Association Between Essential and Non-essential Metals, Body Composition, and Metabolic Syndrome in Adults

The association between heavy metal exposure and obesity: A systematic review and meta-analysis

Background

Obesity and metabolic syndrome are global health concerns associated with development of different types of diseases and serious health threats in the long term. Their metabolic imbalance can be attributable to inherited and environmental factors. As a considerable environmental agent, heavy metals exposure can predispose individuals to diseases like obesity. This systematic review and meta-analysis aimed to evaluate the association between heavy metals exposure and the risk of obesity.

Methods

PubMed/MEDLINE, EMBASE and Web of Science were systematically searched until December 17, 2022. Only observational studies that evaluated heavy metals exposure and obesity were included. Studies were excluded if they assessed maternal or prenatal exposure, the mixture of heavy metals and other chemicals, reported the association with overweight or other diseases, and undesirable study designs. The Joanna Briggs Institute checklist was used for quality assessment. The pooled adjusted odds ratio (aOR) and the pooled standardized mean difference (SMD) with their 95% confidence intervals (CIs) were calculated, respectively. The publication bias was evaluated using Egger's and Begg's tests.

Results

Twenty studies (n = 127755), four case-control and sixteen analytical cross-sectional studies, were included. Lead exposure was significantly associated with a lower risk of obesity (aOR: 0.705, 95% CI: 0.498-0.997), while mercury (aOR: 1.458, 95% CI: 1.048-2.031) and barium (aOR: 1.439, 95% CI: 1.142-1.813) exposure increased the risk of obesity. No significant publication bias was found and the studies had a low risk of bias.

Conclusion

Overall, lead exposure reduced obesity risk, while mercury and barium exposure raised it. Further large-scale observational studies are recommended to determine the roles of heavy metals in obesity.Study registration ID: CRD42023394865.

Supplementary information

The online version contains supplementary material available at 10.1007/s40200-023-01307-0.

Associations of essential metals with the risk of aortic arch calcification: a cross-sectional study in a mid-aged and older population of Shenzhen, China

Vascular calcification is a strong predictor of cardiovascular events. Essential metals play critical roles in maintaining human health. However, the association of essential metal levels with risk of aortic arch calcification (AoAC) remains unclear. We measured the plasma concentrations of nine essential metals in a cross-sectional population and evaluated their individual and combined effects on AoAC risk using multiple statistical methods. We also explored the mediating role of fasting glucose. In the logistic regression model, higher quartiles of magnesium and copper were associated with the decreased AoAC risk, while higher quartile of manganese was associated with higher AoAC risk. The least absolute shrinkage and selection operator penalized regression analysis identified magnesium, manganese, calcium, cobalt, and copper as key metals associated with AoAC risk. The weighted quantile sum regression suggested a combined effect of metal mixture. A linear and positive dose-response relationship was found between manganese and AoAC in males. Moreover, blood glucose might mediate a proportion of 9.38% of the association between manganese exposure and AoAC risk. In summary, five essential metal levels were associated with AoAC and showed combined effect. Fasting glucose might play a significant role in mediating manganese exposure-associated AoAC risk.

Associations of urinary zinc exposure with blood lipid profiles and dyslipidemia: Mediating effect of serum uric acid

The relationship between zinc (Zn) exposure and abnormal blood lipids including dyslipidemia is contentious. Serum uric acid (SUA) has been reported to be correlated to both Zn exposure and dyslipidemia. The underlying mechanisms of Zn exposure associated with blood lipids and the mediating effects of SUA remain unclear. Therefore, this study analyzed the data from Chinese 2110 adults (mean age: 59.0 years old) in rural areas across China to explore the associations of Zn exposure with blood lipid profiles and dyslipidemia, and to further estimate the mediating effects of SUA in these relationships. The study data showed that urinary Zn was associated with increased levels of blood lipid components triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C). Moreover, an increased risk of dyslipidemia was observed in the study participants who had higher urinary Zn levels. Compared with the first quartile, the fourth quartile of urinary Zn concentration corresponded to the increase of TG (β = 0.20, 95 % CI: 0.12, 0.28), LDL-C (β = 0.06, 95 % CI: 0.01, 0.10) and dyslipidemia risk (OR = 2.16, 95 % CI: 1.50, 3.10), respectively. Elevated urinary Zn was also associated with higher levels of SUA and hyperuricemia risk. The SUA levels were positively related to total cholesterol (TC), TG, LDL-C levels and dyslipidemia risk. Mediation analyses revealed that SUA mediated 31.75 %, 46.16 % and 19.25 % of the associations of urinary Zn with TG, LDL-C levels and dyslipidemia risk, respectively. The subgroup and sensitivity analyses confirmed the positive associations between urinary Zn and blood lipid profiles and the mediating effect of SUA. The national population-based study further enhanced our understanding of the associations between Zn exposure and blood lipid profiles and mediating effect of SUA among generally healthy, middle-aged, and elderly individuals.

Prenatal Metal Exposures and Child Social Responsiveness Scale Scores in 2 Prospective Studies

Background

Prenatal exposure to metals is hypothesized to be associated with child autism. We aim to investigate the joint and individual effects of prenatal exposure to urine metals including lead (Pb), mercury (Hg), manganese (Mn), and selenium (Se) on child Social Responsiveness Scale (SRS) scores.

Methods

We used data from 2 cohorts enriched for likelihood of autism spectrum disorder (ASD): Early Autism Risk Longitudinal Investigation (EARLI) and the Markers of Autism Risk in Babies-Learning Early Signs (MARBLES) studies. Metal concentrations were measured in urine collected during pregnancy. We used Bayesian Kernel Machine Regression and linear regression models to investigate both joint and independent associations of metals with SRS Z-scores in each cohort. We adjusted for maternal age at delivery, interpregnancy interval, maternal education, child race/ethnicity, child sex, and/or study site.

Results

The final analytic sample consisted of 251 mother-child pairs. When Pb, Hg, Se, and Mn were at their 75th percentiles, there was a 0.03 increase (95% credible interval [CI]: -0.11, 0.17) in EARLI and 0.07 decrease (95% CI: -0.29, 0.15) in MARBLES in childhood SRS Z-scores, compared to when all 4 metals were at their 50th percentiles. In both cohorts, increasing concentrations of Pb were associated with increasing values of SRS Z-scores, fixing the other metals to their 50th percentiles. However, all the 95% credible intervals contained the null.

Conclusions

There were no clear monotonic associations between the overall prenatal metal mixture in pregnancy and childhood SRS Z-scores at 36 months. There were also no clear associations between individual metals within this mixture and childhood SRS Z-scores at 36 months. The overall effects of the metal mixture and the individual effects of each metal within this mixture on offspring SRS Z-scores might be heterogeneous across child sex and cohort. Further studies with larger sample sizes are warranted.

Associations between plasma metal/metalloid mixtures and the risk of central obesity: A prospective cohort study of Chinese adults

Central obesity has increased rapidly over the past decade and posed a substantial disease burden worldwide. Exposure to metals/metalloids has been acknowledged to be involved in the development of central obesity through regulation of cortisol, insulin resistance, and glucocorticoid receptor reduction. Despite the importance, it is lack of prospective study which comprehensively evaluate the relations between multiple metals exposure and central obesity. We explored the prospective associations of plasma metal concentrations with central obesity in a prospective study of the Dongfeng-Tongji cohort. The present study included 2127 participants with a 6.87-year mean follow-up duration. We measured 23 plasma metal/metalloid concentrations at baseline. The associations between metals and incident central obesity were examined utilizing the Cox proportional hazard regression in single and multiple metals models. Additionally, we applied elastic net (ENET), Bayesian kernel machine regression (BKMR), plasma metal score (PMS), and quantile-based g-computation (Qgcomp) models to explore the joint associations of metal mixtures with central obesity. After adjusting potential confounders, we found significant associations of plasma manganese (Mn) and thallium (Tl) concentrations with a higher risk of central obesity, whereas plasma rubidium (Rb) concentration was associated with a lower risk of central obesity both in single and multiple metals models (all FDR <0.05). The ENET and Qqcomp models verified similar metals (Mn, Rb, and Tl) as important predictors for central obesity. The results of both BKMR model and PMS suggested cumulative exposure to metal mixtures was associated with a higher risk of central obesity. Our findings suggested that co-exposure to metals was associated with a higher risk of central obesity. This study expands our knowledge that the management of metals/metalloids exposure may be beneficial for the prevention of new-onset central obesity, which may subsequently alleviate the disease burden of late-life health outcomes.

Association between serum copper levels and muscle mass: results from NHANES 2011-2016

Copper is essential for various biological processes. However, excess copper has several adverse health effects. The effects of serum copper on muscle mass are poorly understood. This study aimed to investigate the association between serum copper levels and muscle mass in the US population. We utilized National Health and Nutrition Examination Survey (NHANES) data between 2011 and 2016 for analysis. Data on serum copper, muscle mass (measured using the appendicular skeletal muscle mass index (ASMI)), and covariates were extracted and analyzed. Weighted multivariate linear regression analyses and smooth curve fittings were performed to investigate the association between serum copper levels and ASMI. Subgroup analyses stratified according to age and sex were performed. In the presence of nonlinearity, threshold effect analysis was performed using a two-piecewise linear regression model. A total of 3860 participants were included in the final analysis. Serum copper levels were negatively associated with ASMI in the fully adjusted model. Furthermore, by comparing participants in the highest and lowest tertiles of serum copper levels, we found that the ASMI decreased by 0.292 kg/m2. In the sex-stratified subgroup analysis, we observed an inverse association between serum copper levels and the ASMI in both men and women. When stratified by age, the association remained significant among participants < 40 years of age, but not among those ≥ 40 years old. Smooth curve fitting revealed a nonlinear relationship between serum copper and ASMI, with an inflection point identified at 150.6 μg/dL. Our study revealed an inverse relationship between serum copper levels and muscle mass. This finding improves the current knowledge on the impact of serum copper on muscle loss and highlights the importance of serum copper homeostasis in muscle health.

Essential metals modified the effects of polycyclic aromatic hydrocarbons on the metabolic syndrome: Mediation effects of miRNA

Metabolic syndrome (MetS) prevalence has increased dramatically worldwide and has become a public health issue. Polycyclic aromatic hydrocarbons (PAHs) were identified as risk factors of MetS, while essential metals are integral parts of metalloenzymes catalyzing metabolic processes. However, effects of co-exposure to PAHs and essential metals have not been investigated yet. We aimed to assess whether essential metals could modify the hazard effects of PAHs on MetS, and underlying mediation effects of microRNA (miRNAs) were further explored. A cross-sectional study of 1451 males including 278 MetS cases was conducted. Internal exposure levels of 5 classes of PAH metabolites, 7 essential metals, as well as expressions of PAHs-associated 8 plasma miRNAs were assessed. Multiple exposure models, Bayesian kernel machine regression (BKMR), and quantile g-computation (QGcomp) were used simultaneously to identify MetS-related critical chemicals. Mutual effect modification between chemicals and mediation effects of miRNAs on chemical-MetS association was testified. In this study, hydroxyphenanthrene (OHPhe) and selenium (Se) were consistently identified as MetS-related key chemicals in three statistical methods. OHPhe was positively associated with MetS [OR (95 % CI) = 1.79 (1.21, 2.65), P = 0.004], while Se had a negative relationship with MetS [OR (95 % CI) = 0.61 (0.43, 0.87), P = 0.007]. Effect modification analysis observed the association between OHPhe and MetS was weakened with increased Se exposure. Only the expression of miR-24-3p was negatively associated with MetS [OR (95 % CI) = 0.81 (0.66, 0.95), P = 0.048] and could mediate 16.1 % of OHPhe-MetS association in subjects with low Se exposure (≤0.87 μg/mmol creatinine) (P = 0.019). We found a mutual effect modification between OHPhe and Se on MetS, and the positive OHPhe-MetS association was attenuated with increased Se exposure. Mediation effects of miR-24-3p on OHPhe-MetS association were dependent on Se dose. Our findings may provide new insight into the prevention and intervention of MetS.

Recent advances in the application of ionomics in metabolic diseases

Trace elements and minerals play a significant role in human health and diseases. In recent years, ionomics has been rapidly and widely applied to explore the distribution, regulation, and crosstalk of different elements in various physiological and pathological processes. On the basis of multi-elemental analytical techniques and bioinformatics methods, it is possible to elucidate the relationship between the metabolism and homeostasis of diverse elements and common diseases. The current review aims to provide an overview of recent advances in the application of ionomics in metabolic disease research. We mainly focuses on the studies about ionomic or multi-elemental profiling of different biological samples for several major types of metabolic diseases, such as diabetes mellitus, obesity, and metabolic syndrome, which reveal distinct and dynamic patterns of ion contents and their potential benefits in the detection and prognosis of these illnesses. Accumulation of copper, selenium, and environmental toxic metals as well as deficiency of zinc and magnesium appear to be the most significant risk factors for the majority of metabolic diseases, suggesting that imbalance of these elements may be involved in the pathogenesis of these diseases. Moreover, each type of metabolic diseases has shown a relatively unique distribution of ions in biofluids and hair/nails from patients, which might serve as potential indicators for the respective disease. Overall, ionomics not only improves our understanding of the association between elemental dyshomeostasis and the development of metabolic disease but also assists in the identification of new potential diagnostic and prognostic markers in translational medicine.

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.

Exposure to Metal Mixtures and Overweight or Obesity Among Chinese Adults

Previous research has investigated the association between individual metal exposure and overweight/obesity (OW/OB). However, there is limited data about metal mixture exposure and OW/OB. This study aimed to explore the individual and joint effects of 21 metals on OW/OB and its metabolic phenotypes. A total of 4042 participants were enrolled in our study, and 51.0% of them were overweight/obese. We quantified 21 metal levels in the urine sample. OW/OB was defined as BMI ≥ 24 kg/m², while the metabolic phenotypes, including metabolic unhealthy overweight/obesity (MUOW/OB) and metabolic health overweight/obesity (MHOW/OB), were determined by BMI and metabolic state. We used logistic regression to analyze the effect of individual metal exposure on OW/OB and its metabolic phenotypes. Quantile g-computation was applied to evaluate the joint effect of metal exposure on OW/OB and its metabolic phenotypes. In logistic regression, zinc (Zn) was positively associated with OW/OB, with the odds ratio (OR) in the highest quartiles of 2.19 (95% confidence interval (CI), 1.74, 2.77; P trend < 0.001), while arsenic (As) and cadmium (Cd) were negatively associated with OW/OB (OR = 0.70 (0.56, 0.87) and 0.61 (0.48, 0.78), respectively). After adjustment for age, gender, education, cigarette smoking, alcohol drinking, physical activity, meat intake, and vegetable intake, Zn was positively associated with MUOW/OB, while As, Cd, nickel (Ni), and strontium (Sr) were negatively associated with MUOW/OB (all P trend < 0.05). Quantile g-computation showed a significantly negative association between metal mixture exposure and MUOW/OB. Our study suggested that metal mixture exposure might be negatively associated with OW/OB, particularly with MUOW/OB. Zn, As and Cd contributed most to the effect of the mixture. More prospective studies are warranted to confirm these findings and reveal the underlying mechanisms.

Association between Blood Manganese Levels and Visceral Adipose Tissue in the United States: A Population-Based Study

Background: Manganese (Mn) is an essential trace element with a narrow toxic margin for human health. The association between Mn exposure and adverse visceral adipose tissue (VAT) accumulation is unclear. Objective: This study aimed to estimate the associations of blood Mn levels with VAT mass or visceral obesity in the general population in the United States. Method: This cross-sectional study included data of 7297 individuals released by National Health and Nutrition Examination Survey (NHANES). VAT was quantified with dual-energy X-ray absorptiometry, and blood Mn was measured using inductively coupled plasma mass spectrometry. The generalized linear model and generalized additive model (GAM) were applied to estimate the linear and non-linear associations between Mn levels and VAT mass, respectively. Logistic regression was used to estimate the associations between blood Mn levels and the risk of visceral obesity. Results: Fully adjusted generalized linear regression revealed that individuals in the higher quantile of Mn had increased VAT mass compared with those in the lower quantile (β per quantile change = 0.025; 95% CI of 0.017, 0.033; p < 0.001). Positive associations were also observed in males and females (males: β per quantile change = 0.012, 95% CI of 0.002, 0.022 (p = 0.020); female: β per quantile change = 0.036; 95% CI of 0.023, 0.048 (p < 0.001)). The GAM illustrated that the non-linear associations between blood Mn levels and VAT mass were in U-shape patterns (effective degree of freedom >1 in total participants, males, and females). A stratified analysis found significant interactions between Mn and the family income-to-poverty ratio (PIR) in males, with stronger associations in males with a PIR < 1.3 (β = 0.109; 95% CI of 0.048, 0.170). Additional analyses revealed that individuals in the highest quantile of Mn had a 39% higher risk of visceral obesity (OR = 1.39; 95% CI of 1.15−1.69; p < 0.001). Conclusions: Higher blood Mn levels were positively associated with increased VAT mass and visceral obesity risk. The adverse VAT phenotype associated with excessive blood Mn levels should be further investigated.

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.

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.