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We describe 2 families with 5 members from 2 generations whose clinical and laboratory characteristics over up to 15 years were consistent with dysglycemia/impaired glucose tolerance. In both families (2 probands and 3 family members), long-term follow-up excluded diabetes type 1 and type 2. Diabetes type 1 antibodies were persistently negative and C-peptide levels were normal. In Family 1, the proband, during a follow-up of 7 years (10.3-17.5 years of age), exhibited persistently high HbA1c (>5.7%) with fasting blood glucose levels mostly higher than 100 mg/dl and postprandial glucose levels up to 180 mg/dl. She eventually required oral anti-diabetics with an improvement in glycemic balance. The father and sister also had persistent mild hyperglycemia with borderline high HbA1c (mostly > 5.7%) levels over 15 and 6.2 years respectively. In Family 2, the proband exhibited borderline high fasting hyperglycemia (>100 mg/dl) at age 16.2 years with increasing HbA1c levels (from 5.6%–5.9%) and impaired glucose tolerance at age 18.3 years (2 h blood glucose 156 mg/dl after 75 g glucose). His sister also exhibited borderline hyperglycemia with borderline high HbA1c over 2 years (13.6-15.4 years). These subjects shared a unique phenotype. They are tall and slim with decreased BMI. Three subjects from Generation II failed to thrive during infancy. In view of the data from 2 generations suggesting maturity-onset diabetes of the young (MODY) with autosomal dominant inheritance, we sought to analyze the MODY genes. In Family 1, the molecular analysis by the MODY panel including 11 genes and whole exome sequencing did not detect any mutation in the proband. In Family 2, the MODY panel was also negative in the proband’s sister. These families may represent a hitherto unidentified syndrome. Unique features described in this report may help to reveal additional families with similar characteristics and to decipher the molecular basis of this syndrome. In selected cases, oral antidiabetics in adolescents may improve the glycemic balance.

Abstract Background Diabetes mellitus (DM) is a prevalent metabolic disease characterized by chronic hyperglycemia. A primary burden of DM is related to its long-term complications, which have been shown to impact the course of hospitalization and to influence patients’ outcome. Aim To assess the role of in-hospital glucose control on length of stay, 30-days and 1-year mortality. Methods This is a retrospective study that included patients admitted to the cardiac intensive care unit (CICU) of the Edith Wolfson Medical Centre between 01 January, 2010 and 31 December 2013. Blood glucose was measured by glucometer and fed into an interactive database. Glucose status was referred to as controlled when more than 50% of a given patients glucose values were between 71 and 200 mg/dL. Chisquared tests were used to assess the distribution of categorical variables, while the ttest was applied for continuous variables. A multivariate logistic regression model was used to analyze the association between glucose control and mortality. Cox regression was conducted to assess survival and 1-year mortality. Results 2466 patients were admitted to the CICU over the study period, of which 370 had concomitant diabetes mellitus. Controlled glucose status was associated with shorter length of hospital stay (1.6 ± 1.7 versus 2.6 ± 3.0, p

AIMS: The tendency to develop diabetic nephropathy is, in part, genetically determined, however this genetic risk is largely undefined. In this proof-of-concept study, we tested the hypothesis that combined analysis of multiple genetic variants can improve prediction. METHODS: Based on previous reports, we selected 27 SNPs in 15 genes from metabolic pathways involved in the pathogenesis of diabetic nephropathy and genotyped them in 1274 Ashkenazi or Sephardic Jewish patients with Type 1 or Type 2 diabetes of >10 years duration. A logistic regression model was built using a backward selection algorithm and SNPs nominally associated with nephropathy in our population. The model was validated by using random "training" (75%) and "test" (25%) subgroups of the original population and by applying the model to an independent dataset of 848 Ashkenazi patients. RESULTS: The logistic model based on 5 SNPs in 5 genes (HSPG2, NOS3, ADIPOR2, AGER, and CCL5) and 5 conventional variables (age, sex, ethnicity, diabetes type and duration), and allowing for all possible two-way interactions, predicted nephropathy in our initial population (C-statistic = 0.672) better than a model based on conventional variables only (C = 0.569). In the independent replication dataset, although the C-statistic of the genetic model decreased (0.576), it remained highly associated with diabetic nephropathy (χ(2) = 17.79, p

Evidence has accumulated that multiple genetic and environmental factors play important roles in determining susceptibility to type 2 diabetes (T2D). Although variants from candidate genes have become prime targets for genetic analysis, few studies have considered their interplay. Our goal was to evaluate interactions among SNPs within genes frequently identified as associated with T2D.Logistic regression was used to study interactions among 4 SNPs, one each from HNF4A[rs1884613], TCF7L2[rs12255372], WFS1[rs10010131], and KCNJ11[rs5219] in a case-control Ashkenazi sample of 974 diabetic subjects and 896 controls. Nonparametric multifactor dimensionality reduction (MDR) and generalized MDR (GMDR) were used to confirm findings from the logistic regression analysis. HNF4A and WFS1 SNPs were associated with T2D in logistic regression analyses [P