Progression of type 1 diabetes is associated with high levels of soluble PD-1 in islet autoantibody-positive children.

AIMS/HYPOTHESIS: Type 1 diabetes is an autoimmune disorder that is characterised by destruction of pancreatic beta cells by autoreactive T lymphocytes. Although islet autoantibodies (AAb) are an indicator of disease progression, specific immune biomarkers that can be used as target molecules to halt development of type 1 diabetes have not been discovered. Soluble immune checkpoint molecules (sICM) play a pivotal role in counteracting excessive lymphocyte responses, but their role in type 1 diabetes is unexplored. In this longitudinal study, we measured sICM levels in AAb-positive (AAb+) children to identify molecules related to type 1 diabetes progression. METHODS: We measured the levels of 14 sICM in the sera of AAb+ children (n=57) compared to those with recent-onset type 1 diabetes (n=79) and healthy children (n=44), obtained from two cohorts. AAb+ children were followed up and divided based on their progression to type 1 diabetes (AAbP) or not (AAbNP) (if they lost islet autoimmunity and did not develop disease in subsequent years). sICM were also measured in the sample taken at the visit closest to disease onset in AAbP children. RESULTS: We found that AAb+ children had a distinct sICM profile compared with healthy children and those with recent-onset type 1 diabetes. In addition, AAb+ children who progressed to type 1 diabetes (AAbP) had higher sICM concentrations than non-progressors (AAbNP). Further, sICM levels decreased in AAbP children close to disease onset. Application of Cox regression models highlighted that high concentrations of soluble programmed cell death protein 1 (sPD-1) are associated with type 1 diabetes progression (HR 1.71; 95% CI 1.16, 2.51; p=0.007). CONCLUSIONS/INTERPRETATION: This study reveals an sICM profile that is dysregulated during the preclinical stage of type 1 diabetes, and identifies sPD-1 as a pathophysiologically-relevant molecule that is associated with disease progression, offering a potential target for early interventions in autoimmune diabetes.

Islet autoantibody frequency in relatives of children with type 1 diabetes who have a type 2 diabetes diagnosis.

AIM: This study aimed to evaluate characteristics of autoimmunity in individuals who have a type 2 diagnosis and are relatives of children with type 1 diabetes. METHODS: Pre-diagnosis samples (median 17 months before onset) from relatives who were later diagnosed with type 2 diabetes were measured for autoantibodies to glutamate decarboxylase 65 (GADA), islet antigen-2 (IA-2A), zinc transporter 8 (ZnT8A) and insulin (IAA) as well as the type 1 diabetes genetic risk score (GRS2). Associations between islet autoantibodies, insulin treatment and GRS2 were analysed using Fisher's exact and t-tests. RESULTS: Among 226 relatives (64% men; mean age at sampling 41 years; mean age 54 years at diagnosis), 32 (14%) were islet autoantibody-positive for at least one autoantibody more than a decade before diagnosis. Approximately half of these (n = 15) were treated with insulin. GADA-positivity was higher in insulin-treated relatives than in non-insulin-treated relatives (12/18 [67%] vs. 6/18 [33%], p < 0.001). IAA-positivity was observed in 13/32 (41%) of relatives with autoantibodies. GRS2 scores were increased in autoantibody-positive relatives (p = 0.032), but there was no clear evidence for a difference according to treatment (p = 0.072). CONCLUSION: This study highlights the importance of measuring islet autoantibodies, including IAA, in relatives of people with type 1 diabetes to avoid misdiagnosis.

Type 1 diabetes and inborn errors of immunity: Complete strangers or 2 sides of the same coin?

Type 1 diabetes (T1D) is a polygenic disease and does not follow a mendelian pattern. Inborn errors of immunity (IEIs), on the other hand, are caused by damaging germline variants, suggesting that T1D and IEIs have nothing in common. Some IEIs, resulting from mutations in genes regulating regulatory T-cell homeostasis, are associated with elevated incidence of T1D. The genetic spectrum of IEIs is gradually being unraveled; consequently, molecular pathways underlying human monogenic autoimmunity are being identified. There is an appreciable overlap between some of these pathways and the genetic variants that determine T1D susceptibility, suggesting that after all, IEI and T1D are 2 sides of the same coin. The study of monogenic IEIs with a variable incidence of T1D has the potential to provide crucial insights into the mechanisms leading to T1D. These insights contribute to the definition of T1D endotypes and explain disease heterogeneity. In this review, we discuss the interconnected pathogenic pathways of autoimmunity, ß-cell function, and primary immunodeficiency. We also examine the role of environmental factors in disease penetrance as well as the circumstantial evidence of IEI drugs in preventing and curing T1D in individuals with IEIs, suggesting the repositioning of these drugs also for T1D therapy.

Children diagnosed with presymptomatic type 1 diabetes through public health screening have milder diabetes at clinical manifestation.

AIMS/HYPOTHESIS: We aimed to determine whether disease severity was reduced at onset of clinical (stage 3) type 1 diabetes in children previously diagnosed with presymptomatic type 1 diabetes in a population-based screening programme for islet autoantibodies. METHODS: Clinical data obtained at diagnosis of stage 3 type 1 diabetes were evaluated in 128 children previously diagnosed with presymptomatic early-stage type 1 diabetes between 2015 and 2022 in the Fr1da study and compared with data from 736 children diagnosed with incident type 1 diabetes between 2009 and 2018 at a similar age in the DiMelli study without prior screening. RESULTS: At the diagnosis of stage 3 type 1 diabetes, children with a prior early-stage diagnosis had lower median HbA1c (51 mmol/mol vs 91 mmol/mol [6.8% vs 10.5%], p<0.001), lower median fasting glucose (5.3 mmol/l vs 7.2 mmol/l, p<0.05) and higher median fasting C-peptide (0.21 nmol/l vs 0.10 nmol/l, p<0.001) compared with children without previous early-stage diagnosis. Fewer participants with prior early-stage diagnosis had ketonuria (22.2% vs 78.4%, p<0.001) or required insulin treatment (72.3% vs 98.1%, p<0.05) and only 2.5% presented with diabetic ketoacidosis at diagnosis of stage 3 type 1 diabetes. Outcomes in children with a prior early-stage diagnosis were not associated with a family history of type 1 diabetes or diagnosis during the COVID-19 pandemic. A milder clinical presentation was observed in children who participated in education and monitoring after early-stage diagnosis. CONCLUSIONS/INTERPRETATION: Diagnosis of presymptomatic type 1 diabetes in children followed by education and monitoring improved clinical presentation at the onset of stage 3 type 1 diabetes.

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.

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

AIMS/HYPOTHESIS: Islet autoantibodies can be detected prior to the onset of type 1 diabetes and are important tools for aetiologic studies, prevention trials and disease screening. Current risk stratification models rely on the positivity status of islet autoantibodies alone, but additional autoantibody characteristics may be important for understanding disease onset. This work aimed to determine if a data-driven model incorporating characteristics of islet autoantibody development, including timing, type and titre, could stratify risk for type 1 diabetes onset. METHODS: Data on autoantibodies against GAD (GADA), tyrosine phosphatase islet antigen-2 (IA-2A) and insulin (IAA) were obtained for 1,415 children enrolled in The Environmental Determinants of Diabetes in the Young study with at least one positive autoantibody measurement from years 1 to 12 of life. Unsupervised machine learning algorithms were trained to identify clusters of autoantibody development based on islet autoantibody timing, type and titre. Risk for type 1 diabetes across each identified cluster was evaluated using time-to-event analysis. RESULTS: We identified 2-4 clusters in each year cohort that differed by autoantibody timing, titre and type. During the first 3 years of life, risk for type 1 diabetes onset was driven by membership in clusters with high titres of all three autoantibodies (1-year risk: 20.87-56.25%, 5-year risk: 67.73-69.19%). Type 1 diabetes risk transitioned to type-specific titres during ages 4 to 8, as clusters with high titres of IA-2A (1-year risk: 20.88-28.93%, 5-year risk: 62.73-78.78%) showed faster progression to diabetes compared with high titres of GADA (1-year risk: 4.38-6.11%, 5-year risk: 25.06-31.44%). The importance of high GADA titres decreased during ages 9 to 12, with clusters containing high titres of IA-2A alone (1-year risk: 14.82-30.93%) or both GADA and IA-2A (1-year risk: 8.27-25.00%) demonstrating increased risk. CONCLUSIONS/INTERPRETATION: This unsupervised machine learning approach provides a novel tool for stratifying risk for type 1 diabetes onset using multiple autoantibody characteristics. These findings suggest that age-dependent changes in IA-2A titres modulate risk for type 1 diabetes onset across 12 years of life. Overall, this work supports incorporation of islet autoantibody timing, type and titre in risk stratification models for aetiologic studies, prevention trials and disease screening.

The countdown to type 1 diabetes: when, how and why does the clock start?

'The clock to type 1 diabetes has started when islet antibodies are first detected', commented George Eisenbarth with regard to the pathogenesis of type 1 diabetes. This review focuses on 'starting the clock', i.e. the initiation of pre-symptomatic islet autoimmunity/the first appearance of islet autoantibodies. In particular, this review addresses why susceptibility to developing islet autoimmunity is greatest in the first 2 years of life and why beta cells are a frequent target of the immune system during this fertile period. A concept for the development of beta cell autoimmunity in childhood is discussed and three factors are highlighted that contribute to this early predisposition: (1) high beta cell activity and potential vulnerability to stress; (2) high rates of and first exposures to infection; and (3) a heightened immune response, with a propensity for T helper type 1 (Th1) immunity. Arguments are presented that beta cell injury, accompanied by activation of an inflammatory immune response, precedes the initiation of autoimmunity. Finally, the implications for strategies aimed at primary prevention for a world without type 1 diabetes are discussed.

The challenges of identifying and studying type 1 diabetes in adults.

Diagnosing type 1 diabetes in adults is difficult since type 2 diabetes is the predominant diabetes type, particularly with an older age of onset (approximately >30 years). Misclassification of type 1 diabetes in adults is therefore common and will impact both individual patient management and the reported features of clinically classified cohorts. In this article, we discuss the challenges associated with correctly identifying adult-onset type 1 diabetes and the implications of these challenges for clinical practice and research. We discuss how many of the reported differences in the characteristics of autoimmune/type 1 diabetes with increasing age of diagnosis are likely explained by the inadvertent study of mixed populations with and without autoimmune aetiology diabetes. We show that when type 1 diabetes is defined by high-specificity methods, clinical presentation, islet-autoantibody positivity, genetic predisposition and progression of C-peptide loss remain broadly similar and severe at all ages and are unaffected by onset age within adults. Recent clinical guidance recommends routine islet-autoantibody testing when type 1 diabetes is clinically suspected or in the context of rapid progression to insulin therapy after a diagnosis of type 2 diabetes. In this moderate or high prior-probability setting, a positive islet-autoantibody test will usually confirm autoimmune aetiology (type 1 diabetes). We argue that islet-autoantibody testing of those with apparent type 2 diabetes should not be routinely undertaken as, in this low prior-prevalence setting, the positive predictive value of a single-positive islet antibody for autoimmune aetiology diabetes will be modest. When studying diabetes, extremely high-specificity approaches are needed to identify autoimmune diabetes in adults, with the optimal approach depending on the research question. We believe that until these recommendations are widely adopted by researchers, the true phenotype of late-onset type 1 diabetes will remain largely misunderstood.

Genetic determinants of type 1 diabetes in individuals with weak evidence of islet autoimmunity at disease onset.

AIMS/HYPOTHESIS: Islet autoantibodies (AAbs) are detected in >90% of individuals with clinically suspected type 1 diabetes at disease onset. A single AAb, sometimes at low titre, is often detected in some individuals, making their diagnosis uncertain. Type 1 diabetes genetic risk scores (GRS) are a useful tool for discriminating polygenic autoimmune type 1 diabetes from other types of diabetes, particularly the monogenic forms, but testing is not routinely performed in the clinic. Here, we used a type 1 diabetes GRS to screen for monogenic diabetes in individuals with weak evidence of autoimmunity, i.e. with a single AAb at disease onset. METHODS: In a pilot study, we genetically screened 142 individuals with suspected type 1 diabetes, 42 of whom were AAb-negative, 27 of whom had a single AAb (single AAb-positive) and 73 of whom had multiple AAbs (multiple AAb-positive) at disease onset. Next-generation sequencing (NGS) was performed in 41 AAb-negative participants, 26 single AAb-positive participants and 60 multiple AAb-positive participants using an analysis pipeline of more than 200 diabetes-associated genes. RESULTS: The type 1 diabetes GRS was significantly lower in AAb-negative individuals than in those with a single and multiple AAbs. Pathogenetic class 4/5 variants in MODY or monogenic diabetes genes were identified in 15/41 (36.6%) AAb-negative individuals, while class 3 variants of unknown significance were identified in 17/41 (41.5%). Residual C-peptide levels at diagnosis were higher in individuals with mutations compared to those without pathogenetic variants. Class 3 variants of unknown significance were found in 11/26 (42.3%) single AAb-positive individuals, and pathogenetic class 4/5 variants were present in 2/26 (7.7%) single AAb-positive individuals. No pathogenetic class 4/5 variants were identified in multiple AAb-positive individuals, but class 3 variants of unknown significance were identified in 19/60 (31.7%) patients. Several patients across the three groups had more than one class 3 variant. CONCLUSIONS/INTERPRETATION: These findings provide insights into the genetic makeup of patients who show weak evidence of autoimmunity at disease onset. Absence of islet AAbs or the presence of a single AAb together with a low type 1 diabetes GRS may be indicative of a monogenic form of diabetes, and use of NGS may improve the accuracy of diagnosis.

Consortium-based approach to receiving an EMA qualification opinion on the use of islet autoantibodies as enrichment biomarkers in type 1 diabetes clinical studies.

The development of medical products that can delay or prevent progression to stage 3 type 1 diabetes faces many challenges. Of note, optimising patient selection for type 1 diabetes prevention clinical trials is hindered by significant patient heterogeneity and a lack of characterisation of the time-varying probability of progression to stage 3 type 1 diabetes in individuals positive for two or more islet autoantibodies. To meet these needs, the Critical Path Institute's Type 1 Diabetes Consortium was launched in 2017 as a pre-competitive public-private partnership between stakeholders from the pharmaceutical industry, patient advocacy groups, philanthropic organisations, clinical researchers, the National Institutes of Health and the Food and Drug Administration. The Type 1 Diabetes Consortium acquired and aggregated data from three longitudinal observational studies, Environmental Determinants of Diabetes in the Young (TEDDY), Diabetes Autoimmunity Study in the Young (DAISY) and TrialNet Pathway to Prevention (TN01), and used analysis subsets of these data to support the model-based qualification of islet autoantibodies as enrichment biomarkers for patient selection in type 1 diabetes prevention trials, including registration studies. The Type 1 Diabetes Consortium has now received a qualification opinion from the European Medicines Agency for the use of these biomarkers, a major success for the field of type 1 diabetes. This endorsement will improve product developers' ability to design clinical trials of agents intended to prevent or delay type 1 diabetes that are reduced in size and/or length, while being adequately powered.

SARS-CoV-2 Positive Serology and Islet Autoantibodies in Newly Diagnosed Pediatric Cases of Type 1 Diabetes Mellitus: A Single-Center Cohort Study.

Acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, although presenting less severe forms of the disease in children, seems to play a role in the development of other conditions, including type 1 diabetes mellitus (T1DM). After the beginning of the pandemic, an increase in the number of T1DM pediatric patients was observed in several countries, thus leading to many questions about the complex relationship between SARS-CoV-2 infection and T1DM. Our study aimed to highlight possible correlations between SARS-CoV-2 serology and T1DM onset. Therefore, we performed an observational retrospective cohort study that included 158 children diagnosed with T1DM in the period April 2021-April 2022. The presence or absence of SARS-CoV-2 and T1DM-specific antibodies and other laboratory findings were assessed. In the group of patients with positive SARS-CoV-2 serology, a higher percentage had detectable IA-2A antibodies, more children were positive for all three islet autoantibodies determined (GADA, ICA, and IA-2A), and a higher mean HbA1c value was found. No difference existed between the two groups regarding DKA presence and severity. A lower C-peptide level was found in the patients presenting diabetic ketoacidosis (DKA) at T1DM onset. When compared to a group of patients diagnosed before the pandemic, an increased incidence of both DKA and severe DKA, as well as a higher age at diagnosis and higher levels of HbA1c were present in our study group. These findings have important implications for the ongoing monitoring and management of children with T1DM after the COVID-19 pandemic and highlight the need for further research to better understand the complex relationship between SARS-CoV-2 infection and T1DM.

A Concerted Vision to Advance the Knowledge of Diabetes Mellitus Related to Immune Checkpoint Inhibitors.

The rubric of immune-related (ir) diabetes mellitus (DM) (irDM) encompasses various hyperglycemic disorders related to immune checkpoint inhibitors (ICPis). Beyond sharing similarities with conventional DM, irDM is a distinct, yet important, entity. The present narrative review provides a comprehensive overview of the literature regarding irDM published in major databases from January 2018 until January 2023. Initially considered rare, irDM is increasingly being reported. To advance the knowledge of irDM, the present review suggests a concerted vision comprising two intertwined aspects: a scientific-centered and a patient-centered view. The scientific-centered aspect addresses the pathophysiology of irDM, integrating: (i) ICPi-induced pancreatic islet autoimmunity in genetically predisposed patients; (ii) altered gut microbiome; (iii) involvement of exocrine pancreas; (iv) immune-related acquired generalized lipodystrophy. The patient-centered aspect is both nurtured by and nurturing the four pillars of the scientific-centered aspect: awareness, diagnosis, treatment, and monitoring of irDM. The path forward is a multidisciplinary initiative towards: (i) improved characterization of the epidemiological, clinical, and immunological profile of irDM; (ii) standardization of reporting, management, and surveillance protocols for irDM leveraging global registries; (iii) patient stratification according to personalized risk for irDM; (iv) new treatments for irDM; and (v) uncoupling ICPi efficacy from immunotoxicity.

Congenital beta cell defects are not associated with markers of islet autoimmunity, even in the context of high genetic risk for type 1 diabetes.

AIMS/HYPOTHESIS: A key unanswered question in type 1 diabetes is whether beta cells initiate their own destruction or are victims of an aberrant immune response (beta cell suicide or homicide?). To investigate this, we assessed islet autoantibodies in individuals with congenital beta cell defects causing neonatal diabetes mellitus (NDM). METHODS: We measured autoantibodies to GAD (GADA), islet antigen-2 (IA-2A) and zinc transporter 8 (ZnT8A) in 242 individuals with NDM (median age diagnosed 1.8 months [IQR 0.39-2.9 months]; median age collected 4.6 months [IQR 1.8-27.6 months]; median diabetes duration 2 months [IQR 0.6-23 months]), including 75 whose NDM resulted from severe beta cell endoplasmic reticulum (ER) stress. As a control cohort we also tested samples from 69 diabetes-free individuals (median age collected 9.9 months [IQR 9.0-48.6 months]) for autoantibodies. RESULTS: We found low prevalence of islet autoantibodies in individuals with monogenic NDM; 13/242 (5.4% [95% CI 2.9, 9.0%]) had detectable GADA, IA-2A and/or ZnT8A. This was similar to the proportion in the control participants who did not have diabetes (1/69 positive [1.4%, 95% CI 0.03, 7.8%], p=0.3). Importantly, monogenic individuals with beta cell ER stress had a similar rate of GADA/IA-2A/ZnT8A positivity to non-ER stress aetiologies (2.7% [95% CI 0.3, 9.3%] vs 6.6% [95% CI 3.3, 11.5%] p=0.4). We observed no association between islet autoimmunity and genetic risk, age at testing (including 30 individuals >10 years at testing) or diabetes duration (p>0.4 for all). CONCLUSIONS/INTERPRETATION: Our data support the hypothesis that beta cell stress/dysfunction alone does not lead to the production of islet autoantibodies, even in the context of high-risk HLA types. This suggests that additional factors are required to trigger an autoimmune response towards beta cells.

Progression likelihood score identifies substages of presymptomatic type 1 diabetes in childhood public health screening.

AIMS/HYPOTHESIS: The aim of this study was to develop strategies that identify children from the general population who have late-stage presymptomatic type 1 diabetes and may, therefore, benefit from immune intervention. METHODS: We tested children from Bavaria, Germany, aged 1.75-10 years, enrolled in the Fr1da public health screening programme for islet autoantibodies (n=154,462). OGTT and HbA1c were assessed in children with multiple islet autoantibodies for diagnosis of presymptomatic stage 1 (normoglycaemia) or stage 2 (dysglycaemia) type 1 diabetes. Cox proportional hazards and penalised logistic regression of autoantibody, genetic, metabolic and demographic information were used to develop a progression likelihood score to identify children with stage 1 type 1 diabetes who progressed to stage 3 (clinical) type 1 diabetes within 2 years. RESULTS: Of 447 children with multiple islet autoantibodies, 364 (81.4%) were staged. Undiagnosed stage 3 type 1 diabetes, presymptomatic stage 2, and stage 1 type 1 diabetes were detected in 41 (0.027% of screened children), 30 (0.019%) and 293 (0.19%) children, respectively. The 2 year risk for progression to stage 3 type 1 diabetes was 48% (95% CI 34, 58) in children with stage 2 type 1 diabetes (annualised risk, 28%). HbA1c, islet antigen-2 autoantibody positivity and titre, and the 90 min OGTT value were predictors of progression in children with stage 1 type 1 diabetes. The derived progression likelihood score identified substages corresponding to ≤90th centile (stage 1a, n=258) and >90th centile (stage 1b, n=29; 0.019%) of stage 1 children with a 4.1% (95% CI 1.4, 6.7) and 46% (95% CI 21, 63) 2 year risk of progressing to stage 3 type 1 diabetes, respectively. CONCLUSIONS/INTERPRETATION: Public health screening for islet autoantibodies found 0.027% of children to have undiagnosed clinical type 1 diabetes and 0.038% to have undiagnosed presymptomatic stage 2 or stage 1b type 1 diabetes, with 50% risk to develop clinical type 1 diabetes within 2 years.

The measurement of autoantibodies to insulin informs diagnosis of diabetes in a childhood population negative for other autoantibodies.

AIMS: Some childhood type 1 diabetes cases are islet autoantibody negative at diagnosis. Potential explanations include misdiagnosis of genetic forms of diabetes or insufficient islet autoantibody testing. Many NHS laboratories offer combinations of three autoantibody markers. We sought to determine the benefit of testing for additional islet autoantibodies, including insulin (IAA) and tetraspanin 7 (TSPAN7A). METHODS: Radiobinding assays (RBAs) were used to test for four islet autoantibodies in children with newly diagnosed type 1 diabetes (n = 486; 54.1% male; median age 10.4 years [range 0.7-18.0]; median duration 1 day [range -183 to 14]). Islet autoantibody negative children were tested for TSPAN7A using a luminescence-based test. Where available, islet cell antibody (ICA) and human leucocyte antigen (HLA) data were considered. RESULTS: Using three autoantibody markers, 21/486 (4.3%) children were autoantibody negative. Testing for IAA classified a further 9/21 (42.9%) children as autoantibody positive. Of the remaining 12 (2.5%) autoantibody negative children, all were TPAN7A negative, seven were ICA negative and one was positive for the protective variant DQB1*0602. One was subsequently diagnosed with Maturity Onset of Diabetes in the Young, but follow-up was not available in all cases. CONCLUSIONS: Using highly sensitive assays, testing for three autoantibodies fails to detect islet autoimmunity in approximately 1/20 children diagnosed with type 1 diabetes. Testing for IAA in children <5 years and GADA in those >10 years was the most effective strategy for detecting islet autoimmunity. The ability to test for all islet autoantibodies should inform clinical decisions and make screening for monogenic diabetes more cost-effective.

Autoantibodies against ATP4A are a feature of the abundant autoimmunity that develops in first-degree relatives of patients with type 1 diabetes.

OBJECTIVE: Type 1 diabetes is associated with autoantibodies to different organs that include the gut. The objective of the study was to determine the risk of developing gastric parietal cell autoimmunity in relation to other autoimmunity in individuals with a family history of type 1 diabetes. METHODS: Autoantibodies to the parietal cell autoantigen, H+ /K+ ATPase subunit A (ATP4A) was measured in 2218 first-degree relatives of patients with type 1 diabetes, who were prospectively followed from birth for a median of 14.5 years. All were also tested regularly for the development of islet autoantibodies, transglutaminase autoantibodies, and thyroid peroxidase autoantibodies. RESULTS: The cumulative risk to develop ATP4A autoantibodies was 8.1% (95% CI, 6.6-9.6) by age 20 years with a maximum incidence observed at age 2 years. Risk was increased in females (HR, 1.9; 95% CI, 1.3-2.8; p = 0.0004), relatives with the HLA DR4-DQ8/DR4-DQ8 genotype (HR, 3.4; 95% CI, 1.9-5.9; p < 0.0001) and in participants who also had thyroid peroxidase autoantibodies (HR, 3.7; 95% CI, 2.5-5.5; p < 0.0001). Risk for at least one of ATP4A-, islet-, transglutaminase-, or thyroid peroxidase-autoantibodies was 24.7% (95% CI, 22.6-26.7) by age 20 years and was 47.3% (95% CI, 41.3-53.3) in relatives who had an HLA DR3/DR4-DQ8, DR4-DQ8/DR4-DQ8, or DR3/DR3 genotype (p < 0.0001 vs. other genotypes). CONCLUSIONS: Relatives of patients with type 1 diabetes who have risk genotypes are at very high risk for the development of autoimmunity against gastric and other organs.

HbA1c as a time predictive biomarker for an additional islet autoantibody and type 1 diabetes in seroconverted TEDDY children.

OBJECTIVE: Increased level of glycated hemoglobin (HbA1c) is associated with type 1 diabetes onset that in turn is preceded by one to several autoantibodies against the pancreatic islet beta cell autoantigens; insulin (IA), glutamic acid decarboxylase (GAD), islet antigen-2 (IA-2) and zinc transporter 8 (ZnT8). The risk for type 1 diabetes diagnosis increases by autoantibody number. Biomarkers predicting the development of a second or a subsequent autoantibody and type 1 diabetes are needed to predict disease stages and improve secondary prevention trials. This study aimed to investigate whether HbA1c possibly predicts the progression from first to a subsequent autoantibody or type 1 diabetes in healthy children participating in the Environmental Determinants of Diabetes in the Young (TEDDY) study. RESEARCH DESIGN AND METHODS: A joint model was designed to assess the association of longitudinal HbA1c levels with the development of first (insulin or GAD autoantibodies) to a second, second to third, third to fourth autoantibody or type 1 diabetes in healthy children prospectively followed from birth until 15 years of age. RESULTS: It was found that increased levels of HbA1c were associated with a higher risk of type 1 diabetes (HR 1.82, 95% CI [1.57-2.10], p < 0.001) regardless of first appearing autoantibody, autoantibody number or type. A decrease in HbA1c levels was associated with the development of IA-2A as a second autoantibody following GADA (HR 0.85, 95% CI [0.75, 0.97], p = 0.017) and a fourth autoantibody following GADA, IAA and ZnT8A (HR 0.90, 95% CI [0.82, 0.99], p = 0.036). HbA1c trajectory analyses showed a significant increase of HbA1c over time (p < 0.001) and that the increase is more rapid as the number of autoantibodies increased from one to three (p < 0.001). CONCLUSION: In conclusion, increased HbA1c is a reliable time predictive marker for type 1 diabetes onset. The increased rate of increase of HbA1c from first to third autoantibody and the decrease in HbA1c predicting the development of IA-2A are novel findings proving the link between HbA1c and the appearance of autoantibodies.

Efficacy of a new enzyme-linked immunosorbent assay system for three islet cell autoantibodies in Japanese patients with acute-onset type 1 diabetes.

To evaluate the clinical efficacy of a new enzyme-linked immunosorbent assay (ELISA) system for simultaneously detecting three islet cell autoantibodies against glutamic acid decarboxylase (GADA), insulinoma-associated antigen-2 (IA-2A), and zinc transporter 8 (ZnT8A) (3 Screen ICA ELISA) in Japanese patients with acute-onset type 1 diabetes (T1D). In addition, clinical factors affecting the 3 Screen ICA ELISA index were investigated. We compared the positivity values of 3 Screen ICA ELISA with that of each autoantibody alone in 97 patients with acute-onset T1D (mean age 48.7 years, 49% male) and 100 non-diabetic subjects (mean age 47.0 years, 50% male). Serum thyroid stimulating hormone receptor antibody, thyroid peroxidase antibody (TPOAb) and thyroglobulin autoantibody levels were also evaluated. The cut-off value of the 3 Screen ICA ELISA was determined based on the 97th percentile of 100 non-diabetic controls (threshold for positivity, ≥14 index). The mean age of disease onset and duration of diabetes were 34.2 years and 14.5 years, respectively. Among all T1D patients, the positivity of 3 Screen ICA ELISA was 71.1%, while that of GADA, IA-2A, and ZnT8A were 59.8%, 25.8%, and 25.8%, respectively. The median 3 Screen ICA index was 121.9 (8.7-468.2) and was associated with titers of each autoantibody, most so with GADA, and was significantly higher in TPOAb-positive patients than in TPOAb-negative patients. Our findings suggests that the 3 Screen ICA ELISA may be a time-saving diagnostic tool for evaluating islet autoantibodies in acute-onset T1D patients.

Four decades of the Bart's Oxford study: Improved tests to predict type 1 diabetes.

Recent success in clinical trials to delay the onset of type 1 diabetes has heralded a new era of type 1 diabetes research focused on the most accurate methods to predict risk and progression rate in the general population. Risk prediction for type 1 diabetes has been ongoing since the 1970s and 1980s when human leucocyte antigen (HLA) variants and islet autoantibodies associated with type 1 diabetes were first described. Development of prediction methodologies has relied on well-characterised cohorts and samples. The Bart's Oxford (BOX) study of type 1 diabetes has been recruiting children with type 1 diabetes and their first (and second)-degree relatives since 1985. In this review, we use the timeline of the study to review the accompanying basic science developments which have facilitated improved prediction by genetic (HLA analysis through to genetic risk scores) and biochemical strategies (islet cell autoantibodies through to improved individual tests for antibodies to insulin, glutamate decarboxylase, the tyrosine phosphatase IA-2, zinc transporter 8 and tetraspanin 7). The type 1 diabetes community are poised to move forward using the best predictive markers to predict and delay the onset of type 1 diabetes.

Establishing reference intervals for islet autoantibodies in Han Chinese type 1 diabetes.

Currently, islet autoantibodies (IAbs) constitute the most reliable marker for detecting the autoimmune process of type 1 diabetes (T1D). However, there are no appropriate reference intervals (RIs) to interpret the results of IAbs in China. In this study, we aimed to establish the RIs of four common IAbs based on the Han Chinese population and evaluate their clinical diagnostic values in patients with T1D. We collected 177 blood samples from healthy volunteers to detect the levels of IAbs directed against insulin (IAA), glutamic acid decarboxylase-65 (GADA), insulinoma antigen 2 (IA-2A), and zinc transporter-8 (ZnT8A) using a chemiluminescence immunoassay. RIs were calculated using nonparametric 95th percentile intervals in accordance with the Clinical and Laboratory Standards Institute guidelines, and their clinical diagnostic values were evaluated by detecting the levels of IAbs of 140 blood samples from patients with T1D in a clinical setting. We defined 138 individuals as the apparently healthy population from the 177 healthy volunteers based on the exclusion criteria. No association between the levels of the four IAbs and gender (p > .05) and age (p > .05) were found in the apparently healthy population. The combined RIs for GADA, IA-2A, ZnT8A, and IAA were 0-1.78 IU/mL, 0-3.91 IU/mL, 0-2.36 AU/mL, and 0-0.58 COI, respectively. Overall, the diagnostic efficiency for the four IAbs, especially for GADA and IAA, were improved by using the RIs established in this study. The RIs for IAbs established in this study will be a valuable tool for disease diagnosis and the therapeutic management of T1D in a clinical setting.