Search

BackgroundFamily conflict can reduce adolescent adherence to type 1 diabetes management tasks. The Family Teamwork in-person intervention was shown to be efficacious in reducing conflict and low adherence to diabetes-related tasks. Its reach and potential impact, however, were limited by the need to deliver the intervention sessions in person. Relational agents (ie, computerized versions of humans) have been shown to appeal to diverse audiences and may be an acceptable replacement for a human in technology-based behavior change interventions. ObjectiveThe purpose of this paper is to present the results of a pilot study assessing feasibility and acceptability of Diabetes Family Teamwork Online, an adapted version of the Family Teamwork intervention, delivered over the internet and guided by a relational agent. MethodsParent-adolescent dyads were recruited through a diabetes care clinic at a large tertiary care hospital in the southwestern United States. A one-group design, with assessments at baseline, immediate postintervention, and 3 months later, was used to assess feasibility. A priori feasibility criteria included an assessment of recruitment, completion, attrition, program satisfaction, therapeutic alliance, attitudes toward the relational agent, and data collection. The institutional review board at Baylor College of Medicine approved the protocol (H-37245). ResultsTwenty-seven adolescents aged 10 to 15 years with type 1 diabetes and their parents were enrolled. Criteria used to assess feasibility were (1) recruitment goals were met (n=20), (2) families completed ≥75% of the modules, (3) attrition rate was ≤10%, (4) program satisfaction was high (≥80% of families), (5) therapeutic alliance was high (average score of ≥60/84), (6) families expressed positive attitudes toward the relational agent (average item score of ≥5 on ≥4 items), (7) ≥80% of data were collected at post 1 and post 2, and (8) few technical issues (≤10%) occurred during intervention delivery. All feasibility criteria were met. Qualitative data confirmed that adolescents and parents had positive reactions to both the content and approach. ConclusionsThe Diabetes Family Teamwork Online intervention proved to be a feasible and acceptable method for enhancing communication around diabetes management tasks in families with an adolescent who has type 1 diabetes. International Registered Report Identifier (IRRID)RR2-10.2196/resprot.5817

The clinical diagnosis of new-onset type 1 diabetes has, for many years, been considered relatively straightforward. Recently, however, there is increasing awareness that within this single clinical phenotype exists considerable heterogeneity: disease onset spans the complete age range; genetic susceptibility is complex; rates of progression differ markedly, as does insulin secretory capacity; and complication rates, glycemic control, and therapeutic intervention efficacy vary widely. Mechanistic and immunopathological studies typically show considerable patchiness across subjects, undermining conclusions regarding disease pathways. Without better understanding, type 1 diabetes heterogeneity represents a major barrier both to deciphering pathogenesis and to the translational effort of designing, conducting, and interpreting clinical trials of disease-modifying agents. This realization comes during a period of unprecedented change in clinical medicine, with increasing emphasis on greater individualization and precision. For complex disorders such as type 1 diabetes, the option of maintaining the "single disease" approach appears untenable, as does the notion of individualizing each single patient's care, obliging us to conceptualize type 1 diabetes less in terms of phenotypes (observable characteristics) and more in terms of disease endotypes (underlying biological mechanisms). Here, we provide our view on an approach to dissect heterogeneity in type 1 diabetes. Using lessons from other diseases and the data gathered to date, we aim to delineate a roadmap through which the field can incorporate the endotype concept into laboratory and clinical practice. We predict that such an effort will accelerate the implementation of precision medicine and has the potential for impact on our approach to translational research, trial design, and clinical management.

Type 1 diabetes mellitus (T1D) is a heterogeneous condition. We aimed to study the associations between age and sex with clinical characteristics at the onset of pediatric T1D. A secondary analysis was conducted on data collected retrospectively from 706 children newly diagnosed with T1D at a large tertiary hospital in southeastern USA. Age (stratified across three cohorts from 0.84 to 18.08 years), sex, and their interaction were compared for associations with clinical characteristics of T1D at presentation by multivariable regression analyses and pairwise comparisons. Within the participants (mean age 9.71 (SD 4.10), 48.3 % female, 21.0 % Hispanic, 15.3 % non-Hispanic black and 58.7 % non-Hispanic white), children under 6 years had higher glucose (p<0.001), lower hemoglobin A1c (HbA1c) (p<0.001), and lower C-peptide (p<0.001) than the older age groups. Diabetic ketoacidosis (DKA) was more prevalent in the youngest (p=0.005) and the intermediate-aged cohorts (p=0.005), compared to the oldest group. Among the children with DKA, bicarbonate was lower in the youngest (p<0.001) and middle cohorts (p=0.013), compared to the oldest group. Younger age was associated with higher prevalence of insulin autoantibodies (IAA; p<0.001) and IA-2 autoantibodies (IA-2A; p=0.006). Males had higher glucose (p=0.001), but lower HbA1c (p=0.003), lower C-peptide (p<0.001), and lower GAD autoantibody (GADA) prevalence (p=0.001) than females. There was no significant interaction between age and sex. In children with new onset T1D, younger age and male sex were associated with findings suggestive of more rapid and aggressive T1D preclinical course, including poorer beta-cell function, and distinct islet autoantibody profiles. [ABSTRACT FROM AUTHOR]

OBJECTIVE: With high prevalence of obesity and overlapping features between diabetes subtypes, accurately classifying youth-onset diabetes can be challenging. We aimed to develop prediction models that, using characteristics available at diabetes diagnosis, can identify youth who will retain endogenous insulin secretion at levels consistent with type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: We studied 2,966 youth with diabetes in the prospective SEARCH for Diabetes in Youth study (diagnosis age ≤19 years) to develop prediction models to identify participants with fasting C-peptide ≥250 pmol/L (≥0.75 ng/mL) after >3 years' (median 74 months) diabetes duration. Models included clinical measures at the baseline visit, at a mean diabetes duration of 11 months (age, BMI, sex, waist circumference, HDL cholesterol), with and without islet autoantibodies (GADA, IA-2A) and a type 1 diabetes genetic risk score (T1DGRS). RESULTS: Models using routine clinical measures with or without autoantibodies and T1DGRS were highly accurate in identifying participants with C-peptide ≥0.75 ng/mL (17% of participants; 2.3% and 53% of those with and without positive autoantibodies) (area under the receiver operating characteristic curve [AUCROC] 0.95–0.98). In internal validation, optimism was very low, with excellent calibration (slope 0.995–0.999). Models retained high performance for predicting retained C-peptide in older youth with obesity (AUCROC 0.88–0.96) and in subgroups defined by self-reported race and ethnicity (AUCROC 0.88–0.97), autoantibody status (AUCROC 0.87–0.96), and clinically diagnosed diabetes types (AUCROC 0.81–0.92). CONCLUSIONS: Prediction models combining routine clinical measures at diabetes diagnosis, with or without islet autoantibodies or T1DGRS, can accurately identify youth with diabetes who maintain endogenous insulin secretion in the range associated with T2D. [ABSTRACT FROM AUTHOR]

ObjectiveThe type 2 diabetes-associated alleles at the TCF7L2 locus mark a type 1 diabetes phenotype characterized by single islet autoantibody positivity as well as lower glucose and higher C-peptide measures. Here, we studied whether the TCF7L2 locus influences progression of islet autoimmunity, from single to multiple (≥2) autoantibody positivity, in relatives of patients with type 1 diabetes.Research design and methodsWe evaluated 244 participants in the Type 1 Diabetes TrialNet Pathway to Prevention study with confirmed single autoantibody positivity at screening and Immunochip single nucleotide polymorphism data (47.5% male; median age 12.8 years, range 1.2-45.9; 90.2% white). We analyzed risk allele frequency at TCF7L2 rs4506565 (in linkage disequilibrium with rs7903146). Altogether, 62.6% participants carried ≥1 risk allele. Univariate and multivariable Cox proportional hazards models and Kaplan-Meier statistical methods were used.ResultsDuring follow-up (median 5.2 years, range 0.2-12.6), 62% of the single autoantibody-positive participants developed multiple autoantibody positivity. In the overall cohort, the TCF7L2 locus did not significantly predict progression to multiple autoantibody positivity. However, among single GAD65 autoantibody-positive participants (n = 158), those who carried ≥1 risk allele had a lower rate of progression to multiple autoantibody positivity (hazard ratio [HR] 0.65, P = 0.033) than those who did not, after adjustment for HLA risk haplotypes and age. Among subjects who were either IA-2 or insulin autoantibody positive only, carrying ≥1 TCF7L2 risk allele was not a significant factor overall, but in overweight or obese participants, it increased the risk of progression to multiple autoantibody positivity (HR 3.02, P = 0.016) even with adjustment for age.ConclusionsThe type 2 diabetes-associated TCF7L2 locus influences progression of islet autoimmunity, with differential effects by autoantibody specificity and interaction by obesity/overweight.

ObjectiveThe phenotypic diversity of type 1 diabetes suggests heterogeneous etiopathogenesis. We investigated the relationship of type 2 diabetes-associated transcription factor 7 like 2 (TCF7L2) single nucleotide polymorphisms (SNPs) with immunologic and metabolic characteristics at type 1 diabetes diagnosis.Research design and methodsWe studied TrialNet participants with newly diagnosed autoimmune type 1 diabetes with available TCF7L2 rs4506565 and rs7901695 SNP data (n = 810; median age 13.6 years; range 3.3-58.6). We modeled the influence of carrying a TCF7L2 variant (i.e., having 1 or 2 minor alleles) on the number of islet autoantibodies and oral glucose tolerance test (OGTT)-stimulated C-peptide and glucose measures at diabetes diagnosis. All analyses were adjusted for known confounders.ResultsThe rs4506565 variant was a significant independent factor of expressing a single autoantibody, instead of multiple autoantibodies, at diagnosis (odds ratio [OR] 1.66 [95% CI 1.07, 2.57], P = 0.024). Interaction analysis demonstrated that this association was only significant in participants ≥12 years old (n = 504; OR 2.12 [1.29, 3.47], P = 0.003) but not younger ones (n = 306, P = 0.73). The rs4506565 variant was independently associated with higher C-peptide area under the curve (AUC) (P = 0.008) and lower mean glucose AUC (P = 0.0127). The results were similar for the rs7901695 SNP.ConclusionsIn this cohort of individuals with new-onset type 1 diabetes, type 2 diabetes-linked TCF7L2 variants were associated with single autoantibody (among those ≥12 years old), higher C-peptide AUC, and lower glucose AUC levels during an OGTT. Thus, carriers of the TCF7L2 variant had a milder immunologic and metabolic phenotype at type 1 diabetes diagnosis, which could be partly driven by type 2 diabetes-like pathogenic mechanisms.

ObjectiveWe aimed to determine the effect of elevated BMI over time on the progression to type 1 diabetes in youth.Research design and methodsWe studied 1,117 children in the TrialNet Pathway to Prevention cohort (autoantibody-positive relatives of patients with type 1 diabetes). Longitudinally accumulated BMI above the 85th age- and sex-adjusted percentile generated a cumulative excess BMI (ceBMI) index. Recursive partitioning and multivariate analyses yielded sex- and age-specific ceBMI thresholds for greatest type 1 diabetes risk.ResultsHigher ceBMI conferred significantly greater risk of progressing to type 1 diabetes. The increased diabetes risk occurred at lower ceBMI values in children

Background: The TrialNet Oral Insulin (OI) prevention trial showed no overall treatment effect, using the diagnosis of type 1 diabetes as an endpoint. A significant delay in onset was only found in a high‐risk stratum (termed secondary stratum 1) of participants with low first‐phase insulin release (FPIR). Methods: Since trials with an endpoint of type 1 diabetes take years to complete, in this post hoc analysis, we assessed whether a novel combination of glucose and C‐peptide markers could identify a therapeutic benefit after 1 year of follow‐up (trial participants followed for a median 2.7 years). Results: Participants were relatives with multiple islet autoantibodies and low FPIR (n = 40). Glucose rose, and C‐peptide declined in the placebo group, whereas glucose rose minimally, and C‐peptide increased in the OI group. When glucose and C‐peptide were plotted on two‐dimensional grids using 30–120‐min oral glucose tolerance test (OGTT) time points, changes in ratios of their central points (centroid ratio) differed between groups (p = 0.037 adjusted for age, BMI, and baseline C‐peptide and glucose). Conclusions: These findings support a favorable early effect of OI on combined glucose and C‐peptide endpoints in high‐risk individuals, indicating metabolic benefit. With further study, these measures may allow for shorter trials compared to the standard endpoint of type 1 diabetes diagnosis. [ABSTRACT FROM AUTHOR]

We sought to determine if the early months of the coronavirus disease 2019 (COVID-19) pandemic influenced pediatric diabetic ketoacidosis (DKA) hospitalization characteristics. This is a cross-sectional study of youth with laboratory-confirmed DKA admitted to a large tertiary children's hospital in the USA. Data were collected from admissions in March through July 2019 and March through July 2020, respectively. We evaluated the clinical characteristics of hospitalization, including demographic data and DKA severity. We used univariable ordinal logistic regression followed by multiple ordinal logistic regression to adjust for potential confounders. We included 137 children with diabetes admitted for DKA in the relevant period in 2019 and 173 patients admitted for DKA in the same period in 2020. Hemoglobin A1C (HbA1c) upon admission was higher in 2020 (median=12.2 %) than in 2019 (11.5 %, p=0.018). Children who were admitted with DKA in 2020 were less likely to be autoantibody positive than those in 2019 (83 vs. 91 %, p=0.028). In the univariable model, being admitted in 2020 was significantly associated with more severe DKA (p=0.038), as was HbA1c (p=0.001). After adjusting for HbA1c upon admission, admission year was no longer significantly associated with more severe DKA. In this study of pediatric diabetes of any type and duration of diabetes, youth admitted for DKA at the start of the COVID-19 pandemic, compared with those admitted during the year before, were more likely to have autoantibody-negative diabetes and had significantly higher HbA1c. Additionally, higher HbA1c seemed to mediate more severe DKA during the pandemic. [ABSTRACT FROM AUTHOR]

Context Metabolic measures are frequently used to predict type 1 diabetes (T1D) and to understand effects of disease-modifying therapies. Objective Compare metabolic endpoints for their ability to detect preventive treatment effects and predict T1D. Methods Six-month changes in metabolic endpoints were assessed for (1) detecting treatment effects by comparing placebo and treatment arms from the randomized controlled teplizumab prevention trial, a multicenter clinical trial investigating 14-day intravenous teplizumab infusion and (2) predicting T1D in the TrialNet Pathway to Prevention natural history study. For each metabolic measure, t-Values from t tests for detecting a treatment effect were compared with chi-square values from proportional hazards regression for predicting T1D. Participants in the teplizumab prevention trial and participants in the Pathway to Prevention study selected with the same inclusion criteria used for the teplizumab trial were studied. Results Six-month changes in glucose-based endpoints predicted diabetes better than C-peptide–based endpoints, yet the latter were better at detecting a teplizumab effect. Combined measures of glucose and C-peptide were more balanced than measures of glucose alone or C-peptide alone for predicting diabetes and detecting a teplizumab effect. Conclusion The capacity of a metabolic endpoint to detect a treatment effect does not necessarily correspond to its accuracy for predicting T1D. However, combined glucose and C-peptide endpoints appear to be effective for both predicting diabetes and detecting a response to immunotherapy. These findings suggest that combined glucose and C-peptide endpoints should be incorporated into the design of future T1D prevention trials. [ABSTRACT FROM AUTHOR]

The study published in Diabetes Care highlights the challenges in distinguishing maturity-onset diabetes of the young (MODY) from type 2 diabetes in youth, especially in a diverse cohort. The MODY probability calculator and clinical features used for adults were found to be ineffective in youth diagnosed with type 2 diabetes. Body mass index (BMI) emerged as a strong predictor of MODY, outperforming other clinical variables like age of diagnosis and parental history of diabetes. The study emphasizes the need for new biomarkers to differentiate between youth-onset type 2 diabetes and MODY. [Extracted from the article]

OBJECTIVE: Mixed-meal tolerance test–stimulated area under the curve (AUC) C-peptide at 12–24 months represents the primary end point for nearly all intervention trials seeking to preserve β-cell function in recent-onset type 1 diabetes. We hypothesized that participant benefit might be detected earlier and predict outcomes at 12 months posttherapy. Such findings would support shorter trials to establish initial efficacy. RESEARCH DESIGN AND METHODS: We examined data from six Type 1 Diabetes TrialNet immunotherapy randomized controlled trials in a post hoc analysis and included additional stimulated metabolic indices beyond C-peptide AUC. We partitioned the analysis into successful and unsuccessful trials and analyzed the data both in the aggregate as well as individually for each trial. RESULTS: Among trials meeting their primary end point, we identified a treatment effect at 3 and 6 months when using C-peptide AUC (P = 0.030 and P < 0.001, respectively) as a dynamic measure (i.e., change from baseline). Importantly, no such difference was seen in the unsuccessful trials. The use of C-peptide AUC as a 6-month dynamic measure not only detected treatment efficacy but also suggested long-term C-peptide preservation (R 2 for 12-month C-peptide AUC adjusted for age and baseline value was 0.80, P < 0.001), and this finding supported the concept of smaller trial sizes down to 54 participants. CONCLUSIONS: Early dynamic measures can identify a treatment effect among successful immune therapies in type 1 diabetes trials with good long-term prediction and practical sample size over a 6-month period. While external validation of these findings is required, strong rationale and data exist in support of shortening early-phase clinical trials. [ABSTRACT FROM AUTHOR]

ObjectiveTo compare characteristics of autoantibody (aAb)-positive and -negative cases of type 1 diabetes (T1D)

Background. Elevated serum IgA levels have been observed in various autoimmune conditions, including type 1 diabetes (T1D). However, whether children with T1D and elevated serum IgA have unique features has not been studied. We aimed to evaluate the prevalence and characteristics associated with elevated serum IgA at the onset of pediatric T1D. Materials and Methods. We analyzed demographic, clinical, and laboratory data retrospectively collected from 631 racially diverse children (6 months–18 years of age) with T1D who had serum IgA levels measured within 90 days of T1D diagnosis. Univariable and multivariable logistic regression models were used to identify characteristics that were significantly associated with elevated versus normal IgA. Results. Elevated serum IgA was present in 20.3% (128/631) of the children with newly diagnosed T1D. After adjusting for other variables, A1c level (p = 0.029), positive insulin autoantibodies (IAA) (p = 0.041), negative glutamic acid decarboxylase autoantibodies (GADA) (p = 0.005) and Hispanic ethnicity (p < 0.001) were significantly associated with elevated serum IgA. After adjustment for confounders, the odds of elevated serum IgA were significantly increased with positive IAA (OR 1.653, 95% CI 1.019–2.679), higher HbA1c (OR 1.132, 95% CI 1.014–1.268) and Hispanic ethnicity (OR 3.279, 95% CI 2.003–5.359) but decreased with GADA positivity (OR 0.474, 95% CI 0.281–0.805). Conclusions. Elevated serum IgA is present in 20.3% of the children at T1D onset and is associated with specific demographic and clinical characteristics, suggesting a unique pathogenesis in a subset of individuals. Further studies are warranted to investigate the IgA response, its role in T1D pathogenesis, and whether these associations persist over time. [ABSTRACT FROM AUTHOR]

Background. A−β+ ketosis-prone diabetes (KPD) in adults is characterized by presentation with diabetic ketoacidosis (DKA), negative islet autoantibodies, and preserved β-cell function in persons with a phenotype of obesity-associated type 2 diabetes (T2D). The prevalence of KPD has not been evaluated in children. We investigated children with DKA at "T2D" onset and determined the prevalence and characteristics of pediatric A−β+ KPD within this cohort. Methods. We reviewed the records of 716 children with T2D at a large academic hospital and compared clinical characteristics of those with and without DKA at onset. In the latter group, we identified patients with A−β+ KPD using criteria of the Rare and Atypical Diabetes Network (RADIANT) and defined its prevalence and characteristics. Results. Mean age at diagnosis was 13.7 ± 2.4 years: 63% female; 59% Hispanic, 29% African American, 9% non-Hispanic White, and 3% other. Fifty-six (7.8%) presented with DKA at diagnosis and lacked islet autoantibodies. Children presenting with DKA were older and had lower C-peptide and higher glucose concentrations than those without DKA. Twenty-five children with DKA (45%) met RADIANT A−β+ KPD criteria. They were predominantly male (64%), African American or Hispanic (96%), with substantial C-peptide (1.3 ± 0.7 ng/mL) at presentation with DKA and excellent long-term glycemic control (HbA1c 6.6% ± 1.9% at follow-up (median 1.3 years postdiagnosis)). Conclusions. In children with a clinical phenotype of T2D and DKA at diagnosis, approximately half meet criteria for A−β+ KPD. They manifest the key characteristics of obesity, preserved β-cell function, male predominance, and potential to discontinue insulin therapy, similar to adults with A−β+ KPD. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background. Youth with Type 1 diabetes (T1D) who are Black, Hispanic, or lower socioeconomic status (SES) have lower rates of diabetes device use, higher hemoglobin A1c (HbA1c), and higher rates of diabetic ketoacidosis (DKA). However, the associations of individual-level social determinants of health (SDoH) and neighborhood-level factors with device use and clinical outcomes are unknown. Area deprivation index (ADI) is a neighborhood level measure of SES reported in deciles (range 1–10 with 10 representing most deprived neighborhood). Methods. We evaluated the association of ADI and other SDoH factors with pump/continuous glucose monitor (CGM) use, HbA1c, and DKA in 1,461 youth with T1D (50% female, age 12.8 ± 3.6 years, HbA1c 8.7 ± 2.1%, 52% pump, 70% CGM) seen between October 1, 2020 and September 30, 2021 at a large pediatric diabetes center. Multiple logistic regression and multiple linear regression analyses were used to determine statistically significant associations adjusting for potential confounders. Results. Youth were less likely to use an insulin pump if they lived in a higher ADI neighborhood, were Black or Hispanic, had Medicaid or were uninsured, or received government assistance (e.g., Supplemental Security Income, Supplemental Nutritional Assistance Program). Youth were less likely to use a CGM if they lived in a higher ADI neighborhood, were Black or Hispanic, had Medicaid or were uninsured. Youth had higher risk of DKA event in the past year if they used government assistance, whereas pump and CGM use were associated with lower DKA risk. HbA1c (%) increased by 0.09 (95% CI: 0.05, 0.13) per unit increase in ADI. HbA1c was 0.62 lower (95% CI: −0.82, −0.42) in pump users vs. nonusers and 0.78 lower (95% CI: −0.99, −0.56) in CGM users vs. nonusers. Conclusions. Interventions that tailor care plans to address SDoH in families living in deprived neighborhoods may be needed to increase successful technology uptake, optimize HbA1c, and prevent DKA. [ABSTRACT FROM AUTHOR]