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  • American Diabetes Association  (3)
  • Cuthbertson, David  (3)
  • Nathan, Brandon M.  (3)
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  • American Diabetes Association  (3)
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  • 1
    Online Resource
    Online Resource
    Time to Peak Glucose and Peak C-Peptide During the Progression to Type 1 Diabetes in the Diabetes Prevention Trial and TrialNet Cohorts
    American Diabetes Association ; 2021
    In:  Diabetes Care Vol. 44, No. 10 ( 2021-10-01), p. 2329-2336
    Details
    In: Diabetes Care, American Diabetes Association, Vol. 44, No. 10 ( 2021-10-01), p. 2329-2336
    Abstract: 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 & gt;30 min and time to peak C-peptide & gt;60 min (P & lt; 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 & lt; 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.
    Type of Medium: Online Resource
    ISSN: 0149-5992 , 1935-5548
    URL: Article
    DOI: 10.2337/dc21-0226
    Language: English
    Publisher: American Diabetes Association
    Publication Date: 2021
    detail.hit.zdb_id: 1490520-6
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  • 2
    Online Resource
    Online Resource
    Phenotypes Associated With Zones Defined by Area Under the Curve Glucose and C-peptide in a Population With Islet Autoantibodies
    American Diabetes Association ; 2023
    In:  Diabetes Care Vol. 46, No. 5 ( 2023-05-01), p. 1098-1105
    Details
    In: Diabetes Care, American Diabetes Association, Vol. 46, No. 5 ( 2023-05-01), p. 1098-1105
    Abstract: 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 & lt; 0.001). Disease risk decreased markedly in the highest AUCGLU row as AUCPEP increased (0.88–0.41; P & lt; 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 & lt; 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.
    Type of Medium: Online Resource
    ISSN: 0149-5992 , 1935-5548
    URL: Article
    DOI: 10.2337/dc22-2236
    Language: English
    Publisher: American Diabetes Association
    Publication Date: 2023
    detail.hit.zdb_id: 1490520-6
    Location Call Number Limitation Availability
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Persistence of β-Cell Responsiveness for Over Two Years in Autoantibody-Positive Children With Marked Metabolic Impairment at Screening
    American Diabetes Association ; 2022
    In:  Diabetes Care Vol. 45, No. 12 ( 2022-12-01), p. 2982-2990
    Details
    In: Diabetes Care, American Diabetes Association, Vol. 45, No. 12 ( 2022-12-01), p. 2982-2990
    Abstract: We studied longitudinal differences between progressors and nonprogressors to type 1 diabetes with similar and substantial baseline risk. RESEARCH DESIGN AND METHODS Changes in 2-h oral glucose tolerance test indices were used to examine variability in diabetes progression in the Diabetes Prevention Trial–Type 1 (DPT-1) study (n = 246) and Type 1 Diabetes TrialNet Pathway to Prevention study (TNPTP) (n = 503) among autoantibody (Ab)+ children (aged & lt;18.0 years) with similar baseline metabolic impairment (DPT-1 Risk Score [DPTRS] of 6.5–7.5), as well as in TNPTP Ab− children (n = 94). RESULTS Longitudinal analyses revealed annualized area under the curve (AUC) of C-peptide increases in nonprogressors versus decreases in progressors (P ≤ 0.026 for DPT-1 and TNPTP). Vector indices for AUC glucose and AUC C-peptide changes (on a two-dimensional grid) also differed significantly (P & lt; 0.001). Despite marked baseline metabolic impairment of nonprogressors, changes in AUC C-peptide, AUC glucose, AUC C-peptide–to–AUC glucose ratio (AUC ratio), and Index60 did not differ from Ab− relatives during follow-up. Divergence between nonprogressors and progressors occurred by 6 months from baseline in both cohorts (AUC glucose, P ≤ 0.007; AUC ratio, P ≤ 0.034; Index60, P & lt; 0.001; vector indices of change, P & lt; 0.001). Differences in 6-month change were positively associated with greater diabetes risk (respectively, P & lt; 0.001, P ≤ 0.019, P & lt; 0.001, and P & lt; 0.001) in DPT-1 and TNPTP, except AUC ratio, which was inversely associated with risk (P & lt; 0.001). CONCLUSIONS Novel findings show that even with similarly abnormal baseline risk, progressors had appreciably more metabolic impairment than nonprogressors within 6 months and that the measures showing impairment were predictive of type 1 diabetes. Longitudinal metabolic patterns did not differ between nonprogressors and Ab− relatives, suggesting persistent β-cell responsiveness in nonprogressors.
    Type of Medium: Online Resource
    ISSN: 0149-5992 , 1935-5548
    URL: Article
    DOI: 10.2337/dc22-1362
    Language: English
    Publisher: American Diabetes Association
    Publication Date: 2022
    detail.hit.zdb_id: 1490520-6
    Location Call Number Limitation Availability
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    Online Resource
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