<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-13T01:47:30Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:2445/163513" metadataPrefix="qdc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:2445/163513</identifier><datestamp>2025-12-04T22:37:56Z</datestamp><setSpec>com_2072_1057</setSpec><setSpec>col_2072_478825</setSpec><setSpec>col_2072_478858</setSpec><setSpec>col_2072_478917</setSpec><setSpec>col_2072_478924</setSpec></header><metadata><qdc:qualifieddc xmlns:qdc="http://dspace.org/qualifieddc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://purl.org/dc/elements/1.1/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dc.xsd http://purl.org/dc/terms/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dcterms.xsd http://dspace.org/qualifieddc/ http://www.ukoln.ac.uk/metadata/dcmi/xmlschema/qualifieddc.xsd">
   <dc:title>Non-targeted metabolomic biomarkers and metabotypes of type 2 diabetes: A cross-sectional study of PREDIMED trial participants</dc:title>
   <dc:creator>Urpí Sardà, Mireia</dc:creator>
   <dc:creator>Almanza Aguilera, Enrique</dc:creator>
   <dc:creator>Llorach, Rafael</dc:creator>
   <dc:creator>Vázquez Fresno, Rosa</dc:creator>
   <dc:creator>Estruch Riba, Ramon</dc:creator>
   <dc:creator>Corella Piquer, Dolores</dc:creator>
   <dc:creator>Sorlí, José V.</dc:creator>
   <dc:creator>Carmona Pontaque, Francesc</dc:creator>
   <dc:creator>Sànchez, Àlex (Sànchez Pla)</dc:creator>
   <dc:creator>Salas Salvadó, Jordi</dc:creator>
   <dc:creator>Andrés Lacueva, Ma. Cristina</dc:creator>
   <dc:subject>Dietoteràpia</dc:subject>
   <dc:subject>Metabolisme</dc:subject>
   <dc:subject>Marcadors bioquímics</dc:subject>
   <dc:subject>Diabetis no-insulinodependent</dc:subject>
   <dc:subject>Medicina preventiva</dc:subject>
   <dc:subject>Metabolòmica</dc:subject>
   <dc:subject>Factors de risc en les malalties</dc:subject>
   <dc:subject>Diet therapy</dc:subject>
   <dc:subject>Metabolism</dc:subject>
   <dc:subject>Biochemical markers</dc:subject>
   <dc:subject>Non-insulin-dependent diabetes</dc:subject>
   <dc:subject>Preventive medicine</dc:subject>
   <dc:subject>Metabolomics</dc:subject>
   <dc:subject>Risk factors in diseases</dc:subject>
   <dcterms:abstract>Aim. - To characterize the urinary metabolomic fingerprint and multi-metabolite signature associated with type 2 diabetes (T2D), and to classify the population into metabotypes related to T2D. Methods. - A metabolomics analysis using the 1 H-NMR-based, non-targeted metabolomic approach was conducted to determine the urinary metabolomic fingerprint of T2D compared with non-T2D participants in the PREDIMED trial. The discriminant metabolite fingerprint was subjected to logistic regression analysis and ROC analyses to establish and to assess the multi-metabolite signature of T2D prevalence, respectively. Metabotypes associated with T2D were identified using the k-means algorithm. Results. - A total of 33 metabolites were significantly different (P &lt; 0.05) between T2D and non-T2D participants. The multi-metabolite signature of T2D comprised high levels of methylsuccinate, alanine, dimethylglycine and guanidoacetate, and reduced levels of glutamine, methylguanidine, 3-hydroxymandelate and hippurate, and had a 96.4% AUC, which was higher than the metabolites on their own and glucose. Amino-acid and carbohydrate metabolism were the main metabolic alterations in T2D, and various metabotypes were identified in the studied population. Among T2D participants, those with a metabotype of higher levels of phenylalanine, phenylacetylglutamine, p-cresol and acetoacetate had significantly higher levels of plasma glucose. Conclusion. - The multi-metabolite signature of T2D highlights the altered metabolic fingerprint associated mainly with amino-acid, carbohydrate and microbiota metabolism. Metabotypes identified in this patient population could be related to higher risk of long-term cardiovascular events and therefore require further studies. Metabolomics is a useful tool for elucidating the metabolic complexity and interindividual variation in T2D towards the development of stratified precision nutrition and medicine</dcterms:abstract>
   <dcterms:issued>2020-06-02T06:25:35Z</dcterms:issued>
   <dcterms:issued>2020-06-02T06:25:35Z</dcterms:issued>
   <dcterms:issued>2019-04-01</dcterms:issued>
   <dcterms:issued>2020-06-02T06:25:35Z</dcterms:issued>
   <dc:type>info:eu-repo/semantics/article</dc:type>
   <dc:type>info:eu-repo/semantics/acceptedVersion</dc:type>
   <dc:relation>Versió postprint del document publicat a: https://doi.org/10.1016/j.diabet.2018.02.006</dc:relation>
   <dc:relation>Diabetes &amp; Metabolism, 2019, vol. 45, num. 2, p. 167-174</dc:relation>
   <dc:relation>https://doi.org/10.1016/j.diabet.2018.02.006</dc:relation>
   <dc:rights>(c) Elsevier Masson SAS, 2019</dc:rights>
   <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
   <dc:publisher>Elsevier Masson SAS</dc:publisher>
   <dc:source>Articles publicats en revistes (Nutrició, Ciències de l'Alimentació i Gastronomia)</dc:source>
</qdc:qualifieddc></metadata></record></GetRecord></OAI-PMH>