Literature DB >> 18847517

Session 2: Personalised nutrition. Metabolomic applications in nutritional research.

Lorraine Brennan1.   

Abstract

Metabolomics aims to profile all small molecules that are present in biological samples such as biofluids, tissue extracts and culture media. Combining the data obtained with multivariate data analysis tools allows the exploration of changes induced by a biological treatment or changes resulting from phenotype. Recently, there has been a large increase in interest in using metabolomics in nutritional research and because of the intimate relationship between nutrients and metabolism there exists great potential for the use of metabolomics within nutritional research. However, for metabolomics to reach its full potential within this field it is also important to be realistic about the challenges that are faced. Examples of such challenges include the necessity to have a clear understanding of the causes of variation in human metabolomic profiles, the effects of the gut microflora on the metabolomic profile and the interaction of the gut microflora with the host's metabolism. A further challenge that is particularly relevant for human nutritional research is the difficulty associated with biological interpretation of the data. Notwithstanding these and other challenges, several examples of successful applications to nutritional research exist. The link between the human metabolic phenotype, as characterised by metabolomic profiles, and dietary preferences proposes the potential role of metabolomics in personalised nutrition.

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Year:  2008        PMID: 18847517     DOI: 10.1017/S0029665108008719

Source DB:  PubMed          Journal:  Proc Nutr Soc        ISSN: 0029-6651            Impact factor:   6.297


  8 in total

1.  Metabolomic profiling of urine: response to a randomised, controlled feeding study of select fruits and vegetables, and application to an observational study.

Authors:  Damon H May; Sandi L Navarro; Ingo Ruczinski; Jason Hogan; Yuko Ogata; Yvonne Schwarz; Lisa Levy; Ted Holzman; Martin W McIntosh; Johanna W Lampe
Journal:  Br J Nutr       Date:  2013-05-09       Impact factor: 3.718

2.  Targeted metabolomics profiles are strongly correlated with nutritional patterns in women.

Authors:  Cristina Menni; Guangju Zhai; Alexander Macgregor; Cornelia Prehn; Werner Römisch-Margl; Karsten Suhre; Jerzy Adamski; Aedin Cassidy; Thomas Illig; Tim D Spector; Ana M Valdes
Journal:  Metabolomics       Date:  2012-10-06       Impact factor: 4.290

Review 3.  Dietary biomarkers: advances, limitations and future directions.

Authors:  Valisa E Hedrick; Andrea M Dietrich; Paul A Estabrooks; Jyoti Savla; Elena Serrano; Brenda M Davy
Journal:  Nutr J       Date:  2012-12-14       Impact factor: 3.271

4.  Probabilistic principal component analysis for metabolomic data.

Authors:  Gift Nyamundanda; Lorraine Brennan; Isobel Claire Gormley
Journal:  BMC Bioinformatics       Date:  2010-11-23       Impact factor: 3.169

5.  Postprandial differences in the plasma metabolome of healthy Finnish subjects after intake of a sourdough fermented endosperm rye bread versus white wheat bread.

Authors:  Isabel Bondia-Pons; Emilia Nordlund; Ismo Mattila; Kati Katina; Anna-Marja Aura; Marjukka Kolehmainen; Matej Orešič; Hannu Mykkänen; Kaisa Poutanen
Journal:  Nutr J       Date:  2011-10-19       Impact factor: 3.271

6.  Plasma N-acetylputrescine, cadaverine and 1,3-diaminopropane: potential biomarkers of lung cancer used to evaluate the efficacy of anticancer drugs.

Authors:  Ran Liu; Pei Li; Cathy Wenchuan Bi; Ran Ma; Yidi Yin; Kaishun Bi; Qing Li
Journal:  Oncotarget       Date:  2017-07-17

7.  Modifying effect of metabotype on diet-diabetes associations.

Authors:  Anna Riedl; Nina Wawro; Christian Gieger; Christa Meisinger; Annette Peters; Wolfgang Rathmann; Wolfgang Koenig; Konstantin Strauch; Anne S Quante; Barbara Thorand; Cornelia Huth; Hannelore Daniel; Hans Hauner; Jakob Linseisen
Journal:  Eur J Nutr       Date:  2019-05-14       Impact factor: 5.614

8.  A lipidomic analysis approach to evaluate the response to cholesterol-lowering food intake.

Authors:  Ewa Szymańska; Ferdinand A van Dorsten; Jorne Troost; Iryna Paliukhovich; Ewoud J J van Velzen; Margriet M W B Hendriks; Elke A Trautwein; John P M van Duynhoven; Rob J Vreeken; Age K Smilde
Journal:  Metabolomics       Date:  2011-12-07       Impact factor: 4.290

  8 in total

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