High plasma glutamate and low glutamine-to-glutamate ratio are associated with type 2 diabetes: Case-cohort study within the PREDIMED trial.


Journal

Nutrition, metabolism, and cardiovascular diseases : NMCD
ISSN: 1590-3729
Titre abrégé: Nutr Metab Cardiovasc Dis
Pays: Netherlands
ID NLM: 9111474

Informations de publication

Date de publication:
10 2019
Historique:
received: 04 01 2019
revised: 24 05 2019
accepted: 06 06 2019
pubmed: 5 8 2019
medline: 20 2 2020
entrez: 5 8 2019
Statut: ppublish

Résumé

Glutamate, glutamine are involved in energy metabolism, and have been related to cardiometabolic disorders. However, their roles in the development of type-2 diabetes (T2D) remain unclear. The aim of this study was to examine the effects of Mediterranean diet on associations between glutamine, glutamate, glutamine-to-glutamate ratio, and risk of new-onset T2D in a Spanish population at high risk for cardiovascular disease (CVD). The present study was built within the PREDIMED trial using a case-cohort design including 892 participants with 251 incident T2D cases and 641 non-cases. Participants (mean age 66.3 years; female 62.8%) were non diabetic and at high risk for CVD at baseline. Plasma levels of glutamine and glutamate were measured at baseline and after 1-year of intervention. Higher glutamate levels at baseline were associated with increased risk of T2D with a hazard ratio (HR) of 2.78 (95% CI, 1.43-5.41, P for trend = 0.0002). In contrast, baseline levels of glutamine (HR: 0.64, 95% CI, 0.36-1.12; P for trend = 0.04) and glutamine-to-glutamate ratio (HR: 0.31, 95% CI, 0.16-0.57; P for trend = 0.0001) were inversely associated with T2D risk when comparing extreme quartiles. The two Mediterranean diets (MedDiet + EVOO and MedDiet + mixed nuts) did not alter levels of glutamine and glutamate after intervention for 1 year. However, MedDiet mitigated the positive association between higher baseline plasma glutamate and T2D risk (P for interaction = 0.01). Higher levels of glutamate and lower levels of glutamine were associated with increased risk of T2D in a Spanish population at high risk for CVD. Mediterranean diet might mitigate the association between the imbalance of glutamine and glutamate and T2D risk. This trial is registered at http://www.controlled-trials.com, ISRCTN35739639.

Sections du résumé

BACKGROUND AND AIMS
Glutamate, glutamine are involved in energy metabolism, and have been related to cardiometabolic disorders. However, their roles in the development of type-2 diabetes (T2D) remain unclear. The aim of this study was to examine the effects of Mediterranean diet on associations between glutamine, glutamate, glutamine-to-glutamate ratio, and risk of new-onset T2D in a Spanish population at high risk for cardiovascular disease (CVD).
METHODS AND RESULTS
The present study was built within the PREDIMED trial using a case-cohort design including 892 participants with 251 incident T2D cases and 641 non-cases. Participants (mean age 66.3 years; female 62.8%) were non diabetic and at high risk for CVD at baseline. Plasma levels of glutamine and glutamate were measured at baseline and after 1-year of intervention. Higher glutamate levels at baseline were associated with increased risk of T2D with a hazard ratio (HR) of 2.78 (95% CI, 1.43-5.41, P for trend = 0.0002). In contrast, baseline levels of glutamine (HR: 0.64, 95% CI, 0.36-1.12; P for trend = 0.04) and glutamine-to-glutamate ratio (HR: 0.31, 95% CI, 0.16-0.57; P for trend = 0.0001) were inversely associated with T2D risk when comparing extreme quartiles. The two Mediterranean diets (MedDiet + EVOO and MedDiet + mixed nuts) did not alter levels of glutamine and glutamate after intervention for 1 year. However, MedDiet mitigated the positive association between higher baseline plasma glutamate and T2D risk (P for interaction = 0.01).
CONCLUSION
Higher levels of glutamate and lower levels of glutamine were associated with increased risk of T2D in a Spanish population at high risk for CVD. Mediterranean diet might mitigate the association between the imbalance of glutamine and glutamate and T2D risk. This trial is registered at http://www.controlled-trials.com, ISRCTN35739639.

Identifiants

pubmed: 31377179
pii: S0939-4753(19)30233-9
doi: 10.1016/j.numecd.2019.06.005
pmc: PMC9257877
mid: NIHMS1816039
pii:
doi:

Substances chimiques

Biomarkers 0
Glutamine 0RH81L854J
Glutamic Acid 3KX376GY7L

Types de publication

Journal Article Multicenter Study Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

1040-1049

Subventions

Organisme : NIDDK NIH HHS
ID : R01 DK102896
Pays : United States

Informations de copyright

Copyright © 2019 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

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Auteurs

Xiaoran Liu (X)

Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Yan Zheng (Y)

Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; State Key Laboratory of Genetic Engineering, Human Phenome Institute and School of Life Sciences, Fudan University, Shanghai, China.

Marta Guasch-Ferré (M)

Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Miguel Ruiz-Canela (M)

University of Navarra, Department of Preventive Medicine and Public Health, IDISNA (Instituto de Investigación Sanitaria de Navarra), Pamplona, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain.

Estefanía Toledo (E)

University of Navarra, Department of Preventive Medicine and Public Health, IDISNA (Instituto de Investigación Sanitaria de Navarra), Pamplona, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain.

Clary Clish (C)

Broad Institute of MIT and Harvard University, Cambridge, MA, USA.

Liming Liang (L)

Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Cristina Razquin (C)

University of Navarra, Department of Preventive Medicine and Public Health, IDISNA (Instituto de Investigación Sanitaria de Navarra), Pamplona, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain.

Dolores Corella (D)

CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine, University of Valencia, Valencia, Spain.

Ramón Estruch (R)

CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Department of Internal Medicine, Department of Endocrinology and Nutrition Institut d'Investigacions Biomediques August Pi Sunyer (IDI- BAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain.

Montserrat Fito (M)

CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Cardiovascular and Nutrition Research Group (Regicor Study Group), Institut de Recerca-Hospital del Mar (IMIM), Barcelona, Spain.

Enrique Gómez-Gracia (E)

CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine, University of Málaga, Málaga, Spain.

Fernando Arós (F)

CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Department of Cardiology, University Hospital of Alava, Vitoria, Spain.

Emilio Ros (E)

CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Lipid Clinic, Endocrinology and Nutrition Service, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain.

José Lapetra (J)

CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Department of Family Medicine, Research Unit, Primary Care Division of Sevilla, Sevilla, Spain.

Miquel Fiol (M)

CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Institute of Health Sciences IUNICS, University of Balearic Islands and Hospital Son Espases, Palma de Mallorca, Spain.

Lluis Serra-Majem (L)

CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Research Institute of Biomedical and Health Sciences, University of Las Palmas de Gran Canaria, Las Palmas, Spain.

Christopher Papandreou (C)

CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Human Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, Reus, Spain.

Miguel A Martínez-González (MA)

Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; University of Navarra, Department of Preventive Medicine and Public Health, IDISNA (Instituto de Investigación Sanitaria de Navarra), Pamplona, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain.

Frank B Hu (FB)

Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Jordi Salas-Salvadó (J)

CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Human Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, Reus, Spain. Electronic address: jordi.salas@urv.cat.

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Classifications MeSH