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BackgroundThe ability to induce chronic inflammation and immunosuppression are two key characteristics of carcinogens and important forms of immunotoxicity. The National Toxicology Program (NTP) evaluated the immunotoxicity of two per- and polyfluoroalkyl substances (PFASs), PFOA (perfluorooctanoic acid) and PFOS (perfluorooctane sulfonate), in 2016. However, the potential pro-inflammatory and immunosuppressive effects of other PFASs remain largely uncharacterized.MethodsWe developed an expanded set of search terms pertaining to the chronic inflammatory and immunosuppressive effects of PFASs based on those of the International Agency for Research on Cancer (IARC) and NTP. To confirm searching effectiveness and scope, we compared our search term results with those of IARC and NTP for both PFASs and two other known carcinogens, chromium (VI) and benzene. Systematic evidence maps (SEMs) were also produced using Tableau to visualize the distribution of study numbers and types reporting immunotoxic effects and specific biomarkers elicited by PFAS exposures.ResultsIn total, 1155 PFAS studies were retrieved, of which 321 qualified for inclusion in our dataset. Using our search terms, we identified a greater number of relevant studies than those obtained using IARC and NTP's search terms. From the SEM findings, increased cytokine production strengthened an association between PFAS exposure and chronic inflammation, and decreased B-cell activation and altered levels of T-cell subtypes and immunoglobulins confirmed PFAS-induced immunosuppression.ConclusionOur SEM findings confirm that several PFASs commonly found in both in the environment, including those that are lesser-known, may induce immunosuppression and chronic inflammation, two key characteristics of carcinogens. This approach, including development of search terms, study screening process, data coding, and evidence mapping visualizations, can be applied to other key characteristics of chemical carcinogens.

BackgroundComplex systems models of breast cancer have previously focused on prediction of prognosis and clinical events for individual women. There is a need for understanding breast cancer at the population level for public health decision-making, for identifying gaps in epidemiologic knowledge and for the education of the public as to the complexity of this most common of cancers.Methods and findingsWe developed an agent-based model of breast cancer for the women of the state of California using data from the U.S. Census, the California Health Interview Survey, the California Cancer Registry, the National Health and Nutrition Examination Survey and the literature. The model was implemented in the Julia programming language and R computing environment. The Paradigm II model development followed a transdisciplinary process with expertise from multiple relevant disciplinary experts from genetics to epidemiology and sociology with the goal of exploring both upstream determinants at the population level and pathophysiologic etiologic factors at the biologic level. The resulting model reproduces in a reasonable manner the overall age-specific incidence curve for the years 2008-2012 and incidence and relative risks due to specific risk factors such as BRCA1, polygenic risk, alcohol consumption, hormone therapy, breastfeeding, oral contraceptive use and scenarios for environmental toxin exposures.ConclusionsThe Paradigm II model illustrates the role of multiple etiologic factors in breast cancer from domains of biology, behavior and the environment. The value of the model is in providing a virtual laboratory to evaluate a wide range of potential interventions into the social, environmental and behavioral determinants of breast cancer at the population level.

Sufficient evidence supports a relationship between certain myeloid neoplasms and exposure to benzene or formaldehyde. DNA methylation could underlie benzene- and formaldehyde-induced health outcomes, but data in exposed human populations are limited. We conducted two cross-sectional epigenome-wide association studies (EWAS), one in workers exposed to benzene and another in workers exposed to formaldehyde. Using HumanMethylation450 BeadChips, we investigated differences in blood cell DNA methylation among 50 benzene-exposed subjects and 48 controls, and among 31 formaldehyde-exposed subjects and 40 controls. We performed CpG-level and regional-level analyses. In the benzene EWAS, we found genome-wide significant alterations, i.e., FWER-controlled P-values

BackgroundKey characteristics (KCs), properties of agents or exposures that confer potential hazard, have been developed for carcinogens and other toxicant classes. KCs have been used in the systematic assessment of hazards and to identify assay and data gaps that limit screening and risk assessment. Many of the mechanisms through which pharmaceuticals and occupational or environmental agents modulate immune function are well recognized. Thus KCs could be identified for immunoactive substances and applied to improve hazard assessment of immunodulatory agents.ObjectivesThe goal was to generate a consensus-based synthesis of scientific evidence describing the KCs of agents known to cause immunotoxicity and potential applications, such as assays to measure the KCs.MethodsA committee of 18 experts with diverse specialties identified 10 KCs of immunotoxic agents, namely, 1) covalently binds to proteins to form novel antigens, 2) affects antigen processing and presentation, 3) alters immune cell signaling, 4) alters immune cell proliferation, 5) modifies cellular differentiation, 6) alters immune cell-cell communication, 7) alters effector function of specific cell types, 8) alters immune cell trafficking, 9) alters cell death processes, and 10) breaks down immune tolerance. The group considered how these KCs could influence immune processes and contribute to hypersensitivity, inappropriate enhancement, immunosuppression, or autoimmunity.DiscussionKCs can be used to improve efforts to identify agents that cause immunotoxicity via one or more mechanisms, to develop better testing and biomarker approaches to evaluate immunotoxicity, and to enable a more comprehensive and mechanistic understanding of adverse effects of exposures on the immune system. https://doi.org/10.1289/EHP10800.

Exposure to arsenic affects millions of people globally. Changes in the epigenome may be involved in pathways linking arsenic to health or serve as biomarkers of exposure. This study investigated associations between prenatal and early-life arsenic exposure and epigenetic age acceleration (EAA) in adults, a biomarker of morbidity and mortality. DNA methylation was measured in peripheral blood mononuclear cells (PBMCs) and buccal cells from 40 adults (median age = 49 years) in Chile with and without high prenatal and early-life arsenic exposure. EAA was calculated using the Horvath, Hannum, PhenoAge, skin and blood, GrimAge, and DNA methylation telomere length clocks. We evaluated associations between arsenic exposure and EAA using robust linear models. Participants classified as with and without arsenic exposure had a median drinking water arsenic concentration at birth of 555 and 2 μg/l, respectively. In PBMCs, adjusting for sex and smoking, exposure was associated with a 6-year PhenoAge acceleration [B (95% CI) = 6.01 (2.60, 9.42)]. After adjusting for cell-type composition, we found positive associations with Hannum EAA [B (95% CI) = 3.11 (0.13, 6.10)], skin and blood EAA [B (95% CI) = 1.77 (0.51, 3.03)], and extrinsic EAA [B (95% CI) = 4.90 (1.22, 8.57)]. The association with PhenoAge acceleration in buccal cells was positive but not statistically significant [B (95% CI) = 4.88 (-1.60, 11.36)]. Arsenic exposure limited to early-life stages may be associated with biological aging in adulthood. Future research may provide information on how EAA programmed in early life is related to health.

Nuclear receptors (NRs) are important biological targets of endocrine-disrupting chemicals (EDCs). Identifying chemicals that can act as EDCs and modulate the function of NRs is difficult because of the time and cost of in vitro and in vivo screening to determine the potential hazards of the 100 000s of chemicals that humans are exposed to. Hence, there is a need for computational approaches to prioritize chemicals for biological testing. Machine learning (ML) techniques are alternative methods that can quickly screen millions of chemicals and identify those that may be an EDC. Computational models of chemical binding to multiple NRs have begun to emerge. Recently, a Nuclear Receptor Activity (NuRA) dataset, describing experimentally derived small-molecule activity against various NRs has been created. We have used the NuRA dataset to develop an ensemble of ML-based models to predict the agonism, antagonism, binding and effector binding of small molecules to nine different human NRs. We defined the applicability domain of the ML models as a measure of Tanimoto similarity to the molecules in the training set, which enhanced the performance of the developed classifiers. We further developed a user-friendly web server named 'NR-ToxPred' to predict the binding of chemicals to the nine NRs using the best-performing models for each receptor. This web server is freely accessible at http://nr-toxpred.cchem.berkeley.edu. Users can upload individual chemicals using Simplified Molecular-Input Line-Entry System, CAS numbers or sketch the molecule in the provided space to predict the compound's activity against the different NRs and predict the binding mode for each.

Per- and poly-fluoroalkyl substances (PFASs) are used extensively in a broad range of industrial applications and consumer products. While a few legacy PFASs have been voluntarily phased out, over 5000 PFASs have been produced as replacements for their predecessors. The potential endocrine disrupting hazards of most emerging PFASs have not been comprehensively investigated. In silico molecular docking to the human androgen receptor (hAR) combined with machine learning techniques were previously applied to 5206 PFASs and predicted 23 PFASs bind the hAR. Herein, the in silico results were validated in vitro for the five candidate AR ligands that were commercially available. Three manufactured PFASs namely (9-(nonafluorobutyl)- 2,3,6,7-tetrahydro-1 H,5 H,11 H-pyrano[2,3-f]pyrido[3,2,1-ij]quinolin-11-one (NON), 2-(heptafluoropropyl)- 3-phenylquinoxaline (HEP), and 2,2,3,3,4,4,5,5,5-nonafluoro-N-(4-nitrophenyl)pentanamide (NNN) elicited significant antiandrogenic effects at relatively low concentrations. We further investigated the mechanism of AR inhibition and found that all three PFASs inhibited AR transactivation induced by testosterone through a competitive binding mechanism. We then examined the antiandrogenic effects of these PFASs on AR expression and its responsive genes. Consistently, these PFASs significantly decreased the expression of PSA and FKBP5 and increased the expression of AR, similar to the effects elicited by a known competitive AR inhibitor, hydroxyflutamide. This suggests they are competitive antagonists of AR activity and western blot analysis revealed these PFASs decreased intracellular AR protein in androgen sensitive human prostate cancer cells. Hence, the findings presented here corroborate our published in silico approach and indicate these emerging PFASs may adversely affect the human endocrine system.

Epigenetic aging biomarkers are associated with increased morbidity and mortality. We evaluated if occupational exposure to three established chemical carcinogens is associated with acceleration of epigenetic aging. We studied workers in China occupationally exposed to benzene, trichloroethylene (TCE) or formaldehyde by measuring personal air exposures prior to blood collection. Unexposed controls matched by age and sex were selected from nearby factories. We measured leukocyte DNA methylation (DNAm) in peripheral white blood cells using the Infinium HumanMethylation450 BeadChip to calculate five epigenetic aging clocks and DNAmTL, a biomarker associated with leukocyte telomere length and cell replication. We tested associations between exposure intensity and epigenetic age acceleration (EAA), defined as the residuals of regressing the DNAm aging biomarker on chronological age, matching factors and potential confounders. Median differences in EAA between exposure groups were tested using a permutation test with exact p-values. Epigenetic clocks were strongly correlated with age (Spearman r > 0.8) in all three occupational studies. There was a positive exposure-response relationship between benzene and the Skin-Blood Clock EAA biomarker: median EAA was -0.91 years in controls (n = 44), 0.78 years in workers exposed to

BackgroundArsenic (As) exposure through drinking water is a global public health concern. Epigenetic dysregulation including changes in DNA methylation (DNAm), may be involved in arsenic toxicity. Epigenome-wide association studies (EWAS) of arsenic exposure have been restricted to single populations and comparison across EWAS has been limited by methodological differences. Leveraging data from epidemiological studies conducted in Chile and Bangladesh, we use a harmonized data processing and analysis pipeline and meta-analysis to combine results from four EWAS.MethodsDNAm was measured among adults in Chile with and without prenatal and early-life As exposure in PBMCs and buccal cells (N = 40, 850K array) and among men in Bangladesh with high and low As exposure in PBMCs (N = 32, 850K array; N = 48, 450K array). Linear models were used to identify differentially methylated positions (DMPs) and differentially variable positions (DVPs) adjusting for age, smoking, cell type, and sex in the Chile cohort. Probes common across EWAS were meta-analyzed using METAL, and differentially methylated and variable regions (DMRs and DVRs, respectively) were identified using comb-p. KEGG pathway analysis was used to understand biological functions of DMPs and DVPs.ResultsIn a meta-analysis restricted to PBMCs, we identified one DMP and 23 DVPs associated with arsenic exposure; including buccal cells, we identified 3 DMPs and 19 DVPs (FDR

Metformin and weight loss relationships with epigenetic age measures-biological aging biomarkers-remain understudied. We performed a post-hoc analysis of a randomized controlled trial among overweight/obese breast cancer survivors (N = 192) assigned to metformin, placebo, weight loss with metformin, or weight loss with placebo interventions for 6 months. Epigenetic age was correlated with chronological age (r = 0.20-0.86; P

BackgroundThe concept of chemical agents having properties that confer potential hazard called key characteristics (KCs) was first developed to identify carcinogenic hazards. Identification of KCs of cardiovascular (CV) toxicants could facilitate the systematic assessment of CV hazards and understanding of assay and data gaps associated with current approaches.ObjectivesWe sought to develop a consensus-based synthesis of scientific evidence on the KCs of chemical and nonchemical agents known to cause CV toxicity along with methods to measure them.MethodsAn expert working group was convened to discuss mechanisms associated with CV toxicity.ResultsThe group identified 12 KCs of CV toxicants, defined as exogenous agents that adversely interfere with function of the CV system. The KCs were organized into those primarily affecting cardiac tissue (numbers 1-4 below), the vascular system (5-7), or both (8-12), as follows: 1) impairs regulation of cardiac excitability, 2) impairs cardiac contractility and relaxation, 3) induces cardiomyocyte injury and death, 4) induces proliferation of valve stroma, 5) impacts endothelial and vascular function, 6) alters hemostasis, 7) causes dyslipidemia, 8) impairs mitochondrial function, 9) modifies autonomic nervous system activity, 10) induces oxidative stress, 11) causes inflammation, and 12) alters hormone signaling.DiscussionThese 12 KCs can be used to help identify pharmaceuticals and environmental pollutants as CV toxicants, as well as to better understand the mechanistic underpinnings of their toxicity. For example, evidence exists that fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] air pollution, arsenic, anthracycline drugs, and other exogenous chemicals possess one or more of the described KCs. In conclusion, the KCs could be used to identify potential CV toxicants and to define a set of test methods to evaluate CV toxicity in a more comprehensive and standardized manner than current approaches. https://doi.org/10.1289/EHP9321.

ObjectivesThe US National Toxicology Program (NTP) recently recommended in its Report on Carcinogens Monograph for Antimony Trioxide that antimony trioxide be listed as 'reasonably anticipated to be a human carcinogen' based on sufficient evidence of carcinogenicity in experimental animals and supporting evidence from mechanistic studies. Our goal was to estimate the possible human cancer risk from occupational exposure to antimony trioxide.MethodsWe selected data from 2-year inhalation studies in male and female mice conducted by the NTP and performed cancer dose-response analyses using cancer models and benchmark dose methods developed by the US Environmental Protection Agency. In these analyses, we generated benchmark doses and cancer slope factors for antimony trioxide, and then estimated human cancer risk under various exposure scenarios. Typical and worst-case inhalation scenarios in multiple occupational settings were used in risk estimation.ResultsIn typical case scenarios, the occupational cancer risk from antimony trioxide was estimated to be 0.025 (25 in 1000) for persons working with flame retardants in plastics and textiles for 40 years. Under worst-case scenarios, the occupational cancer risk was estimated to be 0.11 (110 in 1000) for persons working with flame retardants in plastics and textiles. At the current Occupational Safety and Health Administration Permissible Exposure Limit, the cancer risk for occupational inhalation exposure of antimony trioxide was estimated to be 0.096 (96 in 1000).ConclusionThe risk estimates calculated in this study suggest that exposure to antimony trioxide at levels present in certain occupational settings results in a large increase in the risk of developing cancer.

BackgroundPeople are exposed to numerous chemicals throughout their lifetimes. Many of these chemicals display one or more of the key characteristics of carcinogens or interact with processes described in the hallmarks of cancer. Therefore, evaluating the effects of chemical mixtures on cancer development is an important pursuit. Challenges involved in designing research studies to evaluate the joint action of chemicals on cancer risk include the time taken to perform the experiments because of the long latency and choosing an appropriate experimental design.ObjectivesThe objectives of this work are to present the case for developing a research program on mixtures of environmental chemicals and cancer risk and describe recommended approaches.MethodsA working group comprising the coauthors focused attention on the design of mixtures studies to inform cancer risk assessment as part of a larger effort to refine the key characteristics of carcinogens and explore their application. Working group members reviewed the key characteristics of carcinogens, hallmarks of cancer, and mixtures research for other disease end points. The group discussed options for developing tractable projects to evaluate the joint effects of environmental chemicals on cancer development.Results and discussionThree approaches for developing a research program to evaluate the effects of mixtures on cancer development were proposed: a chemical screening approach, a transgenic model-based approach, and a disease-centered approach. Advantages and disadvantages of each are discussed. https://doi.org/10.1289/EHP8525.

Environmental exposures often occur in complex mixtures and at low concentrations. Generalized concentration addition (GCA) is a method used to estimate the joint effect of receptor ligands that vary in efficacy. GCA models have been successfully applied to mixtures of aryl hydrocarbon receptor (AhR) and peroxisome proliferator-activated receptor gamma (PPARγ) ligands, each of which can be modeled as a receptor with a single binding site. Here, we evaluated whether GCA could be applied to homodimer nuclear receptors, which have two binding sites, to predict the combined effect of full glucocorticoid receptor (GR) agonists with partial agonists. We measured transcriptional activation of GR using a cell-based bioassay. Individual concentration-response curves for dexamethasone (full agonist), prednisolone (full agonist), and medroxyprogesterone 17-acetate (partial agonist) were generated and applied in three additivity models, GCA, effect summation (ES), and relative potency factor (RPF), to generate response surfaces. GCA and RPF yielded adequate predictions of the experimental data for two full agonists. However, GCA fit experimental data significantly better than ES and RPF for all other binary mixtures. This work extends the application of GCA to homodimer nuclear receptors and improves prediction accuracy of mixture effects of GR agonists.

The key characteristics (KC) of human carcinogens provide a uniform approach to evaluating mechanistic evidence in cancer hazard identification. Refinements to the approach were requested by organizations and individuals applying the KCs. We assembled an expert committee with knowledge of carcinogenesis and experience in applying the KCs in cancer hazard identification. We leveraged this expertise and examined the literature to more clearly describe each KC, identify current and emerging assays and in vivo biomarkers that can be used to measure them, and make recommendations for future assay development. We found that the KCs are clearly distinct from the Hallmarks of Cancer, that interrelationships among the KCs can be leveraged to strengthen the KC approach (and an understanding of environmental carcinogenesis), and that the KC approach is applicable to the systematic evaluation of a broad range of potential cancer hazards in vivo and in vitro We identified gaps in coverage of the KCs by current assays. Future efforts should expand the breadth, specificity, and sensitivity of validated assays and biomarkers that can measure the 10 KCs. Refinement of the KC approach will enhance and accelerate carcinogen identification, a first step in cancer prevention.See all articles in this CEBP Focus section, "Environmental Carcinogenesis: Pathways to Prevention."

BackgroundThe prevalence of type 2 diabetes (T2D) has more than doubled since 1980. Poor nutrition, sedentary lifestyle, and obesity are among the primary risk factors. While an estimated 70% of cases are attributed to excess adiposity, there is an increased interest in understanding the contribution of environmental agents to diabetes causation and severity. Arsenic is one of these environmental chemicals, with multiple epidemiology studies supporting its association with T2D. Despite extensive research, the molecular mechanism by which arsenic exerts its diabetogenic effects remains unclear.ObjectivesWe conducted a literature search focused on arsenite exposure in vivo and in vitro, using relevant end points to elucidate potential mechanisms of oral arsenic exposure and diabetes development.MethodsWe explored experimental results for potential mechanisms and elucidated the distinct effects that occur at high vs. low exposure. We also performed network analyses relying on publicly available data, which supported our key findings.ResultsWhile several mechanisms may be involved, our findings support that arsenite has effects on whole-body glucose homeostasis, insulin-stimulated glucose uptake, glucose-stimulated insulin secretion, hepatic glucose metabolism, and both adipose and pancreatic β-cell dysfunction.DiscussionThis review applies state-of-the-science approaches to identify the current knowledge gaps in our understanding of arsenite on diabetes development. https://doi.org/10.1289/EHP4517.

Racial and ethnic minorities are at higher risk for a variety of diseases. While sociodemographic and lifestyle factors contribute to racial/ethnic health disparities, the biological processes underlying these associations remain poorly understood. Stress and its biological consequences through the glucocorticoid receptor (GR) have been hypothesized to mediate adverse disease outcomes. In fasting morning samples of 503 control women from the San Francisco Bay Area Breast Cancer Study, we used a sensitive Chemical-Activated LUciferase gene eXpression (CALUX) assay to examine the association of sociodemographic and lifestyle factors with plasma glucocorticogenic (G) activity in three racial/ethnic groups. The G activity is a sensitive measure that reflects biological activity of total plasma glucocorticoids including cortisol and glucocorticoid-like compounds. Associations between G activity and sociodemographic and lifestyle factors were examined using multivariable linear regression models. Latina and non-Latina Black (NLB) women had 9% (P = 0.053) and 14% (P = 0.008) lower morning G activity than non-Latina White (NLW) women, respectively. Additionally, we replicated a previously reported association between G activity and alcohol intake (women who drank >10gms had 19% higher G activity than non-drinkers, P = 0.004) in Latina and NLB women. Further research should assess the association between G activity and health outcomes in a prospective cohort so as to characterize the relationship between total plasma G activity in pre-disease state and disease outcomes across different racial/ethnic populations.

Endocrine-disrupting chemicals (EDCs) are exogenous chemicals that interfere with hormone action, thereby increasing the risk of adverse health outcomes, including cancer, reproductive impairment, cognitive deficits and obesity. A complex literature of mechanistic studies provides evidence on the hazards of EDC exposure, yet there is no widely accepted systematic method to integrate these data to help identify EDC hazards. Inspired by work to improve hazard identification of carcinogens using key characteristics (KCs), we have developed ten KCs of EDCs based on our knowledge of hormone actions and EDC effects. In this Expert Consensus Statement, we describe the logic by which these KCs are identified and the assays that could be used to assess several of these KCs. We reflect on how these ten KCs can be used to identify, organize and utilize mechanistic data when evaluating chemicals as EDCs, and we use diethylstilbestrol, bisphenol A and perchlorate as examples to illustrate this approach.

Persistent organic pollutants (POPs), such as dichlorodiphenyltrichloroethane (DDT) and other organochlorine compounds, are abundant in the environment and in foodstuffs from the Indian subcontinent. These environmental contaminants have been associated with a higher risk of diabetes in numerous studies. Asian Indians are well known to have a high risk of diabetes compared with other populations, and this risk is also found in migrant populations of Asian Indians in the United States, Europe, and elsewhere. We hypothesized that high plasma concentrations of POPs in Asian Indian migrants are linked to a variety of diabetes-related pathologies and explored the mechanism for the induction of these effects. We measured 30 environmental pollutants in plasma samples obtained from 147 participants in the Metabolic syndrome and Atherosclerosis in South Asians Living in America pilot study using a gas chromatography-tandem mass spectrometry analytical method that uses less than 0.5 mL of plasma. We found that plasma levels of o,p'-DDT and p,p'-DDT were independently associated with both body mass index (BMI) and waist circumference. Doubling the levels of the sums of these DDTs was associated with insulin insensitivity (-0.38 Matsuda index, p = 0.001), increased adiposity (1.26 kg/m2 BMI and 3.58 cm waist circumference increase, p < 0.0001), circulating insulin (12.9 mIU/L, p = 0.002), hepatic fat (-0.051 HU, p = 0.001), as well as increased odds of obesity (OR = 2.17, p < 0.001, BMI-based; OR = 2.37, p = 0.001, waist-based), prediabetes (OR = 1.55, p = 0.02), diabetes (OR = 1.72, p = 0.01), and fatty liver (OR = 1.66, p = 0.01) in multivariable models accounting for confounding by age, sex, years in the US, education, and fish protein. Furthermore, levels of DDTs were associated with increased hepatic fat and circulating insulin, independent of obesity and confounders. These findings suggest that exposure to DDTs may contribute to the risk of metabolic disease among Asian Indians by affecting hepatic fat levels independent of obesity.

Human exposure to trichloroethylene (TCE) is linked to kidney cancer, autoimmune diseases, and probably non-Hodgkin lymphoma. Additionally, TCE exposed mice and cell cultures show altered DNA methylation. To evaluate associations between TCE exposure and DNA methylation in humans, we conducted an epigenome-wide association study (EWAS) in TCE exposed workers using the HumanMethylation450 BeadChip. Across individual CpG probes, genomic regions, and globally (i.e., the 450K methylome), we investigated differences in mean DNA methylation and differences in variability of DNA methylation between 73 control (< 0.005 ppm TCE), 30 lower exposed (< 10 ppm TCE), and 37 higher exposed ( ≥ 10 ppm TCE) subjects' white blood cells. We found that TCE exposure increased methylation variation globally (Kruskal-Wallis p-value = 3.75e-3) and in 25 CpG sites at a genome-wide significance level (Bonferroni p-value < 0.05). We identified a 609 basepair region in the TRIM68 gene promoter that exhibited hypomethylation with increased exposure to TCE (FWER = 1.20e-2). Also, genes that matched to differentially variable CpGs were enriched in the 'focal adhesion' biological pathway (p-value = 2.80e-2). All in all, human exposure to TCE was associated with epigenetic alterations in genes involved in cell-matrix adhesions and interferon subtype expression, which are important in the development of autoimmune diseases; and in genes related to cancer development. These results suggest that DNA methylation may play a role in the pathogenesis of TCE exposure-related diseases and that TCE exposure may contribute to epigenetic drift.

Androgen receptor (AR) is a steroid hormone nuclear receptor which upon binding its endogenous androgenic ligands (agonists), testosterone and dihydrotestosterone (DHT), alters gene transcription, producing a diverse range of biological effects. Antiandrogens, such as the pharmaceuticals bicalutamide and hydroxyflutamide, act as agonists in the absence of androgens and as antagonists in their presence or in high concentration. The atomic level mechanism of action by agonists and antagonists of AR is less well characterized. Therefore, in this study, multiple 1 μs molecular dynamics (MD), docking simulations, and perturbation-response analyses were performed to more fully explore the nature of interaction between agonist or antagonist and AR and the conformational changes induced in the AR upon interaction with different ligands. We characterized the mechanism of the ligand entry/exit and found that helix-12 and nearby structural motifs respond dynamically in that process. Modeling showed that the agonist and antagonist/agonist form a hydrogen bond with Thr877/Asn705 and that this interaction is absent for antagonists. Agonist binding to AR increases the mobility of residues at allosteric sites and coactivator binding sites, while antagonist binding decreases mobility at these important sites. A new site was also identified as a potential surface for allosteric binding. These results shed light on the effect of agonists and antagonists on the structure and dynamics of AR.

Background: The developing fetus is particularly vulnerable to the effects of endocrine disrupting chemicals (EDCs). Molecular fingerprints of EDCs can be identified via microRNA (miRNA) expression profiles and may be etiologically implicated in the developmental origin of disease (DOHaD). Methods/design: This pilot study includes pregnant women at high risk (smoking at conception), and low risk (non-smoking at conception) for SGA birth (birthweight

BackgroundIdentification of female reproductive toxicants is currently based largely on integrated epidemiological and in vivo toxicology data and, to a lesser degree, on mechanistic data. A uniform approach to systematically search, organize, integrate, and evaluate mechanistic evidence of female reproductive toxicity from various data types is lacking.ObjectiveWe sought to apply a key characteristics approach similar to that pioneered for carcinogen hazard identification to female reproductive toxicant hazard identification.MethodsA working group of international experts was convened to discuss mechanisms associated with chemical-induced female reproductive toxicity and identified 10 key characteristics of chemicals that cause female reproductive toxicity: 1) alters hormone receptor signaling; alters reproductive hormone production, secretion, or metabolism; 2) chemical or metabolite is genotoxic; 3) induces epigenetic alterations; 4) causes mitochondrial dysfunction; 5) induces oxidative stress; 6) alters immune function; 7) alters cell signal transduction; 8) alters direct cell–cell interactions; 9) alters survival, proliferation, cell death, or metabolic pathways; and 10) alters microtubules and associated structures. As proof of principle, cyclophosphamide and diethylstilbestrol (DES), for which both human and animal studies have demonstrated female reproductive toxicity, display at least 5 and 3 key characteristics, respectively. 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), for which the epidemiological evidence is mixed, exhibits 5 key characteristics.DiscussionFuture efforts should focus on evaluating the proposed key characteristics against additional known and suspected female reproductive toxicants. Chemicals that exhibit one or more of the key characteristics could be prioritized for additional evaluation and testing. A key characteristics approach has the potential to integrate with pathway-based toxicity testing to improve prediction of female reproductive toxicity in chemicals and potentially prevent some toxicants from entering common use. https://doi.org/10.1289/EHP4971.

ObjectiveEvaluate whether arsenic-related diabetes risks differ between people of low and high socioeconomic status (SES).MethodsWe used data collected between October 2007-December 2010 from a population-based cancer case-control study (N = 1301) in Northern Chile, an area with high arsenic water concentrations (>800 µg/L) and comprehensive records of past exposure. Information on lifetime exposure and potential confounders were obtained using structured interviews, questionnaires, and residential histories. Type 2 diabetes was defined as physician-diagnosed diabetes or oral hypoglycemic medication use. SES was measured using a 14-point scale based on ownership of household appliances, cars, internet access, or use of domestic help. Logistic regression was used to assess the relationship between arsenic and diabetes within strata of SES.ResultsAmong those with low SES, the odds ratio (OR) for diabetes comparing individuals in the highest to lowest tertile of lifetime average arsenic exposure was 2.12 (95% confidence interval (CI) 1.29-3.49, p = 0.004). However, those in the high SES group were not at increased risk (OR = 1.12 [95% CI = 0.72-1.73]).ConclusionsOur findings provide evidence that risks of arsenic-related diabetes may be higher in Chile in people with low versus high SES.

Estrogens play a significant role in breast cancer development and are not only produced endogenously, but are also mimicked by estrogen-like compounds from environmental exposures. We evaluated associations between estrogenic (E) activity, demographic factors and breast cancer risk factors in Non-Latina Black (NLB), Non-Latina White (NLW), and Latina women. We examined the association between E activity and Indigenous American (IA) ancestry in Latina women. Total E activity was measured with a bioassay in plasma samples of 503 women who served as controls in the San Francisco Bay Area Breast Cancer Study. In the univariate model that included all women with race/ethnicity as the independent predictor, Latinas had 13% lower E activity (p = 0.239) and NLBs had 35% higher activity (p = 0.04) compared to NLWs. In the multivariable model that adjusted for demographic factors, Latinas continued to show lower E activity levels (26%, p = 0.026), but the difference between NLBs and NLWs was no longer statistically significant (p = 0.431). An inverse association was observed between E activity and IA ancestry among Latina women (50% lower in 0% vs. 100% European ancestry, p = 0.027) consistent with our previously reported association between IA ancestry and breast cancer risk. These findings suggest that endogenous estrogens and exogenous estrogen-like compounds that act on the estrogen receptor and modulate E activity may partially explain racial/ethnic differences in breast cancer risk.

BackgroundThe prevalence of type 2 diabetes (T2D) has nearly doubled since 1980. Elevated body mass index (BMI) is the leading risk factor for T2D, mediated by inflammation and oxidative stress. Arsenic shares similar pathogenic processes, and may contribute to hyperglycemia and β-cell dysfunction.ObjectivesWe assessed a unique situation of individuals living in Northern Chile with data on lifetime arsenic exposure to evaluate the relationship between arsenic and T2D, and investigate possible interactions with BMI.MethodsWe analyzed data collected from October 2007-December 2010 from an arsenic-cancer case-control study. Information on self-reported weight, height, smoking, diet, and other factors were obtained. Diabetes was defined by self-reported physician-diagnoses or use of hypoglycemic medication. A total of 1053 individuals, 234 diabetics and 819 without known diabetes were included.ResultsThe T2D odds ratio (OR) for cumulative arsenic exposures of 610-5279 and ≥ 5280 μg/L-years occurring 40 years or more before interview were 0.97 (95% CI: 0.66-1.43) and 1.53 (95% CI: 1.05-2.23), respectively. Arsenic-associated T2D ORs were greater in subjects with increased BMIs. For example, the ORs for past cumulative exposures ≥ 5280 μg/L-years was 1.45 (95% CI: 0.74-2.84) in participants with BMIs

ObjectiveRates of diabetes mellitus are higher in South Asians than in other populations and persist after migration. One unexplored cause may be higher exposure to persistent organic pollutants associated with diabetes in other populations. We compared organochlorine (OC) pesticide concentrations in South Asian immigrants and European whites to determine whether the disease was positively associated with OC pesticides in South Asians.Research design and methodsSouth Asians of Tamil or Telugu descent (n = 120) and European whites (n = 72) were recruited into the London Life Sciences Population Study cohort. Blood samples as well as biometric, clinical, and survey data were collected. Plasma levels of p,p'-dichlorodiphenyldichloroethylene (DDE), p,p'- dichlorodiphenyltrichloroethane, β-hexachlorohexane (HCH), and polychlorinated biphenyl-118 were analyzed by gas chromatography-mass spectrometry. South Asian cases and controls were categorized by binary exposure (above vs below the 50th percentile) to perform logistic regression.ResultsTamils had approximately threefold to ninefold higher levels of OC pesticides, and Telugus had ninefold to 30-fold higher levels compared with European whites. The odds of exposure to p,p'-DDE above the 50th percentile was significantly greater in South Asian diabetes cases than in controls (OR: 7.00; 95% CI: 2.22, 22.06). The odds of exposure to β-HCH above the 50th percentile was significantly greater in the Tamil cases than in controls (OR: 9.35; 95% CI: 2.43, 35.97).ConclusionsSouth Asian immigrants have a higher body burden of OC pesticides than European whites. Diabetes mellitus is associated with higher p,p'-DDE and β-HCH concentrations in this population. Additional longitudinal studies of South Asian populations should be performed.

Research on disease causation often attempts to isolate the effects of individual factors, including individual genes or environmental factors. This reductionist approach has generated many discoveries, but misses important interactive and cumulative effects that may help explain the broad range of variability in disease occurrence observed across studies and individuals. A disease rarely results from a single factor, and instead results from a broader combination of factors, characterized here as intrinsic (I) and extrinsic (E) factors. Intrinsic vulnerability or resilience emanates from a variety of both fixed and shifting biological factors including genetic traits, while extrinsic factors comprise all biologically-relevant external stressors encountered across the lifespan. The I×E concept incorporates the multi-factorial and dynamic nature of health and disease and provides a unified, conceptual basis for integrating results from multiple areas of research, including genomics, G×E, developmental origins of health and disease, and the exposome. We describe the utility of the I×E concept to better understand and characterize the cumulative impact of multiple extrinsic and intrinsic factors on individual and population health. New research methods increasingly facilitate the measurement of multifactorial and interactive effects in epidemiological and toxicological studies. Tiered or indicator-based approaches can guide the selection of potentially relevant I and E factors for study and quantification, and exposomics methods may eventually produce results that can be used to generate a response function over the life course. Quantitative data on I×E interactive effects should generate a better understanding of the variability in human response to environmental factors. The proposed I×E concept highlights the role for broader study design in order to identify extrinsic and intrinsic factors amenable to interventions at the individual and population levels in order to enhance resilience, reduce vulnerability and improve health.

BackgroundPreviously, using microarrays and mRNA-Sequencing (mRNA-Seq) we found that occupational exposure to a range of benzene levels perturbed gene expression in peripheral blood mononuclear cells.ObjectivesIn the current study, we sought to identify gene expression biomarkers predictive of benzene exposure below 1 part per million (ppm), the occupational standard in the U.S.MethodsFirst, we used the nCounter platform to validate altered expression of 30 genes in 33 unexposed controls and 57 subjects exposed to benzene (0.7, p0.9 (p

Inter-individual differences in arsenic metabolism have been linked to arsenic-related disease risks. Arsenic (+3) methyltransferase (AS3MT) is the primary enzyme involved in arsenic metabolism, and we previously demonstrated in vitro that N-6 adenine-specific DNA methyltransferase 1 (N6AMT1) also methylates the toxic inorganic arsenic (iAs) metabolite, monomethylarsonous acid (MMA), to the less toxic dimethylarsonic acid (DMA). Here, we evaluated whether AS3MT and N6AMT1 gene polymorphisms alter arsenic methylation and impact iAs-related cancer risks. We assessed AS3MT and N6AMT1 polymorphisms and urinary arsenic metabolites (%iAs, %MMA, %DMA) in 722 subjects from an arsenic-cancer case-control study in a uniquely exposed area in northern Chile. Polymorphisms were genotyped using a custom designed multiplex, ligation-dependent probe amplification (MLPA) assay for 6 AS3MT SNPs and 14 tag SNPs in the N6AMT1 gene. We found several AS3MT polymorphisms associated with both urinary arsenic metabolite profiles and cancer risk. For example, compared to wildtypes, individuals carrying minor alleles in AS3MT rs3740393 had lower %MMA (mean difference = -1.9%, 95% CI: -3.3, -0.4), higher %DMA (mean difference = 4.0%, 95% CI: 1.5, 6.5), and lower odds ratios for bladder (OR = 0.3; 95% CI: 0.1-0.6) and lung cancer (OR = 0.6; 95% CI: 0.2-1.1). Evidence of interaction was also observed for both lung and bladder cancer between these polymorphisms and elevated historical arsenic exposures. Clear associations were not seen for N6AMT1. These results are the first to demonstrate a direct association between AS3MT polymorphisms and arsenic-related internal cancer risk. This research could help identify subpopulations that are particularly vulnerable to arsenic-related disease. Environ. Mol. Mutagen. 58:411-422, 2017. © 2017 Wiley Periodicals, Inc.

2,4-Dichlorophenoxyacetic acid (2,4-D) is one of the most commonly used selective herbicides in the world. A number of epidemiology studies have found an association between 2,4-D exposure and non-Hodgkin lymphoma (NHL) but these results are inconsistent and controversial. A previous meta-analysis found no clear association overall but did not specifically examine high-exposure groups. We conducted a systematic review and meta-analysis of the peer-reviewed epidemiologic studies of the associations between 2,4-D and NHL, with a particular focus on high-exposure groups, and evaluations of heterogeneity, dose-response, and bias. A total of 12 observational studies, 11 case-control studies, and one cohort study, were included. The summary relative risk for NHL using study results comparing subjects who were ever versus never exposed to 2,4-D was 1.38 (95% confidence interval (CI), 1.07-1.77). However, in analyses focusing on results from highly exposed groups, the summary relative risk for NHL was 1.73 (95% CI, 1.10-2.72). No clear bias based on study design, exposure assessment methodology, or outcome misclassification was seen. Overall, these findings provide new evidence for an association between NHL and exposure to the herbicide 2,4-D.

Benzene, formaldehyde (FA) and trichloroethylene (TCE) are ubiquitous chemicals in workplaces and the general environment. Benzene is an established myeloid leukemogen and probable lymphomagen. FA is classified as a myeloid leukemogen but has not been associated with non-Hodgkin lymphoma (NHL), whereas TCE has been associated with NHL but not myeloid leukemia. Epidemiologic associations between FA and myeloid leukemia, and between benzene, TCE and NHL are, however, still debated. Previously, we showed that these chemicals are associated with hematotoxicity in cross-sectional studies of factory workers in China, which included extensive personal monitoring and biological sample collection. Here, we compare and contrast patterns of hematotoxicity, monosomy 7 in myeloid progenitor cells (MPCs), and B-cell activation biomarkers across these studies to further evaluate possible mechanisms of action and consistency of effects with observed hematologic cancer risks. Workers exposed to benzene or FA, but not TCE, showed declines in cell types derived from MPCs, including granulocytes and platelets. Alterations in lymphoid cell types, including B cells and CD4+ T cells, and B-cell activation markers were apparent in workers exposed to benzene or TCE. Given that alterations in myeloid and lymphoid cell types are associated with hematological malignancies, our data provide biologic insight into the epidemiological evidence linking benzene and FA exposure with myeloid leukemia risk, and TCE and benzene exposure with NHL risk.

Though current functional genomic screening systems are useful for investigating human susceptibility to chemical toxicity, they have limitations. Well-established, high-throughput yeast mutant screens identify only evolutionarily conserved processes. RNA interference can be applied in human cells but is limited by incomplete gene knockout and off-target effects. Human haploid cell screening is advantageous as it requires knockdown of only a single copy of each gene. A human haploid cell mutant library (KBM7-Mu), derived from a chronic myeloid leukemia (CML) patient, was recently developed and has been used to identify genes that modulate sensitivity to infectious agents and pharmaceutical drugs. Here, we sought to improve the KBM7-Mu screening process to enable efficient screening of environmental chemicals. We developed a semi-solid medium based screening approach that cultures individual mutant colonies from chemically resistant cells, faster (by 2-3 weeks) and with less labor than the original liquid medium-based approach. As proof of principle, we identified genetic mutants that confer resistance to the carcinogen formaldehyde (FA, 12 genes, 18 hits) and the CML chemotherapeutic agent imatinib (6 genes, 13 hits). Validation experiments conducted on KBM7 mutants lacking each of the 18 genes confirmed resistance of 6 FA mutants (CTC1, FCRLA, GOT1, LPR5, M1AP, and MAP2K5) and 1 imatinib-resistant mutant (LYRM9). Despite the improvements to the method, it remains technically challenging to limit false positive findings. Nonetheless, our findings demonstrate the broad applicability of this optimized haploid approach to screen toxic chemicals to identify novel susceptibility genes and gain insight into potential mechanisms of toxicity.

Evidence from a small number of studies suggests that longer telomere length measured in peripheral leukocytes is associated with an increased risk of non-Hodgkin lymphoma (NHL). However, these studies may be biased by reverse causation, confounded by unmeasured environmental exposures and might miss time points for which prospective telomere measurement would best reveal a relationship between telomere length and NHL risk. We performed an analysis of genetically inferred telomere length and NHL risk in a study of 10 102 NHL cases of the four most common B-cell histologic types and 9562 controls using a genetic risk score (GRS) comprising nine telomere length-associated single-nucleotide polymorphisms. This approach uses existing genotype data and estimates telomere length by weighing the number of telomere length-associated variant alleles an individual carries with the published change in kb of telomere length. The analysis of the telomere length GRS resulted in an association between longer telomere length and increased NHL risk [four B-cell histologic types combined; odds ratio (OR) = 1.49, 95% CI 1.22-1.82,P-value = 8.5 × 10(-5)]. Subtype-specific analyses indicated that chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL/SLL) was the principal NHL subtype contributing to this association (OR = 2.60, 95% CI 1.93-3.51,P-value = 4.0 × 10(-10)). Significant interactions were observed across strata of sex for CLL/SLL and marginal zone lymphoma subtypes as well as age for the follicular lymphoma subtype. Our results indicate that a genetic background that favors longer telomere length may increase NHL risk, particularly risk of CLL/SLL, and are consistent with earlier studies relating longer telomere length with increased NHL risk.

Under the exposome paradigm all nongenetic factors contributing to disease are considered to be 'environmental' including chemicals, drugs, infectious agents, and psychosocial stress. We can consider these collectively as environmental stressors. Exposomics is the comprehensive analysis of exposure to all environmental stressors and should yield a more thorough understanding of chronic disease development. We can operationalize exposomics by studying all the small molecules in the body and their influence on biological pathways that lead to impaired health. Here, we describe methods by which this may be achieved and discuss the application of exposomics to cumulative risk assessment in vulnerable populations. Since the goal of cumulative risk assessment is to analyze, characterize, and quantify the combined risks to health from exposures to multiple agents or stressors, it seems that exposomics is perfectly poised to advance this important area of environmental health science. We should therefore support development of tools for exposomic analysis and begin to engage impacted communities in participatory exposome research. A first step may be to apply exposomics to vulnerable populations already studied by more conventional cumulative risk approaches. We further propose that recent migrants, low socioeconomic groups with high environmental chemical exposures, and pregnant women should be high priority populations for study by exposomics. Moreover, exposomics allows us to study interactions between chronic stress and environmental chemicals that disrupt stress response pathways (i.e., 'stressogens'). Exploring the impact of early life exposures and maternal stress may be an interesting and accessible topic for investigation by exposomics using biobanked samples.

BackgroundElevated body mass index (BMI) is a risk factor for cardiovascular disease, diabetes, cancer, and other diseases. Inflammation or oxidative stress induced by high BMI may explain some of these effects. Millions of people drink arsenic-contaminated water worldwide, and ingested arsenic has also been associated with inflammation, oxidative stress, and cancer.ObjectivesTo assess the unique situation of people living in northern Chile exposed to high arsenic concentrations in drinking water and investigate interactions between arsenic and BMI, and associations with lung and bladder cancer risks.MethodsInformation on self-reported body mass index (BMI) at various life stages, smoking, diet, and lifetime arsenic exposure was collected from 532 cancer cases and 634 population-based controls.ResultsIn subjects with BMIs 800 µg/L were 1.00, 1.64 (95% CI, 1.19-2.27), and 3.12 (2.30-4.22). In subjects with BMIs ≥90th percentile in early adulthood, the corresponding ORs were higher: 1.00, 1.84 (0.75-4.52), and 9.37 (2.88-30.53), respectively (synergy index=4.05, 95% CI, 1.27-12.88). Arsenic-related cancer ORs >20 were seen in those with elevated BMIs in both early adulthood and in later life. Adjustments for smoking, diet, and other factors had little impact.ConclusionThese findings provide novel preliminary evidence supporting the notion that environmentally-related cancer risks may be markedly increased in people with elevated BMIs, especially in those with an elevated BMI in early-life.

BackgroundFormaldehyde has been classified as a human myeloid leukemogen. However, the mechanistic basis for this association is still debated.ObjectivesWe aimed to evaluate whether circulating immune/inflammation markers were altered in workers occupationally exposed to formaldehyde.MethodsUsing a multiplexed bead-based assay, we measured serum levels of 38 immune/inflammation markers in a cross-sectional study of 43 formaldehyde-exposed and 51 unexposed factory workers in Guangdong, China. Linear regression models adjusting for potential confounders were used to compare marker levels in exposed and unexposed workers.ResultsWe found significantly lower circulating levels of two markers among exposed factory workers compared with unexposed controls that remained significant after adjusting for potential confounders and multiple comparisons using a false discovery rate of 10%, including chemokine (C-X-C motif) ligand 11 (36.2 pg/ml in exposed versus 48.4 pg/ml in controls, P = 0.0008) and thymus and activation regulated chemokine (52.7 pg/ml in exposed versus 75.0 pg/ml in controls, P = 0.0028), suggesting immunosuppression among formaldehyde-exposed workers.ConclusionsOur findings are consistent with recently emerging understanding that immunosuppression might be associated with myeloid diseases. These findings, if replicated in a larger study, may provide insights into the mechanisms by which formaldehyde promotes leukemogenesis.

Benzene and formaldehyde (FA) are important industrial chemicals and environmental pollutants that cause leukemia by inducing DNA damage and chromosome aberrations in hematopoietic stem cells (HSC), the target cells for leukemia. Our previous studies showed that workers exposed to benzene and FA exhibit increased levels of aneuploidy in their blood cells. As centrosome amplification is a common phenomenon in human cancers, including leukemia, and is associated with aneuploidy in carcinogenesis, we hypothesized that benzene and FA would induce centrosome amplification in vitro. We treated human lymphoblastoid TK6 cells with a range of concentrations of hydroquinone (HQ, a benzene metabolite) or FA for 24 h, allowed the cells to recover in fresh medium for 24 h, and examined centrosome amplification; chromosomal gain, loss, and breakage; and cytotoxicity. We included melphalan and etoposide, chemotherapeutic drugs that cause therapy-related acute myeloid leukemia and that have been shown to induce centrosome amplification as well as chromosomal aneuploidy and breakage, as positive controls. Melphalan and etoposide induced centrosome amplification and chromosome gain and breakage in a dose-dependent manner, at cytotoxic concentrations. HQ, though cytotoxic, did not induce centrosome amplification or any chromosomal aberration. FA-induced centrosome amplification and cytotoxicity, but did not induce chromosomal aberrations. Our data suggest, for the first time, that centrosome amplification is a potential mechanism underlying FA-induced leukemogenesis, but not benzene-induced leukemogenesis, as mediated through HQ. Future studies are needed to delineate the mechanisms of centrosome amplification and its association with DNA damage, chromosomal aneuploidy and carcinogenesis, following exposure to FA.

Characterizing variability in the extent and nature of responses to environmental exposures is a critical aspect of human health risk assessment. Chemical toxicants act by many different mechanisms, however, and the genes involved in adverse outcome pathways (AOPs) and AOP networks are not yet characterized. Functional genomic approaches can reveal both toxicity pathways and susceptibility genes, through knockdown or knockout of all non-essential genes in a cell of interest, and identification of genes associated with a toxicity phenotype following toxicant exposure. Screening approaches in yeast and human near-haploid leukemic KBM7 cells have identified roles for genes and pathways involved in response to many toxicants but are limited by partial homology among yeast and human genes and limited relevance to normal diploid cells. RNA interference (RNAi) suppresses mRNA expression level but is limited by off-target effects (OTEs) and incomplete knockdown. The recently developed gene editing approach called clustered regularly interspaced short palindrome repeats-associated nuclease (CRISPR)-Cas9, can precisely knock-out most regions of the genome at the DNA level with fewer OTEs than RNAi, in multiple human cell types, thus overcoming the limitations of the other approaches. It has been used to identify genes involved in the response to chemical and microbial toxicants in several human cell types and could readily be extended to the systematic screening of large numbers of environmental chemicals. CRISPR-Cas9 can also repress and activate gene expression, including that of non-coding RNA, with near-saturation, thus offering the potential to more fully characterize AOPs and AOP networks. Finally, CRISPR-Cas9 can generate complex animal models in which to conduct preclinical toxicity testing at the level of individual genotypes or haplotypes. Therefore, CRISPR-Cas9 is a powerful and flexible functional genomic screening approach that can be harnessed to provide unprecedented mechanistic insight in the field of modern toxicology.

Autoimmune conditions and immune system-related genetic variations are associated with risk of non-Hodgkin lymphoma (NHL). In a pooled analysis of 8,692 NHL cases and 9,260 controls from 14 studies (1988-2007) within the International Lymphoma Epidemiology Consortium, we evaluated the interaction between immune system genetic variants and autoimmune conditions in NHL risk. We evaluated the immunity-related single nucleotide polymorphisms rs1800629 (tumor necrosis factor gene (TNF) G308A), rs1800890 (interleukin-10 gene (IL10) T3575A), rs6457327 (human leukocyte antigen gene (HLA) class I), rs10484561 (HLA class II), and rs2647012 (HLA class II)) and categorized autoimmune conditions as primarily mediated by B-cell or T-cell responses. We constructed unconditional logistic regression models to measure associations between autoimmune conditions and NHL with stratification by genotype. Autoimmune conditions mediated by B-cell responses were associated with increased NHL risk, specifically diffuse large B-cell lymphoma (odds ratio (OR) = 3.11, 95% confidence interval (CI): 2.25, 4.30) and marginal zone lymphoma (OR = 5.80, 95% CI: 3.82, 8.80); those mediated by T-cell responses were associated with peripheral T-cell lymphoma (OR = 2.14, 95% CI: 1.35, 3.38). In the presence of the rs1800629 AG/AA genotype, B-cell-mediated autoimmune conditions increased NHL risk (OR = 3.27, 95% CI: 2.07, 5.16; P-interaction = 0.03) in comparison with the GG genotype (OR = 1.82, 95% CI: 1.31, 2.53). This interaction was consistent across major B-cell NHL subtypes, including marginal zone lymphoma (P-interaction = 0.02) and follicular lymphoma (P-interaction = 0.04).