Co-exposure to perfluoroalkyl acids and heavy metals mixtures associated with impaired kidney function in adults: A community-based population study in China

Analysis of relationship between mixed heavy metal exposure and early renal damage based on a weighted quantile sum regression and Bayesian kernel machine regression model

BACKGROUND

Occupation, environmental heavy metal exposure, and renal function impairment are closely related. The relationship between mixed metal exposure and chronic renal injury is inadequately described, and the interaction between each metal is poorly explored.

OBJECTIVE

This cross-sectional study assessed mixed heavy metal exposure in the general population and their relationship with early renal impairment, as well as possible interactions between metals.

METHODS

The study was conducted in two communities in Taiyuan City in northern China. Multiple linear regression, weighted quantile sum (WQS) and bayesian kernel machine regression (BKMR) regression were used to explore the relationship of mixed heavy metal exposure with indicators of early kidney injury (N-acetyl-β-D- glucosidase (UNAG), urinary albumin (UALB)). Meanwhile, BKMR was used to explore the possible interactions between mixed heavy metal and indicators of early kidney injury.

RESULTS

Based on the WQS regression results, we observed adjusted WQS coefficient β (β-WQS) of 0.711 (95% CI: 0.543, 0.879). Notably, this change was primarily driven by As (35.6%) and Cd (22.5%). In the UALB model, the adjusted β-WQS was 0.657 (95% CI: 0.567, 0.747), with Ni (30.5%), Mn (22.1%), Cd (21.2%), and As (18.6%) exhibiting higher weights in the overall effect. The BKMR results showed a negative interaction between As and other metals in the UNAG and UALB models, a positive interaction between Mn and Ni and other metals. No significant pairwise interaction was observed in the association of metals with indicators of early kidney injury.

CONCLUSION

Through multiple linear regression, WQS regression, and BKMR analyses, we found that exposure to mixed heavy metals such as Cd, Cr, Pb, Mn, As, Co and Ni was positively correlated with UNAG and UALB. Moreover, there are complex interactions between two or more heavy metals in more than one direction.

Key drivers of the oxidative potential of PM2.5 in Beijing in the context of air quality improvement from 2018 to 2022

The mass concentration of atmospheric particulate matter (PM) has been continuously decreasing in the Beijing-Tianjin-Hebei region. However, health endpoints do not exhibit a linear correlation with PM mass concentrations. Thus, it is urgent to clarify the prior toxicological components of PM to further improve air quality. In this study, we analyzed the long-term oxidative potential (OP) of water-soluble PM2.5, which is generally considered more effective in assessing hazardous exposure to PM in Beijing from 2018 to 2022 based on the dithiothreitol assay and identified the crucial drivers of the OP of PM2.5 based on online monitoring of air pollutants, receptor model, and random forest (RF) model. Our results indicate that dust, traffic, and biomass combustion are the main sources of the OP of PM2.5 in Beijing. The complex interactions of dust particles, black carbon, and gaseous pollutants (nitrogen dioxide and sulfur dioxide) are the main factors driving the OP evolution, in particular, leading to the abnormal rise of OP in Beijing in 2022. Our data shows that a higher OP is observed in winter and spring compared to summer and autumn. The diurnal variation of the OP is characterized by a declining trend from 0:00 to 14:00 and an increasing trend from 14:00 to 23:00. The spatial variation in OP of PM2.5 was observed as the OP in Beijing is lower than that in Shijiazhuang, while it is higher than that in Zhenjiang and Haikou, which is primarily influenced by the distribution of black carbon. Our results are of significance in identifying the key drivers influencing the OP of PM2.5 and provide new insights for advancing air quality improvement efforts with a focus on safeguarding human health in Beijing.

Metabolomics perspectives into the co-exposure effect of polycyclic aromatic hydrocarbons and metals on renal function: A meet-in-the-middle approach

Studies on the dose effects of kidney impairment and metabolomes in co-exposure to polycyclic aromatic hydrocarbons (PAHs) and metals are limited. We aimed to identify overall associations and metabolic perturbations in 130 participants (53 petrochemical workers and 77 controls) exposed to a PAHs-metals mixture in Southern China. The urinary 7 hydroxylated PAHs and 15 metal(loid)s were determined, and serum creatinine, beta-2 microglobulin, and estimated glomerular filtration rate were health outcomes. The liquid chromatography-mass spectrometry-based method was applied to serum metabolomics. Generalized weighted quantile sum (gWQS) regressions were used to estimate the overall dose-response relationships, and pathway analysis, "meet-in-the-middle" approach, and mediation effect analyses were conducted to identify potential metabolites and biological mechanisms linking exposure with nephrotoxic effects. Our results indicated that renal function reduction was associated with a PAHs-metals mixture in a dose-dependent manner, and 1-hydroxynaphthalene and copper were the most predominant contributors among the two families of pollutants. Furthermore, the metabolic disruptions associated with the early onset of kidney impairment induced by the combination of PAHs and metals encompassed pathways such as phenylalanine-tyrosine-tryptophan biosynthesis, phenylalanine metabolism, and alpha-linolenic acid metabolism. In addition, the specifically identified metabolites demonstrated excellent potential as bridging biomarkers connecting the reduction in renal function with the mixture of PAHs and metals. These findings shed light on understanding the overall associations and metabolic mechanism of nephrotoxic effects of co-exposure to PAHs and metals.

Cross-sectional and Longitudinal Associations Between Metal Mixtures and Serum C3, C4: Result from the Manganese‑exposed 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.

The mediating role of accelerated biological aging in the association between blood metals and cognitive function

Aging is a key risk factor in cognitive diseases. Recently, metal exposures were found associated with both biological aging and cognitive function. Here, we aim to evaluate the associations of blood metals with cognitive function and the mediated effect of biological aging. Fourteen metals were detected and biological age was calculated through Klemera and Doubal method among 514 adults in Beijing, China. The generalized linear models indicated that the copper (Cu), molybdenum (Mo), and strontium (Sr) were positively associated with biological aging [βCu (95% CI): 12.76 (9.26, 16.27); βMo (95% CI): 1.50 (0.15, 2.85)], and βSr (95% CI): 1.86 (0.68, 3.03)], while vanadium (V) was inversely related to biological aging [βV (95% CI): -0.76 (-1.48, -0.05)]. Subsequently, Cu, lead (Pb), selenium (Se), and biological aging were associated with cognitive function and further mediation analyses confirmed that biological aging partially mediated (33.98%, P = 0.019) the association of Cu and cognitive function. Additionally, we constructed a lifestyle index that implied the modifiable healthy lifestyle could slow aging to attenuate the detrimental effect of metals on cognition. Our findings provide insights into the potential pathways linking multiple metals exposure to aging and cognition and underscore the importance of adopting healthy lifestyles.

Association of Perfluoroalkyl and polyfluoroalkyl substances (PFASs) exposures and the risk of systemic lupus erythematosus: a case-control study in China

Perfluoroalkyl and polyfluoroalkyl substances (PFASs) may have a role in impaired health. However, the data on the association between PFASs and Systemic lupus erythematosus (SLE) have been limited. We designed a population-based case-control study in China and evaluated the association. 100 normal persons (Control) and 100 SLE patients (Case) were obtained from 113 controls and 125 cases according to matching conditions. Serum samples were collected by venipuncture for UHPLC-MRM-MS Analysis to obtain the concentration of five PFASs in participants. Demographic characterization description was performed for the two groups of participants, the PFASs concentration distribution of the two groups was described and compared, then divided into three tiers (< 50th, 50th ~ 75th, > 75th) for subsequent analysis. Conditional logistic regression models were utilized to calculate the odds ratios (ORs) and 95% CIs for SLE. Relationship between changes in the concentration of PFASs and the risk of SLE assessed by restricted cubic spline. As the highest serum levels of the five PFASs tested in this study population, the highest perfluoroundecanoic acid (PFUnA) quartile had a 2.78-fold (95%CI: 1.270, 6.10) compared with the lowest quartile of PFUnA exposure, other types of PFASs also showed high association with SLE as well as PFASs mixture. Additionally, the exposure of PFASs exist a dose-response relationship (ptrend < 0.05). This risk association remained be found after adjusting the covariates in model 1 (adjustment of BMI) and in model 2(adjustment of BMI, smoking, drinking, hypertension and leukocyte). The restricted cubic spline illustrated a gradual increase in the possible risk of SLE with the increasing exposure of PFASs components levels. Our study firstly revealed that PFASs are risk factors for SLE and PFASs exposures are associated with SLE risk in a dose - response manner. Evidence from larger and more adequately powered cohort studies is needed to confirm our results.

The correlation of urinary strontium with the risk of chronic kidney disease among the general United States population

Background

This study sought to illustrate whether urinary strontium levels were related to developing chronic kidney disease (CKD) in the United States population.

Methods

A total of 5,005 subjects were identified from the National Health and Nutrition Examination Survey 2011-2016. Survey-weighted logistic regression analysis, multivariate linear regression analysis, restricted cubic spline (RCS) plots curve and stratified analyses were undertaken to explicate the correlation between urinary strontium and CKD.

Results

With the increase of urinary strontium, the incidence rate of CKD and urinary albumin to creatinine ratio (UACR) levels gradually decreased, and estimated glomerular filtration rate (eGFR) levels gradually increased. After controlling all confounders, only urinary strontium in the fourth quartile was correlated to a lower CKD prevalence (OR: 0.59; 95% CI, 0.44-0.79) compared to the lowest quartile. Multivariate linear regression analysis showed that urinary strontium was positively correlated with eGFR but negatively with UACR. RCS curve suggested a nonlinear relationship between urinary strontium and CKD (P for non-linearity <0.001). Stratified analyses indicated no significant difference in the correlation between urinary strontium and CKD among different subgroups.

Conclusion

Urinary strontium was strongly correlated with a low risk of CKD, and this association was non-linear among the US population.

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.

Maternal co-exposure to mercury and perfluoroalkyl acid isomers and their associations with child neurodevelopment in a Canadian birth cohort

BACKGROUND

Perfluoroalkyl acids (PFAAs) within the broader class of per- and polyfluoroalkyl substances (PFAS) are present in human serum as isomer mixtures, but epidemiological studies have yet to address isomer-specific associations with child development and behavior.

OBJECTIVES

To examine associations between prenatal exposure to 25 PFAAs, including perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) isomers, and child neurodevelopment among 490 mother-child pairs in a prospective Canadian birth cohort, the Alberta Pregnancy Outcomes and Nutrition (APrON) study. To consider the influence of a classic neurotoxicant, total mercury (THg), based on its likelihood of co-exposure with PFAAs from common dietary sources.

METHODS

Maternal blood samples were collected in the second trimester and child neurodevelopment was assessed at 2 years of age using the Bayley Scales of Infant and Toddler Development, 3rd Edition (Bayley-III). Linear or curvilinear multiple regression models were used to examine associations between exposures and neurodevelopment outcomes.

RESULTS

Select PFAAs were associated with lower Cognitive composite scores, including perfluoroheptanoate (PFHpA) (β = -0.88, 95% confidence interval (CI): -1.7, -0.06) and perfluorododecanoate (PFDoA) (β = -2.0, 95% CI: -3.9, -0.01). Non-linear relationships revealed associations of total PFOS (β = -4.4, 95% CI: -8.3, -0.43), and linear-PFOS (β = -4.0, 95% CI: -7.5, -0.57) and 1m-PFOS (β = -1.8, 95% CI: -3.3, -0.24) isomers with lower Language composite scores. Although there was no effect modification, including THg interaction terms in PFAA models revealed negative associations between perfluorononanoate (PFNA) and Motor (β = -3.3, 95% CI: -6.2, -0.33) and Social-Emotional (β = -3.0, 95% CI: -5.6, -0.40) composite scores.

DISCUSSION

These findings reinforce previous reports of adverse effects of maternal PFAA exposure during pregnancy on child neurodevelopment. The unique hazards posed from isomers of PFOS justify isomer-specific analysis in future studies. To control for possible confounding, mercury co-exposure may be considered in studies of PFAAs.

Metals and per- and polyfluoroalkyl substances mixtures and birth outcomes in the New Hampshire Birth Cohort Study: Beyond single-class mixture approaches

We aimed to investigate the joint, class-specific, and individual impacts of (i) PFAS, (ii) toxic metals and metalloids (referred to collectively as "metals"), and (iii) essential elements on birth outcomes in a prospective pregnancy cohort using both established and recent mixture modeling approaches. Participants included 537 mother-child pairs from the New Hampshire Birth Cohort Study. Concentrations of 6 metals and 5 PFAS were measured in maternal toenail clippings and plasma, respectively. Birth weight, birth length, and head circumference at birth were abstracted from medical records. Joint, index-wise, and individual associations of the metals and PFAS concentrations with birth outcomes were evaluated using Bayesian Kernel Machine Regression (BKMR) and Bayesian Multiple Index Models (BMIM). After controlling for potential confounders, the metals-PFAS mixture was associated with a larger head circumference at birth, which was driven by manganese. When using BKMR, the difference in the head circumference z-score when changing manganese from its 25th to 75th percentiles while holding all other mixture components at their medians was 0.22 standard deviations (95% posterior credible interval [CI]: -0.02, 0.46). When using BMIM, the posterior mean of index weight estimates assigned to manganese for head circumference z-score was 0.72 (95% CI: 0, 0.99). Prenatal exposure to the metals-PFAS mixture was not associated with birth weight or birth length by either BKMR or BMIM. Using both traditional and new mixture modeling approaches, prenatal exposure to manganese was associated with a larger head circumference at birth after accounting for exposure to PFAS and multiple toxic and essential metals.

Combined Effects of Multiple Per- and Polyfluoroalkyl Substances Exposure on Allostatic Load Using Bayesian Kernel Machine Regression

This study aims to investigate the combined effects of per- and polyfluoroalkyl substances (PFAS) on allostatic load, an index of chronic stress that is linked to several chronic diseases, including cardiovascular disease and cancer. Using data from the National Health and Nutrition Examination Survey (NHANES) 2007-2014, this study examines the relationship between six PFAS variables (PFDE, PFNA, PFOS, PFUA, PFOA, and PFHS) and allostatic load using Bayesian Kernel Machine Regression (BKMR) analysis. The study also investigates the impact of individual and combined PFAS exposure on allostatic load using various exposure-response relationships, such as univariate, bivariate, or multivariate models. The analysis reveals that the combined exposure to PFDE, PFNA, and PFUA had the most significant positive trend with allostatic load when it was modeled as a binary variable, while PFDE, PFOS, and PFNA had the most significant positive trend with allostatic load when modeled as a continuous variable. These findings provide valuable insight into the consequences of cumulative exposure to multiple PFAS on allostatic load, which can help public health practitioners identify the dangers associated with potential combined exposure to select PFAS of interest. In summary, this study highlights the critical role of PFAS exposure in chronic stress-related diseases and emphasizes the need for effective strategies to minimize exposure to these chemicals to reduce the risk of chronic diseases. It underscores the importance of considering the combined effects of PFAS when assessing their impact on human health and offers valuable information for policymakers and regulators to develop strategies to protect public health.

The Association of Combined Per- and Polyfluoroalkyl Substances and Metals with Allostatic Load Using Bayesian Kernel Machine Regression

Background/Objective: This study aimed to investigate the effect of exposure to per- and polyfluoroalkyl substances (PFAS), a class of organic compounds utilized in commercial and industrial applications, on allostatic load (AL), a measure of chronic stress. PFAS, such as perfluorodecanoic acid (PFDE), perfluorononanoic acid (PFNA), perfluorooctane sulfonic acid (PFOS), perfluoroundecanoic acid (PFUA), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonic acid (PFHS), and metals, such as mercury (Hg), barium (Ba), cadmium (Cd), cobalt (Co), cesium (Cs), molybdenum (Mo), lead (Pb), antimony (Sb), thallium (TI), tungsten (W), and uranium (U) were investigated. This research was performed to explore the effects of combined exposure to PFAS and metals on AL, which may be a disease mediator. Methods: Data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2014 were used to conduct this study on persons aged 20 years and older. A cumulative index of 10 biomarkers from the cardiovascular, inflammatory, and metabolic systems was used to calculate AL out of 10. If the overall index was ≥ 3, an individual was considered to be chronically stressed (in a state of AL). In order to assess the dose-response connections between mixtures and outcomes and to limit the effects of multicollinearity and other potential interaction effects between exposures, Bayesian kernel machine regression (BKMR) was used. Results: The most significant positive trend between mixed PFAS and metal exposure and AL was revealed by combined exposure to cesium, molybdenum, PFHS, PFNA, and mercury (posterior inclusion probabilities, PIP = 1, 1, 0.854, 0.824, and 0.807, respectively). Conclusions: Combined exposure to metals and PFAS increases the likelihood of being in a state of AL.

Associations between multiple metals exposure and biological aging: Evidence from the Dongfeng-Tongji cohort

Aging is related to a progressive decline in physiological functions and is affected by environmental factors. Metal exposures are linked with many health effects, but have poorly understood associations with aging. In this study, a total of 33,916 participants from the Dongfeng-Tongji cohort were included to establish biological age (BA) predictors by using recent advanced algorithms, Klemera and Doubal method (KDM) and Mahalanobis distance. Two biological aging indexes (BAIs), recorded as KDM-accel [the residual from regressing KDM-BA on chronological age] and physiological dysregulation (PD), were separately defined and tested on their associations with mortality by using Cox proportional hazard models. Among 3320 subjects with laboratory determinations of 23 metals in plasma, the individual and overall associations between these metals and BAIs were evaluated by using multiple-linear regression and weighted quantile sum (WQS) models. Both BAIs were prospectively associated with all-cause mortality among the whole participants [KDM-accel: HR(95%CI) = 1.23(1.18, 1.29); PD: HR(95%CI) = 1.37(1.31, 1.42)]. Each 1-unit increment in ln-transformed strontium and molybdenum were cross-sectionally associated with a separate 0.71- and 0.34-year increase in KDM-accel, and each 1 % increment in copper, rubidium, strontium, cobalt was cross-sectionally associated with a separate 0.10 %, 0.10 %, 0.09 %, 0.02 % increase in PD (all FDR < 0.05). The WQS models observed mixture effects of multi-metals on aging, with a 0.20-year increase in KDM-accel and a 0.04 % increase in PD for each quartile increase in ln-transformed concentrations of all metals [KDM-accel: β(95%CI) = 0.20(0.08, 0.32); PD: β(95%CI) = 0.04(0.02, 0.06)]. Our findings revealed that plasma strontium, molybdenum, copper, rubidium and cobalt were associated with accelerated aging. Multi-metals exposure showed mixture effects on the aging process, which highlights potential preventative interventions.