Abstract
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.
Highlights
Dietary assessment plays a crucial role in our ability to clarify relationships between dietary exposure and disease causation
One finding of the present study revealed that the TMAO signal in the nuclear magnetic resonance (NMR) spectra was highly correlated to daily urinary nitrogen excretion
Thereby it was possible to make an explorative investigation of the influence of dietary protein exposure on the metabolite profiles at the group level
Summary
Dietary assessment plays a crucial role in our ability to clarify relationships between dietary exposure and disease causation. High-quality dietary information is a key issue in establishing causality in nutritional studies. The best approach to ascertain valid information of the dietary intake is within the context of prospective dietary intervention studies carried out under highly controlled conditions. Well-controlled feeding studies are costly and often contain a relatively small number of participants and have short duration. A considerable proportion of our knowledge relating dietary intake to phenotypes and disease risks comes from population studies using, for the most part, quantitative food diaries, dietary recalls or food frequency questionnaires. Despite being a well accepted methodology, these methods are often inaccurate as they are based on self-reported data and can be prone to misreporting because of inadequate recalls [1,2] and especially serious underreporting of energy intake has been observed in obese people [3,4]
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