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• Placental mRNAs and miRNAs showed birth weight-related differential expression. • Genomic and epigenomic changes were largely consistent across infant sex. • Associated pathways included glycoprotein VI and growth factor signaling. • Birth weight-associated changes were predicted to be regulated by miRNAs. Birth weight (BW) represents an important clinical and toxicological measure, indicative of the overall health of the newborn as well as potential risk for later-in-life outcomes. BW can be influenced by endogenous and exogenous factors and is known to be heavily impacted in utero by the health and function of the placenta. An aspect that remains understudied is the influence of genomic and epigenomic programming within the placenta on infant BW. To address this gap, we set out to test the hypothesis that genes involved in critical placental cell signaling are associated with infant BW, and are likely regulated, in part, through epigenetic mechanisms based on microRNA (miRNA) mediation. This study leveraged a robust dataset based on 390 infants born at low gestational age (ranged 23–27 weeks) to evaluate genome-wide expression profiles of both mRNAs and miRNAs in placenta tissues and relate these to infant BW. A total of 254 mRNAs and 268 miRNAs were identified as associated with BW, the majority of which showed consistent associations across placentas derived from both males and females. BW-associated mRNAs were found to be enriched for important biological pathways, including glycoprotein VI (the major receptor for collagen), human growth, and hepatocyte growth factor signaling, a portion of which were predicted to be regulated by BW-associated miRNAs. These miRNA-regulated pathways highlight key mechanisms potentially linking endogenous/exogenous factors to changes in birth outcomes that may be deleterious to infant and later-in-life health. [ABSTRACT FROM AUTHOR]

[Display omitted] • Multiple wildfire-relevant exposure conditions were tested in mice. • Extracellular vesicles (EVs) were evaluated in circulating plasma. • Exposures altered EV-encapsulated microRNAs involved in cell stress and hypoxia. • Exposures disrupted cell stress and hypoxia pathways in lung and heart tissues. • Enhanced responses occurred from flaming vs. smoldering burn conditions. Wildfires are a threat to public health world-wide that are growing in intensity and prevalence. The biological mechanisms that elicit wildfire-associated toxicity remain largely unknown. The potential involvement of cross-tissue communication via extracellular vesicles (EVs) is a new mechanism that has yet to be evaluated. Female CD-1 mice were exposed to smoke condensate samples collected from the following biomass burn scenarios: flaming peat; smoldering peat; flaming red oak; and smoldering red oak, representing lab-based simulations of wildfire scenarios. Lung tissue, bronchoalveolar lavage fluid (BALF) samples, peripheral blood, and heart tissues were collected 4 and 24 h post-exposure. Exosome-enriched EVs were isolated from plasma, physically characterized, and profiled for microRNA (miRNA) expression. Pathway-level responses in the lung and heart were evaluated through RNA sequencing and pathway analyses. Markers of cardiopulmonary tissue injury and inflammation from BALF samples were significantly altered in response to exposures, with the greatest changes occurring from flaming biomass conditions. Plasma EV miRNAs relevant to cardiovascular disease showed exposure-induced expression alterations, including miR-150, miR-183, miR-223-3p, miR-30b, and miR-378a. Lung and heart mRNAs were identified with differential expression enriched for hypoxia and cell stress-related pathways. Flaming red oak exposure induced the greatest transcriptional response in the heart, a large portion of which were predicted as regulated by plasma EV miRNAs, including miRNAs known to regulate hypoxia-induced cardiovascular injury. Many of these miRNAs had published evidence supporting their transfer across tissues. A follow-up analysis of miR-30b showed that it was increased in expression in the heart of exposed mice in the absence of changes to its precursor molecular, pri-miR-30b, suggesting potential transfer from external sources (e.g., plasma). This study posits a potential mechanism through which wildfire exposures induce cardiopulmonary responses, highlighting the role of circulating plasma EVs in intercellular and systems-level communication between tissues. [ABSTRACT FROM AUTHOR]

[Display omitted] • Non-targeted analysis identified molecular features associated with preeclampsia. • Molecular feature and patient clusters highlight unique exposure signatures. • Human metabolites, exogenous drugs and non-drugs were detected in placentas. • Metabolites were most abundant and had strongest relation to multi-omic signatures. • Exogenous non-drugs were least abundant and had weaker relation to multi-omic signatures. Environmental health research has recently undergone a dramatic shift, with ongoing technological advancements allowing for broader coverage of exposure and molecular biology signatures. Approaches to integrate such measures are still needed to increase understanding between systems-level exposure and biology. We address this gap by evaluating placental tissues to identify novel chemical-biological interactions associated with preeclampsia. This study tests the hypothesis that understudied chemicals are present in the human placenta and associated with preeclampsia-relevant disruptions, including overall case status (preeclamptic vs. normotensive patients) and underlying transcriptomic/epigenomic signatures. A non-targeted analysis based on high-resolution mass spectrometry was used to analyze placental tissues from a cohort of 35 patients with preeclampsia (n = 18) and normotensive (n = 17) pregnancies. Molecular feature data were prioritized for confirmation based on association with preeclampsia case status and confidence of chemical identification. All molecular features were evaluated for relationships to mRNA, microRNA, and CpG methylation (i.e., multi-omic) signature alterations involved in preeclampsia. A total of 183 molecular features were identified with significantly differentiated abundance in placental extracts of preeclamptic patients; these features clustered into distinct chemical groupings using unsupervised methods. Of these features, 53 were identified (mapping to 40 distinct chemicals) using chemical standards, fragmentation spectra, and chemical metadata. In general, human metabolites had the largest feature intensities and strongest associations with preeclampsia-relevant multi-omic changes. Exogenous drugs were second most abundant and had fewer associations with multi-omic changes. Other exogenous chemicals (non-drugs) were least abundant and had the fewest associations with multi-omic changes. These global data trends suggest that human metabolites are heavily intertwined with biological processes involved in preeclampsia etiology, while exogenous chemicals may still impact select transcriptomic/epigenomic processes. This study serves as a demonstration of merging systems exposures with systems biology to better understand chemical-disease relationships. [ABSTRACT FROM AUTHOR]

The liver is a pivotal organ regulating critical developmental stages of fetal metabolism and detoxification. Though numerous studies have evaluated links between prenatal/perinatal exposures and adverse health outcomes in the developing fetus, the central role of liver to health disruptions resulting from these exposures remains understudied, especially concerning early development and later-in-life health outcomes. While numerous in vitro methods for evaluating liver toxicity have been established, the use of iPSC-derived hepatocytes appears to be particularly well suited to contribute to this critical research gap due to their potential to model a diverse range of disease phenotypes and different stages of liver development. The following key aspects are reviewed: (1) an introduction to developmental liver toxicity; (2) an introduction to embryonic and induced pluripotent stem cell models; (3) methods and challenges for deriving liver cells from stem cells; and (4) applications for iPSC-derived hepatocytes to evaluate liver developmental stages and their associated responses to insults. We conclude that iPSC-derived hepatocytes have great potential for informing liver toxicity and underlying disease mechanisms via the generation of patient-specific iPSCs; implementing large-scale drug and chemical screening; evaluating general biological responses as a potential surrogate target cell; and evaluating inter-individual disease susceptibility and response variability. • In vitro methods for using induced pluripotent stem cells from human samples are growing. • Induced pluripotent stem cell-derived hepatocytes may mimic liver development. • These models can test various disease phenotypes and toxicological responses. • Applications include screening for chemical-induced liver toxicity and therapeutics. • Inter-individual susceptibility can be evaluated across liver developmental stages. [ABSTRACT FROM AUTHOR]

Macrophages are pivotal innate immune cells which exhibit high phenotypic plasticity and can exist in different polarization states dependent on exposure to external stimuli. Numerous methods have been employed to simulate macrophage polarization states to test their function in vitro. However, limited research has explored whether these polarization methods yield comparable populations beyond key gene, cytokine, and cell surface marker expression. Here, we employ an unbiased comprehensive analysis using data organized through the all RNA-seq and ChIP-seq sample and signature search (ARCHS 4 ) database, which compiles all RNAseq data deposited into the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). In silico analyses were carried out demonstrating that commonly employed macrophage polarization methods generate distinct gene expression profiles in macrophage subsets that remained poorly described until now. Our analyses confirm existing knowledge on broad macrophage polarization, while expanding nuanced differences between M2a and M2c subsets, suggesting non-interchangeable stimuli for M2a polarization. Furthermore, we characterize divergent gene expression patterns in M1 macrophages following standard polarization protocols, indicating significant subset distinctions. Consequently, equivalence cannot be assumed among polarization regimens for in vitro macrophage studies, particularly in simulating diverse pathogen responses., (© 2024. The Author(s).)

Introduction: Existing evidence suggests that exposure to phthalates is higher among younger age groups. However, limited knowledge exists on how phthalate exposure, as well as exposure to replacement plasticizers, di(isononyl) cyclohexane-1,2-dicarboxylate (DINCH) and di-2-ethylhexyl terephthalate (DEHTP), change from infancy through early childhood., Methods: Urine samples were collected across the first 5 years of life from typically developing infants and young children enrolled between 2017 and 2020 in the longitudinal UNC Baby Connectome Project. From 438 urine samples among 187 participants, we quantified concentrations of monobutyl phthalate (MnBP), mono-3-carboxypropyl phthalate (MCPP), monoisobutyl phthalate (MiBP), monoethyl phthalate (MEP), monobenzyl phthalate (MBzP), and metabolites of di(2-ethylhexyl) phthalate (DEHP), diisonoyl phthalate (DiNP), DINCH and DEHTP. Specific gravity (SG) adjusted metabolite and molar sum concentrations were compared across age groups. Intraclass correlation coefficients (ICCs) were calculated among 122 participants with multiple urine specimens (373 samples)., Results: Most phthalate metabolites showed high detection frequencies (>80% of samples). Replacement plasticizers DINCH (58-60%) and DEHTP (>97%) were also commonly found. DiNP metabolites were less frequently detected (<10%). For some metabolites, SG-adjusted concentrations were inversely associated with age, with the highest concentrations found in the first year of life. ICCs revealed low to moderate reliability in metabolite measurements (ρ = 0.10-0.48) suggesting a high degree of within-individual variation in exposure among this age group. The first 6 months (compared to remaining age groups) showed an increased ratio of carboxylated metabolites of DEHP and DEHTP, compared to other common metabolites, but no clear age trends for DINCH metabolite ratios were observed., Conclusion: Metabolites of phthalates and replacements plasticizers were widely detected in infancy and early childhood, with the highest concentrations observed in the first year of life for several metabolites. Higher proportions of carboxylated metabolites of DEHP and DEHTP in younger age groups indicate potential differences in metabolism during infancy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Background: Exposure to military burn pit smoke during deployment is associated with different respiratory and non-respiratory diseases. However, information linking smoke exposure to human pulmonary health is lacking. This study examined the effects of simulated burn pit smoke condensates on human airway epithelial cells (HAECs) from twelve donors (smokers/non-smokers, biological female/male) cultured at an air-liquid interface and exposed to condensates from three simulated burn pit waste materials (cardboard, plywood, and plastic) incinerated at two combustion conditions: smoldering and flaming. Cellular gene expression was analyzed using bulk RNA sequencing, and basolateral media cytokine levels were assessed using multiplex immunoassay., Results: Flaming smoke condensates caused more significant differentially expressed genes (DEGs) with plywood flaming smoke being the most potent in altering gene expression and modulating cytokine release. Cardboard and plywood flaming condensates primarily activated detoxification pathways, whereas plastic flaming affected genes related to anti-microbial and inflammatory responses. Correlation analysis between smoke condensate chemicals and gene expression to understand the underlying mechanism revealed crucial role of oxygenated polycyclic aromatic hydrocarbons (PAHs) and aluminum, molybdenum, and silicon elements; IL6 expression was positively correlated with most PAHs. Stratification of data based on HAEC donor demographics suggests that these affect gene expression changes. Enrichment analysis indicated similarity with several deployment-related presumptive and reported diseases, including asthma, emphysema, and cancer of different organs., Conclusions: This study highlights that simulated burn pit smoke exposure of HAECs causes gene expression changes indicative of deployment-related diseases with more pronounced effects seen in smokers and females. Future studies are needed to further characterize how sex and smoking status affect deployment-related diseases., (© 2024. The Author(s).)

Toxicogenomics measures molecular features, such as transcripts, proteins, metabolites and epigenomic modifications, to understand and predict the toxicological effects of environmental and pharmaceutical exposures. Transcriptomics has become an integral tool in contemporary toxicology research owing to innovations in gene expression profiling that can provide mechanistic and quantitative information at scale. These data can be used to predict toxicological hazards through the use of transcriptomic biomarkers, network inference analyses, pattern-matching approaches and artificial intelligence. Furthermore, emerging approaches, such as high-throughput dose-response modelling, can leverage toxicogenomic data for human health protection even in the absence of predicting specific hazards. Finally, single-cell transcriptomics and multi-omics provide detailed insights into toxicological mechanisms. Here, we review the progress since the inception of toxicogenomics in applying transcriptomics towards toxicology testing and highlight advances that are transforming risk assessment., (© 2024. Springer Nature Limited.)

Multiple external stressors are known to have adverse impacts on health and development. Certain groups are more vulnerable and/or more likely to be exposed toenvironmental, psychological, and social stressors simultaneously. Yet, few studies have examined combined exposure to environmental toxicants and psychosocial stress. Here, we integrated environmental chemical exposure data collected using silicone wristbands and self-report social stressor data within the Brain and Early Experience (BEE) perinatal cohort to understand co-exposure to environmental chemicals and social stress. Silicone wristbands were worn for one week by mothers throughout central North Carolina who were 6 months postpartum (n = 97). Exposure to 110 environmental chemicals across eight chemical classes was quantified on silicone wristbands using gas chromatography mass spectrometry. Social stress was evaluated using eight established self-report questionnaires (e.g., Brief Symptom Inventory, Perceived Stress Scale), quantifying experiences such as race-related stress, economic strain, and relationship conflict. Hair cortisol levels were measured as an additional metric of stress. The chemical exposure landscape and associations among chemical exposure, demographic characteristics, and social stress were characterized through individual variable analyses, cluster and data reduction, and compiled scoring approaches to comprehensively evaluate chemical and social stress burdens. We found that chemicals contain co-occurring patterns largely based on chemical class, with phthalates representing the chemical class with highest exposure and polychlorinated biphenyls the lowest. Chemicals showed differential exposure across racial groups, with diethyl phthalate, triphenyl phosphate, and tris(3,5-dimethyl phenyl) phosphate at higher levels in Black participants compared with White participants. Integrating social stressor profiling with chemical exposure data identified one particularly vulnerable subset of participants in which high chemical exposure burden coincided with high experiences of racism and economic stress. These findings demonstrate co-occurring chemical and social stress, warranting further investigation to better understand how these combined stressors may contribute to disparities in maternal and child health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Burn pits are a method of open-air waste management that was common during military operations in Iraq, Afghanistan, and other regions in Southwest Asia. Veterans returning from deployment have reported respiratory symptoms, potentially from exposure to burn pit smoke, yet comprehensive assessment of such exposure on pulmonary health is lacking. We have previously shown that exposure to condensates from burn pit smoke emissions causes inflammation and cytotoxicity in mice. In this study, we explored the effects of burn pit smoke condensates on human airway epithelial cells (HAECs) to understand their impact on cellular targets in the human lung. HAECs were cultured at the air-liquid interface (ALI) and exposed to burn pit waste smoke condensates (plywood, cardboard, plastic, mixed, and mixed with diesel) generated under smoldering and flaming conditions. Cytotoxicity was evaluated by measuring transepithelial electrical resistance (TEER) and lactate dehydrogenase (LDH) release; toxicity scores (TSs) were quantified for each exposure. Pro-inflammatory cytokine release and modulation of gene expression were examined for cardboard and plastic condensate exposures. Burn pit smoke condensates generated under flaming conditions affected cell viability, with flaming mixed waste and plywood exhibiting the highest toxicity scores. Cardboard and plastic smoke condensates modulated cytokine secretion, with GM-CSF and IL-1β altered in more than one exposure group. Gene expression of detoxifying enzymes ( ALDH1A3 , ALDH3A1 , CYP1A1 , CYP1B1 , NQO1 , etc.), mucins ( MUC5AC , MUC5B ), and cytokines was affected by several smoke condensates. Particularly, expression of IL6 was elevated following exposure to all burn pit smoke condensates, and polycyclic aromatic hydrocarbon acenaphthene was positively associated with the IL-6 level in the basolateral media of HAECs. These observations demonstrate that exposure to smoke condensates of materials present in burn pits adversely affects HAECs and that aberrant cytokine secretion and altered gene expression profiles following burn pit material smoke exposure could contribute to the development of airway disease.

Wildfire events are becoming increasingly common across many areas of the United States, including North Carolina (NC). Wildfires can cause immediate damage to properties, and wildfire smoke conditions can harm the overall health of exposed communities. It is critical to identify communities at increased risk of wildfire events, particularly in areas with that have sociodemographic disparities and low socioeconomic status (SES) that may exacerbate incurred impacts of wildfire events. This study set out to: (1) characterize the distribution of wildfire risk across NC; (2) implement integrative cluster analyses to identify regions that contain communities with increased vulnerability to the impacts of wildfire events due to sociodemographic characteristics; (3) provide summary-level statistics of populations with highest wildfire risk, highlighting SES and housing cost factors; and (4) disseminate wildfire risk information via our online web application, ENVIROSCAN. Wildfire hazard potential (WHP) indices were organized at the census tract-level, and distributions were analyzed for spatial autocorrelation via global and local Moran's tests. Sociodemographic characteristics were analyzed via k -means analysis to identify clusters with distinct SES patterns to characterize regions of similar sociodemographic/socioeconomic disparities. These SES groupings were overlayed with housing and wildfire risk profiles to establish patterns of risk across NC. Resulting geospatial analyses identified areas largely in Southeastern NC with high risk of wildfires that were significantly correlated with neighboring regions with high WHP, highlighting adjacent regions of high risk for future wildfire events. Cluster-based analysis of SES factors resulted in three groups of regions categorized through distinct SES profiling; two of these clusters (Clusters 2 and 3) contained indicators of high SES vulnerability. Cluster 2 contained a higher percentage of younger (<5 years), non-white, Hispanic and/or Latino residents; while Cluster 3 had the highest mean WHP and was characterized by a higher percentage of non-white residents, poverty, and less than a high school education. Counties of particular SES and WHP-combined vulnerability include those with majority non-white residents, tribal communities, and below poverty level households largely located in Southeastern NC. WHP values per census tract were dispersed to the public via the ENVIROSCAN application, alongside other environmentally-relevant data., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Winker, Payton, Brown, McDermott, Freedman, Lenhardt, Eaves, Fry and Rager.)

Per- and polyfluoroalkyl substances (PFAS) have emerged as high priority contaminants due to their ubiquity and pervasiveness in the environment. Numerous PFAS co-occur across sources of drinking water, including areas of North Carolina (NC) with some detected concentrations above the Environmental Protection Agency's health advisory levels. While evidence demonstrates PFAS exposure induces harmful effects in the liver, the involvement of extracellular vesicles (EVs) as potential mediators of these effects has yet to be evaluated. This study set out to evaluate the hypothesis that PFAS mixtures induce dose-dependent release of EVs from liver cells, with exposures causing differential loading of microRNAs (miRNAs) and PFAS chemical signatures. To test this hypothesis, a defined PFAS mixture was prioritized utilizing data collected by the NC PFAS Testing Network. This mixture contained three substances, PFOS, PFOA, and PFHxA, selected based upon co-occurrence patterns and the inclusion of both short-chain (PFHxA) and long-chain (PFOA and PFOS) substances. HepG2 liver cells were exposed to equimolar PFAS, and secreted EVs were isolated from conditioned media and characterized for count and molecular content. Exposures induced a dose-dependent release of EVs carrying miRNAs that were differentially loaded upon exposure. These altered miRNA signatures were predicted to target mRNA pathways involved in hepatic fibrosis and cancer. Chemical concentrations of PFOS, PFOA, and PFHxA were also detected in both parent HepG2 cells and their released EVs, specifically within a 15-fold range after normalizing for protein content. This study therefore established EVs as novel biological responders and measurable endpoints for evaluating PFAS-induced toxicity., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Prenatal exposure to metals in private well water may increase the risk of preterm birth (PTB) (delivery < 37 weeks' gestation). In this study, we estimated associations between arsenic, manganese, lead, cadmium, chromium, copper, and zinc concentrations in private well water and PTB incidence in North Carolina (NC)., Methods: Birth certificates from 2003-2015 (n = 1,329,071) were obtained and pregnancies were assigned exposure using the mean concentration and the percentage of tests above the maximum contaminant level (MCL) for the census tract of each individuals' residence at the time of delivery using the NCWELL database (117,960 well water tests from 1998-2019). We evaluated associations between single metals and PTB using adjusted logistic regression models. Metals mixtures were assessed using quantile-based g-computation., Results: Compared with those in other census tracts, individuals residing in tracts where > 25% of tests exceeded the MCL for lead (aOR 1.10, 95%CI 1.02,1.18) or cadmium (aOR 1.11, 95% CI 1.00,1.23) had an increased odds of PTB. Conversely, those residing in areas with > 25% MCL for zinc (aOR 0.77 (95% CI: 0.56,1.02) and copper (aOR 0.53 (95% CI: 0.13,1.34)) had a reduced odds of PTB. A quartile increase in the concentrations of a mixture of lead, cadmium, and chromium was associated with a small increased odds for PTB (aOR 1.02, 95% CI 1.01, 1.03). This metal mixture effect was most pronounced among American Indian individuals (aOR per quartile increase in all metals: 1.19 (95% CI 1.06,1.34))., Conclusions: In a large study population of over one million births, lead and cadmium were found to increase the risk of PTB individually and in a mixture, with additional mixtures-related impacts estimated from co-exposure with chromium. This study highlights critical racial and ethnic health disparities in relation to private well water thereby emphasizing the urgent need for improved private well water quality to protect vulnerable populations., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Extracellular vesicle (EV)-mediated intercellular communication significantly influences pulmonary cell health and disease, yet in vitro methods to investigate these mechanisms are limited. We hypothesize that organotypic models of the airway can be leveraged to investigate EV-mediated intercellular signaling, focusing on EV proteomic content as a case study. Two in vitro airway culture models were evaluated by mass spectrometry-based proteomics analysis: a tri-culture model consisting of alveolar epithelial, fibroblast, and lung microvascular endothelial cells and a co-culture model of alveolar epithelial and fibroblasts. EVs isolated from the tri-culture model were enriched with EV proteins regulating RNA-to-protein translation. EVs isolated from the co-culture model were enriched with EV biogenesis and extracellular matrix signaling proteins. These model-specific differences suggest that different pulmonary cell types uniquely affect EV composition and the biological pathways influenced by the EV proteome in recipient cells. These findings can inform future studies surrounding EV-related pulmonary disease pathogenesis and therapeutics., Competing Interests: The authors declare that they have no competing interests., (© 2023 The Authors.)

Human health risk assessments for complex mixtures can address real-world exposures and protect public health. While risk assessors typically prefer whole mixture approaches over component-based approaches, data from the precise exposure of interest are often unavailable and surrogate data from a sufficiently similar mixture(s) are required. This review describes recent advances in determining sufficient similarity of whole, complex mixtures spanning the comparison of chemical features, bioactivity profiles, and statistical evaluation to determine "thresholds of similarity". Case studies, including water disinfection byproducts, botanical ingredients, and wildfire emissions, are used to highlight tools and methods. Limitations to application of sufficient similarity in risk-based decision making are reviewed and recommendations presented for developing best practice guidelines., Competing Interests: Competing interests The authors declare that they have no competing interests. Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Toxicology research has rapidly evolved, leveraging increasingly advanced technologies in high-throughput approaches to yield important information on toxicological mechanisms and health outcomes. Data produced through toxicology studies are consequently becoming larger, often producing high-dimensional data. These types of data hold promise for imparting new knowledge, yet inherently have complexities causing them to be a rate-limiting element for researchers, particularly those that are housed in "wet lab" settings (i.e., researchers that use liquids to analyze various chemicals and biomarkers as opposed to more computationally focused, "dry lab" researchers). These types of challenges represent topics of ongoing conversation amongst our team and researchers in the field. The aim of this perspective is to i) summarize hurdles in analyzing high-dimensional data in toxicology that require improved training and translation for wet lab researchers, ii) highlight example methods that have aided in translating data analysis techniques to wet lab researchers; and iii) describe challenges that remain to be effectively addressed, to date, in toxicology research. Specific aspects include methodologies that could be introduced to wet lab researchers, including data pre-processing, machine learning, and data reduction. Current challenges discussed include model interpretability, study biases, and data analysis training. Example efforts implemented to translate these data analysis techniques are also mentioned, including online data analysis resources and hands-on workshops. Questions are also posed to continue conversation in the toxicology community. Contents of this perspective represent timely issues broadly occurring in the fields of bioinformatics and toxicology that require ongoing dialogue between wet and dry lab researchers., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Payton, Roell, Rebuli, Valdar, Jaspers and Rager.)

Background: Ozone (O3) exposure causes respiratory effects including lung function decrements, increased lung permeability, and airway inflammation. Additionally, baseline metabolic state can predispose individuals to adverse health effects from O3. For this reason, we conducted an exploratory study to examine the effect of O3 exposure on derivatives of cholesterol biosynthesis: sterols, oxysterols, and secosteroid (25-hydroxyvitamin D) not only in the lung, but also in circulation., Methods: We obtained plasma and induced sputum samples from non-asthmatic (n = 12) and asthmatic (n = 12) adult volunteers 6 hours following exposure to 0.4ppm O3 for 2 hours. We quantified the concentrations of 24 cholesterol precursors and derivatives by UPLC-MS and 30 cytokines by ELISA. We use computational analyses including machine learning to determine whether baseline plasma sterols are predictive of O3 responsiveness., Results: We observed an overall decrease in the concentration of cholesterol precursors and derivatives (e.g. 27-hydroxycholesterol) and an increase in concentration of autooxidation products (e.g. secosterol-B) in sputum samples. In plasma, we saw a significant increase in the concentration of secosterol-B after O3 exposure. Machine learning algorithms showed that plasma cholesterol was a top predictor of O3 responder status based on decrease in FEV1 (>5%). Further, 25-hydroxyvitamin D was positively associated with lung function in non-asthmatic subjects and with sputum uteroglobin, whereas it was inversely associated with sputum myeloperoxidase and neutrophil counts., Conclusion: This study highlights alterations in sterol metabolites in the airway and circulation as potential contributors to systemic health outcomes and predictors of pulmonary and inflammatory responsiveness following O3 exposure., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Perryman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

We aim to infer bioactivity of each chemical by assay endpoint combination, addressing sparsity of toxicology data. We propose a Bayesian hierarchical framework which borrows information across different chemicals and assay endpoints, facilitates out-of-sample prediction of activity for chemicals not yet assayed, quantifies uncertainty of predicted activity, and adjusts for multiplicity in hypothesis testing. Furthermore, this paper makes a novel attempt in toxicology to simultaneously model heteroscedastic errors and a nonparametric mean function, leading to a broader definition of activity whose need has been suggested by toxicologists. Real application identifies chemicals most likely active for neurodevelopmental disorders and obesity., Competing Interests: Conflict of interest: None declared., (© (RSS) Royal Statistical Society 2023. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Due to structural racism and income inequality, exposure to environmental chemicals is tightly linked to socioeconomic factors. In addition, exposure to psychosocial stressors, such as racial discrimination, as well as having limited resources, can increase susceptibility to environmentally induced disease. Yet, studies are often conducted separately in fields of social science and environmental science, reducing the potential for holistic risk estimates. To tackle this gap, we developed the Chemical and Social Stressors Integration Technique (CASS-IT) to integrate environmental chemical and social stressor datasets. The CASS-IT provides a framework to identify distinct geographic areas based on combinations of environmental chemical exposure, social vulnerability, and access to resources. It incorporates two data dimension reduction tools: k-means clustering and latent profile analysis. Here, the CASS-IT was applied to North Carolina (NC) as a case study. Environmental chemical data included toxic metals - arsenic, manganese, and lead - in private drinking well water. Social stressor data were captured by the CDC's social vulnerability index's four domains: socioeconomic status, household composition and disability, minority status and language, and housing type and transportation. Data on resources were derived from Federal Emergency Management Agency (FEMA's) Resilience and Analysis Planning Tool, which generated measures of health resources, social resources, and information resources. The results highlighted 31 NC counties where exposure to both toxic metals and social stressors are elevated, and health resources are minimal; these are counties in which environmental justice is of utmost concern. A census-tract level analysis was also conducted to demonstrate the utility of CASS-IT at different geographical scales. The tract-level analysis highlighted specific tracts within counties of concern that are particularly high priority. In future research, the CASS-IT can be used to analyze United States-wide environmental datasets providing guidance for targeted public health interventions and reducing environmental disparities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

Prenatal exposure to toxic metals is linked to numerous adverse birth and later-in-life outcomes. These outcomes are tied to disrupted biological processes in fetal-derived tissues including the placenta and umbilical cord yet the precise pathways are understudied in these target tissues. We set out to examine the relationship between metal concentrations in umbilical cord and altered gene expression networks in placental tissue. These novel relationships were investigated in a subset of the Extremely Low Gestational Age Newborn (ELGAN) cohort (n = 226). Prenatal exposure to 11 metals/metalloids was measured using inductively coupled plasma tandem-mass spectrometry (ICP-MS/MS) in cord tissue, ensuring passage through the placental barrier. RNA-sequencing was used to quantify >37,000 mRNA transcripts. Differentially expressed genes (DEGs) were identified with respect to each metal. Weighted gene co-expression analysis identified gene networks modulated by metals. Two innovative mixtures modeling techniques, namely principal components analysis and quantile-based g-computation, were employed to identify genes/gene networks associated with multi-metal exposure. Individually, lead was associated with the strongest genomic response of 191 DEGs. Joint lead and cadmium exposure was related to 657 DEGs, including DNA Methyl Transferase 1 (DNMT1). These genes were enriched for the Eukaryotic Initiation Factor 2 (EIF2) pathway. Four gene networks, each containing genes within a Nuclear Factor kappa-light-chain-enhancer of Activated B Cells (NF-kB)-mediated network, were significantly increased in average expression level in relation to increases in all metal concentrations. All four of these metal mixture-associated gene networks were negatively correlated with important predictors of neonatal health including birth weight, placenta weight, and fetal growth. Bringing together novel methodologies from epidemiological mixtures analyses and toxicogenomics, applied to a unique cohort of extremely preterm children, the present study highlighted critical genes and pathways in the placenta dysregulated by prenatal metal mixtures. These represent potential mechanisms underlying the developmental origins of metal-induced disease., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Although evidence linking environmental chemicals to breast cancer is growing, mixtures-based exposure evaluations are lacking., Objective: This study aimed to identify environmental chemicals in use inventories that co-occur and share properties with chemicals that have association with breast cancer, highlighting exposure combinations that may alter disease risk., Methods: The occurrence of chemicals within chemical use categories was characterized using the Chemical and Products Database. Co-exposure patterns were evaluated for chemicals that have an association with breast cancer (BC), no known association (NBC), and understudied chemicals (UC) identified through query of the Silent Spring Institute's Mammary Carcinogens Review Database and the U.S. Environmental Protection Agency's Toxicity Reference Database. UCs were ranked based on structure and physicochemical similarities and co-occurrence patterns with BCs within environmentally relevant exposure sources., Results: A total of 6793 chemicals had data available for exposure source occurrence analyses. 50 top-ranking UCs spanning five clusters of co-occurring chemicals were prioritized, based on shared properties with co-occuring BCs, including chemicals used in food production and consumer/personal care products, as well as potential endocrine system modulators., Significance: Results highlight important co-exposure conditions that are likely prevalent within our everyday environments that warrant further evaluation for possible breast cancer risk., Impact Statement: Most environmental studies on breast cancer have focused on evaluating relationships between individual, well-known chemicals and breast cancer risk. This study set out to expand this research field by identifying understudied chemicals and mixtures that may occur in everyday environments due to their patterns of commercial use. Analyses focused on those that co-occur alongside chemicals associated with breast cancer, based upon in silico chemical database querying and analysis. Particularly in instances when understudied chemicals share physicochemical properties and structural features with carcinogens, these chemical mixtures represent conditions that should be studied in future clinical, epidemiological, and toxicological studies., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Estimates of exposure are critical to prioritize and assess chemicals based on risk posed to public health and the environment. The U.S. Environmental Protection Agency (EPA) is responsible for regulating thousands of chemicals in commerce and the environment for which exposure data are limited. Since 2009 the EPA's ExpoCast ("Exposure Forecasting") project has sought to develop the data, tools, and evaluation approaches required to generate rapid and scientifically defensible exposure predictions for the full universe of existing and proposed commercial chemicals. This review article aims to summarize issues in exposure science that have been addressed through initiatives affiliated with ExpoCast. ExpoCast research has generally focused on chemical exposure as a statistical systems problem intended to inform thousands of chemicals. The project exists as a companion to EPA's ToxCast ("Toxicity Forecasting") project which has used in vitro high-throughput screening technologies to characterize potential hazard posed by thousands of chemicals for which there are limited toxicity data. Rapid prediction of chemical exposures and in vitro-in vivo extrapolation (IVIVE) of ToxCast data allow for prioritization based upon risk of adverse outcomes due to environmental chemical exposure. ExpoCast has developed (1) integrated modeling approaches to reliably predict exposure and IVIVE dose, (2) highly efficient screening tools for chemical prioritization, (3) efficient and affordable tools for generating new exposure and dose data, and (4) easily accessible exposure databases. The development of new exposure models and databases along with the application of technologies like non-targeted analysis and machine learning have transformed exposure science for data-poor chemicals. By developing high-throughput tools for chemical exposure analytics and translating those tools into public health decisions ExpoCast research has served as a crucible for identifying and addressing exposure science knowledge gaps., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Extracellular vesicles (EVs) represent small, membrane-enclosed particles that are derived from parent cells and are secreted into the extracellular space. Once secreted, EVs can then travel and communicate with nearby or distant cells. Due to their inherent stability and biocompatibility, these particles can effectively transfer RNAs, proteins, and chemicals/metabolites from parent cells to target cells, impacting cellular and pathological processes. EVs have been shown to respond to disease-causing agents and impact target cells. Given that disease-causing agents span environmental contaminants, pathogens, social stressors, drugs, and other agents, the translation of EV methods into public health is now a critical research gap. This paper reviews approaches to translate EVs into exposure science, toxicology, and public health applications, highlighting blood as an example due to its common use within clinical, epidemiological, and toxicological studies. Approaches are reviewed surrounding the isolation and characterization of EVs and molecular markers that can be used to inform EV cell-of-origin. Molecular cargo contained within EVs are then discussed, including an original analysis of blood EV data from Vesiclepedia. Methods to evaluate functional consequences and target tissues of EVs are also reviewed. Lastly, the expanded integration of these approaches into future public health applications is discussed, including the use of EVs as promising biomarkers of exposure, effect, and disease. IMPACT STATEMENT: Extracellular vesicles (EVs) represent small, cell-derived structures consisting of molecules that can serve as biomarkers of exposure, effect, and disease. This review lays a novel foundation for integrating EVs, a rapidly advancing molecular biological tool, into the field of public health research including epidemiological, toxicological, and clinical investigations. This article represents an important advancement in public health and exposure science as it is among the first to translate EVs into this field., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: There is an increased awareness regarding the association between exposure to environmental contaminants and adverse pregnancy outcomes including preterm birth. Whether an individual's metabolic profile can be utilized during pregnancy to differentiate the subset of patients who are ultimately destined to delivered preterm remains uncertain but could have MEANINGFUL clinical implications., Objective: We sought to objectively quantify metabolomic profiles of patients at high risk of preterm birth by evaluating midtrimester maternal plasma and to measure whether endogenous metabolites and exogenous environmental substances differ among those who ultimately deliver preterm compared with those who deliver at term., Study Design: This was a case-control analysis from a prospective cohort of patients carrying a singleton, nonanomalous gestation who were at high risk of spontaneous preterm birth. Subjects with a plasma blood sample drawn at <28 weeks' gestation and no evidence of preterm labor at the time of enrollment were included. Metabolites were extracted from frozen samples, and metabolomic analysis was performed using liquid chromatography/mass spectrometry. The primary outcome was preterm birth at 16.0 to 36.9 weeks' gestation., Results: A total of 42 patients met the inclusion criteria. Of these, 25 (59.5%) delivered preterm at <37 weeks' gestation, at a median of 30.14 weeks' gestation (interquartile range, 28.14-34.14). A total of 812 molecular features differed between preterm birth cases and term controls with a minimum fold change of 1.2 and P<.05. Of these, 570 of 812 (70.1%) were found in higher abundances in preterm birth cases; the other 242 of 812 (29.9%) were in higher abundance in term birth controls. The identity of the small molecule/compound represented by the molecular features differing statistically between preterm birth cases and term controls was identified as ranging from those involved with endogenous metabolic pathways (including lipid catabolism, steroids, and steroid-related molecules) to exogenous exposures (including avocadyne, diosgenin, polycyclic aromatic hydrocarbons, acetaminophen metabolites, aspartame, and caffeine). Random forest analyses evaluating the relative contribution of each of the top 30 compounds in differentiating preterm birth and term controls accurately classified 21 of 25 preterm birth cases (84%)., Conclusion: Both endogenous metabolites and exogenous exposures differ in maternal plasma in the midtrimester among patients who ultimately delivered preterm compared with those who deliver at term., (Copyright © 2021. Published by Elsevier Inc.)

Computational methods are needed to more efficiently leverage data from in vitro cell-based models to predict what occurs within whole body systems after chemical insults. This study set out to test the hypothesis that in vitro high-throughput screening (HTS) data can more effectively predict in vivo biological responses when chemical disposition and toxicokinetic (TK) modeling are employed. In vitro HTS data from the Tox21 consortium were analyzed in concert with chemical disposition modeling to derive nominal, aqueous, and intracellular estimates of concentrations eliciting 50% maximal activity. In vivo biological responses were captured using rat liver transcriptomic data from the DrugMatrix and TG-Gates databases and evaluated for pathway enrichment. In vivo dosing data were translated to equivalent body concentrations using HTTK modeling. Random forest models were then trained and tested to predict in vivo pathway-level activity across 221 chemicals using in vitro bioactivity data and physicochemical properties as predictor variables, incorporating methods to address imbalanced training data resulting from high instances of inactivity. Model performance was quantified using the area under the receiver operator characteristic curve (AUC-ROC) and compared across pathways for different combinations of predictor variables. All models that included toxicokinetics were found to outperform those that excluded toxicokinetics. Biological interpretation of the model features revealed that rather than a direct mapping of in vitro assays to in vivo pathways, unexpected combinations of multiple in vitro assays predicted in vivo pathway-level activities. To demonstrate the utility of these findings, the highest-performing model was leveraged to make new predictions of in vivo biological responses across all biological pathways for remaining chemicals tested in Tox21 with adequate data coverage (n = 6617). These results demonstrate that, when chemical disposition and toxicokinetics are carefully considered, in vitro HT screening data can be used to effectively predict in vivo biological responses to chemicals.

Environmental chemicals comprise a major portion of the human exposome, with some shown to impact the health of susceptible populations, including pregnant women and developing fetuses. The placenta and cord blood serve as important biological windows into the maternal and fetal environments. In this article we review how environmental chemicals (defined here to include man-made chemicals [e.g., flame retardants, pesticides/herbicides, per- and polyfluoroalkyl substances], toxins, metals, and other xenobiotic compounds) contribute to the prenatal exposome and highlight future directions to advance this research field. Our findings from a survey of recent literature indicate the need to better understand the breadth of environmental chemicals that reach the placenta and cord blood, as well as the linkages between prenatal exposures, mechanisms of toxicity, and subsequent health outcomes. Research efforts tailored towards addressing these needs will provide a more comprehensive understanding of how environmental chemicals impact maternal and fetal health., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The nature and types of genome editing tools are rapidly expanding and becoming increasingly incorporated into research efforts aimed at understanding human disease. The majority of research involving genome editing has been driven by medical research, with a limited but increasing number of studies currently published in the field of environmental health and toxicology. This review aims to address this research gap by providing a high-level summary of current genome editing techniques and presenting examples of how some of these techniques have been used toxicologically to evaluate environmental exposure-induced disease. Specific strategies surrounding the evaluation of hazardous chemicals, chemical mechanism of action / adverse outcome pathways, and inter-individual response variability are also discussed to aid in the translation of genome editing methods towards toxicological and environmental health research., Competing Interests: Conflict of Interest No conflict of interest exists.

Recently, the key characteristics of carcinogens (KCC) have been proposed as an organizational approach for the evaluation of mechanistic data related to carcinogenicity. Our objective was to develop a framework to systematically and quantitatively integrate KCC data using elements that are important to risk assessment. Methods for developing the framework included: defining objectives, identifying and accommodating key considerations for components, input, and output of the framework, and operational development via iterative testing by a multidisciplinary team. The proposed framework involves 3 steps: (1) a structured, yet flexible, appraisal of individual studies and endpoints, (2) a structured and transparent evaluation of the body of evidence for each key characteristic, and (3) an evaluation of all of the KCC-relevant data relative to tumors and/or cancer types. In step 1, data are assessed and scored for reliability, strength, and activity. In step 2, a mathematical algorithm is used to integrate (and weight) the quality, relevance, and activity for each of the KCCs. These scores facilitate subsequent evaluations related to the overall body of evidence in step 3 in which KCCs can be linked, assessing potential adverse outcome pathways or networks, and finally, considered in the context of observed carcinogenic responses in animals and/or humans. The output is an overall conclusion regarding KCC activity as it relates to carcinogenic responses. The proposed framework provides a flexible solution to quantitatively integrate KCC data in a systematic and transparent manner that provides weighting of data most well-suited for the assessment of potential human carcinogenicity.

Tens-of-thousands of chemicals are registered in the U.S. for use in countless processes and products. Recent evidence suggests that many of these chemicals are measureable in environmental and/or biological systems, indicating the potential for widespread exposures. Traditional public health research tools, including in vivo studies and targeted analytical chemistry methods, have been unable to meet the needs of screening programs designed to evaluate chemical safety. As such, new tools have been developed to enable rapid assessment of potentially harmful chemical exposures and their attendant biological responses. One group of tools, known as "non-targeted analysis" (NTA) methods, allows the rapid characterization of thousands of never-before-studied compounds in a wide variety of environmental, residential, and biological media. This article discusses current applications of NTA methods, challenges to their effective use in chemical screening studies, and ways in which shared resources (e.g., chemical standards, databases, model predictions, and media measurements) can advance their use in risk-based chemical prioritization. A brief review is provided of resources and projects within EPA's Office of Research and Development (ORD) that provide benefit to, and receive benefits from, NTA research endeavors. A summary of EPA's Non-Targeted Analysis Collaborative Trial (ENTACT) is also given, which makes direct use of ORD resources to benefit the global NTA research community. Finally, a research framework is described that shows how NTA methods will bridge chemical prioritization efforts within ORD. This framework exists as a guide for institutions seeking to understand the complexity of chemical exposures, and the impact of these exposures on living systems.

Recent analyses-highlighted by the International Workshops on Genotoxicity Testing Working Group on Quantitative Approaches to Genetic Toxicology Risk Assessment-have identified a correlation between (log) estimates of a carcinogen's in vivo genotoxic potency and in vivo carcinogenic potency in typical laboratory animal models, even when the underlying data have not been matched for tissue, species, or strain. Such a correlation could have important implications for risk assessment, including informing the mode of action (MOA) of specific carcinogens. When in vivo genotoxic potency is weak relative to carcinogenic potency, MOAs other than genotoxicity (e.g., endocrine disruption or regenerative hyperplasia) may be operational. Herein, we review recent in vivo genotoxicity and carcinogenicity data for hexavalent chromium (Cr(VI)), following oral ingestion, in relevant tissues and species in the context of the aforementioned correlation. Potency estimates were generated using benchmark doses, or no-observable-adverse-effect-levels when data were not amenable to dose-response modeling. While the ratio between log values for carcinogenic and genotoxic potency was ≥1 for many compounds, the ratios for several Cr(VI) datasets (including in target tissue) were less than unity. In fact, the ratios for Cr(VI) clustered closely with ratios for chloroform and diethanolamine, two chemicals posited to have non-genotoxic MOAs. These findings suggest that genotoxicity may not play a major role in the cancers observed in rodents following exposure to high concentrations of Cr(VI) in drinking water-a finding consistent with recent MOA and adverse outcome pathway (AOP) analyses concerning Cr(VI). This semi-quantitative analysis, therefore, may be useful to augment traditional MOA and AOP analyses. More case examples will be needed to further explore the general applicability and validity of this approach for human health risk assessment., (Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.)

Ozone (O3) is a criteria air pollutant that is associated with numerous adverse health effects, including altered respiratory immune responses. Despite its deleterious health effects, possible epigenetic mechanisms underlying O3-induced health effects remain understudied. MicroRNAs (miRNAs) are epigenetic regulators of genomic response to environmental insults and unstudied in relationship to O3 inhalation exposure. Our objective was to test whether O3 inhalation exposure significantly alters miRNA expression profiles within the human bronchial airways. Twenty healthy adult human volunteers were exposed to 0.4 ppm O3 for 2 h. Induced sputum samples were collected from each subject 48 h preexposure and 6 h postexposure for evaluation of miRNA expression and markers of inflammation in the airways. Genomewide miRNA expression profiles were evaluated by microarray analysis, and in silico predicted mRNA targets of the O3-responsive miRNAs were identified and validated against previously measured O3-induced changes in mRNA targets. Biological network analysis was performed on the O3-associated miRNAs and mRNA targets to reveal potential associated response signaling and functional enrichment. Expression analysis of the sputum samples revealed that O3 exposure significantly increased the expression levels of 10 miRNAs, namely miR-132, miR-143, miR-145, miR-199a*, miR-199b-5p, miR-222, miR-223, miR-25, miR-424, and miR-582-5p. The miRNAs and their predicted targets were associated with a diverse range of biological functions and disease signatures, noted among them inflammation and immune-related disease. The present study shows that O3 inhalation exposure disrupts select miRNA expression profiles that are associated with inflammatory and immune response signaling. These findings provide novel insight into epigenetic regulation of responses to O3 exposure., (Copyright © 2014 the American Physiological Society.)

MicroRNAs (miRNAs) are critical regulators of gene expression, yet much remains unknown regarding their changes resulting from environmental exposures as they influence cellular signaling across various tissues. We set out to investigate miRNA responses to formaldehyde, a critical air pollutant and known carcinogen that disrupts miRNA expression profiles. Rats were exposed by inhalation to either 0 or 2 ppm formaldehyde for 7, 28, or 28 days followed by a 7-day recovery. Genome-wide miRNA expression profiles were assessed within the nasal respiratory epithelium, circulating white blood cells (WBC), and bone marrow (BM). miRNAs showed altered expression in the nose and WBC but not in the BM. Notably in the nose, miR-10b and members of the let-7 family, known nasopharyngeal carcinoma players, showed decreased expression. To integrate miRNA responses with transcriptional changes, genome-wide messenger RNA profiles were assessed in the nose and WBC. Although formaldehyde-induced changes in miRNA and transcript expression were largely tissue specific, pathway analyses revealed an enrichment of immune system/inflammation signaling in the nose and WBC. Specific to the nose was enrichment for apoptosis/proliferation signaling, involving let-7a, let-7c, and let-7f. Across all tissues and time points assessed, miRNAs were predicted to regulate between 7% and 35% of the transcriptional responses and were suggested to play a role in signaling processes including immune/inflammation-related pathways. These data inform our current hypothesis that formaldehyde-induced inflammatory signals originating in the nose may drive WBC effects.

We previously demonstrated that, in nasal epithelial cells (NECs) from smokers, methylation of an antiviral gene was associated with impaired antiviral defense responses. To expand these findings and better understand biological mechanisms underlying cigarette smoke (CS)-induced modifications of host defense responses, we aimed to compare DNA methylation of genes that may play a role in antiviral response. We used a two-tiered analytical approach, where we first implemented a genome-wide strategy. NECs from smokers differed in the methylation levels of 390 genes, the majority (84%) of which showed decreased methylation in smokers. Secondly, we generated an a priori set of 161 antiviral response-related genes, of which five were differentially methylated in NEC from smokers (CCL2, FDPS, GSK3B, SOCS3, and ULBP3). Assessing these genes at the systems biology level revealed a protein interaction network associated with CS-induced epigenetic modifications involving SOCS3 and ULBP3 signaling, among others. Subsequent confirmation studies focused on SOCS3 and ULBP3, which were hypomethylated and hypermethylated, respectively. Expression of SOCS3 was increased, whereas ULBP3 expression was decreased in NECs from smokers. Addition of the demethylating agent 5-Aza-2-deoxycytidine enhanced ULBP3 expression in NECs from smokers. Furthermore, infection of differentiated NECs with influenza virus resulted in significantly lower levels of ULBP3 in cells from smokers. Taken together, our findings show that genomic DNA methylation profiles are altered in NECs from smokers and that these changes are associated with decreased antiviral host defense responses, indicating that epigenenic dysregulation of genes such as SOCS3 and ULBP3 likely impacts immune responses in the epithelium.