Baseline urinary osteopontin levels are associated with the improvement of metabolic syndrome.

Body mass index Metabolic syndrome Urinary osteopontin Waist circumference

Journal

Nutrition, metabolism, and cardiovascular diseases : NMCD
ISSN: 1590-3729
Titre abrégé: Nutr Metab Cardiovasc Dis
Pays: Netherlands
ID NLM: 9111474

Informations de publication

Date de publication:
29 Mar 2024
Historique:
received: 05 01 2024
revised: 19 03 2024
accepted: 26 03 2024
medline: 26 4 2024
pubmed: 26 4 2024
entrez: 25 4 2024
Statut: aheadofprint

Résumé

While serum osteopontin (OPN)'s established role in cardiometabolic risk is recognized, its potential as a predictor of metabolic syndrome (MetS) improvement through a urine assay has not yet been demonstrated. In this study, we propose its potential predictive role over a 12-month period of standard care, with the ability to complement anthropometric measures. Hierarchical clustering revealed a notable association of urinary OPN (uOPN) with MetS criteria and overcame anthropometric measures in predicting the improvement at 12 months (OR of 2.74 [95% CI 1.32 to 6.29]). uOPN significantly contributed to the homogeneity of the nodes in the random forest and ultimately enhanced the performance of anthropometric measures when assessed for accuracy and area under the curve (AUC). Our findings offer insights into potential applications in cardiometabolic medicine for uOPN, which is easily detectable in non-invasive biological samples through an affordable assay.

Sections du résumé

BACKGROUND AND AIMS OBJECTIVE
While serum osteopontin (OPN)'s established role in cardiometabolic risk is recognized, its potential as a predictor of metabolic syndrome (MetS) improvement through a urine assay has not yet been demonstrated. In this study, we propose its potential predictive role over a 12-month period of standard care, with the ability to complement anthropometric measures.
METHODS AND RESULTS RESULTS
Hierarchical clustering revealed a notable association of urinary OPN (uOPN) with MetS criteria and overcame anthropometric measures in predicting the improvement at 12 months (OR of 2.74 [95% CI 1.32 to 6.29]). uOPN significantly contributed to the homogeneity of the nodes in the random forest and ultimately enhanced the performance of anthropometric measures when assessed for accuracy and area under the curve (AUC).
CONCLUSION CONCLUSIONS
Our findings offer insights into potential applications in cardiometabolic medicine for uOPN, which is easily detectable in non-invasive biological samples through an affordable assay.

Identifiants

DOI: 10.1016/j.numecd.2024.03.028 PMID: 38664124
pubmed: 38664124
pii: S0939-4753(24)00130-3
doi: 10.1016/j.numecd.2024.03.028
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Conflict of interest Luca Liberale is co-inventor on the international patent WO/2020/226,993 filed in April 2020. The patent relates to the use of antibodies which specifically bind IL-1α to reduce various sequelae of ischaemia–reperfusion injury to the central nervous system. Luca Liberale reports speaker fees from Daiichi-Sankyo outside the submitted work and has received funding from the Novartis Foundation for Medical-biological Research (unrelated to this work). The other authors declare they have no conflict of interest.

Auteurs

Margherita Moriero (M)

First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy.

Daniela Verzola (D)

First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy.

Maria Bertolotto (M)

First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy.

Silvia Minetti (S)

First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy.

Paola Contini (P)

First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy.

Davide Ramoni (D)

First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy.

Luca Liberale (L)

First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy; IRCCS Ospedale Policlinico San Martino, Genoa - Italian Cardiovascular Network, Genoa, Italy.

Roberto Pontremoli (R)

First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy; IRCCS Ospedale Policlinico San Martino, Genoa, Genoa, Italy.

Francesca Viazzi (F)

First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy; IRCCS Ospedale Policlinico San Martino, Genoa, Genoa, Italy.

Aldo Pende (A)

First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy; IRCCS Ospedale Policlinico San Martino, Genoa, Genoa, Italy.

Livia Pisciotta (L)

First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy; IRCCS Ospedale Policlinico San Martino, Genoa, Genoa, Italy.

Fabrizio Montecucco (F)

First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy; IRCCS Ospedale Policlinico San Martino, Genoa - Italian Cardiovascular Network, Genoa, Italy.

Federico Carbone (F)

First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy; IRCCS Ospedale Policlinico San Martino, Genoa - Italian Cardiovascular Network, Genoa, Italy. Electronic address: federico.carbone@unige.it.

Classifications MeSH