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.

Associations of circulating multiple metals with the risk of incident hyperuricemia and the average annual change in uric acid levels.

BACKGROUND: Hyperuricemia has been linked to exposure to certain metals in cross-sectional studies. However, prospective studies evaluating the associations of multiple metal exposures with incident hyperuricemia are scarce. OBJECTIVES: To prospectively investigate the associations of multiple metal/metalloid concentrations with incident hyperuricemia as well as average annual change in uric acid levels in a longitudinal cohort. METHODS: A longitudinal cohort study included 3957 subjects who were free of cardiovascular disease with certain risk factors for cardiovascular disease at baseline. Incident hyperuricemia was ascertained if serum uric acid level was ≥ 420 µmol/L for men and ≥ 360 µmol/L for women during the follow-up visit in 2013. The relationships between 17 single plasma metals/metalloids and incident hyperuricemia were assessed using unconditional logistic regression models. For metals/metalloids significantly related to incident hyperuricemia, we further utilized generalized linear regression models to evaluate their associations with the average annual change in uric acid levels. Finally, we applied the weighted quantile sum (WQS) regression to investigate the joint effects of metals/metalloids on hyperuricemia risk and uric acid changes, and to identify the most significant metals. RESULTS: After adjusting for potential confounders, plasma aluminum, arsenic, barium, lead, strontium, vanadium, and zinc concentrations were positively associated with incident hyperuricemia in both main analyses and sensitivity analyzes. Compared to the lowest quartiles, participants in the highest quartiles had 63 %-125 % higher risks of incident hyperuricemia (all FDR < 0.05). Furthermore, the positive associations of these seven metals with an average annual uric acid increase reinforced the findings. Finally, the WQS analyses showed that plasma metals mixtures were positively associated with the risk of incident hyperuricemia (OR: 1.47; 95 % CI: 1.23, 1.76) and the average annual change in uric acid levels (ß: 3.17; 95 % CI: 2.42, 3.93), and strontium and vanadium were the most heavily weighted metals, respectively. CONCLUSION: Our findings identify aluminum, arsenic, barium, lead, strontium, vanadium, and zinc exposures as independent risk factors for hyperuricemia and provide new insights into the prevention of hyperuricemia.

Effect of Yttrium on Ce/Ni-Metakaolin Catalysts for CO2 Methanation.

In recent years, major economies have implemented carbon reduction and carbon neutrality policies. Furthermore, with advancements in science and technology, carbon dioxide (CO2) is now considered a valuable raw material for producing carbon-based fuels through hydrogenation. Various concentrations of yttrium (referred to as Y hereafter) were introduced to assess their influence on the catalytic performance of CO2 methanation. At a temperature of 300 °C, the catalyst exhibited an impressive CO2 conversion rate of 78.4% and maintained remarkable stability throughout a rigorous 100 h stability assessment. The findings suggest that the inclusion of yttrium (Y) promotes the formation of oxygen vacancies and alkaline sites on the catalyst. This, in turn, enhances the reducibility of nickel species, improves the dispersion of nickel particles, and plays a pivotal role in enhancing thermal stability. Furthermore, it offers an innovative design approach for creating highly efficient composite CO2 methanation catalysts by controlling particle size and harnessing synergistic catalytic effects at the metal/support interface.

Integrative analyses of geochemical parameters-microbe interactions reveal the variation of bacterial community assembly in multiple metal(loid)s contaminated arable regions.

Soil microbes play crucial roles in biochemical and geochemical processes in contaminated arable ecosystems. However, what factors determine the assembling process of soil bacterial community under multiple heavy metal (loid)s (HMs) stress and how communities respond to geochemical changes have rarely been understood. Therefore, a number of contaminated soils were sampled to explore the interactions among geochemical parameters, HMs and innate bacterial community. The results showed that soil biochemical activities were inhibited obviously with the increase of HMs. Significant differences were observed in bacterial composition and abundance in studied areas, with Actinobacteria, Proteobacteria, Chloroflexi, Acidobacteria and Firmicutes governing the bacterial community structure. Redundancy analysis and variation partition analysis revealed that about 67.33% of the variation in bacterial assemblages could be explained by physiochemical parameters (21.59%), biochemical parameters (11.64%), toxic metal (loid)s (9.11%) and the interaction effect of these variables (24.99%), among which total-arsenic and moisture were the main factors. Spearman correlation analysis also demonstrated that dehydrogenase, moisture and TOC have a positive correlation with bacterial community structure with As-Cd-Pb gradient. Altogether, this study would provide a comprehensive relationship between major environmental factors and bacterial assemblages, which could offer some baseline data to investigate the mechanisms of how communities respond to physiochemical changes.

Combined exposure to multiple metals and cognitive function in older adults.

Single toxic metal exposure has been reported to be associated with impaired cognitive function, but less is known about the effects of combined exposure to multiple metals. The aim of the study was to investigate the potential associations and interactions of multiple metals with cognitive function in older adults using multi-pollutants approach. A cross-sectional study was conducted in a total of 2879 participants aged ≥ 60 years old. We systematically measured levels of 22 blood metals and used the Mini-Mental State Examination (MMSE) to assess the cognitive function. The least absolute shrinkage and selection operator (LASSO) penalized regression was applied to identify independently main metals. Adjusted estimates of cognitive function with selected metals were investigated by generalized linear regression in the multi-metal model. We found that calcium, titanium, vanadium, copper, zinc, arsenic, selenium, rubidium, molybdenum, cadmium, barium, and lead were independently identified based on LASSO penalized regression. The multi-metal model showed a higher MMSE of 0.384 (95% CI: 0.122-0.646) for a 1-SD increment in log-transformed rubidium and a lower MMSE of 0.460 (95% CI: - 0.706 to - 0.214) for a 1-SD increment in log-transformed cadmium (P < 0.05). The significantly negative associations between cadmium and cognitive function were attenuated to null accompanying with increasing concentrations of rubidium (P interaction = 0.256). Our findings suggested that blood rubidium and cadmium were mainly associated with cognitive function when accounting for co-exposure to other metals and higher level of rubidium appeared to attenuate the toxic effects of cadmium on cognitive function in older adults.

Development of a new method for biomonitoring of multiple metals in occupational exposure.

The assessment of co-exposure to several types of metal contamination poses a hurdle for occupational monitoring. Determination of elements in biological samples is an important way to evaluate occupational exposure. However, optimized methods for the extraction of multiple metals from biological samples have not been reported in recent studies. Therefore, solid-phase extraction (SPE) based on the functionalized nano-zeolite Y was suggested for the biomonitoring of metal co-exposure. SPE was conducted with ammonium pyrrolidine dithiocarbamate (APDC) surrounded by Triton X-100 micelles, which were loaded into the pores of nano-zeolite Y. In this study, SPE was optimized for pre-concentration of trace amounts of chromium (Cr), cadmium (Cd), and lead (Pb) in urine samples with respect to the pH, APDC concentration, elution condition, amount of functionalized nano-zeolite Y, and sample volume. This method has been successfully optimized for the extraction of the mentioned multiple metals with >97% efficiency and an acceptable reproducibility with a coefficient variation of <10%. This method could be used in the extraction of multiple metals in environmental and occupational exposure conditions. In this study, urine samples of welding workers were evaluated following this optimized method.

Association of metals with early postnatal gut microbiota among infants admitted to the neonatal intensive care unit.

The gut microbiota is closely related to infant health. However, the impact of environmental factors on the gut microbiota has not been widely investigated, particularly in vulnerable populations such as infants admitted to the neonatal intensive care unit (NICU). This study investigated the association between exposure to 12 metals and the composition of the gut microbiota in infants admitted to the NICU. Metal concentrations were determined in serum samples obtained from 107 infants admitted to the NICU at Hunan Children's hospital, China. Gut microbiota data were derived from 16S rRNA sequencing using stool samples. Generalized linear regression (GLR) models and Bayesian kernel machine regression (BKMR) analyses were used to estimate the associations between metals and both alpha-diversity indices and bacterial taxa. The GLR models showed that tin correlated negatively with the Shannon index (ß = -0.55, 95% conficence interval [CI]: -0.79, -0.30, PFDR< 0.001) and positively with the Simpson index (ß = 0.26, 95% CI: 0.13, 0.39, PFDR< 0.001). The BKMR analysis yielded similar results, showing that tin had the largest posterior inclusion probability for both the Shannon (0.986) and the Simpson (0.796) indices. Tin, cadmium, mercury, lead, and thallium were associated with changes in one or more taxa at the genus level. The BKMR analysis also revealed a negative correlation between metal mixtures and Clostridium_sensu_stricto, and tin contibuted mostly to the negative correlation. Early postnatal exposure to metals were associated with differences in the microbiome among infants admitted to the NICU. However, as the study was cross-sectional, these relationships must be confirmed in further studies.

Geochip 5.0 insights into the association between bioleaching of heavy metals from contaminated sediment and functional genes expressed in consortiums.

The heavy metal contamination in river and lake sediments endangers aquatic ecosystems. Herein, the feasibility of applying different exogenous mesophile consortiums in bioleaching multiple heavy metal-contaminated sediments from Xiangjiang River was investigated, and a comprehensive functional gene array (GeoChip 5.0) was used to analyze the functional gene expression to reveal the intrinsic association between metal solubilization efficiency and consortium structure. Among four consortiums, the Acidithiobacillus thiooxidans and Leptospirillum ferrooxidans consortium had the highest solubilization efficiencies of Cu, Pb, Zn, and Cd after 15 days, reaching 50.33, 29.93, 47.49, and 79.65%, while Cu, Pb, and Hg had the highest solubilization efficiencies after 30 days, reaching 63.67, 45.33, and 52.07%. Geochip analysis revealed that 31,346 genes involved in different biogeochemical processes had been detected, and the systems of 15 days had lower proportions of unique genes than those of 30 days. Samples from the same stage had more genes overlapping with each other than those from different stages. Plentiful metal-resistant and organic remediation genes were also detected, which means the metal detoxification and organic pollutant degradation had happened with the bioleaching process. The Mantel test revealed that Pb, Zn, As, Cd, and Hg solubilized from sediment influenced the structure of expressed microbial functional genes during bioleaching. This work employed GeoChip to demonstrate the intrinsic association between functional gene expression of mesophile consortiums and the bioleaching efficiency of heavy metal-contaminated sediment, and it provides a good reference for future microbial consortium design and remediation of river and lake sediments.

A Review on Engineering Transition Metal Compound Catalysts to Accelerate the Redox Kinetics of Sulfur Cathodes for Lithium-Sulfur Batteries.

Engineering transition metal compounds (TMCs) catalysts with excellent adsorption-catalytic ability has been one of the most effective strategies to accelerate the redox kinetics of sulfur cathodes. Herein, this review focuses on engineering TMCs catalysts by cation doping/anion doping/dual doping, bimetallic/bi-anionic TMCs, and TMCs-based heterostructure composites. It is obvious that introducing cations/anions to TMCs or constructing heterostructure can boost adsorption-catalytic capacity by regulating the electronic structure including energy band, d/p-band center, electron filling, and valence state. Moreover, the electronic structure of doped/dual-ionic TMCs are adjusted by inducing ions with different electronegativity, electron filling, and ion radius, resulting in electron redistribution, bonds reconstruction, induced vacancies due to the electronic interaction and changed crystal structure such as lattice spacing and lattice distortion. Different from the aforementioned two strategies, heterostructures are constructed by two types of TMCs with different Fermi energy levels, which causes built-in electric field and electrons transfer through the interface, and induces electron redistribution and arranged local atoms to regulate the electronic structure. Additionally, the lacking studies of the three strategies to comprehensively regulate electronic structure for improving catalytic performance are pointed out. It is believed that this review can guide the design of advanced TMCs catalysts for boosting redox of lithium sulfur batteries.

Serum metabolic changes link metal mixture exposures to vascular endothelial inflammation in residents living surrounding rivers near abandoned lead-zinc mines.

Metal exposure is associated with vascular endothelial inflammation, an early pathological phenotype of atherosclerotic cardiovascular events. However, the underlying mechanism linking exposure, metabolic changes, and outcomes remains unclear. We aimed to investigate the metabolic changes underlying the associations of chronic exposure to metal mixtures with vascular endothelial inflammation. We recruited 960 adults aged 20-75 years from residential areas surrounding rivers near abandoned lead-zinc mine and classified them into river area and non-river area exposure groups. Urine levels of 25 metals, Framingham risk score (FRS), and serum concentrations of intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1), as biomarkers of vascular endothelial inflammation, were assessed. A "meet-in-the-middle" approach was applied to identify causal intermediate metabolites and metabolic pathways linking metal exposure to vascular endothelial inflammation in representative metabolic samples from 64 participants. Compared to the non-river area exposure group, the river area exposure group had significantly greater urine concentrations of chromium, copper, cadmium, and lead; lower urine concentrations of selenium; elevated FRS; and increased concentrations of ICAM-1 and VCAM-1. In total, 38 differentially abundant metabolites were identified between the river area and non-river area exposure groups. Among them, 25 metabolites were significantly associated with FRS, 8 metabolites with ICAM-1 expression, and 10 metabolites with VCAM-1 expression. Furthermore, fructose, ornithine, alpha-ketoglutaric acid, urea, and cytidine monophosphate, are potential mediators of the relationship between metal exposure and vascular endothelial inflammation. Additionally, the metabolic changes underlying these effects included changes in arginine and proline metabolism, pyrimidine metabolism, starch and sucrose metabolism, galactose metabolism, arginine biosynthesis, and alanine, aspartate, and glutamate metabolism, suggesting the disturbance of amino acid metabolism, the tricarboxylic acid cycle, nucleotide metabolism, and glycolysis. Overall, our results reveal biomechanisms that may link chronic exposure to multiple metals with vascular endothelial inflammation and elevated cardiovascular risk.

Sex and age disparities in multi-metal mixture exposure and cognitive impairment in urban elderly individuals: The mediation effect and biological function of metabolites.

Studies on the relationships between metal mixtures exposure and cognitive impairment in elderly individuals are limited, particularly the mechanism with metabolite. Few studies are available on the potential sex and age specific associations between metal exposure, metabolites and cognitive impairment. We examined plasma metal and blood metabolite concentrations among 1068 urban elderly participants. Statistical analysis included a battery of variable selection approaches, logistic regression for metal/metabolite associations, and Bayesian kernel machine regression (BKMR) to identify mixed effects of metals/metabolites on cognitive impairment risk. Our results showed that As was positively associated with cognitive impairment in the female (OR 95 % CI = 2.21 (1.36, 3.57)) and 60- to 70-year-old (OR 95 % CI = 2.60 (1.54, 4.41)) groups, Cr was positively associated with cognitive impairment in the male (OR 95 % CI = 2.15 (1.27, 3.63)) and 60- to 70-year-old (OR 95 % CI = 2.10 (1.24, 3.57)) groups, and Zn was negatively associated with cognitive impairment, especially in the female (OR 95 % CI = 0.46 (0.25, 0.84)), 60- to 70-year-old (OR 95 % CI =0.24 (0.12, 0.45)) and ≥ 80-year-old (OR 95 % CI = 0.19 (0.04, 0.86)) groups. Positive associations were observed between combined metals (Cr, Cu and As) and cognitive impairment, but Zn alleviated this tendency, especially in elderly individuals aged ≥80 years. Negative associations were observed between metabolites and cognitive impairment, especially in male, female and 60-70 years old groups. The mediation effects of metabolites on the association between metal exposure and cognitive impairment were observed, and the percentages of these effects were 15.60 % (Glu-Cr), 23.00 % (C5:1-Cu) and 16.36 % (Glu-Zn). Cr, Cu, and Zn could increase cognitive impairment risk through the "Malate-Aspartate Shuttle", "Glucose-Alanine Cycle", etc., pathways. Overall, we hypothesize that metabolites have mediation effects on the relationship between multi-metal exposure and cognitive impairment and that there are sex and age differences.

Complete genome sequences of a Canadian strain of enteroaggregative Escherichia coli (EAEC) with multiple metals and antimicrobial resistance genes isolated from municipal waste-activated sludge.

Enteroaggregative Escherichia coli (EAEC) is an emerging food-borne pathogen causing acute or persistent diarrhea in humans. Here, we report the complete genome sequence of a strain of EAEC with multiple metals and antimicrobial resistance genes isolated from a waste-activated sludge collected from a Canadian municipal wastewater treatment plant.

Association of multi-metals with the risk of hypertension and the interaction with obesity: A cross-sectional study in China.

Background: Environmental exposure to multiple metals have been inconsistently associated with hypertension. Obesity is an important independent risk factor for hypertension, and few studies have assessed the interaction between obesity and metals in this context. We aimed to clarify their association and interaction. Methods: This cross-sectional study included 3,063 adults from 11 districts or counties, Guangdong. We measured the whole blood levels of 13 metals and used multipollutant-based statistical methods to analyze the association of metals with hypertension. The interaction between metals and obesity on hypertension was assessed on additive and multiplicative scales. Results: Four metals (manganese, arsenic, cadmium, and lead) were significantly associated with hypertension risk, five metals (manganese, zinc, arsenic, cadmium, and lead) were related to elevated SBP levels, five metals (manganese, zinc, selenium, cadmium, and lead) were associated with elevated DBP levels in single-metal model. Manganese remained significantly related to hypertension risk [odds ratio, 1.35 (1.02-1.78)] after adjusting for these four metals. Significant positive dose-response relationships between manganese, arsenic, cadmium, lead and hypertension risk were observed (P for overall < 0.001, P for non-linearity > 0.05). Compared with those in the lowest quartile, participants in the highest manganese quartile had a 2.83 mmHg (95% Cl: 0.71-4.96) (P FDR = 0.040) higher level of SBP. Individuals in the highest quartiles of zinc and lead had a 1.45 mmHg (0.10-2.81) (P FDR = 0.033) and 2.06 mmHg (0.59-3.53) (P FDR = 0.020) higher level of DBP, respectively. The negative interactions between cadmium, lead and obesity influences hypertension risk. BKMR analysis showed a significant joint effect of manganese, arsenic, cadmium and lead on hypertension when the concentrations of four metals were at or above their 55th percentile compared to their median values. Conclusions: The combined effect of four metals (manganese, arsenic, cadmium and lead) were associated with the prevalence of hypertension. Potential interaction effects of cadmium, lead and obesity on hypertension risk may exist. Further cohort studies in larger population are needed to clarify these findings.

Multiple metal exposure and metabolic syndrome in elderly individuals: A case-control study in an active mining district, Northwest China.

The prevalence of metabolic syndrome (MetS) is increasing at an alarming rate worldwide, particularly among elderly individuals. Exposure to various metals has been linked to the development of MetS. However, limited studies have focused attention on the elderly population living in active mining districts. Participants with MetS (N = 292) were matched for age (±2 years old) and sex with a healthy subject (N = 292). We measured the serum levels of 14 metals in older people aged 65-85 years. Conditional logistic regression, restricted cubic spline model, multiple linear regression, and Bayesian Kernel Machine Regression (BKMR) were applied to estimate potential associations between multiple metals and the risk of MetS. Serum levels of Sb and Fe were significantly higher than the controls (0.58 µg/L vs 0.46 µg/L, 2167 µg/L vs 2042 µg/L, p < 0.05), while Mg was significantly lower (20035 µg/L vs 20,394 µg/L, p < 0.05). An increased risk of MetS was associated with higher serum Sb levels (adjusted odds ratio (OR) = 1.61 for the highest tertile vs. the lowest tertile, 95% CI = 1.08-2.40, p-trend = 0.018) and serum Fe levels (adjusted OR = 1.55 for the highest tertile, 95% CI = 1.04-2.33, p-trend = 0.032). Higher Mg levels in serum may have potential protective effects on the development of MetS (adjusted OR = 0.61 for the highest tertile, 95% CI = 0.41-0.91, p-trend = 0.013). A joint exposure analysis by the BKMR model revealed that the mixture of 12 metals (except Tl and Cd) was associated with increased risk of MetS. Our results indicated that exposure to Sb and Fe might increase the risk of MetS in an elderly population living in mining-intensive areas. Further work is needed to confirm the protective effect of Mg on MetS.

The impact of multiple metals exposure on the risk of developing proliferative diabetic retinopathy in Anhui, China: a case-control study.

Through multiple different pathways, the environmental multiple metals make their ways to the human bodies, where they induce different levels of the oxidative stress response. This study further investigated the impact of multiple-metal exposure on the risk of developing proliferative diabetic retinopathy (PDR). We designed a case-control study with type 2 diabetic patients (T2D), in which the case group was the proliferative diabetic retinopathy group (PDR group), while the control group was the non-diabetic retinopathy group (NDR group). Graphite furnace atomic absorption spectrometry (GFAAS) and inductively coupled plasma optical emission spectrometry (ICP-OES) were used to detect the metal levels in our participants' urine samples. The least absolute shrinkage and selection operator (LASSO) regression approach was used to include these representative trace elements in a multiple exposure model. Following that, logistic regression models and Bayesian kernel machine regression (BKMR) models were used to describe the effect of different elements and also analyze their combined effect. In the single-element model, we discovered that lithium (Li), cadmium (Cd), and strontium (Sr) were all positively related to PDR. The multiple-exposure model revealed a positive relationship between Li and PDR risk, with a maximum quartile OR of 2.80 (95% CI: 1.10-7.16). The BKMR model also revealed that selenium (Se) might act as a protective agent, whereas magnesium (Mg), Li, and Cd may raise the risk of PDR. In conclusion, our study not only revealed an association between exposure to multiple metals and PDR risk but it also implied that urine samples might be a useful tool to assess PDR risk.

Associations of multiple plasma metals with osteoporosis: findings from the Dongfeng-Tongji cohort.

With the aging population, osteoporosis has become a more prevalent public health issue. Existing researches have indicated significant relations of single metal exposure with osteoporosis (e.g., lead, copper, and zinc), whereas the evidence regarding the joint association of metal mixtures with osteoporosis remain limited and inconclusive. A total of 4924 participants from the Dongfeng-Tongji cohort were included in the present study. Plasma levels of 23 metals were determined by inductively coupled plasma mass spectrometry, and the presence of osteoporosis was defined as a bone mineral density T-score ≤ - 2.5. We applied stepwise regression, plasma metal score, and quantile g-computation model to evaluate the association between plasma metal mixtures and osteoporosis risk. Of the 4924 participants, the prevalence of osteoporosis was 10.9% (N = 265) in males and 27.5% (N = 684) in females. In the multiple-metals model, arsenic was positively associated with osteoporosis in males, while zinc was positively associated with osteoporosis in females. Comparing extreme quartiles, the multivariate-adjusted ORs of osteoporosis were 2.20 (95% CI, 1.29, 3.79; P-trend = 0.006) for arsenic in males and 2.16 (95% CI, 1.44, 3.23; P-trend < 0.001) for zinc in females. The plasma metal score was significantly and positively associated with a higher risk of osteoporosis, with ORs (95% CI) comparing extreme quartiles were 5.00 (95% CI, 3.36, 7.65; P-trend < 0.001) in males and 1.76 (95% CI, 1.35, 2.29; P-trend < 0.001) in females. Furthermore, the results of quantile g-computation revealed a consistent positive trend of metal mixtures with risk of osteoporosis and suggested the dominant role of arsenic in males and zinc in females, respectively. Our findings highlighted the importance of controlling metal mixtures exposure for the prevention of osteoporosis in the middle-aged and elder population. Further prospective studies in larger populations are warranted to confirm our findings.

Associations of exposure to multiple metals with the risk of age-related cataract in Anhui, China: a case-control study.

It's well-known that multiple metal elements can lead to the change of oxidative stress response levels in vivo. However, their relationship with age-related cataract (ARC) had not been well studied. We designed a case-control study including 210 individuals with ARC and 210 matched control group. The metal levels in their urine specimens were measured using graphite furnace atomic absorption spectrometry (GFAAS) and inductively coupled plasma optical emission spectrometry (ICP-OES). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to select representative metals into the multi-element model and reduce dimension. Multivariate logic analysis and Bayesian kernel machine regression (BKMR) were subsequently used to explore the association of ARC risk with multiple metal elements. We found that magnesium (Mg), chromium (Cr), arsenic (As), manganese (Mn), and selenium (Se) were positively associated with ARC in the single-element model. The multiple exposure model indicated a positive association between Mg and As, in which the OR in their highest quartile were 3.32 (95% CI: 1.24-8.89) and 7.09 (95% CI: 2.56-19.63). The BKMR model also showed the effect of As increased monotonically with its increasing concentration, and high levels of Mg and As had a significant positive effect on ARC risk. In conclusion, we found that exposure to multiple metals was associated with increased ARC risk. Further research is needed to verify these findings in the future.

Association between multiple metal(loid)s exposure and renal function: a cross-sectional study from southeastern China.

In the real world, humans are exposed to multiple metal(loid)s (designated hereafter metals) that contain essential metals as well as toxic metals. Exposure to the metal mixture was assumed to be associated with renal function impairment; however, there is no consensus on available studies. Therefore, we here explored the association between multiple metals exposure and indicators of renal function in the general population from southeastern China. A total of 11 metals with 6 human essential metals and 5 toxic metals were determined in the selected 720 subjects. In addition, serum uric acid (SUA), serum creatinine (SCR), and the estimated glomerular filtration rate (eGFR) were measured or calculated as indicators of renal function. Using multiple flexible statistical models of generalized linear model, elastic net regression, and Bayesian kernel machine regression, the joint as well as the individual effect of metals within the mixture, and the interactions between metals were explored. When exposed to the metal mixture, the statistically non-significantly increased SUA, the significantly increased SCR, and the significantly declined eGFR were observed. In addition, the declined renal function may be primarily attributed to lead (Pb), arsenic (As), and nickel (Ni) exposure. Finally, interactions, such as the synergistic effect between Pb and Mo on SUA, whereas the antagonistic effect between Ni and Cd on SCR and eGFR were identified. Our finding suggests that combined exposure to multiple metals would impair renal function. Therefore, reducing exposure to toxic heavy metals of Pb, As, and Cd and limiting exposure to the human essential metal of Ni would protect renal function.

Associations between multiple heavy metals exposure and neural damage biomarkers in welders: A cross-sectional study.

BACKGROUND: Both occupational and environmental exposure to heavy metals are associated with various neurodegenerative diseases. However, limited evidence is available on the potential effects of exposure to metallic mixtures and neural damage. OBJECTIVES: This study aimed to evaluate the association between metal mixtures in urine and neural damage biomarkers in welders. METHODS: In this cross-sectional study, a total of 186 workers were recruited from steel mills. Twenty-three metals in urine were measured by inductively coupled plasma mass spectrometry. Serum neural damage biomarkers, including neurofilament light chain (NfL), sphingosine-1-phosphate (S1P), prolactin (PRL), and dopamine (DA) were detected using enzyme-linked immunosorbent assay kits. Multivariable linear regression, Bayesian kernel machine regression (BKMR), and Quantile g-computation (QG-C) were employed to estimate the association between metals exposure and neural damage biomarkers. RESULTS: Inverted u-shaped associations of nickel with NfL, S1P, and DA were observed in the BKMR model. A non-linear relationship was also found between Fe and PRL. Urinary cobalt was positively associated with serum PRL and had the strongest positive weights in the QG-C model. Urinary lead was associated with higher serum S1P levels. We also found the interaction among nickel, zinc, arsenic, strontium, iron, and lead with the neural damage biomarkers. CONCLUSION: This study provides new evidence of a direct association between metal mixture exposure and the serum biomarkers of neural damage. Several metals Ni, Co, Pb, Sr, As and Fe, may have adverse effects on the nervous system, while Zn may have neuroprotective effects.

Associations of exposure to multiple metals with blood pressure and hypertension: A cross-sectional study in Chinese preschool children.

Exposure to metals might be a risk factor for hypertension, which contributes largely to the global burden of disease and mortality. However, relevant epidemiological studies of associations between metals exposure with hypertension among preschoolers are limited. This study aimed to explore the associations of urine metals with blood pressure and hypertension among Chinese preschoolers. A total of 1220 eligible participants who had urine metals measurement, blood pressure measurements, and relevant covariates were included in this cross-sectional study. Urine concentrations of metals were measured by inductively coupled plasma mass spectrometer. The single and multiple metals regression models were used to investigate the associations of urine metal with blood pressure and the risk of hypertension after adjusting for potential confounders. We observed urine concentrations of chromium, iron, and barium were negatively associated with levels of systolic blood pressure, diastolic blood pressure and the risk of hypertension in the single metal model (all P-FDR adjustment <0.05). Significant associations of urine chromium concentrations with systolic blood pressure, diastolic blood pressure and the risk of hypertension were found in the multi-metal model (ß or OR (95% confidence interval) was -3.07 (-5.12, -1.02), -2.25 (-4.29, -0.22), and 0.51 (0.26, 0.97) for 3rd quartile, compared with 1st quartile, respectively). The same association was found for barium concentrations in the multi-metal model, while none of the associations among iron quartiles was significant. In addition, urine chromium, iron and barium may have joint effects on systolic blood pressure, diastolic blood pressure and hypertension. Children's age and body mass index could modify the associations of chromium, iron, and barium concentrations with blood pressure. Our findings suggested that exposure to chromium, iron, and barium was inversely associated with blood pressure and hypertension among preschool children. These findings need further validation in prospective studies.