Literature DB >> 29917038

Serum untargeted metabolomic profile of the Dietary Approaches to Stop Hypertension (DASH) dietary pattern.

Casey M Rebholz1,2, Alice H Lichtenstein3, Zihe Zheng1,2, Lawrence J Appel1,2,4, Josef Coresh1,2,4.   

Abstract

Background: The Dietary Approaches to Stop Hypertension (DASH) dietary pattern is recommended for cardiovascular disease risk reduction. Assessment of dietary intake has been limited to subjective measures and a few biomarkers from 24-h urine collections. Objective: The aim of the study was to use metabolomics to identify serum compounds that are associated with adherence to the DASH dietary pattern. Design: We conducted untargeted metabolomic profiling in serum specimens collected at the end of 8 wk following the DASH diet (n = 110), the fruit and vegetables diet (n = 111), or a control diet (n = 108) in a multicenter, randomized clinical feeding study (n = 329). Multivariable linear regression was used to determine the associations between the randomized diets and individual log-transformed metabolites after adjustment for age, sex, race, education, body mass index, and hypertension. Partial least-squares discriminant analysis (PLS-DA) was used to identify a panel of compounds that discriminated between the dietary patterns. The area under the curve (C statistic) was calculated as the cumulative ability to distinguish between dietary patterns. We accounted for multiple comparisons with the use of the Bonferroni method (0.05 of 818 metabolites = 6.11 × 10-5).
Results: Serum concentrations of 44 known metabolites differed significantly between participants randomly assigned to the DASH diet compared with both the control diet and the fruit and vegetables diet, which included an amino acid, 2 cofactors and vitamins (n = 2), and lipids (n = 41). With the use of PLS-DA, component 1 explained 29.4% of the variance and component 2 explained 12.6% of the variance. The 10 most influential metabolites for discriminating between the DASH and control dietary patterns were N-methylproline, stachydrine, tryptophan betaine, theobromine, 7-methylurate, chiro-inositol, 3-methylxanthine, methyl glucopyranoside, β-cryptoxanthin, and 7-methylxanthine (C statistic = 0.986). Conclusions: An untargeted metabolomic platform identified a broad array of serum metabolites that differed between the DASH diet and 2 other dietary patterns. This newly identified metabolite panel may be used to assess adherence to the DASH dietary pattern. This trial was registered at http://www.clinicaltrials.gov as NCT03403166.

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Year:  2018        PMID: 29917038      PMCID: PMC6669331          DOI: 10.1093/ajcn/nqy099

Source DB:  PubMed          Journal:  Am J Clin Nutr        ISSN: 0002-9165            Impact factor:   7.045


  37 in total

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Authors:  Ranee Chatterjee; Clemontina A Davenport; Lydia Kwee; David D'Alessio; Laura P Svetkey; Pao-Hwa Lin; Cris A Slentz; Olga Ilkayeva; Johanna Johnson; David Edelman; Svati H Shah
Journal:  Metabolomics       Date:  2020-06-18       Impact factor: 4.290

Review 2.  Metabolomic Biomarkers of Healthy Dietary Patterns and Cardiovascular Outcomes.

Authors:  Hyunju Kim; Casey M Rebholz
Journal:  Curr Atheroscler Rep       Date:  2021-03-30       Impact factor: 5.113

3.  MtpB, a member of the MttB superfamily from the human intestinal acetogen Eubacterium limosum, catalyzes proline betaine demethylation.

Authors:  Jonathan W Picking; Edward J Behrman; Liwen Zhang; Joseph A Krzycki
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4.  Proteomic and Metabolomic Correlates of Healthy Dietary Patterns: The Framingham Heart Study.

Authors:  Maura E Walker; Rebecca J Song; Xiang Xu; Robert E Gerszten; Debby Ngo; Clary B Clish; Laura Corlin; Jiantao Ma; Vanessa Xanthakis; Paul F Jacques; Ramachandran S Vasan
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5.  The Serum Metabolome Identifies Biomarkers of Dietary Acid Load in 2 Studies of Adults with Chronic Kidney Disease.

Authors:  Casey M Rebholz; Aditya Surapaneni; Andrew S Levey; Mark J Sarnak; Lesley A Inker; Lawrence J Appel; Josef Coresh; Morgan E Grams
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6.  Plasma metabolite profiles related to plant-based diets and the risk of type 2 diabetes.

Authors:  Fenglei Wang; Megu Y Baden; Marta Guasch-Ferré; Clemens Wittenbecher; Jun Li; Yanping Li; Yi Wan; Shilpa N Bhupathiraju; Deirdre K Tobias; Clary B Clish; Lorelei A Mucci; A Heather Eliassen; Karen H Costenbader; Elizabeth W Karlson; Alberto Ascherio; Eric B Rimm; JoAnn E Manson; Liming Liang; Frank B Hu
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7.  Metabolomic Markers of Southern Dietary Patterns in the Jackson Heart Study.

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Journal:  Mol Nutr Food Res       Date:  2021-03-11       Impact factor: 5.914

Review 8.  Nutritional Metabolomics and the Classification of Dietary Biomarker Candidates: A Critical Review.

Authors:  Talha Rafiq; Sandi M Azab; Koon K Teo; Lehana Thabane; Sonia S Anand; Katherine M Morrison; Russell J de Souza; Philip Britz-McKibbin
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9.  Serum Metabolites Associated with Healthy Diets in African Americans and European Americans.

Authors:  Hyunju Kim; Emily A Hu; Kari E Wong; Bing Yu; Lyn M Steffen; Sara B Seidelmann; Eric Boerwinkle; Josef Coresh; Casey M Rebholz
Journal:  J Nutr       Date:  2021-01-04       Impact factor: 4.798

10.  Urine and Plasma Metabolome of Healthy Adults Consuming the DASH (Dietary Approaches to Stop Hypertension) Diet: A Randomized Pilot Feeding Study.

Authors:  Shirin Pourafshar; Mira Nicchitta; Crystal C Tyson; Laura P Svetkey; David L Corcoran; James R Bain; Michael J Muehlbauer; Olga Ilkayeva; Thomas M O'Connell; Pao-Hwa Lin; Julia J Scialla
Journal:  Nutrients       Date:  2021-05-22       Impact factor: 5.717

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