Effects of nateglinide on the secretion of glycated insulin and glucose tolerance in type 2 diabetes

Aims: Glycation of insulin has been demonstrated within pancreatic beta-cells and the resulting impaired bioactivity may contribute to insulin resistance in diabetes. We used a novel radioimmunoassay to evaluate the effect of nateglinide on plasma concentrations of glycated insulin and glucose tolerance in type 2 diabetes. Methods. Ten patients (5 M/5 F, age 57.8 +/- 1.9 years, HbA(1c), 7.6 +/- 0.5%,, fasting plasma glucose 9.4 +/- 1.2 mmol/l, creatinine 81.6 +/- 4.5 mumol/l) received oral nateglinide 120 mg or placebo, 10 min prior to 75 g oral glucose in a random, single blind, crossover design, 1 week apart. Blood samples were taken for glycated insulin, glucose, insulin and C-peptide over 225 min. Results: Plasma glucose and glycated insulin responses were reduced by 9% (P = 0.005) and 38% (P = 0.047), respectively, following nateglinide compared with placebo. Corresponding AUC measures for insulin and C-peptide were enhanced by 36% (P = 0.005) and 25% (P = 0.007) by nateglinide. Conclusions: Glycated insulin in type 2 diabetes is reduced in response to the insulin secretagogue nateglinide, resulting in preferential release of native insulin. Since glycated insulin exhibits impaired biological activity, reduced glycated insulin release may contribute to the anti hyperglycaemic action of nateglinide. (C) 2003 Elsevier Ireland Ltd. All rights reserved.

Doxorubicin In Vivo Rapidly Alters Expression and Translation of Myocardial Electron Transport Chain Genes, Leads to ATP Loss and Caspase 3 Activation

Background: Doxorubicin is one of the most effective anti-cancer drugs but its use is limited by cumulative cardiotoxicity that restricts lifetime dose. Redox damage is one of the most accepted mechanisms of toxicity, but not fully substantiated. Moreover doxorubicin is not an efficient redox cycling compound due to its low redox potential. Here we used genomic and chemical systems approaches in vivo to investigate the mechanisms of doxorubicin cardiotoxicity, and specifically test the hypothesis of redox cycling mediated cardiotoxicity.

Association analysis of Notch pathway signalling genes in diabetic nephropathy

Several studies have provided compelling evidence implicating the Notch signalling pathway in diabetic nephropathy. Co-regulation of Notch signalling pathway genes with GREM1 has recently been demonstrated and several genes involved in the Notch pathway are differentially expressed in kidney biopsies from individuals with diabetic nephropathy. We assessed single-nucleotide polymorphisms (SNPs; n = 42) in four of these key genes (JAG1, HES1, NOTCH3 and ADAM10) for association with diabetic nephropathy using a case-control design.
Tag SNPs and potentially functional SNPs were genotyped using Sequenom or Taqman technologies in a total of 1371 individuals with type 1 diabetes (668 patients with nephropathy and 703 controls without nephropathy). Patients and controls were white and recruited from the UK and Ireland. Association analyses were performed using PLINK (http://pngu.mgh.harvard.edu/similar to purcell/plink/) and haplotype frequencies in patients and controls were compared. Adjustment for multiple testing was performed by permutation testing.
In analyses stratified by centre, we identified six SNPs, rs8708 and rs11699674 (JAG1), rs10423702 and rs1548555 (NOTCH3), rs2054096 and rs8027998 (ADAM10) as being associated with diabetic nephropathy before, but not after, adjustment for multiple testing. Haplotype and subgroup analysis according to duration of diabetes also failed to find an association with diabetic nephropathy.
Our results suggest that common variants in JAG1, HES1, NOTCH3 and ADAM10 are not strongly associated with diabetic nephropathy in type 1 diabetes among white individuals. Our findings, however, cannot entirely exclude these genes from involvement in the pathogenesis of diabetic nephropathy.

Harnessing naturally randomized transcription to infer regulatory relationships among genes

We develop an approach utilizing randomized genotypes to rigorously infer causal regulatory relationships among genes at the transcriptional level, based on experiments in which genotyping and expression profiling are performed. This approach can be used to build transcriptional regulatory networks and to identify putative regulators of genes. We apply the method to an experiment in yeast, in which genes known to be in the same processes and functions are recovered in the resulting transcriptional regulatory network.