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The clinical diagnosis of new-onset type 1 diabetes has, for many years, been considered relatively straightforward. Recently, however, there is increasing awareness that within this single clinical phenotype exists considerable heterogeneity: disease onset spans the complete age range; genetic susceptibility is complex; rates of progression differ markedly, as does insulin secretory capacity; and complication rates, glycemic control, and therapeutic intervention efficacy vary widely. Mechanistic and immunopathological studies typically show considerable patchiness across subjects, undermining conclusions regarding disease pathways. Without better understanding, type 1 diabetes heterogeneity represents a major barrier both to deciphering pathogenesis and to the translational effort of designing, conducting, and interpreting clinical trials of disease-modifying agents. This realization comes during a period of unprecedented change in clinical medicine, with increasing emphasis on greater individualization and precision. For complex disorders such as type 1 diabetes, the option of maintaining the "single disease" approach appears untenable, as does the notion of individualizing each single patient's care, obliging us to conceptualize type 1 diabetes less in terms of phenotypes (observable characteristics) and more in terms of disease endotypes (underlying biological mechanisms). Here, we provide our view on an approach to dissect heterogeneity in type 1 diabetes. Using lessons from other diseases and the data gathered to date, we aim to delineate a roadmap through which the field can incorporate the endotype concept into laboratory and clinical practice. We predict that such an effort will accelerate the implementation of precision medicine and has the potential for impact on our approach to translational research, trial design, and clinical management.

OBJECTIVE: With high prevalence of obesity and overlapping features between diabetes subtypes, accurately classifying youth-onset diabetes can be challenging. We aimed to develop prediction models that, using characteristics available at diabetes diagnosis, can identify youth who will retain endogenous insulin secretion at levels consistent with type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: We studied 2,966 youth with diabetes in the prospective SEARCH for Diabetes in Youth study (diagnosis age ≤19 years) to develop prediction models to identify participants with fasting C-peptide ≥250 pmol/L (≥0.75 ng/mL) after >3 years' (median 74 months) diabetes duration. Models included clinical measures at the baseline visit, at a mean diabetes duration of 11 months (age, BMI, sex, waist circumference, HDL cholesterol), with and without islet autoantibodies (GADA, IA-2A) and a type 1 diabetes genetic risk score (T1DGRS). RESULTS: Models using routine clinical measures with or without autoantibodies and T1DGRS were highly accurate in identifying participants with C-peptide ≥0.75 ng/mL (17% of participants; 2.3% and 53% of those with and without positive autoantibodies) (area under the receiver operating characteristic curve [AUCROC] 0.95–0.98). In internal validation, optimism was very low, with excellent calibration (slope 0.995–0.999). Models retained high performance for predicting retained C-peptide in older youth with obesity (AUCROC 0.88–0.96) and in subgroups defined by self-reported race and ethnicity (AUCROC 0.88–0.97), autoantibody status (AUCROC 0.87–0.96), and clinically diagnosed diabetes types (AUCROC 0.81–0.92). CONCLUSIONS: Prediction models combining routine clinical measures at diabetes diagnosis, with or without islet autoantibodies or T1DGRS, can accurately identify youth with diabetes who maintain endogenous insulin secretion in the range associated with T2D. [ABSTRACT FROM AUTHOR]

ObjectiveThe type 2 diabetes-associated alleles at the TCF7L2 locus mark a type 1 diabetes phenotype characterized by single islet autoantibody positivity as well as lower glucose and higher C-peptide measures. Here, we studied whether the TCF7L2 locus influences progression of islet autoimmunity, from single to multiple (≥2) autoantibody positivity, in relatives of patients with type 1 diabetes.Research design and methodsWe evaluated 244 participants in the Type 1 Diabetes TrialNet Pathway to Prevention study with confirmed single autoantibody positivity at screening and Immunochip single nucleotide polymorphism data (47.5% male; median age 12.8 years, range 1.2-45.9; 90.2% white). We analyzed risk allele frequency at TCF7L2 rs4506565 (in linkage disequilibrium with rs7903146). Altogether, 62.6% participants carried ≥1 risk allele. Univariate and multivariable Cox proportional hazards models and Kaplan-Meier statistical methods were used.ResultsDuring follow-up (median 5.2 years, range 0.2-12.6), 62% of the single autoantibody-positive participants developed multiple autoantibody positivity. In the overall cohort, the TCF7L2 locus did not significantly predict progression to multiple autoantibody positivity. However, among single GAD65 autoantibody-positive participants (n = 158), those who carried ≥1 risk allele had a lower rate of progression to multiple autoantibody positivity (hazard ratio [HR] 0.65, P = 0.033) than those who did not, after adjustment for HLA risk haplotypes and age. Among subjects who were either IA-2 or insulin autoantibody positive only, carrying ≥1 TCF7L2 risk allele was not a significant factor overall, but in overweight or obese participants, it increased the risk of progression to multiple autoantibody positivity (HR 3.02, P = 0.016) even with adjustment for age.ConclusionsThe type 2 diabetes-associated TCF7L2 locus influences progression of islet autoimmunity, with differential effects by autoantibody specificity and interaction by obesity/overweight.

ObjectiveThe phenotypic diversity of type 1 diabetes suggests heterogeneous etiopathogenesis. We investigated the relationship of type 2 diabetes-associated transcription factor 7 like 2 (TCF7L2) single nucleotide polymorphisms (SNPs) with immunologic and metabolic characteristics at type 1 diabetes diagnosis.Research design and methodsWe studied TrialNet participants with newly diagnosed autoimmune type 1 diabetes with available TCF7L2 rs4506565 and rs7901695 SNP data (n = 810; median age 13.6 years; range 3.3-58.6). We modeled the influence of carrying a TCF7L2 variant (i.e., having 1 or 2 minor alleles) on the number of islet autoantibodies and oral glucose tolerance test (OGTT)-stimulated C-peptide and glucose measures at diabetes diagnosis. All analyses were adjusted for known confounders.ResultsThe rs4506565 variant was a significant independent factor of expressing a single autoantibody, instead of multiple autoantibodies, at diagnosis (odds ratio [OR] 1.66 [95% CI 1.07, 2.57], P = 0.024). Interaction analysis demonstrated that this association was only significant in participants ≥12 years old (n = 504; OR 2.12 [1.29, 3.47], P = 0.003) but not younger ones (n = 306, P = 0.73). The rs4506565 variant was independently associated with higher C-peptide area under the curve (AUC) (P = 0.008) and lower mean glucose AUC (P = 0.0127). The results were similar for the rs7901695 SNP.ConclusionsIn this cohort of individuals with new-onset type 1 diabetes, type 2 diabetes-linked TCF7L2 variants were associated with single autoantibody (among those ≥12 years old), higher C-peptide AUC, and lower glucose AUC levels during an OGTT. Thus, carriers of the TCF7L2 variant had a milder immunologic and metabolic phenotype at type 1 diabetes diagnosis, which could be partly driven by type 2 diabetes-like pathogenic mechanisms.

ObjectiveWe aimed to determine the effect of elevated BMI over time on the progression to type 1 diabetes in youth.Research design and methodsWe studied 1,117 children in the TrialNet Pathway to Prevention cohort (autoantibody-positive relatives of patients with type 1 diabetes). Longitudinally accumulated BMI above the 85th age- and sex-adjusted percentile generated a cumulative excess BMI (ceBMI) index. Recursive partitioning and multivariate analyses yielded sex- and age-specific ceBMI thresholds for greatest type 1 diabetes risk.ResultsHigher ceBMI conferred significantly greater risk of progressing to type 1 diabetes. The increased diabetes risk occurred at lower ceBMI values in children

The study published in Diabetes Care highlights the challenges in distinguishing maturity-onset diabetes of the young (MODY) from type 2 diabetes in youth, especially in a diverse cohort. The MODY probability calculator and clinical features used for adults were found to be ineffective in youth diagnosed with type 2 diabetes. Body mass index (BMI) emerged as a strong predictor of MODY, outperforming other clinical variables like age of diagnosis and parental history of diabetes. The study emphasizes the need for new biomarkers to differentiate between youth-onset type 2 diabetes and MODY. [Extracted from the article]

OBJECTIVE: Mixed-meal tolerance test–stimulated area under the curve (AUC) C-peptide at 12–24 months represents the primary end point for nearly all intervention trials seeking to preserve β-cell function in recent-onset type 1 diabetes. We hypothesized that participant benefit might be detected earlier and predict outcomes at 12 months posttherapy. Such findings would support shorter trials to establish initial efficacy. RESEARCH DESIGN AND METHODS: We examined data from six Type 1 Diabetes TrialNet immunotherapy randomized controlled trials in a post hoc analysis and included additional stimulated metabolic indices beyond C-peptide AUC. We partitioned the analysis into successful and unsuccessful trials and analyzed the data both in the aggregate as well as individually for each trial. RESULTS: Among trials meeting their primary end point, we identified a treatment effect at 3 and 6 months when using C-peptide AUC (P = 0.030 and P < 0.001, respectively) as a dynamic measure (i.e., change from baseline). Importantly, no such difference was seen in the unsuccessful trials. The use of C-peptide AUC as a 6-month dynamic measure not only detected treatment efficacy but also suggested long-term C-peptide preservation (R 2 for 12-month C-peptide AUC adjusted for age and baseline value was 0.80, P < 0.001), and this finding supported the concept of smaller trial sizes down to 54 participants. CONCLUSIONS: Early dynamic measures can identify a treatment effect among successful immune therapies in type 1 diabetes trials with good long-term prediction and practical sample size over a 6-month period. While external validation of these findings is required, strong rationale and data exist in support of shortening early-phase clinical trials. [ABSTRACT FROM AUTHOR]

OBJECTIVE: The Rare and Atypical Diabetes Network (RADIANT) will perform a study of individuals and, if deemed informative, a study of their family members with uncharacterized forms of diabetes. RESEARCH DESIGN AND METHODS: The protocol includes genomic (whole-genome [WGS], RNA, and mitochondrial sequencing), phenotypic (vital signs, biometric measurements, questionnaires, and photography), metabolomics, and metabolic assessments. RESULTS: Among 122 with WGS results of 878 enrolled individuals, a likely pathogenic variant in a known diabetes monogenic gene was found in 3 (2.5%), and six new monogenic variants have been identified in the SMAD5, PTPMT1, INS, NFKB1, IGF1R, and PAX6 genes. Frequent phenotypic clusters are lean type 2 diabetes, autoantibody-negative and insulin-deficient diabetes, lipodystrophic diabetes, and new forms of possible monogenic or oligogenic diabetes. CONCLUSIONS: The analyses will lead to improved means of atypical diabetes identification. Genetic sequencing can identify new variants, and metabolomics and transcriptomics analysis can identify novel mechanisms and biomarkers for atypical disease. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Metabolic zones were developed to characterize heterogeneity of individuals with islet autoantibodies. RESEARCH DESIGN AND METHODS: Baseline 2-h oral glucose tolerance test data from 6,620 TrialNet Pathway to Prevention Study (TNPTP) autoantibody-positive participants (relatives of individuals with type 1 diabetes) were used to form 25 zones from five area under the curve glucose (AUCGLU) rows and five area under the curve C-peptide (AUCPEP) columns. Zone phenotypes were developed from demographic, metabolic, autoantibody, HLA, and risk data. RESULTS: As AUCGLU increased, changes of glucose and C-peptide response curves (from mean glucose and mean C-peptide values at 30, 60, 90, and 120 min) were similar within the five AUCPEP columns. Among the zones, 5-year risk for type 1 diabetes was highly correlated with islet antigen 2 antibody prevalence (r = 0.96, P < 0.001). Disease risk decreased markedly in the highest AUCGLU row as AUCPEP increased (0.88–0.41; P < 0.001 from lowest AUCPEP column to highest AUCPEP column). AUCGLU correlated appreciably less with Index60 (an indicator of insulin secretion) in the highest AUCPEP column (r = 0.33) than in other columns (r ≥ 0.78). AUCGLU was positively related to "fasting glucose × fasting insulin" and to "fasting glucose × fasting C-peptide" (indicators of insulin resistance) before and after adjustments for Index60 (P < 0.001). CONCLUSIONS: Phenotypes of 25 zones formed from AUCGLU and AUCPEP were used to gain insights into type 1 diabetes heterogeneity. Zones were used to examine GCRC changes with increasing AUCGLU, associations between risk and autoantibody prevalence, the dependence of glucose as a predictor of risk according to C-peptide, and glucose heterogeneity from contributions of insulin secretion and insulin resistance. [ABSTRACT FROM AUTHOR]

Objective: To define the relationship between glucose and C-peptide during the progression to type 1 diabetes (T1D).Research Design and Methods: We longitudinally studied glucose and C-peptide response curves (GCRCs), area under curve (AUC) for glucose, and AUC C-peptide from oral glucose tolerance tests (OGTTs), and Index60 (which integrates OGTT glucose and C-peptide values) in Diabetes Prevention Trial-Type 1 (DPT-1) (n = 72) and TrialNet Pathway to Prevention Study (TNPTP) (n = 82) participants who had OGTTs at baseline and follow-up time points before diagnosis.Results: Similar evolutions of GCRC configurations were evident between DPT-1 and TNPTP from baseline to 0.5 years prediagnosis. Whereas AUC glucose increased throughout from baseline to 0.5 years prediagnosis, AUC C-peptide increased from baseline until 1.5 years prediagnosis (DPT-1, P = 0.004; TNPTP, P = 0.012) and then decreased from 1.5 to 0.5 years prediagnosis (DPT-1, P = 0.017; TNPTP, P = 0.093). This change was mostly attributable to change in the late AUC C-peptide response (i.e., 60- to 120-min AUC C-peptide). Median Index60 values of DPT-1 (1.44) and TNPTP (1.05) progressors to T1D 1.5 years prediagnosis (time of transition from increasing to decreasing AUC C-peptide) were used as thresholds to identify individuals at high risk for T1D in the full cohort at baseline (5-year risk of 0.75-0.88 for those above thresholds).Conclusions: A transition from an increase to a decrease in AUC C-peptide ∼1.5 years prediagnosis was validated in two independent cohorts. The median Index60 value at that time point can be used as a pathophysiologic-based threshold for identifying individuals at high risk for T1D. [ABSTRACT FROM AUTHOR]

Objective: We assessed whether Index60, a composite measure of fasting C-peptide, 60-min C-peptide, and 60-min glucose, could improve the metabolic staging of type 1 diabetes for progression to clinical disease (stage 3) among autoantibody-positive (Ab+) individuals with normal 2-h glucose values (<140 mg/dL).Research Design and Methods: We analyzed 3,058 Type 1 Diabetes TrialNet Pathway to Prevention participants with 2-h glucose <140 mg/dL and Index60 <1.00 values from baseline oral glucose tolerance tests. Characteristics associated with type 1 diabetes (younger age, greater Ab+, higher HLA DR3-DQ2/DR4-DQ8 prevalence, and lower C-peptide) were compared among four mutually exclusive groups: top 2-h glucose quartile only (HI-2HGLU), top Index60 quartile only (HI-IND60), both top quartiles (HI-BOTH), and neither top quartile (LO-BOTH). Additionally, within the 2-h glucose distribution of <140 mg/dL and separately within the Index60 <1.00 distribution, comparisons were made between those above or below the medians.Results: HI-IND60 and HI-BOTH were younger, with greater frequency of more than two Ab+, and lower C-peptide levels, than either HI-2HGLU or LO-BOTH (all P < 0.001). The cumulative incidence for stage 3 was greater for HI-IND60 and HI-BOTH than for either HI-2HGLU or LO-BOTH (all P < 0.001). Those with Index60 values above the median were younger and had higher frequency of two or more Ab+ (P < 0.001) and DR3-DQ2/DR4-DQ8 prevalence (P < 0.001) and lower area under the curve (AUC) C-peptide levels (P < 0.001) than those below. Those above the 2-h glucose median had higher AUC C-peptide levels (P < 0.001), but otherwise did not differ from those below.Conclusions: Index60 identifies individuals with characteristics of type 1 diabetes at appreciable risk for progression who would otherwise be missed by 2-h glucose staging criteria. [ABSTRACT FROM AUTHOR]

Objective: To assess the progression of type 1 diabetes using time to peak glucose or C-peptide during oral glucose tolerance tests (OGTTs) in autoantibody-positive relatives of people with type 1 diabetes.Research Design and Methods: We examined 2-h OGTTs of participants in the Diabetes Prevention Trial Type 1 (DPT-1) and TrialNet Pathway to Prevention (PTP) studies. We included 706 DPT-1 participants (mean ± SD age, 13.84 ± 9.53 years; BMI Z-score, 0.33 ± 1.07; 56.1% male) and 3,720 PTP participants (age, 16.01 ± 12.33 years; BMI Z-score, 0.66 ± 1.3; 49.7% male). Log-rank testing and Cox regression analyses with adjustments (age, sex, race, BMI Z-score, HOMA-insulin resistance, and peak glucose/C-peptide levels, respectively) were performed.Results: In each of DPT-1 and PTP, higher 5-year diabetes progression risk was seen in those with time to peak glucose >30 min and time to peak C-peptide >60 min (P < 0.001 for all groups), before and after adjustments. In models examining strength of association with diabetes development, associations were greater for time to peak C-peptide versus peak C-peptide value (DPT-1: χ2 = 25.76 vs. χ2 = 8.62; PTP: χ2 = 149.19 vs. χ2 = 79.98; all P < 0.001). Changes in the percentage of individuals with delayed glucose and/or C-peptide peaks were noted over time.Conclusions: In two independent at-risk populations, we show that those with delayed OGTT peak times for glucose or C-peptide are at higher risk of diabetes development within 5 years, independent of peak levels. Moreover, time to peak C-peptide appears more predictive than the peak level, suggesting its potential use as a specific biomarker for diabetes progression. [ABSTRACT FROM AUTHOR]

Objective: We aimed to test whether type 2 diabetes (T2D)-associated TCF7L2 genetic variants affect insulin sensitivity or secretion in autoantibody-positive relatives at risk for type 1 diabetes (T1D).Research Design and Methods: We studied autoantibody-positive TrialNet Pathway to Prevention study participants (N = 1,061) (mean age 16.3 years) with TCF7L2 single nucleotide polymorphism (SNP) information and baseline oral glucose tolerance test (OGTT) to calculate indices of insulin sensitivity and secretion. With Bonferroni correction for multiple comparisons, P values < 0.0086 were considered statistically significant.Results: None, one, and two T2D-linked TCF7L2 alleles were present in 48.1%, 43.9%, and 8.0% of the participants, respectively. Insulin sensitivity (as reflected by 1/fasting insulin [1/IF]) decreased with increasing BMI z score and was lower in Hispanics. Insulin secretion (as measured by 30-min C-peptide index) positively correlated with age and BMI z score. Oral disposition index was negatively correlated with age, BMI z score, and Hispanic ethnicity. None of the indices were associated with TCF7L2 SNPs. In multivariable analysis models with age, BMI z score, ethnicity, sex, and TCF7L2 alleles as independent variables, C-peptide index increased with age, while BMI z score was associated with higher insulin secretion (C-peptide index), lower insulin sensitivity (1/IF), and lower disposition index; there was no significant effect of TCF7L2 SNPs on any of these indices. When restricting the analyses to participants with a normal OGTT (n = 743; 70%), the results were similar.Conclusions: In nondiabetic autoantibody-positive individuals, TCF7L2 SNPs were not related to insulin sensitivity or secretion indices after accounting for BMI z score, age, sex, and ethnicity. [ABSTRACT FROM AUTHOR]

The American Diabetes Association 2020 Standards of Medical Care in Diabetes (Standards of Care) recommends a hemoglobin A1c (A1C) of <7% (53 mmol/mol) for many children with type 1 diabetes (T1D), with an emphasis on target personalization. A higher A1C target of <7.5% may be more suitable for youth who cannot articulate symptoms of hypoglycemia or have hypoglycemia unawareness and for those who do not have access to analog insulins or advanced diabetes technologies or who cannot monitor blood glucose regularly. Even less stringent A1C targets (e.g., <8%) may be warranted for children with a history of severe hypoglycemia, severe morbidities, or short life expectancy. During the "honeymoon" period and in situations where lower mean glycemia is achievable without excessive hypoglycemia or reduced quality of life, an A1C <6.5% may be safe and effective. Here, we provide a historical perspective of A1C targets in pediatrics and highlight evidence demonstrating detrimental effects of hyperglycemia in children and adolescents, including increased likelihood of brain structure and neurocognitive abnormalities, microvascular and macrovascular complications, long-term effects, and increased mortality. We also review data supporting a decrease over time in overall severe hypoglycemia risk for youth with T1D, partly associated with the use of newer insulins and devices, and weakened association between lower A1C and severe hypoglycemia risk. We present common barriers to achieving glycemic targets in pediatric diabetes and discuss some strategies to address them. We aim to raise awareness within the community on Standards of Care updates that impact this crucial goal in pediatric diabetes management. [ABSTRACT FROM AUTHOR]

Objective: We tested the ability of a type 1 diabetes (T1D) genetic risk score (GRS) to predict progression of islet autoimmunity and T1D in at-risk individuals.Research Design and Methods: We studied the 1,244 TrialNet Pathway to Prevention study participants (T1D patients' relatives without diabetes and with one or more positive autoantibodies) who were genotyped with Illumina ImmunoChip (median [range] age at initial autoantibody determination 11.1 years [1.2-51.8], 48% male, 80.5% non-Hispanic white, median follow-up 5.4 years). Of 291 participants with a single positive autoantibody at screening, 157 converted to multiple autoantibody positivity and 55 developed diabetes. Of 953 participants with multiple positive autoantibodies at screening, 419 developed diabetes. We calculated the T1D GRS from 30 T1D-associated single nucleotide polymorphisms. We used multivariable Cox regression models, time-dependent receiver operating characteristic curves, and area under the curve (AUC) measures to evaluate prognostic utility of T1D GRS, age, sex, Diabetes Prevention Trial-Type 1 (DPT-1) Risk Score, positive autoantibody number or type, HLA DR3/DR4-DQ8 status, and race/ethnicity. We used recursive partitioning analyses to identify cut points in continuous variables.Results: Higher T1D GRS significantly increased the rate of progression to T1D adjusting for DPT-1 Risk Score, age, number of positive autoantibodies, sex, and ethnicity (hazard ratio [HR] 1.29 for a 0.05 increase, 95% CI 1.06-1.6; P = 0.011). Progression to T1D was best predicted by a combined model with GRS, number of positive autoantibodies, DPT-1 Risk Score, and age (7-year time-integrated AUC = 0.79, 5-year AUC = 0.73). Higher GRS was significantly associated with increased progression rate from single to multiple positive autoantibodies after adjusting for age, autoantibody type, ethnicity, and sex (HR 2.27 for GRS >0.295, 95% CI 1.47-3.51; P = 0.0002).Conclusions: The T1D GRS independently predicts progression to T1D and improves prediction along T1D stages in autoantibody-positive relatives. [ABSTRACT FROM AUTHOR]

Objective: The phenotypic diversity of type 1 diabetes suggests heterogeneous etiopathogenesis. We investigated the relationship of type 2 diabetes-associated transcription factor 7 like 2 (TCF7L2) single nucleotide polymorphisms (SNPs) with immunologic and metabolic characteristics at type 1 diabetes diagnosis.Research Design and Methods: We studied TrialNet participants with newly diagnosed autoimmune type 1 diabetes with available TCF7L2 rs4506565 and rs7901695 SNP data (n = 810; median age 13.6 years; range 3.3-58.6). We modeled the influence of carrying a TCF7L2 variant (i.e., having 1 or 2 minor alleles) on the number of islet autoantibodies and oral glucose tolerance test (OGTT)-stimulated C-peptide and glucose measures at diabetes diagnosis. All analyses were adjusted for known confounders.Results: The rs4506565 variant was a significant independent factor of expressing a single autoantibody, instead of multiple autoantibodies, at diagnosis (odds ratio [OR] 1.66 [95% CI 1.07, 2.57], P = 0.024). Interaction analysis demonstrated that this association was only significant in participants ≥12 years old (n = 504; OR 2.12 [1.29, 3.47], P = 0.003) but not younger ones (n = 306, P = 0.73). The rs4506565 variant was independently associated with higher C-peptide area under the curve (AUC) (P = 0.008) and lower mean glucose AUC (P = 0.0127). The results were similar for the rs7901695 SNP.Conclusions: In this cohort of individuals with new-onset type 1 diabetes, type 2 diabetes-linked TCF7L2 variants were associated with single autoantibody (among those ≥12 years old), higher C-peptide AUC, and lower glucose AUC levels during an OGTT. Thus, carriers of the TCF7L2 variant had a milder immunologic and metabolic phenotype at type 1 diabetes diagnosis, which could be partly driven by type 2 diabetes-like pathogenic mechanisms. [ABSTRACT FROM AUTHOR]

Objective: The type 2 diabetes-associated alleles at the TCF7L2 locus mark a type 1 diabetes phenotype characterized by single islet autoantibody positivity as well as lower glucose and higher C-peptide measures. Here, we studied whether the TCF7L2 locus influences progression of islet autoimmunity, from single to multiple (≥2) autoantibody positivity, in relatives of patients with type 1 diabetes.Research Design and Methods: We evaluated 244 participants in the Type 1 Diabetes TrialNet Pathway to Prevention study with confirmed single autoantibody positivity at screening and Immunochip single nucleotide polymorphism data (47.5% male; median age 12.8 years, range 1.2-45.9; 90.2% white). We analyzed risk allele frequency at TCF7L2 rs4506565 (in linkage disequilibrium with rs7903146). Altogether, 62.6% participants carried ≥1 risk allele. Univariate and multivariable Cox proportional hazards models and Kaplan-Meier statistical methods were used.Results: During follow-up (median 5.2 years, range 0.2-12.6), 62% of the single autoantibody-positive participants developed multiple autoantibody positivity. In the overall cohort, the TCF7L2 locus did not significantly predict progression to multiple autoantibody positivity. However, among single GAD65 autoantibody-positive participants (n = 158), those who carried ≥1 risk allele had a lower rate of progression to multiple autoantibody positivity (hazard ratio [HR] 0.65, P = 0.033) than those who did not, after adjustment for HLA risk haplotypes and age. Among subjects who were either IA-2 or insulin autoantibody positive only, carrying ≥1 TCF7L2 risk allele was not a significant factor overall, but in overweight or obese participants, it increased the risk of progression to multiple autoantibody positivity (HR 3.02, P = 0.016) even with adjustment for age.Conclusions: The type 2 diabetes-associated TCF7L2 locus influences progression of islet autoimmunity, with differential effects by autoantibody specificity and interaction by obesity/overweight. [ABSTRACT FROM AUTHOR]