Serum klotho as a novel biomarker for metabolic syndrome: findings from a large national cohort.

Background: Metabolic syndrome is a cluster of metabolic abnormalities that significantly increase the risk of cardiovascular disease and mortality. The identification of novel biomarkers associated with mortality in patients with metabolic syndrome could facilitate early risk stratification and targeted interventions. Methods: We conducted a large prospective cohort study using data from five cycles (2009-2016) of the National Health and Nutrition Examination Survey (NHANES) database, including a total of 40,439 participants. Logistic regression analysis was used to assess the association between serum klotho protein levels and metabolic syndrome, while Cox regression analysis was employed to examine the correlation between serum klotho levels and all-cause mortality. Mortality data were updated until December 31, 2019. Results: After adjusting for demographic and socioeconomic confounders, the logistic regression model demonstrated that higher serum klotho levels were significantly associated with a decreased prevalence of metabolic syndrome (OR [95% CI] Highest vs. lowest quartile: 0.84 [0.70-0.99], P=0.038). In the Cox regression model, elevated klotho levels were found to significantly reduce the risk of all-cause mortality among individuals with metabolic syndrome (HR [95% CI] Highest vs. lowest quartile: 0.68 [0.51-0.90], P=0.006). Conclusion: Serum klotho levels were found to be inversely associated with the prevalence of metabolic syndrome, independent of potential confounding factors such as demographics, socioeconomic status, and lifestyle factors. Furthermore, higher klotho levels strongly indicated a lower risk of all-cause mortality in individuals with metabolic syndrome.

Inflammation mediates the relationship between diet quality assessed by healthy eating index-2015 and metabolic syndrome.

Background: Metabolic syndrome is a cluster of metabolic disorders, including obesity, hypertension, hyperglycemia, and abnormal lipid levels. However, researches on the association between overall dietary quality measured by the Healthy Eating Index-2015 (HEI-2015) and the risk of metabolic syndrome is still lacking. Methods: This study utilized data from four cycles (2011-2018) of the National Health and Nutrition Examination Survey (NHANES) database, including 17,582 participants. Logistic regression analysis was employed to explore the correlation between HEI and the risk of metabolic syndrome. Additionally, mediation analysis was conducted to examine the effects of Systemic Immune-Inflammation Index (SII) and serum uric acid as potential mediators between HEI and metabolic syndrome risk. Weighted quantile sum (WQS) regression evaluated the composite exposure impact of the 13 components of the HEI on metabolic syndrome, as well as the proportion of their weights. Results: Higher dietary quality measured by HEI-2015 (at the 75th percentile) was negatively correlated with the risk of metabolic syndrome (OR=0.80, 95%CI=0.72-0.89, P=0.003). Higher SII and serum uric acid levels were identified as risk factors for metabolic syndrome (P for trend<0.001). Approximately 37.5% of the effect of HEI on metabolic syndrome occurrence was mediated by SII (Indirect effect=-0.002, 95%CI (-0.003,-0.001), Direct effect=-0.022, 95%CI (-0.0273,-0.015)). Additionally, 25% of the effect of HEI on metabolic syndrome occurrence was mediated by serum uric acid levels (Indirect effect=-0.006, 95%CI (-0.010,-0.012), Direct effect=-0.024, 95%CI (-0.041,-0.009)). WQS regression analysis revealed the highest weighted proportions for seafood and plant proteins (25.20%) and sodium (17.79%), while the weight for whole fruit was the lowest (0.25%). Conclusion: Better dietary quality measured by HEI-2015 was associated with a lower likelihood of metabolic syndrome. Higher SII and serum uric acid levels were identified as risk factors for metabolic syndrome and potential mediators.