Age-Corrected Beta Cell Mass Following Onset of Type 1 Diabetes Mellitus Correlates with Plasma C-Peptide in Humans

The inability to produce insulin endogenously precipitates the clinical symptoms of type 1 diabetes mellitus. However, the dynamic trajectory of beta cell destruction following onset remains unclear. Using model-based inference, the severity of beta cell destruction at onset decreases with age where, on average, a 40% reduction in beta cell mass was sufficient to precipitate clinical symptoms at 20 years of age. While plasma C-peptide provides a surrogate measure of endogenous insulin production post-onset, it is unclear as to whether plasma C-peptide represents changes in beta cell mass or beta cell function. The objective of this paper was to determine the relationship between beta cell mass and endogenous insulin production post-onset.Model-based inference was used to compare direct measures of beta cell mass in 102 patients against contemporary measures of plasma C-peptide obtained from three studies that collectively followed 834 patients post-onset of clinical symptoms. An empirical Bayesian approach was used to establish the level of confidence associated with the model prediction. Age-corrected estimates of beta cell mass that were inferred from a series of landmark pancreatic autopsy studies significantly correlate (p>0.9995) with contemporary measures of plasma C-peptide levels following onset.Given the correlation between beta cell mass and plasma C-peptide following onset, plasma C-peptide may provide a surrogate measure of beta cell mass in humans. The clinical relevance of this study is that therapeutic strategies that provide an increase in plasma C-peptide over the predicted value for an individual may actually improve beta cell mass. The model predictions may establish a standard historical "control" group - a prior in a Bayesian context - for clinical trials

The Type and the Position of HNF1A Mutation Modulate Age at Diagnosis of Diabetes in Patients with Maturity-Onset Diabetes of the Young (MODY)-3

OBJECTIVE—The clinical expression of maturity-onset diabetes of the young (MODY)-3 is highly variable. This may be due to environmental and/or genetic factors, including molecular characteristics of the hepatocyte nuclear factor 1-α (HNF1A) gene mutation. RESEARCH DESIGN AND METHODS—We analyzed the mutations identified in 356 unrelated MODY3 patients, including 118 novel mutations, and searched for correlations between the genotype and age at diagnosis of diabetes. RESULTS—Missense mutations prevailed in the dimerization and DNA-binding domains (74%), while truncating mutations were predominant in the transactivation domain (62%). The majority (83%) of the mutations were located in exons 1- 6, thus affecting the three HNF1A isoforms. Age at diagnosis of diabetes was lower in patients with truncating mutations than in those with missense mutations (18 vs. 22 years, P = 0.005). Missense mutations affecting the dimerization/DNA-binding domains were associated with a lower age at diagnosis than those affecting the transactivation domain (20 vs. 30 years, P = 10−4). Patients with missense mutations affecting the three isoforms were younger at diagnosis than those with missense mutations involving one or two isoforms (P = 0.03). CONCLUSIONS—These data show that part of the variability of the clinical expression in MODY3 patients may be explained by the type and the location of HNF1A mutations. These findings should be considered in studies for the search of additional modifier genetic factors

Clinical Characteristics and Diagnostic Criteria of Maturity-Onset Diabetes Of The Young (MODY) due to Molecular Anomalies of the HNF1A Gene

Context: The diagnosis of maturity-onset diabetes of the young type 3 (MODY3), associated with HNF1A molecular abnormalities, is often missed.Objective: The objective of the study was to describe the phenotypes of a large series of MODY3 patients and to reassess parameters that may improve its diagnosis. Design, Setting, and Patients: This retrospective multicenter study included 487 unrelated patients referred because of suspicion of MODY3. Genetic analysis identified 196 MODY3 and 283 non-MODY3 cases. Criteria associated with MODY3 were assessed by multivariate analysis. The capacity of the model to predict MODY3 diagnosis was assessed by the area under the receiver-operating characteristic curve and was further validated in an independent sample of 851 patients (165 MODY3 and 686 non-MODY3). Results: In the MODY3 patients, diabetes was revealed by clinical symptoms in 25% of the cases and was diagnosed by screening in the others. Age at diagnosis of diabetes was more than 25 yr in 40% of the MODY3 patients. There was considerable variability and overlap of all assessed parameters in MODY3 and non-MODY3 patients. The best predictive model was based on criteria available at diagnosis of diabetes, including age, body mass index, number of affected generations, presence of diabetes symptoms, and geographical origin. The area under the curve of the receiver-operating characteristic analysis was 0.81. When sensitivity was set to 90%, specificity was 49%. Conclusions: Differential diagnosis between MODY3 and early-onset type 2 diabetes remains difficult. Whether the proposed model will improve the pick-up rate of MODY3 diagnosis needs to be confirmed in independent populations

Type 1 diabetes: translating mechanistic observations into effective clinical outcomes

Type 1 diabetes remains an important health problem, particularly in Western countries where the incidence has been increasing in younger children(1). In 1986, Eisenbarth described Type 1 diabetes as a chronic autoimmune disease. Work over the past 3 ½ decades has identified many of the genetic, immunologic, and environmental factors that are involved in the disease and have led to hypotheses concerning its pathogenesis. Based on these findings, clinical trials have been conducted to test these hypotheses but have had mixed results. In this review, we discuss the findings that have led to current concepts of the disease mechanisms, how this understanding has prompted clinical studies, and the results of these studies. The findings from preclinical and clinical studies support the original proposed model for how type 1 diabetes develops, but have also suggested that this disease is more complex than originally thought and will require broader treatment approaches