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Introduction Exposure to inorganic arsenic (As), a toxic and carcinogenic metalloid, is a pervasive global health problem. Arsenic exposure has been associated with a higher risk of numerous adverse health [...], BACKGROUND: Inorganic arsenic (As) may increase the risk of cardiovascular disease (CVD) and all-cause mortality through accelerated aging, which can be estimated using epigenetic-based measures. OBJECTIVES: We evaluated three DNA methylation-based aging measures (PhenoAge, GrimAge, DunedinPACE) (epigenetic aging measures) as potential mediators of the previously reported association of As exposure with CVD incidence, CVD mortality, and all- cause mortality in the Strong Heart Study (SHS), an epidemiological cohort of American Indian adults. METHODS: Blood DNA methylation and urinary As levels were measured in 2,323 SHS participants (41.5% men, mean age of 55 years old). PhenoAge and GrimAge values were calculated using a residual-based method. We tested the association of urinary As with epigenetic aging measures using linear regression, the association of epigenetic aging measures with the three health outcomes using additive hazards models, and the mediation of As-related CVD incidence, CVD mortality, and all-cause mortality by epigenetic aging measures using the product of coefficients method. RESULTS: SHS participants with higher vs. lower urinary As levels had similar PhenoAge age, older GrimAge age, and faster DunedinPACE. An interquartile range increase in urinary As was associated with higher of PhenoAge age acceleration [mean difference (95% confidence interval) = 0.48 (0.17, 0.80) years], GrimAge age acceleration [0.80 (0.60, 1.00) years], and DunedinPACE [0.011 (0.005, 0.018)], after adjusting for age, sex, center location, genetic components, smoking status, and body mass index. Of the 347 incident CVD events per 100,000 person-years associated with a doubling in As exposure, 21.3% (9.1, 57.1) and 22.6% (9.5, 56.9), were attributable to differences in GrimAge and DunedinPACE, respectively. DISCUSSION: Arsenic exposure was associated with older GrimAge and faster DunedinPACE measures of biological age. Furthermore, accelerated biological aging measured from DNA methylation accounted for a relevant fraction of As-associated risk for CVD, CVD mortality, and all-cause mortality in the SHS, supporting the role of As in accelerated aging. Research of the biological underpinnings can contribute to a better understanding of the role of aging in arsenic-related disease. https://doi.org/10.1289/EHP11981

Introduction Arsenic (As) contamination of groundwater is common in many regions of the world. At least 94 million people worldwide are exposed to concentrations exceeding the World Health Organization (WHO) [...], BACKGROUND: Chronic arsenic (As) exposure is a global environmental health issue. Inorganic As (InAs) undergoes methylation to monomethyl (MMAs) and dimethyl-arsenical species (DMAs); full methylation to DMAs facilitates urinary excretion and is associated with reduced risk for As-related health outcomes. Nutritional factors, including folate and creatine, influence one-carbon metabolism, the biochemical pathway that provides methyl groups for As methylation. OBJECTIVE: Our aim was to investigate the effects of supplementation with folic acid (FA), creatine, or the two combined on the concentrations of As metabolites and the primary methylation index (PMI: MMAs/InAs) and secondary methylation index (SMI: DMAs/MMAs) in blood in Bangladeshi adults having a wide range of folate status. METHODS: In a randomized, double-blinded, placebo (PBO)-controlled trial, 622 participants were recruited independent of folate status and assigned to one of five treatment arms: a) PBO (n = 102), b) 400 [micro]g FA/d (400FA; n = 153), c) 800 [micro]g FA/d (800FA; n =151), d) 3 g creatine/d (creatine; n = 101), or e) 3 gcreatine + 400 [micro]g of FA/d (creatine + 400FA; n = 103) for 12 wk. For the following 12 wk, half of the FA participants were randomly switched to the PBO while the other half continued FA supplementation. All participants received As-removal water filters at baseline. Blood As (bAs) metabolites were measured at weeks 0, 1, 12, and 24. RESULTS: At baseline, 80.3% (n = 489) of participants were folate sufficient (>9 nmol/L in plasma). In all groups, bAs metabolite concentrations decreased, likely due to filter use; for example, in the PBO group, blood concentrations of MMAs (bMMAs) (geometric mean [+ or -] geometric standard deviation) decreased from 3.55 [+ or -]1.89 1g/L at baseline to 2.73 [+ or -] 1.74 at week 1. After 1 wk, the mean within- person increase in SMI for the creatine + 400FA group was greater than that of the PBO group (p = 0.05). The mean percentage decrease in bMMAs between baseline and week 12 was greater for all treatment groups compared with the PBO group [400FA: -10.4 (95% CI: -11.9, -8.75), 800FA: -9.54 (95% CI: -11.1, -7.97), creatine: -5.85 (95% CI: -8.59, -3.03), creatine + 400FA: -8.44 (95% CI: -9.95, -6.90), PBO: -2.02 (95% CI: -4.03,0.04)], and the percentage increase in blood DMAs (bDMAs) concentrations for the FA-treated groups significantly exceeded that of PBO [400FA: 12.8 (95% CI: 10.5, 15.2), 800FA: 11.3 (95% CI: 8.95, 13.8), creatine + 400FA: 7.45 (95% CI: 5.23, 9.71), PBO: -0.15 (95% CI: -2.85, 2.63)]. The mean decrease in PMI and increase in SMI in all FA groups significantly exceeded PBO (p < 0.05). Data from week 24 showed evidence of a reversal of treatment effects on As metabolites from week 12 in those who switched from 800FA to PBO, with significant decreases in SMI [-9.0% (95% CI: -3.5, -14.8)] and bDMAs [-5.9% (95% CI: -1.8, -10.2)], whereas PMI and bMMAs concentrations continued to decline [-7.16% (95% CI: -0.48, -14.3) and -3.1% (95% CI: -0.1, -6.2), respectively] for those who remained on 800FA supplementation. CONCLUSIONS: FA supplementation lowered bMMAs and increased bDMAs in a sample of primarily folate-replete adults, whereas creatine supplementation lowered bMMAs. Evidence of the reversal of treatment effects on As metabolites following FA cessation suggests short- term benefits of supplementation and underscores the importance of long-term interventions, such as FA fortification. https://doi.org/10.1289/EHP11270

Background: Numerous methods exist to analyze complex environmental mixtures in health studies. As an illustration of the different uses of mixture methods, we employed methods geared toward distinct research questions concerning persistent organic chemicals (POPs) as a mixture and leukocyte telomere length (LTL) as an outcome.Methods: With information on 18 POPs and LTL among 1,003 U.S. adults (NHANES, 2001-2002), we used unsupervised methods including clustering to identify profiles of similarly exposed participants, and Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) to identify common exposure patterns. We also employed supervised learning techniques, including penalized, weighted quantile sum (WQS), and Bayesian kernel machine (BKMR) regressions, to identify potentially toxic agents, and characterize nonlinear associations, interactions, and the overall mixture effect.Results: Clustering separated participants into high, medium, and low POP exposure groups; longer log-LTL was found among those with high exposure. The first PCA component represented overall POP exposure and was positively associated with log-LTL. Two EFA factors, one representing furans and the other PCBs 126 and 118, were positively associated with log-LTL. Penalized regression methods selected three congeners in common (PCB 126, PCB 118, and furan 2,3,4,7,8-pncdf) as potentially toxic agents. WQS found a positive overall effect of the POP mixture and identified six POPs as potentially toxic agents (furans 1,2,3,4,6,7,8-hxcdf, 2,3,4,7,8-pncdf, and 1,2,3,6,7,8-hxcdf, and PCBs 99, 126, 169). BKMR found a positive linear association with furan 2,3,4,7,8-pncdf, suggestive evidence of linear associations with PCBs 126 and 169, and a positive overall effect of the mixture, but no interactions among congeners.Conclusions: Using different methods, we identified patterns of POP exposure, potentially toxic agents, the absence of interaction, and estimated the overall mixture effect. These applications and results may serve as a guide for mixture method selection based on specific research questions. [ABSTRACT FROM AUTHOR]