Feature ranking based on synergy networks to identify prognostic markers in DPT-1

Interaction among different risk factors plays an important role in the development and progress of complex disease, such as diabetes. However, traditional epidemiological methods often focus on analyzing individual or a few ‘essential’ risk factors, hopefully to obtain some insights into the etiology of complex disease. In this paper, we propose a systematic framework for risk factor analysis based on a synergy network, which enables better identification of potential risk factors that may serve as prognostic markers for complex disease. A spectral approximate algorithm is derived to solve this network optimization problem, which leads to a new network-based feature ranking method that improves the traditional feature ranking by taking into account the pairwise synergistic interactions among risk factors in addition to their individual predictive power. We first evaluate the performance of our method based on simulated datasets, and then, we use our method to study immunologic and metabolic indices based on the Diabetes Prevention Trial-Type 1 (DPT-1) study that may provide prognostic and diagnostic information regarding the development of type 1 diabetes. The performance comparison based on both simulated and DPT-1 datasets demonstrates that our network-based ranking method provides prognostic markers with higher predictive power than traditional analysis based on individual factors

A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study

M. Knip on TEDDY Study Grp -työryhmän jäsen.Regression models are extensively used in many epidemiological studies to understand the linkage between specific outcomes of interest and their risk factors. However, regression models in general examine the average effects of the risk factors and ignore subgroups with different risk profiles. As a result, interventions are often geared towards the average member of the population, without consideration of the special health needs of different subgroups within the population. This paper demonstrates the value of using rule-based analysis methods that can identify subgroups with heterogeneous risk profiles in a population without imposing assumptions on the subgroups or method. The rules define the risk pattern of subsets of individuals by not only considering the interactions between the risk factors but also their ranges. We compared the rule-based analysis results with the results from a logistic regression model in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Both methods detected a similar suite of risk factors, but the rule-based analysis was superior at detecting multiple interactions between the risk factors that characterize the subgroups. A further investigation of the particular characteristics of each subgroup may detect the special health needs of the subgroup and lead to tailored interventions.Peer reviewe

Gastrointestinal Infections Modulate the Risk for Insulin Autoantibodies as the First-Appearing Autoantibody in the TEDDY Study

OBJECTIVE To investigate gastrointestinal infection episodes (GIEs) in relation to the appear-ance of islet autoantibodies in The Environmental Determinants of Diabetes in the Young (TEDDY) cohort. RESEARCH DESIGN AND METHODS GIEs on risk of autoantibodies against either insulin (IAA) or GAD (GADA) as the first-appearing autoantibody were assessed in a 10-year follow-up of 7,867 children. Stool virome was characterized in a nested case-control study. RESULTS GIE reports (odds ratio [OR] 2.17 [95% CI 1.39–3.39]) as well as Norwalk viruses found in stool (OR 5.69 [1.36–23.7]) at <1 year of age were associated with an increased IAA risk at 2–4 years of age. GIEs reported at age 1 to <2 years correlated with a lower risk of IAA up to 10 years of age (OR 0.48 [0.35–0.68]). GIE reports at any other age were associated with an increase in IAA risk (OR 2.04 for IAA when GIE was observed 12–23 months prior [1.41–2.96]). Impacts on GADA risk were limited to GIEs <6 months prior to autoantibody development in children <4 years of age (OR 2.16 [1.54–3.02]). CONCLUSIONS Bidirectional associations were observed. GIEs were associated with increased IAA risk when reported before 1 year of age or 12–23 months prior to IAA. Nor-walk virus was identified as one possible candidate factor. GIEs reported during the 2nd year of life were associated with a decreased IAA risk.Peer reviewe

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.Peer reviewe

Temporal changes in gastrointestinal fungi and the risk of autoimmunity during early childhood: the TEDDY study

Fungal infections are a major health problem that often begin in the gastrointestinal tract. Gut microbe interactions in early childhood are critical for proper immune responses, yet there is little known about the development of the fungal population from infancy into childhood. Here, as part of the TEDDY (The Environmental Determinants of Diabetes in the Young) study, we examine stool samples of 888 children from 3 to 48 months and find considerable differences between fungi and bacteria. The metagenomic relative abundance of fungi was extremely low but increased while weaning from milk and formula. Overall fungal diversity remained constant over time, in contrast with the increase in bacterial diversity. Fungal profiles had high temporal variation, but there was less variation from month-to-month in an individual than among different children of the same age. Fungal composition varied with geography, diet, and the use of probiotics. Multiple Candida spp. were at higher relative abundance in children than adults, while Malassezia and certain food-associated fungi were lower in children. There were only subtle fungal differences associated with the subset of children that developed islet autoimmunity or type 1 diabetes. Having proper fungal exposures may be crucial for children to establish appropriate responses to fungi and limit the risk of infection: the data here suggests those gastrointestinal exposures are limited and variable.</p

Genetic scores to stratify risk of developing multiple islet autoantibodies and type 1 diabetes: A prospective study in children

BackgroundAround 0.3% of newborns will develop autoimmunity to pancreatic beta cells in childhood and subsequently develop type 1 diabetes before adulthood. Primary prevention of type 1 diabetes will require early intervention in genetically at-risk infants. The objective of this study was to determine to what extent genetic scores (two previous genetic scores and a merged genetic score) can improve the prediction of type 1 diabetes.Methods and findingsThe Environmental Determinants of Diabetes in the Young (TEDDY) study followed genetically at-risk children at 3-to 6-monthly intervals from birth for the development of islet auto-antibodies and type 1 diabetes. Infants were enrolled between 1 September 2004 and 28 February 2010 and monitored until 31 May 2016. The risk (positive predictive value) for developing multiple islet autoantibodies (pre-symptomatic type 1 diabetes) and type 1 diabetes was determined in 4,543 children who had no first-degree relatives with type 1 diabetes and either a heterozygous HLA DR3 and DR4-DQ8 risk genotype or a homozygous DR4-DQ8 genotype, and in 3,498 of these children in whom genetic scores were calculated from 41 single nucleotide polymorphisms. In the children with the HLA risk genotypes, risk for developing multiple islet autoantibodies was 5.8% (95% CI 5.0%-6.6%) by age 6 years, and risk for diabetes by age 10 years was 3.7% (95% CI 3.0%-4.4%). Risk for developing multiple islet autoantibodies was 11.0% (95% CI 8.7%-13.3%) in children with a merged genetic score of >14.4 (upper quartile; n = 907) compared to 4.1% (95% CI 3.3%-4.9%, P 14.4 compared with 2.7% (95% CI 1.9%-3.6%) in children with a score of 14.4. Scores were higher in European versus US children (P = 0.003). In children with a merged score of >14.4, risk for multiple islet autoantibodies was similar and consistently >10% in Europe and in the US; risk was greater in males than in females (P = 0.01). Limitations of the study include that the genetic scores were originally developed from case-control studies of clinical diabetes in individuals of mainly European decent. It is, therefore, possible that it may not be suitable to all populations.ConclusionsA type 1 diabetes genetic score identified infants without family history of type 1 diabetes who had a greater than 10% risk for pre-symptomatic type 1 diabetes, and a nearly 2-fold higher risk than children identified by high-risk HLA genotypes alone. This finding extends the possibilities for enrolling children into type 1 diabetes primary prevention trials

Methods, quality control and specimen management in an international multicentre investigation of type 1 diabetes: TEDDY.

The vast array and quantity of longitudinal samples collected in The Environmental Determinants of Diabetes in the Young study present a series of challenges in terms of quality control procedures and data validity. To address this, pilot studies have been conducted to standardize and enhance both biospecimen collection and sample obtainment in terms of autoantibody collection, stool sample preservation, RNA, biomarker stability, metabolic biomarkers and T-cell viability.The Environmental Determinants of Diabetes in the Young is a multicentre, international prospective study (n = 8677) designed to identify environmental triggers of type 1 diabetes (T1D) in genetically at-risk children from ages 3 months until 15 years. The study is conducted through six primary clinical centres located in four countries.As of May 2012, over three million biological samples and 250 million total data points have been collected, which will be analysed to assess autoimmunity status, presence of inflammatory biomarkers, genetic factors, exposure to infectious agents, dietary biomarkers and other potentially important environmental exposures in relation to autoimmunity and progression to T1D.Detailed procedures were utilized to standardize both data harmonization and management when handling a large quantity of longitudinal samples obtained from multiple locations. In addition, a description of the available specimens is provided that serve as an invaluable repository for the elucidation of determinants in T1D focusing on autoantibody concordance and harmonization, transglutaminase autoantibody, inflammatory biomarkers (T-cells), genetic proficiency testing, RNA lab internal quality control testing, infectious agents (monitoring cross-contamination, virus preservation and nasal swab collection validity) and HbA1c testing

Differences in recruitment and early retention among ethnic minority participants in a large pediatric cohort: The TEDDY Study

Objective: The TEDDY Study is an international, multi-center prospective study designed to identify the environmental triggers of type 1 diabetes (T1D) in genetically at-risk children. This report investigates ethnic minority (EM) differences in patterns of enrollment and retention in the US centers. Methods: As of June 2009, 267,739 newborns had been screened at birth for high risk T1D genotypes. Data collected at the time of screening, enrollment and at the baseline visit were used. Descriptive and multiple-logistic regression analyses assessed differences between EM groups regarding exclusion, enrollment and early withdrawal. Results: Of the 10,975 eligible subjects, 6,912 (67%) were invited to participate. EM subjects were more likely to be excluded because of an inability to contact. Of those invited 3,265 (47%) enrolled by the age of 4.5 months. Adjusted analyses showed that except for those classified as other EM, the odds of enrolling were similar across groups. EM subjects had elevated early withdrawal rates. Adjusted models demonstrated that this was significantly more likely among Hispanic subjects. Conclusion: Understanding patterns associated with EM participation in research extends our ability to make more accurate inferences and permits assessment of strategies that promote inclusion of EM to better address health disparities. (C) 2012 Elsevier Inc. All rights reserved

Long-Term Outcome of Individuals Treated With Oral Insulin Diabetes Prevention Trial-Type 1 (DPT-1) oral insulin trial

OBJECTIVE-To evaluate the long-term intervention effects of oral insulin on the development of type 1 diabetes and to assess the rate of progression to type 1 diabetes before and after oral insulin treatment was stopped in the Diabetes Prevention Trial-Type 1 (DPT-1). RESEARCH DESIGN AND METHODS-The follow-up included subjects who participated in the early intervention of oral insulin (1994-2003) to prevent or delay type 1 diabetes. A telephone survey was conducted in 2009 to determine whether diabetes had been diagnosed and, if not, an oral glucose tolerance test (OGTT), hemoglobin A(1c) (HbA(1c)), and autoantibody levels were obtained on all subjects who agreed to participate. RESULTS-Of 372 subjects randomized, 97 developed type I diabetes before follow-up; 75% of the remaining 275 subjects were contacted. In the interim, 77 subjects had been diagnosed with type 1 diabetes and 54 of the remainder have had an OGTT; 10 of these were diagnosed with type 1 diabetes, subsequently. Among individuals meeting the original criteria for insulin auto-antibodies (IAAs) (&gt;= 80 nU/mL), the overall benefit of oral insulin remained significant (P = 0.05). However, the hazard rate in this group increased (from 6.4% [95% Cl 4.5-9.11 to 10.0% [7.1-14.11) after cessation of therapy, which approximated the rate of individuals treated with placebo (10.2% [7.1-14.6]). CONCLUSIONS-Overall, the oral insulin treatment effect in individuals with confirmed IAA &gt;= 80 nU/mL appeared to be maintained with additional follow-up; however, once therapy stopped, the rate of developing diabetes in the oral insulin group increased to a rate similar to that in the placebo group