Literature DB >> 32954362

Nutriome-metabolome relationships provide insights into dietary intake and metabolism.

Joram M Posma1,2, Isabel Garcia-Perez3, Gary Frost3, Ghadeer S Aljuraiban4,5, Queenie Chan5,6, Linda Van Horn7, Martha Daviglus8, Jeremiah Stamler7, Elaine Holmes3,9,10,11, Paul Elliott2,5,6,9,12,13, Jeremy K Nicholson10,11.   

Abstract

Dietary assessment traditionally relies on self-reported data which are often inaccurate and may result in erroneous diet-disease risk associations. We illustrate how urinary metabolic phenotyping can be used as alternative approach for obtaining information on dietary patterns. We used two multi-pass 24-hr dietary recalls, obtained on two occasions on average three weeks apart, paired with two 24-hr urine collections from 1,848 U.S. individuals; 67 nutrients influenced the urinary metabotype measured with 1H-NMR spectroscopy characterized by 46 structurally identified metabolites. We investigated the stability of each metabolite over time and showed that the urinary metabolic profile is more stable within individuals than reported dietary patterns. The 46 metabolites accurately predicted healthy and unhealthy dietary patterns in a free-living U.S. cohort and replicated in an independent U.K. cohort. We mapped these metabolites into a host-microbial metabolic network to identify key pathways and functions. These data can be used in future studies to evaluate how this set of diet-derived, stable, measurable bioanalytical markers are associated with disease risk. This knowledge may give new insights into biological pathways that characterize the shift from a healthy to unhealthy metabolic phenotype and hence give entry points for prevention and intervention strategies.

Entities:  

Year:  2020        PMID: 32954362      PMCID: PMC7497842          DOI: 10.1038/s43016-020-0093-y

Source DB:  PubMed          Journal:  Nat Food        ISSN: 2662-1355


  71 in total

1.  Specificity and stability in topology of protein networks.

Authors:  Sergei Maslov; Kim Sneppen
Journal:  Science       Date:  2002-05-03       Impact factor: 47.728

2.  Analytical reproducibility in (1)H NMR-based metabonomic urinalysis.

Authors:  Hector C Keun; Timothy M D Ebbels; Henrik Antti; Mary E Bollard; Olaf Beckonert; Götz Schlotterbeck; Hans Senn; Urs Niederhauser; Elaine Holmes; John C Lindon; Jeremy K Nicholson
Journal:  Chem Res Toxicol       Date:  2002-11       Impact factor: 3.739

3.  Diet, nutrition and the prevention of chronic diseases.

Authors: 
Journal:  World Health Organ Tech Rep Ser       Date:  2003

4.  Personalized Nutrition by Prediction of Glycemic Responses.

Authors:  David Zeevi; Tal Korem; Niv Zmora; David Israeli; Daphna Rothschild; Adina Weinberger; Orly Ben-Yacov; Dar Lador; Tali Avnit-Sagi; Maya Lotan-Pompan; Jotham Suez; Jemal Ali Mahdi; Elad Matot; Gal Malka; Noa Kosower; Michal Rein; Gili Zilberman-Schapira; Lenka Dohnalová; Meirav Pevsner-Fischer; Rony Bikovsky; Zamir Halpern; Eran Elinav; Eran Segal
Journal:  Cell       Date:  2015-11-19       Impact factor: 41.582

5.  Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Application in 1H NMR metabonomics.

Authors:  Frank Dieterle; Alfred Ross; Götz Schlotterbeck; Hans Senn
Journal:  Anal Chem       Date:  2006-07-01       Impact factor: 6.986

6.  Associations of sodium intake with obesity, body mass index, waist circumference, and weight.

Authors:  Stella S Yi; Susan M Kansagra
Journal:  Am J Prev Med       Date:  2014-06       Impact factor: 5.043

7.  Predicting basal metabolic rate, new standards and review of previous work.

Authors:  W N Schofield
Journal:  Hum Nutr Clin Nutr       Date:  1985

Review 8.  Use of Metabolomics in Improving Assessment of Dietary Intake.

Authors:  Marta Guasch-Ferré; Shilpa N Bhupathiraju; Frank B Hu
Journal:  Clin Chem       Date:  2017-10-16       Impact factor: 8.327

9.  Spot and Cumulative Urine Samples Are Suitable Replacements for 24-Hour Urine Collections for Objective Measures of Dietary Exposure in Adults Using Metabolite Biomarkers.

Authors:  Thomas Wilson; Isabel Garcia-Perez; Joram M Posma; Amanda J Lloyd; Edward S Chambers; Kathleen Tailliart; Hassan Zubair; Manfred Beckmann; John C Mathers; Elaine Holmes; Gary Frost; John Draper
Journal:  J Nutr       Date:  2019-10-01       Impact factor: 4.798

10.  Structure, function and diversity of the healthy human microbiome.

Authors: 
Journal:  Nature       Date:  2012-06-13       Impact factor: 49.962

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  8 in total

1.  Descriptive analysis of dietary (poly)phenol intake in the subcohort MAX from DCH-NG: "Diet, Cancer and Health-Next Generations cohort".

Authors:  Jytte Halkjær; Cristina Andres-Lacueva; Fabian Lanuza; Raul Zamora-Ros; Agnetha Linn Rostgaard-Hansen; Anne Tjønneland; Rikard Landberg
Journal:  Eur J Nutr       Date:  2022-08-22       Impact factor: 4.865

Review 2.  Bioactives in the Food Supply: Effects on CVD Health.

Authors:  Sisi Cao; Connie M Weaver
Journal:  Curr Atheroscler Rep       Date:  2022-05-28       Impact factor: 5.967

3.  Blood pressure interactions with the DASH dietary pattern, sodium, and potassium: The International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP).

Authors:  Queenie Chan; Gina M Wren; Chung-Ho E Lau; Timothy M D Ebbels; Rachel Gibson; Ruey Leng Loo; Ghadeer S Aljuraiban; Joram M Posma; Alan R Dyer; Lyn M Steffen; Beatriz L Rodriguez; Lawrence J Appel; Martha L Daviglus; Paul Elliott; Jeremiah Stamler; Elaine Holmes; Linda Van Horn
Journal:  Am J Clin Nutr       Date:  2022-07-06       Impact factor: 8.472

Review 4.  The Exposome and Toxicology: A Win-Win Collaboration.

Authors:  Robert Barouki; Karine Audouze; Christel Becker; Ludek Blaha; Xavier Coumoul; Spyros Karakitsios; Jana Klanova; Gary W Miller; Elliott J Price; Denis Sarigiannis
Journal:  Toxicol Sci       Date:  2022-02-28       Impact factor: 4.109

5.  Urinary metabolic biomarkers of diet quality in European children are associated with metabolic health.

Authors:  Nikos Stratakis; Alexandros P Siskos; Eleni Papadopoulou; Hector C Keun; Leda Chatzi; Anh N Nguyen; Yinqi Zhao; Katerina Margetaki; Chung-Ho E Lau; Muireann Coen; Lea Maitre; Silvia Fernández-Barrés; Lydiane Agier; Sandra Andrusaityte; Xavier Basagaña; Anne Lise Brantsaeter; Maribel Casas; Serena Fossati; Regina Grazuleviciene; Barbara Heude; Rosemary Rc McEachan; Helle Margrete Meltzer; Christopher Millett; Fernanda Rauber; Oliver Robinson; Theano Roumeliotaki; Eva Borras; Eduard Sabidó; Jose Urquiza; Marina Vafeiadi; Paolo Vineis; Trudy Voortman; John Wright; David V Conti; Martine Vrijheid
Journal:  Elife       Date:  2022-01-25       Impact factor: 8.140

6.  Microbiota responses to different prebiotics are conserved within individuals and associated with habitual fiber intake.

Authors:  Zachary C Holmes; Max M Villa; Heather K Durand; Sharon Jiang; Eric P Dallow; Brianna L Petrone; Justin D Silverman; Pao-Hwa Lin; Lawrence A David
Journal:  Microbiome       Date:  2022-07-29       Impact factor: 16.837

7.  Docosahexaenoic Acid as the Bidirectional Biomarker of Dietary and Metabolic Risk Patterns in Chinese Children: A Comparison with Plasma and Erythrocyte.

Authors:  Zhi Huang; Ping Guo; Ying Wang; Ziming Li; Xiaochen Yin; Ming Chen; Yong Liu; Yuming Hu; Bo Chen
Journal:  Nutrients       Date:  2022-07-28       Impact factor: 6.706

Review 8.  You Are What You Eat: Application of Metabolomics Approaches to Advance Nutrition Research.

Authors:  Abdul-Hamid M Emwas; Nahla Al-Rifai; Kacper Szczepski; Shuruq Alsuhaymi; Saleh Rayyan; Hanan Almahasheer; Mariusz Jaremko; Lorraine Brennan; Joanna Izabela Lachowicz
Journal:  Foods       Date:  2021-05-31
  8 in total

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