Evidence map›Paper›PMID 31072000›Full record

ArticleNutrients2019

Plasma Metabolites Associated with Coffee Consumption: A Metabolomic Approach within the PREDIMED Study.

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

Abstract read
In one paragraph

Article in Nutrients, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Trial
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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.

Christopher PapandreouHuman Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201 Reus, Spain. papchris10@gmail.com.ORCID 0000-0002-6803-507X
Pablo Hernández-AlonsoHuman Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201 Reus, Spain. pablo1280@gmail.com.ORCID 0000-0002-9977-8976
Mònica BullóHuman Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201 Reus, Spain. monica.bullo@urv.cat.ORCID 0000-0002-0218-7046
Miguel Ruiz-CanelaCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain. mcanela@unav.es.ORCID 0000-0002-7684-2787
Edward YuDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. edy356@mail.harvard.edu.
Marta Guasch-FerréHuman Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201 Reus, Spain. mguasch@hsph.harvard.edu.ORCID 0000-0001-8525-1404
Estefanía ToledoCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain. etoledo@unav.es.ORCID 0000-0002-6263-4434
Courtney DennisBroad Institute of MIT and Harvard University, Cambridge, MA 02142, USA. cdennis@broadinstitute.org.
Amy DeikBroad Institute of MIT and Harvard University, Cambridge, MA 02142, USA. adeik@broadinstitute.org.ORCID 0000-0002-9687-0953
Clary ClishBroad Institute of MIT and Harvard University, Cambridge, MA 02142, USA. clary@broadinstitute.org.
Cristina RazquinCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain. crazquin@unav.es.
Dolores CorellaCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain. dolores.corella@uv.es.ORCID 0000-0002-2366-4104
Ramon EstruchCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain. RESTRUCH@clinic.ub.es.
Emilio RosCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain. eros@clinic.ub.es.ORCID 0000-0002-2573-1294
Montserrat FitóCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain. MFito@imim.es.
Fernando ArósCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain. lfaborau@gmail.com.ORCID 0000-0001-8337-7185
Miquel FiolCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain. miquelfiol@yahoo.es.
José LapetraCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain. jlapetra@ono.com.ORCID 0000-0002-3873-5737
Cristina RuanoCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain. cristina.ruano@ulpgc.es.
Liming LiangCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain. lliang@hsph.harvard.edu.ORCID 0000-0001-8261-3174
Miguel A Martínez-GonzálezCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain. mamartinez@unav.es.ORCID 0000-0002-3917-9808
Frank B HuDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. nhbfh@channing.harvard.edu.
Jordi Salas-SalvadóHuman Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201 Reus, Spain. jordi.salas@urv.cat.ORCID 0000-0003-2700-7459

Funding

ROLE OF DIETARY CONSTITUENTS ON GENE EXPRESSION IN INTESTINAL EPITHELIUMP30DK040561 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI CHRISTOPHER P DUGGAN · 1994 to 2026
$31.6M
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
NIDDK NIH HHS P30 DK040561NIDDK NIH HHS R01 DK102896NIH HHS R01DK102896
6 · The paper itself

Abstract

Few studies have examined the association of a wide range of metabolites with total and subtypes of coffee consumption. The aim of this study was to investigate associations of plasma metabolites with total, caffeinated, and decaffeinated coffee consumption. We also assessed the ability of metabolites to discriminate between coffee consumption categories. This is a cross-sectional analysis of 1664 participants from the PREDIMED study. Metabolites were semiquantitatively profiled using a multiplatform approach. Consumption of total coffee, caffeinated coffee and decaffeinated coffee was assessed by using a validated food frequency questionnaire. We assessed associations between 387 metabolite levels with total, caffeinated, or decaffeinated coffee consumption (≥50 mL coffee/day) using elastic net regression analysis. Ten-fold cross-validation analyses were used to estimate the discriminative accuracy of metabolites for total and subtypes of coffee. We identified different sets of metabolites associated with total coffee, caffeinated and decaffeinated coffee consumption. These metabolites consisted of lipid species (e.g., sphingomyelin, phosphatidylethanolamine, and phosphatidylcholine) or were derived from glycolysis (alpha-glycerophosphate) and polyphenol metabolism (hippurate). Other metabolites included caffeine, 5-acetylamino-6-amino-3-methyluracil, cotinine, kynurenic acid, glycocholate, lactate, and allantoin. The area under the curve (AUC) was 0.60 (95% CI 0.56-0.64), 0.78 (95% CI 0.75-0.81) and 0.52 (95% CI 0.49-0.55), in the multimetabolite model, for total, caffeinated, and decaffeinated coffee consumption, respectively. Our comprehensive metabolic analysis did not result in a new, reliable potential set of metabolites for coffee consumption.

Indexed as

CoffeeMetabolomicsAgedCaffeineCase-Control StudiesCohort StudiesCross-Sectional StudiesFemaleHumansMaleMiddle AgedCaffeineCoffeecaffeinecoffeemetabolomicsplasmaPREDIMED

Identifiers

PMID31072000
PMCPMC6566346

What OpenQuestion holds

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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.