Effects Of Metal Mixtures Research Articles

Unveiling the interaction and combined effects of multiple metals/metalloids exposure to TNF-α and kidney function in adults using bayesian kernel machine regression and quantile-based G-computation

BackgroundExposure to multiple metals may cause adverse effects, particularly in the kidneys. However, studies on the combined and interaction effects of metal mixtures on human health remain limited. ObjectiveThe study aims to evaluate the interaction between metals and assess the combined effects of exposure to metal mixtures on tumor necrosis factor-alpha (TNF-α) levels and kidney function MethodsParticular emphasis has been placed on the impact of various metals, including arsenic (As), cadmium (Cd), lead (Pb), as well as essential trace elements, such as cobalt (Co), copper (Cu), selenium (Se), and zinc (Zn), on human health and their potential collective influence on both TNF-α and kidney function. This cross-sectional study analyzed the data of 421 adults who underwent a health examination. Generalized linear model (GLM), Bayesian kernel machine regression (BKMR), and quantile-based G-computation (qgcomp) were used to evaluate the association and joint effects between the metals and TNF-α, as well as kidney function. ResultsIncreased concentrations of As (β = 0.11, 95 % CI = 0.05, 0.17) and Pb (β = 0.30, 95 % CI = 0.23, 0.37) in the blood were associated with elevated levels of TNF-α, while elevated Cu (β = −0.42, 95 % CI = −0.77, −0.07) levels were linked to a significant reduction in TNF-α. The overall effect of metals mixture showed a significant association with a decline in eGFR and an increase TNF-α in the BKMR model. Qgcomp analysis of the metals mixture (β = −0.06, 95 % CI = −0.07, −0.05) indicated that As, Pb, and Zn were the primary contributors to the reduction in eGFR, while As and Pb were the major contributors in metals mixture (β = 0.12, 95 % CI = 0.08, 0.15) to the elevation of TNF-α levels. ConclusionExposure to multiple metals could have joint association with the TNF-α levels and kidney function. Furthermore, TNF-α could act as a mediator between metal mixtures and eGFR.

Thyroid-stimulating hormone (TSH) mediates the associations between maternal metals and neurodevelopment in children: A prospective cohort study

Insufficient research has focused on the effects of metal mixtures on children's neurodevelopment and TSH's potential mediating effect. Plasma concentrations of ten metals were measured among 2887 pregnant women in a persistent Chinese birth cohort. At age two, children's neurodevelopment was assessed using mental development indexes (MDIs) and psychomotor development indexes (PDIs), defining neurodevelopmental delay as MDI≤ 79 (cognitive delay) or PDI≤ 79 (motor delay). The associations between single and mixed metals with neurodevelopment delay risk were examined using generalized linear regression complemented by weighted quantile sum (WQS) regression. To investigate the mediated effects of infant Thyroid-Stimulating Hormone (TSH) on metal-associated neurodevelopment delay risk, mediation analyses were conducted. According to the single-metal model, V, Mn, and Pb levels are positively associated with neurodevelopment delay. The WQS model found consistent associations (Odds Ratio [OR] 1.55, 95% Confidence Interval [CI] 1.23 to 1.95), highlighting V, Mn, and Pb as the main causes of cognitive delay. Further mediation analysis revealed that the association between metals (mainly V, Mn, and Pb) and neurodevelopment delay risk is mediated by TSH, with proportions ranging from 3.18 to 10.14% (all P < 0.05). Our findings highlighted prenatal exposure to metals was associated with higher risks of neurodevelopmental delay, with TSH possibly mediating this effect.

Meet-in-metabonomics: Insights into associations between hair heavy metal and adverse child growth in e-waste recycling area

Heavy metal pollution from informal e-waste recycling may adversely affect child growth. However, the potential toxic mechanisms from a population perspective remain unknown. Herein, 18 hair heavy metals, urinary metabolomics, and three child growth indices [i.e., weight-for-age Z-score (WAZ), height-for-age Z-score (HAZ), and BMI Z-score (BMIZ)] were measured in children from e-waste recycling (ER, N = 426) and control areas (CR, N = 247). We examined longitudinal changes in heavy metal exposure and child growth after e-waste control to further elucidate causal relationships. Results showed that children in regulated ER site were still exposed to higher levels of several heavy metals and experienced poorer growth compared to those in control areas. Elevated exposure to heavy metals like tin, antimony, lead, cadmium, and cobalt correlated with poor child growth, particularly affecting girls and younger children. Tin, rather than traditionally concerning heavy metals, exhibited the most crucial role in driving the adverse effects of metal mixtures on child growth. Reducing heavy metal exposure through e-waste control could notably improve child growth, confirming the causal relationship between heavy metal exposure and poor child growth and underscoring the health benefits of e-waste regulation. Our research identified the roles of steroid biosynthesis, folate biosynthesis, amino acid metabolism, and purine metabolism in mediating the effects of metal exposure on child growth. Testosterone glucuronide, riboflavin, folic acid, xanthosine, and xanthine emerged as key mediators, potentially serving as metabolic signatures of heavy metal exposure. These findings illuminate the toxic mechanisms underlying poor child growth resulted from heavy metal exposure, offering important insights from a population-based perspective. In addition to lead and cadmium, monitoring and regulating tin and antimony are crucial to mitigate their negative impact on child growth in e-waste recycling areas.

Effects of Mixed Metal Exposure on MRI Metrics in Basal Ganglia.

Welding fumes contain various metals. Past studies, however, mainly focused on Manganese (Mn)-related neurotoxicity. This study investigated welding-related mixed metal exposure effects on MRI metrics in the basal ganglia (BG) and their dose-response relationship. Subjects with (N = 23) and without (N = 24) a welding exposure history were examined. Metal exposure was estimated with exposure history questionnaire and whole blood metal levels. T1 (weighted-intensity and relaxation time; estimates of brain Mn accumulation), diffusion tensor imaging [Axial (AD), mean (MD), radial diffusivity (RD), and fractional anisotropy (FA); estimates of microstructural differences] metrics in BG [caudate nucleus, putamen, and globus pallidus (GP)] and voxel-based morphometry (for volume) were examined and related with metal exposure measures. Compared to controls, welders showed higher GP R1 (1/T1; p = 0.034) but no differences in blood metal and T1-weighted (T1W) values in any ROIs (p's > 0.120). They also had higher AD and MD values in the GP (p's < 0.033) but lower FA values in the putamen (p = 0.039) with no morphologic differences. In welders, higher blood Mn and Vanadium (V) levels predicted higher BG R1 and T1W values (p's < 0.015). There also were significant overall metal mixture effects on GP T1W and R1 values. Moreover, GP AD and MD values showed non-linear associations with BG T1W values: They increased with increasing T1W values only above certain threshold of T1 values. The current findings suggest that Mn and V individually but also metal mixtures jointly predict GP T1 signals that may in turn contribute to altered DTI metrics in the BG after certain exposure threshold levels.

Metal Mixture Effects of Ni, Cu, and Zn in a Multispecies, Two-Trophic-Level Algal-Daphnid Microcosm Can Be Predicted From Single-Trophic-Level Effects: The Role of Indirect Toxicity.

Effect assessments of metals are mostly based on single-metal, single-species tests, thereby ignoring metal-mixture effects and indirect effects through species interactions. We tested the combined effects of metal and species interactions in two-trophic algal-daphnid microcosms. Metal-mixture effects on daphnid communities may propagate from effects on the generally more sensitive algal communities. Four different algal communities (three species each), with and without addition of the same daphnid community (three species) were exposed to single metals and one metal mixture (17:17:51 µg/L Ni:Cu:Zn). Daphnid densities were negatively affected by metals in the two-trophic test, the magnitude of which depended on the algal community composition. Algal densities were overall positively affected by the metals in the two-trophic test but negatively in the single-trophic test, illustrating an indirect positive effect in the two-trophic system due to a reduced grazing pressure. Metal effects on daphnid communities in the two-trophic test (day 21) were correlated with metal effects on the single-trophic-level algal communities during exponential growth (R2 = 0.55, p = 0.0011). This finding suggests that metal effects propagate across trophic levels due to a reduced food quantity. However, the indirect positive effects on algal densities, resulting in abundant food quantity, suggests that metal effects can also propagate to daphnids due to a reduced food quality (not measured directly). Metal-mixture interactions on daphnid densities varied during exposure, but were additive or antagonistic relative to independent action when final daphnid densities were considered (day 56). This suggests stronger indirect effects of the mixture compared with the single metals. Overall, our study highlights the dynamic aspect of community-level effects, which empirical reference models such as independent action or concentration addition cannot predict. Environ Toxicol Chem 2024;43:2350-2364. © 2024 SETAC.

Blood Metal Mixture Effects on All-Cause Mortality in American Indian Populations, Strong Heart Study

Blood Metal Mixture Effects on All-Cause Mortality in American Indian Populations, Strong Heart Study

Metabolic signatures of population exposure to metal mixtures: A metabolome-wide association study

Numerous studies have explored the health impacts of individual metal exposures, yet the effects of metal mixtures on human endogenous metabolism remain largely unexplored. We aimed to assess the serum metabolic signatures of people exposed to metal mixtures. Serum and urine samples were collected from 186 workers at a steel factory in Anhui, China, in September 2019. Inductively coupled plasma mass spectrometry was used to analyze the concentrations of 23 metal elements. The serum metabolome was determined by liquid chromatography-mass spectrometry (LC-MS). A metabolome-wide association study (MWAS) was performed across the metal exposures and metabolism using quantile g-computation modeling. Pathway enrichment analysis was performed using MetaboAnalyst. We identified 226 metabolites associated with metal mixtures, primarily involving lipid metabolism (glycerophospholipids, sphingolipids), amino acid metabolism (arginine and proline, alanine, aspartate and glutamate metabolism) and caffeine metabolic pathways. Exposure to metal mixtures is mainly associated with alterations in lipid metabolism and amino acid metabolism, particularly in the glycerophospholipid and arginine and proline metabolism pathways.

Sex-specific associations of a ferroalloy metal mixture with motor function in Italian adolescents.

Motor function is critical for children's health, yet remains an understudied neurodevelopmental domain. Exposure to metals has been linked with motor function, but no study has examined the joint effects of metal mixtures. We evaluated cross-sectional associations between a metal mixture and motor function among 569 adolescents (10-14 years old) living near the ferroalloy industry. Concentrations of blood lead, hair manganese, hair copper, and hair chromium were quantified using inductively coupled plasma mass spectrometry. Neuropsychologists administered multiple fine motor function assessments: pursuit aiming, finger tapping, visual reaction time (VRT), and subtests from the Luria Nebraska battery. We estimated associations between motor function and the metal mixture using quantile-based g-computation and multivariable linear regression, adjusting for child age, sex, and socioeconomic status. We explored sex-specific associations in stratified models. Associations between the metal mixture and motor function were mostly null but were modified by sex. We observed a beneficial association among females: a quartile increase in all metals in the mixture was associated with a 2.6% faster average response time on the VRT (95% confidence interval [CI] = -4.7%, -0.5%), driven by Cu and Cr. In contrast, this association was adverse among males (ß = 1.5% slower response time [95% CI = -0.7%, 3.9%]), driven by Cu and Mn. Results suggest that males may be more susceptible to the adverse effects of metal exposure on motor function during adolescence than females. Future studies, particularly prospective study designs, are warranted to further understand the associations of metal mixtures with motor function.

Association of Blood Metals and Metal Mixtures with the Myocardial Enzyme Profile: An Occupational Population-Based Study in China.

To investigate a cross-sectional association between blood metal mixture and myocardial enzyme profile, we quantified creatine kinase (CK), creatine kinase-MB (CK-MB), lactate dehydrogenase (LD), α-hydroxybutyrate dehydrogenase (α-HBD), and aspartate transaminase (AST) levels among participants from the manganese-exposed workers healthy cohort (MEWHC) (n = 544). The levels of 22 metals in blood cells were determined using inductively coupled plasma mass spectrometry. The least absolute shrinkage and selection operator (LASSO) penalized regression model was utilized for screening metals. The exposure-response relationship between specific metal and myocardial enzyme profile was identified by general linear regression and restricted cubic spline analyses. The overall effect and interactions were evaluated using Bayesian kernel machine regression (BKMR). Manganese was linearly and positively associated with CK (Poverall = 0.019, Pnon-linearity = 0.307), dominating the positive overall effect of mixture exposure (manganese, arsenic, and rubidium) on CK level. Calcium and zinc were linearly and negatively associated with LD levels (Poverall < 0.05, Pnon-linearity > 0.05), and asserted dominance in the negative overall effect of metal mixtures (rubidium, molybdenum, zinc, nickel, cobalt, calcium, and magnesium) on LD level. Interestingly, we observed a U-shaped dose-response relationship of molybdenum with LD level (Poverall < 0.001, Pnon-linearity = 0.015), an interaction between age and calcium on LD level (Pinteration = 0.041), and an interaction between smoking and molybdenum on LD level (Pinteration = 0.035). Our study provides evidence that metal mixture exposure affects the myocardial enzyme profile. Additional investigation is required to confirm these associations, and to reveal the fundamental mechanisms involved.

Prenatal exposure to metal mixtures, body mass index trajectories in early life and effect modifiers: Insights from a prospective birth cohort study

Current scientific knowledge is insufficient on the effects of metal mixtures on early life growth trajectories. This study included 7118 mother-infant pairs from a Chinese birth cohort. Concentrations of 18 maternal urinary metals were quantified, and growth trajectories were conducted based on standardized body mass index (BMI) for up to eight times from 0 to 2 years. A three-phase analytical framework was applied to explore the risk ratios (RR) and 95 % confidence intervals (95 % CI) of co-exposure to metals on dynamic growth, along with potential modifiers. Five growth trajectory groups were identified. Exposure to metal mixtures driven by thallium (Tl, 34.8 %) and aluminum (Al, 16.2 %) was associated with an increased risk of low-rising trajectory (RR=1.58, 95 % CI: 1.25, 2.00); however, exposure to mixtures driven by strontium (Sr, 49.5 %) exhibited an inverse correlation (RR = 0.81, 95 % CI: 0.67, 0.97). Furthermore, infants with varying levels of Tl, Al and Sr, as well as modifiers including pre-pregnancy BMI and infant sex faced distinct risks of low-rising trajectory. Our findings highlighted the Tl, Al, and Sr as key metals in relation to the low-rising trajectory in early life characterized as catch-up growth, with pre-pregnancy BMI and infant sex exerting as potential modifiers.

Association of urinary metal element with semen quality: a cross-sectional study from Eastern China.

The effect of metallic elements on semen quality remains controversial, with limited evidence on the effects of metal mixtures. We conducted a study involving 338 participants from multiple centers in Eastern China, measuring 17 urinary metals and semen quality parameters. Our analysis used various statistical models, including multivariate logistic and linear regression, Bayesian Kernel Machine Regression, and weighted quantile sum models, to examine the associations between metal levels and semen quality. Logistic regression showed that higher urinary lead was associated with increased risk of abnormal sperm concentration (OR = 1.86, p = 0.021), arsenic to higher abnormal progressive motility risk (OR = 1.49, p = 0.027), and antimony to greater abnormal total motility risk (OR = 1.37, p = 0.018). Conversely, tin was negatively correlated with the risk of abnormal progressive motility (OR = 0.76, p = 0.012) and total motility (OR = 0.74, p = 0.003), respectively. Moreover, the linear models showed an inverse association between barium and sperm count, even after adjusting for other metals (β = - 0.32, p < 0.001). Additionally, the WQS models showed that the metal mixture may increase the risk of abnormal total motility (βWQS = 0.55, p = 0.046). In conclusion, semen quality may be adversely affected by exposure to metals such as arsenic, barium, lead, and antimony. The combined effect of the metal mixture appears to be particularly impaired total motility.

Plasma metals, genetic risk, and rapid kidney function decline among type 2 diabetes

BackgroundRapid kidney function decline (RKFD) is a main clinical feature of early chronic kidney disease (CKD) in type 2 diabetes (T2D). Environmental and genetic factors influencing RKFD remain inadequately elucidated. ObjectivesThis study aimed to examine the associations of metals with RKFD among T2D and to further investigate the effect of metal mixtures on RKFD with the modifying effect of genetic susceptibility. MethodsThis study included 2209 people with T2D (1942 had genotyping data) free of CKD at baseline from the Dongfeng-Tongji cohort. We used inductively coupled plasma-mass spectrometry (ICP-MS) to measure 23 metals in baseline plasma. Using elastic net (ENET), multivariate logistic regression, and Bayesian kernel machine regression (BKMR) model, we examined independent associations of multiple metals with RKFD. We calculated the environmental risk score (ERS) to assess the effects of metal mixtures on RKFD and the genetic risk score (GRS) to assess genetic susceptibility. RKFD was defined as estimated glomerular filtration rate (eGFR) loss > 3 mL/min/1.73 m2/year. ResultsDuring a median of 9.8 years follow-up, 262 participants developed RKFD. Aluminum, vanadium, zinc, selenium, rubidium, tin, barium, and tungsten were screened from ENET. In multivariate logistic models, vanadium, selenium, and tungsten were negatively associated with RKFD, while zinc, tin, and rubidium were positively associated. The BKMR showed a nonlinear association of vanadium and rubidium with RKFD and interactions between metals (barium‑vanadium, barium‑rubidium). The ERS was positive associated with RKFD (per SD increase in ERS, OR = 1.94, 95% CI: 1.66, 2.27). No significant interaction between ERS and GRS was observed on RKFD, however, participants in the highest ERS and GRS group had the highest RKFD risk. ConclusionVanadium and rubidium were associated with RKFD in T2D. Metal mixtures was associated with an increased risk of RKFD in T2D, particularly in those at high genetic risk.

Bioaccumulation and sub-lethal physiological effects of metal mixtures on mussel, Mytilus edulis: Continuous exposure to a binary mixture of mercury and cadmium

In the natural ecosystem, aquatic organisms are exposed to a cocktail of chemicals that may result in toxicological responses differing from those of individual chemicals. In the present study, mussels were exposed using a semi-static and triplicated design to either control (no added metal), 50 µg l−1 (Hg alone), 50 µg l−1 (Cd alone), or 50 µg l−1 Hg plus 50 µg l−1 Cd (Hg + Cd) mixture for 14 days. Tissues were collected on days 0, 2, 4, 8, and 14 for metal analysis and sub-lethal responses using a suite of assays. Tissue metal concentrations were not significantly different in the single metal (Hg or Cd) compared to the Hg plus Cd mixture treatment for all tissues, apart from the gill of the Cd alone treatment. At the end of the experiment, the gill Cd concentration was significantly increased in the Hg plus Cd mixture compared to the Cd alone treatment, suggesting the influence of Hg on Cd uptake. The percentage increases of the Hg plus Cd mixture compared to the arithmetic sum of the individual metals were ( %): 20.2, 9.3, 25.1, 23.8, 10.7, and 12.4 for adductor muscle, digestive gland, gill, gonad, remaining soft tissue, and haemolymph, respectively. There were no observed treatment effects on total haemocyte count, haemolymph protein, or glucose concentration in the cell-free haemolymph. Neither was there any treatment effect on osmotic pressure, ions in the tissues, or in the cell-free haemolymph. At the end of the experiment, Hg-mediated oxidative damage, as an increase of thiobarbituric reactive substances (TBARS) and apparent depletion of total glutathione. This was observed in the gill and digestive gland of the Hg alone and Hg plus Cd mixture. Histopathology examination showed similar pathology in the Hg alone and the Hg plus Cd treatment. In conclusion, despite some oxidative stress and pathology during metal exposure, the accumulation of metals and effects on mussel health were similar between single exposures and a mixture of Hg plus Cd. In terms of risk assessment, regulations for the individual metals should suffice to protect against the mixture of Hg plus Cd, at least for adult M. edulis in full-strength seawater.

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.

Comparative mathematical modeling of causal association between metal exposure and development of chronic kidney disease.

Previous studies have identified several genetic and environmental risk factors for chronic kidney disease (CKD). However, little is known about the relationship between serum metals and CKD risk. We investigated associations between serum metals levels and CKD risk among 100 medical examiners and 443 CKD patients in the medical center of the First Hospital Affiliated to China Medical University. Serum metal concentrations were measured using inductively coupled plasma mass spectrometry (ICP-MS). We analyzed factors influencing CKD, including abnormalities in Creatine and Cystatin C, using univariate and multiple analysis such as Lasso and Logistic regression. Metal levels among CKD patients at different stages were also explored. The study utilized machine learning and Bayesian Kernel Machine Regression (BKMR) to assess associations and predict CKD risk based on serum metals. A chained mediation model was applied to investigate how interventions with different heavy metals influence renal function indicators (creatinine and cystatin C) and their impact on diagnosing and treating renal impairment. Serum potassium (K), sodium (Na), and calcium (Ca) showed positive trends with CKD, while selenium (Se) and molybdenum (Mo) showed negative trends. Metal mixtures had a significant negative effect on CKD when concentrations were all from 30th to 45th percentiles compared to the median, but the opposite was observed for the 55th to 60th percentiles. For example, a change in serum K concentration from the 25th to the 75th percentile was associated with a significant increase in CKD risk of 5.15(1.77,8.53), 13.62(8.91,18.33) and 31.81(14.03,49.58) when other metals were fixed at the 25th, 50th and 75th percentiles, respectively. Cumulative metal exposures, especially double-exposure to serum K and Se may impact CKD risk. Machine learning methods validated the external relevance of the metal factors. Our study highlights the importance of employing diverse methodologies to evaluate health effects of metal mixtures.

Association between multiple-heavy-metal exposures and systemic immune inflammation in a middle-aged and elderly Chinese general population

BackgroundExposure to heavy metals alone or in combination can promote systemic inflammation. The aim of this study was to investigate potential associations between multiple plasma heavy metals and markers of systemic immune inflammation.MethodsUsing a cross-sectional study, routine blood tests were performed on 3355 participants in Guangxi, China. Eight heavy metal elements in plasma were determined by inductively coupled plasma mass spectrometry. Immunoinflammatory markers were calculated based on peripheral blood WBC and its subtype counts. A generalised linear regression model was used to analyse the association of each metal with the immunoinflammatory markers, and the association of the metal mixtures with the immunoinflammatory markers was further assessed using weighted quantile sum (WQS) regression.ResultsIn the single-metal model, plasma metal Fe (log10) was significantly negatively correlated with the levels of immune-inflammatory markers SII, NLR and PLR, and plasma metal Cu (log10) was significantly positively correlated with the levels of immune-inflammatory markers SII and PLR. In addition, plasma metal Mn (log10 conversion) was positively correlated with the levels of immune inflammatory markers NLR and PLR. The above associations remained after multiple corrections. In the mixed-metal model, after WQS regression analysis, plasma metal Cu was found to have the greatest weight in the positive effects of metal mixtures on SII and PLR, while plasma metals Mn and Fe had the greatest weight in the positive effects of metal mixtures on NLR and LMR, respectively. In addition, blood Fe had the greatest weight in the negative effects of the metal mixtures for SII, PLR and NLR.ConclusionPlasma metals Cu and Mn were positively correlated with immunoinflammatory markers SII, NLR and PLR. While plasma metal Fe was negatively correlated with immunoinflammatory markers SII, NLR, and PLR.

Joint and interactive effects of metal mixtures on liver damage: Epidemiological evidence from repeated-measures study

BackgroundThe impact of heavy metals on liver function has been examined in numerous epidemiological studies. However, these findings lack consistency and longitudinal validation. MethodsIn this study, we conducted three follow-up surveys with 426 participants from Northeast China. Blood and urine samples were collected, along with questionnaire information. Urine samples were analyzed for concentrations of four metals (chromium [Cr], cadmium [Cd], lead [Pb], and manganese [Mn]), while blood samples were used to measure five liver function indicators (alanine aminotransferase [ALT], aspartate aminotransferase [AST], albumin [ALB], globulin [GLB], and total protein [TP]). We utilized a linear mixed-effects model (LME) to explore the association between individual heavy metal exposure and liver function. Joint effects of metal mixtures were investigated using quantile g-computation and Bayesian kernel machine regression (BKMR). Furthermore, we employed BKMR and Marginal Effect models to examine the interaction effects between metals on liver function. ResultsThe LME results demonstrated a significant association between urinary heavy metals (Cr, Cd, Pb, and Mn) and liver function markers. BKMR results indicated positive associations between heavy metal mixtures and ALT, AST, and GLB, and negative associations with ALB and TP, which were consistent with the g-comp results. Synergistic effects were observed between Cd-Cr on ALT, Mn-Cr and Cr-Pb on ALB, while an antagonistic effect was found between Mn-Pb and Mn-Cd on ALB. Additionally, synergistic effects were observed between Mn-Cr on GLB and Cd-Cr on TP. Furthermore, a three-way antagonistic effect of Mn-Pb-Cr on ALB was identified. ConclusionExposure to heavy metals (Cr, Cd, Mn, Pb) is associated with liver function markers, potentially leading to liver damage. Moreover, there are joint and interaction effects among these metals, which warrant further investigation at both the population and mechanistic levels.

Combined exposure to multiple metals on abdominal aortic calcification: results from the NHANES study.

Exposure to metals increases the risk of many diseases and has become a public health concern. However, few studies have focused on the effect of metal on abdominal aortic calcification (AAC), especially the combined effects of metal mixtures. In this study, we aim to investigate the combined effect of metals on AAC risk and determine the key components in the multiple metals. We tried to investigate the relationship between multiple metal exposure and AAC risk. Fourteen urinary metals were analyzed with five statistical models as follows: generalized linear regression, weighted quantile sum regression (WQS), quantile g-computation (Qgcomp), and Bayesian kernel machine regression (BKMR) models. A total of 838 participants were involved, of whom 241 (28.8%) had AAC. After adjusting for covariates, in multiple metal exposure logistic regression, cadmium (Cd) (OR = 1.364, 95% CI = 1.035-1.797) was positively associated with AAC risk, while cobalt (Co) (OR = 0.631, 95% CI = 0.438-0.908) was negatively associated with AAC risk. A significant positive effect between multiple metal exposure and AAC risk was observed in WQS (OR = 2.090; 95% CI = 1.280-3.420, P < 0.01), Qgcomp (OR = 1.522, 95% CI = 1.012-2.290, P < 0.05), and BKMR models. It was found that the positive association may be driven primarily by Cd, lead (Pb), uranium (U), and tungsten (W). Subgroups analysis showed the association was more significant in participants with BMI ≥ 25kg/m2, abdominal obesity, drinking, and smoking. Our study shows that exposure to multiple metals increases the risk of AAC in adults aged ≥ 40years in the USA and that Cd, Pb, U, and W are the main contributors. The association is stronger in participants who are obese, smoker, or drinker.

Association between Heavy Metals and Trace Elements in Cancerous and Non-cancerous Tissues with the Risk of Colorectal Cancer Progression in Northwest China.

Alterations in heavy metals and trace element levels may be associated with various cancers. However, the role of this interaction in colorectal cancer (CRC) progression is unclear. In recent years, Principal Component Analysis (PCA) and Bayesian Kernel Machine Regression (BKMR) models have provided new ideas for analyzing the effects of metal mixtures on CRC progression. Herein, we assessed the differences in the levels of arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni), selenium (Se), and zinc (Zn) in tumors and adjacent healthy tissues, to investigate the relationship between heavy metals/trace elements and CRC progression. Surgical samples of CRC and noncancerous tissues were collected, and trace metal levels were analyzed using inductively coupled plasma mass spectrometry (ICP-MS). Logistic regression, PCA, and BKMR models were used to investigate the relationship between heavy metals and trace elements and the degree of tumor differentiation and lymph node metastasis in CRC. Cancer tissues showed lower As, Cd, Co, and Cr concentrations, and higher Se concentrations than healthy tissues (P < 0.05). In addition, CRC patients with poorly differentiated tumors and/or positive lymph node metastases had lower levels of Cd, Zn, Cu, and Se (P < 0.05). Logistic regression showed that single metal concentration was negatively correlated with CRC progression. PCA and BKMR models also showed that the metal mixture concentration was negatively correlated with CRC progression, with Cd contributing the most. Overall, changes in heavy metal and trace element levels may be related to the development of CRC; however, further mechanistic studies are required.

Reciprocal Effects of Metal Mixtures on Phytoplankton

Several types of contaminants are anthropogenically introduced into natural aquatic ecosystems and interact with other chemicals and/or with living organisms. Although metal toxicity alone has been relatively well studied, the toxic metal ion effects in the mixture have been thoroughly studied only during the last decades. This review focuses on the published reciprocal effects of different metals on different species of algae, together with describing their toxic effects on studied parameters. Phytoplankton as a bioindicator can help to estimate the reciprocal metal risk factor. Many methodologies have been developed and explored, such as the biotic ligand model (BLM), concentration addition (CA), independent action (IA), sensitivity distribution of EC50 species sensitivity distribution (SSD curves), and others, to study reciprocal metal toxicity and provide promising results, which are briefly mentioned too. From our review, we can commonly conclude the following: Zn acted antagonistically with most heavy metals (Al, Cu, Cd, and Ni). The Cu interaction with Cd, Fe, and Pb was mostly antagonistic. Cd showed synergistic behaviour with Hg, Cu, Zn, and Pb and antagonistic behaviour with Co and Fe in many cases. Methods and techniques need to be developed and optimised to determine reciprocal metal toxicity so that the ecotoxicological predictions made by using phytoplankton can be more accurate and related to real-time toxic metals risks to the aquatic ecosystem. This is the main objective of ecotoxicological tests for risk assessment. Understanding how metals enter algal cells and organelles can help to solve this challenge and was one of the main parts of the review.