6533b7cefe1ef96bd1257af8

RESEARCH PRODUCT

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

Dong D. WangFernando ArósEdward YuMarta Guasch-ferréMarta Guasch-ferréMarta Guasch-ferréClary B. ClishMiquel FiolMontserrat FitóMònica BullóMònica BullóCristina RazquinCristina RazquinLiming LiangEmilio RosEmilio RosMiguel ÁNgel Martínez-gonzálezMiguel Ruiz-canelaMiguel Ruiz-canelaChristopher PapandreouChristopher PapandreouJordi Salas-salvadóJordi Salas-salvadóCourtney DennisAmy DeikFrank B. HuFrank B. HuPablo Hernández-alonsoPablo Hernández-alonsoDolores CorellaDolores CorellaLluis Serra-majemLluis Serra-majemRamon EstruchRamon EstruchEstefanía ToledoEstefanía Toledo

subject

Male0301 basic medicinePopulationWineBiologySensitivity and SpecificityArticleEating03 medical and health sciencesMetabolomicsLinear regressionHumansMetabolomicsFood scienceeducationAgedWineeducation.field_of_study030109 nutrition & dieteticsReceiver operating characteristicSmokingArea under the curveRegression analysisMiddle AgedPredimedDietBloodCross-Sectional Studies030104 developmental biologyArea Under CurveFemaleFood ScienceBiotechnology

description

SCOPE: The relationship between red wine (RW) consumption and metabolism is poorly understood. We 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: Cross-sectional analysis of 1,157 participants. Subjects were divided as non-RW consumers versus RW consumers (> 1 glass/day RW (100 mL/day)). Plasma metabolomics analysis was performed using LC-MS. Associations between 386 identified metabolites and RW consumption were assessed using elastic net regression analysis taking into consideration baseline significant covariates. Ten-cross-validation (CV) was performed and receiver operating characteristic curves were constructed in each of the validation datasets based on weighted models. A subset of 13 metabolites was consistently selected and discriminated RW consumers versus non-consumers. Based on the multi-metabolite model weighted with the regression coefficients of metabolites, the area under the curve was 0.83 (95% CI: 0.80–0.86). These metabolites mainly consisted of lipid species (e.g. triglycerides and phosphatidylcholines), some organic acids and alkaloids. CONCLUSIONS: A multi-metabolite model identified in a Mediterranean population appeared useful to discriminate between frequent RW consumers and non-consumers. Further studies are needed to assess the contribution of these metabolites in health and disease.

https://doi.org/10.1002/mnfr.201900140