Evidence map›Paper›PMID 25411574›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2014

Validation of a dual LC-HRMS platform for clinical metabolic diagnosis in serum, bridging quantitative analysis and untargeted metabolomics.

Ilya Gertsman, Jon A Gangoiti, Bruce A Barshop

Abstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Review
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  6. Review
  7. Article
  8. Observational
  9. Article
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  15. Article
  16. Promises and pitfalls of untargeted metabolomics.Journal of inherited metabolic disease · 2018
    Review
  17. Article
  18. Article
  19. Review
  20. 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

3 authors.

Ilya GertsmanBiochemical Genetics Lab, University of California, San Diego. 9500 Gilman Dr. La Jolla, CA 92093.
Jon A GangoitiBiochemical Genetics Lab, University of California, San Diego. 9500 Gilman Dr. La Jolla, CA 92093.
Bruce A BarshopBiochemical Genetics Lab, University of California, San Diego. 9500 Gilman Dr. La Jolla, CA 92093.

Funding

Genetic Factors Involving Expression of 3-Methylcrotonyl-CoA Carboxylase DeficienR03HD069983 · NICHD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BARSHOP, BRUCE A · 2011 to 2012
$155k
NICHD NIH HHS R03 HD069983
6 · The paper itself

Abstract

Mass spectrometry-based metabolomics is a rapidly growing field in both research and diagnosis. Generally, the methodologies and types of instruments used for clinical and other absolute quantification experiments are different from those used for biomarkers discovery and untargeted analysis, as the former requires optimal sensitivity and dynamic range, while the latter requires high resolution and high mass accuracy. We used a Q-TOF mass spectrometer with two different types of pentafluorophenyl (PFP) stationary phases, employing both positive and negative ionization, to develop and validate a hybrid quantification and discovery platform using LC-HRMS. This dual-PFP LC-MS platform quantifies over 50 clinically relevant metabolites in serum (using both MS and MS/MS acquisitions) while simultaneously collecting high resolution and high mass accuracy full scans to monitor all other co-eluting non-targeted analytes. We demonstrate that the linearity, accuracy, and precision results for the quantification of a number of metabolites, including amino acids, organic acids, acylcarnitines and purines/pyrimidines, meets or exceeds normal bioanalytical standards over their respective physiological ranges. The chromatography resolved highly polar as well as hydrophobic analytes under reverse-phase conditions, enabling analysis of a wide range of chemicals, necessary for untargeted metabolomics experiments. Though previous LC-HRMS methods have demonstrated quantification capabilities for various drug and small molecule compounds, the present study provides an HRMS quant/qual platform tailored to metabolic disease; and covers a multitude of different metabolites including compounds normally quantified by a combination of separate instrumentation.

Indexed as

bioanalytical validationcomprehensive metabolite profilingLC-HRMSmass spectrometryQ-TOFtargeted metabolomicsuntargeted metabolomics

Identifiers

PMID25411574
PMCPMC4234038

What OpenQuestion holds

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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.