Literature DB >> 21999107

Stability and robustness of human metabolic phenotypes in response to sequential food challenges.

Silke S Heinzmann1, Claire A Merrifield, Serge Rezzi, Sunil Kochhar, John C Lindon, Elaine Holmes, Jeremy K Nicholson.   

Abstract

High-resolution spectroscopic profiles of biofluids can define metabolic phenotypes, providing a window onto the impact of diet on health to reflect gene-environment interactions. (1)H NMR spectroscopic profiling was used to characterize the effect of nutritional intervention on the stability of the metabolic phenotype of 7 individuals following a controlled 7 day dietary protocol. Inter-individual metabolic differences influenced proportionally more of the spectrum than dietary modulation, with certain individuals displaying a greater stability of metabolic phenotypes than others. Correlation structures between urinary metabolites were identified and used to map inter-individual pathway differences. Choline degradation was the pathway most affected by the individual, suggesting that the gut microbiota influence host metabolic phenotypes. This influence was further emphasized by the highly correlated excretion of the microbial-mammalian co-metabolites phenylacetylglutamine, 4-cresylsulfate (r = 0.87), and indoxylsulfate (r = 0.67) across all individuals. Above the background of inter-individual differences, clear biochemical effects of single type dietary interventions, animal protein, fruit and wine intake, were observed; for example, the spectral variance introduced by fruit ingestion was attributed to the metabolites tartrate, proline betaine, hippurate, and 4-hydroxyhippurate. This differential metabolic baseline and response to selected dietary challenges highlights the importance of understanding individual differences in metabolism and provides a rationale for evaluating dietary interventions and stratification of individuals with respect to guiding nutrition and health programmes.

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21999107     DOI: 10.1021/pr2005764

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  39 in total

Review 1.  The Role of the Gut Microbiome in Predicting Response to Diet and the Development of Precision Nutrition Models. Part II: Results.

Authors:  Riley L Hughes; Mary E Kable; Maria Marco; Nancy L Keim
Journal:  Adv Nutr       Date:  2019-11-01       Impact factor: 8.701

2.  Current status on genome-metabolome-wide associations: an opportunity in nutrition research.

Authors:  Ivan Montoliu; Ulrich Genick; Mirko Ledda; Sebastiano Collino; François-Pierre Martin; Johannes le Coutre; Serge Rezzi
Journal:  Genes Nutr       Date:  2012-10-16       Impact factor: 5.523

Review 3.  Proteomic urinary biomarker approach in renal disease: from discovery to implementation.

Authors:  Joost P Schanstra; Harald Mischak
Journal:  Pediatr Nephrol       Date:  2014-03-15       Impact factor: 3.714

4.  Systems biology analysis of omeprazole therapy in cirrhosis demonstrates significant shifts in gut microbiota composition and function.

Authors:  Jasmohan S Bajaj; I Jane Cox; Naga S Betrapally; Douglas M Heuman; Mitchell L Schubert; Maiyuran Ratneswaran; Phillip B Hylemon; Melanie B White; Kalyani Daita; Nicole A Noble; Masoumeh Sikaroodi; Roger Williams; Mary M E Crossey; Simon D Taylor-Robinson; Patrick M Gillevet
Journal:  Am J Physiol Gastrointest Liver Physiol       Date:  2014-09-25       Impact factor: 4.052

5.  Quantitative assessment of the impact of the gut microbiota on lysine epsilon-acetylation of host proteins using gnotobiotic mice.

Authors:  Gabriel M Simon; Jiye Cheng; Jeffrey I Gordon
Journal:  Proc Natl Acad Sci U S A       Date:  2012-06-25       Impact factor: 11.205

6.  A nonpyrrolysine member of the widely distributed trimethylamine methyltransferase family is a glycine betaine methyltransferase.

Authors:  Tomislav Ticak; Duncan J Kountz; Kimberly E Girosky; Joseph A Krzycki; Donald J Ferguson
Journal:  Proc Natl Acad Sci U S A       Date:  2014-10-13       Impact factor: 11.205

7.  Inter-individual differences in response to dietary intervention: integrating omics platforms towards personalised dietary recommendations.

Authors:  Johanna W Lampe; Sandi L Navarro; Meredith A J Hullar; Ali Shojaie
Journal:  Proc Nutr Soc       Date:  2013-02-06       Impact factor: 6.297

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

Authors:  Joram M Posma; Isabel Garcia-Perez; Gary Frost; Ghadeer S Aljuraiban; Queenie Chan; Linda Van Horn; Martha Daviglus; Jeremiah Stamler; Elaine Holmes; Paul Elliott; Jeremy K Nicholson
Journal:  Nat Food       Date:  2020-06-22

9.  Relative validation of 24-h urinary hippuric acid excretion as a biomarker for dietary flavonoid intake from fruit and vegetables in healthy adolescents.

Authors:  Katharina J Penczynski; Danika Krupp; Anna Bring; Katja Bolzenius; Thomas Remer; Anette E Buyken
Journal:  Eur J Nutr       Date:  2015-12-10       Impact factor: 5.614

10.  Metabolomics and incident hypertension among blacks: the atherosclerosis risk in communities study.

Authors:  Yan Zheng; Bing Yu; Danny Alexander; Thomas H Mosley; Gerardo Heiss; Jennifer A Nettleton; Eric Boerwinkle
Journal:  Hypertension       Date:  2013-06-17       Impact factor: 10.190

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.