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Plasma Metabolomic Profiles of Glycemic Index, Glycemic Load, and Carbohydrate Quality Index in the PREDIMED Study.
Bulló, Mònica; Papandreou, Christopher; Ruiz-Canela, Miguel; Guasch-Ferré, Marta; Li, Jun; Hernández-Alonso, Pablo; Toledo, Estefania; Liang, Liming; Razquin, Cristina; Corella, Dolores; Estruch, Ramon; Ros, Emilio; Fitó, Montserrat; Arós, Fernando; Fiol, Miquel; Serra-Majem, Lluís; Clish, Clary B; Becerra-Tomás, Nerea; Martínez-González, Miguel A; Hu, Frank B; Salas-Salvadó, Jordi.
Afiliação
  • Bulló M; Universitat Rovira i Virgili, Biochemistry and Biotechnology Department, Human Nutrition Unit, Reus, Spain.
  • Papandreou C; Pere i Virgili Health Research Institute (IISPV), Reus, Spain.
  • Ruiz-Canela M; CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain.
  • Guasch-Ferré M; Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain.
  • Li J; Universitat Rovira i Virgili, Biochemistry and Biotechnology Department, Human Nutrition Unit, Reus, Spain.
  • Hernández-Alonso P; Pere i Virgili Health Research Institute (IISPV), Reus, Spain.
  • Toledo E; CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain.
  • Liang L; Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain.
  • Razquin C; CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain.
  • Corella D; Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain.
  • Estruch R; Navarra Institute for Health Research (IdiSNA), Pamplona, Navarra, Spain.
  • Ros E; Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA.
  • Fitó M; Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA.
  • Arós F; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA.
  • Fiol M; Universitat Rovira i Virgili, Biochemistry and Biotechnology Department, Human Nutrition Unit, Reus, Spain.
  • Serra-Majem L; Pere i Virgili Health Research Institute (IISPV), Reus, Spain.
  • Clish CB; CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain.
  • Becerra-Tomás N; Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain.
  • Martínez-González MA; Department of Endocrinology and Nutrition, Virgen de la Victoria University Hospital, University of Malaga (IBIMA), Malaga, Spain.
  • Hu FB; CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain.
  • Salas-Salvadó J; Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain.
J Nutr ; 151(1): 50-58, 2021 01 04.
Article em En | MEDLINE | ID: mdl-33296468
ABSTRACT

BACKGROUND:

The quality of carbohydrate consumed, assessed by the glycemic index (GI), glycemic load (GL), or carbohydrate quality index (CQI), affects the postprandial glycemic and insulinemic responses, which have been implicated in the etiology of several chronic diseases. However, it is unclear whether plasma metabolites involved in different biological pathways could provide functional insights into the role of carbohydrate quality indices in health.

OBJECTIVES:

We aimed to identify plasma metabolomic profiles associated with dietary GI, GL, and CQI.

METHODS:

The present study is a cross-sectional analysis of 1833 participants with overweight/obesity (mean age = 67 y) from 2 case-cohort studies nested within the PREDIMED (Prevención con Dieta Mediterránea) trial. Data extracted from validated FFQs were used to estimate the GI, GL, and CQI. Plasma concentrations of 385 metabolites were profiled with LC coupled to MS and associations of these metabolites with those indices were assessed with elastic net regression analyses.

RESULTS:

A total of 58, 18, and 57 metabolites were selected for GI, GL, and CQI, respectively. Choline, cotinine, γ-butyrobetaine, and 363 phosphatidylserine plasmalogen were positively associated with GI and GL, whereas they were negatively associated with CQI. Fructose-glucose-galactose was negatively and positively associated with GI/GL and CQI, respectively. Consistent associations of 21 metabolites with both GI and CQI were found but in opposite directions. Negative associations of kynurenic acid, 221 sphingomyelin, and 386 phosphatidylethanolamine, as well as positive associations of 321 phosphatidylcholine with GI and GL were also observed. Pearson correlation coefficients between GI, GL, and CQI and the metabolomic profiles were 0.30, 0.22, and 0.27, respectively.

CONCLUSIONS:

The GI, GL, and CQI were associated with specific metabolomic profiles in a Mediterranean population at high cardiovascular disease risk. Our findings may help in understanding the role of dietary carbohydrate indices in the development of cardiometabolic disorders. This trial was registered at isrctn.com as ISRCTN35739639.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carboidratos da Dieta / Índice Glicêmico / Dieta / Metabolômica / Carga Glicêmica Tipo de estudo: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: J Nutr Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Espanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carboidratos da Dieta / Índice Glicêmico / Dieta / Metabolômica / Carga Glicêmica Tipo de estudo: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: J Nutr Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Espanha