TY - JOUR

T1 - Plasma metabolite profiles associated with the World Cancer Research Fund/American Institute for Cancer Research lifestyle score and future risk of cardiovascular disease and type 2 diabetes

AU - Rios, Santiago

AU - García-Gavilán, Jesús F.

AU - Babio, Nancy

AU - Paz-Graniel, Indira

AU - Ruiz-Canela, Miguel

AU - Liang, Liming

AU - Clish, Clary B.

AU - Toledo, Estefania

AU - Corella, Dolores

AU - Estruch, Ramón

AU - Ros, Emilio

AU - Fitó, Montserrat

AU - Arós, Fernando

AU - Fiol, Miquel

AU - Guasch-Ferré, Marta

AU - Santos-Lozano, José M.

AU - Li, Jun

AU - Razquin, Cristina

AU - Martínez-González, Miguel Ángel

AU - Hu, Frank B.

AU - Salas-Salvadó, Jordi

N1 - Publisher Copyright: © 2023, BioMed Central Ltd., part of Springer Nature.

PY - 2023

Y1 - 2023

N2 - Background: A healthy lifestyle (HL) has been inversely related to type 2 diabetes (T2D) and cardiovascular disease (CVD). However, few studies have identified a metabolite profile associated with HL. The present study aims to identify a metabolite profile of a HL score and assess its association with the incidence of T2D and CVD in individuals at high cardiovascular risk. Methods: In a subset of 1833 participants (age 55-80y) of the PREDIMED study, we estimated adherence to a HL using a composite score based on the 2018 Word Cancer Research Fund/American Institute for Cancer Research recommendations. Plasma metabolites were analyzed using LC-MS/MS methods at baseline (discovery sample) and 1-year of follow-up (validation sample). Cross-sectional associations between 385 known metabolites and the HL score were assessed using elastic net regression. A 10-cross-validation procedure was used, and correlation coefficients or AUC were assessed between the identified metabolite profiles and the self-reported HL score. We estimated the associations between the identified metabolite profiles and T2D and CVD using multivariable Cox regression models. Results: The metabolite profiles that identified HL as a dichotomous or continuous variable included 24 and 58 metabolites, respectively. These are amino acids or derivatives, lipids, and energy intermediates or xenobiotic compounds. After adjustment for potential confounders, baseline metabolite profiles were associated with a lower risk of T2D (hazard ratio [HR] and 95% confidence interval (CI): 0.54, 0.38–0.77 for dichotomous HL, and 0.22, 0.11–0.43 for continuous HL). Similar results were observed with CVD (HR, 95% CI: 0.59, 0.42–0.83 for dichotomous HF and HR, 95%CI: 0.58, 0.31–1.07 for continuous HL). The reduction in the risk of T2D and CVD was maintained or attenuated, respectively, for the 1-year metabolomic profile. Conclusions: In an elderly population at high risk of CVD, a set of metabolites was selected as potential metabolites associated with the HL pattern predicting the risk of T2D and, to a lesser extent, CVD. These results support previous findings that some of these metabolites are inversely associated with the risk of T2D and CVD. Trial registration: The PREDIMED trial was registered at ISRCTN (http://www.isrctn.com/ , ISRCTN35739639).

AB - Background: A healthy lifestyle (HL) has been inversely related to type 2 diabetes (T2D) and cardiovascular disease (CVD). However, few studies have identified a metabolite profile associated with HL. The present study aims to identify a metabolite profile of a HL score and assess its association with the incidence of T2D and CVD in individuals at high cardiovascular risk. Methods: In a subset of 1833 participants (age 55-80y) of the PREDIMED study, we estimated adherence to a HL using a composite score based on the 2018 Word Cancer Research Fund/American Institute for Cancer Research recommendations. Plasma metabolites were analyzed using LC-MS/MS methods at baseline (discovery sample) and 1-year of follow-up (validation sample). Cross-sectional associations between 385 known metabolites and the HL score were assessed using elastic net regression. A 10-cross-validation procedure was used, and correlation coefficients or AUC were assessed between the identified metabolite profiles and the self-reported HL score. We estimated the associations between the identified metabolite profiles and T2D and CVD using multivariable Cox regression models. Results: The metabolite profiles that identified HL as a dichotomous or continuous variable included 24 and 58 metabolites, respectively. These are amino acids or derivatives, lipids, and energy intermediates or xenobiotic compounds. After adjustment for potential confounders, baseline metabolite profiles were associated with a lower risk of T2D (hazard ratio [HR] and 95% confidence interval (CI): 0.54, 0.38–0.77 for dichotomous HL, and 0.22, 0.11–0.43 for continuous HL). Similar results were observed with CVD (HR, 95% CI: 0.59, 0.42–0.83 for dichotomous HF and HR, 95%CI: 0.58, 0.31–1.07 for continuous HL). The reduction in the risk of T2D and CVD was maintained or attenuated, respectively, for the 1-year metabolomic profile. Conclusions: In an elderly population at high risk of CVD, a set of metabolites was selected as potential metabolites associated with the HL pattern predicting the risk of T2D and, to a lesser extent, CVD. These results support previous findings that some of these metabolites are inversely associated with the risk of T2D and CVD. Trial registration: The PREDIMED trial was registered at ISRCTN (http://www.isrctn.com/ , ISRCTN35739639).

KW - Healthy lifestyle

KW - Metabolite profile

KW - Metabolomics

KW - PREDIMED trial

U2 - 10.1186/s12933-023-01912-6

DO - 10.1186/s12933-023-01912-6

M3 - Journal article

C2 - 37716984

AN - SCOPUS:85171396803

VL - 22

JO - Cardiovascular Diabetology

JF - Cardiovascular Diabetology

SN - 1475-2840

M1 - 252

ER -