bioRxivMolecular BiologyPreprint
Differential Impacts of Dietary Modification on Individual Metabolic Phenotypes and their Relationship to Blood Pressure: Evidence of Latent Dietary Responder Sub-phenotypes
Ruey Leng LooiD, Xin Zou, Lawrence J. AppeliD, Jeremy Kirk NicholsoniD, Elaine C. HolmesiD
Abstract
BackgroundHypertension is a worldwide public health issue with significant comorbidity and mortality. We aimed to identify urinary metabolic phenotypes associated with three healthy diets and to establish their relationship to blood pressure (BP).\n\nMethods and Results--24-h urine samples from 158 participants, with pre-hypertension and hypertension, consumed a carbohydrate-rich, a protein-rich and a monounsaturated fat-rich healthy diet (6-week per diet) in randomized order, were analyzed by nuclear magnetic resonance spectroscopy. Combinations of metabolites significantly associated with each diet were identified, and associations between these metabolites and cardiovascular disease risk were established. We found coherent responses to all three diets including increased excretion of metabolites originating from vegetables/fruits, protein, tryptophan metabolism and gut microbial-mammalian co-metabolism. Proline betaine (marker of citrus fruit) was significantly inversely associated with systolic BP; 4-cresyl sulfate (gut microbial metabolite) inversely correlated with both systolic and diastolic BP; and hippurate (gut microbial metabolite) - directly associated with reduced systolic BP.\n\nConclusionsVariation in metabolic phenotypes in response to specific diets may hold clues as to the mechanisms underlying inter-individual differences in dietary response. Stratification of individuals based on diet-specific urinary phenotypes highlights the feasibility for individualized approaches to dietary therapy for lowering BP.\n\nClinical Trial RegistrationThis intervention study is registered at http://www.clinicaltrials.gov as NCT00051350
- organism: human
- assay: metabolomics
- research focus: differential expression
- approach: statistical model
- Citations
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