52 research outputs found

    The influence of body mass index and age on C-peptide at the diagnosis of type 1 diabetes in children who participated in the diabetes prevention trial-type 1

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    BACKGROUND/OBJECTIVE: The extent of influence of BMI and age on C-peptide at the diagnosis of type 1 diabetes (T1D) is unknown. We thus studied the impact of body mass index Z-scores (BMIZ) and age on C-peptide measures at and soon after the diagnosis of T1D. METHODS: Data from Diabetes Prevention Trial-Type 1 (DPT-1) participants <18.0 years at diagnosis was analyzed. Analyses examined associations of C-peptide measures with BMIZ and age in 2 cohorts: oral glucose tolerance tests (OGTTs) at diagnosis (n = 99) and mixed meal tolerance tests (MMTTs) <6 months after diagnosis (n = 80). Multivariable linear regression was utilized. RESULTS: Fasting and area under the curve (AUC) C-peptide from OGTTs (n = 99) at diagnosis and MMTTs (n = 80) after diagnosis were positively associated with BMIZ and age (P < .001 for all). Associations persisted when BMIZ and age were included as independent variables in regression models (P < .001 for all). BMIZ and age explained 31%-47% of the variance of C-peptide measures. In an example, 2 individuals with identical AUC C-peptide values had an approximate 5-fold difference in values after adjustments for BMIZ and age. The association between fasting glucose and C-peptide decreased markedly when fasting C-peptide values were adjusted (r = 0.30, P < .01 to r = 0.07, n.s.). CONCLUSIONS: C-peptide measures are strongly and independently related to BMIZ and age at and soon after the diagnosis of T1D. Adjustments for BMIZ and age cause substantial changes in C-peptide values, and impact the association between glycemia and C-peptide. Such adjustments can improve assessments of β-cell impairment at diagnosis

    Effect of Metformin Added to Insulin on Glycemic Control Among Overweight/Obese Adolescents With Type 1 Diabetes: A Randomized Clinical Trial

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    Importance Previous studies assessing the effect of metformin on glycemic control in adolescents with type 1 diabetes have produced inconclusive results. Objective To assess the efficacy and safety of metformin as an adjunct to insulin in treating overweight adolescents with type 1 diabetes. Design, Setting, and Participants Multicenter (26 pediatric endocrinology clinics), double-blind, placebo-controlled randomized clinical trial involving 140 adolescents aged 12.1 to 19.6 years (mean [SD] 15.3 [1.7] years) with mean type 1 diabetes duration 7.0 (3.3) years, mean body mass index (BMI) 94th (4) percentile, mean total daily insulin 1.1 (0.2) U/kg, and mean HbA1c 8.8% (0.7%). Interventions Randomization to receive metformin (n = 71) (≤2000 mg/d) or placebo (n = 69). Main Outcomes and Measures Primary outcome was change in HbA1c from baseline to 26 weeks adjusted for baseline HbA1c. Secondary outcomes included change in blinded continuous glucose monitor indices, total daily insulin, BMI, waist circumference, body composition, blood pressure, and lipids. Results Between October 2013 and February 2014, 140 participants were enrolled. Baseline HbA1c was 8.8% in each group. At 13-week follow-up, reduction in HbA1c was greater with metformin (−0.2%) than placebo (0.1%; mean difference, −0.3% [95% CI, −0.6% to 0.0%]; P = .02). However, this differential effect was not sustained at 26-week follow up when mean change in HbA1c from baseline was 0.2% in each group (mean difference, 0% [95% CI, −0.3% to 0.3%]; P = .92). At 26-week follow-up, total daily insulin per kg of body weight was reduced by at least 25% from baseline among 23% (16) of participants in the metformin group vs 1% (1) of participants in the placebo group (mean difference, 21% [95% CI, 11% to 32%]; P = .003), and 24% (17) of participants in the metformin group and 7% (5) of participants in the placebo group had a reduction in BMI z score of 10% or greater from baseline to 26 weeks (mean difference, 17% [95% CI, 5% to 29%]; P = .01). Gastrointestinal adverse events were reported by more participants in the metformin group than in the placebo group (mean difference, 36% [95% CI, 19% to 51%]; P < .001). Conclusions and Relevance Among overweight adolescents with type 1 diabetes, the addition of metformin to insulin did not improve glycemic control after 6 months. Of multiple secondary end points, findings favored metformin only for insulin dose and measures of adiposity; conversely, use of metformin resulted in an increased risk for gastrointestinal adverse events. These results do not support prescribing metformin to overweight adolescents with type 1 diabetes to improve glycemic control

    Excess BMI Accelerates Islet Autoimmunity in Older Children and Adolescents

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    Objective: Sustained excess BMI increases the risk of type 1 diabetes (T1D) in autoantibody-positive relatives without diabetes of patients. We tested whether elevated BMI also accelerates the progression of islet autoimmunity before T1D diagnosis. Research design and methods: We studied 706 single autoantibody-positive pediatric TrialNet participants (ages 1.6-18.6 years at baseline). Cumulative excess BMI (ceBMI) was calculated for each participant based on longitudinally accumulated BMI ≥85th age- and sex-adjusted percentile. Recursive partitioning analysis and multivariable modeling defined the age cut point differentiating the risk for progression to multiple positive autoantibodies. Results: At baseline, 175 children (25%) had a BMI ≥85th percentile. ceBMI range was -9.2 to 15.6 kg/m2 (median -1.91), with ceBMI ≥0 kg/m2 corresponding to persistently elevated BMI ≥85th percentile. Younger age increased the progression to multiple autoantibodies, with age cutoff of 9 years defined by recursive partitioning analysis. Although ceBMI was not significantly associated with progression from single to multiple autoantibodies overall, there was an interaction with ceBMI ≥0 kg/m2, age, and HLA (P = 0.009). Among children ≥9 years old without HLA DR3-DQ2 and DR4-DQ8, ceBMI ≥0 kg/m2 increased the rate of progression from single to multiple positive autoantibodies (hazard ratio 7.32, P = 0.004) and conferred a risk similar to that in those with T1D-associated HLA haplotypes. In participants <9 years old, the effect of ceBMI on progression to multiple autoantibodies was not significant regardless of HLA type. Conclusions: These data support that elevated BMI may exacerbate islet autoimmunity prior to clinical T1D, particularly in children with lower risk based on age and HLA. Interventions to maintain normal BMI may prevent or delay the progression of islet autoimmunity

    Early and late C-peptide responses during oral glucose tolerance testing are oppositely predictive of type 1 diabetes in autoantibody-positive individuals

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    We examined whether the timing of the C-peptide response during an oral glucose tolerance test (OGTT) in relatives of patients with type 1 diabetes (T1D) is predictive of disease onset. We examined baseline 2-h OGTTs from 670 relatives participating in the Diabetes Prevention Trial-Type 1 (age: 13.8 ± 9.6 years; body mass index z score: 0.3 ± 1.1; 56% male) using univariate regression models. T1D risk increased with lower early C-peptide responses (30–0 min) (χ2 = 28.8, P < 0.001), and higher late C-peptide responses (120–60 min) (χ2 = 23.3, P < 0.001). When both responses were included in a proportional hazards model, they remained independently and oppositely associated with T1D, with a stronger overall association for the combined model than either response alone (χ2 = 41.1; P < 0.001). Using receiver operating characteristic curve analysis, the combined early and late C-peptide response was more accurately predictive of T1D than area under the curve C-peptide (P = 0.005). Our findings demonstrate that lower early and higher late C-peptide responses serve as indicators of increased T1D risk

    Characteristics of slow progression to diabetes in multiple islet autoantibody-positive individuals from five longitudinal cohorts:the SNAIL study

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    Aims/hypothesis Multiple islet autoimmunity increases risk of diabetes, but not all individuals positive for two or more islet autoantibodies progress to disease within a decade. Major islet autoantibodies recognise insulin (IAA), GAD (GADA), islet antigen-2 (IA-2A) and zinc transporter 8 (ZnT8A). Here we describe the baseline characteristics of a unique cohort of ‘slow progressors’ (n = 132) who were positive for multiple islet autoantibodies (IAA, GADA, IA-2A or ZnT8A) but did not progress to diabetes within 10 years. Methods Individuals were identified from five studies (BABYDIAB, Germany; Diabetes Autoimmunity Study in the Young [DAISY], USA; All Babies in Southeast Sweden [ABIS], Sweden; Bart’s Oxford Family Study [BOX], UK and the Pittsburgh Family Study, USA). Multiple islet autoantibody characteristics were determined using harmonised assays where possible. HLA class II risk was compared between slow progressors and rapid progressors (n = 348 diagnosed <5 years old from BOX) using the χ2 test. Results In the first available samples with detectable multiple antibodies, the most frequent autoantibodies were GADA (92%), followed by ZnT8A (62%), IAA (59%) and IA-2A (41%). High risk HLA class II genotypes were less frequent in slow (28%) than rapid progressors (42%, p = 0.011), but only two slow progressors carried the protective HLA DQ6 allele. Conclusion No distinguishing characteristics of slow progressors at first detection of multiple antibodies have yet been identified. Continued investigation of these individuals may provide insights into slow progression that will inform future efforts to slow or prevent progression to clinical diabetes

    Precision gestational diabetes treatment: a systematic review and meta-analyses

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    Genotype-stratified treatment for monogenic insulin resistance: a systematic review

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    This is the final version. Available from Nature Research via the DOI in this record. Data availability: All data used in this review is available from publicly available and herein referenced sources. A list of included studies is provided in Supplementary Data 1. All data generated or analyzed during this study are included in this published article and its supplementary information files. Source data for the figures are available as Supplementary Data 2.BACKGROUND: Monogenic insulin resistance (IR) includes lipodystrophy and disorders of insulin signalling. We sought to assess the effects of interventions in monogenic IR, stratified by genetic aetiology. METHODS: Systematic review using PubMed, MEDLINE and Embase (1 January 1987 to 23 June 2021). Studies reporting individual-level effects of pharmacologic and/or surgical interventions in monogenic IR were eligible. Individual data were extracted and duplicates were removed. Outcomes were analysed for each gene and intervention, and in aggregate for partial, generalised and all lipodystrophy. RESULTS: 10 non-randomised experimental studies, 8 case series, and 23 case reports meet inclusion criteria, all rated as having moderate or serious risk of bias. Metreleptin use is associated with the lowering of triglycerides and haemoglobin A1c (HbA1c) in all lipodystrophy (n = 111), partial (n = 71) and generalised lipodystrophy (n = 41), and in LMNA, PPARG, AGPAT2 or BSCL2 subgroups (n = 72,13,21 and 21 respectively). Body Mass Index (BMI) is lowered in partial and generalised lipodystrophy, and in LMNA or BSCL2, but not PPARG or AGPAT2 subgroups. Thiazolidinediones are associated with improved HbA1c and triglycerides in all lipodystrophy (n = 13), improved HbA1c in PPARG (n = 5), and improved triglycerides in LMNA (n = 7). In INSR-related IR, rhIGF-1, alone or with IGFBP3, is associated with improved HbA1c (n = 17). The small size or absence of other genotype-treatment combinations preclude firm conclusions. CONCLUSIONS: The evidence guiding genotype-specific treatment of monogenic IR is of low to very low quality. Metreleptin and Thiazolidinediones appear to improve metabolic markers in lipodystrophy, and rhIGF-1 appears to lower HbA1c in INSR-related IR. For other interventions, there is insufficient evidence to assess efficacy and risks in aggregated lipodystrophy or genetic subgroups.Wellcome TrustWellcome Trus

    Diabetes in the Adolescent: Transitional Issues

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    Increased Expression of Monocyte CD11b (Mac-1) in Overweight Recent-Onset Type 1 Diabetic Children

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    AIM: Compelling evidence implicates inflammation in the pathogenesis of type 1 diabetes mellitus (T1DM) and associated vascular complications. Obesity is also characterized by low-grade systemic inflammation. In this study, we characterized the inflammatory response in diabetes by analyzing the expression of a panel of activation markers on the surface of peripheral blood monocytes in recently-diagnosed T1DM patients. The potential effects of glycemic control and body mass index (BMI) on monocyte phenotype were also investigated. METHODS: Using flow cytometry, we analyzed the expression of CD11b, CD49d, CD54, CD62L and CD64 antigens on monocytes in a cohort of 51 T1DM patients (≤ 2 months after diagnosis). To test whether phenotype change in monocytes was associated with abnormal cellular function, we studied the adhesive capacity of monocytes to human umbilical vein endothelial cells (HUVEC). RESULTS: We found that circulating monocytes from T1DM patients tested at the clinical onset of the disease (i.e. within 1 week of diagnosis) had higher CD11b expression compared to patients analyzed 2 months after diagnosis (p = 0.02). The highest CD11b levels were detected in patients with HbA1c < 8% (p = 0.04 vs. patients with HbA1c < 8%). In T1DM children analyzed 2 months after diagnosis, we found that those who were overweight (BMI ≥ 85th percentile) had higher levels of monocyte activation than those who were not (BMI ≤ 85th percentile) (p = 0.03). CD11b and HbA1c were significantly correlated (correlation coefficient 0.329, p = 0.02). Finally, monocytes from T1DM patients showed higher adhesion to HUVEC compared to controls. CONCLUSIONS: Circulating immune cells from T1DM patients display many aspects of a proinflammatory state, as indicated by primed or activated monocytes. Obesity is an important factor in monocyte activation during diabetes
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