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Salivary uric acid as a noninvasive biomarker of metabolic syndrome
BACKGROUND: Elevated serum uric acid is associated with obesity, hypertension and metabolic syndrome. Because a linear relationship exists between serum and salivary uric acid (SUA) concentration, saliva testing may be a useful noninvasive approach for monitoring cardiometabolic risk. The goal of th...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3428646/ https://www.ncbi.nlm.nih.gov/pubmed/22515434 http://dx.doi.org/10.1186/1758-5996-4-14 |
Sumario: | BACKGROUND: Elevated serum uric acid is associated with obesity, hypertension and metabolic syndrome. Because a linear relationship exists between serum and salivary uric acid (SUA) concentration, saliva testing may be a useful noninvasive approach for monitoring cardiometabolic risk. The goal of this pilot study was to determine if SUA is increased in patients with metabolic syndrome and to investigate correlations between SUA and individual cardiometabolic risk factors. FINDINGS: Volunteers between the ages of 18 and 65 without conditions known to affect serum uric acid levels were recruited. Height, weight, blood pressure and waist circumference were measured and a full lipid panel along with fasting blood glucose was obtained. Saliva samples were collected and uric acid levels were determined. 78 volunteers, 35% of whom had metabolic syndrome, completed the study. SUA was significantly elevated in patients with metabolic syndrome (p=.002). The incidence of metabolic syndrome in the 4(th) quartile for SUA was 67% compared to 25% in quartiles1-3 combined. Significant correlations were seen between SUA and systolic blood pressure (r=.440, p=.000), diastolic blood pressure ( r=.304, p=.007), waist circumference (r=.332, p=.003), BMI ( r=.269, p=.018), fasting blood glucose ( r=.341, p=.002), triglycerides (r=.410, p=.000), HDL ( r=.237, p=.036) and the number of cardiometabolic risk factors present (r=0.257, p=.023). CONCLUSIONS: These results suggest that SUA may be a useful biomarker for noninvasive monitoring of cardiometabolic risk. Larger studies are needed to validate this approach. |
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