Humans are exposed to a broad range of organic chemicals. Although targeted gas chromatography mass spectrometry techniques are used to quantify a limited number of persistent organic pollutants and trace organic contaminants in biological samples, nontargeted, high-resolution mass spectrometry (HRMS) methods assess the human exposome more extensively. We present a QuEChERS extraction for targeted and nontargeted analysis of trace organic contaminants using HRMS and compare this method to a traditional, cartridge-based solid-phase extraction (SPE). Following validation using reference and spiked serum samples, the method was applied to plasma samples (n = 75) from the Prospective investigation of Obesity, Energy, and Metabolism (POEM) study. We quantified 44 analytes using targeted analysis and 6247 peaks were detected using the nontargeted approach. Over 90% of targeted analytes were at least 90% recovered using the QuEChERS method in spiked serum samples. In nontargeted analysis, 84% of the peaks were above the method detection limit with area counts up to 3.0 × 105 times greater using the QuEChERS method. Of the targeted compounds, 88% were also identified in the nontargeted analysis. We categorized the 4212 chemicals assigned an identity in using EPA's CompTox Dashboard and 1076 chemicals were found in at least one list. The category with the highest number of chemicals was "androgen or estrogen receptor activity." The findings demonstrate that a QuEChERS technique is suitable for both targeted and nontargeted analysis of trace organic contaminants in biological samples.

Background

Lipoproteins at aberrant levels are known to play a role in cardiovascular disease. The metabolite of the insecticide dichlorodiphenyltrichloroethane (DDT), p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE), physically associates with lipids and accumulates in adipose tissue. Little is known about which lipoproteins associate with p,p'-DDE. An association between p,p'-DDE exposure and altered levels of circulating lipids was assessed in a large human cohort using a detailed analysis of lipoprotein content.

Methods

Plasma samples were collected from the subset of 75-year old Swedes in the Prospective Investigation of the Vasculature of Uppsala Seniors (PIVUS) cohort who were not prescribed lipid lowering medication (n = 571). p,p'-DDE concentrations in plasma were measured using high-throughput solid phase extraction and gas chromatography-high resolution mass spectrometry. Analysis of plasma lipoprotein content was performed with nuclear magnetic resonance spectroscopy.

Results

Detectable levels of p,p'-DDE were found in the plasma samples of all subjects. Elevated p,p'-DDE levels were associated with increased concentrations of lipoproteins of all diameters, with the exception of high density lipoprotein (HDL) of diameters between 14.3 nm-10.9 nm. Of the lipoprotein constituents, triglycerides were most uniformly associated with elevated p,p'-DDE across lipoproteins. p,p'-DDE was furthermore associated with apolipoprotein B, but not apolipoprotein A1.

Conclusions

The positive associations observed between each lipoprotein class and elevated p,p'-DDE support previous data suggesting that p,p'-DDE interacts with lipoproteins within plasma. It is speculated that both physio-chemical and biological mechanisms may explain why p,p'-DDE does not uniformly associate with lipids across lipoproteins.

Visceral adipose tissue (VAT) is a strong prognostic factor for cardiovascular disease and a potential target for cardiovascular risk stratification. Because VAT is difficult to measure in clinical practice, we estimated prediction models with predictors routinely measured in general practice and VAT as outcome using ridge regression in 2,501 middle-aged participants from the Netherlands Epidemiology of Obesity study, 2008-2012. Adding waist circumference and other anthropometric measurements on top of the routinely measured variables improved the optimism-adjusted R2 from 0.50 to 0.58 with a decrease in the root-mean-square error (RMSE) from 45.6 to 41.5 cm2 and with overall good calibration. Further addition of predominantly lipoprotein-related metabolites from the Nightingale platform did not improve the optimism-corrected R2 and RMSE. The models were externally validated in 370 participants from the Prospective Investigation of Vasculature in Uppsala Seniors (PIVUS, 2006-2009) and 1,901 participants from the Multi-Ethnic Study of Atherosclerosis (MESA, 2000-2007). Performance was comparable to the development setting in PIVUS (R2 = 0.63, RMSE = 42.4 cm2, calibration slope = 0.94) but lower in MESA (R2 = 0.44, RMSE = 60.7 cm2, calibration slope = 0.75). Our findings indicate that the estimation of VAT with routine clinical measurements can be substantially improved by incorporating waist circumference but not by metabolite measurements.

Background

The primary biomarkers used to define CKD are serum creatinine and albuminuria. These biomarkers have directed focus on the filtration and barrier functions of the kidney glomerulus even though albuminuria results from tubule dysfunction as well. Given that proximal tubules make up ∼90% of kidney cortical mass, we evaluated whether a sensitive and specific marker of proximal tubule injury, urinary kidney injury molecule-1 (KIM-1), is elevated in individuals with CKD or with risk factors for CKD.

Methods

We measured urinary KIM-1 in participants of five cohort studies from the USA and Sweden. Participants had a wide range of kidney function and were racially and ethnically diverse. Multivariable linear regression models were used to test the association of urinary KIM-1 with demographic, clinical and laboratory values.

Results

In pooled, multivariable-adjusted analyses, log-transformed, creatinine-normalized urinary KIM-1 levels were higher in those with lower eGFR {β = -0.03 per 10 mL/min/1.73 m(2) [95% confidence interval (CI) -0.05 to -0.02]} and greater albuminuria [β = 0.16 per unit of log albumin:creatinine ratio (95% CI 0.15-0.17)]. Urinary KIM-1 levels were higher in current smokers, lower in blacks than nonblacks and lower in users versus nonusers of angiotensin-converting enzyme inhibitors and angiotensin receptor blockers.

Conclusion

Proximal tubule injury appears to be an integral and measurable element of multiple stages of CKD.

Summary: From the lectures presented at the 2nd International Workshop on Obesity and Environmental Contaminants, which was held in Uppsala, Sweden, on 8–9 October 2015, it became evident that the findings from numerous animal and epidemiological studies are consistent with the hypothesis that environmental contaminants could contribute to the global obesity epidemic. To increase awareness of this important issue among scientists, regulatory agencies, politicians, chemical industry management, and the general public, the authors summarize compelling scientific evidence that supports the hypothesis and discuss actions that could restrict the possible harmful effects of environmental contaminants on obesity.

Background

The concept of chemical agents having properties that confer potential hazard called key characteristics (KCs) was first developed to identify carcinogenic hazards. Identification of KCs of cardiovascular (CV) toxicants could facilitate the systematic assessment of CV hazards and understanding of assay and data gaps associated with current approaches.

Objectives

We sought to develop a consensus-based synthesis of scientific evidence on the KCs of chemical and nonchemical agents known to cause CV toxicity along with methods to measure them.

Methods

An expert working group was convened to discuss mechanisms associated with CV toxicity.

Results

The group identified 12 KCs of CV toxicants, defined as exogenous agents that adversely interfere with function of the CV system. The KCs were organized into those primarily affecting cardiac tissue (numbers 1-4 below), the vascular system (5-7), or both (8-12), as follows: 1) impairs regulation of cardiac excitability, 2) impairs cardiac contractility and relaxation, 3) induces cardiomyocyte injury and death, 4) induces proliferation of valve stroma, 5) impacts endothelial and vascular function, 6) alters hemostasis, 7) causes dyslipidemia, 8) impairs mitochondrial function, 9) modifies autonomic nervous system activity, 10) induces oxidative stress, 11) causes inflammation, and 12) alters hormone signaling.

Discussion

These 12 KCs can be used to help identify pharmaceuticals and environmental pollutants as CV toxicants, as well as to better understand the mechanistic underpinnings of their toxicity. For example, evidence exists that fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] air pollution, arsenic, anthracycline drugs, and other exogenous chemicals possess one or more of the described KCs. In conclusion, the KCs could be used to identify potential CV toxicants and to define a set of test methods to evaluate CV toxicity in a more comprehensive and standardized manner than current approaches. https://doi.org/10.1289/EHP9321.

Background

Genome-wide association studies have identified loci influencing circulating lipid concentrations in humans; further information on novel contributing genes, pathways, and biology may be gained through studies of epigenetic modifications.

Methods and results

To identify epigenetic changes associated with lipid concentrations, we assayed genome-wide DNA methylation at cytosine-guanine dinucleotides (CpGs) in whole blood from 2306 individuals from 2 population-based cohorts, with replication of findings in 2025 additional individuals. We identified 193 CpGs associated with lipid levels in the discovery stage (P<1.08E-07) and replicated 33 (at Bonferroni-corrected P<0.05), including 25 novel CpGs not previously associated with lipids. Genes at lipid-associated CpGs were enriched in lipid and amino acid metabolism processes. A differentially methylated locus associated with triglycerides and high-density lipoprotein cholesterol (HDL-C; cg27243685; P=8.1E-26 and 9.3E-19) was associated with cis-expression of a reverse cholesterol transporter (ABCG1; P=7.2E-28) and incident cardiovascular disease events (hazard ratio per SD increment, 1.38; 95% confidence interval, 1.15-1.66; P=0.0007). We found significant cis-methylation quantitative trait loci at 64% of the 193 CpGs with an enrichment of signals from genome-wide association studies of lipid levels (P_TC=0.004, P_HDL-C=0.008 and P_{triglycerides}=0.00003) and coronary heart disease (P=0.0007). For example, genome-wide significant variants associated with low-density lipoprotein cholesterol and coronary heart disease at APOB were cis-methylation quantitative trait loci for a low-density lipoprotein cholesterol-related differentially methylated locus.

Conclusions

We report novel associations of DNA methylation with lipid levels, describe epigenetic mechanisms related to previous genome-wide association studies discoveries, and provide evidence implicating epigenetic regulation of reverse cholesterol transport in blood in relation to occurrence of cardiovascular disease events.

Background

n-3 and n-6 PUFAs have physiologic roles in sleep processes, but little is known regarding circulating n-3 and n-6 PUFA and sleep parameters.

Objectives

We sought to assess associations between biomarkers of n-3 and n-6 PUFA intake with self-reported sleep duration and difficulty falling sleeping in the Fatty Acids and Outcome Research Consortium.

Methods

Harmonized, de novo, individual-level analyses were performed and pooled across 12 cohorts. Participants were 35-96 y old and from 5 nations. Circulating measures included α-linolenic acid (ALA), EPA, docosapentaenoic acid (DPA), DHA, EPA + DPA + DHA, linoleic acid, and arachidonic acid. Sleep duration (10 cohorts, n = 18,791) was categorized as short (≤6 h), 7-8 h (reference), or long (≥9 h). Difficulty falling asleep (8 cohorts, n = 12,500) was categorized as yes or no. Associations between PUFAs, sleep duration, and difficulty falling sleeping were assessed by cross-sectional multinomial logistic regression using standardized protocols and covariates. Cohort-specific multivariable-adjusted ORs per quintile of PUFAs were pooled with inverse-variance weighted meta-analysis.

Results

In pooled analysis adjusted for sociodemographic characteristics and health status, participants with higher very long-chain n-3 PUFAs were less likely to have long sleep duration. In the top compared with the bottom quintiles, the multivariable-adjusted ORs (95% CIs) for long sleep were 0.78 (95% CI: 0.65, 0.95) for DHA and 0.76 (95% CI: 0.63, 0.93) for EPA + DPA + DHA. Significant associations for ALA and n-6 PUFA with short sleep duration or difficulty falling sleeping were not identified.

Conclusions

Participants with higher concentrations of very long-chain n-3 PUFAs were less likely to have long sleep duration. While objective biomarkers reduce recall bias and misclassification, the cross-sectional design limits assessment of the temporal nature of this relation. These novel findings across 12 cohorts highlight the need for experimental and biological assessments of very long-chain n-3 PUFAs and sleep duration.

Obesity is a multifactorial disease with both genetic and environmental components. The prevailing view is that obesity results from an imbalance between energy intake and expenditure caused by overeating and insufficient exercise. We describe another environmental element that can alter the balance between energy intake and energy expenditure: obesogens. Obesogens are a subset of environmental chemicals that act as endocrine disruptors affecting metabolic endpoints. The obesogen hypothesis posits that exposure to endocrine disruptors and other chemicals can alter the development and function of the adipose tissue, liver, pancreas, gastrointestinal tract, and brain, thus changing the set point for control of metabolism. Obesogens can determine how much food is needed to maintain homeostasis and thereby increase the susceptibility to obesity. The most sensitive time for obesogen action is in utero and early childhood, in part via epigenetic programming that can be transmitted to future generations. This review explores the evidence supporting the obesogen hypothesis and highlights knowledge gaps that have prevented widespread acceptance as a contributor to the obesity pandemic. Critically, the obesogen hypothesis changes the narrative from curing obesity to preventing obesity.