Evidence map›Paper›PMID 25261439›Full record

Observational studyJournal of diabetes science and technology2015

A novel test for IGT utilizing metabolite markers of glucose tolerance.

Jeff Cobb, Andrea Eckhart, Regis Perichon, Jacob Wulff, Matthew Mitchell, Klaus-Peter Adam, Robert Wolfert, Eric Button, Kay Lawton, Robert Elverson and 3 more

Open access · bronzeAbstract readObservational Study
In one paragraph

Observational study in Journal of diabetes science and technology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 15% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Review
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  7. Article
  8. D-Serine: A Cross Species Review of Safety.Frontiers in psychiatry · 2021
    Review
  9. Review of methods for detecting glycemic disorders.Diabetes research and clinical practice · 2020
    Review
  10. Article
  11. Article
  12. Article
  13. Observational
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 3 institutions in 3 countries.

Jeff CobbMetabolon, Inc, Durham, NC, USA jcobb@metabolon.com.
Andrea EckhartMetabolon, Inc, Durham, NC, USA.
Regis PerichonMetabolon, Inc, Durham, NC, USA.
Jacob WulffMetabolon, Inc, Durham, NC, USA.
Matthew MitchellMetabolon, Inc, Durham, NC, USA.
Klaus-Peter AdamMetabolon, Inc, Durham, NC, USA.
Robert WolfertMetabolon, Inc, Durham, NC, USA.
Eric ButtonMetabolon, Inc, Durham, NC, USA.
Kay LawtonMetabolon, Inc, Durham, NC, USA.
Robert ElversonMetabolon, Inc, Durham, NC, USA.
Bernadette CarrVhi Healthcare, Dublin, Ireland.
Margaret SinnottVhi Healthcare, Dublin, Ireland Deceased.
Ele FerranniniDepartment of Internal Medicine, University of Pisa, Pisa, Italy.
Metabolon (United States) · USVhi Healthcare · IEUniversity of Pisa · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The oral glucose tolerance test (OGTT) is the only method to diagnose patients having impaired glucose tolerance (IGT), but its use has diminished considerably in recent years. Metabolomic profiling studies have identified a number of metabolites whose fasting levels are associated with dysglycemia and type 2 diabetes. These metabolites may serve as the basis of an alternative test for IGT. Using the stable isotope dilution technique, quantitative assays were developed for 23 candidate biomarker metabolites. These metabolites were measured in fasting plasma samples taken just prior to an OGTT from 1623 nondiabetic subjects: 955 from the Relationship between Insulin Sensitivity and Cardiovascular Disease Study (RISC Study; 11.7% IGT) and 668 subjects from the Diabetes Mellitus and Vascular Health Initiative (DMVhi) cohort from the DEXLIFE project (11.8% IGT). The associations between metabolites, anthropometric, and metabolic parameters and 2hPG values were assessed by Pearson correlation coefficients and Random Forest classification analysis to rank variables for their ability to distinguish IGT from normal glucose tolerance (NGT). Multivariate logistic regression models for estimating risk of IGT were developed and evaluated using AUCs calculated from the corresponding ROC curves. A model based on the fasting plasma levels of glucose, α-hydroxybutyric acid, β-hydroxybutyric acid, 4-methyl-2-oxopentanoic acid, linoleoylglycerophosphocholine, oleic acid, serine and vitamin B5 was optimized in the RISC cohort (AUC = 0.82) and validated in the DMVhi cohort (AUC = 0.83). A novel, all-metabolite-based test is shown to be a discriminate marker of IGT. It requires only a single fasted blood draw and may serve as a more convenient surrogate for the OGTT or as a means of identifying subjects likely to be IGT.

Indexed as

Insulin ResistanceAdultAgedBiomarkersBlood GlucoseCardiovascular DiseasesCohort StudiesDiabetes Mellitus, Type 2FemaleGlucose IntoleranceGlucose Tolerance TestHumansMaleMiddle AgedPredictive Value of TestsRisk FactorsBiomarkersBlood GlucosebiomarkersIGTmetabolomicsOGTT

Identifiers

PMID25261439
PMCPMC4495543
OpenAlexW2099128606

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.