Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multi-marker in the Strong Heart Study.

The statistical analysis of omics data poses a great computational challenge given its ultra-high dimensional nature and frequent between-features correlation. In this work, we extended the Iterative Sure Independence Screening (ISIS) algorithm by pairing ISIS with elastic-net (Enet) and two versions of adaptive Enet (AEnet and MSAEnet) to efficiently improve feature selection and effect estimation in omics research. We subsequently used genome-wide human blood DNA methylation data from American Indians of the Strong Heart Study (N=2,235 participants), measured in 1989-1991, to compare the performance (predictive accuracy, coefficient estimation and computational efficiency) of SIS-paired regularization methods to Bayesian shrinkage and traditional linear regression to identify epigenomic multi-marker of body mass index. ISIS-AEnet outperformed the other methods in prediction. In biological pathway enrichment analysis of genes annotated to BMI-related differentially methylated positions, ISIS-AEnet captured most of the enriched pathways in common for at least two of all the evaluated methods. ISIS-AEnet can favor biological discovery because it identifies the most robust biological pathways while achieving an optimal balance between bias and efficient feature selection. In the extended SIS R package, we also implemented ISIS paired with Cox and logistic regression for time-to-event and binary endpoints, respectively, and bootstrap confidence intervals for the estimated regression coefficients.

Blood DNA methylation and liver cancer in American Indians: evidence from the Strong Heart Study.

PURPOSE: Liver cancer incidence among American Indians/Alaska Natives has risen over the past 20 years. Peripheral blood DNA methylation may be associated with liver cancer and could be used as a biomarker for cancer risk. We evaluated the association of blood DNA methylation with risk of liver cancer. METHODS: We conducted a prospective cohort study in 2324 American Indians, between age 45 and 75 years, from Arizona, Oklahoma, North Dakota and South Dakota who participated in the Strong Heart Study between 1989 and 1991. Liver cancer deaths (n = 21) were ascertained using death certificates obtained through 2017. The mean follow-up duration (SD) for non-cases was 25.1 (5.6) years and for cases, 11.0 (8.8) years. DNA methylation was assessed from blood samples collected at baseline using MethylationEPIC BeadChip 850 K arrays. We used Cox regression models adjusted for age, sex, center, body mass index, low-density lipoprotein cholesterol, smoking, alcohol consumption, and immune cell proportions to examine the associations. RESULTS: We identified 9 CpG sites associated with liver cancer. cg16057201 annotated to MRFAP1) was hypermethylated among cases vs. non-cases (hazard ratio (HR) for one standard deviation increase in methylation was 1.25 (95% CI 1.14, 1.37). The other eight CpGs were hypomethylated and the corresponding HRs (95% CI) ranged from 0.58 (0.44, 0.75) for cg04967787 (annotated to PPRC1) to 0.77 (0.67, 0.88) for cg08550308. We also assessed 7 differentially methylated CpG sites associated with liver cancer in previous studies. The adjusted HR for cg15079934 (annotated to LPS1) was 1.93 (95% CI 1.10, 3.39). CONCLUSIONS: Blood DNA methylation may be associated with liver cancer mortality and may be altered during the development of liver cancer.

Arsenic Exposure, Blood DNA Methylation, and Cardiovascular Disease.

BACKGROUND: Epigenetic dysregulation has been proposed as a key mechanism for arsenic-related cardiovascular disease (CVD). We evaluated differentially methylated positions (DMPs) as potential mediators on the association between arsenic and CVD. METHODS: Blood DNA methylation was measured in 2321 participants (mean age 56.2, 58.6% women) of the Strong Heart Study, a prospective cohort of American Indians. Urinary arsenic species were measured using high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry. We identified DMPs that are potential mediators between arsenic and CVD. In a cross-species analysis, we compared those DMPs with differential liver DNA methylation following early-life arsenic exposure in the apoE knockout (apoE-/-) mouse model of atherosclerosis. RESULTS: A total of 20 and 13 DMPs were potential mediators for CVD incidence and mortality, respectively, several of them annotated to genes related to diabetes. Eleven of these DMPs were similarly associated with incident CVD in 3 diverse prospective cohorts (Framingham Heart Study, Women's Health Initiative, and Multi-Ethnic Study of Atherosclerosis). In the mouse model, differentially methylated regions in 20 of those genes and DMPs in 10 genes were associated with arsenic. CONCLUSIONS: Differential DNA methylation might be part of the biological link between arsenic and CVD. The gene functions suggest that diabetes might represent a relevant mechanism for arsenic-related cardiovascular risk in populations with a high burden of diabetes.

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.

Healthy lifestyle, metabolomics and incident type 2 diabetes in a population-based cohort from Spain.

BACKGROUND: The contribution of metabolomic factors to the association of healthy lifestyle with type 2 diabetes risk is unknown. We assessed the association of a composite measure of lifestyle with plasma metabolite profiles and incident type 2 diabetes, and whether relevant metabolites can explain the prospective association between healthy lifestyle and incident type 2 diabetes. METHODS: A Healthy Lifestyle Score (HLS) (5-point scale including diet, physical activity, smoking status, alcohol consumption and BMI) was estimated in 1016 Hortega Study participants, who had targeted plasma metabolomic determinations at baseline examination in 2001-2003, and were followed-up to 2015 to ascertain incident type 2 diabetes. RESULTS: The HLS was cross-sectionally associated with 32 (out of 49) plasma metabolites (2.5% false discovery rate). In the subset of 830 participants without prevalent type 2 diabetes, the rate ratio (RR) and rate difference (RD) of incident type 2 diabetes (n cases = 51) per one-point increase in HLS was, respectively, 0.69 (95% CI, 0.51, 0.93), and - 8.23 (95% CI, - 16.34, - 0.13)/10,000 person-years. In single-metabolite models, most of the HLS-related metabolites were prospectively associated with incident type 2 diabetes. In probit Bayesian Kernel Machine Regression, these prospective associations were mostly driven by medium HDL particle concentration and phenylpropionate, followed by small LDL particle concentration, which jointly accounted for ~ 50% of the HLS-related decrease in incident type 2 diabetes. CONCLUSIONS: The HLS showed a strong inverse association with incident type 2 diabetes, which was largely explained by plasma metabolites measured years before the clinical diagnosis.

Effects of e-liquid flavor, nicotine content, and puff duration on metal emissions from electronic cigarettes.

Vaping is the action of inhaling and exhaling aerosols from electronic cigarettes. The aerosols contain various amounts of toxic chemicals, including metals. The purpose of this study was to evaluate factors that can influence metal levels, including flavor and nicotine content in the e-liquid, and puff duration. Aerosols were collected from both closed-system (cartridge-based) and open-system e-cigarettes using e-liquids with different flavors (fruit, tobacco, and menthol), nicotine content (0, 6, 24, and 59 mg/mL), and different puff durations (1, 2, and 4 s). The concentrations of 14 metals in the collected aerosols were measured using inductively coupled plasma mass spectroscopy. Aerosol concentrations of As, Fe, and Mn varied significantly among fruit, tobacco, and menthol flavors in both closed-system and open-system devices. Concentrations of Al, Fe, Sn, and U were significantly higher in tobacco or menthol flavored aerosols compared to fruit flavors in closed-system devices. Aerosol W levels were significantly higher in tobacco flavored aerosols compared to fruit flavors in open-system devices. Concentrations of As, Fe, and Mn were higher in tobacco flavored aerosols compared to menthol flavors in both types of devices. The median Pb concentration decreased significantly from 15.8 to 0.88 µg/kg when nicotine content increased from 0 to 59 mg/mL, and median Ni concentration was 9.60 times higher in aerosols with nicotine of 59 mg/mL compared to 24 mg/mL (11.9 vs. 1.24 µg/kg) for closed-system devices. No significant differences were observed in aerosol metal concentrations for different puff durations. Aerosol metal concentrations varied widely between different flavors and nicotine content but not by puff duration. Flavor and nicotine content of the e-liquid could be potential factors in metal emissions. Some elements showed higher concentrations under certain conditions, highlighting the urgent need of developing strict product regulations, especially on e-liquid composition and nicotine content to inform e-cigarette users about metal exposure through vaping.

Arsenic exposure and human blood DNA methylation and hydroxymethylation profiles in two diverse populations from Bangladesh and Spain.

BACKGROUND: Associations of arsenic (As) with the sum of 5-mC and 5-hmC levels have been reported; however, As exposure-related differences of the separated 5-mC and 5-hmC markers have rarely been studied. METHODS: In this study, we evaluated the association of arsenic exposure biomarkers and 5-mC and 5-hmC in 30 healthy men (43-55 years) from the Aragon Workers Health Study (AWHS) (Spain) and 31 healthy men (31-50 years) from the Folic Acid and Creatinine Trial (FACT) (Bangladesh). We conducted 5-mC and 5-hmC profiling using Infinium MethylationEPIC arrays, on paired standard and modified (ox-BS in AWHS and TAB in FACT) bisulfite converted blood DNA samples. RESULTS: The median for the sum of urine inorganic and methylated As species (ΣAs) (µg/L) was 12.5 for AWHS and 89.6 for FACT. The median of blood As (µg/L) was 8.8 for AWHS and 10.2 for FACT. At a statistical significance p-value cut-off of 0.01, the differentially methylated (DMP) and hydroxymethylated (DHP) positions were mostly located in different genomic sites. Several DMPs and DHPs were consistently found in AWHS and FACT both for urine ΣAs and blood models, being of special interest those attributed to the DIP2C gene. Three DMPs (annotated to CLEC12A) for AWHS and one DHP (annotated to NPLOC4) for FACT remained statistically significant after false discovery rate (FDR) correction. Pathways related to chronic diseases including cardiovascular, cancer and neurological were enriched. CONCLUSIONS: While we identified common 5-hmC and 5-mC signatures in two populations exposed to varying levels of inorganic As, differences in As-related epigenetic sites across the study populations may additionally reflect low and high As-specific associations. This work contributes a deeper understanding of potential epigenetic dysregulations of As. However, further research is needed to confirm biological consequences associated with DIP2C epigenetic regulation and to investigate the role of 5-hmC and 5-mC separately in As-induced health disorders at different exposure levels.

Critical Care Requirements Under Uncontrolled Transmission of SARS-CoV-2.

Objectives. To estimate the critical care bed capacity that would be required to admit all critical COVID-19 cases in a setting of unchecked SARS-CoV-2 transmission, both with and without elderly-specific protection measures.Methods. Using electronic health records of all 2432 COVID-19 patients hospitalized in a large hospital in Madrid, Spain, between February 28 and April 23, 2020, we estimated the number of critical care beds needed to admit all critical care patients. To mimic a hypothetical intervention that halves SARS-CoV-2 infections among the elderly, we randomly excluded 50% of patients aged 65 years and older.Results. Critical care requirements peaked at 49 beds per 100 000 on April 1-2 weeks after the start of a national lockdown. After randomly excluding 50% of elderly patients, the estimated peak was 39 beds per 100 000.Conclusions. Under unchecked SARS-CoV-2 transmission, peak critical care requirements in Madrid were at least fivefold higher than prepandemic capacity. Under a hypothetical intervention that halves infections among the elderly, critical care peak requirements would have exceeded the prepandemic capacity of most high-income countries.Public Health Implications. Pandemic control strategies that rely exclusively on protecting the elderly are likely to overwhelm health care systems.

Cost-effectiveness of a Contact Intervention and a Psychotherapeutic Program for Post-discharge Suicide Prevention.

OBJECTIVE: To determine the cost-effectiveness of 2 strategies for post-discharge suicide prevention, an Enhanced Contact intervention based on repeated in-person and telephone contacts, and an individual 2-month long problem-solving Psychotherapy program, in comparison to facilitated access to outpatient care following a suicide attempt. METHODS: We conducted a cost-effectiveness analysis based on a decision tree between January and December 2019. Comparative effectiveness estimates were obtained from an observational study conducted between 2013 and 2017 in Madrid, Spain. Electronic health care records documented resource use (including extra-hospital emergency care, mortality, inpatient admission, and disability leave). Direct cost data were derived from Madrid's official list of public health care prices. Indirect cost data were derived from Spain's National Institute of Statistics. RESULTS: Both augmentation strategies were more cost-effective than a single priority outpatient appointment considering reasonable thresholds of willingness to pay. Under the base-case scenario, Enhanced Contact and Psychotherapy incurred, respectively, €2,340 and 6,260 per averted attempt, compared to a single priority appointment. Deterministic and probabilistic sensitivity analyses showed both augmentation strategies to remain cost-effective under several scenarios. Enhanced Contact was slightly cost minimizing in comparison to Psychotherapy (base-case scenario: €-196 per averted attempt). CONCLUSIONS: Two post-discharge suicide prevention strategies based on Enhanced Contact and Psychotherapy were cost-effective in comparison to a single priority appointment. Increasing contacts between suicide attempters and mental health-care providers was slightly cost minimizing compared to psychotherapy.

DNA methylation and adiposity phenotypes: an epigenome-wide association study among adults in the Strong Heart Study.

BACKGROUND: Elevated adiposity is often posited by medical and public health researchers to be a risk factor associated with cardiovascular disease, diabetes, and other diseases. These health challenges are now thought to be reflected in epigenetic modifications to DNA molecules, such as DNA methylation, which can alter gene expression. METHODS: Here we report the results of three Epigenome Wide Association Studies (EWAS) in which we assessed the differential methylation of DNA (obtained from peripheral blood) associated with three adiposity phenotypes (BMI, waist circumference, and impedance-measured percent body fat) among American Indian adult participants in the Strong Heart Study. RESULTS: We found differential methylation at 8264 CpG sites associated with at least one of our three response variables. Of the three adiposity proxies we measured, waist circumference had the highest number of associated differentially methylated CpGs, while percent body fat was associated with the lowest. Because both waist circumference and percent body fat relate to physiology, we focused interpretations on these variables. We found a low degree of overlap between these two variables in our gene ontology enrichment and Differentially Methylated Region analyses, supporting that waist circumference and percent body fat measurements represent biologically distinct concepts. CONCLUSIONS: We interpret these general findings to indicate that highly significant regions of the genome (DMR) and synthesis pathways (GO) in waist circumference analyses are more likely to be associated with the presence of visceral/abdominal fat than more general measures of adiposity. Our findings confirmed numerous CpG sites previously found to be differentially methylated in association with adiposity phenotypes, while we also found new differentially methylated CpG sites and regions not previously identified.

MLML2R: an R package for maximum likelihood estimation of DNA methylation and hydroxymethylation proportions.

Accurately measuring epigenetic marks such as 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC) at the single-nucleotide level, requires combining data from DNA processing methods including traditional (BS), oxidative (oxBS) or Tet-Assisted (TAB) bisulfite conversion. We introduce the R package MLML2R, which provides maximum likelihood estimates (MLE) of 5-mC and 5-hmC proportions. While all other available R packages provide 5-mC and 5-hmC MLEs only for the oxBS+BS combination, MLML2R also provides MLE for TAB combinations. For combinations of any two of the methods, we derived the pool-adjacent-violators algorithm (PAVA) exact constrained MLE in analytical form. For the three methods combination, we implemented both the iterative method by Qu et al. [Qu, J., M. Zhou, Q. Song, E. E. Hong and A. D. Smith (2013): "Mlml: consistent simultaneous estimates of dna methylation and hydroxymethylation," Bioinformatics, 29, 2645-2646.], and also a novel non iterative approximation using Lagrange multipliers. The newly proposed non iterative solutions greatly decrease computational time, common bottlenecks when processing high-throughput data. The MLML2R package is flexible as it takes as input both, preprocessed intensities from Infinium Methylation arrays and counts from Next Generation Sequencing technologies. The MLML2R package is freely available at https://CRAN.R-project.org/package=MLML2R.

Metal concentrations in electronic cigarette aerosol: Effect of open-system and closed-system devices and power settings.

BACKGROUND: Electronic cigarettes (E-cigarettes) generate aerosol containing metal contaminants. Our goals were to quantify aerosol metal concentrations and to compare the effects of power setting and device type (closed-system vs. open-system) on metal release. METHODS: Aerosol samples were collected from two closed-system devices (a cigalike and pod) and two open-system devices (mods). Each open-system device was operated at three different power settings to examine the effect of device power on metal release. Concentrations of 14 metals in e-cigarette aerosol collected via droplet deposition were measured using inductively coupled plasma mass spectroscopy. Aerosol metal concentrations were reported as mass fractions (µg/kg) in the e-liquid. RESULTS: For open-system device 1 (OD1), median arsenic (As), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), lead (Pb), antimony (Sb), tin (Sn), and zinc (Zn) concentrations increased 14, 54, 17, 30, 41, 96, 14, 81, 631, and 7-fold when the device power was increased from low (20 W) to intermediate (40 W) setting. When the power was further increased from intermediate (40 W) to high (80 W) setting, concentrations of As, Cr, Cu, Mn, Ni, and Sb did not change significantly. For open-system device 2 (OD2), Cr and Mn concentrations increased significantly when device power was increased from low (40 W) to intermediate (120 W) setting, and then decreased significantly when power was further increased from intermediate (120 W) to high (200 W) setting. Among the four devices, aerosol metal concentrations were higher for the open-system than the closed-system devices, except for aluminum (Al) and uranium (U). For Cr, median (interquartile range) concentrations (µg/kg) from the open-system devices were 2.51 (1.55, 4.23) and 15.6 (7.88, 54.5) vs. 0.39 (0.05, 0.72) and 0.41 (0.34, 0.57) for the closed-system devices. For Ni, concentrations (µg/kg) from the open-system devices were 793 (508, 1169) and 2148 (851, 3397) vs. 1.32 (0.39, 3.35) and 11.9 (10.7, 22.7) from the closed-system devices. Inhalation of 0% and 100% of samples from OD1, 7.4% and 88.9% from OD2 by typical e-cigarette users would exceed chronic minimum risk levels (MRL) of Mn and Ni, respectively. No MRL exceedance was predicted for the closed-system devices. A large fraction of users of OD1 (100%) and OD2 (77.8%) would be exposed to Ni levels higher than those from reference tobacco cigarette 3R4F. CONCLUSIONS: Our findings suggest that power setting and device type affect metal release from devices to aerosol which would subsequently be inhaled by users. Metal concentrations from open-system devices first increased with device power, and then leveled off for most metals. Open-system devices generate aerosol with higher metal concentrations than closed-system devices. These findings inform tobacco regulatory science, policy makers and health professionals on potential metal health risks associated with e-cigarette use, design and manufacturing.

Methods for the Analysis of Multiple Epigenomic Mediators in Environmental Epidemiology.

PURPOSE OF REVIEW: Epigenetic changes can be highly influenced by environmental factors and have in turn been proposed to influence chronic disease. Being able to quantify to which extent epigenomic processes are mediators of the association between environmental exposures and diseases is of interest for epidemiologic research. In this review, we summarize the proposed mediation analysis methods with applications to epigenomic data. RECENT FINDINGS: The ultra-high dimensionality and high correlations that characterize omics data have hindered the precise quantification of mediated effects. Several methods have been proposed to deal with mediation in high-dimensional settings, including methods that incorporate dimensionality reduction techniques to the mediation algorithm. Although important methodological advances have been conducted in the previous years, key challenges such as the development of sensitivity analyses, dealing with mediator-mediator interactions, including environmental mixtures as exposures, or the integration of different omic data should be the focus of future methodological developments for epigenomic mediation analysis.

Causal mediation for uncausally related mediators in the context of survival analysis.

Objective: The study of the potential intermediate effect of several variables on the association between an exposure and a time-to-event outcome is a question of interest in epidemiologic research. However, to our knowledge, no tools have been developed for the evaluation of multiple correlated mediators in a survival setting. Methods: In this work, we extended the multimediate algorithm, which conducts mediation analysis in the context of multiple uncausally correlated mediators, to a time-to-event setting using the semiparametric additive hazards model. We theoretically demonstrated that, under certain assumptions, indirect, direct and total effects can be calculated using the counterfactual framework with collapsible survival models. We also adapted the algorithm to accommodate exposure-mediator interactions. Results and conclusions: Using simulations, we demonstrated that our algorithm performs better than the product of coefficients method, even for uncorrelated mediators. The additive hazards model quantifies the effects as rate differences, which constitute a measure of impact, with applications that can be highly informative for public health. Our algorithm can be found in the R package multimediate, which is available in Github.

Method validation for (ultra)-trace element concentrations in urine for small sample volumes in large epidemiological studies: application to the population-based epidemiological multi-ethnic study of atherosclerosis (MESA).

Analysis of essential and non-essential trace elements in urine has emerged as a valuable tool for assessing occupational and environmental exposures, diagnosing nutritional status and guiding public health and health care intervention. Our study focused on the analysis of trace elements in urine samples from the Multi-Ethnic Study of Atherosclerosis (MESA), a precious resource for health research with limited sample volumes. Here we provide a comprehensive and sensitive method for the analysis of 18 elements using only 100 µL of urine. Method sensitivity, accuracy, and precision were assessed. The analysis by inductively coupled plasma mass spectrometry (ICP-MS) included the measurement of antimony (Sb), arsenic (As), barium (Ba), cadmium (Cd), cesium (Cs), cobalt (Co), copper (Cu), gadolinium (Gd), lead (Pb), manganese (Mn), molybdenum (Mo), nickel (Ni), selenium (Se), strontium (Sr), thallium (Tl), tungsten (W), uranium (U), and zinc (Zn). Further, we reported urinary trace element concentrations by covariates including gender, ethnicity/race, smoking and location. The results showed good accuracy and sensitivity of the ICP-MS method with the limit of detections rangings between 0.001 µg L-1 for U to 6.2 µg L-1 for Zn. Intra-day precision for MESA urine analysis varied between 1.4% for Mo and 26% for Mn (average 6.4% for all elements). The average inter-day precision for most elements was <8.5% except for Gd (20%), U (16%) and Mn (19%) due to very low urinary concentrations. Urinary mean concentrations of non-essential elements followed the order of Sr > As > Cs > Ni > Ba > Pb > Cd > Gd > Tl > W > U. The order of urinary mean concentrations for essential trace elements was Zn > Se > Mo > Cu > Co > Mn. Non-adjusted mean concentration of non-essential trace elements in urine from MESA participants follow the order Sr > As > Cs > Ni > Ba > Pb > Cd > Gd > Tl > W > U. The unadjusted urinary mean concentrations of essential trace elements decrease from Zn > Se > Mo > Cu > Co > Mn.

Association of single and joint metals with albuminuria and estimated glomerular filtration longitudinal change in middle-aged adults from Spain: The Aragon workers health study.

The nephrotoxicity of low-chronic metal exposures is unclear, especially considering several metals simultaneously. We assessed the individual and joint association of metals with longitudinal change in renal endpoints in Aragon Workers Health Study participants with available measures of essential (cobalt [Co], copper [Cu], molybdenum [Mo] and zinc [Zn]) and non-essential (As, barium [Ba], Cd, chromium [Cr], antimony [Sb], titanium [Ti], uranium [U], vanadium [V] and tungsten [W]) urine metals and albumin-to-creatinine ratio (ACR) (N = 707) and estimated glomerular filtration rate (eGFR) (N = 1493) change. Median levels were 0.24, 7.0, 18.6, 295, 3.1, 1.9, 0.28, 1.16, 9.7, 0.66, 0.22 µg/g for Co, Cu, Mo, Zn, As, Ba, Cd, Cr, Sb, Ti, V and W, respectively, and 52.5 and 27.2 ng/g for Sb and U, respectively. In single metal analysis, higher As, Cr and W concentrations were associated with increasing ACR annual change. Higher Zn, As and Cr concentrations were associated with decreasing eGFR annual change. The shape of the longitudinal dose-responses, however, was compatible with a nephrotoxic role for all metals, both in ACR and eGFR models. In joint metal analysis, both higher mixtures of Cu-Zn-As-Ba-Ti-U-V-W and Co-Cd-Cr-Sb-V-W showed associations with increasing ACR and decreasing eGFR annual change. As and Cr were main drivers of the ACR change joint metal association. For the eGFR change joint metal association, while Zn and Cr were main drivers, other metals also contributed substantially. We identified potential interactions for As, Zn and W by other metals with ACR change, but not with eGFR change. Our findings support that Zn, As, Cr and W and suggestively other metals, are nephrotoxic at relatively low exposure levels. Metal exposure reduction and mitigation interventions may improve prevention and decrease the burden of renal disease in the population.

Maternal DNA methylation signatures of arsenic exposure is associated with adult offspring insulin resistance in the Strong Heart Study.

Exposure to low to moderate arsenic (As) levels has been associated with type 2 diabetes (T2D) and other chronic diseases in American Indian communities. Prenatal exposure to As may also increase the risk for T2D in adulthood, and maternal As has been associated with adult offspring metabolic health measurements. We hypothesized that T2D-related outcomes in adult offspring born to women exposed to low to moderate As can be evaluated utilizing a maternally-derived molecular biosignature of As exposure. Herein, we evaluated the association of maternal DNA methylation with incident T2D and insulin resistance (Homeostatic model assessment of insulin resistance [HOMA2-IR]) in adult offspring. For DNA methylation, we used 20 differentially methylated cytosine-guanine dinucleotides (CpG) previously associated with the sum of inorganic and methylated As species (ΣAs) in urine in the Strong Heart Study (SHS). Of these 20 CpGs, we found six CpGs nominally associated (p < 0.05) with HOMA2-IR in a fully adjusted model that included clinically relevant covariates and offspring adiposity measurements; a similar model that adjusted instead for maternal adiposity measurements found three CpGs nominally associated with HOMA2-IR, two of which overlapped the offspring adiposity model. After adjusting for multiple comparisons, cg03036214 remained associated with HOMA2-IR (q < 0.10) in the offspring adiposity model. The odds ratio of incident T2D increased with an increase in maternal DNA methylation at one HOMA2-IR associated CpG in the model adjusting for offspring adiposity, cg12116137, whereas adjusting for maternal adiposity had a minimal effect on the association. Our data suggests offspring adiposity, rather than maternal adiposity, potentially influences the effects of maternal DNAm signatures on offspring metabolic health parameters. Here, we have presented evidence supporting a role for epigenetic biosignatures of maternal As exposure as a potential biomarker for evaluating risk of T2D-related outcomes in offspring later in life.

Metal mixtures and DNA methylation measures of biological aging in American Indian populations.

INTRODUCTION: Native American communities suffer disproportionately from elevated metal exposures and increased risk for cardiovascular diseases and diabetes. DNA methylation is a sensitive biomarker of aging-related processes and novel epigenetic-based "clocks" can be used to estimate accelerated biological aging that may underlie increased risk. Metals alter DNA methylation, yet little is known about their individual and combined impact on epigenetic age acceleration. Our objective was to investigate the associations of metals on several DNA methylation-based aging measures in the Strong Heart Study (SHS) cohort. METHODS: Blood DNA methylation data from 2,301 SHS participants was used to calculate age acceleration of epigenetic clocks (PhenoAge, GrimAge, DunedinPACE, Hannum, Horvath). Urinary metals [arsenic (As), cadmium (Cd), tungsten (W), zinc (Zn), selenium (Se), molybdenum (Mo)] were creatinine-adjusted and categorized into quartiles. We examined associations of individual metals through linear regression models and used Bayesian Kernel Machine Regression (BKMR) for the impact of the total metal mixture on epigenetic age acceleration. RESULTS: The mixture of nonessential metals (W, As, Cd) was associated with greater GrimAge acceleration and DunedinPACE, while the essential metal mixture (Se, Zn, Mo) was associated with lower epigenetic age acceleration. Cd was associated with increased epigenetic age acceleration across all clocks and BKMR analysis suggested nonlinear associations between Se and DunedinPACE, GrimAge, and PhenoAge acceleration. No interactions between individual metals were observed. The associations between Cd, Zn, and epigenetic age acceleration were greater in never smokers in comparison to current/former smokers. CONCLUSION: Nonessential metals were positively associated with greater epigenetic age acceleration, with strongest associations observed between Cd and DunedinPACE and GrimAge acceleration. In contrast, essential metals were associated with lower epigenetic aging. Examining the influence of metal mixtures on epigenetic age acceleration can provide insight into metals and aging-related diseases.

Traffic Density Exposure, Oxidative Stress Biomarkers and Plasma Metabolomics in a Population-Based Sample: The Hortega Study.

Exposure to traffic-related air pollution (TRAP) generates oxidative stress, with downstream effects at the metabolic level. Human studies of traffic density and metabolomic markers, however, are rare. The main objective of this study was to evaluate the cross-sectional association between traffic density in the street of residence with oxidative stress and metabolomic profiles measured in a population-based sample from Spain. We also explored in silico the potential biological implications of the findings. Secondarily, we assessed the contribution of oxidative stress to the association between exposure to traffic density and variation in plasma metabolite levels. Traffic density was defined as the average daily traffic volume over an entire year within a buffer of 50 m around the participants' residence. Plasma metabolomic profiles and urine oxidative stress biomarkers were measured in samples from 1181 Hortega Study participants by nuclear magnetic resonance spectroscopy and high-performance liquid chromatography, respectively. Traffic density was associated with 7 (out of 49) plasma metabolites, including amino acids, fatty acids, products of bacterial and energy metabolism and fluid balance metabolites. Regarding urine oxidative stress biomarkers, traffic associations were positive for GSSG/GSH% and negative for MDA. A total of 12 KEGG pathways were linked to traffic-related metabolites. In a protein network from genes included in over-represented pathways and 63 redox-related candidate genes, we observed relevant proteins from the glutathione cycle. GSSG/GSH% and MDA accounted for 14.6% and 12.2% of changes in isobutyrate and the CH2CH2CO fatty acid moiety, respectively, which is attributable to traffic exposure. At the population level, exposure to traffic density was associated with specific urine oxidative stress and plasma metabolites. Although our results support a role of oxidative stress as a biological intermediary of traffic-related metabolic alterations, with potential implications for the co-bacterial and lipid metabolism, additional mechanistic and prospective studies are needed to confirm our findings.

Arsenic Exposure and Epigenetic Aging: The Association with Cardiovascular Disease and All-Cause Mortality in the Strong Heart Study.

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.