Assessment of the Effect of High or Low Protein Diet on the Human Urine Metabolome as Measured by NMR

The objective of this study was to identify urinary metabolite profiles that discriminate between high and low intake of dietary protein during a dietary intervention. Seventy-seven overweight, non-diabetic subjects followed an 8-week low-calorie diet (LCD) and were then randomly assigned to a high (HP) or low (LP) protein diet for 6 months. Twenty-four hours urine samples were collected at baseline (prior to the 8-week LCD) and after dietary intervention; at months 1, 3 and 6, respectively. Metabolite profiling was performed by 1H NMR and chemometrics. Using partial least squares regression (PLS), it was possible to develop excellent prediction models for urinary nitrogen (root mean square error of cross validation (RMSECV) = 1.63 mmol/L; r = 0.89) and urinary creatinine (RMSECV = 0.66 mmol/L; r = 0.98). The obtained high correlations firmly establish the validity of the metabolomic approach since urinary nitrogen is a well established biomarker for daily protein consumption. The models showed that trimethylamine-N-oxide (TMAO) is correlated to urinary nitrogen. Furthermore, urinary creatine was found to be increased by the HP diet whereas citric acid was increased by the LP diet. Despite large variations in individual dietary intake, differentiated metabolite profiles were observed at the dietary group-level.

[1]  D. Higgins,et al.  Influence of acute phytochemical intake on human urinary metabolomic profiles. , 2007, The American journal of clinical nutrition.

[2]  Ying Zhang,et al.  HMDB: the Human Metabolome Database , 2007, Nucleic Acids Res..

[3]  S. Engelsen,et al.  Interval Partial Least-Squares Regression (iPLS): A Comparative Chemometric Study with an Example from Near-Infrared Spectroscopy , 2000 .

[4]  R. Siener,et al.  The effect of different diets on urine composition and the risk of calcium oxalate crystallisation in healthy subjects. , 2002, European urology.

[5]  A. Astrup,et al.  High throughput prediction of chylomicron triglycerides in human plasma by nuclear magnetic resonance and chemometrics , 2010, Nutrition & metabolism.

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

[7]  P. Elliott,et al.  Assessment of analytical reproducibility of 1H NMR spectroscopy based metabonomics for large-scale epidemiological research: the INTERMAP Study. , 2006, Analytical chemistry.

[8]  M. Spraul,et al.  750 MHz 1H and 1H-13C NMR spectroscopy of human blood plasma. , 1995, Analytical chemistry.

[9]  E Holmes,et al.  750 MHz 1H NMR spectroscopy characterisation of the complex metabolic pattern of urine from patients with inborn errors of metabolism: 2-hydroxyglutaric aciduria and maple syrup urine disease. , 1997, Journal of pharmaceutical and biomedical analysis.

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

[11]  L. Lissner,et al.  Dietary underreporting by obese individuals--is it specific or non-specific? , 1995, BMJ.

[12]  M. Wong,et al.  Epidemiological assessment of diet: a comparison of a 7-day diary with a food frequency questionnaire using urinary markers of nitrogen, potassium and sodium. , 2001, International journal of epidemiology.

[13]  Francesco Savorani,et al.  NMR and interval PLS as reliable methods for determination of cholesterol in rodent lipoprotein fractions , 2010, Metabolomics.

[14]  F Savorani,et al.  icoshift: A versatile tool for the rapid alignment of 1D NMR spectra. , 2010, Journal of magnetic resonance.

[15]  M. Katan,et al.  A high-protein diet increases postprandial but not fasting plasma total homocysteine concentrations: a dietary controlled, crossover trial in healthy volunteers. , 2005, The American journal of clinical nutrition.

[16]  N E Day,et al.  Validation of dietary assessment methods in the UK arm of EPIC using weighed records, and 24-hour urinary nitrogen and potassium and serum vitamin C and carotenoids as biomarkers. , 1997, International journal of epidemiology.

[17]  M. Carroll,et al.  Total energy intake of the US population: the third National Health and Nutrition Examination Survey, 1988-1991. , 1995, The American journal of clinical nutrition.

[18]  A. Astrup,et al.  Effect on 24-h energy expenditure of a moderate-fat diet high in monounsaturated fatty acids compared with that of a low-fat, carbohydrate-rich diet: a 6-mo controlled dietary intervention trial. , 2007, The American journal of clinical nutrition.

[19]  L. Dragsted Biomarkers of meat intake and the application of nutrigenomics. , 2010, Meat science.

[20]  W. Yawei,et al.  Analysis of human urine metabolites using SPE and NMR spectroscopy , 2008 .

[21]  R. Sinha,et al.  A Prospective Study of Red and Processed Meat Intake in Relation to Cancer Risk , 2007, PLoS medicine.

[22]  H. Hotelling Analysis of a complex of statistical variables into principal components. , 1933 .

[23]  D A Schoeller,et al.  How accurate is self-reported dietary energy intake? , 2009, Nutrition reviews.

[24]  M. Barker,et al.  Partial least squares for discrimination , 2003 .

[25]  Jeremy K Nicholson,et al.  NMR spectroscopic-based metabonomic studies of urinary metabolite variation in acclimatizing germ-free rats. , 2003, Chemical research in toxicology.

[26]  S. Toubro,et al.  A method to achieve control of dietary macronutrient composition in ad libitum diets consumed by free-living subjects , 1997, European Journal of Clinical Nutrition.

[27]  Elaine Holmes,et al.  Susceptibility of human metabolic phenotypes to dietary modulation. , 2006, Journal of proteome research.

[28]  S. Bingham,et al.  Urine nitrogen as a biomarker for the validation of dietary protein intake. , 2003, The Journal of nutrition.

[29]  D. Bailey,et al.  Trimethylamine oxide, betaine and other osmolytes in deep-sea animals: depth trends and effects on enzymes under hydrostatic pressure. , 2004, Cellular and molecular biology.

[30]  Ian J. Brown,et al.  Human metabolic phenotype diversity and its association with diet and blood pressure , 2008, Nature.

[31]  S. Bingham,et al.  Biomarkers in nutritional epidemiology , 2002, Public Health Nutrition.

[32]  V. Stanford,et al.  Validity of self-reported energy intake in lean and obese young women, using two nutrient databases, compared with total energy expenditure assessed by doubly labeled water , 2001, European Journal of Clinical Nutrition.

[33]  I. Wilson,et al.  Metabonomics, dietary influences and cultural differences: a 1H NMR-based study of urine samples obtained from healthy British and Swedish subjects. , 2004, Journal of pharmaceutical and biomedical analysis.

[34]  R. Sinha,et al.  Meat and meat-mutagen intake and risk of non-Hodgkin lymphoma: results from a NCI-SEER case-control study. , 2006, Carcinogenesis.

[35]  T. Larsen,et al.  The Diet, Obesity and Genes (Diogenes) Dietary Study in eight European countries – a comprehensive design for long‐term intervention , 2010, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[36]  A. Astrup,et al.  Dietary strategy to manipulate ad libitum macronutrient intake, and glycaemic index, across eight European countries in the Diogenes Study , 2010, Obesity reviews : an official journal of the International Association for the Study of Obesity.