Evidence map›Paper›PMID 31291050›Full record

ArticleMolecular nutrition & food research2019

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

Pablo Hernández-Alonso, Christopher Papandreou, Mònica Bulló, Miguel Ruiz-Canela, Courtney Dennis, Amy Deik, Dong D Wang, Marta Guasch-Ferré, Edward Yu, Estefanía Toledo and 13 more

Abstract read
In one paragraph

Article in Molecular nutrition & food research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. Exploring Human Metabolome after Wine Intake-A Review.Molecules (Basel, Switzerland) · 2023
    Review
  7. Article
  8. Article
  9. Dairy consumption, plasma metabolites, and risk of type 2 diabetes.The American journal of clinical nutrition · 2021
    Article
  10. Article
  11. Article
  12. Review
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

23 authors.

Pablo Hernández-AlonsoHuman Nutrition Unit, Faculty of Medicine and Health Sciences, Sant Joan Hospital, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201, Reus, Spain.
Christopher PapandreouHuman Nutrition Unit, Faculty of Medicine and Health Sciences, Sant Joan Hospital, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201, Reus, Spain.
Mònica BullóHuman Nutrition Unit, Faculty of Medicine and Health Sciences, Sant Joan Hospital, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201, Reus, Spain.ORCID 0000-0002-0218-7046
Miguel Ruiz-CanelaCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Courtney DennisBroad Institute of MIT and Harvard University, 02142, Cambridge, MA, USA.
Amy DeikBroad Institute of MIT and Harvard University, 02142, Cambridge, MA, USA.
Dong D WangDepartment of Nutrition, Harvard T.H. Chan School of Public Health, 02115, Boston, MA, USA.
Marta Guasch-FerréHuman Nutrition Unit, Faculty of Medicine and Health Sciences, Sant Joan Hospital, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201, Reus, Spain.
Edward YuDepartment of Nutrition, Harvard T.H. Chan School of Public Health, 02115, Boston, MA, USA.
Estefanía ToledoCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Cristina RazquinCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Dolores CorellaCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Ramon EstruchCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Emilio RosCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Montserrat FitóCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Fernando ArósCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Miquel FiolCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Lluís Serra-MajemCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Liming LiangDepartments of Epidemiology and Statistics, Harvard T.H. Chan School of Public Health, 02115, Boston, MA, USA.
Clary B ClishBroad Institute of MIT and Harvard University, 02142, Cambridge, MA, USA.
Miguel A Martínez-GonzálezCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Frank B HuBroad Institute of MIT and Harvard University, 02142, Cambridge, MA, USA.
Jordi Salas-SalvadóHuman Nutrition Unit, Faculty of Medicine and Health Sciences, Sant Joan Hospital, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201, Reus, Spain.

Funding

ROLE OF DIETARY CONSTITUENTS ON GENE EXPRESSION IN INTESTINAL EPITHELIUMP30DK040561 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI MARTIN TORRIANI · 1994 to 2026
$31.6M
Mediterranean diet, Metabolites, and Cardiovascular DiseaseR01HL118264 · NHLBI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI HU, FRANK B, LAMUELA-RAVENTÓS, ROSA · 2013 to 2025
$6.8M
Dietary Interventions, Metabolites, and Risk of Type 2 DiabetesR01DK102896 · NIDDK · HARVARD SCHOOL OF PUBLIC HEALTH · PI HU, FRANK B, MARTINEZ GONZALEZ, MIGUEL A. · 2014 to 2017
$1.9M
Mediterranean Diet, Polyphenol-Rich Foods, Gut Microbiota and Type 2 DiabetesK99DK119412 · NIDDK · HARVARD SCHOOL OF PUBLIC HEALTH · PI WANG, DONG · 2018 to 2019
$181k
Dietary Interventions, Metabolites, and Type 2 DiabetesF31DK114938 · NIDDK · HARVARD SCHOOL OF PUBLIC HEALTH · PI YU, EDWARD · 2017 to 2017
$29k
NHLBI NIH HHS R01 HL118264NIDDK NIH HHS F31 DK114938NIDDK NIH HHS K99 DK119412NIDDK NIH HHS P30 DK040561NIDDK NIH HHS R01 DK102896
6 · The paper itself

Abstract

scopeThe 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

resultsA 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.

conclusionsA 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.

Indexed as

WineAgedArea Under CurveBloodCross-Sectional StudiesDietEatingFemaleHumansMaleMetabolomicsMiddle AgedSensitivity and SpecificitySmokingLC-MSlipidomicsmetabolitesmetabolomicsred wine

Identifiers

PMID31291050
PMCPMC6771435

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.