Articles producció científica> Bioquímica i Biotecnologia

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

  • Dades identificatives

    Identificador: imarina:9282215
    Autors:
    Micó VSan-Cristobal RMartín RMartínez-González MÁSalas-Salvadó JCorella DFitó MAlonso-Gómez ÁMWärnberg JVioque JRomaguera DLópez-Miranda JEstruch RTinahones FJLapetra JSerra-Majem JLBueno-Cavanillas ATur JAMartín Sánchez VPintó XDelgado-Rodríguez MMatía-Martín PVidal JVázquez CGarcía-Arellano APertusa-Martinez SChaplin AGarcia-Rios AMuñoz Bravo CSchröder HBabio NSorli JVGonzalez JIMartinez-Urbistondo DToledo EBullón VRuiz-Canela MPortillo MPMacías-González MPerez-Diaz-del-Campo NGarcía-Gavilán JDaimiel LMartínez JA
    Resum:
    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.
  • Altres:

    Autor segons l'article: Micó V; San-Cristobal R; Martín R; Martínez-González MÁ; Salas-Salvadó J; Corella D; Fitó M; Alonso-Gómez ÁM; Wärnberg J; Vioque J; Romaguera D; López-Miranda J; Estruch R; Tinahones FJ; Lapetra J; Serra-Majem JL; Bueno-Cavanillas A; Tur JA; Martín Sánchez V; Pintó X; Delgado-Rodríguez M; Matía-Martín P; Vidal J; Vázquez C; García-Arellano A; Pertusa-Martinez S; Chaplin A; Garcia-Rios A; Muñoz Bravo C; Schröder H; Babio N; Sorli JV; Gonzalez JI; Martinez-Urbistondo D; Toledo E; Bullón V; Ruiz-Canela M; Portillo MP; Macías-González M; Perez-Diaz-del-Campo N; García-Gavilán J; Daimiel L; Martínez JA
    Departament: Bioquímica i Biotecnologia
    Autor/s de la URV: Babio Sánchez, Nancy Elvira / Salas Salvadó, Jorge
    Paraules clau: Metabolic syndrome Hepatic enzymes Glucose disorders Food-frequency questionnaire Dyslipidemia Cluster Biomarkers validity risk population outcomes obesity neutrophil-lymphocyte ratio mini-mental state metabolic syndrome inflammation glucose disorders dyslipidemia cluster biomarkers association
    Resum: 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.
    Àrees temàtiques: Medicina veterinaria Medicina iii Medicina ii Medicina i Interdisciplinar Farmacia Endocrinology, diabetes and metabolism Endocrinology & metabolism Ciências biológicas ii Ciências biológicas i
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    Adreça de correu electrònic de l'autor: jordi.salas@urv.cat nancy.babio@urv.cat
    Identificador de l'autor: 0000-0003-2700-7459 0000-0003-3527-5277
    Data d'alta del registre: 2024-09-07
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    Enllaç font original: https://internal-journal.frontiersin.org/articles/10.3389/fendo.2022.936956/full
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Frontiers In Endocrinology. 13
    Referència de l'ítem segons les normes APA: Micó V; San-Cristobal R; Martín R; Martínez-González MÁ; Salas-Salvadó J; Corella D; Fitó M; Alonso-Gómez ÁM; Wärnberg J; Vioque J; Romaguera D; López (2022). Morbid liver manifestations are intrinsically bound to metabolic syndrome and nutrient intake based on a machine-learning cluster analysis. Frontiers In Endocrinology, 13(), -. DOI: 10.3389/fendo.2022.936956
    DOI de l'article: 10.3389/fendo.2022.936956
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2022
    Tipus de publicació: Journal Publications
  • Paraules clau:

    Endocrinology & Metabolism,Endocrinology, Diabetes and Metabolism
    Metabolic syndrome
    Hepatic enzymes
    Glucose disorders
    Food-frequency questionnaire
    Dyslipidemia
    Cluster
    Biomarkers
    validity
    risk
    population
    outcomes
    obesity
    neutrophil-lymphocyte ratio
    mini-mental state
    metabolic syndrome
    inflammation
    glucose disorders
    dyslipidemia
    cluster
    biomarkers
    association
    Medicina veterinaria
    Medicina iii
    Medicina ii
    Medicina i
    Interdisciplinar
    Farmacia
    Endocrinology, diabetes and metabolism
    Endocrinology & metabolism
    Ciências biológicas ii
    Ciências biológicas i
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