Xiaoran Liu1, Yan Zheng2, Marta Guasch-Ferré1, Miguel Ruiz-Canela3, Estefanía Toledo3, Clary Clish4, Liming Liang5, Cristina Razquin3, Dolores Corella6, Ramón Estruch7, Montserrat Fito8, Enrique Gómez-Gracia9, Fernando Arós10, Emilio Ros11, José Lapetra12, Miquel Fiol13, Lluis Serra-Majem14, Christopher Papandreou15, Miguel A Martínez-González16, Frank B Hu17, Jordi Salas-Salvadó18. 1. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 2. 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. 3. 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. 4. Broad Institute of MIT and Harvard University, Cambridge, MA, USA. 5. 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. 6. CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine, University of Valencia, Valencia, Spain. 7. 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. 8. 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. 9. CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine, University of Málaga, Málaga, Spain. 10. CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain; Department of Cardiology, University Hospital of Alava, Vitoria, Spain. 11. 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. 12. 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. 13. 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. 14. 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. 15. 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. 16. 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. 17. 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. 18. 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.
Abstract
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.
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.
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