Emerging And Legacy PFAS And Cytokine Homeostasis In Women of Childbearing Age

The effect of legacy and emerging per- and polyfluoroalkyl substances (PFAS) on cytokine homeostasis in human remains poorly understood. This study aimed to evaluate the associations between legacy and emerging PFAS and cytokine profiles, and identify the main contributors to the disturbance of cytokine homeostasis. We quantified 21 PFAS in 198 Chinese women of childbearing age from 2015 to 2016. 13 cytokines were measured using the Meso Scale Discovery U-PLEX and V-PLEX platforms. The associations between PFAS exposure and cytokine levels were assessed using multiple linear regression (single-exposure), and Bayesian kernel machine regression (BKMR) models (PFAS mixture exposure). In single PFAS models, legacy and alternative PFAS were positively associated with Th1 and Treg cytokines, and negatively associated with Th2 and Th17 cytokines. For instance, each ln-unit increase in 6:2 chlorinated perfluoroalkyl ether sulfonic acid (6:2 Cl-PFESA), perfluorooctanoic acid (PFOA), and perfluorooctane sulfonate (PFOS) was associated with a decrease in IL-10 by -0.228 (95% CI: -0.336, -0.120), -0.153 (95% CI: -0.277, -0.030), and -0.174 (95% CI: -0.339, -0.010), respectively. The BKMR model showed a significantly positive association of PFAS mixture with TGF-β and a negative association with IL-10. Overall, these results indicate that both legacy and emerging PFAS may affect the homeostasis of cytokines.

Association of Rare Earth Elements with Passive Smoking among Housewives in Shanxi Province, China

Background: Rare earth elements (REEs) are emerging contaminants. Previous studies reported the association between REEs and active smoking, but little is known about the effects of passive smoking on this condition. In China, female passive smoking is widespread, particularly in rural areas. Objective: This study aimed to estimate the relationship between REEs accumulation and passive smoking among rural housewives. Methods: We recruited 385 subjects in Shanxi Province of northern China, of whom 117 housewives were exposed to passive smoking, and 268 were not. We analyzed 15 REEs in the hair of housewives with ICP–MS, including lanthanum, cerium, praseodymium, neodymium, samarium, europium, gadolinium, terbium, dysprosium, holmium, erbium, thulium, ytterbium, lutetium, and yttrium. Results: The results indicated higher levels of 14 REEs except for Sm in both the univariate and adjusted models among the housewives exposed to passive smoking. The increasing linear trend of adjusted odds ratios of 15 REEs supported their association. The Bayesian kernel machine regression (BKMR) models showed that 15 REEs had a significant overall effect, and Eu had a single-exposure effect with passive smoking. Conclusion: We concluded that passive smoking might be associated with increased exposure to REEs among rural housewives.

Toxic Metals and Subclinical Atherosclerosis in Carotid, Femoral, and Coronary Vascular Territories: The Aragon Workers Health Study

Objective: Studies evaluating the association of metals with subclinical atherosclerosis are mostly limited to carotid arteries. We assessed individual and joint associations of nonessential metals exposure with subclinical atherosclerosis in 3 vascular territories. Approach and Results: One thousand eight hundred seventy-three Aragon Workers Health Study participants had urinary determinations of inorganic arsenic species, barium, cadmium, chromium, antimony, titanium, uranium, vanadium, and tungsten. Plaque presence in carotid and femoral arteries was determined by ultrasound. Coronary Agatston calcium score ≥1 was determined by computed tomography scan. Median arsenic, barium, cadmium, chromium, antimony, titanium, uranium, vanadium, and tungsten levels were 1.83, 1.98, 0.27, 1.18, 0.05, 9.8, 0.03, 0.66, and 0.23 μg/g creatinine, respectively. The adjusted odds ratio (95% CI) for subclinical atherosclerosis presence in at least one territory was 1.25 (1.03–1.51) for arsenic, 1.67 (1.22–2.29) for cadmium, and 1.26 (1.04–1.52) for titanium. These associations were driven by arsenic and cadmium in carotid, cadmium and titanium in femoral, and titanium in coronary territories and mostly remained after additional adjustment for the other relevant metals. Titanium, cadmium, and antimony also showed positive associations with alternative definitions of increased coronary calcium. Bayesian Kernel Machine Regression analysis simultaneously evaluating metal associations suggested an interaction between arsenic and the joint cadmium-titanium exposure. Conclusions: Our results support arsenic and cadmium and identify titanium and potentially antimony as atherosclerosis risk factors. Exposure reduction and mitigation interventions of these metals may decrease cardiovascular risk in individuals without clinical disease.

Exposure to Cadmium, Lead, Mercury and Arsenic and Uric Acid Levels: Results from NHANES 2007-2016

Background: Mechanisms underlying abnormal uric acid (UA) levels from exposure to heavy metals have not been not fully elucidated, especially in the context of mixtures.Objectives: To identify major heavy metals affected UA levels with a mixture exposure concept in the association model.Methods: 4794 adults from 2007-2016 National Health and Nutrition Examination Survey (NHANES) were involved. Serum UA (SUA) and SUA/SCr were used to estimate the UA levels, and cadmium (Cd), lead (Pb), mercury (Hg) and arsenic (As) in blood and/or urinary were evaluated in the study. We assessed the associations between heavy metals and UA levels using linear regression and Bayesian kernel machine regression (BKMR). Results: The median [P25, P75] SUA/SCr and SUA level were 6.22[5.27, 7.32] and 0.83[0.72, 0.98], respectively. There was no difference for SUA/SCr by gender, (men: 6.25[5.39, 7.29]; women: 6.17[5.17, 7.36], P=0.162), but men had higher SUA than women (men: 0.95[0.85, 1.05]; women: 0.72[0.64, 0.82], P<0.001). Blood Pb (βmen = 0.651 and βwomen =1.014) and urinary Cd (βmen = 0.252 and βwomen = 0.613) were positively associated with SUA/SCr, and urinary Pb (βmen = -0.462 and βwomen = -0.838) was inversely associated with SUA/SCr in multivariate linear regression analysis, but urinary As (βmen= 0.351) was positively associated with SUA/SCr only in men. BKMR showed that higher concentrations of exposure to a mixture of heavy metals was positively associated with higher UA levels, where Cd, Pb and urinary As contributed most to the overall mixture effect in men, while Pb and urinary Cd in women.Conclusions: Our study provided the first evidence that mixtures of metals are associated with the UA levels. Increased concentrations of metals, particularly blood Pb, urinary Cd and As (only in men) may increase the levels of UA.

Urine phthalate levels and liver function in US adolescents: Analyses of NHANES 2007-2016

Phthalates are non-persistent chemicals with endocrine-disrupting abilities widely used in a variety of consumer products. Evidence for the effects of phthalate exposure on liver function in adolescents is lacking. The aim of this study was to investigate the association between urine phthalate levels and changes in liver function indicators. Methods: Data were analyzed from the combined 2007-2016 National Health and Nutrition Examination Survey (NHANES). Weighted linear regressions were used to explore the association between urinary phthalate metabolites and indicators of liver function. Bayesian kernel machine regressions (BKMR) were used to evaluate the joint effects of phthalate metabolite mixtures on indicators of liver function. Results: Weighted Linear regression models showed that MCOP and MiBP were negatively associated with TBIL (all P FDR < 0.05), MCPP was positively correlated with TBIL (P FDR < 0.05), ΣDEHP, MCOP, and MEP (all P FDR < 0.05) were negatively correlated with ALB, while MCPP was positively correlated with ALB (P FDR < 0.05), and MCOP was negatively correlated with TP (P FDR < 0.05). BKMR analysis showed phthalate metabolite mixtures had significant positive dose response relationships with ALT, AST, GGT, ALP and TBIL, and significant negative dose response relationships with ALB and TP. Conclusions: Phathalate metabolites were associated with changes in liver function indicators among U.S. adolescents.

Phylogeny-Guided Microbiome OTU-Specific Association Test (POST)

Background: The relationship between host conditions and microbiome profiles, typically characterized by operational taxonomic units (OTUs), contains important information about the microbial role in human health. Traditional association testing frameworks are challenged by the high-dimensionality and sparsity of typical microbiome profiles. Incorporating phylogenetic information is often used to address these challenges with the assumption that evolutionarily similar taxa tend to behave similarly. However, this assumption may not always be valid due to the complex effect of microbes, and phylogenetic information should be incorporated in a data-supervised fashion. Results: In this work, we propose a local collapsing test called Phylogeny-guided microbiome OTU-Specific association Test (POST). In POST, whether or not to borrow information and how much information to borrow from the neighboring OTUs in the phylogenic tree are supervised by phylogenetic distance and the outcome-OTU association. POST is constructed under the kernel machine framework to accommodate complex OTU effects and extends kernel machine microbiome tests from community-level to OTU-level. Using simulation studies, we showed that when the phylogenetic tree is informative, POST has better performance than existing OTU-level association tests. When the phylogenetic tree is not informative, POST achieves similar performance as existing methods. Finally, we show that POST can identify more outcome-associated OTUs that are of biological relevance in real data applications on bacterial vaginosis and on preterm birth. Conclusions: Using POST, we show that the power of detecting associated microbiome features can be enhanced by adaptively leveraging the phylogenetic information when testing for a target OTU. We developed an user friendly R package POSTm which is now available at CRAN (https://CRAN.R-project.org/package=POSTm) for public access.