Background and aims: 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: 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: 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.

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

Moriero, Margherita;Verzola, Daniela;Bertolotto, Maria;Minetti, Silvia;Contini, Paola;Ramoni, Davide;Liberale, Luca;Pontremoli, Roberto;Viazzi, Francesca;Pende, Aldo;Pisciotta, Livia;Montecucco, Fabrizio;Carbone, Federico
2024-01-01

Abstract

Background and aims: 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: 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: 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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1176078
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