Changes in epigenetic marks such as DNA methylation and histone acetylation are associated with a broad range of disease traits, including cancer, asthma, metabolic disorders, and various ...reproductive conditions. It seems plausible that changes in epigenetic state may be induced by environmental exposures such as malnutrition, tobacco smoke, air pollutants, metals, organic chemicals, other sources of oxidative stress, and the microbiome, particularly if the exposure occurs during key periods of development. Thus, epigenetic changes could represent an important pathway by which environmental factors influence disease risks, both within individuals and across generations. We discuss some of the challenges in studying epigenetic mediation of pathogenesis and describe some unique opportunities for exploring these phenomena.
Gene function annotation is important for a variety of downstream analyses of genetic data. But experimental characterization of function remains costly and slow, making computational prediction an ...important endeavor. Phylogenetic approaches to prediction have been developed, but implementation of a practical Bayesian framework for parameter estimation remains an outstanding challenge. We have developed a computationally efficient model of evolution of gene annotations using phylogenies based on a Bayesian framework using Markov Chain Monte Carlo for parameter estimation. Unlike previous approaches, our method is able to estimate parameters over many different phylogenetic trees and functions. The resulting parameters agree with biological intuition, such as the increased probability of function change following gene duplication. The method performs well on leave-one-out cross-validation, and we further validated some of the predictions in the experimental scientific literature.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Cumulative exposure--the product of intensity and duration for a constant exposure rate or its integral over time if variable--has been widely used in epidemiologic analyses of extended exposures, ...for example, the "pack-years" variable for tobacco smoking. Although the effects of intensity and duration are known to differ for exposures like smoking and ionizing radiation and simple cumulative exposure does not explicitly allow for modification by other time-related variables, such as age at exposure or time since exposure, the cumulative exposure variable has the merit of simplicity and has been shown to be one of the best predictors for many exposure-response relationships. This commentary discusses recent refinements of the pack-years variable, as discussed in this issue of the Journal by Vlaanderen et al. (Am J Epidemiol. 2014;179(3):290-298), in the broader context of general exposure-time-response relationships.
•Per- and polyfluoroalkyl substances (PFASs) are associated with glucose intolerance.•PFAS is associated with increased lipolysis.•Lipid metabolism may contribute to the association of PFAS with ...glucose intolerance.
Per- and polyfluoroalkyl substances (PFASs) exposure is ubiquitous among the US population and has been linked to adverse health outcomes including cardiometabolic diseases, immune dysregulation and endocrine disruption. However, the metabolic mechanism underlying the adverse health effect of PFASs exposure is unknown.
The aim of this project is to investigate the association between PFASs exposure and altered metabolic pathways linked to increased cardiometabolic risk in young adults.
A total of 102 young adults with 82% overweight or obese participants were enrolled from Southern California between 2014 and 2017. Cardiometabolic outcomes were assessed including oral glucose tolerance test (OGTT) measures, body fat and lipid profiles. High-resolution metabolomics was used to quantify plasma exposure levels of three PFAS congeners and intensity profiles of the untargeted metabolome. Fasting concentrations of 45 targeted metabolites involved in fatty acid and lipid metabolism were used to verify untargeted metabolomics findings. Bayesian Kernel Machine Regression (BKMR) was used to examine the associations between PFAS exposure mixture and cardiometabolic outcomes adjusting for covariates. Mummichog pathway enrichment analysis was used to explore PFAS-associated metabolic pathways. Moreover, the effect of PFAS exposure on the metabolic network, including metabolomic profiles and cardiometabolic outcomes, was investigated.
Higher exposure to perfluorooctanoic acid (PFOA) was associated with higher 30-minute glucose levels and glucose area under the curve (AUC) during the OGTT (p < 0.001). PFAS exposure was also associated with altered lipid pathways, which contributed to the metabolic network connecting PFOA and higher glucose levels following the OGTT. Targeted metabolomics analysis indicated that higher PFOA exposure was associated with higher levels of glycerol (p = 0.006), which itself was associated with higher 30-minute glucose (p = 0.006).
Increased lipolysis and fatty acid oxidation could contribute to the biological mechanisms linking PFAS exposure and impaired glucose metabolism among young adults. Findings of this study warrants future experimental studies and epidemiological studies with larger sample size to replicate.
Carbon (C) buried deep in soil (below 1 m) is often hundreds to thousands of years old, though the stability and sensitivity of this deep C to environmental change are not well understood. We ...examined the C dynamics in three soil horizons and their responses to changes in substrate availability in a coarse-textured sandy spodosol (0.0–0.1, 1.0–1.3, and 2.7–3.0 m deep). Substrate additions were intended to mimic an increase in root exudates and available inorganic nitrogen (N) that would follow an increase of belowground biomass at depth, as previously found in a long-term CO2 enrichment experiment at this site. We incubated these soils for 60 days with glucose, alanine, and leaf litter, crossed with an inorganic N amendment equivalent to three times ambient concentrations. The organic substrates were isotopically labeled (13C), allowing us to determine the source of mineralized C and assess the priming effect. Enzyme activity increased as much as 13 times in the two deeper horizons (1.0–1.3, and 2.7–3.0 m) after the addition of the organic substrates, even though the deepest horizon had microbial biomass and microbial phospholipid fatty acids below the level of detection before the experiment. The deepest horizon (2.7–3.0 m) yielded the largest priming response under alanine, indicating that microorganisms in these soil horizons can become active in response to input of organic substrates. Inorganic N amendments significantly decreased the priming effect, suggesting that decomposition may not be N limited. However, alanine (organic N) yielded the highest priming effect at every soil depth, indicating the importance of differentiating effect of organic and inorganic N on decomposition. Distinct priming effects with depth suggest that portions of the soil profile can respond differently to organic inputs. Our findings indicate that the deep soil C pools might be more vulnerable to environmental or anthropogenic change than previously thought, potentially influencing net CO2 exchange estimates between the land and the atmosphere.
•C cycling in deep soil following labile inputs proceeds in near-absence of active microbes.•Mineralization of deep soil C is more vulnerable to priming than surface soil C.•Soil C priming differs with forms of organic C and nitrogen additions; highest with alanine.•Deep C, thought to be stable, is vulnerable to priming due to environmental change.
Recently, many new approaches, study designs, and statistical and analytical methods have emerged for studying gene-environment interactions (G×Es) in large-scale studies of human populations. There ...are opportunities in this field, particularly with respect to the incorporation of -omics and next-generation sequencing data and continual improvement in measures of environmental exposures implicated in complex disease outcomes. In a workshop called "Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases," held October 17-18, 2014, by the National Institute of Environmental Health Sciences and the National Cancer Institute in conjunction with the annual American Society of Human Genetics meeting, participants explored new approaches and tools that have been developed in recent years for G×E discovery. This paper highlights current and critical issues and themes in G×E research that need additional consideration, including the improved data analytical methods, environmental exposure assessment, and incorporation of functional data and annotations.
To quantify the risk of second primary breast cancer in the contralateral breast (CB) after radiotherapy (RT) for first breast cancer.
The study population included participants in the Women's ...Environmental, Cancer, and Radiation Epidemiology study: 708 cases (women with asynchronous bilateral breast cancer) and 1399 controls (women with unilateral breast cancer) counter-matched on radiation treatment. Participants were <55 years of age at first breast cancer. Absorbed doses to quadrants of the CB were estimated. Rate ratios (RR) and 95% confidence intervals (CI) were calculated using multivariable-adjusted conditional logistic regression models.
Across all patients, the mean radiation dose to the specific quadrant of the CB tumor was 1.1 Gy. Women <40 years of age who received >1.0 Gy of absorbed dose to the specific quadrant of the CB had a 2.5-fold greater risk for CB cancer than unexposed women (RR = 2.5, 95% CI 1.4-4.5). No excess risk was observed in women >40 years of age. Women <40 years of age with follow-up periods >5 years had a RR of 3.0 (95% CI 1.1-8.1), and the dose response was significant (excess RR per Gy of 1.0, 95% CI 0.1-3.0).
Women <40 years of age who received a radiation dose >1.0 Gy to the CB had an elevated, long-term risk of developing a second primary CB cancer. The risk is inversely related to age at exposure and is dose dependent.
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