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Rundblad A, Christensen JJ, Hustad KS, Bastani NE, Ottestad I, Holven KB, Ulven SM. Associations between dietary intake and glucose tolerance in clinical and metabolomics-based metabotypes. Genes Nutr 2023; 18:3. [PMID: 36899329 PMCID: PMC10007735 DOI: 10.1186/s12263-023-00721-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 01/23/2023] [Indexed: 03/12/2023]
Abstract
BACKGROUND Metabotyping is a novel concept to group metabolically similar individuals. Different metabotypes may respond differently to dietary interventions; hence, metabotyping may become an important future tool in precision nutrition strategies. However, it is not known if metabotyping based on comprehensive omic data provides more useful identification of metabotypes compared to metabotyping based on only a few clinically relevant metabolites. AIM This study aimed to investigate if associations between habitual dietary intake and glucose tolerance depend on metabotypes identified from standard clinical variables or comprehensive nuclear magnetic resonance (NMR) metabolomics. METHODS We used cross-sectional data from participants recruited through advertisements aimed at people at risk of type 2 diabetes mellitus (n = 203). Glucose tolerance was assessed with a 2-h oral glucose tolerance test (OGTT), and habitual dietary intake was recorded with a food frequency questionnaire. Lipoprotein subclasses and various metabolites were quantified with NMR spectroscopy, and plasma carotenoids were quantified using high-performance liquid chromatography. We divided participants into favorable and unfavorable clinical metabotypes based on established cutoffs for HbA1c and fasting and 2-h OGTT glucose. Favorable and unfavorable NMR metabotypes were created using k-means clustering of NMR metabolites. RESULTS While the clinical metabotypes were separated by glycemic variables, the NMR metabotypes were mainly separated by variables related to lipoproteins. A high intake of vegetables was associated with a better glucose tolerance in the unfavorable, but not the favorable clinical metabotype (interaction, p = 0.01). This interaction was confirmed using plasma concentrations of lutein and zeaxanthin, objective biomarkers of vegetable intake. Although non-significantly, the association between glucose tolerance and fiber intake depended on the clinical metabotypes, while the association between glucose tolerance and intake of saturated fatty acids and dietary fat sources depended on the NMR metabotypes. CONCLUSION Metabotyping may be a useful tool to tailor dietary interventions that will benefit specific groups of individuals. The variables that are used to create metabotypes will affect the association between dietary intake and disease risk.
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Affiliation(s)
- Amanda Rundblad
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, P.O. Box 1046 Blindern, 0317, Oslo, Norway.
| | - Jacob J Christensen
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, P.O. Box 1046 Blindern, 0317, Oslo, Norway
| | - Kristin S Hustad
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, P.O. Box 1046 Blindern, 0317, Oslo, Norway
| | - Nasser E Bastani
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, P.O. Box 1046 Blindern, 0317, Oslo, Norway
| | - Inger Ottestad
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, P.O. Box 1046 Blindern, 0317, Oslo, Norway
| | - Kirsten B Holven
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, P.O. Box 1046 Blindern, 0317, Oslo, Norway.,National Advisory Unit on Familial Hypercholesterolemia, Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
| | - Stine M Ulven
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, P.O. Box 1046 Blindern, 0317, Oslo, Norway
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Hillesheim E, Brennan L. Metabotyping: a tool for identifying subgroups for tailored nutrition advice. Proc Nutr Soc 2023;:1-12. [PMID: 36727494 DOI: 10.1017/S0029665123000058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Diet-related diseases are the leading cause of death globally and strategies to tailor effective nutrition advice are required. Personalised nutrition advice is increasingly recognised as more effective than population-level advice to improve dietary intake and health outcomes. A potential tool to deliver personalised nutrition advice is metabotyping which groups individuals into homogeneous subgroups (metabotypes) using metabolic profiles. In summary, metabotyping has been successfully employed in human nutrition research to identify subgroups of individuals with differential responses to dietary challenges and interventions and diet–disease associations. The suitability of metabotyping to identify clinically relevant subgroups is corroborated by other fields such as diabetes research where metabolic profiling has been intensely used to identify subgroups of patients that display patterns of disease progression and complications. However, there is a paucity of studies examining the efficacy of the approach to improve dietary intake and health parameters. While the application of metabotypes to tailor and deliver nutrition advice is very promising, further evidence from randomised controlled trials is necessary for further development and acceptance of the approach.
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Mena P, Favari C, Acharjee A, Chernbumroong S, Bresciani L, Curti C, Brighenti F, Heiss C, Rodriguez-Mateos A, Del Rio D. Metabotypes of flavan-3-ol colonic metabolites after cranberry intake: elucidation and statistical approaches. Eur J Nutr 2021. [PMID: 34750642 DOI: 10.1007/s00394-021-02692-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 09/28/2021] [Indexed: 12/18/2022]
Abstract
Purpose Extensive inter-individual variability exists in the production of flavan-3-ol metabolites. Preliminary metabolic phenotypes (metabotypes) have been defined, but there is no consensus on the existence of metabotypes associated with the catabolism of catechins and proanthocyanidins. This study aims at elucidating the presence of different metabotypes in the urinary excretion of main flavan-3-ol colonic metabolites after consumption of cranberry products and at assessing the impact of the statistical technique used for metabotyping. Methods Data on urinary concentrations of phenyl-γ-valerolactones and 3-(hydroxyphenyl)propanoic acid derivatives from two human interventions has been used. Different multivariate statistics, principal component analysis (PCA), cluster analysis, and partial least square-discriminant analysis (PLS-DA), have been considered. Results Data pre-treatment plays a major role on resulting PCA models. Cluster analysis based on k-means and a final consensus algorithm lead to quantitative-based models, while the expectation–maximization algorithm and clustering according to principal component scores yield metabotypes characterized by quali-quantitative differences in the excretion of colonic metabolites. PLS-DA, together with univariate analyses, has served to validate the urinary metabotypes in the production of flavan-3-ol metabolites and to confirm the robustness of the methodological approach. Conclusions This work proposes a methodological workflow for metabotype definition and highlights the importance of data pre-treatment and clustering methods on the final outcomes for a given dataset. It represents an additional step toward the understanding of the inter-individual variability in flavan-3-ol metabolism. Trial registration The acute study was registered at clinicaltrials.gov as NCT02517775, August 7, 2015; the chronic study was registered at clinicaltrials.gov as NCT02764749, May 6, 2016. Supplementary Information The online version contains supplementary material available at 10.1007/s00394-021-02692-z.
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Hillesheim E, Ryan MF, Gibney E, Roche HM, Brennan L. Optimisation of a metabotype approach to deliver targeted dietary advice. Nutr Metab (Lond) 2020; 17:82. [PMID: 33005208 PMCID: PMC7523294 DOI: 10.1186/s12986-020-00499-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 09/08/2020] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Targeted nutrition is defined as dietary advice tailored at a group level. Groups known as metabotypes can be identified based on individual metabolic profiles. Metabotypes have been associated with differential responses to diet, which support their use to deliver dietary advice. We aimed to optimise a metabotype approach to deliver targeted dietary advice by encompassing more specific recommendations on nutrient and food intakes and dietary behaviours. METHODS Participants (n = 207) were classified into three metabotypes based on four biomarkers (triacylglycerol, total cholesterol, HDL-cholesterol and glucose) and using a k-means cluster model. Participants in metabotype-1 had the highest average HDL-cholesterol, in metabotype-2 the lowest triacylglycerol and total cholesterol, and in metabotype-3 the highest triacylglycerol and total cholesterol. For each participant, dietary advice was assigned using decision trees for both metabotype (group level) and personalised (individual level) approaches. Agreement between methods was compared at the message level and the metabotype approach was optimised to incorporate messages exclusively assigned by the personalised approach and current dietary guidelines. The optimised metabotype approach was subsequently compared with individualised advice manually compiled. RESULTS The metabotype approach comprised advice for improving the intake of saturated fat (69% of participants), fibre (66%) and salt (18%), while the personalised approach assigned advice for improving the intake of folate (63%), fibre (63%), saturated fat (61%), calcium (34%), monounsaturated fat (24%) and salt (14%). Following the optimisation of the metabotype approach, the most frequent messages assigned to address intake of key nutrients were to increase the intake of fruit and vegetables, beans and pulses, dark green vegetables, and oily fish, to limit processed meats and high-fat food products and to choose fibre-rich carbohydrates, low-fat dairy and lean meats (60-69%). An average agreement of 82.8% between metabotype and manual approaches was revealed, with excellent agreements in metabotype-1 (94.4%) and metabotype-3 (92.3%). CONCLUSIONS The optimised metabotype approach proved capable of delivering targeted dietary advice for healthy adults, being highly comparable with individualised advice. The next step is to ascertain whether the optimised metabotype approach is effective in changing diet quality.
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Affiliation(s)
- Elaine Hillesheim
- UCD Institute of Food and Health, UCD School of Agriculture and Food Science, UCD, Dublin 4, Belfield Ireland
- UCD Conway Institute of Biomolecular and Biomedical Research, UCD, Dublin 4, Belfield Ireland
| | - Miriam F. Ryan
- UCD Institute of Food and Health, UCD School of Agriculture and Food Science, UCD, Dublin 4, Belfield Ireland
| | - Eileen Gibney
- UCD Institute of Food and Health, UCD School of Agriculture and Food Science, UCD, Dublin 4, Belfield Ireland
| | - Helen M. Roche
- UCD Conway Institute of Biomolecular and Biomedical Research, UCD, Dublin 4, Belfield Ireland
- Nutrigenomics Research Group, School of Public Health, Physiotherapy and Sports Science & Diabetes Complications Research Centre, UCD, Dublin 4, Belfield Ireland
| | - Lorraine Brennan
- UCD Institute of Food and Health, UCD School of Agriculture and Food Science, UCD, Dublin 4, Belfield Ireland
- UCD Conway Institute of Biomolecular and Biomedical Research, UCD, Dublin 4, Belfield Ireland
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Mena P, Ludwig IA, Tomatis VB, Acharjee A, Calani L, Rosi A, Brighenti F, Ray S, Griffin JL, Bluck LJ, Del Rio D. Inter-individual variability in the production of flavan-3-ol colonic metabolites: preliminary elucidation of urinary metabotypes. Eur J Nutr 2019; 58:1529-1543. [PMID: 29616322 DOI: 10.1007/s00394-018-1683-4] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Accepted: 03/29/2018] [Indexed: 12/11/2022]
Abstract
PURPOSE There is much information on the bioavailability of (poly)phenolic compounds following acute intake of various foods. However, there are only limited data on the effects of repeated and combined exposure to specific (poly)phenol food sources and the inter-individual variability in their bioavailability. This study evaluated the combined urinary excretion of (poly)phenols from green tea and coffee following daily consumption by healthy subjects in free-living conditions. The inter-individual variability in the production of phenolic metabolites was also investigated. METHODS Eleven participants consumed both tablets of green tea and green coffee bean extracts daily for 8 weeks and 24-h urine was collected on five different occasions. The urinary profile of phenolic metabolites and a set of multivariate statistical tests were used to investigate the putative existence of characteristic metabotypes in the production of flavan-3-ol microbial metabolites. RESULTS (Poly)phenolic compounds in the green tea and green coffee bean extracts were absorbed and excreted after simultaneous consumption, with green tea resulting in more inter-individual variability in urinary excretion of phenolic metabolites. Three metabotypes in the production of flavan-3-ol microbial metabolites were tentatively defined, characterized by the excretion of different amounts of trihydroxyphenyl-γ-valerolactones, dihydroxyphenyl-γ-valerolactones, and hydroxyphenylpropionic acids. CONCLUSIONS The selective production of microbiota-derived metabolites from flavan-3-ols and the putative existence of characteristic metabotypes in their production represent an important development in the study of the bioavailability of plant bioactives. These observations will contribute to better understand the health effects and individual differences associated with consumption of flavan-3-ols, arguably the main class of flavonoids in the human diet.
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Affiliation(s)
- Pedro Mena
- Human Nutrition Unit, Department of Food and Drugs, University of Parma, Medical School Building C, Via Volturno, 39, 43125, Parma, Italy.
| | - Iziar A Ludwig
- Human Nutrition Unit, Department of Food and Drugs, University of Parma, Medical School Building C, Via Volturno, 39, 43125, Parma, Italy
- Food Technology Department, Universitat de Lleida-Agrotecnio Center, Lleida, Spain
| | - Virginia B Tomatis
- UK Medical Research Council Elsie Widdowson Laboratory (formerly MRC Human Nutrition Research), Cambridge, UK
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Animesh Acharjee
- UK Medical Research Council Elsie Widdowson Laboratory (formerly MRC Human Nutrition Research), Cambridge, UK
- Department of Biochemistry, University of Cambridge, Cambridge, UK
- Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, UK
- Institute of Translational Medicine, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Luca Calani
- Human Nutrition Unit, Department of Food and Drugs, University of Parma, Medical School Building C, Via Volturno, 39, 43125, Parma, Italy
| | - Alice Rosi
- Human Nutrition Unit, Department of Food and Drugs, University of Parma, Medical School Building C, Via Volturno, 39, 43125, Parma, Italy
| | - Furio Brighenti
- Human Nutrition Unit, Department of Food and Drugs, University of Parma, Medical School Building C, Via Volturno, 39, 43125, Parma, Italy
| | - Sumantra Ray
- UK Medical Research Council Elsie Widdowson Laboratory (formerly MRC Human Nutrition Research), Cambridge, UK
| | - Julian L Griffin
- UK Medical Research Council Elsie Widdowson Laboratory (formerly MRC Human Nutrition Research), Cambridge, UK
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Les J Bluck
- UK Medical Research Council Elsie Widdowson Laboratory (formerly MRC Human Nutrition Research), Cambridge, UK
| | - Daniele Del Rio
- Human Nutrition Unit, Department of Food and Drugs, University of Parma, Medical School Building C, Via Volturno, 39, 43125, Parma, Italy.
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Ulaszewska MM, Mancini A, Garcia-Aloy M, Del Bubba M, Tuohy KM, Vrhovsek U. Isotopic dilution method for bile acid profiling reveals new sulfate glycine-conjugated dihydroxy bile acids and glucuronide bile acids in serum. J Pharm Biomed Anal 2019; 173:1-17. [PMID: 31100508 DOI: 10.1016/j.jpba.2019.05.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Revised: 04/02/2019] [Accepted: 05/02/2019] [Indexed: 01/08/2023]
Abstract
An ultrahigh performance liquid chromatography tandem mass spectrometry method (UHPLC-MS/MS) was developed for the determination of 41 target and 8 additional bile acids isomers (BAs) in biological fluids. BAs were analysed by solid-phase extraction on 50 μL biofluid-aliquots, followed by a properly optimised 27 min-chromatographic run. The method provided high sensitivity (limits of detection 0.0002-0.03 μM, limits of quantitation 0.0007-0.11 μM), linearity (R2>0.99) and precision (relative standard deviations ≤16%). A strategy of scheduled/ unscheduled injections of real samples together with neutral loss (80 Da and 176 Da) scans allowed us to find additional bile acid isomers not a priori included in the method, while high resolution full scan and MS/MS fragmentation analysis confirmed their structural adherence to the bile acid family. Moreover this is the first study quantifying four sulfate glycine conjugated-dihydroxy bile acid isomers, independently of the diet and postprandial time. Application to a dietary intervention kinetic study confirmed the existence of possible metabotypes amongst the study population (n = 20). A trend differentiating males from females was observed suggesting that serum samples from women contained smaller amounts of certain bile acids.
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Affiliation(s)
- Maria M Ulaszewska
- Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach (FEM), Via Mach 1, 38010, San Michele all'Adige, Trento, Italy.
| | - Andrea Mancini
- Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach (FEM), Via Mach 1, 38010, San Michele all'Adige, Trento, Italy
| | - Mar Garcia-Aloy
- Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach (FEM), Via Mach 1, 38010, San Michele all'Adige, Trento, Italy
| | - Massimo Del Bubba
- Department of Chemistry, University of Florence, Via della Lastruccia 3, 50019, Sesto Fiorentino, Florence, Italy
| | - Kieran Micheal Tuohy
- Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach (FEM), Via Mach 1, 38010, San Michele all'Adige, Trento, Italy
| | - Urska Vrhovsek
- Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach (FEM), Via Mach 1, 38010, San Michele all'Adige, Trento, Italy
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Abstract
Metabonomics, also known as metabolomics, is concerned with the study of metabolite profiles in humans, animals, plants and other systems in order to assess their health or other status and their responses to experimental interventions. Metabonomics is thus widely used in disease diagnosis and in understanding responses to therapies such as drug administration. Pharmacometabonomics, also known as pharmacometabolomics, is a related methodology but with a prognostic as opposed to diagnostic thrust. Pharmacometabonomics aims to predict drug effects including efficacy, safety, metabolism and pharmacokinetics, prior to drug administration, via an analysis of pre-dose metabolite profiles. This article will review the development of pharmacometabonomics as a new field of science that has much promise in helping to deliver more effective personalised medicine, a major goal of twenty-first century healthcare.
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Affiliation(s)
- Jeremy R Everett
- Medway Metabonomics Research Group, University of Greenwich, Kent, UK.
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Urpi-Sarda M, Almanza-Aguilera E, Llorach R, Vázquez-Fresno R, Estruch R, Corella D, Sorli JV, Carmona F, Sanchez-Pla A, Salas-Salvadó J, Andres-Lacueva C. Non-targeted metabolomic biomarkers and metabotypes of type 2 diabetes: A cross-sectional study of PREDIMED trial participants. Diabetes Metab 2018; 45:167-174. [PMID: 29555466 DOI: 10.1016/j.diabet.2018.02.006] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Revised: 01/24/2018] [Accepted: 02/13/2018] [Indexed: 01/20/2023]
Abstract
AIM To characterize the urinary metabolomic fingerprint and multi-metabolite signature associated with type 2 diabetes (T2D), and to classify the population into metabotypes related to T2D. METHODS A metabolomics analysis using the 1H-NMR-based, non-targeted metabolomic approach was conducted to determine the urinary metabolomic fingerprint of T2D compared with non-T2D participants in the PREDIMED trial. The discriminant metabolite fingerprint was subjected to logistic regression analysis and ROC analyses to establish and to assess the multi-metabolite signature of T2D prevalence, respectively. Metabotypes associated with T2D were identified using the k-means algorithm. RESULTS A total of 33 metabolites were significantly different (P<0.05) between T2D and non-T2D participants. The multi-metabolite signature of T2D comprised high levels of methylsuccinate, alanine, dimethylglycine and guanidoacetate, and reduced levels of glutamine, methylguanidine, 3-hydroxymandelate and hippurate, and had a 96.4% AUC, which was higher than the metabolites on their own and glucose. Amino-acid and carbohydrate metabolism were the main metabolic alterations in T2D, and various metabotypes were identified in the studied population. Among T2D participants, those with a metabotype of higher levels of phenylalanine, phenylacetylglutamine, p-cresol and acetoacetate had significantly higher levels of plasma glucose. CONCLUSION The multi-metabolite signature of T2D highlights the altered metabolic fingerprint associated mainly with amino-acid, carbohydrate and microbiota metabolism. Metabotypes identified in this patient population could be related to higher risk of long-term cardiovascular events and therefore require further studies. Metabolomics is a useful tool for elucidating the metabolic complexity and interindividual variation in T2D towards the development of stratified precision nutrition and medicine. Trial registration at www.controlled-trials.com: ISRCTN35739639.
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Affiliation(s)
- M Urpi-Sarda
- Biomarkers and Nutrimetabolomic Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA-UB, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain; CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain.
| | - E Almanza-Aguilera
- Biomarkers and Nutrimetabolomic Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA-UB, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain; CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - R Llorach
- Biomarkers and Nutrimetabolomic Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA-UB, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain; CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - R Vázquez-Fresno
- Biomarkers and Nutrimetabolomic Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA-UB, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain; Department of Computing Science and Biological Sciences, University of Alberta, Edmonton, Canada
| | - R Estruch
- Department of Internal Medicine, Hospital Clinic, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Barcelona, Spain; CIBER Pathophysiology of Obesity and Nutrition (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain
| | - D Corella
- CIBER Pathophysiology of Obesity and Nutrition (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine and Public Health, University of Valencia, Valencia, Spain
| | - J V Sorli
- CIBER Pathophysiology of Obesity and Nutrition (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine and Public Health, University of Valencia, Valencia, Spain
| | - F Carmona
- Statistics Department, Biology Faculty, University of Barcelona, Barcelona, Spain
| | - A Sanchez-Pla
- Statistics Department, Biology Faculty, University of Barcelona, Barcelona, Spain
| | - J Salas-Salvadó
- CIBER Pathophysiology of Obesity and Nutrition (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain; Human Nutrition Unit, Biochemistry and Biotechnology Department. Hospital Universitari de Sant Joan de Reus, Institut d'Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, Reus, Spain
| | - C Andres-Lacueva
- Biomarkers and Nutrimetabolomic Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA-UB, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain; CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain.
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Baldiviez LM, Keim NL, Laugero KD, Hwang DH, Huang L, Woodhouse LR, Burnett DJ, Zerofsky MS, Bonnel EL, Allen LH, Newman JW, Stephensen CB. Design and implementation of a cross-sectional nutritional phenotyping study in healthy US adults. BMC Nutr 2017; 3:79. [PMID: 32153856 PMCID: PMC7050916 DOI: 10.1186/s40795-017-0197-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Accepted: 10/03/2017] [Indexed: 11/30/2022] Open
Abstract
Background Metabolic imbalance is a key determinant of risk of chronic diseases. Metabolic health cannot be assessed solely by body mass calculations or by static, fasted state biochemical readouts. Although previous studies have described temporal responses to dietary challenges, these studies fail to assess the environmental factors associated with certain metabolic phenotypes and therefore, provide little scientific rationale for potentially effective intervention strategies. Methods/design In this phenotyping study of healthy US adults, we are evaluating lifestyle, biological and environmental factors in addition to metabolic parameters to determine the factors associated with variations in metabolic health. A series of practical fitness, dietary, and emotional challenges are introduced and temporal responses in various areas of specialization, including immunology, metabolomics, and endocrinology, are monitored. We expect that this study will identify key factors related to healthy or unhealthy metabolic phenotypes (metabotypes) that may be modifiable targets for the prevention of chronic diseases in an individual. Discussion This study will provide novel insights into metabolic variability among healthy adults in balanced strata defined by sex, age and body mass index. Usual dietary intake and physical activity will be evaluated across these strata to determine how diet is associated with health status defined using many indicators including immune function, metabolism, body composition, physiology, response to exercise andmeal challenges and neuroendocrine assessment. A principal study goal is to identify dietary and other personal factors that will differentiate different levels of "health" among study participants. Trial registration ClinicalTrials.gov NCT02367287.
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Affiliation(s)
- Lacey M Baldiviez
- 1United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA USA.,2Department of Nutrition, University of California Davis, Davis, CA USA
| | - Nancy L Keim
- 1United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA USA.,2Department of Nutrition, University of California Davis, Davis, CA USA
| | - Kevin D Laugero
- 1United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA USA.,2Department of Nutrition, University of California Davis, Davis, CA USA
| | - Daniel H Hwang
- 1United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA USA.,2Department of Nutrition, University of California Davis, Davis, CA USA
| | - Liping Huang
- 1United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA USA.,2Department of Nutrition, University of California Davis, Davis, CA USA
| | - Leslie R Woodhouse
- 1United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA USA.,2Department of Nutrition, University of California Davis, Davis, CA USA
| | - Dustin J Burnett
- 1United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA USA.,2Department of Nutrition, University of California Davis, Davis, CA USA
| | - Melissa S Zerofsky
- 1United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA USA
| | - Ellen L Bonnel
- 1United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA USA.,2Department of Nutrition, University of California Davis, Davis, CA USA
| | - Lindsay H Allen
- 1United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA USA.,2Department of Nutrition, University of California Davis, Davis, CA USA
| | - John W Newman
- 1United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA USA.,2Department of Nutrition, University of California Davis, Davis, CA USA.,NIH West Coast Metabolomics Center, Davis, CA USA
| | - Charles B Stephensen
- 1United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA USA.,2Department of Nutrition, University of California Davis, Davis, CA USA
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Espín JC, González-Sarrías A, Tomás-Barberán FA. The gut microbiota: A key factor in the therapeutic effects of (poly)phenols. Biochem Pharmacol 2017; 139:82-93. [PMID: 28483461 DOI: 10.1016/j.bcp.2017.04.033] [Citation(s) in RCA: 361] [Impact Index Per Article: 51.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Accepted: 04/21/2017] [Indexed: 12/13/2022]
Abstract
(Poly)phenols (PPs) constitute a large family of phytochemicals with high chemical diversity that are known to be active principles of plant-derived nutraceuticals and herbal medicinal products. Their pharmacological activity, however, is difficult to demonstrate due to their mild physiological effects, and to the large inter-individual variability observed. Many PPs have little bioavailability and reach the colon almost unaltered. There they encounter the gut microbes resulting in a two-way interaction in which PPs modulate the gut microbiota composition, and the intestinal microbes catabolize the ingested PPs to release metabolites that are often more active and better absorbed than the native phenolic compounds. The type and quantity of the PP metabolites produced in humans depend on the gut microbiota composition and function, and different metabotypes have been identified. However, not all the metabolites have the same biological activity, and therefore the final health effects of dietary PPs depend on the gut microbiota composition. Stratification in clinical trials according to individuals' metabotypes is necessary to fully understand the health effects of PPs. In this review, we present and discuss the most significant and updated knowledge regarding the reciprocal interrelation of the gut microbiota with dietary PPs as a key factor that modulates the health effects of these compounds. The review will focus in those PPs that are known to be metabolized by gut microbiota resulting in bioactive metabolites.
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Barroso E, Muñoz-González I, Jiménez E, Bartolomé B, Moreno-Arribas MV, Peláez C, Del Carmen Martínez-Cuesta M, Requena T. Phylogenetic profile of gut microbiota in healthy adults after moderate intake of red wine. Mol Nutr Food Res 2016; 61. [PMID: 27794201 DOI: 10.1002/mnfr.201600620] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Revised: 10/20/2016] [Accepted: 10/24/2016] [Indexed: 01/22/2023]
Abstract
SCOPE There is growing interest in understanding how human colonic microbiota can be modified by dietary habits. We examined the influence of moderate red wine intake on the colonic microbiota of 15 healthy volunteers, related to the high concentration of polyphenols present in this beverage. The volunteers were classified into high, moderate, and low polyphenol metabolizers (metabotypes) due to their ability to metabolize polyphenols and the results were compared with that of five control (no wine intake) subjects. METHODS AND RESULTS We analyzed the composition, diversity, and dynamics of their fecal microbiota before and after 1 month of wine consumption. The 16S rDNA sequencing allowed detection of 2324 phylotypes, of which only 30 were found over the 0.5% of mean relative frequency, representing 84.6% of the total taxonomical assignments. The samples clustered more strongly by individuals than by wine intake or metabotypes, however an increase in diversity, after the wine intake, was observed. CONCLUSION The results of this study suggest an increase in the global fecal microbial diversity associated to the consumption of red wine, confirm the high variability of the microbiota from different individuals, and show the stability of their singular microbiota composition to small and short-term dietary changes.
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Affiliation(s)
- Elvira Barroso
- Instituto de Investigación en Ciencias de la Alimentación, CIAL (CSIC-UAM), CEI (UAM+CSIC), Madrid, Spain
| | - Irene Muñoz-González
- Instituto de Investigación en Ciencias de la Alimentación, CIAL (CSIC-UAM), CEI (UAM+CSIC), Madrid, Spain
| | - Esther Jiménez
- Departamento de Nutrición, Bromatologı́a y Tecnología de los Alimentos, Universidad Complutense de Madrid, Madrid, Spain.,ProbiSearch, Tres Cantos, Spain
| | - Begoña Bartolomé
- Instituto de Investigación en Ciencias de la Alimentación, CIAL (CSIC-UAM), CEI (UAM+CSIC), Madrid, Spain
| | - M Victoria Moreno-Arribas
- Instituto de Investigación en Ciencias de la Alimentación, CIAL (CSIC-UAM), CEI (UAM+CSIC), Madrid, Spain
| | - Carmen Peláez
- Instituto de Investigación en Ciencias de la Alimentación, CIAL (CSIC-UAM), CEI (UAM+CSIC), Madrid, Spain
| | | | - Teresa Requena
- Instituto de Investigación en Ciencias de la Alimentación, CIAL (CSIC-UAM), CEI (UAM+CSIC), Madrid, Spain
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