Evidence map›Paper›PMID 28841195›Full record

ArticleMetabolites2017

Recommendations for Improving Identification and Quantification in Non-Targeted, GC-MS-Based Metabolomic Profiling of Human Plasma.

Hanghang Wang, Michael J Muehlbauer, Sara K O'Neal, Christopher B Newgard, Elizabeth R Hauser, James R Bain, Svati H Shah

Abstract read
In one paragraph

Article in Metabolites, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Cardiovascular Metabolomics.Circulation research · 2018
    Review
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.

Hanghang WangDuke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701, USA. hanghang.wang@duke.edu.
Michael J MuehlbauerDuke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701, USA. michael.muehlbauer@duke.edu.
Sara K O'NealDuke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701, USA. sara.oneal@duke.edu.
Christopher B NewgardDuke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701, USA. chris.newgard@duke.edu.
Elizabeth R HauserDuke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701, USA. elizabeth.hauser@duke.edu.
James R BainDuke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701, USA. james.bain@duke.edu.
Svati H ShahDuke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 27701, USA. svati.shah@duke.edu.

Funding

Trace the flow of genes in the gut microbiome of obese and lean twin pairsP01DK078669 · NIDDK · WASHINGTON UNIVERSITY · PI GORDON, JEFFREY I · 2007 to 2018
$16.0M
MULTIDISCIPLINARY HEART &VASCULAR DISEASEST32HL007101 · NHLBI · DUKE UNIVERSITY · PI FREEDMAN, NEIL J. · 1985 to 2020
$9.8M
Renal Genomics CoreP30DK096493 · NIDDK · DUKE UNIVERSITY · PI COFFMAN, THOMAS M · 2012 to 2016
$5.9M
NHLBI NIH HHS T32 HL007101NIDDK NIH HHS P01 DK078669NIDDK NIH HHS P30 DK096493
6 · The paper itself

Abstract

The field of metabolomics as applied to human disease and health is rapidly expanding. In recent efforts of metabolomics research, greater emphasis has been placed on quality control and method validation. In this study, we report an experience with quality control and a practical application of method validation. Specifically, we sought to identify and modify steps in gas chromatography-mass spectrometry (GC-MS)-based, non-targeted metabolomic profiling of human plasma that could influence metabolite identification and quantification. Our experimental design included two studies: (1) a limiting-dilution study, which investigated the effects of dilution on analyte identification and quantification; and (2) a concentration-specific study, which compared the optimal plasma extract volume established in the first study with the volume used in the current institutional protocol. We confirmed that contaminants, concentration, repeatability and intermediate precision are major factors influencing metabolite identification and quantification. In addition, we established methods for improved metabolite identification and quantification, which were summarized to provide recommendations for experimental design of GC-MS-based non-targeted profiling of human plasma.

Indexed as

GC-MShuman plasmametabolomic profiling

Identifiers

PMID28841195
PMCPMC5618330

What OpenQuestion holds

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Registered trials

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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.