Quality Control Analysis in Real-time (QC-ART) : A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those because of collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected. In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality because of the need for instrument cleaning and/or re-calibration. To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired to dynamically flag potential issues with instrument performance or sample quality. QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis. We demonstrate the utility and performance of QC-ART in identifying deviations in data quality because of both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments.Peer reviewe

Plasma 25-Hydroxyvitamin D Concentration and Risk of Islet Autoimmunity

We examined the association between plasma 25-hydroxyvitamin D [25(OH)D] concentration and islet autoimmunity (IA) and whether vitamin D gene polymorphisms modify the effect of 25(OH)D on IA risk. We followed 8,676 children at increased genetic risk of type 1 diabetes at six sites in the U.S. and Europe. We defined IA as positivity for at least one autoantibody (GADA, IAA, or IA-2A) on two or more visits. We conducted a risk set sampled nested case-control study of 376 IA case subjects and up to 3 control subjects per case subject. 25(OH)D concentration was measured on all samples prior to, and including, the first IA positive visit. Nine polymorphisms in VDR, CYP24A, CYP27B1, GC, and RXRA were analyzed as effect modifiers of 25(OH)D. Adjusting for HLA-DR-DQ and ancestry, higher childhood 25(OH)D was associated with lower IA risk (odds ratio = 0.93 for a 5 nmol/L difference; 95% CI 0.89, 0.97). Moreover, this association was modified by VDR rs7975232 (interaction P = 0.0072), where increased childhood 25(OH)D was associated with a decreasing IA risk based upon number of minor alleles: 0 (1.00; 0.93, 1.07), 1 (0.92; 0.89, 0.96), and 2 (0.86; 0.80, 0.92). Vitamin D and VDR may have a combined role in IA development in children at increased genetic risk for type 1 diabetes.Peer reviewe

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

Cesarean Section on the Risk of Celiac Disease in the Offspring: The Teddy Study

Objective: Cesarean section (C-section) is associated with various immune-mediated diseases in the offspring. We investigated the relationship between mode of delivery and celiac disease (CD) and CD autoimmunity (CDA) in a multinational birth cohort. Methods: From 2004 to 2010, infants from the general population who tested positive for HLADR3-DQ2 or DR4-DQ8 were enrolled in The Environmental Determinants for Diabetes in the Young (TEDDY) study. Children were annually screened for transglutaminase autoantibodies, if positive, they are retested after 3 to 6 months and those persistently positive defined as CDA. Associations of C-section with maternal (age, education level, parity, pre-pregnancy weight, diabetes, smoking, weight gain during pregnancy) and child characteristics (gestational age, birth weight) were examined by Fisher exact test or Wilcoxon rank-sum test. Hazard ratios (HRs) for CDA or CD were calculated by Cox proportional hazard regression models. Results: Of 6087 analyzed singletons, 1600 (26%) were born by C-section (Germany 38%, United States 37%, Finland 18%, Sweden 16%), and the remaining were born vaginally without instrumental support;979 (16%) had developed CDA and 343 (6%) developed CD. C-section was associated with lower risk for CDA (hazard ratio [HR] = 0.85;95% confidence interval [CI] 0.73, 0.99 P = 0.032) and CD (HR = 0.75;95% CI 0.58, 0.98;P = 0.034). After adjusting for country, sex, HLA-genotype, CD in family, maternal education, and breast-feeding duration, significance was lost for CDA (HR = 0.91;95% CI 0.78, 1.06;P = 0.20) and CD (HR = 0.85;95% CI 0.65, 1.11;P = 0.24). Presurgical ruptured membranes had no influence on CDA or CD development. Conclusion: C-section is not associated with increased risk for CDA or CD in the offspring

Participant Experiences in the Environmental Determinants of Diabetes in the Young Study : Common Reasons for Withdrawing

M. Knip on TEDDY Study Grp -työryhmän jäsen.Background. To characterize participant reasons for withdrawing from a diabetes focused longitudinal clinical observational trial (TEDDY) during the first three study years. Methods. 8677 children were recruited into the TEDDY study. At participant withdrawal staff recorded any reason parents provided for withdrawal. Reasons were categorized into (1) family characteristics and (2) protocol reasons. Families who informed staff of their withdrawal were classified as active withdrawals (AW); families without a final contact were considered passive withdrawals (PW). Results. Withdrawal was highest during the first study year (n = 1220). Most families were AW(n = 1549; 73.4%). PW was more common in the United States (n = 1001; 37.8%) and among young mothers (p = 0.001). The most frequent protocol characteristic was blood draw (55%) and the most common family reason was not having enough time (66%). The blood draw was more common among female participants; being too busy was more common among males. Both reasons were associated with study satisfaction. Conclusions. Results suggest that, for families of children genetically at risk for diabetes, procedures that can be painful/frightening should be used with caution. Study procedures must also be considered for the demands placed on participants. Study satisfaction should be regularly assessed as an indicator of risk for withdrawal.Peer reviewe

Metagenomics of the faecal virome indicate a cumulative effect of enterovirus and gluten amount on the risk of coeliac disease autoimmunity in genetically at risk children: the TEDDY study

Objective: Higher gluten intake, frequent gastrointestinal infections and adenovirus, enterovirus, rotavirus and reovirus have been proposed as environmental triggers for coeliac disease. however, it is not known whether an interaction exists between the ingested gluten amount and viral exposures in the development of coeliac disease. This study investigated whether distinct viral exposures alone or together with gluten increase the risk of coeliac disease autoimmunity (cDa) in genetically predisposed children. Design: The environmental Determinants of Diabetes in the Young study prospectively followed children carrying the hla risk haplotypes DQ2 and/or DQ8 and constructed a nested case–control design. From this design, 83 cDa case–control pairs were identified. Median age of cDa was 31 months. stool samples collected monthly up to the age of 2 years were analysed for virome composition by illumina next-generation sequencing followed by comprehensive computational virus profiling. Results: The cumulative number of stool enteroviral exposures between 1 and 2 years of age was associated with an increased risk for cDa. in addition, there was a significant interaction between cumulative stool enteroviral exposures and gluten consumption. The risk conferred by stool enteroviruses was increased in cases reporting higher gluten intake. Conclusions: Frequent exposure to enterovirus between 1 and 2 years of age was associated with increased risk of cDa. The increased risk conferred by the interaction between enteroviruses and higher gluten intake indicate a cumulative effect of these factors in the development of cDa.Peer reviewe

A combined risk score enhances prediction of type 1 diabetes among susceptible children

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordType 1 diabetes (T1D)-an autoimmune disease that destroys the pancreatic islets, resulting in insulin deficiency-often begins early in life when islet autoantibody appearance signals high risk1. However, clinical diabetes can follow in weeks or only after decades, and is very difficult to predict. Ketoacidosis at onset remains common2,3 and is most severe in the very young4,5, in whom it can be life threatening and difficult to treat6-9. Autoantibody surveillance programs effectively prevent most ketoacidosis10-12 but require frequent evaluations whose expense limits public health adoption13. Prevention therapies applied before onset, when greater islet mass remains, have rarely been feasible14 because individuals at greatest risk of impending T1D are difficult to identify. To remedy this, we sought accurate, cost-effective estimation of future T1D risk by developing a combined risk score incorporating both fixed and variable factors (genetic, clinical and immunological) in 7,798 high-risk children followed closely from birth for 9.3 years. Compared with autoantibodies alone, the combined model dramatically improves T1D prediction at ≥2 years of age over horizons up to 8 years of age (area under the receiver operating characteristic curve ≥ 0.9), doubles the estimated efficiency of population-based newborn screening to prevent ketoacidosis, and enables individualized risk estimates for better prevention trial selection.National Institutes of Health/National Center for Advancing Translational Sciences Clinical and Translational ScienceDiabetes Research CenterDiabetes UKWellcome TrustJDR