CGM Metrics Predict Imminent Progression to Type 1 Diabetes: Autoimmunity Screening for Kids (ASK) Study

OBJECTIVE

Children identified with stage 1 type 1 diabetes are at high risk for progressing to stage 3 (clinical) diabetes and require accurate monitoring. Our aim was to establish continuous glucose monitoring (CGM) metrics that could predict imminent progression to diabetes.

RESEARCH DESIGN AND METHODS

In the Autoimmunity Screening for Kids study, 91 children who were persistently islet autoantibody positive (median age 11.5 years; 48% non-Hispanic White; 57% female) with a baseline CGM were followed for development of diabetes for a median of 6 (range 0.2-34) months. Of these, 16 (18%) progressed to clinical diabetes in a median of 4.5 (range 0.4-29) months.

RESULTS

Compared with children who did not progress to clinical diabetes (nonprogressors), those who did (progressors) had significantly higher average sensor glucose levels (119 vs. 105 mg/dL, P < 0.001) and increased glycemic variability (SD 27 vs. 16, coefficient of variation, 21 vs. 15, mean of daily differences 24 vs. 16, and mean amplitude of glycemic excursions 43 vs. 26, all P < 0.001). For progressors, 21% of the time was spent with glucose levels >140 mg/dL (TA140) and 8% of time >160 mg/dL, compared with 3% and 1%, respectively, for nonprogressors. In survival analyses, the risk of progression to diabetes in 1 year was 80% in those with TA140 >10%; in contrast, it was only 5% in the other participants. Performance of prediction by receiver operating curve analyses showed area under the curve of ≥0.89 for both individual and combined CGM metric models.

CONCLUSIONS

TA140 >10% is associated with a high risk of progression to clinical diabetes within the next year in autoantibody-positive children. CGM should be included in the ongoing monitoring of high-risk children and could be used as potential entry criterion for prevention trials.

Characteristics of children diagnosed with type 1 diabetes before vs after 6 years of age in the TEDDY cohort study

AIMS/HYPOTHESIS

Prognostic factors and characteristics of children diagnosed with type 1 diabetes before 6 years of age were compared with those diagnosed at 6-13 years of age in the TEDDY study.

METHODS

Genetically high-risk children (n = 8502) were followed from birth for a median of 9.9 years; 328 (3.9%) were diagnosed with type 1 diabetes. Cox proportional hazard model was used to assess the association of prognostic factors with the risk of type 1 diabetes in the two age groups.

RESULTS

Children in the younger group tended to develop autoantibodies earlier than those in the older group did (mean age 1.5 vs 3.5 years), especially insulin autoantibodies (IAA), which developed earlier than GAD autoantibodies (GADA). Children in the younger group also progressed to diabetes more rapidly than the children in the older group did (mean duration 1.9 vs 5.4 years). Children with autoantibodies first appearing against insulinoma antigen-2 (IA-2A) were found only in the older group. The significant diabetes risk associated with the country of origin in the younger group was no longer significant in the older group. Conversely, the diabetes risk associated with HLA genotypes was statistically significant also in the older group. Initial seroconversion after and before 2 years of age was associated with decreased risk for diabetes diagnosis in children positive for multiple autoantibodies, but the diabetes risk did not decrease further with increasing age if initial seroconversion occurred after age 2. Diabetes risk associated with the minor alleles of rs1004446 (INS) was decreased in both the younger and older groups compared with other genotypes (HR 0.67). Diabetes risk was significantly increased with the minor alleles of rs2476601 (PTPN22) (HR 2.04 and 1.72), rs428595 (PPIL2) (HR 2.13 and 2.10), rs113306148 (PLEKHA1) (HR 2.34 and 2.21) and rs73043122 (RNASET2) (HR 2.31 and 2.54) (HR values represent the younger and older groups, respectively).

CONCLUSIONS/INTERPRETATIONS

Diabetes at an early age is likely to be preceded by IAA autoantibodies and is a more aggressive form of the disease. Among older children, once multiple autoantibodies have been observed there does not seem to be any association between progression to diabetes and the age of the child or family history.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT00279318.

25(OH)D Levels in Infancy Is Associated With Celiac Disease Autoimmunity in At-Risk Children: A Case-Control Study

Objectives: An observed variation in the risk of celiac disease, according to the season of birth, suggests that vitamin D may affect the development of the disease. The aim of this study was to investigate if vitamin D concentration is associated with the risk of celiac disease autoimmunity (CDA) in genetically at-risk children. Study Design: Children prospectively followed in the multinational The Environmental Determinants of Diabetes in the Young study, conducted at six centers in Europe and the US, were selected for a 1-to-3 nested case-control study. In total, 281 case-control sets were identified. CDA was defined as positivity for tissue transglutaminase autoantibodies (tTGA) on two or more consecutive visits. Vitamin D was measured as 25-hydroxyvitamin D [25(OH)D] concentrations in all plasma samples prior to, and including, the first tTGA positive visit. Conditional logistic regression was used to examine the association between 25(OH)D and risk of CDA. Results: No significant association was seen between 25(OH)D concentrations (per 5 nmol/L increase) and risk for CDA development during early infancy (odds ratio [OR] 0.99, 95% confidence interval [CI] 0.95-1.04) or childhood (OR 1.02, 95% CI 0.97-1.07). When categorizing 25(OH)D concentrations, there was an increased risk of CDA with 25(OH)D concentrations <30 nmol/L (OR 2.23, 95% CI 1.29, 3.84) and >75 nmol/L (OR 2.10, 95% CI 1.28-3.44) in early infancy, as compared with 50-75 nmol/L. Conclusion: This study indicates that 25(OH)D concentrations <30 nmol/L and >75 nmol/L during early infancy were associated with an increased risk of developing CDA in genetically at-risk children. The non-linear relationship raises the need for more studies on the possible role of 25(OH)D in the relation to celiac disease onset.

Prevalence of SARS-CoV-2 Antibodies in Children and Adults with Type 1 Diabetes

Objective: As diabetes is a risk factor for severe symptoms, hospitalization, and death with COVID-19 disease, we aimed to assess the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in children and adults with and without type 1 diabetes in Colorado during 2020. Research Design and Methods: We developed a highly sensitive and specific test for antibodies against SARS-CoV-2 and measured the antibodies in children and adults with new-onset (n = 129) and established type 1 diabetes (n = 94) seen for routine diabetes care at our center between January and October 2020. The antibodies were also measured in 562 children and 102 adults from the general population of Colorado. Results: The prevalence of SARS-CoV-2 antibodies in persons with new-onset type 1 diabetes (0.8%; 95% confidence interval 0.1%-4.2%) or those with established disease (4.3%; 1.7%-10.4%) did not differ from that in the general population children (2.8%; 1.8%-4.6%) or adults (3.9%; 1.5%-9.7%). In a subset of individuals with positive antibodies (n = 31), antibodies remained positive for up to 9 months, although the levels decreased starting 3 months after the infection (P = 0.007). Conclusions: From January to October 2020, the prevalence of SARS-CoV-2 antibodies were not different in children and adults with and without type 1 diabetes in Colorado. We found no evidence for increased prevalence of COVID-19 infections among youth with newly diagnosed type 1 diabetes. (COMIRB Protocol 20-1007).

Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes

We report the largest and most diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 78 genome-wide-significant (P < 5 × 10-8) regions, including 36 that are new. We define credible sets of T1D-associated variants and show that they are enriched in immune-cell accessible chromatin, particularly CD4+ effector T cells. Using chromatin-accessibility profiling of CD4+ T cells from 115 individuals, we map chromatin-accessibility quantitative trait loci and identify five regions where T1D risk variants co-localize with chromatin-accessibility quantitative trait loci. We highlight rs72928038 in BACH2 as a candidate causal T1D variant leading to decreased enhancer accessibility and BACH2 expression in T cells. Finally, we prioritize potential drug targets by integrating genetic evidence, functional genomic maps and immune protein-protein interactions, identifying 12 genes implicated in T1D that have been targeted in clinical trials for autoimmune diseases. These findings provide an expanded genomic landscape for T1D.

Associations of breastfeeding with childhood autoimmunity, allergies, and overweight: The Environmental Determinants of Diabetes in the Young (TEDDY) study

BACKGROUND

Breastfeeding has beneficial effects on numerous health outcomes.

OBJECTIVES

We investigated whether breastfeeding duration is associated with the development of early childhood autoimmunity, allergies, or obesity in a multinational prospective birth cohort.

METHODS

Infants with genetic susceptibility for type 1 diabetes (n = 8676) were followed for the development of autoantibodies to islet autoantigens or transglutaminase, allergies, and for anthropometric measurements to a median age of 8.3 y (IQR: 2.8-10.2 y). Information on breastfeeding was collected at 3 mo of age and prospectively thereafter. A propensity score for longer breastfeeding was calculated from the variables that were likely to influence any or exclusive breastfeeding. The risks of developing autoimmunity or allergy were assessed using Cox proportional hazards models, and the risk of obesity at 5.5 y of age was assessed using logistic regression with adjustment by the propensity score.

RESULTS

Breastfeeding duration was not associated with a lower risk of either islet or transglutaminase autoimmunity (any breastfeeding >6 mo, adjusted HR: 1.07; 95% CI: 0.96, 1.19; exclusive breastfeeding >3 mo, adjusted HR: 1.03; 95% CI: 0.92, 1.15). Exclusive breastfeeding >3 mo was associated with a decreased risk of seasonal allergic rhinitis (adjusted HR: 0.70; 95% CI: 0.53, 0.92; P < 0.01). Any breastfeeding >6 mo and exclusive breastfeeding >3 mo were associated with decreased risk of obesity (adjusted OR: 0.62; 95% CI: 0.47, 0.81; P < 0.001; and adjusted OR: 0.68; 95% CI: 0.47, 0.95; P < 0.05, respectively).

CONCLUSIONS

Longer breastfeeding was not associated with a lower risk of childhood (islet or transglutaminase) autoimmunity in genetically at-risk children but was associated with decreased risk of seasonal allergic rhinitis and obesity at 5.5 y of age.

Transcriptional networks in at-risk individuals identify signatures of type 1 diabetes progression

Type 1 diabetes (T1D) is a disease of insulin deficiency that results from autoimmune destruction of pancreatic islet β cells. The exact cause of T1D remains unknown, although asymptomatic islet autoimmunity lasting from weeks to years before diagnosis raises the possibility of intervention before the onset of clinical disease. The number, type, and titer of islet autoantibodies are associated with long-term disease risk but do not cause disease, and robust early predictors of individual progression to T1D onset remain elusive. The Environmental Determinants of Diabetes in the Young (TEDDY) consortium is a prospective cohort study aiming to determine genetic and environmental interactions causing T1D. Here, we analyzed longitudinal blood transcriptomes of 2013 samples from 400 individuals in the TEDDY study before both T1D and islet autoimmunity. We identified and interpreted age-associated gene expression changes in healthy infancy and age-independent changes tracking with progression to both T1D and islet autoimmunity, beginning before other evidence of islet autoimmunity was present. We combined multivariate longitudinal data in a Bayesian joint model to predict individual risk of T1D onset and validated the association of a natural killer cell signature with progression and the model's predictive performance on an additional 356 samples from 56 individuals in the independent Type 1 Diabetes Prediction and Prevention study. Together, our results indicate that T1D is characterized by early and longitudinal changes in gene expression, informing the immunopathology of disease progression and facilitating prediction of its course.

Factors Associated With the Decline of C-Peptide in a Cohort of Young Children Diagnosed With Type 1 Diabetes

CONTEXT

Understanding factors involved in the rate of C-peptide decline is needed to tailor therapies for type 1 diabetes (T1D).

OBJECTIVE

Evaluate factors associated with rate of C-peptide decline after a T1D diagnosis in young children.

DESIGN

Observational study.

SETTING

Academic centers.

PARTICIPANTS

A total of 57 participants from the Environmental Determinants of Diabetes in the Young (TEDDY) study who were enrolled at 3 months of age and followed until T1D, and 56 age-matched children diagnosed with T1D in the community.

INTERVENTION

A mixed meal tolerance test was used to measure the area under the curve (AUC) C-peptide at 1, 3, 6, 12, and 24 months postdiagnosis.

OUTCOME

Factors associated with rate of C-peptide decline during the first 2 years postdiagnosis were evaluated using mixed effects models, adjusting for age at diagnosis and baseline C-peptide.

RESULTS

Adjusted slopes of AUC C-peptide decline did not differ between TEDDY subjects and community controls (P = 0.21), although the former had higher C-peptide baseline levels. In univariate analyses combining both groups (n = 113), younger age, higher weight and body mass index z-scores, female sex, an increased number increased number of islet autoantibodies, and IA-2A or ZnT8A positivity at baseline were associated with a higher rate of C-peptide loss. Younger age, female sex, and higher weight z-score remained significant in multivariate analysis (all P < 0.02). At 3 months after diagnosis, higher HbA1c became an additional independent factor associated with a higher rate of C-peptide decline (P < 0.01).

CONCLUSION

Younger age at diagnosis, female sex, higher weight z-score, and HbA1c were associated with a higher rate of C-peptide decline after T1D diagnosis in young children.

An Age-Related Exponential Decline in the Risk of Multiple Islet Autoantibody Seroconversion During Childhood

OBJECTIVE

Islet autoimmunity develops before clinical type 1 diabetes and includes multiple and single autoantibody phenotypes. The objective was to determine age-related risks of islet autoantibodies that reflect etiology and improve screening for presymptomatic type 1 diabetes.

RESEARCH DESIGN AND METHODS

The Environmental Determinants of Diabetes in the Young study prospectively monitored 8,556 genetically at-risk children at 3- to 6-month intervals from birth for the development of islet autoantibodies and type 1 diabetes. The age-related change in the risk of developing islet autoantibodies was determined using landmark and regression models.

RESULTS

The 5-year risk of developing multiple islet autoantibodies was 4.3% (95% CI 3.8-4.7) at 7.5 months of age and declined to 1.1% (95% CI 0.8-1.3) at a landmark age of 6.25 years (P < 0.0001). Risk decline was slight or absent in single insulin and GAD autoantibody phenotypes. The influence of sex, HLA, and other susceptibility genes on risk subsided with increasing age and was abrogated by age 6 years. Highest sensitivity and positive predictive value of multiple islet autoantibody phenotypes for type 1 diabetes was achieved by autoantibody screening at 2 years and again at 5-7 years of age.

CONCLUSIONS

The risk of developing islet autoimmunity declines exponentially with age, and the influence of major genetic factors on this risk is limited to the first few years of life.

Prediction of the development of islet autoantibodies through integration of environmental, genetic, and metabolic markers

BACKGROUND

The Environmental Determinants of the Diabetes in the Young (TEDDY) study has prospectively followed, from birth, children at increased genetic risk of type 1 diabetes. TEDDY has collected heterogenous data longitudinally to gain insights into the environmental and biological mechanisms driving the progression to persistent islet autoantibodies.

METHODS

We developed a machine learning model to predict imminent transition to the development of persistent islet autoantibodies based on time-varying metabolomics data integrated with time-invariant risk factors (eg, gestational age). The machine learning was initiated with 221 potential features (85 genetic, 5 environmental, 131 metabolomic) and an ensemble-based feature evaluation was utilized to identify a small set of predictive features that can be interrogated to better understand the pathogenesis leading up to persistent islet autoimmunity.

RESULTS

The final integrative machine learning model included 42 disparate features, returning a cross-validated receiver operating characteristic area under the curve (AUC) of 0.74 and an AUC of ~0.65 on an independent validation dataset. The model identified a principal set of 20 time-invariant markers, including 18 genetic markers (16 single nucleotide polymorphisms [SNPs] and two HLA-DR genotypes) and two demographic markers (gestational age and exposure to a prebiotic formula). Integration with the metabolome identified 22 supplemental metabolites and lipids, including adipic acid and ceramide d42:0, that predicted development of islet autoantibodies.

CONCLUSIONS

The majority (86%) of metabolites that predicted development of islet autoantibodies belonged to three pathways: lipid oxidation, phospholipase A2 signaling, and pentose phosphate, suggesting that these metabolic processes may play a role in triggering islet autoimmunity.

Parent and Pediatrician Preferences for Type 1 Diabetes Screening in the U.S

OBJECTIVE

The purpose of this study was to use a discrete-choice experiment methodology to understand the relative importance of the attributes of screening tests for type 1 diabetes among parents and pediatricians in the U.S.

RESEARCH DESIGN AND METHODS

Online surveys presented hypothetical screening test profiles from which respondents chose their preferred test profile. Survey attributes were based on likely screening test options and included the mode of administration, where and when the test was conducted, the type of education and monitoring available to lower the risk of diabetic ketoacidosis (DKA), and whether a treatment was available that would delay onset of insulin dependence. Data were analyzed using random-parameters logit models.

RESULTS

Parents placed the highest relative importance on monitoring programs that could reduce the risk of DKA to 1%, followed by treatment to delay onset of insulin dependence by 1 or 2 years, and, finally, avoiding a $50 out-of-pocket cost. Pediatricians placed equal importance on monitoring programs that reduced a patient's risk of DKA to 1% and on avoiding a $50 out-of-pocket cost for the screening test, followed by the option of a treatment to delay the onset of insulin dependence. The mode of administration and location and timing of the screening were much less important to parents and pediatricians.

CONCLUSIONS

Parents and pediatricians preferred screening tests that were accompanied by education and monitoring plans to reduce the risk of DKA, had available treatment to delay type 1 diabetes, and had lower out-of-pocket costs.

Childhood growth prior to screen-detected celiac disease: prospective follow-up of an at-risk birth cohort

OBJECTIVES

To determine the association between childhood growth prior to the development of celiac disease (CD) and CD autoimmunity (CDA) identified by periodic serological screening.

STUDY DESIGN

The Diabetes Autoimmunity Study in the Young cohort includes 1979 genetically at-risk children from Denver, Colorado, with annual growth measurements from age nine months until ten years. Between 1993 and February 2019, 120 children developed CDA defined by persistent positive tissue transglutaminase autoantibodies (TGA); among these, 71 met our criteria for CD based on histopathological findings or high TGA levels. Age- and sex-specific z-scores of weight, body mass index (BMI), and height prior to seroconversion were derived using US reference charts as standards. Joint modeling of serial growth measurements was used to estimate adjusted hazard ratios (aHRs) accounting for celiac-associated human leukocyte antigens, early-life feeding practices, and socio-demographics.

RESULTS

In the first 10 years of life, there were no significant associations between the child's current weight, BMI and height and the risk of screening-detected CDA or CD, neither was the weight nor BMI velocity associated with CDA or CD as identified by screening (all aHRs approximated 1). Increased height velocity was associated with later CD, but not CDA, development (aHR per 0.01-z score/year, 1.28; 95% confidence interval [CI] 1.18-1.38 and 1.03; 0.97-1.09, respectively).

CONCLUSIONS

In the first 10 years of life, from prospectively collected serial growth measurements, we found no evidence of impaired childhood growth before CD and CDA development as identified through early and periodic screening.

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

Type 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.

Detection of T cells Reactive to Hybrid Insulin Peptides in Subjects at Risk for Type 1 Diabetes

Our lab recently established that Hybrid Insulin Peptides (HIPs) are antigenic ligands for diabetogenic T cell clones in the NOD mouse model of autoimmune diabetes. Importantly, we have found that the phenotype of HIP-reactive T cells present in the peripheral blood of NOD mice is indicative of ongoing autoimmunity in the pancreas. In the human setting, we demonstrated that T cells reactive to HIPs are present in the residual islets of type 1 diabetic (T1D) organ donors and more recently, in PBMC from T1D patients. Using an IFN-g ELISPOT assay to test T cell reactivity in the peripheral blood of T1D patients or control subjects to a panel of 16 HIPs, we demonstrated that 70% of the responding patients showed reactivity to multiple HIPs. To determine whether the presence of HIP-reactive T cells might serve as a biomarker of disease activity in humans, we are following longitudinally a cohort of subjects positive for multiple islet autoantibodies (Ab+), individuals that are at high risk for developing T1D. Using IFN-g ELISPOT and CFSE dilution assays, our data indicate that HIP-reactive T cells with an inflammatory phenotype can be detected before disease onset. In one Ab+ individual that showed HIP reactivity, we used single-cell RNA sequencing to study the phenotype and TCR usage of HIP-responding T cells. We observed that T cells with a regulatory phenotype (FoxP3+, CTLA-4+, LAG3+) can be observed when a proliferative (but not inflammatory) response is detected. In this ongoing study, we are reporting for the first time that HIP-reactive T cells can be observed in the peripheral blood of subjects at risk for T1D, suggesting that the balance of inflammatory vs. regulatory signals of HIP-reactive T cells could be potential indicators of disease activity.

Progression from islet autoimmunity to clinical type 1 diabetes is influenced by genetic factors: results from the prospective TEDDY study

BACKGROUND

Progression time from islet autoimmunity to clinical type 1 diabetes is highly variable and the extent that genetic factors contribute is unknown.

METHODS

In 341 islet autoantibody-positive children with the human leucocyte antigen (HLA) DR3/DR4-DQ8 or the HLA DR4-DQ8/DR4-DQ8 genotype from the prospective TEDDY (The Environmental Determinants of Diabetes in the Young) study, we investigated whether a genetic risk score that had previously been shown to predict islet autoimmunity is also associated with disease progression.

RESULTS

Islet autoantibody-positive children with a genetic risk score in the lowest quartile had a slower progression from single to multiple autoantibodies (p=0.018), from single autoantibodies to diabetes (p=0.004), and by trend from multiple islet autoantibodies to diabetes (p=0.06). In a Cox proportional hazards analysis, faster progression was associated with an increased genetic risk score independently of HLA genotype (HR for progression from multiple autoantibodies to type 1 diabetes, 1.27, 95% CI 1.02 to 1.58 per unit increase), an earlier age of islet autoantibody development (HR, 0.68, 95% CI 0.58 to 0.81 per year increase in age) and female sex (HR, 1.94, 95% CI 1.28 to 2.93).

CONCLUSIONS

Genetic risk scores may be used to identify islet autoantibody-positive children with high-risk HLA genotypes who have a slow rate of progression to subsequent stages of autoimmunity and type 1 diabetes.

Early Probiotic Supplementation and the Risk of Celiac Disease in Children at Genetic Risk

Probiotics are linked to positive regulatory effects on the immune system. The aim of the study was to examine the association between the exposure of probiotics via dietary supplements or via infant formula by the age of 1 year and the development of celiac disease autoimmunity (CDA) and celiac disease among a cohort of 6520 genetically susceptible children. Use of probiotics during the first year of life was reported by 1460 children. Time-to-event analysis was used to examine the associations. Overall exposure of probiotics during the first year of life was not associated with either CDA (n = 1212) (HR 1.15; 95%CI 0.99, 1.35; p = 0.07) or celiac disease (n = 455) (HR 1.11; 95%CI 0.86, 1.43; p = 0.43) when adjusting for known risk factors. Intake of probiotic dietary supplements, however, was associated with a slightly increased risk of CDA (HR 1.18; 95%CI 1.00, 1.40; p = 0.043) compared to children who did not get probiotics. It was concluded that the overall exposure of probiotics during the first year of life was not associated with CDA or celiac disease in children at genetic risk.

Continuous Glucose Monitoring Predicts Progression to Diabetes in Autoantibody Positive Children

CONTEXT

Accurate measures are needed for the prediction and diagnosis of type 1 diabetes (T1D) in at-risk persons.

OBJECTIVE

The purpose of this study was to explore the value of continuous glucose monitoring (CGM) in predicting T1D onset.

DESIGN AND SETTING

The Diabetes Autoimmunity Study in the Young (DAISY) prospectively follows children at increased risk for development of islet autoantibodies (islet autoantibody positive; Ab+) and T1D.

PARTICIPANTS

We analyzed 23 Ab+ participants with available longitudinal CGM data.

MAIN OUTCOME MEASURE

CGM metrics as glycemic predictors of progression to T1D.

RESULTS

Of 23 Ab+ participants with a baseline CGM, 8 progressed to diabetes at a median age of 13.8 years during a median follow-up of 17.7 years (interquartile range, 14.6 to 22.0 years). Compared with nonprogressors, participants who progressed to diabetes had significantly increased baseline glycemic variability (SD, 29 vs 21 mg/dL; P = 0.047), daytime sensor average (122 vs 106 mg/dL; P = 0.02), and daytime sensor area under the curve (AUC, 470,370 vs 415,465; P = 0.047). They spent 24% of time at >140 mg/dL and 12% at >160 mg/dL compared with, respectively, 8% and 3% for nonprogressors (both P = 0.005). A receiver-operating characteristic curve analysis showed an AUC of 0.85 for percentage of time spent at >140 or 160 mg/dL. The cutoff of 18% time spent at >140 mg/dL had 75% sensitivity, 100% specificity, and a 100% positive predictive value for diabetes prediction, although these values could change because some nonprogressors may develop diabetes with longer follow-up.

CONCLUSIONS

Eighteen percent or greater CGM time spent at >140 mg/dL predicts progression to diabetes in Ab+ children.

Accurate mass and retention time library of serum lipids for type 1 diabetes research

Dysregulated lipid species are linked to various disease pathologies and implicated as potential biomarkers for type 1 diabetes (T1D). However, it is challenging to comprehensively profile the blood specimen lipidome with full structural details of every lipid molecule. The commonly used reversed-phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS)-based lipidomics approach is powerful for the separation of individual lipid species, but lipids belonging to different classes may still co-elute and result in ion suppression and misidentification of lipids. Using offline mixed-mode and RPLC-based two-dimensional separations coupled with MS/MS, a comprehensive lipidomic profiling was performed on human sera pooled from healthy and T1D subjects. The elution order of lipid molecular species on RPLC showed good correlations to the total number of carbons in fatty acyl chains and total number of double bonds. This observation together with fatty acyl methyl ester analysis was used to enhance the confidence of identified lipid species. The final T1D serum lipid library database contains 753 lipid molecular species with accurate mass and RPLC retention time uniquely annotated for each of the species. This comprehensive human serum lipid library can serve as a database for high-throughput RPLC-MS-based lipidomic analysis of blood samples related to T1D and other childhood diseases. Graphical abstract.

Predicting Islet Cell Autoimmunity and Type 1 Diabetes: An 8-Year TEDDY Study Progress Report

OBJECTIVE

Assessment of the predictive power of The Environmental Determinants of Diabetes in the Young (TEDDY)-identified risk factors for islet autoimmunity (IA), the type of autoantibody appearing first, and type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

A total of 7,777 children were followed from birth to a median of 9.1 years of age for the development of islet autoantibodies and progression to T1D. Time-dependent sensitivity, specificity, and receiver operating characteristic (ROC) curves were calculated to provide estimates of their individual and collective ability to predict IA and T1D.

RESULTS

HLA genotype (DR3/4 vs. others) was the best predictor for IA (Youden's index J = 0.117) and single nucleotide polymorphism rs2476601, in PTPN22, was the best predictor for insulin autoantibodies (IAA) appearing first (IAA-first) (J = 0.123). For GAD autoantibodies (GADA)-first, weight at 1 year was the best predictor (J = 0.114). In a multivariate model, the area under the ROC curve (AUC) was 0.678 (95% CI 0.655, 0.701), 0.707 (95% CI 0.676, 0.739), and 0.686 (95% CI 0.651, 0.722) for IA, IAA-first, and GADA-first, respectively, at 6 years. The AUC of the prediction model for T1D at 3 years after the appearance of multiple autoantibodies reached 0.706 (95% CI 0.649, 0.762).

CONCLUSIONS

Prediction modeling statistics are valuable tools, when applied in a time-until-event setting, to evaluate the ability of risk factors to discriminate between those who will and those who will not get disease. Although significantly associated with IA and T1D, the TEDDY risk factors individually contribute little to prediction. However, in combination, these factors increased IA and T1D prediction substantially.

Gluten Intake and Risk of Islet Autoimmunity and Progression to Type 1 Diabetes in Children at Increased Risk of the Disease: The Diabetes Autoimmunity Study in the Young (DAISY)

OBJECTIVE

To study the association of gluten intake with development of islet autoimmunity and progression to type 1 diabetes.

RESEARCH DESIGN AND METHODS

The Diabetes Autoimmunity Study in the Young (DAISY) follows children with an increased risk of type 1 diabetes. Blood samples were collected at 9, 15, and 24 months of age, and annually thereafter. Islet autoimmunity was defined by the appearance of at least one autoantibody against insulin, IA2, GAD, or ZnT8 (zinc transporter 8) in at least two consecutive blood samples. Using food frequency questionnaires, we estimated the gluten intake (in grams per day) annually from 1 year of age. Cox regression modeling early gluten intake, and joint modeling of the cumulative gluten intake during follow-up, were used to estimate hazard ratios adjusted for confounders (aHR).

RESULTS

By August 2017, 1,916 subjects were included (median age at end of follow-up 13.5 years), islet autoimmunity had developed in 178 participants, and 56 of these progressed to type 1 diabetes. We found no association between islet autoimmunity and gluten intake at 1-2 years of age or during follow-up (aHR per 4 g/day increase in gluten intake 1.00, 95% CI 0.85-1.17 and 1.01, 0.99-1.02, respectively). We found similar null results for progression from islet autoimmunity to type 1 diabetes. Introduction of gluten at <4 months of age was associated with an increased risk of progressing from islet autoimmunity to type 1 diabetes compared with introduction at 4-5.9 months (aHR 8.69, 95% CI 1.69-44.8).

CONCLUSIONS

Our findings indicate no strong rationale to reduce the amount of gluten in high-risk children to prevent development of type 1 diabetes.

Genetic Determinants of Glycated Hemoglobin in Type 1 Diabetes

Glycated hemoglobin (HbA_1c) is an important measure of glycemia in diabetes. HbA_1c is influenced by environmental and genetic factors both in people with and in people without diabetes. We performed a genome-wide association study (GWAS) for HbA_1c in a Finnish type 1 diabetes (T1D) cohort, FinnDiane. Top results were examined for replication in T1D cohorts DCCT/EDIC, WESDR, CACTI, EDC, and RASS, and a meta-analysis was performed. Three SNPs in high linkage disequilibrium on chromosome 13 near relaxin family peptide receptor 2 (RXFP2) were associated with HbA_1c in FinnDiane at genome-wide significance (P < 5 × 10^-8). The minor alleles of rs2085277 and rs1360072 were associated with higher HbA_1c also in the meta-analysis with RASS (P < 5 × 10^-8), where these variants had minor allele frequencies ≥1%. Furthermore, these SNPs were associated with HbA_1c in an East Asian population without diabetes (P ≤ 0.013). A weighted genetic risk score created from 55 HbA_1c-associated variants from the literature was associated with HbA_1c in FinnDiane but explained only a small amount of variation. Understanding the genetic basis of glycemic control and HbA_1c may lead to better prevention of diabetes complications.

Genetic Contribution to the Divergence in Type 1 Diabetes Risk Between Children From the General Population and Children From Affected Families

The risk for autoimmunity and subsequently type 1 diabetes is 10-fold higher in children with a first-degree family history of type 1 diabetes (FDR children) than in children in the general population (GP children). We analyzed children with high-risk HLA genotypes (n = 4,573) in the longitudinal TEDDY birth cohort to determine how much of the divergent risk is attributable to genetic enrichment in affected families. Enrichment for susceptible genotypes of multiple type 1 diabetes-associated genes and a novel risk gene, BTNL2, was identified in FDR children compared with GP children. After correction for genetic enrichment, the risks in the FDR and GP children converged but were not identical for multiple islet autoantibodies (hazard ratio [HR] 2.26 [95% CI 1.6-3.02]) and for diabetes (HR 2.92 [95% CI 2.05-4.16]). Convergence varied depending upon the degree of genetic susceptibility. Risks were similar in the highest genetic susceptibility group for multiple islet autoantibodies (14.3% vs .12.7%) and diabetes (4.8% vs. 4.1%) and were up to 5.8-fold divergent for children in the lowest genetic susceptibility group, decreasing incrementally in GP children but not in FDR children. These findings suggest that additional factors enriched within affected families preferentially increase the risk of autoimmunity and type 1 diabetes in lower genetic susceptibility strata.

The relationships between markers of tubular injury and intrarenal haemodynamic function in adults with and without type 1 diabetes: Results from the Canadian Study of Longevity in Type 1 Diabetes

OBJECTIVE

Our aim was to define the relationships between plasma biomarkers of kidney injury and intrarenal haemodynamic function (glomerular filtration rate [GFR], effective renal plasma flow [ERPF], renal vascular resistance [RVR]) in adults with type 1 diabetes (T1D).

METHODS

The study sample comprised patients with longstanding T1D (duration ≥50 years), among whom 44 were diabetic kidney disease (DKD) resistors (eGFR >60 mL/min/1.73 m² and <30 mg/d urine albumin excretion) and 22 had DKD, in addition to 73 control participants. GFR_INULIN and ERPF_PAH were measured, RVR was calculated, and afferent (R_A )/efferent (R_E ) areteriolar resistances were derived from Gomez equations. Plasma neutrophil gelatinase-associated lipocalin (NGAL), β2 microglobulin (B2M), osteopontin (OPN) and uromodulin (UMOD) were measured using immunoassay kits from Meso Scale Discovery.

RESULTS

Plasma NGAL, B2M and OPN were higher and UMOD was lower in DKD patients vs DKD resistors and non-diabetic controls. In participants with T1D, plasma NGAL inversely correlated with GFR (r = -0.33; P = 0.006) and ERPF (r = -0.34; P = 0.006), and correlated positively with R_A (r = 0.26; P = 0.03) and RVR (r = 0.31; P = 0.01). In participants without T1D, NGAL and B2M inversely correlated with GFR (NGAL r = -0.18; P = 0.13 and B2M r = -0.49; P < 0.0001) and with ERPF (NGAL r = -0.19; P = 0.1 and B2M r = -0.42; P = 0.0003), and correlated positively with R_A (NGAL r = 0.19; P = 0.10 and B2M r = 0.3; P = 0.01) and with RVR (NGAL r = 0.20; P = 0.09 and B2M r = 0.34; P = 0.003). Differences were significant after adjusting for age, sex, HbA1c, SBP and LDL. There were statistical interactions between T1D status, B2M and intrarenal haemodynamic function (P < 0.05).

CONCLUSIONS

Elevated NGAL relates to intrarenal haemodynamic dysfunction in T1D, whereas elevated NGAL and B2M relate to intrarenal haemodynamic dysfunction in adults without T1D. These data may define a diabetes-specific interplay between tubular injury and intrarenal haemodynamic dysfunction.

Type 1 Diabetes Risk in African-Ancestry Participants and Utility of an Ancestry-Specific Genetic Risk Score

OBJECTIVE

Genetic risk scores (GRS) have been developed that differentiate individuals with type 1 diabetes from those with other forms of diabetes and are starting to be used for population screening; however, most studies were conducted in European-ancestry populations. This study identifies novel genetic variants associated with type 1 diabetes risk in African-ancestry participants and develops an African-specific GRS.

RESEARCH DESIGN AND METHODS

We generated single nucleotide polymorphism (SNP) data with the ImmunoChip on 1,021 African-ancestry participants with type 1 diabetes and 2,928 control participants. HLA class I and class II alleles were imputed using SNP2HLA. Logistic regression models were used to identify genome-wide significant (P < 5.0 × 10-8) SNPs associated with type 1 diabetes in the African-ancestry samples and validate SNPs associated with risk in known European-ancestry loci (P < 2.79 × 10-5).

RESULTS

African-specific (HLA-DQA1*03:01-HLA-DQB1*02:01) and known European-ancestry HLA haplotypes (HLA-DRB1*03:01-HLA-DQA1*05:01-HLA-DQB1*02:01, HLA-DRB1*04:01-HLA-DQA1*03:01-HLA-DQB1*03:02) were significantly associated with type 1 diabetes risk. Among European-ancestry defined non-HLA risk loci, six risk loci were significantly associated with type 1 diabetes in subjects of African ancestry. An African-specific GRS provided strong prediction of type 1 diabetes risk (area under the curve 0.871), performing significantly better than a European-based GRS and two polygenic risk scores in independent discovery and validation cohorts.

CONCLUSIONS

Genetic risk of type 1 diabetes includes ancestry-specific, disease-associated variants. The GRS developed here provides improved prediction of type 1 diabetes in African-ancestry subjects and a means to identify groups of individuals who would benefit from immune monitoring for early detection of islet autoimmunity.