| 11. |
- Bonifacio, Ezio, et al.
(författare)
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Genetic scores to stratify risk of developing multiple islet autoantibodies and type 1 diabetes : A prospective study in children
- 2018
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Ingår i: PLoS Medicine. - : Public Library of Science (PLoS). - 1549-1676. ; 15:4
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Tidskriftsartikel (refereegranskat)abstract
- Background: Around 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 findings: The 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 autoantibodies 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 < 0.001) in children with a genetic score of ≤14.4 (n = 2,591). Risk for developing diabetes by age 10 years was 7.6% (95% CI 5.3%–9.9%) in children with a merged score of >14.4 compared with 2.7% (95% CI 1.9%–3.6%) in children with a score of ≤14.4 (P < 0.001). Of 173 children with multiple islet autoantibodies by age 6 years and 107 children with diabetes by age 10 years, 82 (sensitivity, 47.4%; 95% CI 40.1%–54.8%) and 52 (sensitivity, 48.6%, 95% CI 39.3%–60.0%), respectively, had a score >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. Conclusions: A 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.
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| 12. |
- Elding Larsson, Helena, et al.
(författare)
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Pandemrix® vaccination is not associated with increased risk of islet autoimmunity or type 1 diabetes in the TEDDY study children
- 2018
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 61:1, s. 193-202
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Tidskriftsartikel (refereegranskat)abstract
- Aims/hypothesis: During the A/H1N1 2009 (A/California/04/2009) pandemic, mass vaccination with a squalene-containing vaccine, Pandemrix®, was performed in Sweden and Finland. The vaccination was found to cause narcolepsy in children and young adults with the HLA-DQ 6.2 haplotype. The aim of this study was to investigate if exposure to Pandemrix® similarly increased the risk of islet autoimmunity or type 1 diabetes. Methods: In The Environmental Determinants of Diabetes in the Young (TEDDY) study, children are followed prospectively for the development of islet autoimmunity and type 1 diabetes. In October 2009, when the mass vaccination began, 3401 children at risk for islet autoimmunity and type 1 diabetes were followed in Sweden and Finland. Vaccinations were recorded and autoantibodies against insulin, GAD65 and insulinoma-associated protein 2 were ascertained quarterly before the age of 4 years and semi-annually thereafter. Results: By 5 August 2010, 2413 of the 3401 (71%) children observed as at risk for an islet autoantibody or type 1 diabetes on 1 October 2009 had been vaccinated with Pandemrix®. By 31 July 2016, 232 children had at least one islet autoantibody before 10 years of age, 148 had multiple islet autoantibodies and 96 had developed type 1 diabetes. The risk of islet autoimmunity was not increased among vaccinated children. The HR (95% CI) for the appearance of at least one islet autoantibody was 0.75 (0.55, 1.03), at least two autoantibodies was 0.85 (0.57, 1.26) and type 1 diabetes was 0.67 (0.42, 1.07). In Finland, but not in Sweden, vaccinated children had a lower risk of islet autoimmunity (0.47 [0.29, 0.75]), multiple autoantibodies (0.50 [0.28, 0.90]) and type 1 diabetes (0.38 [0.20, 0.72]) compared with those who did not receive Pandemrix®. The analyses were adjusted for confounding factors. Conclusions/interpretation: Children with an increased genetic risk for type 1 diabetes who received the Pandemrix® vaccine during the A/H1N1 2009 pandemic had no increased risk of islet autoimmunity, multiple islet autoantibodies or type 1 diabetes. In Finland, the vaccine was associated with a reduced risk of islet autoimmunity and type 1 diabetes.
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| 13. |
- Endesfelder, David, et al.
(författare)
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Time-resolved autoantibody profiling facilitates stratification of preclinical type 1 diabetes in children
- 2019
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Ingår i: Diabetes. - : American Diabetes Association. - 0012-1797 .- 1939-327X. ; 68:1, s. 119-130
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Tidskriftsartikel (refereegranskat)abstract
- Progression to clinical type 1 diabetes varies among children who develop b-cell autoantibodies. Differences in autoantibody patterns could relate to disease progression and etiology. Here we modeled complex longitudinal autoantibody profiles by using a novel wavelet-based algorithm. We identified clusters of similar profiles associated with various types of progression among 600 children from The Environmental Determinants of Diabetes in the Young (TEDDY) birth cohort study; these children developed persistent insulin autoantibodies (IAA), GAD autoantibodies (GADA), insulinoma-associated antigen 2 autoantibodies (IA-2A), or a combination of these, and they were followed up prospectively at 3- to 6-month intervals (median follow-up 6.5 years). Children who developed multiple autoantibody types (n = 370) were clustered, and progression from seroconversion to clinical diabetes within 5 years ranged between clusters from 6% (95% CI 0, 17.4) to 84% (59.2, 93.6). Children who seroconverted early in life (median age <2 years) and developed IAA and IA-2A that were stable-positive on follow-up had the highest risk of diabetes, and this risk was unaffected by GADA status. Clusters of children who lacked stable-positive GADA responses contained more boys and lower frequencies of the HLA-DR3 allele. Our novel algorithm allows refined grouping of b-cell autoantibody–positive children who distinctly progressed to clinical type 1 diabetes, and it provides new opportunities in searching for etiological factors and elucidating complex disease mechanisms.
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| 14. |
- Ghalwash, Mohamed, et al.
(författare)
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Data-Driven Phenotyping of Presymptomatic Type 1 Diabetes Using Longitudinal Autoantibody Profiles
- 2024
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Ingår i: Diabetes Care. - 0149-5992. ; 47:8, s. 1424-1431
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE To characterize distinct islet autoantibody profiles preceding stage 3 type 1 diabetes RESEARCH DESIGN AND METHODS The T1DI (Type 1 Diabetes Intelligence) study combined data from 1,845 genetically susceptible prospectively observed children who were positive for at least one islet au-toantibody: insulin autoantibody (IAA), GAD antibody (GADA), or islet antigen 2 antibody (IA-2A). Using a novel similarity algorithm that considers an individual’s temporal autoantibody profile, age at autoantibody appearance, and variation in the positivity of autoantibody types, we performed an unsupervised hierarchical clustering analysis. Progression rates to diabetes were analyzed via survival analysis. RESULTS We identified five main clusters of individuals with distinct autoantibody profiles characterized by seroconversion age and sequence of appearance of the three auto-antibodies. The highest 5-year risk from first positive autoantibody to type 1 diabetes (69.9%; 95% CI 60.0–79.2) was observed in children who first developed IAA in early life (median age 1.6 years) followed by GADA (1.9 years) and then IA-2A (2.1 years). Their 10-year risk was 89.9% (95% CI 81.9–95.4). A high 5-year risk was also found in children with persistent IAA and GADA (39.1%) and children with persistent GADA and IA-2A (30.9%). A lower 5-year risk (10.5%) was observed in children with a late appearance of persistent GADA (6.1 years). The lowest 5-year diabetes risk (1.6%) was associated with positivity for a single, often reverting, autoantibody. CONCLUSIONS The novel clustering algorithm identified children with distinct islet autoantibody profiles and progression rates to diabetes. These results are useful for prediction, selection of individuals for prevention trials, and studies investigating various pathways to type 1 diabetes.
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| 15. |
- Ghalwash, Mohamed, et al.
(författare)
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Islet autoantibody screening in at-risk adolescents to predict type 1 diabetes until young adulthood : a prospective cohort study
- 2023
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Ingår i: The Lancet Child and Adolescent Health. - 2352-4642. ; 7:4, s. 261-268
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Tidskriftsartikel (refereegranskat)abstract
- Background: Screening for islet autoantibodies in children and adolescents identifies individuals who will later develop type 1 diabetes, allowing patient and family education to prevent diabetic ketoacidosis at onset and to enable consideration of preventive therapies. We aimed to assess whether islet autoantibody screening is effective for predicting type 1 diabetes in adolescents aged 10−18 years with an increased risk of developing type 1 diabetes. Methods: Data were harmonised from prospective studies from Finland (the Diabetes Prediction and Prevention study), Germany (the BABYDIAB study), and the USA (Diabetes Autoimmunity Study in the Young and the Diabetes Evaluation in Washington study). Autoantibodies against insulin, glutamic acid decarboxylase, and insulinoma-associated protein 2 were measured at each follow-up visit. Children who were lost to follow-up or diagnosed with type 1 diabetes before 10 years of age were excluded. Inverse probability censoring weighting was used to include data from remaining participants. Sensitivity and the positive predictive value of these autoantibodies, tested at one or two ages, to predict type 1 diabetes by the age of 18 years were the main outcomes. Findings: Of 20 303 children with an increased type 1 diabetes risk, 8682 were included for the analysis with inverse probability censoring weighting. 1890 were followed up to 18 years of age or developed type 1 diabetes between the ages of 10 years and 18 years, and their median follow-up was 18·3 years (IQR 14·5–20·3). 442 (23·4%) of 1890 adolescents were positive for at least one islet autoantibody, and 262 (13·9%) developed type 1 diabetes. Time from seroconversion to diabetes diagnosis increased by 0·64 years (95% CI 0·34–0·95) for each 1-year increment of diagnosis age (Pearson's correlation coefficient 0·88, 95% CI 0·50–0·97, p=0·0020). The median interval between the last prediagnostic sample and diagnosis was 0·3 years (IQR 0·1–1·3) in the 227 participants who were autoantibody positive and 6·8 years (1·6–9·9) for the 35 who were autoantibody negative. Single screening at the age of 10 years was 90% (95% CI 86–95) sensitive, with a positive predictive value of 66% (60–72) for clinical diabetes. Screening at two ages (10 years and 14 years) increased sensitivity to 93% (95% CI 89–97) but lowered the positive predictive value to 55% (49–60). Interpretation: Screening of adolescents at risk for type 1 diabetes only once at 10 years of age for islet autoantibodies was highly effective to detect type 1 diabetes by the age of 18 years, which in turn could enable prevention of diabetic ketoacidosis and participation in secondary prevention trials. Funding: JDRF International.
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| 16. |
- Ghalwash, Mohamed, et al.
(författare)
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Two-age islet-autoantibody screening for childhood type 1 diabetes : a prospective cohort study
- 2022
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Ingår i: The Lancet Diabetes and Endocrinology. - 2213-8587. ; 10:8, s. 589-596
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Tidskriftsartikel (refereegranskat)abstract
- Background: Early prediction of childhood type 1 diabetes reduces ketoacidosis at diagnosis and provides opportunities for disease prevention. However, only highly efficient approaches are likely to succeed in public health settings. We sought to identify efficient strategies for initial islet autoantibody screening in children younger than 15 years. Methods: We harmonised data from five prospective cohorts from Finland (DIPP), Germany (BABYDIAB), Sweden (DiPiS), and the USA (DAISY and DEW-IT) into the Type 1 Diabetes Intelligence (T1DI) cohort. 24 662 children at high risk of diabetes enrolled before age 2 years were included and followed up for islet autoantibodies and diabetes until age 15 years, or type 1 diabetes onset, whichever occurred first. Islet autoantibodies measured included those against glutamic acid decarboxylase, insulinoma antigen 2, and insulin. Main outcomes were sensitivity and positive predictive value (PPV) of detected islet autoantibodies, tested at one or two fixed ages, for diagnosis of clinical type 1 diabetes. Findings: Of the 24 662 participants enrolled in the Type 1 Diabetes Intelligence cohort, 6722 total were followed up to age 15 years or until onset of type 1 diabetes. Type 1 diabetes developed by age 15 years in 672 children, but did not develop in 6050 children. Optimal screening ages for two measurements were 2 years and 6 years, yielding sensitivity of 82% (95% CI 79–86) and PPV of 79% (95% CI 75–80) for diabetes by age 15 years. Autoantibody positivity at the beginning of each test age was highly predictive of diagnosis in the subsequent 2–5·99 year or 6–15-year age intervals. Autoantibodies usually appeared before age 6 years even in children diagnosed with diabetes much later in childhood. Interpretation: Our results show that initial screening for islet autoantibodies at two ages (2 years and 6 years) is sensitive and efficient for public health translation but might require adjustment by country on the basis of population-specific disease characteristics. Funding: Juvenile Diabetes Research Foundation.
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| 17. |
- Hadley, David, et al.
(författare)
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HLA-DPB1*04:01 Protects Genetically Susceptible Children from Celiac Disease Autoimmunity in the TEDDY Study.
- 2015
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Ingår i: American Journal of Gastroenterology. - : Ovid Technologies (Wolters Kluwer Health). - 1572-0241 .- 0002-9270. ; 110:6, s. 915-920
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Tidskriftsartikel (refereegranskat)abstract
- Tissue transglutaminase autoantibodies (tTGAs) represent the first evidence of celiac disease (CD) development. Associations of HLA-DR3-DQA1*05:01-DQB1*02:01 (i.e., DR3-DQ2) and, to a lesser extent, DR4-DQA1*03:01-DQB1*03:02 (i.e., DR4-DQ8) with the risk of CD differ by country, consistent with additional genetic heterogeneity that further refines risk. Therefore, we examined human leukocyte antigen (HLA) factors other than DR3-DQ2 for their contribution to developing tTGAs.
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| 18. |
- Haghighi, Mona, et al.
(författare)
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A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study
- 2016
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 6
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 19. |
- Hagopian, William A., et al.
(författare)
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TEDDY- The environmental determinants of diabetes in the young - An observational clinical trial
- 2006
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Ingår i: Annals of the New York Academy of Sciences. - : Wiley. - 0077-8923. ; 1079, s. 320-326
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Tidskriftsartikel (refereegranskat)abstract
- The aim of the TEDDY study is to identify infectious agents, dietary factors, or other environmental agents, including psychosocial factors, which may either trigger islet autoimmunity, type 1 diabetes mellitus (T1DM), or both. The study has two end points: (a) appearance of islet autoantibodies and (b) clinical diagnosis of T1DM. Six clinical centers screen newborns for high-risk HLA genotypes. As of December 2005 a total of 54,470 newborns have been screened. High-risk HLA genotypes among 53,560 general population (GP) infants were 2576 (4.8%) and among 910 newborns with a first-degree relative (FDR) were 194 (21%). A total of 1061 children have been enrolled. The initial enrollment results demonstrate the feasibility of this complex and demanding a prospective study.
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| 20. |
- Hagopian, William A, et al.
(författare)
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The Environmental Determinants of Diabetes in the Young (TEDDY): genetic criteria and international diabetes risk screening of 421 000 infants.
- 2011
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Ingår i: Pediatric Diabetes. - : Hindawi Limited. - 1399-543X. ; 12, s. 733-743
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Tidskriftsartikel (refereegranskat)abstract
- Hagopian WA, Erlich H, Lernmark Å, Rewers M, Ziegler AG, Simell O, Akolkar B, Vogt Jr R, Blair A, Ilonen J, Krischer J, She J, and the TEDDY Study Group. The Environmental Determinants of Diabetes in the Young (TEDDY): genetic criteria and international diabetes risk screening of 421 000 infants. Aims: The Environmental Determinants of Diabetes in the Young (TEDDY) study seeks to identify environmental factors influencing the development of type 1 diabetes (T1D) using intensive follow-up of children at elevated genetic risk. This study requires a cost-effective yet accurate screening strategy to identify the high-risk cohort. Methods: The TEDDY cohort was identified through newborn screening using human leukocyte antigen (HLA) class II genes based on criteria established with pre-TEDDY data. HLA typing was completed at six international centers using different genotyping methods that can achieve >98% accuracy. Results: TEDDY developed separate inclusion criteria for the general population (GP) and first-degree relatives (FDRs) of T1D patients. The FDR eligibility includes nine haplogenotypes (DR3/4, DR4/4, DR4/8, DR3/3, DR4/4b, DR4/1, DR4/13, DR4/9, and DR3/9) for broad HLA diversity, whereas the GP eligibility includes only the first four haplogenotypes with DRB1*0403 as an exclusion allele. TEDDY has screened 414 714 GP infants, of which 19 906 (4.8%) were eligible, whereas 1415 of the 6333 screened FDR infants (22.2%) were eligible. High-resolution confirmation testing of the eligible subjects indicated that the low-cost and low-resolution genotyping techniques employed at the screening centers yielded an accuracy of 99%. There were considerable variations in eligibility rates among the centers for GP (3.5-7.4%) and FDR (19-32%) subjects. The eligibility rates among US ethnic groups were 0.9, 1.3, 5.0, and 6.9% for Asians, Black, Caucasians, and Hispanics, respectively. Conclusions: Different low-cost and low-resolution genotyping methods are useful for the efficient and accurate identification of a high-risk cohort for follow-up based on the TEDDY HLA inclusion criteria (ClinicalTrials.gov NCT00279318).
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