4.7 Article

Plasma Metabolites Associated with Frequent Red Wine Consumption: A Metabolomics Approach within the PREDIMED Study

Journal

MOLECULAR NUTRITION & FOOD RESEARCH
Volume 63, Issue 17, Pages -

Publisher

WILEY
DOI: 10.1002/mnfr.201900140

Keywords

LC-MS; lipidomics; metabolites; metabolomics; red wine

Funding

  1. National Institutes of Health [R01DK102896, F31DK114938]
  2. Spanish Ministry of Health (Instituto de Salud Carlos III)
  3. Ministerio de Economia y Competitividad-Fondo Europeo de Desarrollo Regional [CNIC-06/2007, RTIC G03/140, CIBER 06/03, PI06-1326, PI07-0954, PI11/02505, SAF2009-12304, AGL2010-22319-C03-03]
  4. Generalitat Valenciana [ACOMP2010-181, AP111/10, AP-042/11, ACOM2011/145, ACOMP/2012/190, ACOMP/2013/159, ACOMP/213/165]
  5. Autonomous Government of Catalonia (PERIS 2016-2020 Incorporacio de Cientifics I Tecnlegs) [SLT002/0016/00428]
  6. EFSD (European Foundation for the Study of Diabetes)/Lilly through the Institut d'Investigacions Sanitaries Pere I Virgili (IISPV)

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Scope The relationship between red wine (RW) consumption and metabolism is poorly understood. It is aimed to assess the systemic metabolomic profiles in relation to frequent RW consumption as well as the ability of a set of metabolites to discriminate RW consumers. Methods and results A cross-sectional analysis of 1157 participants is carried out. Subjects are divided as non-RW consumers versus RW consumers (>1 glass per day RW [100 mL per day]). Plasma metabolomics analysis is performed using LC-MS. Associations between 386 identified metabolites and RW consumption are assessed using elastic net regression analysis taking into consideration baseline significant covariates. Ten-cross-validation (CV) is performed and receiver operating characteristic curves are constructed in each of the validation datasets based on weighted models. A subset of 13 metabolites is consistently selected and RW consumers versus nonconsumers are discriminated. Based on the multi-metabolite model weighted with the regression coefficients of metabolites, the area under the curve is 0.83 (95% CI: 0.80-0.86). These metabolites mainly consisted of lipid species, some organic acids, and alkaloids. Conclusions A multi-metabolite model identified in a Mediterranean population appears useful to discriminate between frequent RW consumers and nonconsumers. Further studies are needed to assess the contribution of these metabolites in health and disease.

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