Diesel exhaust (DE) is a major contributor to ambient air pollution around the world. It is a known human carcinogen that targets the respiratory system and increases risk for many diseases, but there is limited research on the effects of DE exposure on the epigenome of human bronchial epithelial cells. Understanding the epigenetic impact of this environmental pollutant can elucidate biological mechanisms involved in the pathogenesis of harmful DE-related health effects. To estimate the causal effect of short-term DE exposure on the bronchial epithelial epigenome, we conducted a controlled single-blinded randomized crossover human experiment of exposure to DE and used bronchoscopy and Illumina 450K arrays for data collection and analysis, respectively. Of the 13 participants, 11 (85%) were male and 2 (15%) were female, and 12 (92%) were White and one (8%) was Hispanic; the mean age was 26 years (SD = 3.8 years). Eighty CpGs were differentially methylated, achieving the minimum possible exact P-value of P =2.44 × 10-4 (i.e. 2/213). In regional analyses, we found two differentially methylated regions (DMRs) annotated to the chromosome 5 open reading frame 63 genes (C5orf63; 7-CpGs) and unc-45 myosin chaperone A gene (UNC45A; 5-CpGs). Both DMRs showed increased DNA methylation after DE exposure. The average causal effects for the DMRs ranged from 1.5% to 6.0% increases in DNA methylation at individual CpGs. In conclusion, we found that short-term DE alters DNA methylation of genes in target bronchial epithelial cells, demonstrating epigenetic level effects of exposure that could be implicated in pulmonary pathologies.
Studies have pointed out that air pollution may be a contributing factor to the coronavirus disease 2019 (COVID-19) pandemic. However, the specific links between air pollution and severe acute respiratory syndrome-coronavirus-2 infection remain unclear. Here we provide evidence from in vitro, animal and human studies from the existing literature. Epidemiological investigations have related various air pollutants to COVID-19 morbidity and mortality at the population level, however, those studies suffer from several limitations. Air pollution may be linked to an increase in COVID-19 severity and lethality through its impact on chronic diseases, such as cardiopulmonary diseases and diabetes. Experimental studies have shown that exposure to air pollution leads to a decreased immune response, thus facilitating viral penetration and replication. Viruses may persist in air through complex interactions with particles and gases depending on: 1) chemical composition; 2) electric charges of particles; and 3) meteorological conditions such as relative humidity, ultraviolet (UV) radiation and temperature. In addition, by reducing UV radiation, air pollutants may promote viral persistence in air and reduce vitamin D synthesis. Further epidemiological studies are needed to better estimate the impact of air pollution on COVID-19. In vitro and in vivo studies are also strongly needed, in particular to more precisely explore the particle-virus interaction in air.
BACKGROUND: Multiple Sclerosis (MS) remains to be a public health challenge, due to its unknown biological mechanisms and clinical impacts on young people. The prevalence of this disease in Iran is reported to be 5.30 to 74.28 per 100,000-person. Because of high prevalence of this disease in Fars province, the purpose of this study was to assess the spatial pattern of MS incidence rate by modeling both the associations s of spatial dependence between neighboring regions and risk factors in a Bayesian Poisson model, which can lead to the improvement of health resource allocation decisions.
METHOD: Data from 5468 patients diagnosed with MS were collected, according to the McDonald's criteria. New cases of MS were reported by the MS Society of Fars province from 1991 until 2016. The association between the percentage of people with low vitamin D intake, smoking, abnormal BMI and alcohol consumption in addition to spatial structure in a Bayesian spatio-temporal hierarchical model were used to determine the relative risk and trend of MS incidence rate in 29 counties of Fars province.
RESULTS: County-level crude incidence rates ranged from 0.22 to 11.31 cases per 100,000-person population. The highest relative risk was estimated at 1.80 in the county of Shiraz, the capital of Fars province, while the lowest relative risk was estimated at 0.11 in Zarindasht county in southern of Fars. The percentages of vitamin D supplementation intake and smoking were significantly associated with the incidence rate of MS. The results showed that 1% increase in vitamin D supplementation intake is associated with 2% decrease in the risk of MS and 1% increase in smoking is associated with 16% increase in the risk of MS.
CONCLUSION: Bayesian spatio-temporal analysis of MS incidence rate revealed that the trend in the south and south east of Fars province is less steep than the mean trend of this disease. The lower incidence rate was associated with a higher percentage of vitamin D supplementation intake and a lower percentage of smoking. Previous studies have also shown that smoking and low vitamin D, among all covariates or risk factors, might be associated with high incidence of MS.
OBJECTIVES: Oral and oropharyngeal squamous cell carcinoma (SCC) is the 10th most common cancer in the United States (8th in males, 13th in females), with an estimated 54,010 new cases expected in 2021, and is primarily associated with smoked tobacco, heavy alcohol consumption, areca nut use and persistent high-risk human papillomavirus (HPV). Family history of cancer (FHC) and family history of head and neck cancer (FHHNC) have been reported to play an important role in the development of OSCC. We aimed to investigate the role of FHC, FHHNC and personal history of cancer in first/second degree-relatives as co-risk factors for oral cancer.
METHODS: This was a retrospective study of patients diagnosed with OSCC at the Division of Oral Medicine and Dentistry at Brigham and Women's Hospital and at the Division of Head and Neck Oncology at Dana Farber Cancer Institute. Conditional logistic regressions were performed to examine whether OSCC was associated with FHC and FHHNC of FDRs and SDRs, personal history of cancer and secondary risk factors.
RESULTS: Overall, we did not find an association between FHC, FHHNC and OSCC risk, whereas patients with a cancer history in one of their siblings were 1.6-times more likely to present with an OSCC. When secondary risk factors were considered, patients with a history of oral leukoplakia and dysplasia had a 16-times higher risk of having an OSCC.
CONCLUSIONS: Our study confirmed that a previous history of oral leukoplakia or dysplasia was an independent risk factor for OSCC. A positive family history of cancer in one or more siblings may be an additional risk factor for OSCC.
Per- and polyfluoroalkyl substances (PFASs) are highly persistent in the environment and may cause depressed immune function. Previous studies have linked PFAS exposure to lower vaccine responses in children, but research in adults is limited. Therefore, the present study evaluated the associations between exposure to PFASs and serum antibody concentrations in adults vaccinated at age 28 years in the Faroe Islands. PFAS concentrations were determined from cord-blood collected at birth and serum samples collected at ages 7, 14, 22, and 28 years. Serum antibody concentrations against hepatitis type A and B, diphtheria, and tetanus were analyzed from blood samples collected about 6 mo after the first vaccine inoculation at age 28 years. Linear regression models were used to estimate changes in antibody concentration for each doubling of PFAS concentration. Potential effect modification by sex was assessed by including an interaction term between PFAS and sex. Although the 95% confidence intervals contain the null value, inverse trends were observed between serum perfluorooctanoate (PFOA) at ages 14 and 28 years and hepatitis type A antibody (anti-HAV) concentrations, as revealed by an estimated decrease of 0.71 (95% CI: -1.52, 0.09) and 0.24 (95% CI: -0.59, 0.10) signal-to-cutoff ratio for each doubling of exposure, respectively. Inverse trends were also observed between serum PFOA at ages 22 and 28 years and hepatitis type B antibody (anti-HBs) concentration, with an estimated decrease of 21% (95% CI: -42.20%, 7.34%) and of 17% (95% CI: -35.47%, 7.35%) in anti-HBs for each doubling of exposure, respectively. Sex-specific associations with anti-HAV were observed for cord-blood PFASs and serum PFAS concentrations at ages 7 and 14 years. No inverse associations of PFAS exposure were found with diphtheria and tetanus antibody concentrations. Future studies are needed to confirm these findings and further investigate the effects of PFASs on adult immune function.
Mycotoxins are secondary metabolites produced by a variety of fungi that contaminate food and feed resources, and are capable of inducing a wide range of toxicity. Here, we studied the developmental and behavioral toxicity in zebrafish (Danio rerio) embryos and larvae exposed to three mycotoxins: beauvericin (BEA), Enniatin A (ENN A), and Ennitain B (ENN B). Zebrafish embryos were collected after fertilization, treated individually from 1 to 6 dpf with BEA at 8, 16, 32 and, 64 μM and for both enniatins at 3.12, 6.25, 12.5 and, 25 μM. Mixture of mycotoxins were assayed as follows: i) for BEA + ENN A and BEA + ENN B at [32 + 12.5] μM and [16 + 6.25] μM; ii) for ENN A + ENN B at [12.5 + 12.5] μM and [6.25 + 6.25] μM and, iii) for BEA + ENN A + ENN B at [32 + 12.5 + 12.5] μM and [16 + 6.25 + 6.25] μM. Response was collected after a white light-flash intermittent coming on for 5 s during 2 h with a imaging platform. Outcomes measured were: time to death, response to light, and circadian rhythm. This last outcome was measured in a plate where embryos had evolved in natural intervals of light and dark until day 7 or in a plate maintained in darkness. Images of all stages and evolution were collected. Results indicated that mycotoxins induced toxicity at the concentrations tested. All exposed zebrafish induced developmental defects, specifically hatching time and motion activity. After exposure, fish showed enhanced baseline activity but they lost their responsiveness to light.
When addressing environmental health-related questions, most often, only observational data are collected for ethical or practical reasons. However, the lack of randomized exposure often prevents the comparison of similar groups of exposed and unexposed units. This design barrier leads the environmental epidemiology field to mainly estimate associations between environmental exposures and health outcomes. A recently developed causal inference pipeline was developed to guide researchers interested in estimating the effects of plausible hypothetical interventions for policy recommendations. This article illustrates how this multistaged pipeline can help environmental epidemiologists reconstruct and analyze hypothetical randomized experiments by investigating whether an air pollution reduction intervention decreases the risk of multiple sclerosis relapses in Alsace region, France. The epidemiology literature reports conflicted findings on the relationship between air pollution and multiple sclerosis. Some studies found significant associations, whereas others did not. Two case-crossover studies reported significant associations between the risk of multiple sclerosis relapses and the exposure to air pollutants in the Alsace region. We use the same study population as these epidemiological studies to illustrate how appealing this causal inference approach is to estimate the effects of hypothetical, but plausible, environmental interventions.
In randomized experiments, Fisher-exact P values are available and should be used to help evaluate results rather than the more commonly reported asymptotic P values. One reason is that using the latter can effectively alter the question being addressed by including irrelevant distributional assumptions. The Fisherian statistical framework, proposed in 1925, calculates a P value in a randomized experiment by using the actual randomization procedure that led to the observed data. Here, we illustrate this Fisherian framework in a crossover randomized experiment. First, we consider the first period of the experiment and analyze its data as a completely randomized experiment, ignoring the second period; then, we consider both periods. For each analysis, we focus on 10 outcomes that illustrate important differences between the asymptotic and Fisher tests for the null hypothesis of no ozone effect. For some outcomes, the traditional P value based on the approximating asymptotic Student's t distribution substantially subceeded the minimum attainable Fisher-exact P value. For the other outcomes, the Fisher-exact null randomization distribution substantially differed from the bell-shaped one assumed by the asymptotic t test. Our conclusions: When researchers choose to report P values in randomized experiments, 1) Fisher-exact P values should be used, especially in studies with small sample sizes, and 2) the shape of the actual null randomization distribution should be examined for the recondite scientific insights it may reveal.
BACKGROUND: The mechanisms by which exposure to particulate matter might increase risk of cardiovascular morbidity and mortality are not fully known. However, few existing studies have investigated the potential role of particle radioactivity. Naturally occurring radionuclides attach to particulate matter and continue to release ionizing radiation after inhalation and deposition in the lungs. We hypothesize that exposure to particle radioactivity increases biomarkers of inflammation.
METHODS: Our repeated-measures study included 752 men in the greater Boston area. We estimated regional particle radioactivity as a daily spatial average of gross beta concentrations from five monitors in the study area. We used linear mixed-effects regression models to estimate short- and medium-term associations between particle radioactivity and biomarkers of inflammation and endothelial dysfunction, with and without adjustment for additional particulate air pollutants.
RESULTS: We observed associations between particle radioactivity on C-reactive protein (CRP), intercellular adhesion molecule-1 (ICAM-1), and vascular cell adhesion molecule-1 (VCAM-1), but no associations with fibrinogen. An interquartile range width increase in mean 7-day particle radioactivity (1.2 × 10 Bq/m) was associated with a 4.9% increase in CRP (95% CI = 0.077, 9.9), a 2.8% increase in ICAM-1 (95% CI = 1.4, 4.2), and a 4.3% increase in VCAM-1 (95% CI = 2.5, 6.1). The main effects of particle radioactivity remained similar after adjustment in most cases. We also obtained similar effect estimates in a sensitivity analysis applying a robust causal model.
CONCLUSION: Regional particle radioactivity is positively associated with inflammatory biomarkers, indicating a potential pathway for radiation-induced cardiovascular effects.
The presence of mycotoxins in food has created concern. Mycotoxin prevalence in our environment has changed in the last few years maybe due to climatic and other environmental changes. Evidence has emerged from in vitro and in vivo models: some mycotoxins have been found to be potentially carcinogenic, embryogenically harmful, teratogenic, and to generate nephrotoxicity. The risk assessment of exposures to mycotoxins at early life stages became mandatory. In this regard, the effects of toxic compounds on zebrafish have been widely studied, and more recently, mycotoxins have been tested with respect to their effects on developmental and teratogenic effects in this model system, which offers several advantages as it is an inexpensive and an accessible vertebrate model to study developmental toxicity. External post-fertilization and quick maturation make it sensitive to environmental effects and facilitate the detection of endpoints such as morphological deformities, time of hatching, and behavioral responses. Therefore, there is a potential for larval zebrafish to provide new insights into the toxicological effects of mycotoxins. We provide an overview of recent mycotoxin toxicological research in zebrafish embryos and larvae, highlighting its usefulness to toxicology and discuss the strengths and limitations of this model system.
This study aimed to evaluate the effectiveness of an educational intervention at improving Oral Health Professionals (OHP's) knowledge of HPV and comfortability to discuss vaccination with their American Indian and Alaskan Native patients. OHP's attended an educational lecture covering HPV vaccination. Participants completed four validated questionnaires that encompassed a sociodemographic survey, a pre-lecture questionnaire (pre-Q), a post-lecture questionnaire (post-Q), and a follow-up questionnaire (follow-Q). The McNemar test was used to assess the significance of marginal probabilities in the responses between the pre-Q and post-Q and the Chi-square test to assess responses between the post-Q and follow-Q. A total of 122 OHP's completed the sociodemographic survey, pre-Q, and post-Q. Among these, 29 OHP's completed the eight-week follow-Q. The majority of all the participants were White/Caucasian (41%), 31 to 60 years of age (72%), females (64%), and held a graduate/professional degree (52%). Analysis of the pre-Q responses showed that only 6.8% of OHP's discuss the connection between HPV and oropharyngeal cancer with patients and a lack of information on the topic was the major barrier reported. After the educational intervention (post-Q), 86.5% of OHP's reported they were more likely to recommend the HPV vaccine and 69.8% felt more comfortable administering it. Comparison between the pre-Q and the post-Q showed a significant improvement in overall HPV knowledge. Similarly, a comparison between the post-Q and the follow-Q showed retained knowledge overtime. Our study suggests that the educational intervention was effective at improving OHP's knowledge of HPV and enhancing their comfortability and preparedness to discuss the vaccination with their patients.
The aim of this study was to evaluate the effectiveness of an educational intervention on HPV infection, HPV-related cancers and prevention modalities to improve Oral Health Care Providers (OHPs) knowledge and awareness about these topics, considering the rise of HPV-related malignancies in the USA. Educational sessions on HPV were offered to OHPs between 2016 and 2018 in the New England area. Participants were asked to fill out a questionnaire both before and after each session. Responses from the pre-questionnaire were compared to those from the post-questionnaire to evaluate the effectiveness of the lectures in increasing HPV-related knowledge of the OHPs. Among 277 participants, 263 completed both the pre- and post-questionnaire. A significant improvement was observed for the following categories: epidemiology of HPV infections, HPV-related diseases, and HPV vaccination and prevention. After the educational intervention, OHPs also indicated an increased comfort level in regard to educating their patients about the importance of HPV vaccination. Educational lectures can be effective in increasing OHPs knowledge and awareness about HPV, HPV-related cancers, and vaccination. More educational sessions on HPV are needed to reach a larger number of OHPs. OHPs may be the first to identify signs and symptoms of HPV-related oropharyngeal cancers. In addition, they may encourage their patients to take advantage of the HPV vaccine.
The analysis of the gut microbiome with respect to health care prevention and diagnostic purposes is increasingly the focus of current research. We analyzed around 2000 stool samples from the KORA (Cooperative Health Research in the Region of Augsburg) cohort using high-throughput 16S rRNA gene amplicon sequencing representing a total microbial diversity of 2089 operational taxonomic units (OTUs). We evaluated the combination of three different components to assess the reflection of obesity related to microbiota profiles: (i) four prediction methods (i.e., partial least squares (PLS), support vector machine regression (SVMReg), random forest (RF), and M5Rules); (ii) five OTU data transformation approaches (i.e., no transformation, relative abundance without and with log-transformation, as well as centered and isometric log-ratio transformations); and (iii) predictions from nine measurements of obesity (i.e., body mass index, three measures of body shape, and five measures of body composition). Our results showed a substantial impact of all three components. The applications of SVMReg and PLS in combination with logarithmic data transformations resulted in considerably predictive models for waist circumference-related endpoints. These combinations were at best able to explain almost 40% of the variance in obesity measurements based on stool microbiota data (i.e., OTUs) only. A reduced loss in predictive performance was seen after sex-stratification in waist-height ratio compared to other waist-related measurements. Moreover, our analysis showed that the contribution of OTUs less prevalent and abundant is minor concerning the predictive power of our models.
The study of racial/ethnic inequalities in health is important to reduce the uneven burden of disease. In the case of colorectal cancer (CRC), disparities in survival among non-Hispanic Whites and Blacks are well documented, and mechanisms leading to these disparities need to be studied formally. It has also been established that body mass index (BMI) is a risk factor for developing CRC, and recent literature shows BMI at diagnosis of CRC is associated with survival. Since BMI varies by racial/ethnic group, a question that arises is whether differences in BMI are partially responsible for observed racial/ethnic disparities in survival for CRC patients. This article presents new methodology to quantify the impact of the hypothetical intervention that matches the BMI distribution in the Black population to a potentially complex distributional form observed in the White population on racial/ethnic disparities in survival. Our density mediation approach can be utilized to estimate natural direct and indirect effects in the general causal mediation setting under stronger assumptions. We perform a simulation study that shows our proposed Bayesian density regression approach performs as well as or better than current methodology allowing for a shift in the mean of the distribution only, and that standard practice of categorizing BMI leads to large biases when BMI is a mediator variable. When applied to motivating data from the Cancer Care Outcomes Research and Surveillance (CanCORS) Consortium, our approach suggests the proposed intervention is potentially beneficial for elderly and low-income Black patients, yet harmful for young or high-income Black populations.
We used a randomized crossover experiment to estimate the effects of ozone (vs. clean air) exposure on genome-wide DNA methylation of target bronchial epithelial cells, using 17 volunteers, each randomly exposed on two separated occasions to clean air or 0.3-ppm ozone for two hours. Twenty-four hours after exposure, participants underwent bronchoscopy to collect epithelial cells whose DNA methylation was measured using the Illumina 450 K platform. We performed global and regional tests examining the ozone versus clean air effect on the DNA methylome and calculated Fisher-exact p-values for a series of univariate tests. We found little evidence of an overall effect of ozone on the DNA methylome but some suggestive changes in PLSCR1, HCAR1, and LINC00336 DNA methylation after ozone exposure relative to clean air. We observed some participant-to-participant heterogeneity in ozone responses.
Consider a statistical analysis that draws causal inferences from an observational dataset, inferences that are presented as being valid in the standard frequentist senses; i.e. the analysis produces: (1) consistent point estimates, (2) valid p-values, valid in the sense of rejecting true null hypotheses at the nominal level or less often, and/or (3) confidence intervals, which are presented as having at least their nominal coverage for their estimands. For the hypothetical validity of these statements, the analysis must embed the observational study in a hypothetical randomized experiment that created the observed data, or a subset of that hypothetical randomized data set. This multistage effort with thought-provoking tasks involves: (1) a purely conceptual stage that precisely formulate the causal question in terms of a hypothetical randomized experiment where the exposure is assigned to units; (2) a design stage that approximates a randomized experiment before any outcome data are observed, (3) a statistical analysis stage comparing the outcomes of interest in the exposed and non-exposed units of the hypothetical randomized experiment, and (4) a summary stage providing conclusions about statistical evidence for the sizes of possible causal effects. Stages 2 and 3 may rely on modern computing to implement the effort, whereas Stage 1 demands careful scientific argumentation to make the embedding plausible to scientific readers of the proffered statistical analysis. Otherwise, the resulting analysis is vulnerable to criticism for being simply a presentation of scientifically meaningless arithmetic calculations. The conceptually most demanding tasks are often the most scientifically interesting to the dedicated researcher and readers of the resulting statistical analyses. This perspective is rarely implemented with any rigor, for example, completely eschewing the first stage. We illustrate our approach using an example examining the effect of parental smoking on children's lung function collected in families living in East Boston in the 1970s.
We present a randomization-based inferential framework for experiments characterized by a strongly ignorable assignment mechanism where units have independent probabilities of receiving treatment. Previous works on randomization tests often assume these probabilities are equal within blocks of units. We consider the general case where they differ across units and show how to perform randomization tests and obtain point estimates and confidence intervals. Furthermore, we develop rejection-sampling and importance-sampling approaches for conducting randomization-based inference conditional on any statistic of interest, such as the number of treated units or forms of covariate balance. We establish that our randomization tests are valid tests, and through simulation we demonstrate how the rejection-sampling and importance-sampling approaches can yield powerful randomization tests and thus precise inference. Our work also has implications for observational studies, which commonly assume a strongly ignorable assignment mechanism. Most methodologies for observational studies make additional modeling or asymptotic assumptions, while our framework only assumes the strongly ignorable assignment mechanism, and thus can be considered a minimal-assumption approach.