Metabolic syndrome and cardiovascular risk

Structural Equation Modelling for Predicting the Relative Contribution of Each Component in the Metabolic Syndrome Status Change

Understanding the factor weighting in the development of metabolic syndrome (MetS) may help to predict the progression for cardiovascular and metabolic diseases. Thus, the aim of this study was to develop a confirmatory model to describe and explain the direct and indirect effect of each component in MetS status change. A total of 3581 individuals diagnosed with MetS, aged 18−102 years, were selected between January 2019 and December 2020 from a community-representative sample of Portuguese adults in a north-eastern Portuguese region to test the model’s goodness of fit. A structural equation modelling (SEM) approach and a two-way ANOVA (age × body composition) were performed to compare the relative contribution of each MetS component using joint interim statement (JIS). Waist circumference (β = 0.189−0.373, p < 0.001), fasting glucose (β = 0.168−0.199, p < 0.001) and systolic blood pressure (β = 0.140−0.162, p < 0.001) had the highest direct effect on the change in MetS status in the overall population and concerning both sexes. Moreover, diastolic blood pressure (DBP), triglycerides (TG) and high-density lipoprotein cholesterol (HDL-c) had a low or non-significant effect. Additionally, an indirect effect was reported for age and body composition involving the change in MetS status. The findings may suggest that other components with higher specificity and sensitivity should be considered to empirically validate the harmonised definition of MetS. Current research provides the first multivariate model for predicting the relative contribution of each component in the MetS status change, specifically in Portuguese adults.

The roles of IGF2 and DNMT methylation and elongase6 related fatty acids in metabolic syndrome

Background: The prevalence of metabolic syndrome (MetS) has increased along with rapid socio-economic development in China in recent decades, aggravating the burden of the health care system. Both plasma levels of fatty acids (FAs) and aberrant DNA methylation profiles are associated with MetS risk. However, studies exploring the role of DNA methylation and FAs simultaneously in MetS etiology are sparse. Objective: We aimed to explore the association between the gene methylation levels of insulin-like growth factor II (IGF2), H19, DNA methyltransferases 1 (DNMT1), DNA methyltransferases 3a (DNMT3a), and DNA methyltransferases 3b (DNMT3b) and MetS risk, and the etiological role of elongation of very-long-chain fatty acid elongase 6 (ELOVL6) related fatty acids. Method: Plasma levels of FAs were measured using a Gas Chromatography-Flame Ionization Detector (GC-FID) after organic extraction, and gene methylation was quantified using a real-time Quantitative Polymerase Chain Reaction (Q-PCR) detecting system after bisulfite treatment. The C18/C16 ratio was used as the indicator of ELOVL6 activity. Odds Ratio (OR) and 95% Confidence Interval (CI) were estimated with logistic regression. Results: Methylation levels in IGF2 and DNMT3a were not significantly associated with MetS risk. However, when stratified by C18/C16 ratio (high vs. low), positive associations were observed between the risk of MetS and methylation levels (>median) of IGF2a3 (OR = 3.1, 95% CI = 1.3-7.5) and DNMT3a (OR = 2.5, 95% CI = 1.1-5.8) genes, in individuals with lower C18/C16 ratios, while no significant associations were observed in subjects with high C18/C16 ratios. Conclusion: Methylation levels in IGF2 and DNMT3a genes may affect the risk of MetS in an ELOVL6 activity-dependent way among Chinese adults. Further studies in other populations are needed to validate this finding.

Natural Polyphenols in Metabolic Syndrome: Protective Mechanisms and Clinical Applications

Metabolic syndrome (MetS) is a chronic disease, including abdominal obesity, dyslipidemia, hyperglycemia, and hypertension. It should be noted that the occurrence of MetS is closely related to oxidative stress-induced mitochondrial dysfunction, ectopic fat accumulation, and the impairment of the antioxidant system, which in turn further aggravates the intracellular oxidative imbalance and inflammatory response. As enriched anti-inflammatory and antioxidant components in plants, natural polyphenols exhibit beneficial effects, including improving liver fat accumulation and dyslipidemia, reducing blood pressure. Hence, they are expected to be useful in the prevention and management of MetS. At present, epidemiological studies indicate a negative correlation between polyphenol intake and MetS incidence. In this review, we summarized and discussed the most promising natural polyphenols (including flavonoid and non-flavonoid drugs) in the precaution and treatment of MetS, including their anti-inflammatory and antioxidant properties, as well as their regulatory functions involved in glycolipid homeostasis.

Metabolic Syndrome and Coronary Artery Disease Risk: A Meta-Analysis of Observational Studies

Although numerous studies have described the link between metabolic syndrome (MetS) and Coronary Artery Disease (CAD), no meta-analysis has been carried out on this relationship. Thus, the present study intended to address this limitation. A systematic search was carried out using electronic databases, such as PubMed, CINAHL Plus, Medline, and Web of Science. A sum of 10 studies (n = 9327) was incorporated in the meta-analysis. Compared with non-MetS, MetS was significantly associated with high CAD risk (OR = 4.03, 95% CI = 3.56–4.56). The MetS components were also significantly correlated with high CAD risk (OR = 3.72, 95% CI = 3.22–4.40). The presence of two (OR = 3.93, 95% CI = 2.81–5.49), three (OR = 4.09, 95% CI = 2.85–5.86), four (OR = 4.04, 95% CI = 2.83–5.78), or all five MetS components (OR = 3.92, 95% CI = 3.11–4.93), were significantly associated with a high risk of CAD. MetS and its individual or combined elements were linked with high CAD risk based on contemporary evidence. Thus, the assessment of MetS and its components might help identify people at a higher risk of advancing CAD in the future.