The longitudinal loss of islet autoantibody responses from diagnosis of type 1 diabetes occurs progressively over follow-up and is determined by low autoantibody titres, early-onset, and genetic variants

Establishing the performance and acceptability of dried blood spot sampling to screen for islet-specific autoantibodies

BACKGROUND

Islet-specific autoantibodies predate and predict the onset of type 1 diabetes and can be used to screen for presymptomatic disease. Dried blood spots (DBS) offer a convenient and reliable method for community-based capillary sampling requiring low blood volumes compared to venous collection. We aimed to verify the use of DBS for detecting autoantibodies by the ElisaRSR (3-screen) multiplex assay compared to venous sampling and also explore the acceptability of DBS sampling.

METHODS

Paired serum and DBS samples were collected from healthy controls (HC) and individuals with type 1 diabetes on insulin. Validation and verification of a 3-screen Islet cell autoantibody (IA-2A, GADA and ZnT8A) ELISA assay was undertaken for both matrices and compared. Perceived acceptability of DBS testing was explored via semi-structured interviews with parents and professional stakeholders.

RESULTS

Temporally paired serum and DBS samples were collected for 101 individuals with type 1 diabetes (aged 7-73 years) and 22 HC (aged 18-60 years). Performance characteristics were similar for serum and DBS; sensitivity for serum was 86% compared to 89% for DBS and a specificity of 97% for serum compared to 100% for DBS. Parents (n = 38) and stakeholders (n = 25) thought DBS testing offered a minimally invasive, convenient screening test. Parents emphasised choice of screening location, including home and community settings.

CONCLUSIONS

DBS sampling can be used as an alternative to serum for use with the 3-screen assay for general population type 1 diabetes autoantibody screening. DBS sampling appears acceptable to parents and stakeholders.

Autoantibodies to Truncated GAD(96-585) Antigen Stratify Risk of Early Insulin Requirement in Adult-Onset Diabetes

We investigated whether characterization of full-length GAD (f-GADA) antibody (GADA) responses could identify early insulin requirement in adult-onset diabetes. In 179 f-GADA-positive participants diagnosed with type 2 diabetes, we assessed associations of truncated GADA (t-GADA) positivity, f-GADA IgG subclasses, and f-GADA affinity with early insulin requirement (<5 years), type 1 diabetes genetic risk score (T1D GRS), and C-peptide. t-GADA positivity was lower in f-GADA-positive without early insulin in comparison with f-GADA-positive type 2 diabetes requiring insulin within 5 years, and T1D (75% vs. 91% and 95% respectively, P < 0.0001). t-GADA positivity (in those f-GADA positive) identified a group with a higher T1D genetic susceptibility (mean T1D GRS 0.248 vs. 0.225, P = 0.003), lower C-peptide (1,156 pmol/L vs. 4,289 pmol/L, P = 1 × 10-7), and increased IA-2 antigen positivity (23% vs. 6%, P = 0.03). In survival analysis, t-GADA positivity was associated with early insulin requirement compared with those only positive for f-GADA, independently from age of diagnosis, f-GADA titer, and duration of diabetes (adjusted hazard ratio 5.7 [95% CI 1.4, 23.5], P = 0.017). The testing of t-GADA in f-GADA-positive individuals with type 2 diabetes identifies those who have genetic and clinical characteristics comparable to T1D and stratifies those at higher risk of early insulin requirement.

ARTICLE HIGHLIGHTS

The INNODIA Type 1 Diabetes Natural History Study: a European cohort of newly diagnosed children, adolescents and adults

AIMS/HYPOTHESIS

Type 1 diabetes is an heterogenous condition. Characterising factors explaining differences in an individual's clinical course and treatment response will have important clinical and research implications. Our aim was to explore type 1 diabetes heterogeneity, as assessed by clinical characteristics, autoantibodies, beta cell function and glycaemic outcomes, during the first 12 months from diagnosis, and how it relates to age at diagnosis.

METHODS

Data were collected from the large INNODIA cohort of individuals (aged 1.0-45.0 years) newly diagnosed with type 1 diabetes, followed 3 monthly, to assess clinical characteristics, C-peptide, HbA1c and diabetes-associated antibodies, and their changes, during the first 12 months from diagnosis, across three age groups: <10 years; 10-17 years; and ≥18 years.

RESULTS

The study population included 649 individuals (57.3% male; age 12.1±8.3 years), 96.9% of whom were positive for one or more diabetes-related antibodies. Baseline (IQR) fasting C-peptide was 242.0 (139.0-382.0) pmol/l (AUC 749.3 [466.2-1106.1] pmol/l × min), with levels increasing with age (p<0.001). Over time, C-peptide remained lower in participants aged <10 years but it declined in all age groups. In parallel, glucose levels progressively increased. Lower baseline fasting C-peptide, BMI SD score and presence of diabetic ketoacidosis at diagnosis were associated with lower stimulated C-peptide over time. HbA1c decreased during the first 3 months (p<0.001), whereas insulin requirement increased from 3 months post diagnosis (p<0.001).

CONCLUSIONS/INTERPRETATION

In this large cohort with newly diagnosed type 1 diabetes, we identified age-related differences in clinical and biochemical variables. Of note, C-peptide was lower in younger children but there were no main age differences in its rate of decline.

Atypical Diabetes: What Have We Learned and What Does the Future Hold?

As our understanding of the pathophysiology of diabetes evolves, we increasingly recognize that many patients may have a form of diabetes that does not neatly fit with a diagnosis of either type 1 or type 2 diabetes. The discovery and description of these forms of "atypical diabetes" have led to major contributions to our collective understanding of the basic biology that drives insulin secretion, insulin resistance, and islet autoimmunity. These discoveries now pave the way to a better classification of diabetes based on distinct endotypes. In this review, we highlight the key biological and clinical insights that can be gained from studying known forms of atypical diabetes. Additionally, we provide a framework for identification of patients with atypical diabetes based on their clinical, metabolic, and molecular features. Helpful clinical and genetic resources for evaluating patients suspected of having atypical diabetes are provided. Therefore, appreciating the various endotypes associated with atypical diabetes will enhance diagnostic accuracy and facilitate targeted treatment decisions.

Diabetes Study of Children of Diverse Ethnicity and Race: Study design

AIMS

Determining diabetes type in children has become increasingly difficult due to an overlap in typical characteristics between type 1 diabetes (T1D) and type 2 diabetes (T2D). The Diabetes Study in Children of Diverse Ethnicity and Race (DISCOVER) programme is a National Institutes of Health (NIH)-supported multicenter, prospective, observational study that enrols children and adolescents with non-secondary diabetes. The primary aim of the study was to develop improved models to differentiate between T1D and T2D in diverse youth.

MATERIALS AND METHODS

The proposed models will evaluate the utility of three existing T1D genetic risk scores in combination with data on islet autoantibodies and other parameters typically available at the time of diabetes onset. Low non-fasting serum C-peptide (<0.6 nmol/L) between 3 and 10 years after diabetes diagnosis will be considered a biomarker for T1D as it reflects the loss of insulin secretion ability. Participating centres are enrolling youth (<19 years old) either with established diabetes (duration 3-10 years) for a cross-sectional evaluation or with recent onset diabetes (duration 3 weeks-15 months) for the longitudinal observation with annual visits for 3 years. Cross-sectional data will be used to develop models. Longitudinal data will be used to externally validate the best-fitting model.

RESULTS

The results are expected to improve the ability to classify diabetes type in a large and growing subset of children who have an unclear form of diabetes at diagnosis.

CONCLUSIONS

Accurate and timely classification of diabetes type will help establish the correct clinical management early in the course of the disease.

Correlation analysis between cytokines' profile, autoimmune antibodies and the duration of type 1 diabetes: A case control study in a specialized children's centre in Riyadh

OBJECTIVE

The aim of this study was to investigate the role of cytokines in children with T1D living in Saudi Arabia and their correlation with disease duration and autoimmune antibody markers.

METHODS

A case-control study was conducted in the endocrine clinic of King Abdullah Specialized Children's Hospital in Riyadh. A total of 274 T1D and healthy control children were enrolled in the study. 5 mL of venous blood samples were collected in the morning after 9 to 12 h of fasting in BD Vacutainer® EDTA tubes and centrifuged at 250g for 15 min at. Plasma was then stored at -20°C for detection of anti-islet, anti-GAD antibodies (Abs), and C-peptide using commercial ELISA kits from Thermo Fisher Scientific. The levels of cytokines were measured using commercial sandwich ELISA kits from Abcam.

RESULTS

Median differences in cytokine levels (IFN-γ, TNF-α, IL-1β, IL-2, IL-4, IL-6, IL-10, IL-13, IL-18, IL-21, IL-35, and IL-37) were significantly higher in T1D patients compared with healthy controls (p-value < .001). Spearman's Rho correlation indicated that TNFα, IL-1β, IL-4, IL-10, IL-13, and IL-21 correlated significantly with T1D Abs (p-value = .01). HbA1C correlated negatively with IL-35 and IL-37, and positively with IL-18 (p-value = .01). Linear regression analysis showed a significant increase in anti-glutamic acid antibodies (GAD) in patients with >3 years of T1D duration.

CONCLUSION

Autoantibodies remained positive at high levels in our patients over a 3-year duration of the disease and correlated with specific cytokines. The clear correlations with disease duration and profile of specific cytokines could be targets for future therapeutic interventions.