The Influence of Pubertal Development on Autoantibody Appearance and Progression to Type 1 Diabetes in the TEDDY Study.

Context: The 2 peaks of type 1 diabetes incidence occur during early childhood and puberty. Objective: We sought to better understand the relationship between puberty, islet autoimmunity, and type 1 diabetes. Methods: The relationships between puberty, islet autoimmunity, and progression to type 1 diabetes were investigated prospectively in children followed in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Onset of puberty was determined by subject self-assessment of Tanner stages. Associations between speed of pubertal progression, pubertal growth, weight gain, homeostasis model assessment of insulin resistance (HOMA-IR), islet autoimmunity, and progression to type 1 diabetes were assessed. The influence of individual factors was analyzed using Cox proportional hazard ratios. Results: Out of 5677 children who were still in the study at age 8 years, 95% reported at least 1 Tanner Stage score and were included in the study. Children at puberty (Tanner Stage ≥2) had a lower risk (HR 0.65, 95% CI 0.45-0.93; P = .019) for incident autoimmunity than prepubertal children (Tanner Stage 1). An increase of body mass index Z-score was associated with a higher risk (HR 2.88, 95% CI 1.61-5.15; P < .001) of incident insulin autoantibodies. In children with multiple autoantibodies, neither HOMA-IR nor rate of progression to Tanner Stage 4 were associated with progression to type 1 diabetes. Conclusion: Rapid weight gain during puberty is associated with development of islet autoimmunity. Puberty itself had no significant influence on the appearance of autoantibodies or type 1 diabetes. Further studies are needed to better understand the underlying mechanisms.

Caesarean section and risk of type 1 diabetes.

AIMS/HYPOTHESIS: Delivery by Caesarean section continues to rise globally and has been associated with the risk of developing type 1 diabetes and the rate of progression from pre-symptomatic stage 1 or 2 type 1 diabetes to symptomatic stage 3 disease. The aim of this study was to examine the association between Caesarean delivery and progression to stage 3 type 1 diabetes in children with pre-symptomatic early-stage type 1 diabetes. METHODS: Caesarean section was examined in 8135 children from the TEDDY study who had an increased genetic risk for type 1 diabetes and were followed from birth for the development of islet autoantibodies and type 1 diabetes. RESULTS: The likelihood of delivery by Caesarean section was higher in children born to mothers with type 1 diabetes (adjusted OR 4.61, 95% CI 3.60, 5.90, p<0.0001), in non-singleton births (adjusted OR 4.35, 95% CI 3.21, 5.88, p<0.0001), in premature births (adjusted OR 1.91, 95% CI 1.53, 2.39, p<0.0001), in children born in the USA (adjusted OR 2.71, 95% CI 2.43, 3.02, p<0.0001) and in children born to older mothers (age group >28-33 years: adjusted OR 1.19, 95% CI 1.04, 1.35, p=0.01; age group >33 years: adjusted OR 1.80, 95% CI 1.58, 2.06, p<0.0001). Caesarean section was not associated with an increased risk of developing pre-symptomatic early-stage type 1 diabetes (risk by age 10 years 5.7% [95% CI 4.6%, 6.7%] for Caesarean delivery vs 6.6% [95% CI 6.0%, 7.3%] for vaginal delivery, p=0.07). Delivery by Caesarean section was associated with a modestly increased rate of progression to stage 3 type 1 diabetes in children who had developed multiple islet autoantibody-positive pre-symptomatic early-stage type 1 diabetes (adjusted HR 1.36, 95% CI 1.03, 1.79, p=0.02). No interaction was observed between Caesarean section and non-HLA SNPs conferring susceptibility for type 1 diabetes. CONCLUSIONS/INTERPRETATION: Caesarean section increased the rate of progression to stage 3 type 1 diabetes in children with pre-symptomatic early-stage type 1 diabetes. DATA AVAILABILITY: Data from the TEDDY study ( https://doi.org/10.58020/y3jk-x087 ) reported here will be made available for request at the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repository (NIDDK-CR) Resources for Research (R4R) ( https://repository.niddk.nih.gov/ ).

Childhood screening for type 1 diabetes comparing automated multiplex Antibody Detection by Agglutination-PCR (ADAP) with single plex islet autoantibody radiobinding assays.

BACKGROUND: Two or more autoantibodies against either insulin (IAA), glutamic acid decarboxylase (GADA), islet antigen-2 (IA-2A) or zinc transporter 8 (ZnT8A) denote stage 1 (normoglycemia) or stage 2 (dysglycemia) type 1 diabetes prior to stage 3 type 1 diabetes. Automated multiplex Antibody Detection by Agglutination-PCR (ADAP) assays in two laboratories were compared to single plex radiobinding assays (RBA) to define threshold levels for diagnostic specificity and sensitivity. METHODS: IAA, GADA, IA-2A and ZnT8A were analysed in 1504 (54% females) population based controls (PBC), 456 (55% females) doctor's office controls (DOC) and 535 (41% females) blood donor controls (BDC) as well as in 2300 (48% females) patients newly diagnosed (1-10 years of age) with stage 3 type 1 diabetes. The thresholds for autoantibody positivity were computed in 100 10-fold cross-validations to separate patients from controls either by maximizing the χ2-statistics (chisq) or using the 98th percentile of specificity (Spec98). Mean and 95% CI for threshold, sensitivity and specificity are presented. FINDINGS: The ADAP ROC curves of the four autoantibodies showed comparable AUC in the two ADAP laboratories and were higher than RBA. Detection of two or more autoantibodies using chisq showed 0.97 (0.95, 0.99) sensitivity and 0.94 (0.91, 0.97) specificity in ADAP compared to 0.90 (0.88, 0.95) sensitivity and 0.97 (0.94, 0.98) specificity in RBA. Using Spec98, ADAP showed 0.92 (0.89, 0.95) sensitivity and 0.99 (0.98, 1.00) specificity compared to 0.89 (0.77, 0.86) sensitivity and 1.00 (0.99, 1.00) specificity in the RBA. The diagnostic sensitivity and specificity were higher in PBC compared to DOC and BDC. INTERPRETATION: ADAP was comparable in two laboratories, both comparable to or better than RBA, to define threshold levels for two or more autoantibodies to stage type 1 diabetes. FUNDING: Supported by The Leona M. and Harry B. Helmsley Charitable Trust (grant number 2009-04078), the Swedish Foundation for Strategic Research (Dnr IRC15-0067) and the Swedish Research Council, Strategic Research Area (Dnr 2009-1039). AL was supported by the DiaUnion collaborative study, co-financed by EU Interreg ÖKS, Capital Region of Denmark, Region Skåne and the Novo Nordisk Foundation.

HLA Class II (DR, DQ, DP) Genes Were Separately Associated With the Progression From Seroconversion to Onset of Type 1 Diabetes Among Participants in Two Diabetes Prevention Trials (DPT-1 and TN07).

OBJECTIVE: To explore associations of HLA class II genes (HLAII) with the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: Next-generation targeted sequencing was used to genotype eight HLAII genes (DQA1, DQB1, DRB1, DRB3, DRB4, DRB5, DPA1, DPB1) in 1,216 participants from the Diabetes Prevention Trial-1 and Randomized Diabetes Prevention Trial with Oral Insulin sponsored by TrialNet. By the linkage disequilibrium, DQA1 and DQB1 are haplotyped to form DQ haplotypes; DP and DR haplotypes are similarly constructed. Together with available clinical covariables, we applied the Cox regression model to assess HLAII immunogenic associations with the disease progression. RESULTS: First, the current investigation updated the previously reported genetic associations of DQA1*03:01-DQB1*03:02 (hazard ratio [HR] = 1.25, P = 3.50*10-3) and DQA1*03:03-DQB1*03:01 (HR = 0.56, P = 1.16*10-3), and also uncovered a risk association with DQA1*05:01-DQB1*02:01 (HR = 1.19, P = 0.041). Second, after adjusting for DQ, DPA1*02:01-DPB1*11:01 and DPA1*01:03-DPB1*03:01 were found to have opposite associations with progression (HR = 1.98 and 0.70, P = 0.021 and 6.16*10-3, respectively). Third, DRB1*03:01-DRB3*01:01 and DRB1*03:01-DRB3*02:02, sharing the DRB1*03:01, had opposite associations (HR = 0.73 and 1.44, P = 0.04 and 0.019, respectively), indicating a role of DRB3. Meanwhile, DRB1*12:01-DRB3*02:02 and DRB1*01:03 alone were found to associate with progression (HR = 2.6 and 2.32, P = 0.018 and 0.039, respectively). Fourth, through enumerating all heterodimers, it was found that both DQ and DP could exhibit associations with disease progression. CONCLUSIONS: These results suggest that HLAII polymorphisms influence progression from islet autoimmunity to T1D among at-risk subjects with islet autoantibodies.

Intake of B vitamins and the risk of developing islet autoimmunity and type 1 diabetes in the TEDDY study.

PURPOSE: The aim was to study the association between dietary intake of B vitamins in childhood and the risk of islet autoimmunity (IA) and progression to type 1 diabetes (T1D) by the age of 10 years. METHODS: We followed 8500 T1D-susceptible children born in the U.S., Finland, Sweden, and Germany in 2004 -2010 from the Environmental Determinants of Diabetes in the Young (TEDDY) study, which is a prospective observational birth cohort. Dietary intake of seven B vitamins was calculated from foods and dietary supplements based on 24-h recall at 3 months and 3-day food records collected regularly from 6 months to 10 years of age. Cox proportional hazard models were adjusted for energy, HLA-genotype, first-degree relative with T1D, sex, and country. RESULTS: A total of 778 (9.2) children developed at least one autoantibody (any IA), and 335 (3.9%) developed multiple autoantibodies. 280 (3.3%) children had IAA and 319 (3.8%) GADA as the first autoantibody. 344 (44%) children with IA progressed to T1D. We observed that higher intake of niacin was associated with a decreased risk of developing multiple autoantibodies (HR 0.95; 95% CI 0.92, 0.98) per 1 mg/1000 kcal in niacin intake. Higher intake of pyridoxine (HR 0.66; 95% CI 0.46, 0.96) and vitamin B12 (HR 0.87; 95% CI 0.77, 0.97) was associated with a decreased risk of IAA-first autoimmunity. Higher intake of riboflavin (HR 1.38; 95% CI 1.05, 1.80) was associated with an increased risk of GADA-first autoimmunity. There were no associations between any of the B vitamins and the outcomes "any IA" and progression from IA to T1D.  CONCLUSION: In this multinational, prospective birth cohort of children with genetic susceptibility to T1D, we observed some direct and inverse associations between different B vitamins and risk of IA.

Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data.

The type 1 diabetes community is coalescing around the benefits and advantages of early screening for disease risk. To be accepted by healthcare providers, regulatory authorities and payers, screening programmes need to show that the testing variables allow accurate risk prediction and that individualised risk-informed monitoring plans are established, as well as operational feasibility, cost-effectiveness and acceptance at population level. Artificial intelligence (AI) has the potential to contribute to solving these issues, starting with the identification and stratification of at-risk individuals. ASSET (AI for Sustainable Prevention of Autoimmunity in the Society; www.asset.healthcare ) is a public/private consortium that was established to contribute to research around screening for type 1 diabetes and particularly to how AI can drive the implementation of a precision medicine approach to disease prevention. ASSET will additionally focus on issues pertaining to operational implementation of screening. The authors of this article, researchers and clinicians active in the field of type 1 diabetes, met in an open forum to independently debate key issues around screening for type 1 diabetes and to advise ASSET. The potential use of AI in the analysis of longitudinal data from observational cohort studies to inform the design of improved, more individualised screening programmes was also discussed. A key issue was whether AI would allow the research community and industry to capitalise on large publicly available data repositories to design screening programmes that allow the early detection of individuals at high risk and enable clinical evaluation of preventive therapies. Overall, AI has the potential to revolutionise type 1 diabetes screening, in particular to help identify individuals who are at increased risk of disease and aid in the design of appropriate follow-up plans. We hope that this initiative will stimulate further research on this very timely topic.

Distinct transcriptomic profiles in children prior to the appearance of type 1 diabetes-linked islet autoantibodies and following enterovirus infection.

Although the genetic basis and pathogenesis of type 1 diabetes have been studied extensively, how host responses to environmental factors might contribute to autoantibody development remains largely unknown. Here, we use longitudinal blood transcriptome sequencing data to characterize host responses in children within 12 months prior to the appearance of type 1 diabetes-linked islet autoantibodies, as well as matched control children. We report that children who present with insulin-specific autoantibodies first have distinct transcriptional profiles from those who develop GADA autoantibodies first. In particular, gene dosage-driven expression of GSTM1 is associated with GADA autoantibody positivity. Moreover, compared with controls, we observe increased monocyte and decreased B cell proportions 9-12 months prior to autoantibody positivity, especially in children who developed antibodies against insulin first. Lastly, we show that control children present transcriptional signatures consistent with robust immune responses to enterovirus infection, whereas children who later developed islet autoimmunity do not. These findings highlight distinct immune-related transcriptomic differences between case and control children prior to case progression to islet autoimmunity and uncover deficient antiviral response in children who later develop islet autoimmunity.

HLA Genotype and Probiotics Modify the Association Between Timing of Solid Food Introduction and Islet Autoimmunity in the TEDDY Study.

OBJECTIVE: To study the interaction among HLA genotype, early probiotic exposure, and timing of complementary foods in relation to risk of islet autoimmunity (IA). RESEARCH DESIGN AND METHODS: The Environmental Determinants of Diabetes in the Young (TEDDY) study prospectively follows 8,676 children with increased genetic risk of type 1 diabetes. We used a Cox proportional hazards regression model adjusting for potential confounders to study early feeding and the risk of IA in a sample of 7,770 children. RESULTS: Any solid food introduced early (<6 months) was associated with increased risk of IA if the child had the HLA DR3/4 genotype and no probiotic exposure during the 1st year of life. Rice introduced at 4-5.9 months compared with later in the U.S. was associated with an increased risk of IA. CONCLUSIONS: Timing of solid food introduction, including rice, may be associated with IA in children with the HLA DR3/4 genotype not exposed to probiotics. The microbiome composition under these exposure combinations requires further study.

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 appearance 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. Norwalk virus was identified as one possible candidate factor. GIEs reported during the 2nd year of life were associated with a decreased IAA risk.

Executive Summary: Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus.

BACKGROUND: Numerous laboratory tests are used in the diagnosis and management of patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially. An expert committee compiled evidence-based recommendations for laboratory analysis in patients with diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments in the full version of the guideline). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association of Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association. CONTENT: Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (Hb A1c) in the blood. Glycemic control is monitored by the patients measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring devices and also by laboratory analysis of Hb A1c. The potential roles of noninvasive glucose monitoring; genetic testing; and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed. SUMMARY: The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

Executive Summary: Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus.

BACKGROUND: Numerous laboratory tests are used in the diagnosis and management of patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially. An expert committee compiled evidence-based recommendations for laboratory analysis in patients with diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments in the full version of the guideline). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association for Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association. CONTENT: Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (HbA1c) in the blood. Glycemic control is monitored by the patients measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring devices and also by laboratory analysis of HbA1c. The potential roles of noninvasive glucose monitoring; genetic testing; and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed. SUMMARY: The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus.

BACKGROUND: Numerous laboratory tests are used in the diagnosis and management of diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially. APPROACH: An expert committee compiled evidence-based recommendations for laboratory analysis in screening, diagnosis, or monitoring of diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association for Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association. CONTENT: Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (HbA1c) in the blood. Glycemic control is monitored by the people with diabetes measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring (CGM) devices and also by laboratory analysis of HbA1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed. SUMMARY: The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus.

BACKGROUND: Numerous laboratory tests are used in the diagnosis and management of diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially. APPROACH: An expert committee compiled evidence-based recommendations for laboratory analysis in screening, diagnosis, or monitoring of diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association of Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association. CONTENT: Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (Hb A1c) in the blood. Glycemic control is monitored by the people with diabetes measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring (CGM) devices and also by laboratory analysis of Hb A1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed. SUMMARY: The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

Plasma protein biomarkers predict the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity.

Type 1 diabetes (T1D) results from autoimmune destruction of ß cells. Insufficient availability of biomarkers represents a significant gap in understanding the disease cause and progression. We conduct blinded, two-phase case-control plasma proteomics on the TEDDY study to identify biomarkers predictive of T1D development. Untargeted proteomics of 2,252 samples from 184 individuals identify 376 regulated proteins, showing alteration of complement, inflammatory signaling, and metabolic proteins even prior to autoimmunity onset. Extracellular matrix and antigen presentation proteins are differentially regulated in individuals who progress to T1D vs. those that remain in autoimmunity. Targeted proteomics measurements of 167 proteins in 6,426 samples from 990 individuals validate 83 biomarkers. A machine learning analysis predicts if individuals would remain in autoimmunity or develop T1D 6 months before autoantibody appearance, with areas under receiver operating characteristic curves of 0.871 and 0.918, respectively. Our study identifies and validates biomarkers, highlighting pathways affected during T1D development.

Possible heterogeneity of initial pancreatic islet beta-cell autoimmunity heralding type 1 diabetes.

The etiology of type 1 diabetes (T1D) foreshadows the pancreatic islet beta-cell autoimmune pathogenesis that heralds the clinical onset of T1D. Standardized and harmonized tests of autoantibodies against insulin (IAA), glutamic acid decarboxylase (GADA), islet antigen-2 (IA-2A), and ZnT8 transporter (ZnT8A) allowed children to be followed from birth until the appearance of a first islet autoantibody. In the Environmental Determinants of Diabetes in the Young (TEDDY) study, a multicenter (Finland, Germany, Sweden, and the United States) observational study, children were identified at birth for the T1D high-risk HLA haploid genotypes DQ2/DQ8, DQ2/DQ2, DQ8/DQ8, and DQ4/DQ8. The TEDDY study was preceded by smaller studies in Finland, Germany, Colorado, Washington, and Sweden. The aims were to follow children at increased genetic risk to identify environmental factors that trigger the first-appearing autoantibody (etiology) and progress to T1D (pathogenesis). The larger TEDDY study found that the incidence rate of the first-appearing autoantibody was split into two patterns. IAA first peaked already during the first year of life and tapered off by 3-4 years of age. GADA first appeared by 2-3 years of age to reach a plateau by about 4 years. Prior to the first-appearing autoantibody, genetic variants were either common or unique to either pattern. A split was also observed in whole blood transcriptomics, metabolomics, dietary factors, and exposures such as gestational life events and early infections associated with prolonged shedding of virus. An innate immune reaction prior to the adaptive response cannot be excluded. Clarifying the mechanisms by which autoimmunity is triggered to either insulin or GAD65 is key to uncovering the etiology of autoimmune T1D.

Physical Activity and the Development of Islet Autoimmunity and Type 1 Diabetes in 5- to 15-Year-Old Children Followed in the TEDDY Study.

OBJECTIVE: This study investigated physical activity and its association with the development of islet autoimmunity and type 1 diabetes in genetically at-risk children aged 5-15 years. RESEARCH DESIGN AND METHODS: As part of the longitudinal Environmental Determinants of Diabetes in the Young (TEDDY) study, annual assessment of activity using accelerometry was conducted from age 5 years. Time-to-event analyses using Cox proportional hazard models were used to assess the association between time spent in moderate to vigorous physical activity per day and the appearance of one or several autoantibodies and progression to type 1 diabetes in three risk groups: 1) 3,869 islet autoantibody (IA)-negative children, of whom 157 became single IA positive; 2) 302 single IA-positive children, of whom 73 became multiple IA positive; and 3) 294 multiple IA-positive children, of whom 148 developed type 1 diabetes. RESULTS: No significant association was found in risk group 1 or risk group 2. A significant association was seen in risk group 3 (hazard ratio 0.920 [95% CI 0.856, 0.988] per 10-min increase; P = 0.021), particularly when glutamate decarboxylase autoantibody was the first autoantibody (hazard ratio 0.883 [95% CI 0.783, 0.996] per 10-min increase; P = 0.043). CONCLUSIONS: More daily minutes spent in moderate to vigorous physical activity was associated with a reduced risk of progression to type 1 diabetes in children aged 5-15 years who had developed multiple IAs.

Interaction Between Dietary Iron Intake and Genetically Determined Iron Overload: Risk of Islet Autoimmunity and Progression to Type 1 Diabetes in the TEDDY Study.

OBJECTIVE: To examine whether iron intake and genetically determined iron overload interact in predisposing to the development of childhood islet autoimmunity (IA) and type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: In The Environmental Determinants of Diabetes in the Young (TEDDY) study, 7,770 genetically high-risk children were followed from birth until the development of IA and progression to T1D. Exposures included energy-adjusted iron intake in the first 3 years of life and a genetic risk score (GRS) for increased circulating iron. RESULTS: We found a U-shaped association between iron intake and risk of GAD antibody as the first autoantibody. In children with GRS ≥2 iron risk alleles, high iron intake was associated with an increased risk of IA, with insulin as first autoantibody (adjusted hazard ratio 1.71 [95% CI 1.14; 2.58]) compared with moderate iron intake. CONCLUSIONS: Iron intake may alter the risk of IA in children with high-risk HLA haplogenotypes.

Islet Autoantibody Levels Differentiate Progression Trajectories in Individuals With Presymptomatic Type 1 Diabetes.

In our previous data-driven analysis of evolving patterns of islet autoantibodies (IAb) against insulin (IAA), GAD (GADA), and islet antigen 2 (IA-2A), we discovered three trajectories, characterized according to multiple IAb (TR1), IAA (TR2), or GADA (TR3) as the first appearing autoantibodies. Here we examined the evolution of IAb levels within these trajectories in 2,145 IAb-positive participants followed from early life and compared those who progressed to type 1 diabetes (n = 643) with those remaining undiagnosed (n = 1,502). With use of thresholds determined by 5-year diabetes risk, four levels were defined for each IAb and overlaid onto each visit. In diagnosed participants, high IAA levels were seen in TR1 and TR2 at ages <3 years, whereas IAA remained at lower levels in the undiagnosed. Proportions of dwell times (total duration of follow-up at a given level) at the four IAb levels differed between the diagnosed and undiagnosed for GADA and IA-2A in all three trajectories (P < 0.001), but for IAA dwell times differed only within TR2 (P < 0.05). Overall, undiagnosed participants more frequently had low IAb levels and later appearance of IAb than diagnosed participants. In conclusion, while it has long been appreciated that the number of autoantibodies is an important predictor of type 1 diabetes, consideration of autoantibody levels within the three autoimmune trajectories improved differentiation of IAb-positive children who progressed to type 1 diabetes from those who did not.

Predictors of the Initiation of Islet Autoimmunity and Progression to Multiple Autoantibodies and Clinical Diabetes: The TEDDY Study.

OBJECTIVE: To distinguish among predictors of seroconversion, progression to multiple autoantibodies and from multiple autoantibodies to type 1 diabetes in young children. RESEARCH DESIGN AND METHODS: Genetically high-risk newborns (n = 8,502) were followed for a median of 11.2 years (interquartile range 9.3-12.6); 835 (9.8%) developed islet autoantibodies and 283 (3.3%) were diagnosed with type 1 diabetes. Predictors were examined using Cox proportional hazards models. RESULTS: Predictors of seroconversion and progression differed, depending on the type of first appearing autoantibody. Male sex, Finnish residence, having a sibling with type 1 diabetes, the HLA DR4 allele, probiotic use before age 28 days, and single nucleotide polymorphism (SNP) rs689_A (INS) predicted seroconversion to IAA-first (having islet autoantibody to insulin as the first appearing autoantibody). Increased weight at 12 months and SNPs rs12708716_G (CLEC16A) and rs2292239_T (ERBB3) predicted GADA-first (autoantibody to GAD as the first appearing). For those having a father with type 1 diabetes, the SNPs rs2476601_A (PTPN22) and rs3184504_T (SH2B3) predicted both. Younger age at seroconversion predicted progression from single to multiple autoantibodies as well as progression to diabetes, except for those presenting with GADA-first. Family history of type 1 diabetes and the HLA DR4 allele predicted progression to multiple autoantibodies but not diabetes. Sex did not predict progression to multiple autoantibodies, but males progressed more slowly than females from multiple autoantibodies to diabetes. SKAP2 and MIR3681HG SNPs are newly reported to be significantly associated with progression from multiple autoantibodies to type 1 diabetes. CONCLUSIONS: Predictors of IAA-first versus GADA-first autoimmunity differ from each other and from the predictors of progression to diabetes.