The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Development and Performance of a Gas Chromatography−Time-of-Flight Mass Spectrometry Analysis for Large-Scale Nontargeted Metabolomic Studies of Human Serum
Abstract
A method for the preparation and GC-TOF-MS analysis of human serum samples has been developed and evaluated for application in long-term metabolomic studies. Serum samples were deproteinized using 3:1 methanol/serum, dried in a vacuum concentrator, and chemically derivatized in a two-stage process. Samples were analyzed by GC-TOF-MS with a 25 min analysis time. In addition, quality control (QC) samples were used to quantify process variability. Optimization of chemical derivatization was performed. Products were found to be stable for 30 h after derivatization. An assessment of within-day repeatability and within-week reproducibility demonstrates that excellent performance is observed with our developed method. Analyses were consistent over a 5 month period. Additional method testing, using spiked serum samples, showed the ability to define metabolite differences between samples from a population and samples spiked with metabolites standards. This methodology allows the continuous acquisition and application of data acquired over many months in long-term metabolomic studies, including the HUSERMET project (http://www.husermet.org/).
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Sumner, L. W., Amberg, A., Barrett, D., Beale, M. H., Beger, R., Daykin, C. A., Fan, T. W.-M., Fiehn, O., Goodacre, R., Griffin, J. L., et al. (2007) · Metabolomics · doi:10.1007/s11306-007-0082-2 · Cited by 5,368
Self-citationGenetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum
Gieger, C., Geistlinger, L., Altmaier, E., Hrabé de Angelis, M., Kronenberg, F., Meitinger, T., Mewes, H.-W., Wichmann, H.-E., Weinberger, K. M., Adamski, J., et al. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000282 · Cited by 737
Atherton, H. J., Bailey, N. J., Zhang, W., Taylor, J., Major, H., Shockcor, J., Clarke, K., & Griffin, J. L. (2006) · Physiological Genomics · doi:10.1152/physiolgenomics.00060.2006 · Cited by 159
Cited by
The Human Serum Metabolome (HUSERMET) Consortium, Dunn, W. B., Broadhurst, D., Begley, P., Zelena, E., Francis-McIntyre, S., Anderson, N., Brown, M., Knowles, J. D., Halsall, A., et al. (2011) · Nature Protocols · doi:10.1038/nprot.2011.335 · Cited by 3,294
Self-citationCurrent approaches and challenges for the metabolite profiling of complex natural extracts
Wolfender, J.-L., Marti, G., Thomas, A., & Bertrand, S. (2015) · Journal of Chromatography A · doi:10.1016/j.chroma.2014.10.091 · Cited by 635
Mass Spectrometry Strategies in Metabolomics
Lei, Z., Huhman, D. V., & Sumner, L. W. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.r111.238691 · Cited by 481
Kuehnbaum, N. L., & Britz-McKibbin, P. (2013) · Chemical Reviews · doi:10.1021/cr300484s · Cited by 354
Quality assurance procedures for mass spectrometry untargeted metabolomics. a review
Dudzik, D., Barbas-Bernardos, C., García, A., & Barbas, C. (2018) · Journal of Pharmaceutical and Biomedical Analysis · doi:10.1016/j.jpba.2017.07.044 · Cited by 344
Mass spectrometric based approaches in urine metabolomics and biomarker discovery
Khamis, M. M., Adamko, D. J., & El‐Aneed, A. (2017) · Mass Spectrometry Reviews · doi:10.1002/mas.21455 · Cited by 342
A cheminformatics approach to characterize metabolomes in stable-isotope-labeled organisms
Tsugawa, H., Nakabayashi, R., Mori, T., Yamada, Y., Takahashi, M., Rai, A., Sugiyama, R., Yamamoto, H., Nakaya, T., Yamazaki, M., et al. (2019) · Nature Methods · doi:10.1038/s41592-019-0358-2 · Cited by 299
A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes
Smallbone, K., Messiha, H. L., Carroll, K. M., Winder, C. L., Malys, N., Dunn, W. B., Murabito, E., Swainston, N., Dada, J. O., Khan, F., et al. (2013) · FEBS Letters · doi:10.1016/j.febslet.2013.06.043 · Cited by 147
Self-citationRattray, N. J. W., Trivedi, D. K., Xu, Y., Chandola, T., Johnson, C. H., Marshall, A. D., Mekli, K., Rattray, Z., Tampubolon, G., Vanhoutte, B., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12716-2 · Cited by 101
Self-citationXu, J., Begley, P., Church, S. J., Patassini, S., McHarg, S., Kureishy, N., Hollywood, K. A., Waldvogel, H. J., Liu, H., Zhang, S., et al. (2016) · Scientific Reports · doi:10.1038/srep27524 · Cited by 85
Self-citationGonzález-Domínguez, R., García-Barrera, T., Vitorica, J., & Gómez-Ariza, J. L. (2015) · Biochimie · doi:10.1016/j.biochi.2015.01.005 · Cited by 49
Multiomics Implicate Gut Microbiota in Altered Lipid and Energy Metabolism in Parkinson’s Disease
Pereira, P. A. B., Trivedi, D. K., Silverman, J., Duru, I. C., Paulin, L., Auvinen, P., & Scheperjans, F. (2022) · npj Parkinson s Disease · doi:10.1038/s41531-022-00300-3 · Cited by 40
Metadata
- Authors
- Begley, P., Francis-McIntyre, S., Dunn, W. B., Broadhurst, D. I., Halsall, A., Tseng, A., Knowles, J., HUSERMET Consortium, Goodacre, R., & Kell, D. B.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2009-07-16
- Volume
- 81
- Issue
- 16
- Pages
- 7038-7046
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W1978346875
- Cited by
- 189
- References
- 3
- FWCI
- 3.84
- Type
- journal article
- Language
- en
- Open access
- closed
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