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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 IL6was 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.

A weighted chemical coexpression network analysis (WCCNA) was utilized to identify chemicals co-modulated to variable burning of anthropogenic materials and to link chemicals to biological responses (lung toxicity and mutagenicity). Polyaromatic hydrocarbons (PAHs) were co-modulated with increased concentrations in flaming smoke particulate matter (PM) from the burning of plastic-containing materials and showed significant association with increased neutrophil influx, cytokine levels, and mutagenicity. Inorganic elements were co-modulated with increased concentrations in flaming plywood and cardboard smoke PM and showed significant association with increased protein and albumin levels. This study shows the potential for using a computational network analysis to identify and prioritize hazardous chemical components within complex environmental mixtures and provides guidance on key chemical tracers required for intervention research to protect public health from the exposure.

The prevalence of wildfires continues to grow globally with exposures resulting in increased disease risk. Characterizing these health risks remains difficult due to the wide landscape of exposures that can result from different burn conditions and fuel types. This study tested the hypothesis that biomass smoke exposures from variable fuels and combustion conditions group together based on similar transcriptional response profiles, informing which wildfire-relevant exposures may be considered as a group for health risk evaluations. Mice (female CD-1) were exposed via oropharyngeal aspiration to equal mass biomass smoke condensates produced from flaming or smoldering burns of eucalyptus, peat, pine, pine needles, or red oak species. Lung transcriptomic signatures were used to calculate transcriptomic similarity scores across exposures, which informed exposure groupings. Exposures from flaming peat, flaming eucalyptus, and smoldering eucalyptus induced the greatest responses, with flaming peat grouping with the pro-inflammatory agent lipopolysaccharide. Smoldering red oak and smoldering peat induced the least transcriptomic response. Groupings paralleled pulmonary toxicity markers, though they were better substantiated by higher data dimensionality and resolution provided through -omic-based evaluation. Interestingly, groupings based on smoke chemistry signatures differed from transcriptomic/toxicity-based groupings. Wildfire-relevant exposure groupings yield insights into risk assessment strategies to ultimately protect public health.

ABSTRACTAdverse pregnancy outcomes disproportionately affect non-Hispanic (NH) Black patients in the United States. Structural racism has been associated with increased psychosocial distress and inflammation and may trigger oxidative stress. Thus, the nitric oxide (NO) pathway (involved in the regulation of inflammation and oxidative stress) may partly explain the underlying disparities in obstetric outcomes.Cohort study of 154 pregnant patients with high-risk obstetric histories; n = 212 mRNAs and n = 108 microRNAs (miRNAs) in the NO pathway were evaluated in circulating white blood cells. NO pathway mRNA and miRNA transcript counts were compared by self-reported race; NH Black patients were compared with women of other races/ethnicities. Finally, miRNA-mRNA expression levels were correlated.Twenty-two genes (q < 0.10) were differentially expressed in self-identified NH Black individuals. Superoxide dismutase 1 (SOD1), interleukin-8 (IL-8), dynein light chain LC8-type 1 (DYNLL1), glutathione peroxidase 4 (GPX4), and glutathione peroxidase 1 (GPX1) were the five most differentially expressed genes among NH Black patients compared to other patients. There were 63 significantly correlated miRNA-mRNA pairs (q < 0.10) demonstrating potential miRNA regulation of associated target mRNA expression. Ten miRNAs that were identified as members of significant miRNA-mRNA pairs were also differentially expressed among NH Black patients (q < 0.10).These findings support an association between NO pathway and inflammation and infection-related mRNA and miRNA expression in blood drawn during pregnancy and patient race/ethnicity. These findings may reflect key differences in the biology of inflammatory gene dysregulation that occurs in response to the stress of systemic racism and that underlies disparities in pregnancy outcomes.

Exposure to polycyclic aromatic hydrocarbons (PAHs) often occurs as complex chemical mixtures, which are linked to numerous adverse health outcomes in humans, with cancer as the greatest concern. The cancer risk associated with PAH exposures is commonly evaluated using the relative potency factor (RPF) approach, which estimates PAH mixture carcinogenic potential based on the sum of relative potency estimates of individual PAHs, compared to benzo[a]pyrene (BAP), a reference carcinogen. The present study evaluates molecular mechanisms related to PAH cancer risk through integration of transcriptomic and bioinformatic approaches in a 3D human bronchial epithelial cell model. Genes with significant differential expression from human bronchial epithelium exposed to PAHs were analyzed using a weighted gene coexpression network analysis (WGCNA) two-tiered approach: first to identify gene sets comodulated to RPF and second to link genes to a more comprehensive list of regulatory values, including inhalation-specific risk values. Over 3000 genes associated with processes of cell cycle regulation, inflammation, DNA damage, and cell adhesion processes were found to be comodulated with increasing RPF with pathways for cell cycle S phase and cytoskeleton actin identified as the most significantly enriched biological networks correlated to RPF. In addition, comodulated genes were linked to additional cancer-relevant risk values, including inhalation unit risks, oral cancer slope factors, and cancer hazard classifications from the World Health Organization’s International Agency for Research on Cancer (IARC). These gene sets represent potential biomarkers that could be used to evaluate cancer risk associated with PAH mixtures. Among the values tested, RPF values and IARC categorizations shared the most similar responses in positively and negatively correlated gene modules. Together, we demonstrated a novel manner of integrating gene sets with chemical toxicity equivalence estimates through WGCNA to understand potential mechanisms.

Atmospheric pollution represents a complex mixture of air chemicals that continually interact and transform, making it difficult to accurately evaluate associated toxicity responses representative of real-world exposure. This study leveraged data from a previously published article and reevaluated lung cell transcriptional response induced by outdoor atmospheric pollution mixtures using field-based exposure conditions in the industrialized Houston Ship Channel. The tested hypothesis was that individual and co-occurring chemicals in the atmosphere relate to altered expression of critical genes involved in inflammation and cancer-related processes in lung cells. Human lung cells were exposed at an air–liquid interface to ambient air mixtures for 4 h, with experiments replicated across 5 days. Real-time monitoring of primary and secondary gas-phase pollutants, as well as other atmospheric conditions, was simultaneously conducted. Transcriptional analysis of exposed cells identified critical genes showing differential expression associated with both individual and chemical mixtures. The individual pollutant identified with the largest amount of associated transcriptional response was benzene. Tumor necrosis factor (TNF) and interferon regulatory factor 1 (IRFN1) were identified as key upstream transcription factor regulators of the cellular response to benzene. This study is among the first to measure lung cell transcriptional responses in relation to real-world, gas-phase air mixtures.

The nature and type 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. The aim of the review is 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 interindividual response variability are also discussed to aid in the translation of genome editing methods toward toxicological and environmental health research.

Prenatal inorganic arsenic (iAs) exposure influences the expression of critical genes and proteins associated with adverse outcomes in newborns, in part through epigenetic mediators. The doses at which these genomic and epigenomic changes occur have yet to be evaluated in the context of dose–response modeling. The goal of the present study was to estimate iAs doses that correspond to changes in transcriptomic, proteomic, epigenomic, and integrated multi-omic signatures in human cord blood through benchmark dose (BMD) modeling. Genome-wide DNA methylation, microRNA expression, mRNA expression, and protein expression levels in cord blood were modeled against total urinary arsenic (U-tAs) levels from pregnant women exposed to varying levels of iAs. Dose–response relationships were modeled in BMDExpress, and BMDs representing 10% response levels were estimated. Overall, DNA methylation changes were estimated to occur at lower exposure concentrations in comparison to other molecular endpoints. Multi-omic module eigengenes were derived through weighted gene co-expression network analysis, representing co-modulated signatures across transcriptomic, proteomic, and epigenomic profiles. One module eigengene was associated with decreased gestational age occurring alongside increased iAs exposure. Genes/proteins within this module eigengene showed enrichment for organismal development, including potassium voltage-gated channel subfamily Q member 1 (KCNQ1), an imprinted gene showing differential methylation and expression in response to iAs. Modeling of this prioritized multi-omic module eigengene resulted in a BMD(BMDL) of 58(45) μg/L U-tAs, which was estimated to correspond to drinking water arsenic concentrations of 51(40) μg/L. Results are in line with epidemiological evidence supporting effects of prenatal iAs occurring at levels <100 μg As/L urine. Together, findings present a variety of BMD measures to estimate doses at which prenatal iAs exposure influences neonatal outcome-relevant transcriptomic, proteomic, and epigenomic profiles.

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.

The relationship between genotoxicity and cancer has been extensively demonstrated and is well accepted; however, the role of epigenetic regulators that are involved in genotoxic events and carcinogenic processes is less understood. Epigenetic mechanisms are known to play important roles in carcinogenesis, and connections between epigenetics and DNA damage and repair have been reported. This mini review discusses some of the known relationships between epigenetic mechanisms and DNA damage, focusing on DNA methylation, histone modification, and microRNAs. Examples include: (i) preferential binding of reactive chemicals or metabolites to methylated cytosines at mutational “hotspots” that lead to carcinogenesis, (ii) histone modifications that affect chromatin structure, resulting in altered accessibility of DNA to damaging agents and/or DNA repair machinery and/or recruitment of DNA repair machinery to sites of damage, and (iii) changes in abundance of microRNAs that regulate the expression of genes involved in DNA damage response. Still, there remains a need for further research on these topics, as key findings on epigenetic alterations will advance the understanding of chemical-induced cancer, including cases that involve genotoxicity. A better understanding of the role of the epigenome in chemical carcinogenesis will contribute to improvements in human health hazard assessments and screening efforts for potential carcinogens.

•Computational methods are needed to leverage in vitromodels to inform toxicology.•Machine learning was integrated with toxicokinetic modeling to predict biology.•In vitroTox21 data were able to predict in vivo-omics responses in the liver.•Models improved after including toxicokinetics and chemical disposition modeling.•Models were used to predict pathway responses across understudied chemicals.