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Which salivary components can differentiate metabolic obesity?
Lucyna Ostrowska1, Agnieszka Gornowicz2, Barbara Pietraszewska1
1Department of Dietetics and Clinical Nutrition, Medical University of Bialystok, Bialystok, Poland.
Saliva analysis revealed higher levels of interleukin-8 (IL-8), calprotectin, and matrix metalloproteinase-2 (MMP-2) in women with metabolic obesity. These salivary markers, including tumor necrosis factor-α (TNF-α), correlate with obesity indicators like BMI and body fat.
Area of Science:
- Biochemistry
- Human Physiology
- Metabolic Health
Background:
- Obesity is a complex global health issue.
- Metabolic obesity is characterized by increased health risks.
- Salivary biomarkers are being explored for non-invasive health assessments.
Purpose of the Study:
- To assess salivary concentrations of specific inflammatory markers and enzymes in women with varying body composition.
- To determine if salivary markers can indicate metabolic obesity.
- To explore correlations between salivary markers and obesity indicators.
Main Methods:
- A pilot study involving 10 women with obesity and 6 healthy controls.
- Enzyme-linked immunosorbent assay (ELISA) was used to measure salivary levels of TNF-α, IL-8, sICAM1, calprotectin, MMP-9, MMP-2, and TLR2.
- Statistical analysis to correlate salivary marker levels with body composition parameters (BMI, body fat percentage, VAT, WHR) and insulin levels.
Main Results:
- Women with metabolic obesity showed significantly elevated salivary IL-8, calprotectin, and MMP-2 compared to controls.
- Body Mass Index (BMI) positively correlated with salivary TNF-α, IL-8, and MMP-2.
- Body fat mass and percentage showed positive correlations with TNF-α, IL-8, and MMP-2; visceral adipose tissue (VAT) and waist-hip ratio (WHR) correlated with TNF-α and MMP-2.
Conclusions:
- Salivary concentrations of TNF-α, MMP-2, and IL-8 are positively correlated with BMI.
- These three salivary components show potential as non-invasive indicators of metabolic obesity.
- Further research with larger cohorts is recommended to validate these findings.
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