Literature DB >> 24047691

Impact of geographical region on urinary metabolomic and plasma fatty acid profiles in subjects with the metabolic syndrome across Europe: the LIPGENE study.

Marianne C Walsh1, Gerard A McLoughlin1, Helen M Roche1, Jane F Ferguson2, Christian A Drevon3, Wim H M Saris4, Julie A Lovegrove5, Ulf Risérus6, José López-Miranda7, Catherine Defoort8, Beata Kieć-Wilk9, Lorraine Brennan1, Michael J Gibney1.   

Abstract

The application of metabolomics in multi-centre studies is increasing. The aim of the present study was to assess the effects of geographical location on the metabolic profiles of individuals with the metabolic syndrome. Blood and urine samples were collected from 219 adults from seven European centres participating in the LIPGENE project (Diet, genomics and the metabolic syndrome: an integrated nutrition, agro-food, social and economic analysis). Nutrient intakes, BMI, waist:hip ratio, blood pressure, and plasma glucose, insulin and blood lipid levels were assessed. Plasma fatty acid levels and urine were assessed using a metabolomic technique. The separation of three European geographical groups (NW, northwest; NE, northeast; SW, southwest) was identified using partial least-squares discriminant analysis models for urine (R² X: 0·33, Q²: 0·39) and plasma fatty acid (R² X: 0·32, Q²: 0·60) data. The NW group was characterised by higher levels of urinary hippurate and N-methylnicotinate. The NE group was characterised by higher levels of urinary creatine and citrate and plasma EPA (20 : 5 n-3). The SW group was characterised by higher levels of urinary trimethylamine oxide and lower levels of plasma EPA. The indicators of metabolic health appeared to be consistent across the groups. The SW group had higher intakes of total fat and MUFA compared with both the NW and NE groups (P≤ 0·001). The NE group had higher intakes of fibre and n-3 and n-6 fatty acids compared with both the NW and SW groups (all P< 0·001). It is likely that differences in dietary intakes contributed to the separation of the three groups. Evaluation of geographical factors including diet should be considered in the interpretation of metabolomic data from multi-centre studies.

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Year:  2013        PMID: 24047691     DOI: 10.1017/S0007114513002602

Source DB:  PubMed          Journal:  Br J Nutr        ISSN: 0007-1145            Impact factor:   3.718


  6 in total

1.  Identifying biomarkers of dietary patterns by using metabolomics.

Authors:  Mary C Playdon; Steven C Moore; Andriy Derkach; Jill Reedy; Amy F Subar; Joshua N Sampson; Demetrius Albanes; Fangyi Gu; Jukka Kontto; Camille Lassale; Linda M Liao; Satu Männistö; Alison M Mondul; Stephanie J Weinstein; Melinda L Irwin; Susan T Mayne; Rachael Stolzenberg-Solomon
Journal:  Am J Clin Nutr       Date:  2016-12-28       Impact factor: 7.045

2.  Genomic and Metabolomic Profile Associated to Clustering of Cardio-Metabolic Risk Factors.

Authors:  Vannina G Marrachelli; Pilar Rentero; María L Mansego; Jose Manuel Morales; Inma Galan; Mercedes Pardo-Tendero; Fernando Martinez; Juan Carlos Martin-Escudero; Laisa Briongos; Felipe Javier Chaves; Josep Redon; Daniel Monleon
Journal:  PLoS One       Date:  2016-09-02       Impact factor: 3.240

3.  Phenotype-driven identification of modules in a hierarchical map of multifluid metabolic correlations.

Authors:  Kieu Trinh Do; Maik Pietzner; David Jnp Rasp; Nele Friedrich; Matthias Nauck; Thomas Kocher; Karsten Suhre; Dennis O Mook-Kanamori; Gabi Kastenmüller; Jan Krumsiek
Journal:  NPJ Syst Biol Appl       Date:  2017-09-21

4.  Dietary patterns in internal migrants in a continental country: A population-based study.

Authors:  Antonio Augusto Ferreira Carioca; Bartira Gorgulho; Juliana Araujo Teixeira; Regina Mara Fisberg; Dirce Maria Marchioni
Journal:  PLoS One       Date:  2017-10-16       Impact factor: 3.240

Review 5.  A Scoping Review of the Application of Metabolomics in Nutrition Research: The Literature Survey 2000-2019.

Authors:  Eriko Shibutami; Toru Takebayashi
Journal:  Nutrients       Date:  2021-10-24       Impact factor: 5.717

6.  Targeted Metabolomics for Plasma Amino Acids and Carnitines in Patients with Metabolic Syndrome Using HPLC-MS/MS.

Authors:  Li-Li Gong; Song Yang; Wen Zhang; Fei-Fei Han; Ling-Ling Xuan; Ya-Li Lv; He Liu; Li-Hong Liu
Journal:  Dis Markers       Date:  2020-07-17       Impact factor: 3.434

  6 in total

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