Background Prenatal exposure to arsenic has been linked to a range of adverse health conditions in later life. Such fetal origins of disease are frequently the result of environmental effects on the epigenome, leading to long-term alterations in gene expression. Several studies have demonstrated effects of prenatal arsenic exposure on DNA methylation; however the impact of arsenic on the generation and decoding of post-translational histone modifications (PTHMs) is less well characterized, and has not been studied in the context of prenatal human exposures. Methods In the current study, we examined the effect of exposure to low-to-moderate levels of arsenic in a US birth cohort, on the expression of 138 genes encoding key epigenetic regulators in the fetal portion of the placenta. Our candidate genes included readers, writers and erasers of PTHMs, and chromatin remodelers. Results Arsenic exposure was associated with the expression of 27 of the 138 epigenetic genes analyzed. When the cohort was stratified by fetal sex, arsenic exposure was associated with the expression of 40 genes in male fetal placenta, and only 3 non-overlapping genes in female fetal placenta. In particular, we identified an inverse relationship between arsenic exposure and expression of the gene encoding the histone methyltransferase, PRDM6 ( p < 0.001). Mutation of PRDM6 has been linked to the congenital heart defect, patent ductus arteriosus. Conclusions Our findings suggest that prenatal arsenic exposure may have sex-specific effects on the fetal epigenome, which could plausibly contribute to its subsequent health impacts. Electronic supplementary material The online version of this article (10.1186/s12940-019-0455-9) contains supplementary material, which is available to authorized users.

Background: Unmeasured confounders are commonplace in observational studies conducted using real-world data. Prior event rate ratio (PERR) adjustment is a technique shown to perform well in addressing such confounding.However, it has been demonstrated that, in some circumstances, the PERR method actually increases rather than decreases bias. In this work, we seek to better understand the robustness of PERR adjustment. Methods:We begin with a Bayesian network representation of a generalized observational study, which is subject to unmeasured confounding. Previous work evaluating PERR performance used Monte Carlo simulation to calculate joint probabilities of interest within the study population. Here, we instead use a Bayesian networks framework.Results: Using this streamlined analytic approach, we are able to conduct probabilistic bias analysis (PBA) using large numbers of combinations of parameters and thus obtain a comprehensive picture of PERR performance. We apply our methodology to a recent study that used the PERR in evaluating elderly-specific high-dose (HD) influenza vaccine in the US Veterans Affairs population. That study obtained an HD relative effectiveness of 25% (95% CI: 2%-43%) against influenza-and pneumonia-associated hospitalization, relative to standard-dose influenza vaccine. In this instance, we find that the PERR-adjusted result is more like to underestimate rather than to overestimate the relative effectiveness of the intervention. Conclusions:Although the PERR is a powerful tool for mitigating the effects of unmeasured confounders, it is not infallible. Here, we develop some general guidance for when a PERR approach is appropriate and when PBA is a safer option. KEYWORDSBayesian networks, observational studies, probabilistic bias analysis, prior event rate ratio (PERR), unmeasured confoundersThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Objective:Clostridioides difficile infection (CDI) remains a significant public health concern, resulting in excess morbidity, mortality, and costs. Additional insight into the burden of CDI in adults aged <65 years is needed.Design/Setting:A 6-year retrospective cohort study was conducted using data extracted from United States Veterans Health Administration electronic medical records.Patients/Methods:Patients aged 18–64 years on January 1, 2011, were followed until incident CDI, death, loss-to-follow-up, or December 31, 2016. CDI was identified by a diagnosis code accompanied by metronidazole, vancomycin, or fidaxomicin therapy, or positive laboratory test. The clinical setting of CDI onset was defined according to 2017 SHEA-IDSA guidelines.Results:Of 1,073,900 patients, 10,534 had a CDI during follow-up. The overall incidence rate was 177 CDIs per 100,000 person years, rising steadily from 164 per 100,000 person years in 2011 to 189 per 100,000 person years in 2016. Those with a CDI were slightly older (55 vs 51 years) and sicker, with a higher baseline Charlson comorbidity index score (1.4 vs 0.5) than those without an infection. Nearly half (48%) of all incident CDIs were community associated, and this proportion rose from 41% in 2011 to 56% in 2016.Conclusions:The findings from this large retrospective study indicate that CDI incidence, driven primarily by increasing community-associated infection, is rising among young and middle-aged adult Veterans with high service-related disability. The increasing burden of community associated CDI in this vulnerable population warrants attention. Future studies quantifying the economic and societal burden of CDI will inform decisions surrounding prevention strategies.

ObjectivesAccurate assessment of tobacco smoke exposure is key to evaluate its effects. We sought to validate and establish cut-offs for self-reported smoking and secondhand smoke (SHS) exposure during pregnancy using urinary cotinine and 4-(methylnitrosamino)-1-(-3-pyridyl)-1-butanol (NNAL) in a large contemporary prospective study from the USA, with lower smoking prevalence than has previously been evaluated.DesignProspective birth cohort.SettingPregnancy clinics in New Hampshire and Vermont, USA.Participants1396 women enrolled in the New Hampshire Birth Cohort Study with self-reported smoking, urinary cotinine, NNAL and pregnancy outcomes.Primary and secondary outcome measuresCut-offs for urinary cotinine and NNAL concentrations were estimated from logistic regression models using Youden’s method to predict SHS and active smoking. Cotinine and NNAL were each used as the exposure in separate multifactorial models for pregnancy outcomes.ResultsSelf-reported maternal smoking was: 72% non-smokers, 5.7% ex-smokers, 6.4% SHS exposure, 6.2% currently smoked, 10% unreported. Cotinine and NNAL levels were low and highly intercorrelated (r=0.91). Geometric mean cotinine, NNAL were 0.99 ng/mL, 0.05 pmol/mL, respectively. Cotinine cut-offs for SHS, current smoking were 1.2 ng/mL and 1.8 ng/mL (area under curve (AUC) 95% CI: 0.52 (0.47 to 0.57), 0.90 (0.85 to 0.94)). NNAL cut-off for current smoking was 0.09 pmol/mL (AUC=0.82 (95% CI 0.77 to 0.87)). Using cotinine and NNAL cut-offs combined gave similar AUC to cotinine alone, 0.87 (95% CI 0.82 to 0.91). Cotinine and NNAL gave almost identical effect estimates when modelling pregnancy outcomes.ConclusionsIn this population, we observed high concordance between self-complete questionnaire smoking data and urinary cotinine and NNAL. With respect to biomarkers, either cotinine or NNAL can be used as a measure of tobacco smoke exposure overall but only cotinine can be used to detect SHS.

As part of the New Hampshire Birth Cohort Study, children 3 to 5 years of age participated in a personal PM2.5 exposure study. This paper characterizes the personal PM2.5 exposure and protocol compliance measured with a wearable sensor. The MicroPEM™ collected personal continuous and integrated measures of PM2.5 exposure and compliance data on 272 children. PM2.5, black carbon (BC), and brown carbon tobacco smoke (BrC-ETS) exposure was measured from the filters. We performed a multivariate analysis of woodstove presence and other factors that influenced PM2.5, BC, and BrC exposures. We collected valid exposure data from 258 of the 272 participants (95%). Children wore the MicroPEM for an average of 46% of the 72-h period, and over 80% for a 2-day, 1-night period (with sleep hours counted as non-compliance for this study). Elevated PM2.5 exposures occurred in the morning, evening, and overnight. Median PM2.5, BC, and BrC-ETS concentrations were 8.1 μg/m3, 3.6 μg/m3, and 2.4 μg/m3. The combined BC and BrC-ETS mass comprised 72% of the PM2.5. Woodstove presence, hours used per day, and the primary heating source were associated with the children’s PM2.5 exposure and air filters were associated with reduced PM2.5 concentrations. Our findings suggest that woodstove smoke contributed significantly to this cohort’s PM2.5 exposure. The high sample validity and compliance rate demonstrated that the MicroPEM can be worn by young children in epidemiologic studies to measure their PM2.5 exposure, inform interventions to reduce the exposures, and improve children’s health.