Interlaboratory Reproducibility of a Targeted Metabolomics Platform for Analysis of Human Serum and Plasma
Open accessAbstract
A critical question facing the field of metabolomics is whether data obtained from different centers can be effectively compared and combined. An important aspect of this is the interlaboratory precision (reproducibility) of the analytical protocols used. We analyzed human samples in six laboratories using different instrumentation but a common protocol (the AbsoluteIDQ p180 kit) for the measurement of 189 metabolites via liquid chromatography (LC) or flow injection analysis (FIA) coupled to tandem mass spectrometry (MS/MS). In spiked quality control (QC) samples 82% of metabolite measurements had an interlaboratory precision of <20%, while 83% of averaged individual laboratory measurements were accurate to within 20%. For 20 typical biological samples (serum and plasma from healthy individuals) the median interlaboratory coefficient of variation (CV) was 7.6%, with 85% of metabolites exhibiting a median interlaboratory CV of <20%. Precision was largely independent of the type of sample (serum or plasma) or the anticoagulant used but was reduced in a sample from a patient with dyslipidaemia. The median interlaboratory accuracy and precision of the assay for standard reference plasma (NIST SRM 1950) were 107% and 6.7%, respectively. Likely sources of irreproducibility were the near limit of detection (LOD) typical abundance of some metabolites and the degree of manual review and optimization of peak integration in the LC-MS/MS data after acquisition. Normalization to a reference material was crucial for the semi-quantitative FIA measurements. This is the first interlaboratory assessment of a widely used, targeted metabolomics assay illustrating the reproducibility of the protocol and how data generated on different instruments could be directly integrated in large-scale epidemiological studies.
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The targeted metabolomics approach used is quantitative and reliable and can be more readily confirmed and validated in other laboratories compared with whole-metabolome analyses.
“While our targeted approach is restrictive in that regard, it is quantitative and reliable (39) and, compared with whole-metabolome analyses, can be more readily confirmed and validated in other laboratories.”
From Separation of circadian- and behavior-driven metabolite rhythms in humans provides a window on peripheral oscillators and metabolism (2018) · cites this paper as [39]
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Cites
Nicholson, J. K., Lindon, J. C., & Holmes, E. C. (1999) · Xenobiotica · doi:10.1080/004982599238047 · Cited by 3,903 · see citing works
Metabolomics—the link between genotypes and phenotypes
Fiehn, O. (2002) · Plant Molecular Biology · doi:10.1023/a:1013713905833 · Cited by 3,445 · see citing works
Metabolomics — the link between genotypes and phenotypes
Fiehn, O. (2002) · Springer eBooks · doi:10.1007/978-94-010-0448-0_11 · Cited by 3,168 · see citing works
Metabolomics--the link between genotypes and phenotypes.
Fiehn, O. (2002) · PubMed · Cited by 1,517 · see citing works
Floegel, A., Stefan, N., Yu, Z., Mühlenbruch, K., Drogan, D., Joost, H.-G., Fritsche, A., Häring, H.-U., Hrabě de Angelis, M., Peters, A., et al. (2013) · Diabetes · doi:10.2337/db12-0495 · Cited by 988 · see citing works
Self-citationNovel biomarkers for pre-diabetes identified by metabolomics
Wang‐Sattler, R., Yu, Z., Herder, C., Messias, A. C., Floegel, A., He, Y., Heim, K., Campillos, M., Holzapfel, C., Thorand, B., et al. (2012) · Molecular Systems Biology · doi:10.1038/msb.2012.43 · Cited by 701 · see citing works
Self-citationA genome-wide perspective of genetic variation in human metabolism
Illig, T., Gieger, C., Zhai, G., Römisch-Margl, W., Wang-Sattler, R., Prehn, C., Altmaier, E., Kastenmüller, G., Kato, B. S., Mewes, H.-W., et al. (2010) · Nature Genetics · doi:10.1038/ng.507 · Cited by 653 · see citing works
Self-citationMetabolic Footprint of Diabetes: A Multiplatform Metabolomics Study in an Epidemiological Setting
Suhre, K., Meisinger, C., Döring, A., Altmaier, E., Belcredi, P., Gieger, C., Chang, D., Milburn, M. V., Gall, W. E., Weinberger, K. M., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013953 · Cited by 557 · see citing works
Self-citationEffect of sleep deprivation on the human metabolome
Davies, S. K., Ang, J. E., Revell, V. L., Holmes, B., Mann, A., Robertson, F. P., Cui, N., Middleton, B., Ackermann, K., Kayser, M., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1402663111 · Cited by 527 · see citing works
Self-citationDifferences between Human Plasma and Serum Metabolite Profiles
Yu, Z., Kastenmüller, G., He, Y., Belcredi, P., Möller, G., Prehn, C. P., Mendes, J., Wahl, S., Roemisch‐Margl, W., Ceglarek, U., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021230 · Cited by 496 · see citing works
Self-citationSchmidt, J. A., Rinaldi, S., Scalbert, A., Ferrari, P., Achaintre, D., Gunter, M. J., Appleby, P. N., Key, T. J., & Travis, R. C. (2016) · European Journal of Clinical Nutrition · doi:10.1038/ejcn.2015.144 · Cited by 349 · see citing works
Self-citationHuman serum metabolic profiles are age dependent
Yu, Z., Zhai, G., Singmann, P., He, Y., Xu, T., Prehn, C., Römisch‐Margl, W., Lattka, E., Gieger, C., Soranzo, N., et al. (2012) · Aging Cell · doi:10.1111/j.1474-9726.2012.00865.x · Cited by 340 · see citing works
Self-citationSimón‐Manso, Y., Lowenthal, M. S., Kilpatrick, L. E., Sampson, M. L., Telu, K. H., Rudnick, P. A., Mallard, W. G., Bearden, D. W., Schock, T. B., Tchekhovskoi, D. V., et al. (2013) · Analytical Chemistry · doi:10.1021/ac402503m · Cited by 298 · see citing works
Analytical Reproducibility in 1H NMR-Based Metabonomic Urinalysis
Keun, H. C., Ebbels, T. M. D., Antti, H., Bollard, M. E., Beckonert, O. P., Schlotterbeck, G., Senn, H., Niederhauser, U., Holmes, E. C., Lindon, J. C., et al. (2002) · Chemical Research in Toxicology · doi:10.1021/tx0255774 · Cited by 247 · see citing works
Self-citationKuhn, T. E., Floegel, A., Sookthai, D., Johnson, T., Rolle-Kampczyk, U. E., Otto, W., von Bergen�, M., Boeing, H., & Kaaks, R. (2016) · BMC Medicine · doi:10.1186/s12916-016-0552-3 · Cited by 241 · see citing works
Targeted Metabolomics Identifies Reliable and Stable Metabolites in Human Serum and Plasma Samples
Breier, M., Wahl, S., Prehn, C. P., Fugmann, M., Ferrari, U., Weise, M., Banning, F., Seißler, J., Grallert, H., Adamski, J., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0089728 · Cited by 240 · see citing works
Self-citationInternational NMR-Based Environmental Metabolomics Intercomparison Exercise
Viant, M. R., Bearden, D. W., Bundy, J. G., Burton, I. W., Collette, T. W., Ekman, D. R., Ezernieks, V., Karakach, T. K., Lin, C., Rochfort, S. J., et al. (2008) · Environmental Science & Technology · doi:10.1021/es802198z · Cited by 155 · see citing works
Xu, T., Holzapfel, C., Dong, X., Bader, E., Yu, Z., Prehn, C. P., Perstorfer, K., Jaremek, M., Roemisch‐Margl, W., Rathmann, W., et al. (2013) · BMC Medicine · doi:10.1186/1741-7015-11-60 · Cited by 140 · see citing works
Self-citationCarayol, M., Licaj, I., Achaintre, D., Sacerdote, C., Vineis, P., Key, T. J., Onland‐Moret, N. C., Scalbert, A., Rinaldi, S., & Ferrari, P. (2015) · PLoS ONE · doi:10.1371/journal.pone.0135437 · Cited by 139 · see citing works
Self-citationNicholson, G., Rantalainen, M., Li, J. V., Maher, A. D., Malmodin, D., Ahmadi, K. R., Faber, J. H., Barrett, A., Min, J. L., Rayner, N. W., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002270 · Cited by 136 · see citing works
Self-citationFloegel, A., Drogan, D., Wang-Sattler, R., Prehn, C., Illig, T., Adamski, J., Joost, H.-G., Boeing, H., & Pischon, T. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021103 · Cited by 135 · see citing works
Martin, J., Maillot, M., Mazerolles, G., Verdu, A., Lyan, B., Migné, C., Defoort, C., Canlet, C., Junot, C., gualbert, G. C., et al. (2014) · Metabolomics · doi:10.1007/s11306-014-0740-0 · Cited by 129 · see citing works
Development of a Standard Reference Material for Metabolomics Research
Phinney, K. W., Ballihaut, G., Bedner, M., Benford, B. S., Camara, J. E., Christopher, S. J., Davis, W. C., Dodder, N. G., Eppe, G., Lang, B. E., et al. (2013) · Analytical Chemistry · doi:10.1021/ac402689t · Cited by 128 · see citing works
Allwood, J. W., Erban, A., de Koning, S., Dunn, W. B., Luedemann, A., Lommen, A., Kay, L., Löscher, R., Kopka, J., & Goodacre, R. (2009) · Metabolomics · doi:10.1007/s11306-009-0169-z · Cited by 125 · see citing works
Anton, G., Wilson, R., Yu, Z., Prehn, C. P., Zukunft, S., Adamski, J., Heier, M., Meisinger, C., Römisch‐Margl, W., Wang‐Sattler, R., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0121495 · Cited by 113 · see citing works
Self-citationBody Fat Free Mass Is Associated with the Serum Metabolite Profile in a Population-Based Study
Jourdan, C., Petersen, A.-K., Gieger, C., Döring, A., Illig, T., Wang‐Sattler, R., Meisinger, C., Peters, A., Adamski, J., Prehn, C. P., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0040009 · Cited by 107 · see citing works
Self-citationWard, J. L., Baker, J. M., Miller, S. J., et al. (2010) · Metabolomics · doi:10.1007/s11306-010-0200-4 · Cited by 106 · see citing works
Floegel, A., Wientzek, A., Bachlechner, U., Jacobs, S., Drogan, D., Prehn, C. P., Adamski, J., Krumsiek, J., Schulze, M. B., Pischon, T., et al. (2014) · International Journal of Obesity · doi:10.1038/ijo.2014.39 · Cited by 105 · see citing works
Self-citationStępień, M., Duarte‐Salles, T., Fedirko, V., Floegel, A., Barupal, D. K., Rinaldi, S., Achaintre, D., Assi, N., Tjønneland, A. M., Overvad, K., et al. (2015) · International Journal of Cancer · doi:10.1002/ijc.29718 · Cited by 96 · see citing works
Self-citationBenton, H. P., Want, E. J., Keun, H. C., et al. (2012) · Analytical Chemistry · doi:10.1021/ac203200x · Cited by 47 · see citing works
Self-citationPiccinonna, S., Ragone, R., Stocchero, M., et al. (2015) · Food Chemistry · doi:10.1016/j.foodchem.2015.12.064 · Cited by 43 · see citing works
Pham, H. T., Arnhard, K., Asad, Y. J., Deng, L., Felder, T. K., John‐Williams, L. S., Kaever, V., Leadley, M., Mitro, N., Muccio, S., et al. (2016) · The Journal of Applied Laboratory Medicine · doi:10.1373/jalm.2016.020537 · Cited by 43 · see citing works
Self-citationInterlaboratory comparison for quantitative primary metabolite profiling in Pichia pastoris
Klavins, K., Neubauer, S., Chalabi, A. A., et al. (2013) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-013-6964-4 · Cited by 27 · see citing works
Ang, J. E., Pandher, R., Ang, J. C., Asad, Y. J., Henley, A. T., Valenti, M. R., Box, G., Brandon, A. D. H., Baird, R. D., Friedman, L. S., et al. (2016) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-15-0815 · Cited by 20 · see citing works
Self-citationIntegrating Metabolomics Profiling Measurements Across Multiple Biobanks
Dane, A. D., Hendriks, M. M. W. B., Reijmers, T. H., Harms, A. C., Troost, J., Vreeken, R. J., Boomsma, D. I., van Duijn, C. M., Slagboom, P. E., & Hankemeier, T. (2014) · Analytical Chemistry · doi:10.1021/ac404191a · Cited by 19 · see citing works
Cheema, A. K., Asara, J. M., Wang, Y., Neubert, T. A., Tolstikov, V., & Turck, C. W. (2015) · Journal of Biomolecular Techniques JBT · doi:10.7171/jbt.15-2603-001 · Cited by 11 · see citing works
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Research works printed but not linked: 4
- [2]Fiehn O Plant Mol Biol 2002 48 155 171 11860207
- [4]Wang-Sattler R Yu Z Herder C Messias AC Floegel A He Y Heim K Campillos M Holzapfel C Thorand B Grallert H Mol Syst Biol 2012 8 615 (pages 1-11) 23010998 PMC3472689
- [24]Simón-Manso Y Lowenthal MS Kilpatrick LE Sampson ML Telu KH Rudnick PA Mallard WG Bearden DW Schock TB Tchekhovskoi DV Blonder N Anal Chem 2013 85 11725 11731 24147600
- [29]Alwood JW Erban A de Koning S Dunn WB Luedemann A Lommen A Kay L Löscher R Kopka J Goodacre R Metabolomics 2009 5 479 496 20376177 PMC2847149
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Skene, D. J., Skornyakov, E., Chowdhury, N. R., Gajula, R. P., Middleton, B., Satterfield, B. C., Porter, K. I., Van Dongen, H. P. A., & Gaddameedhi, S. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1801183115 · Cited by 176 · see citing works
- Authors
- Siskos, A. P., Jain, P., Römisch-Margl, W., Bennett, M., Achaintre, D., Asad, Y., Marney, L., Richardson, L., Koulman, A., Griffin, J. L., Raynaud, F., Scalbert, A., Adamski, J., Prehn, C., & Keun, H. C.
- Affiliations
- Imperial College London (GB)
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Centre international de recherche sur le cancer (FR)
- Institute of Cancer Research (GB)
- MRC Elsie Widdowson Laboratory (GB)
- Helmholtz Munich (DE)
- Corresponding author
- Keun, Hector C.
- ORCID
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2016-12-13
- Volume
- 89
- Issue
- 1
- Pages
- 656-665
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- PMC
- PMC6317696
- OpenAlex
- W2558872626
- Cited by
- 269
- References
- 36
- Citations by year
- 2026: 24 · 2025: 19 · 2024: 22 · 2023: 30 · 2022: 26 · 2021: 39 · 2020: 40 · 2019: 26 · 2018: 26 · 2017: 17
- FWCI
- 11.96
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Analytical Chemistry (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Apollo (University of Cambridge) (submittedVersion)
- Site cant be reached (submittedVersion)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
- Spiral (Imperial College London) (submittedVersion)
- Apollo
- Funders
- Medical Research Council (MC_PC_13030, MC_PC_13046, MC_UP_A090_1006)
- Seventh Framework Programme (259867, 266838, 602156, 603864)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Health Sciences › Medicine › Physiology › Clinical Laboratory Practices and Quality Control
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Scientific Measurement and Uncertainty Evaluation
- Keywords
- interlaboratory reproducibility, targeted metabolomics, human serum, human plasma, LC-MS/MS, flow injection analysis, coefficient of variation, quality control samples, NIST SRM 1950, peak integration, dyslipidemia, detection limit
- MeSH terms
- Humans, Laboratories, Quality Control, Reference Standards, Reproducibility of Results, Tandem Mass Spectrometry, Metabolomics, Limit of Detection
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