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

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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

DOI 10.1002/jssc.200900152

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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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Authors: Issaq, H. J., Van, Q. N., Waybright, T. J., Muschik, G. M., & Veenstra, T. D.
Affiliations: National Cancer Institute (US)
ORCID: Van, Que N.
Waybright, Timothy J.
Veenstra, Timothy D.
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
DOI: 10.1002/jssc.200900152
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
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor)
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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Analytical and statistical approaches to metabolomics research

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