• Mi Re-Unir
    Búsqueda Avanzada
    JavaScript is disabled for your browser. Some features of this site may not work without it.
    Ver ítem 
    •   Inicio
    • RESULTADOS DE INVESTIGACIÓN
    • Otras Publicaciones: artículos, libros...
    • Ver ítem
    •   Inicio
    • RESULTADOS DE INVESTIGACIÓN
    • Otras Publicaciones: artículos, libros...
    • Ver ítem

    Urinary Hippuric Acid as a Sex-Dependent Biomarker for Fruit and Nut Intake Raised from the EAT-Lancet Index and Nuclear Magnetic Resonance Analysis

    Autor: 
    Fernández-Cruz, Edwin
    ;
    de la O, Víctor
    ;
    M Fernández-Diaz, Cristina
    ;
    Matía-Martín, Pilar
    ;
    Rubio-Herrera, M Ángel
    ;
    Amigó, Nuria
    ;
    L Calle-Pascual, Alfonso
    ;
    Martínez, J Alfredo
    Fecha: 
    2025
    Palabra clave: 
    EAT-Lancet index; biomarker of food intake; dietary assessment; hippuric acid; precision nutrition
    Revista / editorial: 
    Metabolites
    Citación: 
    Fernández-Cruz E, de la O V, Fernández-Diaz CM, Matía-Martín P, Rubio-Herrera MÁ, Amigó N, Calle-Pascual AL, Martínez JA. Urinary Hippuric Acid as a Sex-Dependent Biomarker for Fruit and Nut Intake Raised from the EAT-Lancet Index and Nuclear Magnetic Resonance Analysis. Metabolites. 2025 May 23;15(6):348. doi: 10.3390/metabo15060348. PMID: 40559371; PMCID: PMC12194962.
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/19517
    DOI: 
    https://doi.org/10.3390/metabo15060348
    Dirección web: 
    https://www.mdpi.com/2218-1989/15/6/348
    Open Access
    Resumen:
    Background/Objectives: Assessing nutrient intake is essential for understanding body homeostasis and diet-health interactions. Traditional methods, such as dietary questionnaires and quality indices, are limited by subjectivity and variability in food composition tables. Metabolomic markers, like urinary hippuric acid, provide an objective means to estimate food and nutrient intake, helping to link dietary patterns with metabolic outputs and health outcomes. This study uniquely evaluates urinary hippuric acid as a putative biomarker of nut intake, expanding the previously known role as a fruit intake marker, and investigates sex-related differences in the excretion. Methods: Using Nuclear Magnetic Resonance (NMR) spectroscopy, 34 urinary metabolites from 138 participants (69.7% women) in the Dietary Deal project were analyzed. Metabolite concentrations were categorized by median adherence to the EAT-Lancet score (≤p50 or >p50). A validated Food Frequency Questionnaire (FFQ) assessed dietary and energy intake. Correlation analyses linked metabolites to the 14 EAT-Lancet food groups, and a linear regression adjusted model examined associations between urinary hippuric acid and fruit/nut consumption, with sensitivity analysis for sex. Results: The EAT-Lancet index, stratified by median adherence, effectively distinguished between high and low dietary intake of fruits (p = 0.012) and nuts (p < 0.001). Urinary hippuric acid concentrations were found to be influenced by sex (p = 0.020), with females showing a 44.7% higher mean concentration. Overall, urinary hippuric acid levels were positively associated with FFQ-estimated nut consumption (p = 0.049), providing the first evidence of potential suitability as a nut intake biomarker. Conclusions: Hippuric acid emerges as a promising dietary biomarker for assessing nut intake in healthy populations. This study provides novel insights that extend the application of hippuric acid to dietary nut assessment and emphasizes the importance of a sex-specific interpretation for precision nutrition purposes using NMR technology.
    Mostrar el registro completo del ítem
    Ficheros en el ítem
    icon
    Nombre: metabolites-15-00348-2.pdf
    Tamaño: 1.487Mb
    Formato: application/pdf
    Ver/Abrir
    Este ítem aparece en la(s) siguiente(s) colección(es)
    • Otras Publicaciones: artículos, libros...

    Estadísticas de uso

    Año
    2012
    2013
    2014
    2015
    2016
    2017
    2018
    2019
    2020
    2021
    2022
    2023
    2024
    2025
    2026
    Vistas
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    17
    Descargas
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    2

    Ítems relacionados

    Mostrando ítems relacionados por Título, autor o materia.

    • Translational algorithms for technological dietary quality assessment integrating nutrimetabolic data with machine learning methods 

      de la O, Victor; Fernández-Cruz, Edwin; Matía Matín, Pilar; Larrad-Sainz, Angélica; Espadas Gil, Jose Luis; Barabash, Ana; Fernández-Díaz, Cristina M.; Calle-Pascual, Alfonso L.; Rubio-Herrera, Miguel A.; Martínez, J. Alfredo (MDPI, 2024)
      Recent advances in machine learning technologies and omics methodologies are revolutionizing dietary assessment by integrating phenotypical, clinical, and metabolic biomarkers, which are crucial for personalized precision ...
    • Upgraded Estimation of Dietary Intake Using Phenotypic and Biochemical Markers by Supervised Equations: Applicability for Categorizing DQI 

      Fernandez-Cruz, Edwin; de la O, Victor; Fernandez, Cristina M.; Rubio-Herrera, Miguel A.; Matía-Martín, Pilar; Calle-Pascual, Alfonso L.; Barabash, Ana; Martinez, J. Alfredo (Journal of the American Nutrition Association, 2025)
      Objective: Dietary and nutrient intake directly impact health, whereby adherence to certain dietary patterns is linked to positive outcomes. Traditional methods like the Food Frequency Questionnaire (FFQ) and 24-hour recall ...
    • Development of computational algorithmics using biochemical data to predict dietary habits: insights from the dietary deal study 

      Fernández-Cruz, Edwin; Calle-Pascual, Alfonso L.; Rubio, Miguel A.; Matía, Pilar; Martínez Hernández, José Alfredo; De La O, Víctor; Espadas, José Luis (Elsevier, 2024)
      Objectives: Assessing dietary intake and understanding the underlaying contributions to health is crucial from achieving metabolic wellbeing. Traditional methods to measure food intake such as food questionnaires and dietary ...

    Mi cuenta

    AccederRegistrar

    ¿necesitas ayuda?

    Manual de UsuarioContacto: reunir@unir.net

    Listar

    todo Re-UnirComunidades y coleccionesPor fecha de publicaciónAutoresTítulosPalabras claveTipo documentoTipo de accesoEsta colecciónPor fecha de publicaciónAutoresTítulosPalabras claveTipo documentoTipo de acceso






    Aviso Legal Política de Privacidad Política de Cookies Cláusulas legales RGPD
    © UNIR - Universidad Internacional de La Rioja
     
    Aviso Legal Política de Privacidad Política de Cookies Cláusulas legales RGPD
    © UNIR - Universidad Internacional de La Rioja