Evidence map›Paper›PMID 30146690›Full record

Observational studyDiabetes, obesity & metabolism2019

Changes in arginine are inversely associated with type 2 diabetes: A case-cohort study in the PREDIMED trial.

Edward Yu, Miguel Ruiz-Canela, Cristina Razquin, Marta Guasch-Ferré, Estefania Toledo, Dong D Wang, Christopher Papandreou, Courtney Dennis, Clary Clish, Liming Liang and 15 more

Open access · greenAbstract readObservational Study
In one paragraph

Observational study in Diabetes, obesity & metabolism, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 19% of its field
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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
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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

25 authors at 9 institutions in 2 countries.

Edward YuDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Miguel Ruiz-CanelaDepartment of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain.
Cristina RazquinDepartment of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain.
Marta Guasch-FerréDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.ORCID 0000-0001-8525-1404
Estefania ToledoDepartment of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain.
Dong D WangDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Christopher PapandreouHuman Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, Reus, Spain.ORCID 0000-0002-6803-507X
Courtney DennisBroad Institute of MIT and Harvard University, Cambridge, Massachusetts.
Clary ClishBroad Institute of MIT and Harvard University, Cambridge, Massachusetts.
Liming LiangDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Monica BulloHuman Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, Reus, Spain.
Dolores CorellaCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Montserrat FitóCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Mario Gutiérrez-BedmarDepartment of Preventive Medicine, University of Málaga, Málaga, Spain.
José LapetraCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Ramón EstruchCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Emilio RosCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Montserrat CofánCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Fernando ArósCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Dora RomagueraCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Lluis Serra-MajemCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Jose V SorlíCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Jordi Salas-SalvadóCIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Frank B HuDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Miguel A Martínez-GonzálezDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Instituto de Salud Carlos III · ESHarvard University · USUniversitat de València · ESBroad Institute · USInstitut de Recerca Biomèdica Catalunya Sud · ESBrigham and Women's Hospital · USUniversidad de Las Palmas de Gran Canaria · ESUniversidad de Málaga · ESUniversidad de Navarra · ES

Funding

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
NIDDK NIH HHS F31 DK114938NIDDK NIH HHS K99 DK119412NIDDK NIH HHS R01 DK102896
6 · The paper itself

Abstract

The associations between arginine-based metabolites and incident type 2 diabetes (T2D) are unknown. We employed a case-cohort design, nested within the PREDIMED trial, to examine six plasma metabolites (arginine, citrulline, ornithine, asymmetric dimethylarginine [ADMA], symmetric dimethylarginine [SDMA] and N-monomethyl-l-arginine [NMMA]) among 892 individuals (251 cases) for associations with incident T2D and insulin resistance. Weighted Cox models with robust variance were used. The 1-year changes in arginine (adjusted hazard ratio [HR] per SD 0.68, 95% confidence interval [CI] 0.49, 0.95; Q4 vs. Q1 0.46, 95% CI 0.21, 1.04; P trend = 0.02) and arginine/ADMA ratio (adjusted HR per SD 0.73, 95% CI 0.51, 1.04; Q4 vs. Q1 0.52, 95% CI 0.22, 1.25; P trend = 0.04) were associated with a lower risk of T2D. Positive changes of citrulline and ornithine, and negative changes in SDMA and arginine/(ornithine + citrulline) were associated with concurrent 1-year changes in homeostatic model assessment of insulin resistance. Individuals in the low-fat-diet group had a higher risk of T2D for 1-year changes in NMMA than individuals in Mediterranean-diet groups (P interaction = 0.02). We conclude that arginine bioavailability is important in T2D pathophysiology.

Indexed as

AgedAged, 80 and overArginineCase-Control StudiesCitrullineCohort StudiesDiabetes Mellitus, Type 2Diet, Fat-RestrictedDiet, MediterraneanFemaleHumansIncidenceInsulin ResistanceMaleMiddle Agedomega-N-MethylarginineArginineCitrullineN,N-dimethylarginineomega-N-MethylarginineOrnithinesymmetric dimethylargininecohort studydietary interventioninsulin resistanceobservational studypopulation study, type 2 diabetes

Identifiers

PMID30146690
PMCPMC6329637
OpenAlexW2889044189

What OpenQuestion holds

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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.