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This study investigates a missing value imputation approach for longitudinal growth data in pediatric studies from multiple countries. We analyzed a combined cohort from five natural history studies of type 1 diabetes (T1D) in the US and EU with longitudinal growth measurements for 23,201 subjects. We developed a multiple imputation methodology using LMS parameters of CDC reference data. We measured imputation errors on both combined and individual cohorts using mean absolute percentage error (MAPE) and normalized root-mean-square error (NRMSE). Our results show low imputation errors using CDC reference. Overall height imputation errors were lower than for weight. The largest MAPE for weight and height among all age groups was 4.8% and 1.7%, respectively. When comparing performance between CDC reference and country-specific growth charts, we found no significant differences for height (CDC vs. German: p =0.993, CDC vs. Swedish: p=0.368) and for weight (CDC vs. Swedish: p=0.513) for all ages., (©2021 AMIA - All rights reserved.)

Type 1 diabetes (T1D) is a chronic autoimmune disease that affects about 1 in 300 children and up to 1 in 100 adults during their life-time 1 . Improvements in early prediction of T1D onset may help prevent diagnosis for diabetic ketoacidosis, a serious complication often associated with a missed or delayed T1D diagnosis. In addition to genetic factors, progression to T1D is strongly associated with immunologic factors that can be measured during clinical visits. We developed a T1D-specific ontology that captures the dynamic patterns of these biomarkers and used it together with a survival model, RankSvx, proposed in our prior work 2 . We applied this approach to a T1D dataset harmonized from three birth cohort studies from the United States, Finland, and Sweden. Results show that the dynamic biomarker patterns captured in the proposed ontology are able to improve prediction performance (in concordance index) by 5.3%, 3.3%, 2.8%, and 1.0% over baseline for 3, 6, 9, and 12 month duration windows, respectively., (©2020 AMIA - All rights reserved.)

Objectives: Body size is postulated to modulate type 1 diabetes as either a trigger of islet autoimmunity or an accelerator to clinical onset after seroconversion. As overweight and obesity continue to rise among children, the aim of this study was to determine whether human leukocyte antigen DQ (HLA-DQ) genotypes may be related to body size among children genetically at risk for type 1 diabetes., Methods: Repeated measures of weight and height were collected from 5969 children 2-4 years of age enrolled in The Environmental Determinants of Diabetes in the Young prospective study. Overweight and obesity was determined by the International Obesity Task Force cutoff values that correspond to body mass index (BMI) of 25 and 30 kg m(-)(2) at age 18., Results: The average BMI was comparable across specific HLA genotypes at every age point. The proportion of overweight was not different by HL A, but percent obesity varied by age with a decreasing trend among DQ2/8 carriers (P for trend=0.0315). A multivariable regression model suggested DQ2/2 was associated with higher obesity risk at age 4 (odds ratio, 2.41; 95% confidence interval, 1.21-4.80) after adjusting for the development of islet autoantibody and/or type 1 diabetes., Conclusions: The HLA-DQ2/2 genotype may predispose to obesity among 2-4-year-old children with genetic risk for type 1 diabetes.

Objective: Young children have an unacceptably high prevalence of diabetic ketoacidosis (DKA) at the clinical diagnosis of type 1 diabetes. The aim of this study was to determine whether knowledge of genetic risk and close follow-up for development of islet autoantibodies through participation in The Environmental Determinants of Diabetes in the Young (TEDDY) study results in lower prevalence of DKA at diabetes onset in children aged <2 and <5 years compared with population-based incidence studies and registries., Research Design and Methods: Symptoms and laboratory data collected on TEDDY participants diagnosed with type 1 diabetes between 2004 and 2010 were compared with data collected during the similar periods from studies and registries in all TEDDY-participating countries (U.S., SEARCH for Diabetes in Youth Study; Sweden, Swediabkids; Finland, Finnish Pediatric Diabetes Register; and Germany, Diabetes Patienten Verlaufsdokumenation [DPV] Register)., Results: A total of 40 children younger than age 2 years and 79 children younger than age 5 years were diagnosed with type 1 diabetes in TEDDY as of December 2010. In children <2 years of age at onset, DKA prevalence in TEDDY participants was significantly lower than in all comparative registries (German DPV Register, P < 0.0001; Swediabkids, P = 0.02; SEARCH, P < 0.0001; Finnish Register, P < 0.0001). The prevalence of DKA in TEDDY children diagnosed at <5 years of age (13.1%) was significantly lower compared with SEARCH (36.4%) (P < 0.0001) and the German DPV Register (32.2%) (P < 0.0001) but not compared with Swediabkids or the Finnish Register., Conclusions: Participation in the TEDDY study is associated with reduced risk of DKA at diagnosis of type 1 diabetes in young children.