BACKGROUND: Rapid 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.
OBJECTIVE: This 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.
METHODS: This 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.
RESULTS: During 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.
CONCLUSIONS: Vanadium 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.

Chronic environmental exposure to toxic heavy metals, which often occurs as a mixture through occupational and industrial sources, has been implicated in various neurological disorders, including Parkinsonism. Vanadium pentoxide (V2O5) typically presents along with manganese (Mn), especially in welding rods and high-capacity batteries, including electric vehicle batteries; however, the neurotoxic effects of vanadium (V) and Mn co-exposure are largely unknown. In this study, we investigated the neurotoxic impact of MnCl2, V2O5, and MnCl2-V2O5 co-exposure in an animal model. C57BL/6 mice were intranasally administered either de-ionized water (vehicle), MnCl2 (252 µg) alone, V2O5 (182 µg) alone, or a mixture of MnCl2 (252 µg) and V2O5 (182 µg) three times a week for up to one month. Following exposure, we performed behavioral, neurochemical, and histological studies. Our results revealed dramatic decreases in olfactory bulb (OB) weight and levels of tyrosine hydroxylase, dopamine, and 3,4-dihydroxyphenylacetic acid in the treatment groups compared to the control group, with the Mn/V co-treatment group producing the most significant changes. Interestingly, increased levels of α-synuclein expression were observed in the substantia nigra (SN) of treated animals. Additionally, treatment groups exhibited locomotor deficits and olfactory dysfunction, with the co-treatment group producing the most severe deficits. The treatment groups exhibited increased levels of the oxidative stress marker 4-hydroxynonenal in the striatum and SN, as well as the upregulation of the pro-apoptotic protein PKCδ and accumulation of glomerular astroglia in the OB. The co-exposure of animals to Mn/V resulted in higher levels of these metals compared to other treatment groups. Taken together, our results suggest that co-exposure to Mn/V can adversely affect the olfactory and nigral systems. These results highlight the possible role of environmental metal mixtures in the etiology of Parkinsonism.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.

The present study was aimed at evaluating the influence of the subchronic exposure of cadmium (Cd), copper (Cu), and nickel (Ni) mixtures on affective behaviors, memory impairment, and oxidative stress (OS) in the hippocampus. Thirty male Wistar rats were divided into 5 equal groups. Group 1 (control) received a saline solution (NaCl 0.9%). Groups 2, 3, and 4 received Cd (0.25 mg/kg), Cu (0.5 mg/kg), and Ni (0.25 mg/kg), respectively, while group 5 received a Cd, Cu, and Ni mixture through intraperitoneal injections for 2 months. After the exposure period, all rats were submitted to behavioral tests. Subsequently, OS markers and histological changes in the rats\' hippocampi were assessed. Results showed that a 2-month exposure to the mixtures of metals (MM) has led to higher anxiety-like and depression-like behaviors and cognitive deficits in rats when compared to the control group and the individual metals. Furthermore, the MM induced heightened OS, evidenced by the rise in lipid peroxidation and nitric oxide levels. These effects were accompanied by a decrease in superoxide dismutase and catalase activities in the hippocampus. The histopathological analysis also supported that MM caused a neuronal loss in the CA3 sub-region. Overall, this study underscores that subchronic exposure to the Cd, Cu, and Ni mixture induces an OS status and histological changes in the hippocampus, with important affective and cognitive behavior variations in rats.

Exposure to metal mixtures compromises the immune system, with the complement system connecting innate and adaptive immunity. Herein, we sought to explore the relationships between blood cell metal mixtures and the third and fourth components of serum complement (C3, C4). A total of 538 participants were recruited in November 2017, and 289 participants were followed up in November 2021. We conducted a cross-sectional analysis at baseline and a longitudinal analysis over 4 years. Least Absolute Shrinkage and Selection Operator (LASSO) was employed to identify the primary metals related to serum C3, C4; generalized linear model (GLM) was further used to evaluate the cross-sectional associations of the selected metals and serum C3, C4. Furthermore, participants were categorized into three groups according to the percentage change in metal concentrations over 4 years. GLM was performed to assess the associations between changes in metal concentrations and changes in serum C3, C4 levels. At baseline, each 1-unit increase in log10-transformed in magnesium, manganese, copper, rubidium, and lead was significantly associated with a change in serum C3 of 0.226 (95% CI: 0.146, 0.307), 0.055 (95% CI: 0.022, 0.088), 0.113 (95% CI: 0.019, 0.206), - 0.173 (95% CI: - 0.262, - 0.083), and - 0.020 (95% CI: - 0.039, - 0.001), respectively. Longitudinally, decreased copper concentrations were negatively associated with an increment in serum C3 levels, while decreased lead concentrations were positively associated with an increment in serum C3 levels. However, no metal was found to be primarily associated with serum C4 in LASSO, so we did not further explore the relationship between them. Our research indicates that copper and lead may affect complement system homeostasis by influencing serum C3 levels. Further investigation is necessary to elucidate the underlying mechanisms.

Heavy metals are now persistently present in living things\' environments, in addition to their potential toxicity. Therefore, the aim of this study was to utilize D. melanogaster to determine the biological effects induced by different heavy metals including cadmium chloride (CdCl2), copper (II) sulfate pentahydrate (CuSO 4.5 H2O), and silver nitrate (AgNO3). In vivo experiments were conducted utilizing three low and environmentally relevant concentrations from 0.01 to 0.5 mM under single and combined exposure scenarios on D. melanogaster larvae. The endpoints measured included viability, reactive oxygen species (ROS) generation and genotoxic effects using Comet assay and the wing-spot test. Results indicated that tested heavy metals were not toxic in the egg-to adult viability. However, combined exposure (CdCl2+AgNO3 and CdCl2+AgNO3+CuSO 4.5 H2O) resulted in significant genotoxic and unfavorable consequences, as well as antagonistic and/or synergistic effects on oxidative damage and genetic damage.

BACKGROUND: Dental caries is the most common non-communicable human disease, yet little is known about the role of environmental metals, despite teeth consisting of a hard matrix of trace elements. We conducted a cross-sectional study of associations between environmental metals and objective assessment of dental caries and subjective assessments of oral health among a representative sample of U.S. children and adolescents.
METHODS: Data were from the 2017-March 2020 pre-pandemic data file of the National Health and Nutrition Examination Survey (NHANES). To account for metal mixtures, we used weighted quantile sum (WQS) regression to estimate the joint impact of multiple trace elements assessed in blood and urine with oral disease outcomes.
RESULTS: The blood metal mixture index was associated with a 32% (95% CI: 1.11, 1.56) increased risk of decayed surfaces while the urine metal mixture index was associated with a 106%, RR (95% CI = 2.06 (1.58, 2.70) increased caries risk. For both blood and urine, Mercury (Hg) had the largest contribution to the mixture index followed by Lead (Pb). The WQS blood metal mixture index was also significantly associated with poorer self-rated oral health, although the magnitude of the association was not as strong as for the objective oral disease measures, RR (95% CI) = 1.04 (1.02, 1.07).
CONCLUSIONS: Increased exposure to a metal mixture was significantly related to poorer objective and subjective oral health outcomes among U.S. children and adolescents. These are among the first findings showing that metal mixtures are a significant contributor to poor oral health.

Children are frequently exposed to various biological trace metals, some essential for their development, while others can be potent neurotoxicants. Furthermore, the inflammatory and metabolic conditions associated with obesity may interact with and amplify the impact of metal exposure on neurodevelopment. However, few studies have assessed the potential modification effect of body mass index (BMI). As a result, we investigated the role of child BMI phenotype on the relationship between prenatal exposure to metal mixtures and temporal processing. Leveraging the PROGRESS birth cohort in Mexico City, children (N = 563) aged 6-9 years completed a Temporal Response Differentiation (TRD) task where they had to hold a lever down for 10-14 s. Blood and urinary metal (As, Pb, Cd, and Mn) measurements were collected from mothers in the 2nd and 3rd trimesters. Child BMI z-scores were dichotomized to normal (between -2 and +0.99) and high (≥1.00). Covariate-adjusted weighted quantile sum (WQS) regression models were used to estimate and examine the combined effect of metal biomarkers (i.e., blood and urine) on TRD measures. Effect modification by the child\'s BMI was evaluated using 2-way interaction terms. Children with a high BMI and greater exposure to the metal mixture during prenatal development exhibited significant temporal processing deficits compared to children with a normal BMI. Notably, children with increased exposure to the metal mixture and higher BMI had a decrease in the percent of tasks completed (β = -10.13; 95 % CI: -19.84, -0.42), number of average holds (β = -2.15; 95 % CI: -3.88, -0.41), longer latency (β = 0.78; 95 % CI: 0.13, 1.44), and greater variability in the standard deviation of the total hold time (β = 2.08; 95 % CI: 0.34, 3.82) compared to normal BMI children. These findings implicate that high BMI may amplify the effect of metals on children\'s temporal processing. Understanding the relationship between metal exposures, temporal processing, and childhood obesity can provide valuable insights for developing targeted environmental interventions.

The most common construction material used in Taiwan is concrete, potentially contaminated by geologic heavy metals (HMs). Younger children spend much time indoors, increasing HM exposure risks from household dust owing to their behaviors. We evaluated arsenic (As), cadmium (Cd), and lead (Pb) concentrations in fingernails among 280 preschoolers between 2017 and 2023. We also analyzed HM concentrations, including As, Cd, Pb, chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), iron (Fe), and manganese (Mn), in 90 household dust and 50 road dust samples from a residential area where children lived between 2019 and 2021 to deepen the understanding of sources and health risks of exposure to HMs from household dust. The average As, Cd, and Pb concentrations in fingernails were 0.12 ± 0.06, 0.05 ± 0.05, and 0.95 ± 0.77 μg/g, respectively. Soil parent materials, indoor construction activities, vehicle emissions, and mixed indoor combustion were the pollution sources of HMs in household dust. Higher Cr and Pb levels in household dust may pose non-carcinogenic risks to preschoolers. Addressing indoor construction and soil parent materials sources is vital for children\'s health. The finding of the present survey can be used for indoor environmental management to reduce the risks of HM exposure and avoid potential adverse health effects for younger children.

BACKGROUND: Machine learning models have promising applications in capturing the complex relationship between mixtures of exposures and outcomes.
OBJECTIVE: Our study aimed at introducing an explainable machine learning (EML) model to assess the association between metal mixtures with potentially opposing renal effects and renal function in middle-aged and older adults.
METHODS: This study extracted data from two cycle years of the National Health and Nutrition Examination Survey (NHANES). Participants aged 45 years or older with complete data on six metals (lead, cadmium, manganese, mercury, and selenium) and related covariates were enrolled. The EML model was developed by the optimized machine learning model together with Shapley Additive exPlanations (SHAP) to assess the chronic kidney disease (CKD) risk with metal mixtures. The results from EML were further compared in detail with multiple logistic regression (MLR) and Bayesian kernel machine regression (BKMR).
RESULTS: After adjusting for included covariates, MLR pointed out the lead and arsenic were generally positively associated with CKD, but manganese had a negative association. In the BKMR analysis, each metal was found to have a non-linear association with the risk of CKD, and interactions can exist between metals, especially for arsenic and lead. The EML ranked the feature importance: lead, manganese, arsenic and selenium were close behind in importance after gender, age or BMI for participants with CKD. Strong interactions between mercury and lead, manganese and cadmium and arsenic and manganese were identified by partial dependence plot (PDP) of SHAP and bivariate exposure-response effect plots of BKMR. The EML model determined the \"trigger point\" at which the risk of CKD abruptly changed.
CONCLUSIONS: Co-exposure to metals with different nephrotoxicity could have different joint association with renal function, and EML can be a powerful method for studying complex exposure mixtures.