Abstract

* Many studies have investigated the effects of thiazolidinediones on isolated biochemical markers (biomarkers) or sets of markers in Type 2 diabetes mellitus (T2DM) patients and healthy volunteers. * However, a limited number of parameters is not capable of capturing the broad response to pharmacological intervention with these types of (pleiotropic) drugs, which are known to activate the nuclear transcription factor peroxisome proliferator activated receptor gamma (PPARgamma). * Our study tested the new hypothesis (primary objective) that nuclear magnetic resonance (NMR)-based metabolomics, capable of providing a readout of global metabolite concentrations in biofluids, could provide a better (more holistic) picture of the the multiparametric response to pharmacological intervention with a PPARgamma agonist and thus yield a broad array of biomarkers ('fingerprint') that could be used to support and expedite clinical development of novel thiazolidinediones. * NMR-based metabolomics coupled with sophisticated bioinformatics is indeed capable of identifying rapid changes in global metabolite profiles in urine and plasma (treatment 'fingerprints'), which may be linked to the well-documented early changes in hepatic insulin senstitivity following thiazolidinedione intervention in T2DM patients. * Consequently, this approach (upon proper validation) comprises an important new addition to the early clinical development 'proof of concept' toolbox for thiazolidinediones, and may also be applicable to other classes of drugs. To explore the usefulness of metabolomics as a method to obtain a broad array of biomarkers for the pharmacological effects of rosiglitazone (RSG) in plasma and urine samples from patients with type 2 diabetes mellitus (T2DM) and healthy volunteers (HVs). Additionally, we explored the differences in metabolite concentrations between T2DM patients and HVs to identify a putative metabolic disease fingerprint for T2DM. (1)H nuclear magnetic resonance (NMR) spectroscopy was used to profile blood plasma and urine samples of 16 T2DM patients and 16 HVs receiving RSG 4 mg or placebo twice daily for 6 weeks. Multivariate analyses were employed to identify treatment- and disease-related effects on global endogenous metabolite profiles. RSG treatment led to a rapid relative reduction in urinary hippurate and aromatic amino acids as well as an increase in plasma branched chain amino acids and alanine, glutamine and glutamate in the T2DM group. No RSG treatment effects were noted in the HV group. Exploratory baseline analyses showed that urine and plasma metabolites discriminated between genders and disease state. T2DM patients showed a relative increase in urinary concentrations of several amino acids, citrate, phospho(enol)pyruvate and hippurate. Putative T2DM-related changes in plasma were largely attributable to increased plasma lipids. The results of this study indicate that NMR-based metabolomics of urine and blood plasma samples can yield a broad array of early responding biomarkers for the effects of RSG in T2DM patients, as well as nonglucose biomarkers that may reflect the T2DM state.

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