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SHR Neuro Krebs Kardio Lipid Stoffw Microb

Gil-Redondo, R; Conde, R; Bruzzone, C; Seco, ML; Bizkarguenaga, M; González-Valle, B; de, Diego, A; Laín, A; Habisch, H; Haudum, C; Verheyen, N; Obermayer-Pietsch, B; Margarita, S; Pelusi, S; Verde, I; Oliveira, N; Sousa, A; Zabala-Letona, A; Santos-Martin, A; Loizaga-Iriarte, A; Unda-Urzaiz, M; Kazenwadel, J; Berezhnoy, G; Geisler, T; Gawaz, M; Cannet, C; Schäfer, H; Diercks, T; Trautwein, C; Carracedo, A; Madl, T; Valenti, L; Spraul, M; Lu, SC; Embade, N; Mato, JM; Millet, O.
MetSCORE: a molecular metric to evaluate the risk of metabolic syndrome based on serum NMR metabolomics.
Cardiovasc Diabetol. 2024; 23(1): 272 Doi: 10.1186/s12933-024-02363-3 [OPEN ACCESS]
Web of Science PubMed PUBMED Central FullText FullText_MUG

 

Co-Autor*innen der Med Uni Graz
Habisch Hansjörg
Haudum Christoph
Madl Tobias
Obermayer-Pietsch Barbara
Verheyen Nicolas Dominik
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Abstract:
BACKGROUND: Metabolic syndrome (MetS) is a cluster of medical conditions and risk factors correlating with insulin resistance that increase the risk of developing cardiometabolic health problems. The specific criteria for diagnosing MetS vary among different medical organizations but are typically based on the evaluation of abdominal obesity, high blood pressure, hyperglycemia, and dyslipidemia. A unique, quantitative and independent estimation of the risk of MetS based only on quantitative biomarkers is highly desirable for the comparison between patients and to study the individual progression of the disease in a quantitative manner. METHODS: We used NMR-based metabolomics on a large cohort of donors (n = 21,323; 37.5% female) to investigate the diagnostic value of serum or serum combined with urine to estimate the MetS risk. Specifically, we have determined 41 circulating metabolites and 112 lipoprotein classes and subclasses in serum samples and this information has been integrated with metabolic profiles extracted from urine samples. RESULTS: We have developed MetSCORE, a metabolic model of MetS that combines serum lipoprotein and metabolite information. MetSCORE discriminate patients with MetS (independently identified using the WHO criterium) from general population, with an AUROC of 0.94 (95% CI 0.920-0.952, p < 0.001). MetSCORE is also able to discriminate the intermediate phenotypes, identifying the early risk of MetS in a quantitative way and ranking individuals according to their risk of undergoing MetS (for general population) or according to the severity of the syndrome (for MetS patients). CONCLUSIONS: We believe that MetSCORE may be an insightful tool for early intervention and lifestyle modifications, potentially preventing the aggravation of metabolic syndrome.
Find related publications in this database (using NLM MeSH Indexing)
Humans - administration & dosage
Metabolic Syndrome - diagnosis, blood, epidemiology, urine
Female - administration & dosage
Metabolomics - administration & dosage
Male - administration & dosage
Biomarkers - blood, urine
Middle Aged - administration & dosage
Risk Assessment - administration & dosage
Predictive Value of Tests - administration & dosage
Adult - administration & dosage
Magnetic Resonance Spectroscopy - administration & dosage
Aged - administration & dosage
Lipoproteins - blood
Prognosis - administration & dosage
Risk Factors - administration & dosage
Cardiometabolic Risk Factors - administration & dosage
Young Adult - administration & dosage

Find related publications in this database (Keywords)
Metabolic syndrome
Lipoproteins
Obesity
Dyslipidemia
Diabetes
Hypertension
NMR spectroscopy
Precision medicine
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