Micó, VíctorFitó Colomer, MontserratSchröder, Helmut, 1958-Martínez, José Alfredo2023-02-092023-02-092022Micó V, San-Cristobal R, Martín R, Martínez-González MÁ, Salas-Salvadó J, Corella D, et al. Morbid liver manifestations are intrinsically bound to metabolic syndrome and nutrient intake based on a machine-learning cluster analysis. Front Endocrinol (Lausanne). 2022 Sep 6; 13: 936956. DOI: 10.3389/fendo.2022.9369561664-2392http://hdl.handle.net/10230/55680Metabolic syndrome (MetS) is one of the most important medical problems around the world. Identification of patient´s singular characteristic could help to reduce the clinical impact and facilitate individualized management. This study aimed to categorize MetS patients using phenotypical and clinical variables habitually collected during health check-ups of individuals considered to have high cardiovascular risk. The selected markers to categorize MetS participants included anthropometric variables as well as clinical data, biochemical parameters and prescribed pharmacological treatment. An exploratory factor analysis was carried out with a subsequent hierarchical cluster analysis using the z-scores from factor analysis. The first step identified three different factors. The first was determined by hypercholesterolemia and associated treatments, the second factor exhibited glycemic disorders and accompanying treatments and the third factor was characterized by hepatic enzymes. Subsequently four clusters of patients were identified, where cluster 1 was characterized by glucose disorders and treatments, cluster 2 presented mild MetS, cluster 3 presented exacerbated levels of hepatic enzymes and cluster 4 highlighted cholesterol and its associated treatments Interestingly, the liver status related cluster was characterized by higher protein consumption and cluster 4 with low polyunsaturated fatty acid intake. This research emphasized the potential clinical relevance of hepatic impairments in addition to MetS traditional characterization for precision and personalized management of MetS patients.application/pdfengCopyright © 2022 Micó, San-Cristobal, Martín, Martínez-González, Salas-Salvadó, Corella, Fitó, Alonso-Gómez, Wärnberg, Vioque, Romaguera, López-Miranda, Estruch, Tinahones, Lapetra, Serra-Majem, Bueno-Cavanillas, Tur, Martín Sánchez, Pintó, Delgado-Rodríguez, Matía, Vidal, Vázquez, García-Arellano, Pertusa-Martinez, Chaplin, Garcia-Rios, Muñoz Bravo, Schröder, Babio, Sorli, Gonzalez, Martinez-Urbistondo, Toledo, Bullón, Ruiz-Canela, Portillo, Macías-González, Perez-Diaz-del-Campo, García-Gavilán, Daimiel and Martínez. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) http://creativecommons.org/licenses/by/4.0/. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply winfo:eu-repo/semantics/articlehttp://dx.doi.org/10.3389/fendo.2022.936956BiomarkersClusterDyslipidemiaGlucose disordersHepatic enzymesMetabolic syndromeinfo:eu-repo/semantics/openAccess