Cited by 227Metabolomics and Mass Spectrometry StudiesAdvanced Chemical Sensor TechnologiesSpectroscopy and Chemometric Analyses

Analytical and statistical approaches to metabolomics research

Issaq, Haleem J., Van, Que N., Waybright, Timothy J., Muschik, Gary M., Veenstra, Timothy D.·2009·Journal of Separation Science

Abstract

Metabolomics, the global profiling of metabolites in different living systems, has experienced a rekindling of interest partially due to the improved detection capabilities of the instrumental techniques currently being used in this area of biomedical research. The analytical methods of choice for the analysis of metabolites in search of disease biomarkers in biological specimens, and for the study of various low molecular weight metabolic pathways include NMR spectroscopy, GC/MS, CE/MS, and HPLC/MS. Global metabolite analysis and profiling of two different sets of data results in a plethora of data that is difficult to manage or interpret manually because of their subtle differences. Multivariate statistical methods and pattern-recognition programs were developed to handle the acquired data and to search for the discriminating features between data acquired from two sample sets, healthy and diseased. Metabolomics have been used in toxicology, plant physiology, and biomedical research. In this paper, we discuss various aspects of metabolomic research including sample collection, handling, storage, requirements for sample analysis, peak alignment, data interpretation using statistical approaches, metabolite identification, and finally recommendations for successful analysis.

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Crossref · 10.1002/jssc.200900152

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  • NMR is robust, nondestructive, and quantitative but has relatively low sensitivity, limiting its coverage of the food metabolome to predominant nutrients, sugars, and microbial metabolites at millimolar to micromolar concentrations.

    “Briefly, NMR is robust, nondestructive, and quantitative but has a relatively low sensitivity, which narrows its coverage of the food metabolome to predominant nutrients, sugars, and microbial metabolites present at millimolar to micromolar concentrations.”

    From The food metabolome: a window over dietary exposure (2014) · cites this paper as [113]

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Authors
Issaq, H. J., Van, Q. N., Waybright, T. J., Muschik, G. M., & Veenstra, T. D.
Affiliations
National Cancer Institute (US)
Venue
Journal of Separation Science
Publisher
Wiley
Published
2009-06-30
Volume
32
Issue
13
Pages
2183-2199
ISSN
  • 1615-9306 (ISSN-L)
  • 1615-9314
OpenAlex
W2103773262
Cited by
227
References
133
Citations by year
2026: 4 · 2025: 12 · 2024: 8 · 2023: 7 · 2022: 6 · 2021: 11 · 2020: 4 · 2019: 17 · 2018: 6 · 2017: 7 · 2016: 11 · 2015: 15 · 2014: 27 · 2013: 22 · 2012: 18
FWCI
1.76
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Separation Science (publishedVersion)
  • PubMed (publishedVersion)
  • DigitalCommons-Cedarville (Cedarville University) (submittedVersion)
Funders
National Cancer Institute, National Institutes of Health (HHSN261200800001E)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
  • Physical Sciences › Engineering › Biomedical Engineering › Advanced Chemical Sensor Technologies
  • Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
Keywords
metabolomics, multivariate analysis, pattern recognition, disease biomarkers, metabolite profiling, sample collection and storage, peak alignment, metabolite identification, NMR spectroscopy, gas chromatography-mass spectrometry, HPLC-MS, capillary electrophoresis-mass spectrometry, toxicology, plant physiology
MeSH terms
Chromatography, High Pressure Liquid, Humans, Gas Chromatography-Mass Spectrometry, Software, Specimen Handling, Biomarkers, Electrophoresis, Capillary, Nuclear Magnetic Resonance, Biomolecular, Biomedical Research, Metabolomics

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