Evidence map›Paper›PMID 17488363›Full record

Trial reportBritish journal of clinical pharmacology2007

Evaluation of metabolite profiles as biomarkers for the pharmacological effects of thiazolidinediones in Type 2 diabetes mellitus patients and healthy volunteers.

Martijn van Doorn, Jack Vogels, Albert Tas, Ewoud Jan van Hoogdalem, Jacobus Burggraaf, Adam Cohen, Jan van der Greef

Open access · bronzeAbstract readRandomized Controlled Trial
In one paragraph

Trial report in British journal of clinical pharmacology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
3.3field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed, 125 citations in OpenAlex.

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  15. The serum metabolomics signature of type 2 diabetes is obscured in Alzheimer's disease.American journal of physiology. Endocrinology and metabolism · 2018
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Martijn van DoornCentre for Human Drug Research, Leiden, The Netherlands. mdoorn@chdr.nl
Jack Vogels
Albert Tas
Ewoud Jan van Hoogdalem
Jacobus Burggraaf
Adam Cohen
Jan van der Greef
Centre for Human Drug Research · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

what is already known about this subject* 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. WHAT THIS STUDY ADDS: * 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.

aimsTo 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.

methods(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.

resultsRSG 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.

conclusionThe 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.

Indexed as

AdultAgedBiomarkersBlood GlucoseDiabetes Mellitus, Type 2Double-Blind MethodFemaleHumansHypoglycemic AgentsMagnetic Resonance SpectroscopyMaleMiddle AgedPrincipal Component AnalysisRosiglitazoneThiazolidinedionesBiomarkersBlood GlucoseHypoglycemic AgentsRosiglitazoneThiazolidinediones

Identifiers

PMID17488363
PMCPMC2000756
OpenAlexW2091084261

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.