The DOI matches its Crossref record; 36 of the 38 references it cites were found in a registry or an index.
Reliability of Serum Metabolite Concentrations over a 4-Month Period Using a Targeted Metabolomic Approach
Open accessAbstract
Metabolomics is a promising tool for discovery of novel biomarkers of chronic disease risk in prospective epidemiologic studies. We investigated the between- and within-person variation of the concentrations of 163 serum metabolites over a period of 4 months to evaluate the metabolite reliability expressed by the intraclass-correlation coefficient (ICC: the ratio of between-person variance and total variance). The analyses were performed with the BIOCRATES AbsoluteIDQ™ targeted metabolomics technology, including acylcarnitines, amino acids, glycerophospholipids, sphingolipids and hexose in 100 healthy individuals from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study who had provided two fasting blood samples 4 months apart. Overall, serum reliability of metabolites over a 4-month period was good. The median ICC of the 163 metabolites was 0.57. The highest ICC was observed for hydroxysphingomyelin C14:1 (ICC = 0.85) and the lowest was found for acylcarnitine C3:1 (ICC = 0). Reliability was high for hexose (ICC = 0.76), sphingolipids (median ICC = 0.66; range: 0.24-0.85), amino acids (median ICC = 0.58; range: 0.41-0.72) and glycerophospholipids (median ICC = 0.58; range: 0.03-0.81). Among acylcarnitines, reliability of short and medium chain saturated compounds was good to excellent (ICC range: 0.50-0.81). Serum reliability was lower for most hydroxyacylcarnitines and monounsaturated acylcarnitines (ICC range: 0.11-0.45 and 0.00-0.63, respectively). For most of the metabolites a single measurement may be sufficient for risk assessment in epidemiologic studies with healthy subjects.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“On the basis of a previous evaluation of the reliability of measurements (23), we excluded metabolites below the limit of detection (n = 30) and those with very high analytic variance (n = 6).”
From Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes (2015) · cites this paper as [23]
In the citing paper
“However, FFQs showed good reliability and relative validity to assess meat intake, and investigated metabolites showed good reliability in validation studies (23).”
From Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes (2015) · cites this paper as [23]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Design and Analysis of Clinical Experiments
Fleiss, J. L. (1999) · Wiley eBooks · doi:10.1002/9781118032923 · Cited by 4,819
Fundamentals of Biostatistics.
(1969) · Annals of Internal Medicine · doi:10.7326/0003-4819-70-4-873 · Cited by 4,573
Zelena, E., Dunn, W. B., Broadhurst, D., Francis‐McIntyre, S., Carroll, K. M., Begley, P., O’Hagan, S., Knowles, J. D., Halsall, A., HUSERMET Consortium, et al. (2009) · Analytical Chemistry · doi:10.1021/ac8019366 · Cited by 815
Metabolomics-based methods for early disease diagnostics
Gowda, G. A. N., Zhang, S., Gu, H., Asiago, V. M., Shanaiah, N., & Raftery, D. (2008) · Expert Review of Molecular Diagnostics · doi:10.1586/14737159.8.5.617 · Cited by 705
Mihalik, S. J., Goodpaster, B. H., Kelley, D. E., Chace, D. H., Vockley, J., Toledo, F. G. S., & DeLany, J. P. (2010) · Obesity · doi:10.1038/oby.2009.510 · Cited by 653
A 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 · cited 1×
“This metabolomic approach has already been successfully applied in the human KORA cohort study [7,8], and covers acylcarnitines, amino acids, glycerophospholipids, sphingolipids and hexoses, constituting a biologically relevant panel of 163 metabolites.”
MethodAdams, S. H., Hoppel, C. L., Lok, K. H., Zhao, L., Wong, S. W., Minkler, P. E., Hwang, D. H., Newman, J. W., & Garvey, W. T. (2009) · The Journal of Nutrition · doi:10.3945/jn.108.103754 · Cited by 598 · cited 1×
“Increased acylcarnitine concentrations have been associated with type 2 diabetes mellitus previously [18,19].”
BackgroundRecruitment Procedures of EPIC-Germany
Boeing, H., Korfmann, A., & Bergmann, M. M. (1999) · Annals of Nutrition and Metabolism · doi:10.1159/000012787 · Cited by 307
Fleiss, J. L. (1999) · doi:10.1002/9781118032923.ch1 · Cited by 296 · cited 4×
“To address this issue, the present study aimed to evaluate the reliability, expressed by the intraclass-correlation coefficient (ICC) [5], as the ratio of between-person variance and total variance, of 163 targeted metabolites in fasting serum samples over a 4-month period within a sub-sample of the European Prospecti…”
BackgroundMethodInfluentialRömisch‐Margl, W., Prehn, C. P., Bogumil, R., Röhring, C., Suhre, K., & Adamski, J. (2011) · Metabolomics · doi:10.1007/s11306-011-0293-4 · Cited by 292
EPIC-Germany – A Source for Studies into Diet and Risk of Chronic Diseases
Boeing, H., Wahrendorf, J., & Becker, N. (1999) · Annals of Nutrition and Metabolism · doi:10.1159/000012786 · Cited by 256
Exploring Disease through Metabolomics
Vinayavekhin, N., Homan, E. A., & Saghatelian, A. (2009) · ACS Chemical Biology · doi:10.1021/cb900271r · Cited by 238 · cited 1×
“proteins [1,2,3].”
Application of Metabolomics to Cardiovascular Biomarker and Pathway Discovery
Lewis, G. D., Asnani, A. H., & Gerszten, R. E. (2008) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2008.03.043 · Cited by 228 · cited 1×
“Thus, the high sensitivity of the metabolome to internal or external stimuli (such as age, hormonal status, diet and lifestyle) may potentially limit their use for risk assessment in large-scale epidemiologic studies that are based on single blood measurements [6], but little is known on their within- and between-pers…”
BackgroundIntraclass Correlation Coefficient
Koch, G. G. (2005) · Encyclopedia of Statistical Sciences · doi:10.1002/0471667196.ess1275.pub2 · Cited by 197
Zhao, X., Peter, A., Fritsche, J., Elcnerova, M., Fritsche, A., Häring, H.-U., Schleicher, E. D., Xu, G., & Lehmann, R. (2009) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.90748.2008 · Cited by 170 · cited 1×
“De-novo synthesis and redistribution from plasma membranes may impact phosphatidylcholine and lysophosphatidylcholine concentrations in blood [20].”
BackgroundMetabolomics, a novel tool for studies of nutrition, metabolism and lipid dysfunction
Orešič, M. (2009) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2009.04.018 · Cited by 165 · cited 1×
“However, it was important to measure those as well, as their concentrations may increase drastically in disease or upon environmental challenge [28,29,30].”
BackgroundSphingomyelinases: their regulation and roles in cardiovascular pathophysiology
Pavoine, C., & Pecker, F. (2009) · Cardiovascular Research · doi:10.1093/cvr/cvp030 · Cited by 162 · cited 1×
“Besides being part of membranes, they are also involved in signal transduction such as nuclear factor-kB pathways [21].”
BackgroundEffects of sample handling and storage on quantitative lipid analysis in human serum
Zivkovic, A. M., Wiest, M. M., Nguyen, U. T., Davis, R., Watkins, S. M., & German, J. B. (2009) · Metabolomics · doi:10.1007/s11306-009-0174-2 · Cited by 154 · cited 1×
“Reliability studies often focus on technological improvement of biochemical assays, sample handling or storage conditions [10,11,12,13].”
BackgroundZhang, P., Liu, B., Jenkins, G. M., Hannun, Y. A., & Obeid, L. M. (1997) · Journal of Biological Chemistry · doi:10.1074/jbc.272.15.9609 · Cited by 153 · cited 1×
“This action requires enzymatical breakdown of sphingomyelins and release of ceramides [22].”
BackgroundAdiponectin: Stability in Plasma over 36 Hours and Within-Person Variation over 1 Year
Pischon, T., Hotamışlıgil, G. S., & Rimm, E. B. (2003) · Clinical Chemistry · doi:10.1373/49.4.650 · Cited by 147 · cited 1×
“Reliability studies often focus on technological improvement of biochemical assays, sample handling or storage conditions [10,11,12,13].”
BackgroundFollow-Up Procedures in EPIC-Germany – Data Quality Aspects
Bergmann, M. M., Bussas, U., & Boeing, H. (1999) · Annals of Nutrition and Metabolism · doi:10.1159/000012789 · Cited by 140
Crews, B. O., Wikoff, W. R., Patti, G. J., Woo, H., Kalisiak, E., Heideker, J., & Siuzdak, G. E. (2009) · Analytical Chemistry · doi:10.1021/ac9014947 · Cited by 129 · cited 1×
“However, studies investigating the biological variance and over-time reliability of metabolite concentrations are rarely found in the literature [14,15,16].”
BackgroundKotsopoulos, J., Tworoger, S. S., Campos, H., Chung, F., Clevenger, C. V., Franke, A. A., Mantzoros, C. S., Ricchiuti, V., Willett, W. C., Hankinson, S. E., et al. (2010) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-09-1318 · Cited by 121
Wang‐Sattler, R., Yu, Y., Mittelstraß, K., Lattka, E., Altmaier, E., Gieger, C., Ladwig, K., Dahmen, N., Weinberger, K. M., Hao, P., et al. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003863 · Cited by 120 · cited 1×
“This metabolomic approach has already been successfully applied in the human KORA cohort study [7,8], and covers acylcarnitines, amino acids, glycerophospholipids, sphingolipids and hexoses, constituting a biologically relevant panel of 163 metabolites.”
MethodNonnegative Minimum Biased Invariant Estimation in Variance Component Models
Hartung, J. G. (1981) · The Annals of Statistics · doi:10.1214/aos/1176345394 · Cited by 93 · cited 2×
“For negative values ICC was calculated based on positive variance estimators [33].”
MethodKoeberl, D. D., Young, S. P., Gregersen, N., Vockley, J. E., Smith, W. E., Benjamin, D. K., An, Y., Weavil, S. D., Chaing, S., Bali, D. S., et al. (2003) · Pediatric Research · doi:10.1203/01.pdr.0000074972.36356.89 · Cited by 87 · cited 1×
“However, it was important to measure those as well, as their concentrations may increase drastically in disease or upon environmental challenge [28,29,30].”
BackgroundLong-Term Stability of Amino Acids and Acylcarnitines in Dried Blood Spots
Strnadová, K. A., Holub, M., Mühl, A., Heinze, G., Ratschmann, R., Mascher, H. J., Stöckler‐Ipsiroglu, S., Waldhauser, F., Votava, F., Lebl, J., et al. (2007) · Clinical Chemistry · doi:10.1373/clinchem.2006.076679 · Cited by 87
Within-Individual Stability of Obesity-Related Biomarkers among Women
Kaplan, R. C., Ho, G., Xue, X., Rajpathak, S. N., Cushman, M., Rohan, T. E., Strickler, H. D., Scherer, P. E., & Anastos, K. (2007) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-06-1089 · Cited by 61
Einsatz von Metabolomics zur Diagnose von Stoffwechselkrankheiten
Weinberger, K. M. (2008) · Therapeutische Umschau · doi:10.1024/0040-5930.65.9.487 · Cited by 39
The intraclass correlation coefficient
ROSNER, B. A. (2000) · Medical Entomology and Zoology · Cited by 32
Searching for ‘omic’ biomarkers
Lin, D. T. S., Hollander, Z., Meredith, A., & McManus, B. M. (2009) · Canadian Journal of Cardiology · doi:10.1016/s0828-282x(09)71048-7 · Cited by 17
Within-subject variation of plasma resistin levels over a 1-year period
Weikert, C., Westphal, S., Luley, C. H., Willich, S. N., Boeing, H., & Pischon, T. (2007) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm.2007.148 · Cited by 12
Plasma Carnitines: Reference Values in an Ambulatory Population
Boulat, O., Janin, B., Francioli, P. B., & Bachmann, C. (1993) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm.1993.31.9.585 · Cited by 9 · cited 1×
“However, it was important to measure those as well, as their concentrations may increase drastically in disease or upon environmental challenge [28,29,30].”
Background(2016) · Advances in computer and electrical engineering book series · doi:10.4018/978-1-4666-9429-3.ch005 · Cited by 9
Heritability of plasma amino acid levels in different nutritional states
McBride, K. L., Belmont, J. W., O’Brien, W. E., Amin, T. J., Carter, S., & Lee, B. (2006) · Molecular Genetics and Metabolism · doi:10.1016/j.ymgme.2006.08.010 · Cited by 8 · cited 2×
“Investigators previously reported similar high ICCs for plasma concentrations of amino acids in different nutritional states [17].”
BackgroundReproducibility of in vivo measures of platelet membrane phospholipids in human subjects
Soares, J. C., Dippold, C. S., Wells, K. F., Houck, P., & Mallinger, A. G. (1999) · Psychiatry Research · doi:10.1016/s0165-1781(99)00028-1 · Cited by 5 · cited 1×
“A previous study that investigated the reproducibility of platelet phospholipid measures in 12 subjects over a 3-week period reported similar ICCs as observed in our study [23].”
Result
Flagged first, then by citations
2 of the 38 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- KM Weinberger, 2008, [Metabolomics in diagnosing metabolic diseases]., Ther Umsch, 65, 487
Cited by
Sorted by citations
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
“measured in participants over a 4-month period, indicating reasonable reliability of the measurements (31).”
BackgroundSelf-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
Self-citationDunn, W. B., Wilson, I. D., Nicholls, A. W., & Broadhurst, D. (2012) · Bioanalysis · doi:10.4155/bio.12.204 · Cited by 456
Metabolomics for clinical use and research in chronic kidney disease
Hocher, B., & Adamski, J. (2017) · Nature Reviews Nephrology · doi:10.1038/nrneph.2017.30 · Cited by 339
Siskos, A. P., Jain, P., Römisch-Margl, W., Bennett, M., Achaintre, D., Asad, Y., Marney, L., Richardson, L., Koulman, A., Griffin, J. L., et al. (2017) · Analytical Chemistry · doi:10.1021/acs.analchem.6b02930 · Cited by 269
Self-citation
Metadata
- Authors
- Floegel, A., Drogan, D., Wang-Sattler, R., Prehn, C., Illig, T., Adamski, J., Joost, H.-G., Boeing, H., & Pischon, T.
- Affiliations
- German Institute of Human Nutrition (DE)
- Helmholtz Munich (DE)
- Max Delbrück Center (DE)
- Corresponding author
- Floegel, Anna
- ORCID
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2011-06-15
- Volume
- 6
- Issue
- 6
- Pages
- e21103
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3115978
- OpenAlex
- W2042418561
- Cited by
- 135
- References
- 38
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 5 · 2023: 5 · 2022: 9 · 2021: 14 · 2020: 9 · 2019: 7 · 2018: 14 · 2017: 15 · 2016: 14 · 2015: 6 · 2014: 13 · 2013: 7 · 2012: 7
- FWCI
- 3.63
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Site cant be reached (submittedVersion, cc-by)
- Funders
- Bundesministerium für Bildung und Forschung (01GI0922)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Health Sciences › Health Professions › Medical Laboratory Technology › Clinical Laboratory Practices and Quality Control
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
- Keywords
- serum metabolites, intraclass correlation coefficient, between-person variation, within-person variability, targeted metabolomics, acylcarnitines, sphingolipids, glycerophospholipids, amino acids, hexoses, biomarkers, chronic disease risk
- MeSH terms
- Female, Humans, Male, Middle Aged, Reproducibility of Results, Serum, Metabolomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
