A Federated Database for Obesity Research: An IMI-SOPHIA Study.

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.

Clinical characteristics and outcomes of children, adolescents and young adults with overweight or obesity and mental health disorders.

BACKGROUND: Mental disorders are important comorbidities in youth with obesity. Aim was to describe the clinical characteristics and outcome of youth with overweight or obesity having comorbid mental disorders. METHODS: Data from children, adolescents, and young adults (age 6-30 years) with overweight or obesity and mental disorders (depression, anxiety disorder, eating disorder, attention deficit disorder (ADHD)) from 226 centers in Germany and Austria participating in the Adiposity Patient Registry (APV) were analyzed and compared with those without reported mental disorders using regression modeling. RESULTS: Mental health comorbidity was reported in a total of 3969 out of 114,248 individuals with overweight or obesity: 42.5% had ADHD, 31.3% anxiety disorders, 24.3% depression, and 12.9% eating disorders. Being male (OR 1.39 (95%CI 1.27;1.52)), of older age (1.42 (1.25;1.62)), or with extreme obesity (1.45 (1.30;1.63)) were most strongly associated with mental health comorbidity. Regression analysis showed that mean BMI-SDS was significantly higher in the group of individuals with depression and eating disorders (BMI-SDS 2.13 (lower; upper mean:2.09;2.16) and 2.22 (2.17;2.26)) compared to those without reported mental health comorbidity (BMI-SDS 2.008 (2.005;2.011); p < 0.001). In youth with ADHD, BMI-SDS was lower compared to those without reported mental disorders (BMI-SDS 1.91 (1.89;1.93) vs 2.008 (2.005;2.011); p < 0.001). Proportion of severe obesity was higher in individuals with depression (23.7%), anxiety disorders (17.8%), and eating disorders (33.3%), but lower in ADHD (10.3%), compared to those without reported mental disorders (13.5%, p < 0.002). Proportions of dyslipidaemia and abnormal carbohydrate metabolism were not different in youth with and without reported mental health comorbidity. BMI-SDS change after one year of lifestyle intervention program ranged between -0.22 and -0.16 and was similar in youth without and with different mental disorders. CONCLUSION: Health care professionals caring for youth with overweight or obesity should be aware of comorbid mental disorders and regular mental health screening should be considered.

BMI Z-Score (SDS) versus Calculated Body Fat Percentage: Association with Cardiometabolic Risk Factors in Obese Children and Adolescents.

INTRODUCTION: BMI or BMI-standardized deviation score (SDS) in children and adolescents is still the standard for weight classification. [BMJ. 2019;366:4293] developed a formula to calculate body fat percentage (%BF) based on age, sex, height, weight, and ethnicity. Using data from the German/Austrian APV registry, we investigated whether the calculated %BF is superior to BMI-SDS in predicting arterial hypertension, dyslipidaemia, and impaired glucose metabolism. METHODS: 94,586 children and adolescents were included (12.5 years, 48.3% male). Parental birth country (BC) was used to depict ethnicity (15.8% migration background); 95.67% were assigned to the ethnicity "white." %BF was calculated based on the Hudda formula. The relationship between BMI-SDS or %BF quartiles and outcome variables was investigated by logistic regression models, adjusted for age, sex, and migration background. Vuong test was applied to analyse predictive power. RESULTS: 58.4% had arterial hypertension, 33.5% had dyslipidaemia, and 11.6% had impaired glucose metabolism. Boys were significantly more often affected, although girls had higher calculated %BF (each p < 0.05). After adjustment, both models revealed significant differences between the quartiles (all p < 0.001). The predictive power of BMI-SDS was superior to %BF for all three comorbidities (all p < 0.05). DISCUSSION: The prediction of cardiometabolic comorbidities by calculated %BF was not superior to BMI-SDS. This formula developed in a British population may not be suitable for a central European population, which is applicable to this possibly less heterogeneous collective. Additional parameters, especially puberty status, should be taken into account. However, objective determinations such as bioimpedance analysis may possibly be superior to assess fat mass and cardiometabolic risk than calculated %BF.

Who benefits most from outpatient lifestyle intervention? An IMI-SOPHIA study on pediatric individuals living with overweight and obesity.

OBJECTIVE: The first-line approach for childhood obesity is lifestyle intervention (LI); however, success varies. This study aimed first to identify distinct subgroups of response in children living with overweight and obesity and second to elucidate predictors for subclusters. METHODS: Based on the obesity patient follow-up registry the APV (Adipositas-Patienten-Verlaufsdokumentation) initiative, a total of 12,453 children and adolescents (median age: 11.5 [IQR: 9.7-13.2] years; BMI z score [BMIz]: 2.06 [IQR: 1.79-2.34]; 52.6% girls) living with overweight/obesity and participating in outpatient LI were studied. Longitudinal k-means clustering was used to identify individual BMIz response curve for up to 2 years after treatment initiation. Multinomial logistic regression was used to elucidate predictors for cluster membership. RESULTS: A total of 36.3% of children and adolescents experienced "no BMIz loss." The largest subcluster (44.8%) achieved "moderate BMIz loss," with an average delta-BMIz of -0.23 (IQR: -0.33 to -0.14) at study end. A total of 18.9% had a "pronounced BMIz loss" up to -0.61 (IQR: -0.76 to -0.49). Younger age and lower BMIz at LI initiation, larger initial BMIz loss, and less social deprivation were linked with higher likelihood for moderate or pronounced BMIz loss compared with the no BMIz loss cluster (all p < 0.05). CONCLUSIONS: These results support the importance of patient-tailored intervention and earlier treatment escalation in high-risk individuals who have little chance of success.

Is COVID-19 to Blame? Trends of Incidence and Sex Ratio in Youth-Onset Type 2 Diabetes in Germany.

OBJECTIVE: We investigated the incidence of pediatric type 2 diabetes (T2D) in Germany during 2 years of the coronavirus disease 2019 (COVID-19) pandemic (2020-2021) compared with the control period 2011-2019. RESEARCH DESIGN AND METHODS: Data on T2D in children (aged 6 to <18 years) were obtained from the DPV (German Diabetes Prospective Follow-up) Registry. Poisson regression was used to estimate incidences for 2020 and 2021 based on data from 2011 to 2019, and these were compared with observed incidences in 2020 and 2021 by estimating incidence rate ratios (IRRs) with 95% CIs. RESULTS: Incidence of youth-onset T2D increased from 0.75 per 100,000 patient-years (PYs) in 2011 (95% CI 0.58, 0.93) to 1.25 per 100,000 PYs in 2019 (95% CI 1.02, 1.48), an annual increase of 6.8% (95% CI 4.1, 9.6). In 2020, T2D incidence increased to 1.49 per 100,000 PYs (95% CI 1.23, 1.81), which was not significantly higher than predicted (IRR 1.15; 95% CI 0.90, 1.48). In 2021, the observed incidence was significantly higher than expected (1.95; 95% CI 1.65, 2.31 vs. 1.38; 95% CI 1.13, 1.69 per 100,000 PYs; IRR 1.41; 95% CI 1.12, 1.77). Although there was no significant increase in incidence in girls in 2021, the observed incidence in boys (2.16; 95% CI 1.73, 2.70 per 100,000 PYs) significantly exceeded the predicted rate (IRR 1.55; 95% CI 1.14, 2.12), leading to a reversal of the sex ratio of pediatric T2D incidence. CONCLUSIONS: In Germany, incidence of pediatric T2D increased significantly in 2021. Adolescent boys were more affected by this increase, resulting in a reversal of the sex ratio of youth-onset T2D.

The association between perinatal factors and cardiometabolic risk factors in children and adolescents with overweight or obesity: A retrospective two-cohort study.

BACKGROUND: Children with obesity have an increased risk of cardiometabolic risk factors, but not all children carry a similar risk. Perinatal factors, i.e., gestational age (GA) and birth weight for GA, may affect the risk for metabolic complications. However, there are conflicting data whether the association between birth size and cardiometabolic risk factors is independent among children with obesity. Moreover, differential effects of GA and birth weight for GA on cardiometabolic risk factors in pediatric obesity are still unexplored. We aimed to investigate the association between birth weight for GA and cardiometabolic risk factors in children and adolescents with overweight or obesity and to assess whether the association is modified by prematurity. METHODS AND FINDINGS: We conducted a retrospective study of 2 cohorts, using data from the world's 2 largest registers of pediatric obesity treatment-The Swedish childhood obesity treatment register (BORIS) and The Adiposity Patients Registry (APV) (1991 to 2020). Included were individuals with overweight or obesity between 2 to 18 years of age who had data of birth characteristics and cardiometabolic parameters. Birth data was collected as exposure variable and the first reported cardiometabolic parameters during pediatric obesity treatment as the main outcome. The median (Q1, Q3) age at the outcome measurement was 11.8 (9.4, 14.0) years. The main outcomes were hypertensive blood pressure (BP), impaired fasting glucose, elevated glycated hemoglobin (HbA1c), elevated total cholesterol, elevated low-density lipoprotein (LDL) cholesterol, elevated triglycerides, decreased high-density lipoprotein (HDL) cholesterol, and elevated transaminases. With logistic regression, we calculated the odds ratio (OR) and its 95% confidence interval (CI) for each cardiometabolic parameter. All the analyses were adjusted for sex, age, degree of obesity, migratory background, and register source. In total, 42,760 (51.9% females) individuals were included. Small for GA (SGA) was prevalent in 10.4%, appropriate for GA (AGA) in 72.4%, and large for GA (LGA) in 17.2%. Most individuals (92.5%) were born full-term, 7.5% were born preterm. Median (Q1, Q3) body mass index standard deviation score at follow-up was 2.74 (2.40, 3.11) units. Compared with AGA, children born SGA were more likely to have hypertensive BP (OR = 1.20 [95% CI 1.12 to 1.29], p < 0.001), elevated HbA1c (1.33 [1.06 to 1.66], p = 0.03), and elevated transaminases (1.21 [1.10 to 1.33], p < 0.001) as well as low HDL (1.19 [1.09 to 1.31], p < 0.001). On the contrary, individuals born LGA had lower odds for hypertensive BP (0.88 [0.83 to 0.94], p < 0.001), elevated HbA1c (0.81 [0.67 to 0.97], p < 0.001), and elevated transaminases (0.88 [0.81 to 0.94], p < 0.001). Preterm birth altered some of the associations between SGA and outcomes, e.g., by increasing the odds for hypertensive BP and by diminishing the odds for elevated transaminases. Potential selection bias due to occasionally missing data could not be excluded. CONCLUSIONS: Among children and adolescents with overweight/obesity, individuals born SGA are more likely to possess cardiometabolic risk factors compared to their counterparts born AGA. Targeted screening and treatment of obesity-related comorbidities should therefore be considered in this high-risk group of individuals.

Uric acid and gamma-glutamyl-transferase in children and adolescents with obesity: Association to anthropometric measures and cardiometabolic risk markers depending on pubertal stage, sex, degree of weight loss and type of patient care: Evaluation of the adiposity patient follow-up registry.

OBJECTIVES: Associations between body mass index (BMI)- standard deviation score (SDS)/waist-to-height ratio (WHtR) were studied with (i) serum uric acid (sUA)/gamma-glutamyl-transferase (GGT) and (ii) cardiometabolic risk markers in children with obesity, considering sex, pubertal development, and degree of weight loss/type of patient care. METHODS: 102 936 children from the Adiposity-Follow-up registry (APV; 47% boys) were included. Associations were analysed between sUA/GGT and anthropometrics, transaminases, lipids, fasting insulin (FI), homeostasis model assessment of insulin resistance (HOMA-IR), triglycerides to HDL-cholesterol (TG/HDL)-ratio. Follow-up analyses (3-24 months after baseline) considered a BMI-SDS reduction ≥0.2 (n = 11 096) or ≥0.5 (n = 3728). Partialized correlation analyses for sex and BMI-SDS were performed, taking pubertal development into consideration. RESULTS: At baseline, BMI-SDS showed the strongest correlations to sUA (r = 0.35; n = 26 529), HOMA-IR/FI (r = 0.30; n = 5513 /n = 5880), TG/HDL-ratio (r = 0.23; n = 24 501), and WHtR to sUA (r = 0.32; n = 10 805), GGT (r = 0.34; n = 11 862) and Alanine-aminotransferase (ALAT) (r = 0.33; n = 11 821), with stronger correlations in boys (WHtR and GGT: r = 0.36, n = 5793) and prepubertal children (r = 0.36; n = 2216). GGT and sUA (after partializing effects of age, sex, BMI-SDS) showed a correlation to TG/HDL-ratio (r = 0.27; n = 24 501). Following a BMI-SDS reduction ≥0.2 or ≥0.5, GGT was most strongly related to Aspartate-aminotransferase (ASAT)/ ALAT, most evident in prepuberty and with increasing weight loss, and also to TG/HDL-ratio (r = 0.22; n = 1528). Prepubertal children showed strongest correlations between BMI-SDS/WHtR and GGT. ΔBMI-SDS was strongly correlated to ΔsUA (r = 0.30; n = 4160) and ΔGGT (r = 0.28; n = 3562), and ΔWHtR to ΔGGT (r = 0.28; n = 3562) (all p < 0.0001). CONCLUSION: Abdominal obesity may trigger hyperuricemia and hepatic involvement already in prepuberty. This may be stronger in infancy than anticipated to date. Even moderate weight loss has favourable effects on cardiometabolic risk profile and glucose homeostasis.

Prevalence of type 1 and type 2 diabetes in children and adolescents in Germany from 2002 to 2020: A study based on electronic health record data from the DPV registry.

BACKGROUND: To provide estimates of the nationwide prevalence of type 1 diabetes (T1D) and type 2 diabetes (T2D) in individuals younger than 20 years of age in Germany from 2002 to 2020 and to identify trends. METHODS: Data were obtained from the electronic health record "Diabetes Prospective Follow-up Registry (DPV)" specific to diabetes care. Prevalence was estimated based on prevalent cases at the end of each year for the years 2002, 2008, 2014, and 2020 per 100 000 persons assuming a Poisson distribution and directly age- and/or sex-standardized to the population in 2020. Individuals younger than 20 years of age with a clinical diagnosis of T1D or 10-19-year-olds with T2D were eligible for inclusion in the study. RESULTS: The standardized T1D prevalence per 100 000 persons was 138.9 (95% CI: 137.1; 140.6) in 2002 and 245.6 (243.1; 248.0) in 2020. The standardized T2D prevalence per 100 000 persons was 3.4 (3.1; 3.8) in 2002 and 10.8 (10.1; 11.5) in 2020. The annual percent change (APC) in prevalence declined over the three periods 2002-2008/2008-2014/2014-2020 (T1D: 6.3% [3.6%; 9.0%]/3.1% [0.7%; 5.5%]/0.5% [-1.7%; 2.85], T2D: 12.3% [5.3%; 20.8%]/4.7% [-0.6%; 10.3%]/3.0% [-1.8%; 8.0%]). From 2014 to 2020, the highest APCs were observed among 15-19-year-olds (T1D: 2.5% [1.3%; 3.6%], T2D: 3.4% [-0.5%; 7.5%]). CONCLUSIONS: The increase in diabetes prevalence has slowed, but medical care should be prepared for an increase in adolescents with diabetes.

Three-variate trajectories of metabolic control, body mass index, and insulin dose: Heterogeneous response to initiation of pump therapy in youth with type 1 diabetes.

OBJECTIVE: Continuous subcutaneous insulin infusion (CSII) in youths with type 1 diabetes (T1D) is often associated with lower HbA1c, lower total daily insulin dose (TDD), and lower body mass index (BMI) compared with multiple daily injections (MDI). Individual responses to CSII are diverse. The aim was to identify unique three-variate patterns of HbA1c, BMI standard deviation score (SDS), and TDD after switching to CSII. METHODS: Five thousand one hundred and thirty-three youths (≤20 years; 48% boys; median age at pump start 12.5 years) with T1D duration ≥3 years at CSII initiation were selected from the multicenter DPV registry. We applied group-based multitrajectory modeling to identify groups of individuals following similar trajectories. Measurements were aggregated quarterly during a 3-year follow-up period. Trajectory variables were changes of HbA1c, BMI-SDS, and TDD from baseline (delta = quarterly aggregated values at each time point [i] minus the respective baseline value). RESULTS: Four groups of diverging Delta-HbA1c, Delta-BMI-SDS, and Delta-TDD patterns were identified. All showed improvements in HbA1c during the first 3 months. Group 1 (12%) was characterized by modest HbA1c increase thereafter, TDD reduction, and stable BMI-SDS. In Group 2 (39%), increasing HbA1c, decreasing BMI-SDS, and stable TDD were found. By contrast, sustainably improved HbA1c, increasing BMI-SDS, and stable TDD were observed in Group 3 (32%). Group 4 (17%) was characterized by increasing levels for HbA1c, BMI-SDS, and TDD. Between-group differences in baseline HbA1c, BMI-SDS, TDD as well as in sex ratio, age at diabetes onset and at pump start were observed. CONCLUSIONS: Definite trajectories of glycemic control, BMI, and TDD over 3 years after CSII initiation were identified in youths with T1D allowing a more personalized treatment recommendation.

Not All Type-2-Diabetes Patients Increase Body Mass Index After Initiating Insulin: Results of Latent Class Analysis from the DPV Registry.

Background: Is insulin initiation linked to increasing body mass index (BMI) in all patients with type-2-diabetes (T2D)? To determine distinct longitudinal patterns of BMI change over time. Materials and Methods: 5057 patients with T2D (55% males, median BMI [IQR]: 30.0 [26.9-33.3] kg/m2) aged ≥40 years at diabetes diagnosis and with ≥2 years of follow-up after insulin initiation irrespective of previous or concurrent use of metformin/dipeptidyl peptidase-4-inhibitor from the multicenter prospective diabetes registry DPV were studied. To identify subgroups following a similar pattern of BMI change after insulin initiation, longitudinal group-based trajectory modeling was applied. Multinomial logistic regression was then used to analyze covariates associated with group membership. Results: Three heterogeneous groups with either relevant BMI increase (delta-BMI: +4.0 kg/m2 after 2 years; 12% of patients); slight BMI increase (+0.4 kg/m2; 80%); or BMI decrease (-3.2 kg/m2; 8%) were identified. Patients with older age [OR (95% CI): 1.37 (1.11-1.69)] and obesity [2.05 (1.65-2.55)] before insulin start were more often in the BMI decreasing group, and less often in the BMI increasing class [0.80 (0.67-0.95); 0.82 (0.69-0.98)]. A worse HbA1c both at insulin start and during follow-up [1.90 (1.60-2.26); 1.17 (1.07-1.27)], a higher insulin dose [1.67 (1.33-2.10)], and severe hypoglycemic events [2.38 (1.60-3.53)] after insulin initiation were all linked with higher odds of belonging to the BMI increasing trajectory. Conclusions: Patient heterogeneity with respect to weight gain after initiation of insulin therapy in adult T2D was detected by an objective computer algorithm. Older people with obesity should not defer from insulin use due to fear of weight gain.

Feasibility and Acceptability of Photographic Food Record, Food Diary and Weighed Food Record in People with Serious Mental Illness.

People with serious mental illness (SMI) experience challenges that may make typical dietary assessment methods less feasible and accurate. This study aims to determine the feasibility, acceptability and preliminary validity of a 3-day photographic food record (PR), a 1-day food diary (FD) and a 1-day weighed food protocol (WR) in people with SMI. Participants completed measures at two timepoints, with a 4-week interval. Feasibility and acceptability for each method were measured through four outcomes: percent of completers, quality assessment, number of participants requiring technical devices and satisfaction questionnaire. Relative validity was measured by agreement in estimated energy intake between methods, using Bland-Altman analysis and WR as the benchmark, and prevalence of misreporting, using the Goldberg cut-off method, updated by Black. In total, 63 participants were recruited, with a dropout rate of 19.0% prior to timepoint 1 and additional 6.4% prior to timepoint 2. Quality deficits were identified for all methods. The FD was most acceptable to participants, followed by the PR. The difference in estimated energy intake between assessment methods was not statistically significant, though there was considerable individual variability. Underreporting was considerable across all methods but appeared highest in the PR. A FD and PR present as feasible and acceptable methods for assessing dietary intake in people with SMI. Further validity testing is required. In addition, clear guidance for completion and removal of potential barriers is required for participants.

Characteristics of Patients with Type 1 Diabetes and Additional Autoimmune Disease in the DPV Registry.

CONTEXT: Autoimmune diseases affect ~8% of the population. Type 1 diabetes mellitus (T1DM) is linked to other autoimmune diseases (AIDs), such as autoimmune thyroid disease or Addison's disease (AD), that may impact diabetes therapy and outcome. OBJECTIVE: To analyze demographic and clinical characteristics of other AIDs in T1DM from a large standardized registry, the Prospective Diabetes Follow-up Registry (DPV). METHODS: We searched the registry for T1DM with the additional diagnosis of Hashimoto's thyroiditis (HT), Graves' disease (GD), and/or AD. T1DM with other AIDs (n = 6166, 5.4%) were compared with isolated T1DM (n = 107 457). For group comparisons, we used multivariable regression models with age, sex, diabetes duration, migration background, and type of insulin regimen as basic adjustments (microvascular endpoints: additionally adjusted for glycated hemoglobin). RESULTS: Patients with additional AIDs were more often female (54.7 vs 32.0%, P < .001) and had a longer diabetes duration (7.9 [4.2-12.5] vs 6.7 [2.7-12.9] years, P < .001). After adjustment, daily insulin dosage was higher in AD and HT than in isolated T1DM (0.858 ±â€…0.032 and 0.813 ±â€…0.005 vs 0.793 ±â€…0.001 IU/kg per day). Retinopathy was less common in HT (1.5%), whereas it was more frequent in GD (3.1%) than in isolated T1DM (1.8%). In both GD and HT, microalbuminuria occurred less often (10.6% and 14.3% vs 15.5%) and neuropathy (2.1% and 1.8% vs 0.8%) was more common than in isolated T1DM. All P < .05. CONCLUSION: T1DM with additional AIDs show heterogeneous differences compared with isolated T1DM. T1DM plus AD or HT requires more insulin. Further, the rate of neuropathy is higher in HT or GD, whereas the rate of microalbuminuria is lower.

A Comparison of Familial and Sporadic Type 1 Diabetes Among Young Patients.

OBJECTIVE: To investigate natural course, treatment, and outcomes in familial versus sporadic type 1 diabetes. RESEARCH DESIGN AND METHODS: In a population-based study, we compared patients with onset of type 1 diabetes before the age of 20 years who had a first-degree relative with type 1 diabetes (familial diabetes) with patients with type 1 diabetes who had no first-degree relative with type 1 diabetes (sporadic diabetes) at diagnosis and over the first 10 treatment years, using multivariable regression and proportional hazards models. Patients were identified from the Diabetes Prospective Follow-up Registry (DPV) between 1995 and 2018. RESULTS: Of 57,371 patients with type 1 diabetes, 53,606 (93.4%) had sporadic diabetes and 3,765 (6.6%) had familial diabetes. Familial diabetes, compared with sporadic diabetes, was associated with younger age (median 7.9 vs. 9.7 years, P < 0.001), lower prevalence of ketoacidosis (11.9% vs. 20.4%, P < 0.001), and lower HbA1c levels (9.7% vs. 11.1%, P < 0.001) at onset and higher prevalence of associated autoimmune disease (16.7% vs. 13.6%, P < 0.001). Over 10 years, patients with familial diabetes, in comparison with sporadic diabetes, more often used insulin pumps (P < 0.001) and had a lower rate of severe hypoglycemia (12.97 vs. 14.44 per 100 patient-years, P < 0.001) but similar HbA1c levels (P ≥ 0.08) and ketoacidosis rates (1.85 vs. 2.06 per 100 patient-years, P = 0.11). In familial and sporadic diabetes, absence of ketoacidosis at onset predicted fewer events of severe hypoglycemia (hazard ratio [HR] 0.67, P < 0.001, and 0.91, P < 0.001, respectively) and of ketoacidosis (HR 0.64, P = 0.007, and 0.66, P < 0.001, respectively) after 10 years. CONCLUSIONS: Familial type 1 diabetes, compared with sporadic type 1 diabetes, is characterized by earlier disease manifestation and higher autoimmune comorbidity as well as less metabolic decompensation at onset, likely related to higher disease awareness in affected families, while the course of disease is similar. These findings may have implications for the generalizability of results of diabetes prevention trials from patients with familial type 1 diabetes to patients with sporadic type 1 diabetes.

Thiamine-Responsive Megaloblastic Anemia-Related Diabetes: Long-Term Clinical Outcomes in 23 Pediatric Patients From the DPV and SWEET Registries.

OBJECTIVES: To describe clinical presentation and long-term outcomes in a large cohort of children diagnosed with thiamine-responsive megaloblastic anemia (TRMA)-related diabetes. METHODS: Data from the Diabetes Patienten Verlaufsdokumentation (DPV) and Better control in Pediatric and Adolescent diabeteS: Working to crEate CEnTers of Reference (SWEET) registries were used to identify cases. Complementary information was collected through a chart review of each case. Descriptive analyses with medians and interquartile ranges and numbers (proportions) were tabulated. RESULTS: We identified 23 cases (52% male) in the 2 registries. Eighteen (78%) had genetic confirmation of TRMA. Median age at diabetes onset was 1.4 (quartiles 0.8 to 3.6) years and median age at initiation of thiamine treatment was 5.9 (2.4 to 12.4) years. At their most recent visit, patients' median age was 14.3 (8.1 to 17.5) years, glycated hemoglobin level was 6.9% (6.1% to 7.9%), insulin dose was 0.9 (0.4 to 1.2) units/kg per day and thiamine dose was 200 (100 to 300) mg/day. Three patients were not treated with insulin or antidiabetic drugs. There was no difference in diabetes outcomes in patients with initiation of thiamine ≤1 year after diabetes onset compared to patients with initiation of thiamine >1 year after diabetes onset. CONCLUSIONS: This is the longest case series of pediatric TRMA-related diabetes reported to date. Diabetes onset often occurs several years before initiation of thiamine supplementation. Early initiation of thiamine (within 1 year of diabetes onset) was not linked to improved diabetes outcome. However, the role of thiamine in pancreatic function needs further assessment. Patients with TRMA-related diabetes maintained good glycemic control even after 9 years (median) of follow up.

Glucose Tolerance in Patients with Cystic Fibrosis - Results from the German Cystic Fibrosis Registry.

BACKGROUND: Oral glucose tolerance (OGT) deteriorates progressively in cystic fibrosis (CF). Clinical registries provide a unique basis to study real-world data. PATIENTS & METHODS: OGT tests (OGTTs) documented in the German CF-registry in 2016 were classified according WHO, modified by ADA: normal glucose tolerance (NGT), indeterminate glycaemia (INDET), impaired fasting glucose (IFG), impaired glucose tolerance (IGT), IFG+IGT, diabetes mellitus (DM). To study the association with lung function, multivariable regression adjusted for age, sex, and CFTR mutation was performed. RESULTS: Overall, OGTT screening was done in 35% of CF patients ≧10 years. Of the 996 patients (46.4% females; median age (IQR): 19 (14-27) years) with evaluable OGTTs, 56.2% had either NGT or INDET, whereas 34% had a pre-diabetic OGTT (IFG; IGT; IFG+IGT) and 9.8% a diabetic OGTT. 7 patients had glucose tolerance abnormalities <10 years. DM was more common in females or patients with F508del homozygote mutation, whereas IFG was more frequent in males (all p<0.05). Nearly 75% of patients after transplantation and about half with enteral/parental nutrition and/or steroid use had either a pre-diabetic or diabetic glucose tolerance. In the adjusted model, age (p<0.001) and OGTT category (p=0.013) had both a significant impact on %FEV1. CONCLUSION: Our data of the German CF-registry highlights incidence of glucose tolerance abnormalities in second decade of life in CF patients. However, it also underlines the need for improvement of the documentation and/or performance of OGTT screening in real-world CF care. HINTERGRUND: Bei Mukoviszidose (zystischer Fibrose: CF) verschlechtert sich die orale Glukosetoleranz (OGT) im Krankheitsverlauf. PATIENTEN & METHODEN: OGT Tests (OGTTs), die 2016 im Deutschen CF-Register dokumentiert waren, wurden gemäß WHO (modifiziert nach ADA) kategorisiert: Normale Glukosetoleranz (NGT), intermittierende Glykämie (INDET), eingeschränkte Nüchternglukosetoleranz (IFG), gestörte Glukosetoleranz (IGT), IFG+IGT, Diabetes Mellitus (DM). Um den Zusammenhang mit der Lungenfunktion zu analysieren, wurde eine multivariable Regressionsanalyse adjustiert für Alter, Geschlecht und CFTR Mutation durchgeführt. ERGEBNISSE: Insgesamt wurden 35% der CF-Patienten ≥10 Jahre mittels OGTT gescreent. Von den 996 Patienten (46,4% weiblich, medianes Alter (IQR): 19 (14-27) Jahre) mit auswertbaren OGTTs hatten 56,2% entweder NGT oder INDET, wohingegen bei 34% ein prädiabetischer (IFG; IGT; IFG+IGT) und bei 9,8% ein diabetischer OGTT beobachtet wurde. Bei 7 Patienten zeigten sich vor dem 10. LJ Abnormalitäten im Glukosestoffwechsel. DM war häufiger bei Frauen und Patienten mit homozygoter F508del Mutation, wobei IFG öfters bei Männern vorlag (alle p<0,05). Ca. 75% der Patienten mit Transplantation und etwa die Hälfte der Patienten mit künstlicher Ernährung und/oder Steroidgabe hatten eine prädiabetische oder diabetische Glukosetoleranz. Das Alter (p<0,001) und die OGTT Kategorie (p=0,013) zeigten im adjustierten Modell eine signifikante Assoziation mit %FEV1. SCHLUSSFOLGERUNG: Unsere Daten unterstreichen das Auftreten von Abnormalitäten im Glukosestoffwechsel bei CF im 2. Lebensjahrzehnt. Jedoch weißt es auf die Notwendigkeit eines regelmäßigen Diabetesscreenings und/oder Dokumentation von OGTTs bei CF hin.

Longitudinal trajectories of BMI z-score: an international comparison of 11,513 Australian, American and German/Austrian/Luxembourgian youth with type 1 diabetes.

BACKGROUND: BMI fluctuations during puberty are common. Data on individual change in BMI from childhood to young adulthood are limited in youth with type 1 diabetes. OBJECTIVES: To compare longitudinal trajectories of body mass index z score (BMIz) from childhood to adolescence across three registries spanning five countries. METHODS: Data sources: T1DX (USA), DPV (Germany/Austria/Luxembourg) and ADDN (Australia). The analysis included 11,513 youth with type 1 diabetes, duration >1 year, at least one BMI measure at baseline (age 8-10 years) and >5 aggregated BMI measures by year of age during follow-up until age 17 years. BMIz was calculated based on WHO charts. Latent class growth modelling was used to identify subgroups following a similar trajectory of BMIz over time. RESULTS: Five distinct trajectories of BMIz were present in the T1DX and ADDN cohorts, while six trajectories were identified in the DPV cohort. Boys followed more often a low/near-normal pattern while elevated BMIz curves were more likely in girls (ADDN; DPV). For T1DX cohort, no sex differences were observed. Comparing the reference group (BMIz ~0) with the other groups during puberty, higher BMIz was significantly associated with older age at T1D onset, racial/ethnic minority and elevated HbA1c (all p<0.05). CONCLUSION: This multinational study presents unique BMIz trajectories in youth with T1D across three continents. The prevalence of overweight and the longitudinal persistence of overweight support the need for close monitoring of weight and nutrition in this population. The international and individual differences likely result from diverse genetic, environmental and therapeutic factors.

Lower HbA1c in patients with type 1 diabetes and celiac disease who reached celiac-specific antibody-negativity-A multicenter DPV analysis.

OBJECTIVES: To study celiac-specific antibody status over 3 years in patients with type 1 diabetes and biopsy-proven celiac disease (T1D + CD). Furthermore, to determine clinical differences after diagnosis between patients reaching constant antibody-negativity (Ab-neg) and staying antibody-positive (Ab-pos). METHODS: A total of 608 pediatric T1D + CD patients from the multicenter DPV registry were studied longitudinally regarding their CD specific antibody-status. Differences between Ab-neg (n = 218) and Ab-pos (n = 158) patients 3 years after biopsy were assessed and compared with 26 833 T1D patients without CD by linear and logistic regression adjusted for age, gender, diabetes duration and migration background. RESULTS: Thirty-six percent of T1D + CD patients reached and sustained antibody-negativity 3 years after CD diagnosis. The median time until patients returned to Ab-neg was 0.86 (0.51;1.16) years. Three years after diagnosis, HbA1c was lowest in Ab-neg and highest in Ab-pos patients compared to T1D-only patients (adjusted mean (95%CI): 7.72 (7.51-7.92) % vs 8.44 (8.20-8.68) % vs 8.19 (8.17-8.21) %, adjusted P < 0.001, respectively). Total cholesterol, LDL-cholesterol and frequency of dyslipidemia were significantly lower in Ab-neg compared to T1D-only patients (167 (161-173) mg/dl vs 179 (178-179) mg/dl, P < .001; 90 (84-96) mg/dl vs 99 (98-99) mg/dl, P = .005; 15.7 (10.5-22.9) % vs 25.9 (25.2-26.6) %, P = .017). In longitudinal analyses over 6 years after diagnosis, a constantly higher HbA1c (P < .001) and a lower height-SDS (P = .044) was observed in Ab-pos compared to Ab-neg patients. CONCLUSION: Only one third of T1D + CD patients reached constant Ab-negativity after CD diagnosis. Achieving Ab-negativity after diagnosis seems to be associated with better metabolic control and growth, supposedly due to a higher adherence to therapy in general.

Five heterogeneous HbA1c trajectories from childhood to adulthood in youth with type 1 diabetes from three different continents: A group-based modeling approach.

OBJECTIVES: Only a fraction of youth meet established targets for glycemic control; many experience deteriorating control over time. We compared trajectories of hemoglobin A1c (HbA1c) among youth from three trans-continental type 1 diabetes (T1D) registries and identified clinical variables associated with the odds of following increasing vs stable trajectories. RESEARCH DESIGN AND METHODS: Analyses included longitudinal data from 15 897 individuals age 8 to 18 with T1D for at least 2 years and HbA1c measurements in at least 5 years during the observation period. Cohorts were selected from Australasian Diabetes Data Network (ADDN; Australia), German/Austrian/Luxembourgian Diabetes-Patienten-Verlaufsdokumentation initiative (DPV; Germany/Austria/Luxembourga), and the T1D Exchange Clinic Network (T1DX; US) clinic registries. Group-based trajectory modeling and multivariable logistic regression identified unique HbA1c trajectories and their predictors. RESULTS: Five heterogeneous trajectories of glycemic control in each registry were identified: low, intermediate, high stable; intermediate and high increasing. The overall HbA1c level for each trajectory group tended to be lowest in the DPV, higher in the ADDN, and highest in the T1DX. The absolute level of HbA1c and the proportion of individuals within each trajectory varied across registries: 17% to 22% of individuals followed an increasing trajectory. Compared with maintaining a stable trajectory, following an increasing trajectory was significantly associated with ethnic minority status, lower height z-score, higher BMI z-score, insulin injection therapy, and the occurrence of severe hypoglycemia; however, these factors were not consistent across the three registries. CONCLUSIONS: We report the first multinational registry-based comparison of glycemic control trajectories among youth with T1D from three continents and identify possible targets for intervention in those at risk of an increasing HbA1c trajectory.