Dietary copper and selenium are associated with insulin resistance in overweight and obese Malaysian adults

Molecular Aspects in the Development of Type 2 Diabetes and Possible Preventive and Complementary Therapies

The incidence of diabetes, including type 2 diabetes (T2DM), is increasing sharply worldwide. To reverse this, more effective approaches in prevention and treatment are needed. In our review, we sought to summarize normal insulin action and the pathways that primarily influence the development of T2DM. Normal insulin action involves mitogenic and metabolic pathways, as both are important in normal metabolic processes, regeneration, etc. However, through excess energy, both can be hyperactive or attenuated/inactive leading to disturbances in the cellular and systemic regulation with the consequence of cellular stress and systemic inflammation. In this review, we detailed the beneficial molecular changes caused by some important components of nutrition and by exercise, which act in the same molecular targets as the developed drugs, and can revert the damaged pathways. Moreover, these induce entire networks of regulatory mechanisms and proteins to restore unbalanced homeostasis, proving their effectiveness as preventive and complementary therapies. These are the main steps for success in prevention and treatment of developed diseases to rid the body of excess energy, both from stored fats and from overnutrition, while facilitating fat burning with adequate, regular exercise in healthy people, and together with necessary drug treatment as required in patients with insulin resistance and T2DM.

Serum copper and obesity among healthy adults in the National Health and Nutrition Examination Survey

BACKGROUND

Copper (Cu) homeostasis are important processes in the cause of metabolic diseases, but the association between Cu and obesity remains unclear.

METHODS

Participants were drawn from the 2011-2016 National Health and Nutrition Examination Survey (NHANES). Weighted logistic regression assessed the associations of serum Cu concentrations (tertiles) with obesity and central obesity in individuals without comorbidities. Obesity was defined as a BMI ≥30.0 kg/m2, and central obesity was defined as a waist circumference ≥80 cm for women and ≥95 cm for men.

RESULTS

This cross-sectional study included 1,665 adults without comorbidities, representing 24,744,034 people (mean age 35.1 years, 48.5% female). High serum Cu levels (tertile 3: ≥19.19 μmol/L) were associated with higher odds of obesity (adjusted odds ratio [OR]: 4.48, 95% CI[confidence interval]: 2.44-8.32) and central obesity (OR: 2.36, 95% CI: 1.19-4.66) compared to low serum Cu levels (tertile 1: ≤15.64 μmol/L). The dose-response curve showed a nonlinear association between Cu levels and obesity (P-nonlinear = 0.02) and a linear association with central obesity (P-nonlinear = 0.21).

CONCLUSION

This study suggests that higher serum Cu levels are associated with increased odds of obesity in healthy American adults.

Overweight, Obesity, Hypertriglyceridemia, and Insulin Resistance Are Positively Associated with High Serum Copper Levels in Mexican Adults

Recently, the role of trace elements in the pathophysiology of obesity, insulin resistance (IR), and metabolic diseases has been explored. In this cross-sectional study, we aimed to assess the association of overweight, obesity, and cardiometabolic traits with serum copper (Cu) levels in 346 Mexican adults. Serum Cu level was measured by inductively coupled plasma mass spectrometry (ICP-MS). Anthropometrical data were collected, and biochemical parameters were measured. The triglyceride-glucose (TyG) index was used as a surrogate marker to evaluate IR. Overweight and obesity status was positively associated with the serum Cu level (β = 19.434 ± 7.309, p = 0.008). Serum Cu level was observed to have a positive association with serum triglycerides level (β = 0.160 ± 0.045, p < 0.001) and TyG (β = 0.001 ± 0.001, p < 0.001). Additionally, high serum Cu level was positively associated with overweight and obesity status (odds ratio [OR] = 1.9, 95% confidence interval [95% CI] 1.1-3.4, p = 0.014), hypertriglyceridemia (OR = 3.0, 95% CI 1.7-5.3, p < 0.001), and IR (OR = 2.6, 95% CI 1.4-4.6, p = 0.001). In conclusion, our results suggest that overweight, obesity, hypertriglyceridemia, and IR are positively associated with serum Cu levels in Mexican adults.

Association of multiple serum minerals and vitamins with metabolic dysfunction-associated fatty liver disease in US adults: National Health and Nutrition Examination Survey 2017-2018

Background

Despite the rapid increase in the global prevalence of Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD), there are no approved therapeutic drugs for MAFLD yet. Nutrient supplementation might mitigate the risk of MAFLD. It is more typical for individuals to consume multiple nutrients simultaneously. However, the studies exploring the combined effects of multiple nutrients on MAFLD are limited. This study aimed to investigate the relationship between both individual nutrients and their combined influence on the risk of MAFLD.

Methods

Data were obtained from National Health and Nutrition Examination Survey (NHANES), and 18 types of nutrients were considered in this study. Logistic regression analysis was performed to evaluate the correlation between single nutrients and the risk of MAFLD. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was performed to pinpoint the most relevant nutrient associated with the risk of MAFLD. Subsequently, both Weighted Quantile Sum (WQS) regression and Quantile g-computation (Qgcomp) were used to assess the combined effects of multiple nutrients on the risk of MAFLD.

Results

A total of 3,069 participants were included in this study. LASSO regression analysis showed that Se, α-tocopherol, and γ-tocopherol exhibited a positive association with the risk of MAFLD. In contrast, the serum levels of Co, P, α-cryptoxanthin, LZ, and trans-β-carotene were inversely associated with the prevalence of MAFLD. When Se and two types of vitamin E were excluded, the WQS index showed a significant inverse relationship between the remaining 15 nutrients and the risk of MAFLD; α-cryptoxanthin showed the most substantial contribution. Similarly, Qgcomp suggested that the combined effects of these 15 nutrients were associated with a lower risk of MAFLD, with α-cryptoxanthin possessing the most significant negative weights.

Conclusion

This study suggested that the complex nutrients with either a low proportion of Se, α-tocopherol, and γ-tocopherol or without them should be recommended for patients with MAFLD to reduce its risk.

Effects of Various Heavy Metal Exposures on Insulin Resistance in Non-diabetic Populations: Interpretability Analysis from Machine Learning Modeling Perspective

Increasing and compelling evidence has been proved that heavy metal exposure is involved in the development of insulin resistance (IR). We trained an interpretable predictive machine learning (ML) model for IR in the non-diabetic populations based on levels of heavy metal exposure. A total of 4354 participants from the NHANES (2003-2020) with complete information were randomly divided into a training set and a test set. Twelve ML algorithms, including random forest (RF), XGBoost (XGB), logistic regression (LR), GaussianNB (GNB), ridge regression (RR), support vector machine (SVM), multilayer perceptron (MLP), decision tree (DT), AdaBoost (AB), Gradient Boosting Decision Tree (GBDT), Voting Classifier (VC), and K-Nearest Neighbour (KNN), were constructed for IR prediction using the training set. Among these models, the RF algorithm had the best predictive performance, showing an accuracy of 80.14%, an AUC of 0.856, and an F1 score of 0.74 in the test set. We embedded three interpretable methods, the permutation feature importance analysis, partial dependence plot (PDP), and Shapley additive explanations (SHAP) in RF model for model interpretation. Urinary Ba, urinary Mo, blood Pb, and blood Cd levels were identified as the main influencers of IR. Within a specific range, urinary Ba (0.56-3.56 µg/L) and urinary Mo (1.06-20.25 µg/L) levels exhibited the most pronounced upwards trend with the risk of IR, while blood Pb (0.05-2.81 µg/dL) and blood Cd (0.24-0.65 µg/L) levels showed a declining trend with IR. The findings on the synergistic effects demonstrated that controlling urinary Ba levels might be more crucial for the management of IR. The SHAP decision plot offered personalized care for IR based on heavy metal control. In conclusion, by utilizing interpretable ML approaches, we emphasize the predictive value of heavy metals for IR, especially Ba, Mo, Pb, and Cd.

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.

The Role of Copper Intake in the Development and Management of Type 2 Diabetes: A Systematic Review

Diabetes mellitus is a worldwide public health issue with numerous complications. Several risk factors are associated with diabetes, mainly due to patients following an unhealthy lifestyle. Copper is a crucial trace element, with various physiological actions. Different intake levels of copper might contribute to diabetes development due to its dual action as both an anti- and pro-oxidant. Aim: Due to the inconclusive findings regarding the relationship between copper consumption and the management of diabetes, we decided to conduct this extensive systematic review. Up to this date, no similar study has been available in the literature. In this review, we used the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines. Relevant articles were identified by searching the electronic databases CINAHL, EMBASE and Medline from their respective index dates to September 2022 using keywords such as “Copper Intake” and “Type 2 Diabetes”. Any paper that has investigated copper exposure through supplementation or any other method that indicates copper intake in human subjects with type 2 diabetes and measures at least one of the outcomes of interest related to diabetes was included in this review. This review is comprised of 4 cross-sectional studies, 3 cohort studies, 2 RCTs, and 2 interventional studies. Two cohort studies found positive associations between copper intake and the risk of developing T2DM, while no significant association was found in the third study. Regarding diabetes outcomes in the four cross-sectional studies, two found inverse associations, one found a positive relationship, and one found no significant association. In interventional studies, all studies found a protective effect of copper, including the RCT, while one found no significant association. The results are inconsistent concerning the association between copper consumption and the likelihood of developing diabetes are inconsistent. Individuals should receive an adequate dietary amount of copper that is within the RDA levels (900 µg/day) to avoid copper deficiency or toxicity. Further studies, especially RCTs, are strongly needed to enable researchers to elucidate more robust conclusions regarding this association.

Evaluation of the Effect of Different Cooking Methods on the Heavy Metal Levels in Crayfish Muscle

The current study investigated the effects of various cooking styles (boiling, frying, and steaming) and seasoning methods (home cooking and ready-to-eat commodity) on levels of nine heavy metals in the crayfish (Procambarus clarkii) muscle. The estimated daily intake (EDI), target hazard quotients (THQ), and target cancer risk (TCR) were used to assess the health risk in the crayfish muscle. The results showed that cooking processes significantly increased the concentration of Cu, which raises a potential risk for children (the THQ values > 1). The levels of toxic heavy metals in the ready-to-eat crayfish muscle were significantly higher than those in household cooking. Especially for As, the THQ values rose to 7.1 and 13.2 for adults and children respectively. Therefore, home cooking is safer than ready-to-eat crayfish, and children should consume crayfish within a limited range. The recommended consumption of the cooked abdominal muscle of crayfish should be 257 and 58 g/day, for children (16 kg) and adults (70 kg), respectively.

Development and Validation of an Insulin Resistance Model for a Population with Chronic Kidney Disease Using a Machine Learning Approach

Background: Chronic kidney disease (CKD) is a complex syndrome without a definitive treatment. For these patients, insulin resistance (IR) is associated with worse renal and patient outcomes. Until now, no predictive model using machine learning (ML) has been reported on IR in CKD patients. Methods: The CKD population studied was based on results from the National Health and Nutrition Examination Survey (NHANES) of the USA from 1999 to 2012. The homeostasis model assessment of IR (HOMA-IR) was used to assess insulin resistance. We began the model building process via the ML algorithm (random forest (RF), eXtreme Gradient Boosting (XGboost), logistic regression algorithms, and deep neural learning (DNN)). We compared different receiver operating characteristic (ROC) curves from different algorithms. Finally, we used SHAP values (SHapley Additive exPlanations) to explain how the different ML models worked. Results: In this study population, 71,916 participants were enrolled. Finally, we analyzed 1,229 of these participants. Their data were segregated into the IR group (HOMA IR > 3, n = 572) or non-IR group (HOMR IR ≤ 3, n = 657). In the validation group, RF had a higher accuracy (0.77), specificity (0.81), PPV (0.77), and NPV (0.77). In the test group, XGboost had a higher AUC of ROC (0.78). In addition, XGBoost also had a higher accuracy (0.7) and NPV (0.71). RF had a higher accuracy (0.7), specificity (0.78), and PPV (0.7). In the RF algorithm, the body mass index had a much larger impact on IR (0.1654), followed by triglyceride (0.0117), the daily calorie intake (0.0602), blood HDL value (0.0587), and age (0.0446). As for the SHAP value, in the RF algorithm, almost all features were well separated to show a positive or negative association with IR. Conclusion: This was the first study using ML to predict IR in patients with CKD. Our results showed that the RF algorithm had the best AUC of ROC and the best SHAP value differentiation. This was also the first study that included both macronutrients and micronutrients. We concluded that ML algorithms, particularly RF, can help determine risk factors and predict IR in patients with CKD.

Recent development in fluorescent probes for copper ion detection

Abstract:

Copper is the third most common heavy metal and an indispensable component of life. Variations of body copper levels, both structural and cellular, are related to a number of disorders; consequently, pathophysiological importance of copper ions demands the development of sensitivity and selective for detecting these organisms in biological systems. In recent years, the area of fluorescent sensors for detecting copper metal ions has seen revolutionary advances. Consequently, closely related fields have raised awareness of several diseases linked to copper fluctuations. Further developments in this field of analysis could pave the way for new and innovative treatments to combat these diseases. This review reports on recent progress in the advancement of three fields of fluorescent probes; chemodosimeters, near IR fluorescent probes, and ratiometric fluorescent probes. Methods used to develop these fluorescent probes and the mechanisms that govern their reaction to specific analytes and their applications in studying biological systems, are also given.

Associations of Dietary Antioxidants with Glycated Hemoglobin and Insulin Sensitivity in Adults with and without Type 1 Diabetes

Type 1 diabetes (T1D) has been associated with increased risks of atherosclerotic cardiovascular disease, and poor glycemic control and oxidative stress play a major role in its pathology. There is a lack of data on the role of dietary antioxidant micronutrients, including vitamins and trace elements, in glycemic control in T1D. The aim of this study is to examine associations of dietary intakes of micronutrients with glycemic status. We report data from a cross-sectional analysis from the coronary artery calcification in type 1 diabetes (CACTI) study (n = 1257; T1D: n = 568; nondiabetic controls: n = 689) collected between the years 2000 and 2002. Participants completed a validated food frequency questionnaire, a physical examination, and biochemical analyses. Linear regression was used to examine the associations of dietary antioxidant micronutrients with HbA1c and estimated insulin sensitivity (eIS) in models adjusted for relevant covariates and stratified by diabetes status. In adults with T1D, we observed higher dietary manganese intake associated with higher eIS in the model adjusted for age, sex, diabetes duration, and total calories. In nondiabetic controls, higher intake of manganese associated with lower HbA1c and higher eIS values that persisted in models adjusted for all relevant covariates. On the other hand, dietary copper revealed a positive association with HbA1c in models adjusted for all covariates, except BMI and plasma lipids. No associations were noted for vitamins C and E and dietary carotenoids in either group. These findings reveal dietary antioxidant micronutrients, especially trace elements such as copper and manganese deserve special attention in glycemic control in adults with T1D as well as in nondiabetic controls.This trial is register with NCT00005754.