Walnut Consumption, Plasma Metabolomics, and Risk of Type 2 Diabetes and Cardiovascular Disease.


Journal

The Journal of nutrition
ISSN: 1541-6100
Titre abrégé: J Nutr
Pays: United States
ID NLM: 0404243

Informations de publication

Date de publication:
01 02 2021
Historique:
received: 10 07 2020
revised: 07 10 2020
accepted: 29 10 2020
pubmed: 1 1 2021
medline: 11 5 2021
entrez: 31 12 2020
Statut: ppublish

Résumé

Walnut consumption is associated with lower risk of type 2 diabetes (T2D) and cardiovascular disease (CVD). However, it is unknown whether plasma metabolites related to walnut consumption are also associated with lower risk of cardiometabolic diseases. The study aimed to identify plasma metabolites associated with walnut consumption and evaluate the prospective associations between the identified profile and risk of T2D and CVD. The discovery population included 1833 participants at high cardiovascular risk from the PREvención con DIeta MEDiterránea (PREDIMED) study with available metabolomics data at baseline. The study population included 57% women (baseline mean BMI (in kg/m2): 29.9; mean age: 67 y). A total of 1522 participants also had available metabolomics data at year 1 and were used as the internal validation population. Plasma metabolomics analyses were performed using LC-MS. Cross-sectional associations between 385 known metabolites and walnut consumption were assessed using elastic net continuous regression analysis. A 10-cross-validation (CV) procedure was used, and Pearson correlation coefficients were assessed between metabolite weighted models and self-reported walnut consumption in each pair of training-validation data sets within the discovery population. We further estimated the prospective associations between the identified metabolite profile and incident T2D and CVD using multivariable Cox regression models. A total of 19 metabolites were significantly associated with walnut consumption, including lipids, purines, acylcarnitines, and amino acids. Ten-CV Pearson correlation coefficients between self-reported walnut consumption and the plasma metabolite profile were 0.16 (95% CI: 0.11, 0.20) in the discovery population and 0.15 (95% CI: 0.10, 0.20) in the validation population. The metabolite profile was inversely associated with T2D incidence (HR per 1 SD: 0.83; 95% CI: 0.71, 0.97; P = 0.02). For CVD incidence, the HR per 1-SD was 0.71 (95% CI: 0.60, 0.85; P < 0.001). A metabolite profile including 19 metabolites was associated with walnut consumption and with a lower risk of incident T2D and CVD in a Mediterranean population at high cardiovascular risk.

Sections du résumé

BACKGROUND
Walnut consumption is associated with lower risk of type 2 diabetes (T2D) and cardiovascular disease (CVD). However, it is unknown whether plasma metabolites related to walnut consumption are also associated with lower risk of cardiometabolic diseases.
OBJECTIVES
The study aimed to identify plasma metabolites associated with walnut consumption and evaluate the prospective associations between the identified profile and risk of T2D and CVD.
METHODS
The discovery population included 1833 participants at high cardiovascular risk from the PREvención con DIeta MEDiterránea (PREDIMED) study with available metabolomics data at baseline. The study population included 57% women (baseline mean BMI (in kg/m2): 29.9; mean age: 67 y). A total of 1522 participants also had available metabolomics data at year 1 and were used as the internal validation population. Plasma metabolomics analyses were performed using LC-MS. Cross-sectional associations between 385 known metabolites and walnut consumption were assessed using elastic net continuous regression analysis. A 10-cross-validation (CV) procedure was used, and Pearson correlation coefficients were assessed between metabolite weighted models and self-reported walnut consumption in each pair of training-validation data sets within the discovery population. We further estimated the prospective associations between the identified metabolite profile and incident T2D and CVD using multivariable Cox regression models.
RESULTS
A total of 19 metabolites were significantly associated with walnut consumption, including lipids, purines, acylcarnitines, and amino acids. Ten-CV Pearson correlation coefficients between self-reported walnut consumption and the plasma metabolite profile were 0.16 (95% CI: 0.11, 0.20) in the discovery population and 0.15 (95% CI: 0.10, 0.20) in the validation population. The metabolite profile was inversely associated with T2D incidence (HR per 1 SD: 0.83; 95% CI: 0.71, 0.97; P = 0.02). For CVD incidence, the HR per 1-SD was 0.71 (95% CI: 0.60, 0.85; P < 0.001).
CONCLUSIONS
A metabolite profile including 19 metabolites was associated with walnut consumption and with a lower risk of incident T2D and CVD in a Mediterranean population at high cardiovascular risk.

Identifiants

pubmed: 33382410
pii: S0022-3166(22)00054-2
doi: 10.1093/jn/nxaa374
pmc: PMC7850062
doi:

Substances chimiques

Amino Acids 0
Biomarkers 0
Lipids 0
Purines 0
acylcarnitine 0
Carnitine S7UI8SM58A

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

303-311

Subventions

Organisme : NIDDK NIH HHS
ID : P30 DK040561
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK102896
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL118264
Pays : United States

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press on behalf of the American Society for Nutrition.

Auteurs

Marta Guasch-Ferré (M)

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

Pablo Hernández-Alonso (P)

Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Hospital Universitari San Joan de Reus, Reus, Spain.
Institut d'Investigació Pere Virgili, Reus, Spain.
Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.

Jean-Philippe Drouin-Chartier (JP)

Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Centre Nutrition, Santé et Société, Institut sur la Nutrition et les Aliments Fonctionnels, Faculté de Pharmacie, Université Laval, Québec, Canada.

Miguel Ruiz-Canela (M)

Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
Department of Preventive Medicine and Public Health, Navarra Health Research Institute (IDISNA), University of Navarra, Pamplona, Spain.

Cristina Razquin (C)

Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
Department of Preventive Medicine and Public Health, Navarra Health Research Institute (IDISNA), University of Navarra, Pamplona, Spain.

Estefanía Toledo (E)

Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
Department of Preventive Medicine and Public Health, Navarra Health Research Institute (IDISNA), University of Navarra, Pamplona, Spain.

Jun Li (J)

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

Courtney Dennis (C)

The Broad Institute of Harvard and MIT, Boston, MA, USA.

Clemens Wittenbecher (C)

Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany.
German Center for Diabetes Research, Neuherberg, Germany.

Dolores Corella (D)

Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
Department of Preventive Medicine, University of Valencia, Valencia, Spain.

Ramon Estruch (R)

Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer, Hospital Clinic, University of Barcelona, Barcelona, Spain.

Montserrat Fitó (M)

Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
Cardiovascular and Nutrition Research Group, Institut de Recerca Hospital del Mar, Barcelona, Spain.

Emilio Ros (E)

Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
Lipid Clinic, Department of Endocrinology and Nutrition, Agust Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain.

Nancy Babio (N)

Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Hospital Universitari San Joan de Reus, Reus, Spain.
Institut d'Investigació Pere Virgili, Reus, Spain.
Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.

Shilpa N Bhupathiraju (SN)

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

Clary B Clish (CB)

The Broad Institute of Harvard and MIT, Boston, 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.

Miguel A Martínez-González (MA)

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

Frank B Hu (FB)

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

Jordi Salas-Salvadó (J)

Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Hospital Universitari San Joan de Reus, Reus, Spain.
Institut d'Investigació Pere Virgili, Reus, Spain.
Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH