Abstract
BackgroundDue to the challenges associated with accurate monitoring of dietary intake in humans, nutritional metabolomics (including food intake biomarkers) analysis as a complementary tool to traditional dietary assessment methods has been explored. Food intake biomarker assessment using postprandial dried blood spot (DBS) collection can be a convenient and accurate means of monitoring dietary intake vs 24-hour urine collection. ObjectiveThe objective of this study was to use nutritional metabolomics analysis to differentiate a high-fat, high-protein meat (HFPM) diet from a high-carbohydrate vegan (HCV) diet in postprandial DBS and 24-hour urine. DesignThis was a randomized controlled crossover feeding trial. Participants/settingParticipants were healthy young adult volunteers (n = 8) in California. The study was completed in August 2019. InterventionThe standardized isocaloric diet interventions included an HFPM and an HCV diet. Participants attended 2 intervention days, separated by a 2-week washout. Main outcome measuresDuring each intervention day, a finger-prick blood sample was collected in the fasting state, 3 hours post breakfast, and 3 hours post lunch. Participants also collected their urine for 24 hours. DBS and urine samples were analyzed by ultra-performance liquid chromatography mass spectrometry to identify potential food intake biomarkers. Statistical analyses performedPrincipal component analysis for discriminatory analysis and univariate analysis using paired t tests were performed. ResultsPrincipal component analysis found no discrimination of baseline DBS samples. In both the postprandial DBS and 24-hour urine, post-HFPM consumption had higher (P < 0.05) levels of acylcarnitines, creatine, and cis-trans hydroxyproline, and the HCV diet was associated with elevated sorbitol (P < 0.05). The HFPM diet had higher concentrations of triacylglycerols with fewer than 54 total carbons in DBS, and 24-hour urine had higher nucleoside mono- and di-phosphates (P < 0.05). ConclusionsNutritional metabolomics profiles of postprandial DBS and 24-hour urine collections were capable of differentiating the HFPM and HCV diets. The potential use of postprandial DBS-based metabolomic analysis deserves further investigation for dietary intake monitoring.
Highlights
ObjectiveThe objective of this study was to use nutritional metabolomics analysis to differentiate a high-fat, high-protein meat (HFPM) diet from a high-carbohydrate vegan (HCV) diet in postprandial dried blood spot (DBS) and 24-hour urine
Due to the challenges associated with accurate monitoring of dietary intake in humans, nutritional metabolomics analysis as a complementary tool to traditional dietary assessment methods has been explored
Similar to the dried blood spot (DBS) samples, the compounds methionine, leucine, and isoleucine were significantly elevated in the HFPM diet urine samples, and sorbitol was significantly elevated in the high-carbohydrate vegan (HCV) diet urine samples (Figure 5).[5,19,26,27,28,29]
Summary
The objective of this study was to use nutritional metabolomics analysis to differentiate a high-fat, high-protein meat (HFPM) diet from a high-carbohydrate vegan (HCV) diet in postprandial DBS and 24-hour urine. Design This was a randomized controlled crossover feeding trial. Main outcome measures During each intervention day, a finger-prick blood sample was collected in the fasting state, 3 hours post breakfast, and 3 hours post lunch. Participants collected their urine for 24 hours. Statistical analyses performed Principal component analysis for discriminatory analysis and univariate analysis using paired t tests were performed
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