The Influence of Pubertal Development on Autoantibody Appearance and Progression to Type 1 Diabetes in the TEDDY Study.

Context: The 2 peaks of type 1 diabetes incidence occur during early childhood and puberty. Objective: We sought to better understand the relationship between puberty, islet autoimmunity, and type 1 diabetes. Methods: The relationships between puberty, islet autoimmunity, and progression to type 1 diabetes were investigated prospectively in children followed in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Onset of puberty was determined by subject self-assessment of Tanner stages. Associations between speed of pubertal progression, pubertal growth, weight gain, homeostasis model assessment of insulin resistance (HOMA-IR), islet autoimmunity, and progression to type 1 diabetes were assessed. The influence of individual factors was analyzed using Cox proportional hazard ratios. Results: Out of 5677 children who were still in the study at age 8 years, 95% reported at least 1 Tanner Stage score and were included in the study. Children at puberty (Tanner Stage ≥2) had a lower risk (HR 0.65, 95% CI 0.45-0.93; P = .019) for incident autoimmunity than prepubertal children (Tanner Stage 1). An increase of body mass index Z-score was associated with a higher risk (HR 2.88, 95% CI 1.61-5.15; P < .001) of incident insulin autoantibodies. In children with multiple autoantibodies, neither HOMA-IR nor rate of progression to Tanner Stage 4 were associated with progression to type 1 diabetes. Conclusion: Rapid weight gain during puberty is associated with development of islet autoimmunity. Puberty itself had no significant influence on the appearance of autoantibodies or type 1 diabetes. Further studies are needed to better understand the underlying mechanisms.

Dietary Intake and Body Mass Index Influence the Risk of Islet Autoimmunity in Genetically At-Risk Children: A Mediation Analysis Using the TEDDY Cohort.

Background/Objective: Growth and obesity have been associated with increased risk of islet autoimmunity (IA) and progression to type 1 diabetes. We aimed to estimate the effect of energy-yielding macronutrient intake on the development of IA through BMI. Research Design and Methods: Genetically at-risk children (n = 5,084) in Finland, Germany, Sweden, and the USA, who were autoantibody negative at 2 years of age, were followed to the age of 8 years, with anthropometric measurements and 3-day food records collected biannually. Of these, 495 (9.7%) children developed IA. Mediation analysis for time-varying covariates (BMI z-score) and exposure (energy intake) was conducted. Cox proportional hazard method was used in sensitivity analysis. Results: We found an indirect effect of total energy intake (estimates: indirect effect 0.13 [0.05, 0.21]) and energy from protein (estimates: indirect effect 0.06 [0.02, 0.11]), fat (estimates: indirect effect 0.03 [0.01, 0.05]), and carbohydrates (estimates: indirect effect 0.02 [0.00, 0.04]) (kcal/day) on the development of IA. A direct effect was found for protein, expressed both as kcal/day (estimates: direct effect 1.09 [0.35, 1.56]) and energy percentage (estimates: direct effect 72.8 [3.0, 98.0]) and the development of GAD autoantibodies (GADA). In the sensitivity analysis, energy from protein (kcal/day) was associated with increased risk for GADA, hazard ratio 1.24 (95% CI: 1.09, 1.53), p = 0.042. Conclusions: This study confirms that higher total energy intake is associated with higher BMI, which leads to higher risk of the development of IA. A diet with larger proportion of energy from protein has a direct effect on the development of GADA.

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.

Power prior models for estimating response rates in a small n, sequential, multiple assignment, randomized trial.

A small n, sequential, multiple assignment, randomized trial (snSMART) is a small sample, two-stage design where participants receive up to two treatments sequentially, but the second treatment depends on response to the first treatment. The parameters of interest in an snSMART are the first-stage response rates of the treatments, but outcomes from both stages can be used to obtain more information from a small sample. A novel way to incorporate the outcomes from both stages uses power prior models, in which first stage outcomes from an snSMART are regarded as the primary (internal) data and second stage outcomes are regarded as supplemental data (co-data). We apply existing power prior models to snSMART data, and we also develop new extensions of power prior models. All methods are compared to each other and to the Bayesian joint stage model (BJSM) via simulation studies. By comparing the biases and the efficiency of the response rate estimates among all proposed power prior methods, we suggest application of Fisher's Exact Test or the Bhattacharyya's overlap measure to an snSMART to estimate the response rates in an snSMART, which both have performance mostly as good or better than the BJSM. We describe the situations where each of these suggested approaches is preferred.

The association of physical activity to oral glucose tolerance test outcomes in multiple autoantibody positive children: The TEDDY Study.

OBJECTIVE: To examine the association of physical activity (PA), measured by accelerometry, to hemoglobin AIC (HbA1c) and oral glucose tolerance test (OGTT) outcomes in children who were multiple persistent confirmed autoantibody positive for type 1 diabetes (T1D). METHODS: The Environmental Determinants of Diabetes in the Young (TEDDY) multinational study followed children from birth. Children ≥3 years of age who were multiple persistent confirmed autoantibody positive were monitored by OGTTs every 6 months. TEDDY children's PA was measured by accelerometry beginning at 5 years of age. We examined the relationship between moderate plus vigorous (mod + vig) PA, HbA1c, and OGTT in 209 multiple autoantibody children who had both OGTT and PA measurements. RESULTS: Mod + vig PA was associated with both glucose and C-peptide measures (fasting, 120-min, and AUC); higher mod + vig PA was associated with a better OGTT response primarily in children with longer duration of multiple autoantibody positivity. Mod + vig PA also interacted with child age; lower mod + vig PA was associated with a greater increase in C-peptide response across age. Mod + vig PA was not related to fasting insulin, HOMA-IR or HbA1c. CONCLUSIONS: The OGTT is the gold standard for diabetes diagnosis and is used to monitor those at high risk for T1D. We found higher levels of mod + vig PA were associated with better OGTT outcomes in children ≥5 years of age who have been multiple autoantibody positive for longer periods of time. Physical activity should be the focus of future efforts to better understand the determinants of disease progression in high-risk children.

Complete blood counts with red blood cell determinants associate with reduced beta-cell function in seroconverted Swedish TEDDY children.

OBJECTIVES: To investigate whether changes in complete blood count (CBC) in islet autoantibody positive children with increased genetic risk for type 1 diabetes are associated with oral glucose tolerance tests (OGTT) and HbA1c over time. METHODS: The Environmental Determinants of Diabetes in the Young (TEDDY) study follows children with increased risk for type 1 diabetes in the United States, Germany, Sweden and Finland. In the current study, 89 Swedish TEDDY children (median age 8.8 years) positive for one or multiple islet autoantibodies were followed up to 5 (median 2.3) years for CBC, OGTT and HbA1c. A statistical mixed effect model was used to investigate the association between CBC and OGTT or HbA1c. RESULTS: HbA1c over time increased by the number of autoantibodies (p < .001). Reduction in mean corpuscular haemoglobin (MCH) and mean cell volume (MCV) was both associated with an increase in HbA1c (p < .001). A reduction in red blood cell (RBC) counts (p = .003), haemoglobin (p = .002) and haematocrit (p = .006) levels was associated with increased fasting glucose. Increased red blood cells, haemoglobin, haematocrit and MCH but decreased levels of red blood cell distribution widths (RDW) were all associated with increased fasting insulin. CONCLUSIONS: The decrease in RBC indices with increasing HbA1c and the decrease in RBC and its parameters with increasing fasting glucose in seroconverted children may reflect an insidious deterioration in glucose metabolism associated with islet beta-cell autoimmunity.

Maternal food consumption during late pregnancy and offspring risk of islet autoimmunity and type 1 diabetes.

AIMS/HYPOTHESIS: We aimed to investigate the association between maternal consumption of gluten-containing foods and other selected foods during late pregnancy and offspring risk of islet autoimmunity (IA) and type 1 diabetes in The Environmental Determinants of Diabetes in the Young (TEDDY) study. METHODS: The TEDDY study recruited children at high genetic risk for type 1 diabetes at birth, and prospectively follows them for the development of IA and type 1 diabetes (n = 8556). A questionnaire on the mother's diet in late pregnancy was completed by 3-4 months postpartum. The maternal daily intake was estimated from a food frequency questionnaire for eight food groups: gluten-containing foods, non-gluten cereals, fresh milk, sour milk, cheese products, soy products, lean/medium-fat fish and fatty fish. For each food, we described the distribution of maternal intake among the four participating countries in the TEDDY study and tested the association of tertile of maternal food consumption with risk of IA and type 1 diabetes using forward selection time-to-event Cox regression. RESULTS: By 28 February 2019, 791 cases of IA and 328 cases of type 1 diabetes developed in TEDDY. There was no association between maternal late-pregnancy consumption of gluten-containing foods or any of the other selected foods and risk of IA, type 1 diabetes, insulin autoantibody-first IA or GAD autoantibody-first IA (all p ≥ 0.01). Maternal gluten-containing food consumption in late pregnancy was higher in Sweden (242 g/day), Germany (247 g/day) and Finland (221 g/day) than in the USA (199 g/day) (pairwise p < 0.05). CONCLUSIONS/INTERPRETATION: Maternal food consumption during late pregnancy was not associated with offspring risk for IA or type 1 diabetes. TRIAL REGISTRATION: ClinicalTrials.gov NCT00279318.

Bayesian methods to compare dose levels with placebo in a small n, sequential, multiple assignment, randomized trial.

Clinical trials studying treatments for rare diseases are challenging to design and conduct due to the limited number of patients eligible for the trial. One design used to address this challenge is the small n, sequential, multiple assignment, randomized trial (snSMART). We propose a new snSMART design that investigates the response rates of a drug tested at a low and high dose compared with placebo. Patients are randomized to an initial treatment (stage 1). In stage 2, patients are rerandomized, depending on their initial treatment and their response to that treatment in stage 1, to either the same or a different dose of treatment. Data from both stages are used to determine the efficacy of the active treatment. We present a Bayesian approach where information is borrowed between stage 1 and stage 2. We compare our approach to standard methods using only stage 1 data and a log-linear Poisson model that uses data from both stages where parameters are estimated using generalized estimating equations. We observe that the Bayesian method has smaller root-mean-square-error and 95% credible interval widths than standard methods in the tested scenarios. We conclude that it is advantageous to utilize data from both stages for a primary efficacy analysis and that the specific snSMART design shown here can be used in the registration of a drug for the treatment of rare diseases.

Adherence to oral glucose tolerance testing in children in stage 1 of type 1 diabetes: The TEDDY study.

OBJECTIVE: To examine adherence to the oral glucose tolerance test (OGTT) in multiple islet autoantibody children in stage 1 of developing type 1 diabetes (T1D). METHODS: Children are followed from birth in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Completion of an OGTT is recommended every 6 months in children ≥3 years of age who are multiple islet autoantibody positive. Factors associated with adherence to the OGTT protocol were examined. RESULTS: The average subject level adherence with the OGTT protocol was 62% although there were large differences across countries; Finnish participants and older children from Sweden were more adherent than participants from the United States and Germany. Factors associated with nonadherence included having a first-degree relative with T1D, using a local laboratory rather than a TEDDY center for the OGTT, and maternal underestimation of the child's risk for T1D. Children were more adherent to the OGTT if their mothers: were more satisfied with TEDDY participation, reported monitoring the child for T1D by checking blood glucose levels at home, and viewed participating in TEDDY as the primary way they were monitoring the child for T1D. CONCLUSIONS: In a study of children in stage 1 of T1D, adherence to an OGTT protocol was suboptimal despite extensive efforts to communicate the child's high risk to parents. These findings provide important guidance for development of strategies to improve methods for detecting progression or the development of T1D in high-risk pediatric populations.

Design and analysis considerations for utilizing a mapping function in a small sample, sequential, multiple assignment, randomized trials with continuous outcomes.

Small sample, sequential, multiple assignment, randomized trials (snSMARTs) are multistage trials with the overall goal of determining the best treatment after a fixed amount of time. In snSMART trials, patients are first randomized to one of three treatments and a binary (e.g. response/nonresponse) outcome is measured at the end of the first stage. Responders to first stage treatment continue their treatment. Nonresponders to first stage treatment are rerandomized to one of the remaining treatments. The same binary outcome is measured at the end of the first and second stages, and data from both stages are pooled together to find the best first stage treatment. However, in many settings the primary endpoint may be continuous, and dichotomizing this continuous variable may reduce statistical efficiency. In this article, we extend the snSMART design and methods to allow for continuous outcomes. Instead of requiring a binary outcome at the first stage for rerandomization, the probability of staying on the same treatment or switching treatment is a function of the first stage outcome. Rerandomization based on a mapping function of a continuous outcome allows for snSMART designs without requiring a binary outcome. We perform simulation studies to compare the proposed design with continuous outcomes to standard snSMART designs with binary outcomes. The proposed design results in more efficient treatment effect estimates and similar outcomes for trial patients.

Genetic Subtype-Phenotype Analysis of Growth Hormone Treatment on Psychiatric Behavior in Prader-Willi Syndrome.

Prader-Willi syndrome (PWS) is a complex multisystemic condition caused by a lack of paternal expression of imprinted genes from the 15q11.2-q13 region. Limited literature exists on the association between molecular classes, growth hormone use, and the prevalence of psychiatric phenotypes in PWS. In this study, we analyzed nine psychiatric phenotypes (depressed mood, anxiety, skin picking, nail picking, compulsive counting, compulsive ordering, plays with strings, visual hallucinations, and delusions) recognized in PWS and investigated associations with growth hormone treatment (GHT), deletions (DEL) and uniparental disomy (UPD) in a cohort of 172 individuals with PWS who met the criteria for analysis. Associations were explored using Pearson chi-square tests and univariable and multivariable logistic regression analyses to control for confounding exposures. This observational study of the largest dataset of patients with PWS to date suggested the following genetic subtype and phenotype correlations in psychiatric behaviors: (1) skin picking was more frequent in those with DEL vs. UPD; (2) anxiety was more common in those with UPD vs. DEL; and (3) an increased frequency of anxiety was noted in the UPD group treated with GHT compared to the DEL group. No other significant associations were found between the genetic subtype or GHT including for depressed mood, nail picking, compulsive counting, compulsive ordering, playing with strings, and visual hallucinations. Further studies will be required before any conclusions can be reached.

Sample size determination for Bayesian analysis of small n sequential, multiple assignment, randomized trials (snSMARTs) with three agents.

The small n, Sequential, Multiple Assignment, Randomized Trial (snSMART) is a two-stage clinical trial design for rare diseases motivated by the comparison of three active treatments for isolated skin vasculitis in the ongoing clinical trial ARAMIS (a randomized multicenter study for isolated skin vasculitis, NCT09239573). In Stage 1, all patients are randomized to one of three treatments. In Stage 2, patients who respond to their initial treatment receive the same treatment again, while those who fail to respond are re-randomized to one of the two remaining treatments. A Bayesian method for estimating the response rate of each individual treatment in a three-arm snSMART demonstrated efficiency gains for a given sample size relative to other existing frequentist approaches. However, these efficiency gains are dependent upon knowing how many subjects are required to determine a specific difference in the treatment response rates. Because few sample size calculation methods for snSMARTs exist, we propose a Bayesian sample size calculation for an snSMART designed to distinguish the best treatment from the second-best treatment. Although our methods are based on asymptotic approximations, we demonstrate via simulations that our proposed sample size calculation approach produces the desired statistical power, even in small samples. Moreover, our methods and applet produce sample sizes quickly, thereby saving time relative to using simulations to determine the appropriate sample size. We compare our proposed sample size to an existing frequentist method based upon a weighted Z-statistic and demonstrate that the Bayesian method requires far fewer patients than the frequentist method for a study with the same design parameters.

Protocol for a randomized multicenter study for isolated skin vasculitis (ARAMIS) comparing the efficacy of three drugs: azathioprine, colchicine, and dapsone.

BACKGROUND: Skin-limited forms of vasculitis, while lacking systemic manifestations, can persist or recur indefinitely, cause pain, itch, or ulceration, and be complicated by infection or scarring. High-quality evidence on how to treat these conditions is lacking. The aim of this comparative effectiveness study is to determine the optimal management of patients with chronic skin-limited vasculitis. METHODS: ARAMIS is a multicenter, sequential, multiple assignment randomized trial with an enrichment design (SMARTER) aimed at comparing the efficacy of three drugs-azathioprine, colchicine, and dapsone-commonly used to treat various forms of isolated skin vasculitis. ARAMIS will enroll patients with isolated cutaneous small or medium vessel vasculitis, including cutaneous small vessel vasculitis, immunoglobulin A (IgA) vasculitis (skin-limited Henoch-Schönlein purpura), and cutaneous polyarteritis nodosa. Patients not responding to the initial assigned therapy will be re-randomized to one of the remaining two study drugs (Stage 2). Those with intolerance or contraindication to a study drug can be randomized directly into Stage 2. Target enrollment is 90 participants, recruited from international centers affiliated with the Vasculitis Clinical Research Consortium. The number of patients enrolled directly into Stage 2 of the study will be capped at 10% of the total recruitment target. The primary study endpoint is the proportion of participants from the pooled study stages with a response to therapy at month 6, according to the study definition. DISCUSSION: ARAMIS will help identify effective agents for skin-limited forms of vasculitis, an understudied group of diseases. The SMARTER design may serve as an example for future trials in rare diseases. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02939573. Registered on 18 October 2016.

Early Diagnosis in Prader-Willi Syndrome Reduces Obesity and Associated Co-Morbidities.

Prader-Willi syndrome (PWS) is an imprinting genetic disorder characterized by lack of expression of genes on the paternal chromosome 15q11-q13 region. Growth hormone (GH) replacement positively influences stature and body composition in PWS. Our hypothesis was that early diagnosis delays onset of obesity in PWS. We studied 352 subjects with PWS, recruited from the NIH Rare Disease Clinical Research Network, to determine if age at diagnosis, ethnicity, gender, and PWS molecular class influenced the age they first become heavy, as determined by their primary care providers, and the age they first developed an increased appetite and began seeking food. The median ages that children with PWS became heavy were 10 years, 6 years and 4 years for age at diagnosis < 1 year, between 1 and 3 years, and greater than 3 years of age, respectively. The age of diagnosis and ethnicity were significant factors influencing when PWS children first became heavy (p < 0.01), however gender and the PWS molecular class had no influence. Early diagnosis delayed the onset of becoming heavy in individuals with PWS, permitting early GH and other treatment, thus reducing the risk of obesity-associated co-morbidities. Non-white individuals had an earlier onset of becoming heavy.

Randomized Trial of Lisinopril Versus Carvedilol to Prevent Trastuzumab Cardiotoxicity in Patients With Breast Cancer.

BACKGROUND: Trastuzumab is highly effective for human epidermal growth factor receptor type 2 (HER2)-positive breast cancer but is associated with a decline in left ventricular ejection fraction. OBJECTIVES: The purpose of this study was to determine whether angiotensin-converting enzyme inhibitors or beta-blockers reduce the rate of trastuzumab-induced cardiotoxicity (left ventricular ejection fraction decrease >10%, or >5% if below 50%) and limit treatment interruptions. METHODS: In this double-blind, multicenter, placebo-controlled trial, cardiotoxicity and treatment interruptions in patients with HER2-positive breast cancer treated with trastuzumab for 12 months were evaluated over a 2-year period. Patients were stratified by anthracycline use and then randomized to receive lisinopril, carvedilol, or placebo. RESULTS: The study included 468 women, age 51 ± 10.7 years. For the entire cohort, cardiotoxicity was comparable in the 3 arms and occurred in 32% of patients on placebo, 29% on carvedilol, and 30% on lisinopril. For patients receiving anthracyclines, the event rates were higher in the placebo group (47%) than in the lisinopril (37%) and the carvedilol (31%) groups. Cardiotoxicity-free survival was longer on both carvedilol (hazard ratio: 0.49; 95% confidence interval: 0.27 to 0.89; p = 0.009) and lisinopril (hazard ratio: 0.53; 95% confidence interval: 0.30 to 0.94; p = 0.015) than on placebo. In the whole cohort, as well as in the anthracycline arm, patients on active therapy with either angiotensin-converting enzyme inhibitor or beta-blockers experienced fewer interruptions in trastuzumab than those on placebo. CONCLUSIONS: In patients with HER2-positive breast cancer treated with trastuzumab, both lisinopril and carvedilol prevented cardiotoxicity in patients receiving anthracyclines. For such patients, lisinopril or carvedilol should be considered to minimize interruptions of trastuzumab. (Lisinopril or Coreg CR in Reducing Side Effects in Women With Breast Cancer Receiving Trastuzumab; NCT01009918).

Birth seasonality studies in a large Prader-Willi syndrome cohort.

Prader-Willi syndrome (PWS) is generally due to sporadic paternal deletions of the chromosome 15q11-q13 region followed by maternal disomy 15. Advanced maternal age is more commonly seen in those with maternal disomy 15. Environmental factors (e.g., drug use, occupational chemical exposure, infectious agents, and irradiation) could account for chromosome changes. Previous evidence of differences in male and female gametogenesis could suggest an environmental role in the causation of the paternal 15q11-q13 deletion seen in PWS. Certain occupations such as hydrocarbon-exposing occupations (e.g., landscaping, farming, and painting) and viral exposure (e.g., human coronavirus 229E causing upper respiratory infections in adults with an incorporation site in the human genome at chromosome 15q11) can be seasonal in nature and contribute to chromosome damage. To assess, we reviewed birth seasonality data in a large cohort of individuals with PWS recruited nationally (N = 355) but no significant differences were seen by month between those with the 15q11-q13 deletion compared with maternal disomy 15 when analyzing quarterly seasonal patterns. Although early evidence supported birth seasonality differences in PWS, a larger number of individuals in our recent study using advanced genetic testing methods did not find this observation.

Predicting progression to type 1 diabetes from ages 3 to 6 in islet autoantibody positive TEDDY children.

OBJECTIVE: The capacity to precisely predict progression to type 1 diabetes (T1D) in young children over a short time span is an unmet need. We sought to develop a risk algorithm to predict progression in children with high-risk human leukocyte antigen (HLA) genes followed in The Environmental Determinants of Diabetes in the Young (TEDDY) study. METHODS: Logistic regression and 4-fold cross-validation examined 38 candidate predictors of risk from clinical, immunologic, metabolic, and genetic data. TEDDY subjects with at least one persistent, confirmed autoantibody at age 3 were analyzed with progression to T1D by age 6 serving as the primary endpoint. The logistic regression prediction model was compared to two non-statistical predictors, multiple autoantibody status, and presence of insulinoma-associated-2 autoantibodies (IA-2A). RESULTS: A total of 363 subjects had at least one autoantibody at age 3. Twenty-one percent of subjects developed T1D by age 6. Logistic regression modeling identified 5 significant predictors - IA-2A status, hemoglobin A1c, body mass index Z-score, single-nucleotide polymorphism rs12708716_G, and a combination marker of autoantibody number plus fasting insulin level. The logistic model yielded a receiver operating characteristic area under the curve (AUC) of 0.80, higher than the two other predictors; however, the differences in AUC, sensitivity, and specificity were small across models. CONCLUSIONS: This study highlights the application of precision medicine techniques to predict progression to diabetes over a 3-year window in TEDDY subjects. This multifaceted model provides preliminary improvement in prediction over simpler prediction tools. Additional tools are needed to maximize the predictive value of these approaches.

Molecular genetic classification in Prader-Willi syndrome: a multisite cohort study.

BACKGROUND: Prader-Willi syndrome (PWS) is due to errors in genomic imprinting. PWS is recognised as the most common known genetic cause of life-threatening obesity. This report summarises the frequency and further characterises the PWS molecular classes and maternal age effects. METHODS: High-resolution microarrays, comprehensive chromosome 15 genotyping and methylation-specific multiplex ligation probe amplification were used to describe and further characterise molecular classes of maternal disomy 15 (UPD15) considering maternal age. RESULTS: We summarised genetic data from 510 individuals with PWS and 303 (60%) had the 15q11-q13 deletion; 185 (36%) with UPD15 and 22 (4%) with imprinting defects. We further characterised UPD15 findings into subclasses based on the presence (size, location) or absence of loss of heterozygosity (LOH). Additionally, significantly older mothers (mean age=32.5 years vs 27.7 years) were found in the UPD15 group (n=145) compared with the deletion subtype (n=200). CONCLUSIONS: We report on molecular classes in PWS using advanced genomic technology in the largest cohort to date. LOH patterns in UPD15 may impact the risk of having a second genetic condition if the mother carries a recessive mutant allele in the isodisomic region on chromosome 15. The risk of UPD15 may also increase with maternal age.

Maternal dietary supplement use and development of islet autoimmunity in the offspring: TEDDY study.

OBJECTIVE: We investigated the association between maternal use of vitamin D and omega-3 fatty acids (n-3 FAs) supplements during pregnancy and risk of islet autoimmunity (IA) in the offspring. METHODS: The Environmental Determinants of Diabetes in the Young (TEDDY) Study is prospectively following 8676 children with increased genetic risk for type 1 diabetes in Finland, Germany, Sweden, and the United States. Blood samples were collected every 3 months between 3 and 48 months of age then every 6 months thereafter to determine persistent IA. Duration, frequency, and supplement dose during pregnancy were recalled by mothers at 3 to 4 months postpartum. Cumulative intakes of supplemental vitamin D and n-3 FAs were analyzed as continuous or binary variables. We applied time-to-event analysis to study the association between maternal supplement use and IA, adjusting for country, human leukocyte antigen-DR-DQ genotype, family history of type 1 diabetes and sex. Secondary outcomes included insulin autoantibodies (IAA) or glutamic acid decarboxylase (GADA) as the first appearing autoantibody. RESULTS: As of February 2018, there were 747 (9.0%) children with IA. Vitamin D supplement intake during pregnancy (any vs none) was not associated with risk for IA (hazard ratio [HR] 1.11; 95% confidence interval [CI] 0.94, 1.31); neither was cumulative vitamin D supplement intake. Supplemental n-3 FA intake was similarly not associated with IA risk (HR: 1.19, 95% CI 0.98, 1.45). Similar lack of association was observed for either IAA or GADA as the first appearing autoantibody. CONCLUSIONS: The TEDDY cohort showed no evidence of benefit regarding IA risk for vitamin D or n-3 FA supplementation during pregnancy.