Frontiers in Endocrinology (Sep 2022)

Morbid liver manifestations are intrinsically bound to metabolic syndrome and nutrient intake based on a machine-learning cluster analysis

  • Víctor Micó,
  • Rodrigo San-Cristobal,
  • Roberto Martín,
  • Miguel Ángel Martínez-González,
  • Miguel Ángel Martínez-González,
  • Miguel Ángel Martínez-González,
  • Jordi Salas-Salvadó,
  • Jordi Salas-Salvadó,
  • Dolores Corella,
  • Dolores Corella,
  • Montserrat Fitó,
  • Montserrat Fitó,
  • Ángel M. Alonso-Gómez,
  • Ángel M. Alonso-Gómez,
  • Julia Wärnberg,
  • Julia Wärnberg,
  • Jesús Vioque,
  • Jesús Vioque,
  • Dora Romaguera,
  • Dora Romaguera,
  • José López-Miranda,
  • José López-Miranda,
  • Ramon Estruch,
  • Ramon Estruch,
  • Francisco J. Tinahones,
  • Francisco J. Tinahones,
  • José Lapetra,
  • José Lapetra,
  • J. Luís Serra-Majem,
  • J. Luís Serra-Majem,
  • Aurora Bueno-Cavanillas,
  • Aurora Bueno-Cavanillas,
  • Josep A. Tur,
  • Josep A. Tur,
  • Josep A. Tur,
  • Vicente Martín Sánchez,
  • Vicente Martín Sánchez,
  • Xavier Pintó,
  • Xavier Pintó,
  • Miguel Delgado-Rodríguez,
  • Pilar Matía-Martín,
  • Josep Vidal,
  • Josep Vidal,
  • Clotilde Vázquez,
  • Clotilde Vázquez,
  • Ana García-Arellano,
  • Salvador Pertusa-Martinez,
  • Alice Chaplin,
  • Alice Chaplin,
  • Antonio Garcia-Rios,
  • Antonio Garcia-Rios,
  • Carlos Muñoz Bravo,
  • Carlos Muñoz Bravo,
  • Helmut Schröder,
  • Nancy Babio,
  • Nancy Babio,
  • Jose V. Sorli,
  • Jose V. Sorli,
  • Jose I. Gonzalez,
  • Jose I. Gonzalez,
  • Diego Martinez-Urbistondo,
  • Estefania Toledo,
  • Estefania Toledo,
  • Vanessa Bullón,
  • Miguel Ruiz-Canela,
  • María Puy- Portillo,
  • María Puy- Portillo,
  • María Puy- Portillo,
  • Manuel Macías-González,
  • Manuel Macías-González,
  • Nuria Perez-Diaz-del-Campo,
  • Jesús García-Gavilán,
  • Jesús García-Gavilán,
  • Lidia Daimiel,
  • J. Alfredo Martínez,
  • J. Alfredo Martínez,
  • J. Alfredo Martínez

DOI
https://doi.org/10.3389/fendo.2022.936956
Journal volume & issue
Vol. 13

Abstract

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Metabolic 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.

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