Relationship between urinary heavy metals with metabolic syndrome and its components in population from Hoveyzeh cohort study: A case-control study in Iran

The effect of consuming bread contaminated with heavy metals on cardiovascular disease and calculating its risk assessment

Heavy metals (HMs) may cause the generation of reactive oxygen species (ROS), which results in oxidative stress and eventually leads to an increase in cardiovascular diseases (CVD). The Hoveyzeh Cohort Study Center provided clinical data for cardiovascular cases. The collection of samples was done randomly. The association between CVD and HMs has been evaluated utilizing seven machine-learning techniques. The results showed that the effect coefficient (β) of bread consumption in the incidence of heart disease is 4.6908 × 10-02. Consumption of bread contaminated with chromium (P value < 0.0217), cadmium (P value < 2.95 × 10-6) and arsenic (P value < 1.15 × 10-07) is significantly related to cardiovascular incidence. Each unit of bread consumption increases As intake by 0.494 (β = 4.940 × 10-01) and CVD incidence by 11.9% (OR = 1.1190). Bread consumption increases Cd intake by 0.479 (β = 4.799 × 10-1) and cardiovascular disease incidence by 11.97% (OR = 1.1197) per unit. The findings indicated that bread intake in the study region is not correlated with non-carcinogenic or carcinogenic risks, since the cancer risk and incremental lifetime cancer risk for both groups were below 1*10^-6. In the present investigation, bread had HMs included As, Cd, Cr, and Pb higher than the limit declared by WHO. The results of the present study showed that bread is a mediating factor (between HMs and the incidence of CVD).

Biochemical study of the risk of diabetes, prediabetic and insulin resistance in car painters and its association with mercury exposure: a retrospective case-control study

Purpose

There is controversy about the effect of mercury (Hg) exposure on developing diabetes and insulin resistance. This study aimed to assess the risk of diabetes and insulin resistance in car painters using biochemical markers and serum Hg levels.

Methods

A retrospective case-control study involving 210 male participants aged between 25 and 50 years. The participants were divided into two groups: Car painters for at least one year and healthy people who had not worked as car painters and had no health concerns or chronic diseases.

Results

The serum levels of Hg, MDA (malondialdehyde), interleukin (IL)-1β, visfatin, fasting insulin, and fasting blood glucose (FBG) were evaluated. Serum Hg levels were significantly higher in car painters compared to the control group (19.00 ± 7.20 vs. 8.339 ± 3.916 μg/L, P-value < 0.001). Serum levels of visfatin, MDA, insulin, FBG, and IL-1β were significantly higher in the car painter compared to the control (P-value < 0.001). There was a significantly higher proportion of people with diabetes in car painters compared to control (8.6% vs. 0%) and higher prediabetic (30.5% vs. 13.3%, P-value < 0.001). In car painter workers, levels of Hg were significantly higher in DM compared to prediabetic and normoglycemic car painter workers (27.01 ± 1.59, 23.98 ± 4.31, and 15.39 ± 6.41 μg/mL, respectively, P-value < 0.001); additionally, levels of Hg were significantly higher car painter with insulin resistance compared to non-insulin resistance workers (21.18 ± 7.29 vs. 16.79 ± 16.7 μg/mL, P-value < 0.001).

Conclusions

Increased serum Hg in car painters increases the risk of insulin resistance and diabetes/prediabetes status.

Particulate polycyclic aromatic hydrocarbons and metals, DNA methylation and DNA methyltransferase among middle-school students in China

The main components of particulate matter (PM) had been reported to change DNA methylation levels. However, the mixed effect of PM and its constituents on DNA methylation and the underlying mechanism in children has not been well characterized. To investigate the association between single or mixture exposures and global DNA methylation or DNA methyltransferases (DNMTs), 273 children were recruited (110 in low-exposed area and 163 in high-exposed area) in China. Serum benzo[a]pyridin-7,8-dihydroglycol-9, 10-epoxide (BPDE)-albumin adduct and urinary metals were determined as exposure markers. The global DNA methylation (% 5mC) and the mRNA expression of DNMT1, and DNMT3A were measured. The linear regression, quantile-based g-computation (QGC), and mediation analyses were performed to investigate the effects of individual and mixture exposure. We found that significantly lower levels of % 5mC (P < 0.001) and the mRNA expression of DNMT3A in high-PM exposed group (P = 0.031). After adjustment for age, gender, BMI z-score, detecting status of urinary cotinine, serum folate, and white blood cells, urinary arsenic (As) was negatively correlated with the % 5mC. One IQR increase in urinary As (19.97 μmol/mol creatinine) was associated with a 11.06 % decrease in % 5mC (P = 0.026). Serum BPDE-albumin adduct and urinary cadmium (Cd) were negatively correlated with the levels of DNMT1 and DNMT3A (P < 0.05). Mixture exposure was negatively associated with expression of DNMT3A in QGC analysis (β: -0.19, P < 0.001). Mixture exposure was significantly associated with decreased % 5mC in the children with non-detected cotinine or normal serum folate (P < 0.05), which the most contributors were PAHs and As. The mediated effect of hypomethylation through DNMT1 or DNMT3A pathway was not observed. Our findings indicated that individual and mixture exposure PAHs and metal components had negative associations with global DNA methylation and decreased DNMT3A expression significantly in school-age individuals.

Relationship between heavy metal concentrations and Chronic kidney disease in population of Hoveyzeh cohort study: A cross-sectional study in Iran

BACKGROUND

Chronic kidney disease (CKD) is a multifactorial disease whose prevalence is increasing worldwide. CKD affects 700 million to 1 billion people worldwide, with a prevalence of 9.1% to 13.4%. In Iran, the reported prevalence of CKD is 15.14%, even higher than the global prevalence. Some studies introduced heavy metals as possible risk factors of CKD. We conducted the first study in Iran to examine the relationship between 10 selected urinary heavy metals and CKD in the Hovayzeh cohort study population.

METHODS

In this cross-sectional study, urine samples were collected from two groups of ca ses (suffering from CKD) and controls (without CKD) with equal size (47 people each). Analysis of the 10 sellected heavy metals in the samples was conducted using inductively coupled plasma emission spectroscopy. Basic Information was obtained from the Howayizeh Cohort Study Center. The data was analyzed using SPSS-26 and Excel-2016 software.

RESULTS

There were no significant differences between urinary heavy metal concentrations of case and control groups (P < 0.05). While, the concentration of As, Cr, Cu, Mn, and Ni exceeded the reference limits of Germany, Canada, England, and Belgium. Se and Cd also surpassed the reference limits of England. After adjusting for confounding variables for each μg/l increase in urinary Cd, Ni, Pb, and Se the OR of CKD increased by 20.2%, 4.8%, 3.1%, and 2.6%, respectively. Although, these relationships were not statistically significant. In addition, two groups of heavy metals had a positive and significant correlation: (1) Se, Zn, As, Cu, and Cr; (2) Pb, Cd, and As; and (3) Cd and Ni.

CONCLUSION

we found no significant relationship between urinary heavy metal and CKD. However, there was significant positive correlation in some of urinary heavy metals may indicate their shared resources. Furthermore, the concentration of most heavy metals in the urine of the participants was higher than the reference limits of these metals in the urine of healthy people from other countries. Thus, the elevated levels of these metals could still pose a risk to human health. Therefore, it is necessary to conduct prospective studies with a larger sample size in this area.

The relationship between heavy metals and metabolic syndrome using machine learning

Background

Exposure to high levels of heavy metals has been widely recognized as an important risk factor for metabolic syndrome (MetS). The main purpose of this study is to assess the associations between the level of heavy metal exposure and Mets using machine learning (ML) method.

Methods

The data used in this study are from the national health and nutrition examination survey 2003-2018. According to the demographic information and heavy metal exposure level of participants, a total of 22 variables were included. Lasso was used to screen out the key variables, and 9 commonly used ML models were selected to establish the associations with the 5-fold cross validation method. Finally, we choose the SHapley Additive exPlanations (SHAP) method to explain the prediction results of Adaboost model.

Results

11,667 eligible individuals were randomly divided into two groups to train and verify the prediction model. Through lasso, characteristic variables were selected from 24 variables as predictors. The AUC (area under curve) of the models selected in this study were all greater than 0.7, and AdaBoost was the best model. The AUC value of AdaBoost was 0.807, the accuracy was 0.720, and the sensitivity was 0.792. It is noteworthy that higher levels of cadmium, body mass index, cesium, being female, and increasing age were associated with an increased probability of MetS. Conversely, lower levels of cobalt and molybdenum were linked to a decrease in the estimated probability of MetS.

Conclusion

Our study highlights the AdaBoost model proved to be highly effective, precise, and resilient in detecting a correlation between exposure to heavy metals and MetS. Through the use of interpretable methods, we identified cadmium, molybdenum, cobalt, cesium, uranium, and barium as prominent contributors within the predictive model.

Effect of exposures to multiple metals on blood pressure and hypertension in the elderly: a community-based study

A chronic disease, hypertension (HTN) is prevalent among the elderly. Exploring the factors that influence HTN and blood pressure (BP) changes is of great public health significance. However, mixed exposure to multiple serum metals has had less research on the effects on BP and HTN for the elderly. From April to August 2019, 2372 people participated in the community physical examination program for the elderly in Tongling City, Anhui Province. We measured BP and serum levels of 10 metals and collected basic demographic information. We analyzed the relationship between metal levels and changes in BP and HTN by the least absolute shrinkage and selection operator regression, Bayesian kernel machine regression model, and generalized linear model. In multiple models, lead (Pb) and cadmium (Cd) were still significantly associated with HTN occurrence after adjusting for potential confounders (Pb: ORquartile 4 VS quartile 1 = 1.20, 95% CI 1.01-1.43; Cd: ORquartile 4 VS quartile 1 = 1.37, 95% CI 1.16-1.62). In the male subgroup, results were similar to those of the general population. In the female group, Cd was positively correlated with HTN and systolic blood pressure, while Pb was not. According to this study, Pb and Cd were correlated with BP and HTN positively, and there was a certain joint effect. To some extent, our findings provide clues for the prevention of hypertension in the elderly.

Heavy metal exposure linked to metabolic syndrome in Korean male firefighters: FRESH cohort cross-sectional analysis

This study aimed to identify the relationship between blood lead and Cadmium (Cd) concentrations and metabolic syndromes (MetS), including its components (central obesity, hypertriglyceridemia, low high-density lioioritein, hypertension, and hyperglycemia) among Korean firefighters. A total of 965 firefighters of the Enhancement of Safety and Health cohort were analyzed in this study. MetS was defined according to the 2005 revised National Cholesterol Education Program-Adult Treatment Panel III criteria and the Korean Society for the Study of Obesity criteria for waist circumference. The collected data were analyzed using a logistic regression model. Of the 965 participants, 190 (19.7%) had MetS. After adjusting for age, body mass index, smoking, drinking, exercise, shift duty, and main duty position, the Cd level was significantly associated with an increased risk of MetS in the Korean firefighter population (odds ratio [OR] = 1.62, 95% confidence interval [CI] 1.07, 2.46). This association was significant among non-smokers and ex-smokers (OR = 1.58, 95% CI 1.03, 2.43), non-drinkers and ex-drinkers (OR = 1.77, 95% CI 1.06, 2.94), firefighters aged 40 year or older (OR = 1.77, 95% CI 1.10, 2.86), and office administrators (OR = 3.85, 95% CI 1.42, 10.39). This outcome suggests that exposure to Cd is likely to increase risk of MetS among firefighters.

Association between Heavy Metals, Metalloids and Metabolic Syndrome: New Insights and Approaches

Metabolic syndrome (MetS) is an important public health issue that affects millions of people around the world and is growing to pandemic-like proportions. This syndrome is defined by the World Health Organization (WHO) as a pathologic condition characterized by abdominal obesity, insulin resistance, hypertension, and hyperlipidemia. Moreover, the etiology of MetS is multifactorial, involving many environmental factors, including toxicant exposures. Several studies have associated MetS with heavy metals exposure, which is the focus of this review. Environmental and/or occupational exposure to heavy metals are a major risk, contributing to the development of chronic diseases. Of particular note, toxic metals such as mercury, lead, and cadmium may contribute to the development of MetS by altering oxidative stress, IL-6 signaling, apoptosis, altered lipoprotein metabolism, fluid shear stress and atherosclerosis, and other mechanisms. In this review, we discuss the known and potential roles of heavy metals in MetS etiology as well as potential targeted pathways that are associated with MetS. Furthermore, we describe how new approaches involving proteomic and transcriptome analysis, as well as bioinformatic tools, may help bring about an understanding of the involvement of heavy metals and metalloids in MetS.

The mediating role of telomere length in multi-pollutant exposure associated with metabolic syndrome in adults

Metabolic syndrome is a chronic and complex disease characterized by environmental and genetic factors. However, the underlying mechanisms remain unclear. This study assessed the relationship between exposure to a mixture of environmental chemicals and metabolic syndrome (MetS) and further examined whether telomere length (TL) moderated these relationships. A total of 1265 adults aged > 20 years participated in the study. Data on multiple pollutants (polycyclic aromatic hydrocarbons, phthalates, and metals), MetS, leukocyte telomere length (LTL), and confounders were provided in the 2001-2002 National Health and Nutrition Examination Survey. The correlations between multi-pollutant exposure, TL, and MetS in the males and females were separately assessed using principal component analysis (PCA), logistic and extended linear regression models, Bayesian kernel machine regression (BKMR), and mediation analysis. Four factors were generated in PCA that accounted for 76.2% and 77.5% of the total environmental pollutants in males and females, respectively. The highest quantiles of PC2 and PC4 were associated with the risk of TL shortening (P < 0.05). We observed that the relationship between PC2, PC4, and MetS risk was significant in the participants with median TL levels (P for trend = 0.04 for PC2, and P for trend = 0.01 for PC4). Furthermore, mediation analysis revealed that TL could explain 26.1% and 17.1% of the effects of PC2 and PC4 associated with MetS in males, respectively. The results of BKMR model revealed that these associations were mainly driven by 1-PYE (cPIP = 0.65) and Cd (cPIP = 0.29) in PC2. Meanwhile, TL could explain 17.7% of the mediation effects of PC2 associated with MetS in the females. However, the relationships between pollutants and MetS were sparse and inconsistent in the females. Our findings suggest that the effects of the risk of MetS associated with mixed exposure to multiple pollutants are mediated by TL, and this mediating effect in the males is more pronounced than that in the females.

Examining dyslipidaemia, metabolic syndrome and liver enzyme levels in patients with prediabetes and type 2 diabetes in population from Hoveyzeh cohort study: A case-control study in Iran

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is among the world's top 10 leading causes of death. Additionally, prediabetes is a major risk factor for diabetes. Identifying diabetes co-occurring disorders can aid in reducing adverse effects and facilitating early detection. In this study, we evaluated dyslipidaemia, metabolic syndrome (MetS), and liver enzyme levels in pre-diabetic and T2DM patients in the Persian cohort compared to a control group.

MATERIALS AND METHODS

In this cross-sectional study, 2259 pre-diabetes, 1664 T2DM and 5840 controls (35-70 years) who were selected from the Hoveyzeh cohort centre were examined. Body mass index, blood pressure, fasting blood glucose (FBG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG) and liver enzymes: γ-glutamyltransferase (GGT), alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were determined using the standard protocols. MetS subjects were also identified based on the National Cholesterol Education Program guidelines.

RESULTS

Prediabetes and T2MD were closely correlated with the lipid profile, MetS, and liver enzymes (ALT, GGT, ALT/AST). MetS increases the risk of T2DM by 12.45 [95% CI: 10.88-14.24] fold, while an increase in ALT/AST ratio increases the risk of T2DM by 3.68 [95% CI: 3.159-4.154] fold. ROC curve analysis also revealed the diagnostic roles of GGT, ALT, AST and the ALT/AST ratio among pre-diabetics, diabetics and the control group. The GGT level corresponds to the highest AUCs (0.685) with the highest sensitivity (70.25%).

CONCLUSIONS

Our results indicated a significant increase in liver enzymes, lipid profile and MetS status in both pre-diabetic and T2MD subjects, with the differences being more pronounced in diabetic individuals. Consequently, on the one hand, these variables may be considered predictive risk factors for diabetes, and on the other hand, they may be used as diagnostic factors. In order to confirm the clinical applications of these variables, additional research is required.

Independent, combine and interactive effects of heavy metal exposure on dyslipidemia biomarkers: A cross-sectional study in northeastern China

Dyslipidemia is a common disease in the older population and represents a considerable disease burden worldwide. Epidemiological and experimental studies have indicated associations between heavy metal exposure and dyslipidemia; few studies have investigated the effects of heavy metal mixture and interactions between metals on dyslipidemia. We recruited 1121 participants living in heavy metal-contaminated and control areas in northeast China from a cross-sectional survey (2017-2019). Urinary metals including chromium (Cr), cadmium (Cd), lead (Pb), and manganese (Mn) and dyslipidemia biomarkers, namely triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) levels, were measured. The generalized linear model (GLM) was used to explore the association of a single metal with dyslipidemia biomarkers. Bayesian kernel machine regression (BKMR) and multivariable linear regression were performed to explore the overall effect of metal mixture and the interaction between metals on dyslipidemia. Heavy metal mixture was positively associated with LDL-C, TC, and TG and negatively with HDL-C. In multivariable linear regression, Pb and Cd exhibited a synergistic association with LDL-C in the participants without hyperlipemia. Mn-Cd and Pb-Cr also showed a synergistic association with increasing the level of LDL-C in subjects without hyperlipemia. Cd-Cr showed an antagonistic association with HDL-C, respectively. Cr-Mn exhibited an antagonistic association with decreased HDL-C and TG levels. No significant interaction was noted among the three metals. Our study indicated that exposure to heavy metals is associated with dyslipidemia biomarkers and the presence of potential synergistic or antagonistic interactions between the heavy metals.

A Longitudinal Study of Exposure to Manganese and Incidence of Metabolic Syndrome

The association between manganese (Mn) and metabolic syndrome (MetS) is unclear, and no prior study has studied this association longitudinally. The aim of this study was to assess longitudinal associations of Mn exposure with MetS and metabolic outcomes. We used data from the San Luis Valley Diabetes Study (SLVDS), a prospective cohort from rural Colorado with data collected from 1984−1998 (n = 1478). Urinary Mn was measured at baseline (range = 0.20−42.5 µg/L). We assessed the shape of the cross-sectional association between Mn and MetS accounting for effect modification by other metals at baseline using Bayesian kernel machine regression. We assessed longitudinal associations between baseline quartiles of Mn and incident MetS using Fine and Gray competing risks regression models (competing risk = mortality) and between quartiles of Mn and metabolic outcomes using linear mixed effects models. We did not observe evidence that quartiles of Mn were associated with incident MetS (p-value for trend = 0.52). Quartiles of Mn were significantly associated with lower fasting glucose (p-value for trend < 0.01). Lead was found to be a possible effect modifier of the association between Mn and incident MetS. Mn was associated with lower fasting glucose in this rural population. Our results support a possible beneficial effect of Mn on diabetic markers.

Manganese Exposure and Metabolic Syndrome: A Systematic Review and Meta-Analysis

Manganese (Mn) is an essential element acting as a co-factor of superoxide dismutase, and it is potentially beneficial for cardiometabolic health by reducing oxidative stress. Although some studies have examined the relationship between Mn and metabolic syndrome (MetS), no systematic review and meta-analysis has been presented to summarize the evidence. Therefore, the present review examined the association between dietary and environmental Mn exposure, and MetS risk. A total of nine cross-sectional studies and three case-control studies were included, which assessed Mn from diet, serum, urine, and whole blood. The association of the highest Mn level from diet (three studies, odds ratio (OR): 0.83, 95% confidence interval (C.I.) = 0.57, 1.21), serum (two studies, OR: 0.87, 95% C.I. = 0.66, 1.14), urine (two studies, OR: 0.84, 95% C.I. = 0.59, 1.19), and whole blood (two studies, OR: 0.92, 95% C.I. = 0.53, 1.60) were insignificant, but some included studies have suggested a non-linear relationship of urinary and blood Mn with MetS, and higher dietary Mn may associate with a lower MetS risk in some of the included studies. While more evidence from prospective cohorts is needed, future studies should use novel statistical approaches to evaluate relative contribution of Mn on MetS risk along with other inter-related exposures.

Association between heavy metals and metabolic syndrome in drinking water and surface soil: case-control study in Iran

Although obesity is a major risk factor for metabolic syndrome (MetS), not all obese people develop MetS that is directly related to obesity. This suggests that the risk of MetS is influenced by other genetic or environmental agents such as heavy metals. The aim of this study was to investigate the relationship between heavy metals in drinking water and surface soil, and its relationship with the incidence of MetS. To determine the sampling points of drinking water and surface soil, from the location of 150 people selected for inclusion in the study, 16 points were selected randomly for heavy metal concentration analysis. Results were indicated that mean concentrations of V, Mn, Ni, As, Cd, and Sr in drinking water of MetS group were higher than control group. The concentration of heavy metals in drinking water, except for Mn and Sr, did not show a significant difference between case and control groups. The results of this study showed that concentration of heavy metals in drinking water and surface soil was positively associated with the incidence of MetS.

Mercury Exposure and Risk of Type 2 Diabetes: A Systematic Review and Meta-Analysis

METHODS

Scopus and PubMed databases were systematically searched from their inception to November 2021 to obtain pertinent studies. Standardized mean differences (SMDs) with corresponding 95% confidence intervals (CIs) were calculated to evaluate the difference in Hg levels between people with and without T2DM. The association of the Hg exposure with T2DM was assessed using a random-effects model by pooling the odds ratios (ORs) and 95% CIs.

RESULTS

A total of 17 studies, with 42,917 participants, aged ≥18 years, were analyzed. Overall, Hg levels were significantly higher in T2DM patients compared with non-T2DM controls (SMD = 1.07; 95%CI = 0.59 to 1.55, P ≤ 0.001), with significant heterogeneity across studies (I² = 96.1%; P=≤0.001). No significant association was found between Hg exposure and risk of T2DM in the overall analysis and subgroup analysis based on the source of sample and study design. However, higher exposure to Hg was related to reduced risk of T2DM in men (OR = 0.71; 95%CI = 0.57 to 0.88), but not in women. No significant evidence for publication bias was detected.

CONCLUSIONS

Although the Hg level in T2DM is significantly higher than that of nondiabetics, there was no association between Hg exposure and the overall risk of T2DM. Nevertheless, our study shows that higher exposure to Hg might reduce the risk of T2DM in men.