Characterization of metabolic responses to healthy diets and association with blood pressure: application to the Optimal Macronutrient Intake Trial for Heart Health (OmniHeart), a randomized controlled study
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Published version
Author(s)
Loo, Ruey Leng
Zou, Xin
Appel, Lawrence J
Nicholson, Jeremy K
Holmes, Elaine
Type
Journal Article
Abstract
Background
Interindividual variation in the response to diet is common, but the underlying mechanism for such variation is unclear.
Objective
The objective of this study was to use a metabolic profiling approach to identify a panel of urinary metabolites representing individuals demonstrating typical (homogeneous) metabolic responses to healthy diets, and subsequently to define the association of these metabolites with improvement of risk factors for cardiovascular diseases (CVDs).
Design
24-h urine samples from 158 participants with pre-hypertension and stage 1 hypertension, collected at baseline and following the consumption of a carbohydrate-rich, a protein-rich, and a monounsaturated fat–rich healthy diet (6 wk/diet) in a randomized, crossover study, were analyzed by proton (1H) nuclear magnetic resonance (NMR) spectroscopy. Urinary metabolite profiles were interrogated to identify typical and variable responses to each diet. We quantified the differences in absolute excretion of metabolites, distinguishing between dietary comparisons within the typical response groups, and established their associations with CVD risk factors using linear regression.
Results
Globally all 3 diets induced a similar pattern of change in the urinary metabolic profiles for the majority of participants (60.1%). Diet-dependent metabolic variation was not significantly associated with total cholesterol or low-density lipoprotein (LDL) cholesterol concentration. However, blood pressure (BP) was found to be significantly associated with 6 urinary metabolites reflecting dietary intake [proline-betaine (inverse), carnitine (direct)], gut microbial co-metabolites [hippurate (direct), 4-cresyl sulfate (inverse), phenylacetylglutamine (inverse)], and tryptophan metabolism [N-methyl-2-pyridone-5-carboxamide (inverse)]. A dampened clinical response was observed in some individuals with variable metabolic responses, which could be attributed to nonadherence to diet (≤25.3%), variation in gut microbiome activity (7.6%), or a combination of both (7.0%).
Conclusions
These data indicate interindividual variations in BP in response to dietary change and highlight the potential influence of the gut microbiome in mediating this relation. This approach provides a framework for stratification of individuals undergoing dietary management. The original OmniHeart intervention study and the metabolomics study were registered at www.clinicaltrials.gov as NCT00051350 and NCT03369535, respectively.
Interindividual variation in the response to diet is common, but the underlying mechanism for such variation is unclear.
Objective
The objective of this study was to use a metabolic profiling approach to identify a panel of urinary metabolites representing individuals demonstrating typical (homogeneous) metabolic responses to healthy diets, and subsequently to define the association of these metabolites with improvement of risk factors for cardiovascular diseases (CVDs).
Design
24-h urine samples from 158 participants with pre-hypertension and stage 1 hypertension, collected at baseline and following the consumption of a carbohydrate-rich, a protein-rich, and a monounsaturated fat–rich healthy diet (6 wk/diet) in a randomized, crossover study, were analyzed by proton (1H) nuclear magnetic resonance (NMR) spectroscopy. Urinary metabolite profiles were interrogated to identify typical and variable responses to each diet. We quantified the differences in absolute excretion of metabolites, distinguishing between dietary comparisons within the typical response groups, and established their associations with CVD risk factors using linear regression.
Results
Globally all 3 diets induced a similar pattern of change in the urinary metabolic profiles for the majority of participants (60.1%). Diet-dependent metabolic variation was not significantly associated with total cholesterol or low-density lipoprotein (LDL) cholesterol concentration. However, blood pressure (BP) was found to be significantly associated with 6 urinary metabolites reflecting dietary intake [proline-betaine (inverse), carnitine (direct)], gut microbial co-metabolites [hippurate (direct), 4-cresyl sulfate (inverse), phenylacetylglutamine (inverse)], and tryptophan metabolism [N-methyl-2-pyridone-5-carboxamide (inverse)]. A dampened clinical response was observed in some individuals with variable metabolic responses, which could be attributed to nonadherence to diet (≤25.3%), variation in gut microbiome activity (7.6%), or a combination of both (7.0%).
Conclusions
These data indicate interindividual variations in BP in response to dietary change and highlight the potential influence of the gut microbiome in mediating this relation. This approach provides a framework for stratification of individuals undergoing dietary management. The original OmniHeart intervention study and the metabolomics study were registered at www.clinicaltrials.gov as NCT00051350 and NCT03369535, respectively.
Date Issued
2018-03-01
Date Acceptance
2017-12-13
Citation
AMERICAN JOURNAL OF CLINICAL NUTRITION, 2018, 107 (3), pp.323-334
ISSN
0002-9165
Publisher
AMER SOC NUTRITION-ASN
Start Page
323
End Page
334
Journal / Book Title
AMERICAN JOURNAL OF CLINICAL NUTRITION
Volume
107
Issue
3
Copyright Statement
© 2018 American Society for Nutrition.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000427882800004&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Life Sciences & Biomedicine
Nutrition & Dietetics
diets
gut microbiome
hypertension
metabolic profiling
metabonomic
metabolomic
personalized health care
OPTIMIZED STATISTICAL APPROACH
NUTRITIONAL INTERVENTION
1-METHYLNICOTINAMIDE MNA
HYPERTENSIVE-RATS
PROLINE BETAINE
L-CARNITINE
CHOLESTEROL
BIOMARKERS
SERUM
IDENTIFICATION
Publication Status
Published
Date Publish Online
2018-03-16