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.

Body surface area is a predictor of 90-day all-cause mortality in critically ill patients with acute kidney injury.

OBJECTIVE: To clarify the prognosis effect between body surface area (BSA) and patients with acute kidney injury (AKI), we attempted to analyze the association between BSA and 90-day all-cause mortality in critically ill patients with AKI. METHODS: Clinical data of 9195 critically ill patients with AKI were retrieved from the Medical Information Mart for Intensive Care III database were then retrospectively analyzed. BSA were calculated using the Mosteller formula. We analyzed the correlation between BSA and 90-day all-cause mortality in critically ill patients with AKI based on Kaplan-Meier curve analysis and adjusted Cox regression model. RESULTS: Of the 9195 critically ill patients with AKI, there were 3778 (41.1%) female patients and 2001 90-day all-cause deaths (female: 22.2%, male: 21.5%). Kaplan-Meier curve analysis revealed that a lower body surface area indicated a higher 90-day all-cause mortality in both male and female patients with AKI (log-rank P < 0.001). Cox regression model showed that a higher BSA was independently correlated with a lower 90-day all-cause mortality (female: hazard ratio=0.657, 95% confidence interval: 0.550-0.784, P < 0.001; male: hazard ratio=0.655, 95% confidence interval: 0.565-0.760, P < 0.001). CONCLUSIONS: BSA was negatively correlated with 90-day all-cause mortality in critically ill patients with AKI. BSA can therefore be used as a prognostic indicator for poor outcomes in critically ill patients with AKI.

Cross-sectional and Longitudinal Associations Between Metal Mixtures and Serum C3, C4: Result from the Manganese­exposed Workers Healthy Cohort.

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.

Associations of metal mixtures with thyroid function and potential interactions with iodine status: results from a cross-sectional study in MEWHC.

Few studies are available on associations between metal mixture exposures and disrupted thyroid hormone homeostasis; particularly, the role of iodine status was ignored. Here, we aimed to explore the cross-sectional relationship of blood cell metals with thyroid homeostasis and explore the potential modifying effect of iodine status. Among 328 workers from the manganese-exposed workers healthy cohort (MEWHC), we detected thyroid function parameters: thyroid stimulating hormone (TSH), total triiodothyronine (TT3), free triiodothyronine (FT3), total tetraiodothyronine (TT4), free tetraiodothyronine (FT4) as well as calculated sum activity of peripheral deiodinases (GD) and thyroid's secretory capacity (GT). Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure 22 metal concentrations in blood cells. Based on the consistent results of least absolute shrinkage and selection operator (LASSO) and Bayesian kernel machine regression (BKMR) analyses, there were significant positive associations between copper and TSH (ß = 2.016), iron and FT4 (ß = 0.403), titanium and GD (ß = 0.142), nickel and GD (ß = 0.057), and negative associations between copper and FT4 (ß = - 0.226), selenium and GD (ß = - 0.332), among the participants. Interestingly, we observed an inverted-U shape relationship between magnesium and FT4. Furthermore, we found a synergistic effect between arsenic and copper on the TSH level, while antagonistic effects between nickel and copper as well as nickel and selenium on the TSH level. We observed a modified effect of iodine status on association between strontium and GD (Pinteraction = 0.026). It suggests metal mixture exposures can alter thyroid homeostasis among the occupational population, and deiodinase activity had a modified effect on association between strontium and GD. Validation of these associations and elucidation of underlying mechanisms require further researches in the future.