The class II major histocompatibility complex molecule I-Ag7 is strongly linked to the development of spontaneous insulin-dependent diabetes mellitus (IDDM) in non obese diabetic mice and to the induction of experimental allergic encephalomyelitis in Biozzi AB/H mice. Structurally, it resembles the HLA-DQ molecules associated with human IDDM, in having a non-Asp residue at position 57 in its β chain. To identify the requirements for peptide binding to I-Ag7 and thereby potentially pathogenic T cell epitopes, we analyzed a known I-Ag7-restricted T cell epitope, hen egg white lysozyme (HEL) amino acids 9–27. NH2- and COOH-terminal truncations demonstrated that the minimal epitope for activation of the T cell hybridoma 2D12.1 was M12-R21 and the minimum sequence for direct binding to purified I-Ag7 M12-Y20/ K13-R21. Alanine (A) scanning revealed two primary anchors for binding at relative positions (p) 6 (L) and 9 (Y) in the HEL epitope. The critical role of both anchors was demonstrated by incorporating L and Y in poly(A) backbones at the same relative positions as in the HEL epitope. Well-tolerated, weakly tolerated, and nontolerated residues were identified by analyzing the binding of peptides containing multiple substitutions at individual positions. Optimally, p6 was a large, hydrophobic residue (L, I, V, M), whereas p9 was aromatic and hydrophobic (Y or F) or positively charged (K, R). Specific residues were not tolerated at these and some other positions. A motif for binding to I-Ag7 deduced from analysis of the model HEL epitope was present in 27/30 (90%) of peptides reported to be I-Ag7–restricted T cell epitopes or eluted from I-Ag7. Scanning a set of overlapping peptides encompassing human proinsulin revealed the motif in 6/6 good binders (sensitivity = 100%) and 4/13 weak or non-binders (specificity = 70%). This motif should facilitate identification of autoantigenic epitopes relevant to the pathogenesis and immunotherapy of IDDM.
OBJECTIVEGlucose fluctuations trigger activation of oxidative stress, a main mechanism leading to secondary diabetes complications. We evaluated the relationship between glycemic variability and β-cell dysfunction.RESEARCH DESIGN AND METHODSWe conducted a cross-sectional study in 59 patients with type 2 diabetes (aged 64.2 ± 8.6 years, A1C 6.5 ± 1.0%, and BMI 29.8 ± 3.8 kg/m2[mean ± SD]) using either oral hypoglycemic agents (OHAs) (n = 34) or diet alone (nonusers). As a measure of glycemic variability, the mean amplitude of glycemic excursions (MAGE) was computed from continuous glucose monitoring data recorded over 3 consecutive days. The relationships between MAGE, β-cell function, and clinical parameters were assessed by including postprandial β-cell function (PBCF) and basal β-cell function (BBCF) obtained by a model-based method from plasma C-peptide and plasma glucose during a mixed-meal test as well as homeostasis model assessment of insulin sensitivity, clinical factors, carbohydrate intake, and type of OHA.RESULTSMAGE was nonlinearly correlated with PBCF (r = 0.54, P < 0.001) and with BBCF (r = 0.31, P = 0.025) in OHA users but failed to correlate with these parameters in nonusers (PBCF P = 0.21 and BBCF P = 0.07). The stepwise multiple regression analysis demonstrated that PBCF and OHA combination treatment were independent contributors to MAGE (R2 = 0.50, P < 0.010), whereas insulin sensitivity, carbohydrate intake, and nonglycemic parameters failed to contribute.CONCLUSIONSPBCF appears to be an important target to reduce glucose fluctuations in OHA-treated type 2 diabetes.
Autoimmune-mediated destruction of pancreatic islet beta cells leads to insulin-dependent diabetes in non-obese diabetic (NOD) mice. Although both direct cytotoxic T cell- and indirect cytokine-, nitric oxide- or free radical-mediated mechanisms induce beta-cell apoptosis in vitro, beta-cell death in vivo in spontaneous autoimmune diabetes is not well-characterized. Furthermore, whether beta cells die gradually, or rapidly in the late pre-clinical stage, is a question of current interest. To investigate beta-cell death in vivo, we measured the frequency and intra-islet localisation of apoptosis, defined as DNA strand breaks by the terminal deoxynucleotidyl transferase-mediated dUTP nick end labelling (TUNEL) technique, during spontaneous and cyclophosphamide-accelerated diabetes in NOD mice. In spontaneous diabetes, the frequency of apoptosis in islets correlated with the progression of beta-cell destruction with age. Although apoptosis was detected at low frequency within the reduced insulin-positive islet area of pre-diabetic mice at 90 days of age, it was rarely co-localised to beta cells. After acceleration of beta-cell destruction with cyclophosphamide, the frequency of apoptosis reached maximum at 12 days, at which time 3.2 % of apoptotic cells were beta cells. Apoptosis was most frequent in the insulin-negative islet area comprised of mononuclear cell infiltrate and was localized to CD8+ T cells. The rarity of detectable apoptotic beta cells in spontaneous pre-diabetic mice with pronounced insulitis and reduced insulin-positive islet areas most likely reflects the rapid clearance of apoptotic beta cells. Our findings are more consistent with gradual destruction of non-renewable beta-cells in spontaneous diabetes, than with their rapid, accelerated destruction (as after cyclophosphamide) in the late pre-clinical stage.
BackgroundContinuous glucose monitoring (CGM) has revolutionised diabetes management. CGM enables complete visualisation of the glucose profile, and the uncovering of metabolic ‘weak points’. A standardised procedure to evaluate the complex data acquired by CGM, and to create patient-tailored recommendations has not yet been developed. We aimed to develop a new patient-tailored approach for the routine clinical evaluation of CGM profiles. We developed a metric allowing screening for profiles that require therapeutic action and a method to identify the individual CGM parameters with improvement potential.MethodsFifteen parameters frequently used to assess CGM profiles were calculated for 1,562 historic CGM profiles from subjects with type 1 or type 2 diabetes. Factor analysis and varimax rotation was performed to identify factors that accounted for the quality of the profiles.ResultsWe identified five primary factors that determined CGM profiles (central tendency, hyperglycaemia, hypoglycaemia, intra- and inter-daily variations). One parameter from each factor was selected for constructing the formula for the screening metric, (the ‘Q-Score’). To derive Q-Score classifications, three diabetes specialists independently categorised 766 CGM profiles into groups of ‘very good’, ‘good’, ‘satisfactory’, ‘fair’, and ‘poor’ metabolic control. The Q-Score was then calculated for all profiles, and limits were defined based on the categorised groups (<4.0, very good; 4.0–5.9, good; 6.0–8.4, satisfactory; 8.5–11.9, fair; and ≥12.0, poor). Q-Scores increased significantly (P <0.01) with increasing antihyperglycaemic therapy complexity. Accordingly, the percentage of fair and poor profiles was higher in insulin-treated compared with diet-treated subjects (58.4% vs. 9.3%). In total, 90% of profiles categorised as fair or poor had at least three parameters that could potentially be optimised. The improvement potential of those parameters can be categorised as ‘low’, ‘moderate’ and ‘high’.ConclusionsThe Q-Score is a new metric suitable to screen for CGM profiles that require therapeutic action. Moreover, because single components of the Q-Score formula respond to individual weak points in glycaemic control, parameters with improvement potential can be identified and used as targets for optimising patient-tailored therapies.Electronic supplementary materialThe online version of this article (doi:10.1186/s12902-015-0019-0) contains supplementary material, which is available to authorized users.
OBJECTIVE -We sought to assess the benefit of the Karlsburg Diabetes Management System (KADIS) in conjunction with the continuous glucose monitoring system (CGMS) in an outpatient setting.RESEARCH DESIGN AND METHODS -A multicentric trial was performed in insulin-treated outpatients (n ϭ 49), aged 21-70 years, with a mean diabetes duration of 14.2 years. Subjects were recruited from five outpatient centers and randomized for CGMS-or CGMS/ KADIS-based decision support and followed up for 3 months. After two CGMS monitorings, the outcome parameters A1C (%), mean sensor glucose of the CGMS profile (MSG) (mmol/l), and duration of hyperglycemia (h/day) were evaluated.RESULTS -In contrast with the CGMS group (0.27 Ϯ 0.67%), mean change in A1C decreased in the CGMS/KADIS group during the follow-up (Ϫ0.34 Ϯ 0.49%; P Ͻ 0.01). MSG levels were not affected in the CGMS group (7.75 Ϯ 1.33 vs. 8.45 Ϯ 2.46 mmol/l) but declined in the CGMS/KADIS group (8.43 Ϯ 1.33 vs. 7.59 Ϯ 1.47 mmol/l; P Ͻ 0.05). Net KADIS effect (Ϫ0.60 [95% CI Ϫ0.96 to Ϫ 0.25%]; P Ͻ 0.01) was associated with reduced duration of hyperglycemia (4.6 vs. 1.0 h/day; P Ͻ 0.01) without increasing hypoglycemia. Multiple regression revealed that the A1C outcome was dependent on KADIS-based decision support. Age, sex, physician's specialty, diabetes type, and BMI had no measurable effect. CONCLUSIONS -If physicians were supported by CGMS/KADIS in therapeutic decisions, they achieved better glycemic control for their patients compared with support by CGMS alone. KADIS is a suitable decision support tool for physicians in outpatient diabetes care and has the potential to improve evidence-based management of diabetes.
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