Raised dietary Zn:Cu ratio increases the risk of atherosclerosis in type 2 diabetes

Unlocking the Dietary Puzzle: How Macronutrient Intake Shapes the Relationship between Visfatin and Atherosclerosis in Type 2 Diabetes

Background and Objectives. Optimal nutrition for type 2 diabetes (T2DM) aims to improve glycemic control by promoting weight loss and reducing adipose tissue, consequently improving cardiovascular health. Dietary alterations can influence adipose tissue metabolism and potentially impact adipocytokines like visfatin, thereby affecting atherosclerosis development. This study aimed to investigate dietary habits and adherence to recommendations among individuals with T2DM and to examine how dietary adherence influences the association between visfatin and subclinical atherosclerosis. Materials and Methods: This cross-sectional multicenter study involved 216 adults (30-70 years) with T2DM, assessing dietary habits, adherence to recommendations (carbohydrates, fats, protein, fiber, saturated fatty acid, polyunsaturated and monounsaturated fatty acid (PUFA and MUFA) and salt), and the association between visfatin and subclinical atherosclerosis. Participants completed 24 h dietary recalls; dietary misreporting was assessed using the Goldberg cut-off method. Carotid intima-media thickness (IMT) and plaque occurrence were evaluated with ultrasound, while visfatin levels were measured using Luminex's xMAP technology. Results: Three of the eight recommendations were followed in 31% of subjects, two in 26%, and four in 20%, with the highest adherence to MUFA and protein intake. Significant correlations between IMT and visfatin were observed in individuals with specific dietary patterns. The association between IMT and visfatin persisted when PUFA and MUFA intake aligned with recommendations. PUFA intake ≤ 10% and MUFA ≤ 20% of total energy significantly correlated with carotid artery IMT (p = 0.010 and p = 0.006, respectively). Visfatin's associations with IMT remained significant (p = 0.006) after adjusting for common risk factors, medication use, and dietary nonadherence. No association was observed with carotid artery plaque. Conclusions: Dietary compliance was limited, as only 31% adhered even to three of eight recommendations. A common dietary pattern characterized by low carbohydrate and fiber but high fat, total fat, saturated fat, and salt intake was identified. This pattern amplifies the statistical association between visfatin and subclinical atherosclerosis.

Copper and Diabetes: Current Research and Prospect

Copper is an essential trace metal for normal cellular functions; a lack of copper is reported to impair the function of important copper-binding enzymes, while excess copper could lead to cell death. Numerous studies have shown an association between dietary copper consumption or plasma copper levels and the incidence of diabetes/diabetes complications. And experimental studies have revealed multiple signaling pathways that are triggered by copper shortages or copper overload in diabetic conditions. Moreover, studies show that treated with copper chelators improve vascular function, maintain copper homeostasis, inhibit cuproptosis, and reduce cell toxicity, thereby alleviating diabetic neuropathy, retinopathy, nephropathy, and cardiomyopathy. However, the mechanisms reported in these studies are inconsistent or even contradictory. This review summarizes the precise and tight regulation of copper homeostasis processes, and discusses the latest progress in the association of diabetes and dietary copper/plasma copper. Further, the study pays close attention to the therapeutic potential of copper chelators and copper in diabetes and its complications, and hopes to provide new insight for the treatment of diabetes.

Relationship between Copper, Zinc, and Copper-to-Zinc Ratio in Hair and Severity of Coronary Artery Disease according to the SYNTAX Score

Coronary artery disease (CAD) continues to be a foremost contributor to global mortality, and the quest for modifiable risk factors could improve prophylactic strategies. Recent studies suggest a significant role of zinc (Zn) and copper (Cu) deficiency in atheromatous plaque formation. Furthermore, hair was previously described as a valuable source of information on elemental burden during the 6-8 week period before sampling. The aim of this study was to investigate the possibility of correlation between the extent of CAD evaluated with the SYNergy Between PCI With TAXUS and the Cardiac Surgery (SYNTAX) score with Cu and Zn content in hair samples, as well as with the Cu/Zn ratio in a cohort of 130 patients. Our findings describe a statistically significant inverse correlation between Cu content and the Cu/Zn ratio in hair samples and the extent of CAD. In contrast, no significant correlation was found between Zn content and the extent of CAD. Considering the scarcity of existing data on the subject, the analysis of hair samples could yield a novel insight into elemental deficiencies and their potential influence on CAD extent.

A machine learning-based diagnosis modelling of type 2 diabetes mellitus with environmental metal exposure

BACKGROUND AND OBJECTIVE

Increasing and compelling evidence has been proved that urinary and dietary metal exposure are underappreciated but potentially modifiable biomarkers for type 2 diabetes mellitus (T2DM). The aims of this study were (1) to identify the key potential biomarkers which contributed to T2DM with effective and parsimonious features and (2) to assess the utility of baseline variables and metal exposure in the diagnosis of T2DM.

METHODS

Based on the National Health and Nutrition Examination Survey (NHANES), we selected 9822 screening records with 82 significant variables covering demographics, lifestyle, anthropometric measures, diet and metal exposure for this study. Combining extreme gradient boosting (XGBoost), random forest and light gradient boosting machine (lightGBM), a soft voting ensemble model was proposed to measure the importance of 82 features. With this soft voting ensemble model and variance inflation factor (VIF), strong multicollinear features with low importance scores were further removed from candidate biomarkers. Then, a soft voting ensemble classifier was adopted to demonstrate the efficiency of the proposed feature selection method.

RESULTS

With the novel feature selection method, 12 baseline variables and 3 metal variables were selected to detect patients at risk for T2DM in our study. For metal variables, the dietary copper (Cu), urinary cadmium (Cd) and urinary mercury (Hg) metals were selected as the most remarkable metal exposure and the corresponding P-values were all less than 0.05. In a classification model of T2DM with 12 baseline biomarkers, the addition of 3 metal exposure improved the classification accuracy of T2DM from a traditional area under the curve (AUC) 0.792 of the receiver operating characteristic (ROC) to an AUC 0.847.

CONCLUSIONS

This was the first demonstration of T2DM classification with machine learning under urinary and dietary metal exposure. Improved prediction precision illustrated the effectiveness of the proposed machine learning-based diagnosis model facilitated lifestyle/dietary intervention for T2DM prevention.

Single and Combined Associations of Plasma and Urine Essential Trace Elements (Zn, Cu, Se, and Mn) with Cardiovascular Risk Factors in a Mediterranean Population

Trace elements are micronutrients that are required in very small quantities through diet but are crucial for the prevention of acute and chronic diseases. Despite the fact that initial studies demonstrated inverse associations between some of the most important essential trace elements (Zn, Cu, Se, and Mn) and cardiovascular disease, several recent studies have reported a direct association with cardiovascular risk factors due to the fact that these elements can act as both antioxidants and pro-oxidants, depending on several factors. This study aims to investigate the association between plasma and urine concentrations of trace elements and cardiovascular risk factors in a general population from the Mediterranean region, including 484 men and women aged 18−80 years and considering trace elements individually and as joint exposure. Zn, Cu, Se, and Mn were determined in plasma and urine using an inductively coupled plasma mass spectrometer (ICP-MS). Single and combined analysis of trace elements with plasma lipid, blood pressure, diabetes, and anthropometric variables was undertaken. Principal component analysis, quantile-based g-computation, and calculation of trace element risk scores (TERS) were used for the combined analyses. Models were adjusted for covariates. In single trace element models, we found statistically significant associations between plasma Se and increased total cholesterol and systolic blood pressure; plasma Cu and increased triglycerides and body mass index; and urine Zn and increased glucose. Moreover, in the joint exposure analysis using quantile g-computation and TERS, the combined plasma levels of Zn, Cu, Se (directly), and Mn (inversely) were strongly associated with hypercholesterolemia (OR: 2.03; 95%CI: 1.37−2.99; p < 0.001 per quartile increase in the g-computation approach). The analysis of urine mixtures revealed a significant relationship with both fasting glucose and diabetes (OR: 1.91; 95%CI: 1.01−3.04; p = 0.046). In conclusion, in this Mediterranean population, the combined effect of higher plasma trace element levels (primarily Se, Cu, and Zn) was directly associated with elevated plasma lipids, whereas the mixture effect in urine was primarily associated with plasma glucose. Both parameters are relevant cardiovascular risk factors, and increased trace element exposures should be considered with caution.

A proposed method for defining the required fortification level of micronutrients in foods: An example using iron

In 2006, the WHO published a framework for calculating the desired level of fortification of any micronutrient in any staple food vehicle, to reduce micronutrient malnutrition. This framework set the target median nutrient intake, of the population consuming the fortified food, at the 97.5th percentile of their nutrient requirement distribution; the Probability of Inadequacy (PIA) of the nutrient would then be 2.5%. We argue here that the targeted median nutrient intake should be at Estimated Average Requirement (50^th percentile), since the intake distribution will then overlap the requirement distribution in a population that is in homeostasis, resulting in a PIA of 50%. It is also important to recognize that setting the target PIA at 2.5% may put a sizable proportion at risk of adverse consequences associated with exceeding the tolerable upper limit (TUL) of intake. This is a critical departure from the WHO framework. For a population with different age- and sex-groups, the pragmatic way to fix the fortification level for a staple food vehicle is by achieving a target PIA of 50% in the most deprived age- or sex-group of that population, subject to the condition that only a very small proportion of intakes exceed the TUL. The methods described here will aid precision in public health nutrition, to pragmatically determine the precise fortification level of a nutrient in a food vehicle, while balancing risks of inadequacy and excess intake.