Reliability of Serum Metabolite Concentrations over a 4-Month Period Using a Targeted Metabolomic Approach

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.

[1]  M. Orešič,et al.  Metabolomics, a novel tool for studies of nutrition, metabolism and lipid dysfunction. , 2009, Nutrition, metabolism, and cardiovascular diseases : NMCD.

[2]  E. Schleicher,et al.  Changes of the plasma metabolome during an oral glucose tolerance test: is there more than glucose to look at? , 2009, American journal of physiology. Endocrinology and metabolism.

[3]  Gary G. Koch,et al.  Intraclass Correlation Coefficient , 2011, International Encyclopedia of Statistical Science.

[4]  Joseph L. Fleiss,et al.  Reliability of Measurement , 2011 .

[5]  B. McManus,et al.  Searching for 'omic' biomarkers. , 2009, The Canadian journal of cardiology.

[6]  Jerzy Adamski,et al.  Procedure for tissue sample preparation and metabolite extraction for high-throughput targeted metabolomics , 2011, Metabolomics.

[7]  H. Boeing,et al.  Recruitment Procedures of EPIC-Germany , 1999, Annals of Nutrition and Metabolism.

[8]  Correction: Reproducibility of Plasma and Urine Biomarkers among Premenopausal and Postmenopausal Women from the Nurses' Health Studies , 2011, Cancer Epidemiology, Biomarkers & Prevention.

[9]  H. Boeing,et al.  EPIC-Germany – A Source for Studies into Diet and Risk of Chronic Diseases , 1999, Annals of Nutrition and Metabolism.

[10]  Christian Gieger,et al.  Metabolic Profiling Reveals Distinct Variations Linked to Nicotine Consumption in Humans — First Results from the KORA Study , 2008, PloS one.

[11]  J. Belmont,et al.  Heritability of plasma amino acid levels in different nutritional states. , 2007, Molecular genetics and metabolism.

[12]  W. R. Wikoff,et al.  Variability analysis of human plasma and cerebral spinal fluid reveals statistical significance of changes in mass spectrometry-based metabolomics data. , 2009, Analytical chemistry.

[13]  C. Hoppel,et al.  Plasma acylcarnitine profiles suggest incomplete long-chain fatty acid beta-oxidation and altered tricarboxylic acid cycle activity in type 2 diabetic African-American women. , 2009, The Journal of nutrition.

[14]  D. Raftery,et al.  Metabolomics-based methods for early disease diagnostics , 2008, Expert review of molecular diagnostics.

[15]  Y. Hannun,et al.  Expression of Neutral Sphingomyelinase Identifies a Distinct Pool of Sphingomyelin Involved in Apoptosis* , 1997, The Journal of Biological Chemistry.

[16]  H. Boeing,et al.  Follow-Up Procedures in EPIC-Germany – Data Quality Aspects , 1999, Annals of Nutrition and Metabolism.

[17]  Bernard R. Rosner,et al.  Fundamentals of Biostatistics. , 1992 .

[18]  H. Boeing,et al.  Recruitment procedures of EPIC-Germany. European Investigation into Cancer and Nutrition. , 1999, Annals of nutrition & metabolism.

[19]  A. Mallinger,et al.  Reproducibility of in vivo measures of platelet membrane phospholipids in human subjects , 1999, Psychiatry Research.

[20]  J. Hartung Nonnegative Minimum Biased Invariant Estimation in Variance Component Models , 1981 .

[21]  Klaus M. Weinberger,et al.  Einsatz von Metabolomics zur Diagnose von Stoffwechselkrankheiten , 2008 .

[22]  P. Francioli,et al.  Plasma Carnitines: Reference Values in an Ambulatory Population , 1993, European journal of clinical chemistry and clinical biochemistry : journal of the Forum of European Clinical Chemistry Societies.

[23]  J. Fleiss The design and analysis of clinical experiments , 1987 .

[24]  E. Rimm,et al.  Adiponectin: stability in plasma over 36 hours and within-person variation over 1 year. , 2003, Clinical chemistry.

[25]  J. Bruce German,et al.  Effects of sample handling and storage on quantitative lipid analysis in human serum , 2009, Metabolomics.

[26]  R. Gerszten,et al.  Application of metabolomics to cardiovascular biomarker and pathway discovery. , 2008, Journal of the American College of Cardiology.

[27]  K. Weinberger,et al.  [Metabolomics in diagnosing metabolic diseases]. , 2008, Therapeutische Umschau. Revue therapeutique.

[28]  F. Toledo,et al.  Increased Levels of Plasma Acylcarnitines in Obesity and Type 2 Diabetes and Identification of a Marker of Glucolipotoxicity , 2010, Obesity.

[29]  S. Willich,et al.  Within-subject variation of plasma resistin levels over a 1-year period , 2007, Clinical chemistry and laboratory medicine.

[30]  Joshua D. Knowles,et al.  Development of a robust and repeatable UPLC-MS method for the long-term metabolomic study of human serum. , 2009, Analytical chemistry.

[31]  F. Pecker,et al.  Sphingomyelinases: their regulation and roles in cardiovascular pathophysiology. , 2009, Cardiovascular research.

[32]  K. Anastos,et al.  Within-Individual Stability of Obesity-Related Biomarkers among Women , 2007, Cancer Epidemiology Biomarkers & Prevention.

[33]  Christian Gieger,et al.  A genome-wide perspective of genetic variation in human metabolism , 2010, Nature Genetics.

[34]  Georg Heinze,et al.  Long-term stability of amino acids and acylcarnitines in dried blood spots. , 2007, Clinical chemistry.

[35]  J. Vockley,et al.  Rare Disorders of Metabolism with Elevated Butyryl- and Isobutyryl-Carnitine Detected by Tandem Mass Spectrometry Newborn Screening , 2003, Pediatric Research.

[36]  A. Saghatelian,et al.  Exploring disease through metabolomics. , 2010, ACS chemical biology.