AESurv: autoencoder survival analysis for accurate early prediction of coronary heart disease.

Coronary heart disease (CHD) is one of the leading causes of mortality and morbidity in the United States. Accurate time-to-event CHD prediction models with high-dimensional DNA methylation and clinical features may assist with early prediction and intervention strategies. We developed a state-of-the-art deep learning autoencoder survival analysis model (AESurv) to effectively analyze high-dimensional blood DNA methylation features and traditional clinical risk factors by learning low-dimensional representation of participants for time-to-event CHD prediction. We demonstrated the utility of our model in two cohort studies: the Strong Heart Study cohort (SHS), a prospective cohort studying cardiovascular disease and its risk factors among American Indians adults; the Women's Health Initiative (WHI), a prospective cohort study including randomized clinical trials and observational study to improve postmenopausal women's health with one of the main focuses on cardiovascular disease. Our AESurv model effectively learned participant representations in low-dimensional latent space and achieved better model performance (concordance index-C index of 0.864 ± 0.009 and time-to-event mean area under the receiver operating characteristic curve-AUROC of 0.905 ± 0.009) than other survival analysis models (Cox proportional hazard, Cox proportional hazard deep neural network survival analysis, random survival forest, and gradient boosting survival analysis models) in the SHS. We further validated the AESurv model in WHI and also achieved the best model performance. The AESurv model can be used for accurate CHD prediction and assist health care professionals and patients to perform early intervention strategies. We suggest using AESurv model for future time-to-event CHD prediction based on DNA methylation features.

Urinary Metal Levels and Coronary Artery Calcification: Longitudinal Evidence in the Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Exposure to metals, a newly recognized risk factor for cardiovascular disease (CVD), could be related to atherosclerosis progression. OBJECTIVES: The authors hypothesized that higher urinary levels of nonessential (cadmium, tungsten, uranium) and essential (cobalt, copper, zinc) metals previously associated with CVD would be associated with baseline and rate of change of coronary artery calcium (CAC) progression, a subclinical marker of CVD in MESA (Multi-Ethnic Study of Atherosclerosis). METHODS: We analyzed data from 6,418 MESA participants with spot urinary metal levels at baseline (2000-2002) and 1 to 4 repeated, continuous measures of CAC over a 10-year period. We used linear mixed-effect models to assess the association of baseline urinary metal levels with baseline CAC and cumulative change in CAC over a 10-year period. Urinary metals (µg/g creatinine) and CAC were log transformed. Models were adjusted for baseline sociodemographic factors, estimated glomerular filtration rate, lifestyle factors, and clinical factors. RESULTS: At baseline, the median CAC was 6.3 (Q1-Q3: 0.7-58.2). Comparing the highest to lowest quartile of urinary cadmium, CAC levels were 51% (95% CI: 32%, 74%) higher at baseline and 75% (95% CI: 47%, 107%) higher over the 10-year period. For urinary tungsten, uranium, and cobalt, the corresponding CAC levels over the 10-year period were 45% (95% CI: 23%, 71%), 39% (95% CI: 17%, 64%), and 47% (95% CI: 25%, 74%) higher, respectively, with no difference for models with and without adjustment for clinical factors. For copper and zinc, the corresponding estimates dropped from 55% to 33% and from 85% to 57%, respectively, after adjustment for clinical factors. The associations of metals with CAC were comparable in magnitude to those for classical CVD risk factors. CONCLUSIONS: Exposure to metals was generally associated with extent of coronary calcification at baseline and follow-up. These findings support that metals are associated with the progression of atherosclerosis, potentially providing a novel strategy for the prevention and treatment of atherosclerosis progression.

An epigenome-wide study of selenium status and DNA methylation in the Strong Heart Study.

BACKGROUND: Selenium (Se) is an essential nutrient linked to adverse health endpoints at low and high levels. The mechanisms behind these relationships remain unclear and there is a need to further understand the epigenetic impacts of Se and their relationship to disease. We investigated the association between urinary Se levels and DNA methylation (DNAm) in the Strong Heart Study (SHS), a prospective study of cardiovascular disease (CVD) among American Indians adults. METHODS: Selenium concentrations were measured in urine (collected in 1989-1991) using inductively coupled plasma mass spectrometry among 1,357 participants free of CVD and diabetes. DNAm in whole blood was measured cross-sectionally using the Illumina MethylationEPIC BeadChip (850 K) Array. We used epigenome-wide robust linear regressions and elastic net to identify differentially methylated cytosine-guanine dinucleotide (CpG) sites associated with urinary Se levels. RESULTS: The mean (standard deviation) urinary Se concentration was 51.8 (25.1) µg/g creatinine. Across 788,368 CpG sites, five differentially methylated positions (DMP) (hypermethylated: cg00163554, cg18212762, cg11270656, and hypomethylated: cg25194720, cg00886293) were significantly associated with Se in linear regressions after accounting for multiple comparisons (false discovery rate p-value: 0.10). The top hypermethylated DMP (cg00163554) was annotated to the Disco Interacting Protein 2 Homolog C (DIP2C) gene, which relates to transcription factor binding. Elastic net models selected 425 hypo- and hyper-methylated DMPs associated with urinary Se, including three sites (cg00163554 [DIP2C], cg18212762 [MAP4K2], cg11270656 [GPIHBP1]) identified in linear regressions. CONCLUSIONS: Urinary Se was associated with minimal changes in DNAm in adults from American Indian communities across the Southwest and the Great Plains in the United States, suggesting that other mechanisms may be driving health impacts. Future analyses should explore other mechanistic biomarkers in human populations, determine these relationships prospectively, and investigate the potential role of differentially methylated sites with disease endpoints.

Volume of alcohol intake, heavy episodic drinking, and all-cause mortality in Spain: A longitudinal population-based study.

INTRODUCTION: The impact of alcohol consumption on health, particularly in low quantities, remains controversial. Our objective was to assess the association between alcohol volume and heavy episodic drinking (HED) with all-cause mortality, while minimizing many of the known methodological issues. METHODOLOGY: This longitudinal study used data from the 2011-2012 National Health Survey and the 2014 European Health Survey in Spain. Data from 43,071 participants aged ≥ 15 years were linked to mortality records as of December 2021. Alcohol consumption categories were defined based on intake volume and frequency: never-drinkers, former drinkers, infrequent occasional drinkers (≤once/month), frequent occasional drinkers ( once /month). Regular drinkers (≥once/week) were further classified by volume: >0-10 g/day, >10-20 g/day, >20-40 g/day, and > 40 g/day. Heavy Episodic Drinking (HED) was defined as ≥ 6 and ≥ 5 standard drinks (10 g) within 4-6 h for men and women, respectively. Hazard ratios (HR) were calculated using Cox regression, adjusting for sociodemographic variables, lifestyle factors, health status, and alcohol volume or HED. RESULTS: Compared to infrequent occasional drinkers, HRs for never-drinkers and former drinkers were 1.30 (95 %CI:1.14-1.47) and 1.32 (95 %CI:1.15-1.50), respectively. No differences in mortality risk were observed for intakes up to 20 g/day, but it increased for consumptions > 20-40 g/day and > 40 g/day (HR = 1.29; 95 %CI:1.05-1.58 and HR = 1.57; 95 %CI:1.14-2.17, respectively). The HR of weekly HED vs. never was 1.31 (95 %CI:0.98-1.75). CONCLUSIONS: Compared to infrequent occasional drinking, consuming low amounts of alcohol had no impact on mortality risk. However, never-drinkers, former drinkers, individuals with regular consumption > 20 g/day, and those engaging in weekly HED, experienced higher mortality risk.

metaGWASmanager: a toolbox for an automated workflow from phenotypes to meta-analysis in GWAS consortia.

SUMMARY: This article introduces the metaGWASmanager, which streamlines genome-wide association studies within large-scale meta-analysis consortia. It is a toolbox for both the central consortium analysis group and participating studies to generate homogeneous phenotypes, minimize unwanted variability from inconsistent methodologies, ensure high-quality association results, and implement time-efficient quality control workflows. The toolbox features a plug-in-based approach for customization of association testing. RESULTS: The metaGWASmanager toolbox has been successfully deployed in both the CKDGen and MetalGWAS Initiative consortia across hundreds of participating studies, demonstrating its effectiveness in GWAS analysis optimization by automating routine tasks and ensuring the value and reliability of association results, thus, ultimately promoting scientific discovery. We provide a simulated data set with examples for script customization so that readers can reproduce the pipeline at their convenience. AVAILABILITY AND IMPLEMENTATION: GitHub: https://github.com/genepi-freiburg/metaGWASmanager.

Glyphosate exposure, muscular health and functional limitations in middle-aged and older adults.

BACKGROUND: Glyphosate is the most widely used herbicide worldwide, both in domestic and industrial settings. Experimental research in animal models has demonstrated changes in muscle physiology and reduced contractile strength associated with glyphosate exposure, while epidemiological studies have shown associations between glyphosate exposure and adverse health outcomes in critical biological systems affecting muscle function. METHODS: This study used data from a nationally representative survey of the non-institutionalized U.S. general population (NHANES, n = 2132). Urine glyphosate concentrations were determined by ion chromatography with tandem mass spectrometry. Hand grip strength (HGS) was measured using a Takei Dynamometer, and relative strength estimated as the ratio between HGS in the dominant hand and the appendicular lean mass (ALM) to body mass index (ALMBMI) ratio. Low HGS and low relative HGS were defined as 1 sex-, age- and race-specific SD below the mean. Physical function limitations were identified as significant difficulty or incapacity in various activities. RESULTS: In fully-adjusted models, the Mean Differences (MD) and 95% confidence intervals [95%CI] per doubling increase in glyphosate concentrations were -0.55 [-1.09, -0.01] kg for HGS in the dominant hand, and -0.90 [-1.58. -0.21] kg for HGS/ALMBMI. The Odds Ratios (OR) [95% CI] for low HGS, low relative HGS and functional limitations by glyphosate concentrations were 1.27 [1.03, 1.57] for low HGS; 1.43 [1.05; 1.94] for low relative HGS; 1.33 [1.08, 1.63] for stooping, crouching or kneeling difficulty; 1.17 [0.91, 1.50] for lifting or carrying items weighting up to 10 pounds difficulty; 1.21 [1.01, 1.40] for standing up from armless chair difficulty; and 1.47 [1.05, 2.29] for ascending ten steps without pause difficulty. CONCLUSIONS: Glyphosate exposure may be a risk factor for decreased grip strength and increased physical functional limitations. More studies investigating the influence of this and other environmental pollutants on functional aging are needed.

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.

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

The statistical analysis of omics data poses a great computational challenge given their 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 2 versions of adaptive elastic-net (adaptive elastic-net (AEnet) and multistep adaptive elastic-net (MSAEnet)) to efficiently improve feature selection and effect estimation in omics research. We subsequently used genome-wide human blood DNA methylation data from American Indian participants in the Strong Heart Study (n = 2235 participants; measured in 1989-1991) to compare the performance (predictive accuracy, coefficient estimation, and computational efficiency) of ISIS-paired regularization methods with that of a bayesian shrinkage and traditional linear regression to identify an epigenomic multimarker of body mass index (BMI). 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 2 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 a bootstrap approach for the estimation of regression coefficients.

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.

Alcohol consumption patterns and adherence to the Mediterranean diet in the adult population of Spain.

PURPOSE: The objective is to evaluate the association between various indicators of alcohol consumption and the degree of adherence to the Mediterranean diet among the Spanish adult population. METHODS: A cross-sectional study including 44,834 participants ≥ 15 years of age from the 2017 National Health Survey and the 2020 European Health Survey in Spain. Alcohol patterns were defined based on (1) average intake: individuals were classified as low risk (1-20 g/day in men and 1-10 g/day in women) and high risk (> 20 g/day in men or > 10 g/day in women), (2) binge drinking, and (3) alcoholic beverage preference. Non-adherence to the Mediterranean diet was defined as scoring < 7 points on an adapted Mediterranean Diet Adherence Screener index (range 0-10). Odds ratios (OR) were estimated using logistic regression models adjusted for relevant covariates. RESULTS: Compared to non-drinkers, low and high-risk drinkers were more likely to report non-adherence to the Mediterranean diet: ORs 1.35 (95% CI 1.23; 1.49) and 1.54 (95% CI 1.34; 1.76), respectively. Similarly, reports of binge drinking less than once a month was associated with higher likelihood of non-adherence (OR 1.17; 95% CI 1.04; 1.31). Individuals reporting no preference for a specific beverage and those with a preference for beer or for spirits had lower adherence: ORs 1.18 (95% CI 1.05; 1.33), 1.31 (95% CI 1.17; 1.46), and 1.72 (95% CI 1.17; 2.54), respectively, while a preference for wine showed no association (OR 1.01; 95% CI 0.90; 1.13). CONCLUSION: Alcohol consumption, even in low amounts, is associated with lower adherence to the Mediterranean diet. Therefore, alcoholic beverages should not be included in measures that define the Mediterranean diet.

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 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.

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.

Urinary Metal Levels and Coronary Artery Calcification: Longitudinal Evidence in the Multi-Ethnic Study of Atherosclerosis (MESA).

Objective: Growing evidence indicates that exposure to metals are risk factors for cardiovascular disease (CVD). We hypothesized that higher urinary levels of metals with prior evidence of an association with CVD, including non-essential (cadmium , tungsten, and uranium) and essential (cobalt, copper, and zinc) metals are associated with baseline and rate of change of coronary artery calcium (CAC) progression, a subclinical marker of atherosclerotic CVD. Methods: We analyzed data from 6,418 participants in the Multi-Ethnic Study of Atherosclerosis (MESA) with spot urinary metal levels at baseline (2000-2002) and 1-4 repeated measures of spatially weighted coronary calcium score (SWCS) over a ten-year period. SWCS is a unitless measure of CAC highly correlated to the Agatston score but with numerical values assigned to individuals with Agatston score=0. We used linear mixed effect models to assess the association of baseline urinary metal levels with baseline SWCS, annual change in SWCS, and SWCS over ten years of follow-up. Urinary metals (adjusted to µg/g creatinine) and SWCS were log transformed. Models were progressively adjusted for baseline sociodemographic factors, estimated glomerular filtration rate, lifestyle factors, and clinical factors. Results: At baseline, the median and interquartile range (25th, 75th) of SWCS was 6.3 (0.7, 58.2). For urinary cadmium, the fully adjusted geometric mean ratio (GMR) (95%Cl) of SWCS comparing the highest to the lowest quartile was 1.51 (1.32, 1.74) at baseline and 1.75 (1.47, 2.07) at ten years of follow-up. For urinary tungsten, uranium, and cobalt the corresponding GMRs at ten years of follow-up were 1.45 (1.23, 1.71), 1.39 (1.17, 1.64), and 1.47 (1.25, 1.74), respectively. For copper and zinc, the association was attenuated with adjustment for clinical risk factors; GMRs at ten years of follow-up before and after adjustment for clinical risk factors were 1.55 (1.30, 1.84) and 1.33 (1.12, 1.58), respectively, for copper and 1.85 (1.56, 2.19) and 1.57 (1.33, 1.85) for zinc. Conclusion: Higher levels of cadmium, tungsten, uranium, cobalt, copper, and zinc, as measured in urine, were associated with subclinical CVD at baseline and at follow-up. These findings support the hypothesis that metals are pro-atherogenic factors.

Smoking, blood DNA methylation sites and lung cancer risk.

Altered DNA methylation (DNAm) might be a biological intermediary in the pathway from smoking to lung cancer. In this study, we investigated the contribution of differential blood DNAm to explain the association between smoking and lung cancer incidence. Blood DNAm was measured in 2321 Strong Heart Study (SHS) participants. Incident lung cancer was assessed as time to event diagnoses. We conducted mediation analysis, including validation with DNAm and paired gene expression data from the Framingham Heart Study (FHS). In the SHS, current versus never smoking and pack-years single-mediator models showed, respectively, 29 and 21 differentially methylated positions (DMPs) for lung cancer with statistically significant mediated effects (14 of 20 available, and five of 14 available, positions, replicated, respectively, in FHS). In FHS, replicated DMPs showed gene expression downregulation largely in trans, and were related to biological pathways in cancer. The multimediator model identified that DMPs annotated to the genes AHRR and IER3 jointly explained a substantial proportion of lung cancer. Thus, the association of smoking with lung cancer was partly explained by differences in baseline blood DNAm at few relevant sites. Experimental studies are needed to confirm the biological role of identified eQTMs and to evaluate potential implications for early detection and control of lung cancer.

Association of blood cadmium and lead levels with self-reported reproductive lifespan and pregnancy loss: The national health and nutrition examination survey 1999-2018.

Cadmium and lead are known to interfere with the endocrine function. Thus, hormonally regulated processes such as menarche, menopause and pregnancy are likely influenced by chronic exposure to these metals. In US post-menopausal women, who already completed their reproductive lifespan, we evaluated the association between blood cadmium and lead levels with self-reported reproductive lifespan and personal history of pregnancy loss. We selected 5317 post-menopausal women participating in the National Health and Nutrition Examination Survey (NHANES), 1999-2018. Blood cadmium and lead levels were measured by inductively coupled plasma mass spectrometry. Reproductive lifespan was defined as the number of years between self-reported age at menarche and menopause. Personal history of pregnancy loss was defined as number of self-reported pregnancy losses out of the self-reported number of pregnancies. The fully adjusted mean difference in reproductive lifespan (95% confidence interval [CI]) comparing the 80th to the 20th percentiles of blood cadmium and lead distributions was, respectively, 0.50 (0.10, 0.91) and 0.72 (0.41, 1.03) years. Ever smoker showed stronger association of blood lead with reproductive lifespan. For self-reported pregnancy loss, the corresponding fully adjusted relative prevalence (95% CI) was 1.10 (0.93, 1.31) for cadmium and 1.10 (1.00, 1.21) for lead, and remained similar after additional adjustment for reproductive lifespan. In never smokers, the relative prevalence was 1.07 (1.04, 1.11) and 1.16 (1.05, 1.28) for blood cadmium and lead, respectively. These findings suggest that blood cadmium and lead exposures increase reproductive lifespan and prevalence of pregnancy loss in the general population. Additional studies are needed to improve the understanding of mechanisms and prevention potential of metals-related pregnancy outcomes.

A State-of-the-Science Review on Metal Biomarkers.

PURPOSE OF REVIEW: Biomarkers are commonly used in epidemiological studies to assess metals and metalloid exposure and estimate internal dose, as they integrate multiple sources and routes of exposure. Researchers are increasingly using multi-metal panels and innovative statistical methods to understand how exposure to real-world metal mixtures affects human health. Metals have both common and unique sources and routes of exposure, as well as biotransformation and elimination pathways. The development of multi-element analytical technology allows researchers to examine a broad spectrum of metals in their studies; however, their interpretation is complex as they can reflect different windows of exposure and several biomarkers have critical limitations. This review elaborates on more than 500 scientific publications to discuss major sources of exposure, biotransformation and elimination, and biomarkers of exposure and internal dose for 12 metals/metalloids, including 8 non-essential elements (arsenic, barium, cadmium, lead, mercury, nickel, tin, uranium) and 4 essential elements (manganese, molybdenum, selenium, and zinc) commonly used in multi-element analyses. RECENT FINDINGS: We conclude that not all metal biomarkers are adequate measures of exposure and that understanding the metabolic biotransformation and elimination of metals is key to metal biomarker interpretation. For example, whole blood is a good biomarker of exposure to arsenic, cadmium, lead, mercury, and tin, but it is not a good indicator for barium, nickel, and uranium. For some essential metals, the interpretation of whole blood biomarkers is unclear. Urine is the most commonly used biomarker of exposure across metals but it should not be used to assess lead exposure. Essential metals such as zinc and manganese are tightly regulated by homeostatic processes; thus, elevated levels in urine may reflect body loss and metabolic processes rather than excess exposure. Total urinary arsenic may reflect exposure to both organic and inorganic arsenic, thus, arsenic speciation and adjustment for arsebonetaine are needed in populations with dietary seafood consumption. Hair and nails primarily reflect exposure to organic mercury, except in populations exposed to high levels of inorganic mercury such as in occupational and environmental settings. When selecting biomarkers, it is also critical to consider the exposure window of interest. Most populations are chronically exposed to metals in the low-to-moderate range, yet many biomarkers reflect recent exposures. Toenails are emerging biomarkers in this regard. They are reliable biomarkers of long-term exposure for arsenic, mercury, manganese, and selenium. However, more research is needed to understand the role of nails as a biomarker of exposure to other metals. Similarly, teeth are increasingly used to assess lifelong exposures to several essential and non-essential metals such as lead, including during the prenatal window. As metals epidemiology moves towards embracing a multi-metal/mixtures approach and expanding metal panels to include less commonly studied metals, it is important for researchers to have a strong knowledge base about the metal biomarkers included in their research. This review aims to aid metals researchers in their analysis planning, facilitate sound analytical decision-making, as well as appropriate understanding and interpretation of results.

Contaminant Metals as Cardiovascular Risk Factors: A Scientific Statement From the American Heart Association.

Exposure to environmental pollutants is linked to increased risk of cardiovascular disease. Beyond the extensive evidence for particulate air pollution, accumulating evidence supports that exposure to nonessential metals such as lead, cadmium, and arsenic is a significant contributor to cardiovascular disease worldwide. Humans are exposed to metals through air, water, soil, and food and extensive industrial and public use. Contaminant metals interfere with critical intracellular reactions and functions leading to oxidative stress and chronic inflammation that result in endothelial dysfunction, hypertension, epigenetic dysregulation, dyslipidemia, and changes in myocardial excitation and contractile function. Lead, cadmium, and arsenic have been linked to subclinical atherosclerosis, coronary artery stenosis, and calcification as well as to increased risk of ischemic heart disease and stroke, left ventricular hypertrophy and heart failure, and peripheral artery disease. Epidemiological studies show that exposure to lead, cadmium, or arsenic is associated with cardiovascular death mostly attributable to ischemic heart disease. Public health measures reducing metal exposure are associated with reductions in cardiovascular disease death. Populations of color and low socioeconomic means are more commonly exposed to metals and therefore at greater risk of metal-induced cardiovascular disease. Together with strengthening public health measures to prevent metal exposures, development of more sensitive and selective measurement modalities, clinical monitoring of metal exposures, and the development of metal chelation therapies could further diminish the burden of cardiovascular disease attributable to metal exposure.

Cardiovascular risk of metabolically healthy obesity in two european populations: Prevention potential from a metabolomic study.

BACKGROUND: A new definition of metabolically healthy obesity (MHO) has recently been proposed to stratify the heterogeneous mortality risk of obesity. Metabolomic profiling provides clues to metabolic alterations beyond clinical definition. We aimed to evaluate the association between MHO and cardiovascular events and assess its metabolomic pattern. METHODS: This prospective study included Europeans from two population-based studies, the FLEMENGHO and the Hortega study. A total of 2339 participants with follow-up were analyzed, including 2218 with metabolomic profiling. Metabolic health was developed from the third National Health and Nutrition Examination Survey and the UK biobank cohorts and defined as systolic blood pressure < 130 mmHg, no antihypertensive drugs, waist-to-hip ratio < 0.95 for women or 1.03 for men, and the absence of diabetes. BMI categories included normal weight, overweight, and obesity (BMI < 25, 25-30, ≥ 30 kg/m2). Participants were classified into six subgroups according to BMI category and metabolic healthy status. Outcomes were fatal and nonfatal composited cardiovascular events. RESULTS: Of 2339 participants, the mean age was 51 years, 1161 (49.6%) were women, 434 (18.6%) had obesity, 117 (5.0%) were classified as MHO, and both cohorts had similar characteristics. Over a median of 9.2-year (3.7-13.0) follow-up, 245 cardiovascular events occurred. Compared to those with metabolically healthy normal weight, individuals with metabolic unhealthy status had a higher risk of cardiovascular events, regardless of BMI category (adjusted HR: 3.30 [95% CI: 1.73-6.28] for normal weight, 2.50 [95% CI: 1.34-4.66] for overweight, and 3.42 [95% CI: 1.81-6.44] for obesity), whereas those with MHO were not at increased risk of cardiovascular events (HR: 1.11 [95% CI: 0.36-3.45]). Factor analysis identified a metabolomic factor mainly associated with glucose regulation, which was associated with cardiovascular events (HR: 1.22 [95% CI: 1.10-1.36]). Individuals with MHO tended to present a higher metabolomic factor score than those with metabolically healthy normal weight (0.175 vs. -0.057, P = 0.019), and the score was comparable to metabolically unhealthy obesity (0.175 vs. -0.080, P = 0.91). CONCLUSIONS: Individuals with MHO may not present higher short-term cardiovascular risk but tend to have a metabolomic pattern associated with higher cardiovascular risk, emphasizing a need for early intervention.

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.