Recent interest in reference-free deconvolution of DNA methylation data has led to several supervised methods, but these methods do not easily permit the interpretation of underlying cell types.
We ...propose a simple method for reference-free deconvolution that provides both proportions of putative cell types defined by their underlying methylomes, the number of these constituent cell types, as well as a method for evaluating the extent to which the underlying methylomes reflect specific types of cells. We demonstrate these methods in an analysis of 23 Infinium data sets from 13 distinct data collection efforts; these empirical evaluations show that our algorithm can reasonably estimate the number of constituent types, return cell proportion estimates that demonstrate anticipated associations with underlying phenotypic data; and methylomes that reflect the underlying biology of constituent cell types.
Our methodology permits an explicit quantitation of the mediation of phenotypic associations with DNA methylation by cell composition effects. Although more work is needed to investigate functional information related to estimated methylomes, our proposed method provides a novel and useful foundation for conducting DNA methylation studies on heterogeneous tissues lacking reference data.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Exposure to chemical mixtures is recognized as the real-life scenario in all populations, needing new statistical methods that can assess their complex effects.
We aimed to assess the joint effect of ...in utero exposure to arsenic, manganese, and lead on children's neurodevelopment.
We employed a novel statistical approach, Bayesian kernel machine regression (BKMR), to study the joint effect of coexposure to arsenic, manganese, and lead on neurodevelopment using an adapted Bayley Scale of Infant and Toddler Development™. Third Edition, in 825 mother-child pairs recruited into a prospective birth cohort from two clinics in the Pabna and Sirajdikhan districts of Bangladesh. Metals were measured in cord blood using inductively coupled plasma-mass spectrometry.
Analyses were stratified by clinic due to differences in exposure profiles. In the Pabna district, which displayed high manganese levels interquartile range (IQR): 4.8, 18 μg/dl, we found a statistically significant negative effect of the mixture of arsenic, lead, and manganese on cognitive score when cord blood metals concentrations were all above the 60th percentile (As≥0.7 μg/dl, Mn≥6.6 μg/dl, Pb≥4.2 μg/dl) compared to the median (As=0.5 μg/dl, Mn=5.8 μg/dl, Pb=3.1 μg/dl). Evidence of a nonlinear effect of manganese was found. A change in log manganese from the 25th to the 75th percentile when arsenic and manganese were at the median was associated with a decrease in cognitive score of −0.3 (−0.5, −0.1) standard deviations. Our study suggests that arsenic might be a potentiator of manganese toxicity.
Employing a novel statistical method for the study of the health effects of chemical mixtures, we found evidence of neurotoxicity of the mixture, as well as potential synergism between arsenic and manganese. https://doi.org/10.1289/EHP614.
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CEKLJ, DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
Recent studies indicate airborne PAH levels have decreased in the U.S., but it is unclear if this has resulted in PAH exposure changes in the U.S. population.
Examine temporal trends in urinary ...metabolites of Naphthalene, Fluorene, Phenanthrene, and Pyrene in U.S. non-smokers, 6+ years old.
We used biomonitoring data from the National Health and Nutrition Examination Survey (NHANES) program, 2001–2014, (N = 11,053) using survey weighted linear regression. Models were adjusted for age, sex, race/ethnicity, creatinine, BMI, income, diet, and seasonality. Stratified models evaluated the effect of age, sex, and race/ethnicity on trends.
Between 2001 and 2014, Naphthalene exposure increased 36% (p < 0.01); Pyrene exposure increased 106% (p < 0.01); Fluorene and Phenanthrene exposure decreased 55% (p < 0.01), and 37% (p < 0.01), respectively. Naphthalene was the most abundant urinary PAH, 20-fold higher than Fluorene and Phenanthrene, and over 50-fold higher than Pyrene compared to reference groups, effect modification was observed by age (Naphthalene, Pyrene), sex (Fluorene, Pyrene), and race/ethnicity (Naphthalene, Fluorene, Phenanthrene, Pyrene).
This study shows exposure to Naphthalene and Pyrene increased, while exposure to Fluorene and Phenanthrene decreased among the non-smoking U.S. general population between 2001 and 2014, suggesting environmental sources of PAHs have changed over the time period.
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•Polycyclic aromatic hydrocarbons are ubiquitous environmental pollutants.•Urinary PAH metabolites detected in 96% of U.S. non-smokers, age 6+ years, 2001–14.•In U.S. non-smokers 2001–14, exposure to Naphthalene and Pyrene increased.•In U.S. non-smokers 2001–14, exposure to Fluorene and Phenanthrene decreased.•In U.S. non-smokers 2001–14, Non-Hispanic Blacks had highest PAH exposures.
Background: Arsenic is an epigenetic toxicant and could influence fetal developmental programming. Objectives: We evaluated the association between arsenic exposure and DNA methylation in maternal ...and umbilical cord leukocytes. Methods: Drinking-water and urine samples were collected when women were at ≤ 28 weeks gestation; the samples were analyzed for arsenic using inductively coupled plasma mass spectrometry. DNA methylation at CpG sites in p16 (n = 7) and p53 (n = 4), and in LINE-1 and Alu repetitive elements (3 CpG sites in each), was quantified using pyrosequencing in 113 pairs of maternal and umbilical blood samples. We used general linear models to evaluate the relationship between DNA methylation and tertiles of arsenic exposure. Results: Mean (± SD) drinking-water arsenic concentration was 14.8 ± 36.2 µg/L (range: < 1-230 µg/L). Methylation in LINE-1 increased by 1.36% 95% confidence interval (CI): 0.52, 2.21% and 1.08% (95% CI: 0.07, 2.10%) in umbilical cord and maternal leukocytes, respectively, in association with the highest versus lowest tertile of total urinary arsenic per gram creatinine. Arsenic exposure was also associated with higher methylation of some of the tested CpG sites in the promoter region of p16 in umbilical cord and maternal leukocytes. No associations were observed for Alu or p53 methylation. Conclusions: Exposure to higher levels of arsenic was positively associated with DNA methylation in LINE-1 repeated elements, and to a lesser degree at CpG sites within the promoter region of the tumor suppressor gene p16. Associations were observed in both maternal and fetal leukocytes. Future research is needed to confirm these results and determine if these small increases in methylation are associated with any health effects.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
Arsenic has antimicrobial properties at high doses yet few studies have examined its effect on gut microbiota. This warrants investigation since arsenic exposure increases the risk of many diseases ...in which gut microbiota have been shown to play a role. We examined the association between arsenic exposure from drinking water and the composition of intestinal microbiota in children exposed to low and high arsenic levels during prenatal development and early life.
16S rRNA gene sequencing revealed that children with high arsenic exposure had a higher abundance of Proteobacteria in their stool compared to matched controls with low arsenic exposure. Furthermore, whole metagenome shotgun sequencing identified 332 bacterial SEED functions that were enriched in the high exposure group. A separate model showed that these genes, which included genes involved in virulence and multidrug resistance, were positively correlated with arsenic concentration within the group of children in the high arsenic group. We performed reference free genome assembly, and identified strains of E.coli as contributors to the arsenic enriched SEED functions. Further genome annotation of the E.coli genome revealed two strains containing two different arsenic resistance operons that are not present in the gut microbiome of a recently described European human cohort (Metagenomics of the Human Intestinal Tract, MetaHIT). We then performed quantification by qPCR of two arsenic resistant genes (ArsB, ArsC). We observed that the expression of these two operons was higher among the children with high arsenic exposure compared to matched controls.
This preliminary study indicates that arsenic exposure early in life was associated with altered gut microbiota in Bangladeshi children. The enrichment of E.coli arsenic resistance genes in the high exposure group provides an insight into the possible mechanisms of how this toxic compound could affect gut microbiota.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Driven by major scientific advances in analytical methods, biomonitoring, computation, and a newly articulated vision for a greater impact in public health, the field of exposure science is ...undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the “systems approaches” used in the biological sciences is a necessary step in this evolution. Here we propose the aggregate exposure pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the adverse outcome pathway (AOP) concept in the toxicological sciences. Aggregate exposure pathways offer an intuitive framework to organize exposure data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathways and adverse outcome pathways, completing the source to outcome continuum for more meaningful integration of exposure assessment and hazard identification. Together, the two frameworks form and inform a decision-making framework with the flexibility for risk-based, hazard-based, or exposure-based decision making.
Heavy metals can act as co-selecting agents and promote antibiotic resistance. Most frequent resistances to heavy metals are observed for zinc and cadmium. P. aeruginosa and E. coli are commonly ...resistant to heavy metals and antibiotics. Heavy metals proliferate antibiotic resistance through co- and cross-resistance. Heavy metal and antibiotic resistances are common near anthropogenic activities.
Antibiotic resistance in human pathogens can proliferate under selective pressures. Heavy metals in environmental reservoirs may contribute to selecting antibiotic-resistant strains. To determine the associations between heavy metals and antibiotic resistance, a literature review was conducted to systematically collect and categorize evidence for co-occurrence of resistance to heavy metals and antibiotics within human pathogenic bacteria in water, wastewater, and soil. In total, 42 publications adhered to inclusion criteria. Across the reservoirs, zinc and cadmium were the most commonly observed heavy metals associated with resistance to antibiotics. Pseudomonas aeruginosa and Escherichia coli were the most commonly studied bacteria with reported co-occurrence of resistance to several heavy metals and antibiotic classes. As co-selecting agents, prevalence of heavy metals in the environment can proliferate resistance to heavy metals and antibiotics through co-resistance and cross-resistance mechanisms. In comparing different reservoirs, soils and sediments harbor higher heavy metal and antibiotic resistances compared to water environments. Additionally, abiotic factors such as pH can affect the solubility and hence, the availability of heavy metals to bacterial pathogens. Overall, our review demonstrates heavy metals act as co-selecting agents in the proliferation of antibiotic resistance in human pathogens in multiple environmental reservoirs. More studies that include statistical data are needed to further describe the exposure-response relationships between heavy metals and antibiotic resistance in different environmental media. Moreover, integration of culture-based and molecular-based methods in future studies are recommended to better inform our understanding of bacterial co- and cross-resistance mechanisms to heavy metals and antibiotics.
Silicone wristbands can be used as passive sampling tools for measuring personal environmental exposure to organic compounds. Due to the lightweight and simple design, the wristband may be a useful ...technique for measuring children's exposure. In this study, we tested the stability of flame retardant compounds in silicone wristbands and developed an analytical approach for measuring 41 flame retardants in the silicone wristband in order to evaluate exposure to these compounds in preschool-aged children. To evaluate the robustness of using wristbands to measure flame retardants, we evaluated the stability of 3 polybrominated diphenyl ethers (BDEs), and 2 organophosphate flame retardants (OPFRs) in wristbands over 84 days and did not find any evidence of significant loss over time at either 4 or −20°C (p>0.16). We recruited a cohort of 92 preschool aged children in Oregon to wear the wristband for 7 days in order to characterize children's acceptance of the technology, and to characterize their exposure to flame retardants. Seventy-seven parents returned the wristbands for analysis of 35 BDEs, 4 OPFRs, and 2 other brominated flame retardants although 5 were excluded from the exposure assessment due to protocol deviations (n=72). A total of 20 compounds were detected above the limit of quantitation, and 11 compounds including 4 OPFRs and 7 BDEs were detected in over 60% of the samples. Children's gender, age, race, recruitment site, and family context were not significantly associated with returning wristbands or compliance with protocols. Comparisons between flame retardant data and socio-demographic information revealed significant differences in total exposures to both ΣBDEs and ΣOPFRs based on age of house, vacuuming frequency, and family context. These results demonstrate that preschool children in Oregon are exposed to BDEs that are no longer being produced in the United States and to OPFRs that have been used as an alternative to polybrominated compounds. Silicone wristbands were well tolerated by young children and were useful for characterizing personal exposure to flame retardants that were not bound to particulate matter.
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•Silicone wristbands are a non-invasive approach for personal sampling of chemical mixtures.•Flame retardants were stable in a simulation of transport and storage stability in wristband samplers.•A total of 20 flame retardants were detected in silicone wristbands worn by children.•Some flame retardants measured in wristbands were associated with house age, vacuum frequency, and family context.
Antibiotic resistance is a leading cause of hospitalization and death worldwide. Heavy metals such as arsenic have been shown to drive co-selection of antibiotic resistance, suggesting ...arsenic-contaminated drinking water is a risk factor for antibiotic resistance carriage. This study aimed to determine the prevalence and abundance of antibiotic-resistant Escherichia coli (AR-Ec) among people and drinking water in high (Hajiganj, >100 μg/L) and low arsenic-contaminated (Matlab, <20 μg/L) areas in Bangladesh. Drinking water and stool from mothers and their children (<1 year) were collected from 50 households per area. AR-Ec was detected via selective culture plating and isolates were tested for antibiotic resistance, arsenic resistance, and diarrheagenic genes by PCR. Whole-genome sequencing (WGS) analysis was done for 30 E. coli isolates from 10 households. Prevalence of AR-Ec was significantly higher in water in Hajiganj (48%) compared to water in Matlab (22%, p <0.05) and among children in Hajiganj (94%) compared to children in Matlab (76%, p <0.05), but not among mothers. A significantly higher proportion of E. coli isolates from Hajiganj were multidrug-resistant (83%) compared to isolates from Matlab (71%, p <0.05). Co-resistance to arsenic and multiple antibiotics (MAR index >0.2) was observed in a higher proportion of water (78%) and child stool (100%) isolates in Hajiganj than in water (57%) and children (89%) in Matlab (p <0.05). The odds of arsenic-resistant bacteria being resistant to third-generation cephalosporin antibiotics were higher compared to arsenic-sensitive bacteria (odds ratios, OR 1.2-7.0, p <0.01). WGS-based phylogenetic analysis of E. coli isolates did not reveal any clustering based on arsenic exposure and no significant difference in resistome was found among the isolates between the two areas. The positive association detected between arsenic exposure and antibiotic resistance carriage among children in arsenic-affected areas in Bangladesh is an important public health concern that warrants redoubling efforts to reduce arsenic exposure.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Biomonitoring data shows that people are exposed to phthalates, phenols and perchlorates. Many of these compounds are endocrine disrupting compounds that affect thyroid hormone levels. Yet the effect ...of these compounds on thyroid hormone levels are often evaluated individually rather than as a mixture. Our objective was to examine the association between 11 urinary endocrine disrupting compounds and thyroid hormones using structural equation models.
Using data from the National Health and Nutrition and Examination Survey 2007–2008, we fit a latent variable utilizing urinary measurements of 9 compounds in females (perchlorate, bisphenol A, benzophenone-3, mono-2ethyl5carboxypentyl phthalate, mono-n-butyl phthalate, mono-(3-carboxypropyl) phthalate, mono(2ethyl5hydroxyhexyl) phthalate, mono-benzyl phthalate, and mono-isobutyl phthalate) and 8 compounds in males (without benzophenone-3). The association of the latent variable with serum thyroid hormones (Total T3, Total T4, and Thyroid Stimulating Hormones) was assessed in females (N = 710) and males (N = 850) over the age of 12 controlling for age, race, and urinary creatinine.
In males, urinary endocrine disrupting compound levels were negatively associated with thyroxine (β: −0.19, 95% Confidence Interval (95% CI): −0.31, −0.05). In females, urinary endocrine disrupting compound levels were positively associated with triiodothyronine serum concentrations (β: 0.09, 95% CI: −0.03, 0.21) however this association was not statistically significant.
This cross-sectional analysis provides additional evidence that environmental exposure to phthalates and phenols is associated with endocrine-related processes. Furthermore, these results suggested sex-specific differences in exposure to endocrine disrupting mixtures, and the exposure-response between endocrine disrupting mixtures and thyroid hormone levels. Specifically, higher exposure to a mixture of endocrine disrupting compounds was associated with lower levels of total T4 in males but not in females. While a structural methodological framework was used to assess these complex relationships, the cross sectional nature of this analysis limits causal inference and further research is needed to determine the clinical significance of these findings.
•A SEM of several EDCs and thyroid hormones is proposed.•A more realistic exposure scenario was modeled.•In males, a negative relationship between EDCs and T4 was observed.
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