb detection in the low-prevalence population did not always suggest T1D phenotype. Combined detection of IAbs by RBA and ECL assays had a significant clinical utility to distinguish autoimmune diabetes in the low-prevalence population with low BMI, poor β-cell function at the diagnosis, and an accelerated decline in β-cell function during the follow-up.

CONCLUSIONS

Combined autoantibody detection by RBA and ECL assays improved differentiating autoimmune from non-autoimmune diabetes in the low-prevalence population.

Pediatric obesity-Long-term consequences and effect of weight loss

Childhood obesity is, according to the WHO, one of the most serious challenges of the 21st century. More than 100 million children have obesity today. Already during childhood, almost all organs are at risk of being affected by obesity. In this review, we present the current knowledge about diseases associated with childhood obesity and how they are affected by weight loss. One major causative factor is obesity-induced low-grade chronic inflammation, which can be observed already in preschool children. This inflammation-together with endocrine, paracrine, and metabolic effects of obesity-increases the long-term risk for several severe diseases. Type 2 diabetes is increasingly prevalent in adolescents and young adults who have had obesity during childhood. When it is diagnosed in young individuals, the morbidity and mortality rate is higher than when it occurs later in life, and more dangerous than type 1 diabetes. Childhood obesity also increases the risk for several autoimmune diseases such as multiple sclerosis, Crohn's disease, arthritis, and type 1 diabetes and it is well established that childhood obesity also increases the risk for cardiovascular disease. Consequently, childhood obesity increases the risk for premature mortality, and the mortality rate is three times higher already before 30 years of age compared with the normal population. The risks associated with childhood obesity are modified by weight loss. However, the risk reduction is affected by the age at which weight loss occurs. In general, early weight loss-that is, before puberty-is more beneficial, but there are marked disease-specific differences.

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.

Toward an Improved Classification of Type 2 Diabetes: Lessons From Research into the Heterogeneity of a Complex Disease

CONTEXT

Accumulating evidence indicates that type 2 diabetes (T2D) is phenotypically heterogeneous. Defining and classifying variant forms of T2D are priorities to better understand its pathophysiology and usher clinical practice into an era of "precision diabetes."

EVIDENCE ACQUISITION AND METHODS

We reviewed literature related to heterogeneity of T2D over the past 5 decades and identified a range of phenotypic variants of T2D. Their descriptions expose inadequacies in current classification systems. We attempt to link phenotypically diverse forms to pathophysiology, explore investigative methods that have characterized "atypical" forms of T2D on an etiological basis, and review conceptual frameworks for an improved taxonomy. Finally, we propose future directions to achieve the goal of an etiological classification of T2D.

EVIDENCE SYNTHESIS

Differences among ethnic and racial groups were early observations of phenotypic heterogeneity. Investigations that uncover complex interactions of pathophysiologic pathways leading to T2D are supported by epidemiological and clinical differences between the sexes and between adult and youth-onset T2D. Approaches to an etiological classification are illustrated by investigations of atypical forms of T2D, such as monogenic diabetes and syndromes of ketosis-prone diabetes. Conceptual frameworks that accommodate heterogeneity in T2D include an overlap between known diabetes types, a "palette" model integrated with a "threshold hypothesis," and a spectrum model of atypical diabetes.

CONCLUSION

The heterogeneity of T2D demands an improved, etiological classification scheme. Excellent phenotypic descriptions of emerging syndromes in different populations, continued clinical and molecular investigations of atypical forms of diabetes, and useful conceptual models can be utilized to achieve this important goal.

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.

Autoantibody-Negative Type 1 Diabetes: A Neglected Subtype

Up to 15% of individuals with a clinical phenotype of type 1 diabetes (T1D) do not have evidence of seropositivity for pancreatic islet autoantibodies. On this basis, they are classified as nonimmune or idiopathic, and remain an understudied population, as they are excluded from T1D immunomodulatory trials. Our limited understanding of the disease aetiopathogenesis in autoantibody-negative T1D hinders our ability to improve diagnostic pathways and discover novel therapeutic agents; particularly as we progress towards an era of precision medicine. This review summarises the current understanding and challenges in studying autoantibody-negative T1D. We review the literature regarding T1D classification, and the role of autoimmunity and defects in the immunogenic pathway that may distinguish autoantibody-positive and -negative T1D.

Beta cell function in participants with single or multiple islet autoantibodies at baseline in the TEDDY Family Prevention Study: TEFA

Aim

The aim of the present study was to assess beta cell function based on an oral glucose tolerance test (OGTT) in participants with single islet autoantibody or an intravenous glucose tolerance test (IvGTT) in participants with multiple islet autoantibodies.

Materials and methods

Healthy participants in Sweden and Finland, between 2 and 49.99 years of age previously identified as positive for a single (n = 30) autoantibody to either insulin, glutamic acid decarboxylase, islet antigen-2, zinc transporter 8 or islet cell antibodies or multiple autoantibodies (n = 46), were included. Participants positive for a single autoantibody underwent a 6-point OGTT while participants positive for multiple autoantibodies underwent an IvGTT. Glucose, insulin and C-peptide were measured from OGTT and IvGTT samples.

Results

All participants positive for a single autoantibody had a normal glucose tolerance test with 120 minutes glucose below 7.70 mmol/L and HbA1c values within the normal range (<42 mmol/mol). Insulin responses to the glucose challenge on OGTT ranged between 13.0 and 143 mIU/L after 120 minutes with C-peptide values between 0.74 and 4.60 nmol/L. In Swedish participants, the first-phase insulin response (FPIR) on IvGTT was lower in those positive for three or more autoantibodies (n = 13; median 83.0 mIU/L; range 20.0-343) compared to those with two autoantibodies (n = 15; median 146 mIU/L; range 19.0-545; P = .0330).

Conclusion

Participants positive for a single autoantibody appeared to have a normal beta cell function. Participants positive for three or more autoantibodies had a lower FPIR as compared to participants with two autoantibodies, supporting the view that their beta cell function had deteriorated.

Pancreatic islet reserve in type 1 diabetes

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by pancreatic islet β cell loss and dysfunction resulting in insulin deficiency and hyperglycemia. During a presymptomatic phase of established β cell autoimmunity, β cell loss may first be evident through assessment of β cell secretory capacity, a measure of functional β cell mass. Reduction in pancreatic islet β cell reserve eventually manifests as impaired first-phase insulin response to glucose and abnormal glucose tolerance, which progresses until the functional capacity for β cell secretion can no longer meet the demand for insulin to control glycemia. A functional β cell mass of ∼25% of normal may be required to avoid symptomatic T1D but is already associated with dysregulated glucagon secretion. With symptomatic T1D, stimulated C-peptide levels >0.60 ng/mL (0.200 pmol/mL) indicate the presence of clinically meaningful residual β cell function for contributing to glycemic control, although even higher residual C-peptide appears necessary for evidencing glucose-dependent islet β and α cell function that may contribute to maintaining (near)normal glycemia. β cell replacement by islet transplantation can restore a physiologic reserve capacity for insulin secretion, confirming thresholds for functional β cell mass required for independence from insulin therapy.