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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.
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“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]
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“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]
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Niewczas, M. A., Sirich, T. L., Mathew, A. V., SKUPIEN, J. K., Mohney, R. P., Warram, J. H., Smiles, A. M., Huang, X., Walker, W., Byun, J., et al. (2014) · Kidney International · doi:10.1038/ki.2013.497 · Cited by 225
“…persistent, defined here as “stable” and of particular interest, which remains in accordance with the systematic report by Floegel et al. (27) Fold differences between the mean plasma concentration in progressors to ESRD and non-progressors were analyzed for the 262 common metabolites…”
MethodUrinary metabolic signatures of human adiposity
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“These ICC coefficients are similar to those described previously for a range of metabolites in serum (54, 55) and urine (56) based on mass spectrometry (MS) and gas chromatography.”
ResultMetabolomics in Epidemiology: Sources of Variability in Metabolite Measurements and Implications
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“The phosphatidylcholines reference values of the present study were slightly lower than those reported in 100 HVs from the EPIC-Potsdam cohort [6], probably because the 100 HVs recruited by Floegel et al. were aged between 35 and 65, compared to the present 18–86 year-old 800 HVs, 391 of whom were…”
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“The nomenclature of the metabolites was published previously (9).”
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“Another strength is that our results showed overall good reliability over a 2-year interval which represents a longer time interval compared to previous investigations involving the same metabolites spectrum [11,12,15].”
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Prospective analysis of circulating metabolites and breast cancer in EPIC
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Targeted metabolomics profiles are strongly correlated with nutritional patterns in women
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“Floegel et al. (2011) investigated the between- and within-person variation in the metabolite measurements of the 163 serum metabolites in Biocrates panel was analysed the in 100 subjects who had provided two fasting blood samples taken 4 months apart.”
InfluentialWittenbecher, C., Mühlenbruch, K., Kröger, J., Jacobs, S., Kuxhaus, O., Floegel, A., Fritsche, A., Pischon, T., Prehn, C., Adamski, J., et al. (2015) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.114.099150 · Cited by 120
“The measurement of the samples of this study as well as the assay procedure was described elsewhere in detail (22, 23).”
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Floegel, A., Kuhn, T. E., Sookthai, D., Johnson, T., Prehn, C. P., Rolle-Kampczyk, U. E., Otto, W., Weikert, C., Illig, T., von Bergen�, M., et al. (2017) · European Journal of Epidemiology · doi:10.1007/s10654-017-0333-0 · Cited by 103
“However, in a previous study we found a relatively high reliability of most of the metabolites included in our study over 4 month and others reported a high reliability over a 2-year period [45, 46].”
ResultThe impact of ambient air pollution on the human blood metabolome
Vlaanderen, J. J., Janssen, N., Hoek, G., Keski‐Rahkonen, P., Barupal, D. K., Cassee, F. R., Gosens, I., Strak, M., Steenhof, M., Lan, Q., et al. (2017) · Environmental Research · doi:10.1016/j.envres.2017.03.042 · Cited by 97
“Limited information is available from other studies about day to day variability in the blood metabolome (Breier et al., 2014; Carayol et al., 2015; Chaleckis et al., 2016; Floegel et al., 2011).”
Midttun, Ø., Townsend, M. K., Nygard, O. K., Tworoger, S. S., Brennan, P., Johansson, M., & Ueland, P. M. (2014) · Journal of Nutrition · doi:10.3945/jn.113.189738 · Cited by 95
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“Considering the appropriateness of population-based referencing, we preferred a relatively stable biomarker with a small intrasubject variance compared with the between-subject variance (28).”
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“Although sources of variability in urine, serum, and plasma metabolite measurements have been studied (33, 43, 44), data on sources of variability in fecal metabolite measurements are lacking.”
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“70), suggesting that a single measurement may be adequate for most metabolites [18, 39, 40], although the reproducibility was lower for some acylcarnitines and a few amino acids [18, 39].”
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“Most detection limits are in the nanomolar ranges [71], thus allowing hundreds to thousands of compounds to be detected in a single analysis for high-throughput clinical analysis [69].”
BackgroundChanges in the serum metabolite profile in obese children with weight loss
Reinehr, T., Wolters, B., Knop, C., Lass, N., Hellmuth, C., Harder, U., Peißner, W., Wahl, S., Grallert, H., Adamski, J., et al. (2014) · European Journal of Nutrition · doi:10.1007/s00394-014-0698-8 · Cited by 78
Blood Metabolic Signatures of Body Mass Index: A Targeted Metabolomics Study in the EPIC Cohort
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1 H-NMR analysis provides a metabolomic profile of patients with multiple sclerosis
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The metabolic fingerprint of p,p′-DDE and HCB exposure in humans
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“6), similar to the 2 year ICCs [42] but weaker than the shorter term reproducibility [43, 44].”
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Metabolomics Biomarkers for Detection of Colorectal Neoplasms: A Systematic Review
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“Metabolites in serum remained stable over a 4-months period frozen at −80 ◦C [87].”
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“In addition, the high sensitivity and reliability of this technology makes it suitable for monitoring metabolite changes over time (Floegel et al., 2011).”
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“the respective LOD and could be detected in 95% of the examined samples (24).”
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“Nevertheless, several studies showed a good stability and reproducibility of metabolomic measurements for most of metabolites (44, 45).”
BackgroundLi‐Gao, R., Hughes, D. A., le Cessie, S., de Mutsert, R., den Heijer, M., Rosendaal, F. R., van Dijk, K. W., Timpson, N. J., & Mook-Kanamori, D. O. (2019) · PLoS ONE · doi:10.1371/journal.pone.0218549 · Cited by 57
“Nonetheless, previous studies reported relatively stable short-term metabolic profiles for both plasma and urine specimens across different metabolomics platforms (7-10).”
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The role of metabolomics in neurological disease
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“This data supports the concept that a single analysis of metabolites can potentially be used for disease risk assessment (Floegel et al., 2011).”
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“metabolomic measurements for most of metabolites.(51,52) Finally, a quantification analysis of plasma levels of key identified metabolites will be necessary to propose potential predictive biomarkers for cancer prevention.”
BackgroundDiscovering and validating between-subject variations in plasma lipids in healthy subjects
Begum, H., Li, B., Shui, G., Cazenave‐Gassiot, A., Soong, R. C. T., Ong, R. T., Little, P., Teo, Y., & Wenk, M. R. (2016) · Scientific Reports · doi:10.1038/srep19139 · Cited by 50
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“This threshold has been selected according to a similar study done on 100 EPIC subjects in which researchers evaluated the reliability of serum metabolite measurements [49].”
MethodProspective analysis of circulating metabolites and endometrial cancer risk
Dossus, L., Kouloura, E., Biessy, C., Viallon, V., Siskos, A., Dimou, N. L., Rinaldi, S., Merritt, M. A., Allen, N. E., Fortner, R. T., et al. (2021) · Gynecologic Oncology · doi:10.1016/j.ygyno.2021.06.001 · Cited by 46
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Fatty Liver Due to Increased de novo Lipogenesis: Alterations in the Hepatic Peroxisomal Proteome
Knebel, B., Fahlbusch, P., Dille, M. A., Wahlers, N., Hartwig, S., Jacob, S., Kettel, U., Schiller, M., Herebıan, D., Koellmer, C., et al. (2019) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2019.00248 · Cited by 44
Endocrinology Meets Metabolomics: Achievements, Pitfalls, and Challenges
Tokarz, J., Haid, M., Cecil, A., Prehn, C. P., Artati, A., Möller, G., & Adamski, J. (2017) · Trends in Endocrinology and Metabolism · doi:10.1016/j.tem.2017.07.001 · Cited by 44
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van Roekel, E. H., Trijsburg, L. E., Assi, N., Carayol, M., Achaintre, D., Murphy, N., Rinaldi, S., Schmidt, J. A., Stępień, M., Kaaks, R., et al. (2018) · Nutrients · doi:10.3390/nu10050654 · Cited by 41
“A good to excellent reliability for the majority of compounds measured through this method was observed when comparing samples collected in the same individuals over a period of four months [27] and two years [25] (intra-class correlation coefficients > 0.”
Breeur, M., Ferrari, P., Dossus, L., Jenab, M., Johansson, M., Rinaldi, S., Travis, R. C., His, M., Key, T., Schmidt, J. A., et al. (2022) · BMC Medicine · doi:10.1186/s12916-022-02553-4 · Cited by 42
Pathway and Time-Resolved Benzo[a]pyrene Toxicity on Hepa1c1c7 Cells at Toxic and Subtoxic Exposure
Kalkhof, S., Dautel, F., Loguercio, S., Baumann, S., Trump, S., Jungnickel, H., Otto, W., Rudzok, S., Potratz, S., Luch, A., et al. (2014) · Journal of Proteome Research · doi:10.1021/pr500957t · Cited by 40
Verma, M., Khoury, M. J., & Ioannidis, J. P. A. (2012) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-12-1263 · Cited by 41
“in ovarian cancer (102, 103); to evaluate nutritional factors and disease development (197, 198); life-style factors that”
Suvitaival, T., Mantere, O., Kieseppä, T., Mattila, I. M., Pöhö, P., Hyötyläinen, T., Suvisaari, J., & Orešič, M. (2016) · Translational Psychiatry · doi:10.1038/tp.2016.222 · Cited by 40
Sources of Variability in Metabolite Measurements from Urinary Samples
Xiao, Q., Moore, S. C., Boca, S. M., Matthews, C. E., Rothman, N., Stolzenberg‐Solomon, R. Z., Sinha, R. R., Cross, A. J., & Sampson, J. N. (2014) · PLoS ONE · doi:10.1371/journal.pone.0095749 · Cited by 37
Bachlechner, U., Floegel, A., Steffen, A., Prehn, C. P., Adamski, J., Pischon, T., & Boeing, H. (2016) · Nutrition and Diabetes · doi:10.1038/nutd.2016.23 · Cited by 36
Assessment of metabolic phenotypic variability in children’s urine using 1H NMR spectroscopy
Maître, L., Lau, C. E., Vizcaíno, E., Robinson, O., Casas, M., Siskos, A., Want, E. J., Athersuch, T. J., Slama, R., Vrijheid, M., et al. (2017) · Scientific Reports · doi:10.1038/srep46082 · Cited by 35
Wang, Y., Hodge, R. A., Stevens, V. L., Hartman, T. J., & McCullough, M. L. (2020) · Metabolites · doi:10.3390/metabo10100382 · Cited by 34
“A few previous studies examined the reproducibility of metabolites over a period, although did not focus on diet related biomarkers [36,37].”
BackgroundKey elements of metabolomics in the study of biomarkers of diabetes
Adamski, J. (2016) · Diabetologia · doi:10.1007/s00125-016-4044-y · Cited by 32
“However, the human metabolome is very stable over months [20] and even years [21] and deviations from conserved patterns may reflect a disease, environmental”
BackgroundSchlecht, I., Gronwald, W., Behrens, G., Baumeister, S. E., Hertel, J., Hochrein, J., Zacharias, H. U., Fischer, B., Oefner, P. J., & Leitzmann, M. F. (2017) · PLoS ONE · doi:10.1371/journal.pone.0175133 · Cited by 34
Lécuyer, L., Dalle, C., Lefèvre‐Arbogast, S., Micheau, P., Lyan, B., Rossary, A., Demidem, A., Pétéra, M., Lagrée, M., Centeno, D., et al. (2019) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-19-0900 · Cited by 32
“Nevertheless, several studies have showed a good reproducibility of metabolomic measurements for most of metabolites (63, 64).”
BackgroundWu, F., Chi, L., Ru, H., Parvez, F., Slavkovich, V. N., Eunus, M., Ahmed, A., Islam, T., Rakibuz‐Zaman, M., Hasan, R., et al. (2018) · Environmental Health Perspectives · doi:10.1289/ehp1992 · Cited by 32
“5 covering several months to a year (Floegel et al. 2011; Sampson et al. 2013; Townsend et al. 2013).”
BackgroundInfluentialAssi, N., Thomas, D. C., Leitzmann, M. F., Stępień, M., Chajès, V., Philip, T. O., Vineis, P., Bamia, C., Boutron‐Ruault, M., Sandanger, T. M., et al. (2018) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-17-0649 · Cited by 31
“It is worth noting that lifestyle and metabolite concentrations reflect different exposure windows, with metabolites likely reflecting exogenous and endogenous exposures in a limited timeframe (37, 38, 84).”
BackgroundFetal Serum Metabolites Are Independently Associated with Gestational Diabetes Mellitus
Lu, Y.-P., Reichetzeder, C., Prehn, C. P., von Websky, K., Slowinski, T., Chen, Y.-P., Yin, L., Kleuser, B., Yang, X., Adamski, J., et al. (2018) · Cellular Physiology and Biochemistry · doi:10.1159/000487119 · Cited by 27
Lin, X., Lécuyer, L., Liu, X., Triba, M. N., Deschasaux, M., Demidem, A., Liu, Z., Palama, T., Rossary, A., Vasson, M., et al. (2021) · Cancers · doi:10.3390/cancers13133140 · Cited by 27
“Despite that, several metabolomic studies showed good stability and reproducibility for most metabolites [74,75].”
BackgroundYin, X., Prendiville, O., McNamara, A. E., & Brennan, L. (2022) · Journal of Proteome Research · doi:10.1021/acs.jproteome.1c00440 · Cited by 26
“8 − 10 For example, Floegel et al. (2011) evaluated the serum metabolite reproducibility ( n = 163) in 100 healthy participants (50 men and 50 women) from the cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study over a period of 4 months.”
Wientzek, A., Floegel, A., Knüppel, S., Vigl, M., Drogan, D., Adamski, J., Pischon, T., & Boeing, H. (2014) · International Journal of Sport Nutrition and Exercise Metabolism · doi:10.1123/ijsnem.2013-0048 · Cited by 26
Loef, M., von Hegedus, J. H., Ghorasaini, M., Kroon, F. P. B., Giera, M. A., Ioan‐Facsinay, A., & Kloppenburg, M. (2020) · Metabolites · doi:10.3390/metabo11010026 · Cited by 25
Valvi, D., Walker, D. I., Inge, T. H., Bartell, S. M., Jenkins, T. M., Helmrath, M. A., Ziegler, T. R., Merrill, M. A. L., Eckel, S. P., Conti, D. V., et al. (2020) · Environment International · doi:10.1016/j.envint.2020.105957 · Cited by 26
“Prospective investigations with repeated measures of untargeted high-resolution metabolomics could help address uncertainty in the temporal variability of some metabolites that has not been extensively studied (Carayol et al. 2015; Floegel et al. 2011).”
BackgroundRankin, N., Preiss, D., Welsh, P. I., & Sattar, N. A. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw271 · Cited by 24
Li, Z., Shen, Q., Wang, J., Tuo, J., Tan, Y., Li, H., & Xiang, Y. (2024) · EBioMedicine · doi:10.1016/j.ebiom.2024.104990 · Cited by 23
“Although the reproducibility of many circulating metabolites over time has been demonstrated, 68 – 70 longitudinal studies with repeated measurements are necessitated to account for within-person variations and to assess the dynamic changes of metabolites in relation to liver cancer risk.”
BackgroundInfluentialKoch, M., Freitag‐Wolf, S., Schlesinger, S., Borggrefe, J., Hov, J. R., Jensen, M. K., Pick, J., Markus, M. R. P., Höpfner, T., Jacobs, G., et al. (2017) · European Journal of Clinical Nutrition · doi:10.1038/ejcn.2017.43 · Cited by 22
NMR metabolomic profiles associated with long-term risk of prostate cancer
Lécuyer, L., Bala, A. V., Demidem, A., Rossary, A., Bouchemal, N., Triba, M. N., Galan, P., Herçberg, S., Partula, V., Srour, B., et al. (2021) · Metabolomics · doi:10.1007/s11306-021-01780-9 · Cited by 22
Zheng, Y., Yu, B., Alexander, D. C., Couper, D. J., & Boerwinkle, E. (2014) · OMICS A Journal of Integrative Biology · doi:10.1089/omi.2014.0019 · Cited by 21
“There are little data concerning medium-term, or week-toweek, biologic variability associated with metabolomic bio- markers (Evans et al., 2003; Floegel et al., 2011), although a number of population studies have collected and preserved a multitude of samples appropriate for untargeted metabolomic…”
BackgroundResultInfluentialCharacterisation of Fasting and Postprandial NMR Metabolites: Insights from the ZOE PREDICT 1 Study
Bermingham, K. M., Mazidi, M., Franks, P. W., Maher, T., Valdes, A. M., Linenberg, I., Wolf, J., Hadjigeorgiou, G. M., Spector, T. D., Menni, C., et al. (2023) · Nutrients · doi:10.3390/nu15112638 · Cited by 22
“reliability over time of fasting blood metabolites has been investigated (18, 19, 25) and 211 reliability over time has been shown to decrease in non-fasting samples (22).”
BackgroundBermingham, K. M., Brennan, L., Segurado, R., Barron, R. E., Gibney, E. R., Ryan, M. F., Gibney, M. J., & O’Sullivan, A. M. (2021) · Journal of Proteome Research · doi:10.1021/acs.jproteome.1c00319 · Cited by 18
Murphy, R. A., Moore, S. C., Playdon, M. C., Kritchevsky, S. B., Newman, A. B., Satterfield, S., Ayonayon, H. N., Clish, C. B., Gerszten, R. E., & Harris, T. B. (2017) · The Journals of Gerontology Series A · doi:10.1093/gerona/glx233 · Cited by 18
“However, a prior study, which measured serum metabolite concentrations 4 months apart, reported reliable metabolite concentrations and concluded a single measurement reflects long-term metabolite concentrations (51).”
BackgroundLécuyer, L., Dalle, C., Micheau, P., Pétéra, M., Centeno, D., Lyan, B., Lagrée, M., Galan, P., Herçberg, S., Rossary, A., et al. (2020) · European Journal of Nutrition · doi:10.1007/s00394-020-02177-5 · Cited by 18
“Nevertheless, several studies showed a good stability and reproducibility of metabolomic measurements for most of endogenous metabolites [73, 74].”
Backgroundvan Roekel, E. H., Bours, M. J. L., Breukink, S. O., Aquarius, M., Keulen, E. T. P., Gicquiau, A., Rinaldi, S., Vineis, P., Arts, I. C. W., Gunter, M. J., et al. (2022) · International Journal of Cancer · doi:10.1002/ijc.34252 · Cited by 16
Ishibashi, Y., Harada, S., Takeuchi, A., Iida, M., Kurihara, A., Kato, S., Kuwabara, K., Hirata, A., Shibuki, T., Okamura, T., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-86600-9 · Cited by 17
Reproducibility of the Blood and Urine Exposome: A Systematic Literature Review and Meta-Analysis
Goerdten, J., Li, Y., Huybrechts, I., Neveu, V., Nöthlings, U., Ahrens, W., Scalbert, A., & Floegel, A. (2022) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-22-0090 · Cited by 15
“This translates to a smaller within-subject variance over time compared to the between-subject variance, which should explain most of the variation seen in the measurement (10, 11).”
BackgroundOosterwegel, M. J., Ibi, D., Portengen, L., Probst-Hensch, N. M., Tarallo, S., Naccarati, A., Imboden, M., Jeong, A., Robinot, N. R., Scalbert, A., et al. (2023) · Environmental Science & Technology · doi:10.1021/acs.est.3c03233 · Cited by 16
Mullen, W., Saigusa, D., Abe, T., Adamski, J., & Mischak, H. (2014) · Seminars in Nephrology · doi:10.1016/j.semnephrol.2014.02.009 · Cited by 13
Genetic variants including markers from the exome chip and metabolite traits of type 2 diabetes
Jäger, S., Wahl, S., Kröger, J., Sharma, S., Hoffmann, P., Floegel, A., Pischon, T., Prehn, C. P., Adamski, J., Müller‐Nurasyid, M., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-06158-3 · Cited by 14
Comparison of metabolite networks from four German population-based studies
Iqbal, K., Dietrich, S., Wittenbecher, C., Krumsiek, J., Kuhn, T. E., Lacruz, M. E., Kluttig, A., Prehn, C. P., Adamski, J., von Bergen�, M., et al. (2018) · International Journal of Epidemiology · doi:10.1093/ije/dyy119 · Cited by 13
“CVs of metabolite measurements were similar between the cohorts and comparable to other metabolomic studies that measured the same metabolites.(23,40) However, a general limitation of metabolomic studies is that many metabolites are measured simultaneously and CVs of metabolites are usually higher than CVs of single b…”
ResultOluwagbemigun, K., Anesi, A., Clarke, G. A., Schmid, M. C., Mattivi, F., & Nöthlings, U. (2021) · International Journal of Tryptophan Research · doi:10.1177/11786469211041376 · Cited by 12
Östman, J. R., Pinto, R. C., Ebbels, T. M. D., Thysell, E., Hallmans, G., & Moazzami, A. A. (2022) · International Journal of Cancer · doi:10.1002/ijc.34223 · Cited by 12
“term (ie, a period of 4-48 months) reproducibility of metabolite concentrations has been shown.(31,32) Moreover, our study was also limited by including participants only from a cohort of individuals from a single European country (ie, NSHDS, Sweden), not consider-”
Jäger, S., Cuadrat, R. R. C., Wittenbecher, C., Floegel, A., Hoffmann, P., Prehn, C. P., Adamski, J., Pischon, T., & Schulze, M. B. (2020) · Nutrients · doi:10.3390/nu12123890 · Cited by 13
“All samples of EPIC-Potsdam have been processed in one batch [22].”
MethodMichel, M., Salvador, C., Wiedemair, V., Adam, M. G., Laser, K. T., Dubowy, K., Entenmann, A., Karall, D., Geiger, R., Zlamy, M., et al. (2020) · Metabolomics · doi:10.1007/s11306-020-01741-8 · Cited by 11
NMR-Metabolomics Reveals a Metabolic Shift after Surgical Resection of Non-Small Cell Lung Cancer
Derveaux, E., Geubbelmans, M., Criel, M., Demedts, I., Himpe, U., Tournoy, K. G., Vercauter, P., Johansson, E., Valkenborg, D., Vanhove, K., et al. (2023) · Cancers · doi:10.3390/cancers15072127 · Cited by 10
Early Life Factors, Obesity Risk, and the Metabolome of Young Adults
Rauschert, S., Mori, T. A., Beilin, L. J., Jacoby, P. A., Uhl, O., Koletzko, B. V., Oddy, W. H., & Hellmuth, C. (2017) · Obesity · doi:10.1002/oby.21915 · Cited by 9
“These associations can be examined using metabolomics, the study of the smallest molecules in the metabolism, to detect metabolomic patterns and changes in metabolism due to disease states (14).”
BackgroundJungert, A., & Frank, J. (2021) · Antioxidants · doi:10.3390/antiox10030448 · Cited by 9
“To allow a reliable extrapolation from a single measurement to long-term biomarker status, the inter-individual variance had to be the overriding proportion of the observed total variance in the respective biomarker compared to the intra-individual variance [31].”
Biomarkers of mammographic density in premenopausal women
His, M., Lajous, M., Gómez‐Flores‐Ramos, L., Monge, A., Dossus, L., Viallon, V., Gicquiau, A., Biessy, C., Gunter, M. J., & Rinaldi, S. (2021) · Breast Cancer Research · doi:10.1186/s13058-021-01454-3 · Cited by 11
Specific Metabolic Markers Are Associated with Future Waist-Gaining Phenotype in Women
Merz, B., Nöthlings, U., Wahl, S., Haftenberger, M., Schienkiewitz, A., Adamski, J., Suhre, K., Wang‐Sattler, R., Grallert, H., Thorand, B., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0157733 · Cited by 8
Kuhn, T. E., Sookthai, D., Rolle-Kampczyk, U. E., Otto, W., von Bergen�, M., Kaaks, R., & Johnson, T. (2016) · Metabolomics · doi:10.1007/s11306-016-1133-3 · Cited by 9
“Carayol and co-workers examined the biological reproducibility of 180 metabolites covered by the AbsolueIDQp180 kit from Biocrates using serum samples collected two years apart in the EPIC cohorts in Turin (27 men, fasting) and Utrecht (39 women, non-fasting) (Carayol et al. 2015).”
BackgroundMethodResultInfluential
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
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