Metabolite patterns predicting sex and age in participants of the Karlsruhe Metabolomics and Nutrition (KarMeN) study

Physiological and functional parameters, such as body composition, or physical fitness are known to differ between men and women and to change with age. The goal of this study was to investigate how sex and age-related physiological conditions are reflected in the metabolome of healthy humans and whether sex and age can be predicted based on the plasma and urine metabolite profiles. In the cross-sectional KarMeN (Karlsruhe Metabolomics and Nutrition) study 301 healthy men and women aged 18–80 years were recruited. Participants were characterized in detail applying standard operating procedures for all measurements including anthropometric, clinical, and functional parameters. Fasting blood and 24 h urine samples were analyzed by targeted and untargeted metabolomics approaches, namely by mass spectrometry coupled to one- or comprehensive two-dimensional gas chromatography or liquid chromatography, and by nuclear magnetic resonance spectroscopy. This yielded in total more than 400 analytes in plasma and over 500 analytes in urine. Predictive modelling was applied on the metabolomics data set using different machine learning algorithms. Based on metabolite profiles from urine and plasma, it was possible to identify metabolite patterns which classify participants according to sex with > 90% accuracy. Plasma metabolites important for the correct classification included creatinine, branched-chain amino acids, and sarcosine. Prediction of age was also possible based on metabolite profiles for men and women, separately. Several metabolites important for this prediction could be identified including choline in plasma and sedoheptulose in urine. For women, classification according to their menopausal status was possible from metabolome data with > 80% accuracy. The metabolite profile of human urine and plasma allows the prediction of sex and age with high accuracy, which means that sex and age are associated with a discriminatory metabolite signature in healthy humans and therefore should always be considered in metabolomics studies.

[1]  Doris M Jacobs,et al.  Probing gender-specific metabolism differences in humans by nuclear magnetic resonance-based metabonomics. , 2006, Analytical biochemistry.

[2]  Paul Henman.  Targeted! , 2004 .

[3]  A. Astrup,et al.  Standardization of factors that influence human urine metabolomics , 2011, Metabolomics.

[4]  S. Kulling,et al.  Age-Related Changes of Plasma Bile Acid Concentrations in Healthy Adults—Results from the Cross-Sectional KarMeN Study , 2016, PloS one.

[5]  B. Kiens,et al.  Gender Differences in Skeletal Muscle Substrate Metabolism – Molecular Mechanisms and Insulin Sensitivity , 2014, Front. Endocrinol..

[6]  M. Schulze,et al.  Linking diet, physical activity, cardiorespiratory fitness and obesity to serum metabolite networks: findings from a population-based study , 2014, International Journal of Obesity.

[7]  S. Kulling,et al.  A peaklet-based generic strategy for the untargeted analysis of comprehensive two-dimensional gas chromatography mass spectrometry data sets. , 2015, Journal of chromatography. A.

[8]  Fabian J Theis,et al.  Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers , 2011, PLoS genetics.

[9]  E. Riboli,et al.  North–south gradients in plasma concentrations of B-vitamins and other components of one-carbon metabolism in Western Europe: results from the European Prospective Investigation into Cancer and Nutrition (EPIC) Study , 2012, British Journal of Nutrition.

[10]  T. Ebbels,et al.  Statistical Correlations between NMR Spectroscopy and Direct Infusion FT-ICR Mass Spectrometry Aid Annotation of Unknowns in Metabolomics. , 2016, Analytical chemistry.

[11]  Bernhard Watzl,et al.  The Karlsruhe Metabolomics and Nutrition (KarMeN) Study: Protocol and Methods of a Cross-Sectional Study to Characterize the Metabolome of Healthy Men and Women , 2016, JMIR research protocols.

[12]  Kelly W. Williams,et al.  Differential Effects of Military Training on Fat-Free Mass and Plasma Amino Acid Adaptations in Men and Women , 2012, Nutrients.

[13]  K. Laukens,et al.  Getting Your Peaks in Line: A Review of Alignment Methods for NMR Spectral Data , 2013, Metabolites.

[14]  C. Mølgaard,et al.  Nuclear magnetic resonance-based metabonomics reveals strong sex effect on plasma metabolism in 17-year-old Scandinavians and correlation to retrospective infant plasma parameters. , 2009, Metabolism: clinical and experimental.

[15]  H. Refsum,et al.  Amino acid changes during transition to a vegan diet supplemented with fish in healthy humans , 2016, European Journal of Nutrition.

[16]  D. Kassel,et al.  Urinary metabolites of L-threonine in type 1 diabetes determined by combined gas chromatography/chemical ionization mass spectrometry. , 1986, Biomedical & environmental mass spectrometry.

[17]  A. Mero,et al.  Serum amino acid concentrations in aging men and women , 2003, Amino Acids.

[18]  T. Ebbels,et al.  Optimizing the use of quality control samples for signal drift correction in large-scale urine metabolic profiling studies. , 2012, Analytical chemistry.

[19]  Gabi Kastenmüller,et al.  Network-based approach for analyzing intra- and interfluid metabolite associations in human blood, urine, and saliva. , 2015, Journal of proteome research.

[20]  H. Völzke,et al.  Measuring Biological Age via Metabonomics: The Metabolic Age Score. , 2016, Journal of proteome research.

[21]  T. Lehtimäki,et al.  A metabolic view on menopause and ageing , 2014, Nature Communications.

[22]  M. Milburn,et al.  Analysis of the adult human plasma metabolome. , 2008, Pharmacogenomics.

[23]  E. Gibney,et al.  The relationship between aerobic fitness level and metabolic profiles in healthy adults. , 2013, Molecular nutrition & food research.

[24]  Bowei Xi,et al.  1H NMR metabolomics study of age profiling in children , 2009, NMR in biomedicine.

[25]  Kosuke Saito,et al.  Plasma and Serum Lipidomics of Healthy White Adults Shows Characteristic Profiles by Subjects’ Gender and Age , 2014, PloS one.

[26]  T. Pischon,et al.  Serum metabolites related to cardiorespiratory fitness, physical activity energy expenditure, sedentary time and vigorous activity. , 2014, International journal of sport nutrition and exercise metabolism.

[27]  Sungha Park,et al.  Metabolomic approaches to the normal aging process , 2014, Metabolomics.

[28]  Morten Arendt Rasmussen,et al.  A primer to nutritional metabolomics by NMR spectroscopy and chemometrics , 2013 .

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

[30]  Romanas Chaleckis,et al.  Individual variability in human blood metabolites identifies age-related differences , 2016, Proceedings of the National Academy of Sciences.

[31]  Russ Greiner,et al.  Investigations of the effects of gender, diurnal variation, and age in human urinary metabolomic profiles. , 2007, Analytical chemistry.

[32]  E. Thévenot,et al.  Analysis of the Human Adult Urinary Metabolome Variations with Age, Body Mass Index, and Gender by Implementing a Comprehensive Workflow for Univariate and OPLS Statistical Analyses. , 2015, Journal of proteome research.

[33]  Andrew J Chetwynd,et al.  Use of a pre-analysis osmolality normalisation method to correct for variable urine concentrations and for improved metabolomic analyses. , 2016, Journal of chromatography. A.

[34]  G. Mercuro,et al.  Serum metabolomic profiles suggest influence of sex and oral contraceptive use. , 2014, American journal of translational research.

[35]  N. Verhoeven,et al.  Detection of transaldolase deficiency by quantification of novel seven-carbon chain carbohydrate biomarkers in urine , 2007, Journal of Inherited Metabolic Disease.

[36]  Y. Bao,et al.  The metabolite profiles of the obese population are gender-dependent. , 2014, Journal of proteome research.

[37]  Christian Gieger,et al.  Metabolomic markers reveal novel pathways of ageing and early development in human populations , 2013, International journal of epidemiology.

[38]  R. Sinha,et al.  Sources of Variability in Metabolite Measurements from Urinary Samples , 2014, PloS one.

[39]  C. Gieger,et al.  Human serum metabolic profiles are age dependent , 2012, Aging cell.

[40]  Gender-specific pathway differences in the human serum metabolome , 2015, Metabolomics.

[41]  E. Jellum,et al.  The identification and metabolic origin of 2-furoylglycine and 2,5-furandicarboxylic acid in human urine. , 1972, Clinica chimica acta; international journal of clinical chemistry.

[42]  M. Elisaf,et al.  Gender‐related and age‐related urinalysis of healthy subjects by NMR‐based metabonomics , 2008, NMR in biomedicine.

[43]  G. Schmitz,et al.  A rapid GC-MS method for quantification of positional and geometric isomers of fatty acid methyl esters. , 2012, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[44]  T. Spector,et al.  Targeted metabolomics profiles are strongly correlated with nutritional patterns in women , 2012, Metabolomics.

[45]  Fabian J Theis,et al.  The dynamic range of the human metabolome revealed by challenges , 2012, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

[46]  Erik J. Saude,et al.  Variation of metabolites in normal human urine , 2007, Metabolomics.

[47]  S. Cai,et al.  Identification of biochemical changes in lactovegetarian urine using 1H NMR spectroscopy and pattern recognition , 2010, Analytical and bioanalytical chemistry.

[48]  T. Key,et al.  Plasma concentrations and intakes of amino acids in male meat-eaters, fish-eaters, vegetarians and vegans: a cross-sectional analysis in the EPIC-Oxford cohort , 2015, European Journal of Clinical Nutrition.

[49]  Rasmus Bro,et al.  Automated alignment of chromatographic data , 2006 .

[50]  Joshua D. Knowles,et al.  Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry , 2011, Nature Protocols.

[51]  P. Steinberg,et al.  The influence of a chronic L‐carnitine administration on the plasma metabolome of male Fischer 344 rats* , 2017, Molecular nutrition & food research.

[52]  D. Jacobs,et al.  GC-MS methods for metabolic profiling of microbial fermentation products of dietary polyphenols in human and in vitro intervention studies. , 2008, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[53]  Kang Li,et al.  Plasma Metabolic Profiles in Women are Menopause Dependent , 2015, PloS one.

[54]  Johann A. Gagnon-Bartsch,et al.  Statistical methods for handling unwanted variation in metabolomics data. , 2015, Analytical chemistry.

[55]  P. Brigidi,et al.  Metabolic Signatures of Extreme Longevity in Northern Italian Centenarians Reveal a Complex Remodeling of Lipids, Amino Acids, and Gut Microbiota Metabolism , 2013, PloS one.

[56]  Zerihun T. Dame,et al.  The Human Urine Metabolome , 2013, PloS one.

[57]  D. Simpson.  Citrate excretion: a window on renal metabolism. , 1983, The American journal of physiology.

[58]  J. Manson,et al.  Cumulative consumption of branched-chain amino acids and incidence of type 2 diabetes. , 2016, International journal of epidemiology.

[59]  Burkhard Luy,et al.  Influence of Freezing and Storage Procedure on Human Urine Samples in NMR-Based Metabolomics , 2013, Metabolites.

[60]  K. Pappan,et al.  Differences in metabolite profiles between blood matrices, ages, and sexes among Caucasian individuals and their inter-individual variations , 2013, Metabolomics.

[61]  M. De la Fuente,et al.  Human Aging Is a Metabolome-related Matter of Gender. , 2016, The journals of gerontology. Series A, Biological sciences and medical sciences.

[62]  Björn Egert,et al.  On the applicability of comprehensive two-dimensional gas chromatography combined with a fast-scanning quadrupole mass spectrometer for untargeted large-scale metabolomics. , 2015, Journal of chromatography. A.

[63]  C Zuppi,et al.  1H NMR spectra of normal urines: reference ranges of the major metabolites. , 1997, Clinica chimica acta; international journal of clinical chemistry.

[64]  Douglas B. Kell,et al.  Molecular phenotyping of a UK population: defining the human serum metabolome , 2014, Metabolomics.

[65]  Daniel Raftery,et al.  Identification of 4-deoxythreonic acid present in human urine using HPLC and NMR techniques. , 2009, Journal of pharmaceutical and biomedical analysis.

[66]  H. U. Zacharias,et al.  Performance evaluation of algorithms for the classification of metabolic 1H NMR fingerprints. , 2012, Journal of proteome research.

[67]  H. Blom,et al.  Sedoheptulokinase deficiency due to a 57‐kb deletion in cystinosis patients causes urinary accumulation of sedoheptulose: elucidation of the CARKL gene , 2008, Human mutation.