Scott S. Auerbach

A common MUC5B promoter polymorphism and pulmonary fibrosis.

BACKGROUND The mutations that have been implicated in pulmonary fibrosis account for only a small proportion of the population risk. METHODS Using a genomewide linkage scan, we detected linkage between idiopathic interstitial pneumonia and a 3.4-Mb region of chromosome 11p15 in 82 families. We then evaluated genetic variation in this region in gel-forming mucin genes expressed in the lung among 83 subjects with familial interstitial pneumonia, 492 subjects with idiopathic pulmonary fibrosis, and 322 controls. MUC5B expression was assessed in lung tissue. RESULTS Linkage and fine mapping were used to identify a region of interest on the p-terminus of chromosome 11 that included gel-forming mucin genes. The minor-allele of the single-nucleotide polymorphism (SNP) rs35705950, located 3 kb upstream of the MUC5B transcription start site, was present at a frequency of 34% among subjects with familial interstitial pneumonia, 38% among subjects with idiopathic pulmonary fibrosis, and 9% among controls (allelic association with familial interstitial pneumonia, P=1.2×10(-15); allelic association with idiopathic pulmonary fibrosis, P=2.5×10(-37)). The odds ratios for disease among subjects who were heterozygous and those who were homozygous for the minor allele of this SNP were 6.8 (95% confidence interval [CI], 3.9 to 12.0) and 20.8 (95% CI, 3.8 to 113.7), respectively, for familial interstitial pneumonia and 9.0 (95% CI, 6.2 to 13.1) and 21.8 (95% CI, 5.1 to 93.5), respectively, for idiopathic pulmonary fibrosis. MUC5B expression in the lung was 14.1 times as high in subjects who had idiopathic pulmonary fibrosis as in those who did not (P<0.001). The variant allele of rs35705950 was associated with up-regulation in MUC5B expression in the lung in unaffected subjects (expression was 37.4 times as high as in unaffected subjects homozygous for the wild-type allele, P<0.001). MUC5B protein was expressed in lesions of idiopathic pulmonary fibrosis. CONCLUSIONS A common polymorphism in the promoter of MUC5B is associated with familial interstitial pneumonia and idiopathic pulmonary fibrosis. Our findings suggest that dysregulated MUC5B expression in the lung may be involved in the pathogenesis of pulmonary fibrosis. (Funded by the National Heart, Lung, and Blood Institute and others.).

The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance

The concordance of RNA-sequencing (RNA-seq) with microarrays for genome-wide analysis of differential gene expression has not been rigorously assessed using a range of chemical treatment conditions. Here we use a comprehensive study design to generate Illumina RNA-seq and Affymetrix microarray data from the same liver samples of rats exposed in triplicate to varying degrees of perturbation by 27 chemicals representing multiple modes of action (MOAs). The cross-platform concordance in terms of differentially expressed genes (DEGs) or enriched pathways is linearly correlated with treatment effect size (R20.8). Furthermore, the concordance is also affected by transcript abundance and biological complexity of the MOA. RNA-seq outperforms microarray (93% versus 75%) in DEG verification as assessed by quantitative PCR, with the gain mainly due to its improved accuracy for low-abundance transcripts. Nonetheless, classifiers to predict MOAs perform similarly when developed using data from either platform. Therefore, the endpoint studied and its biological complexity, transcript abundance and the genomic application are important factors in transcriptomic research and for clinical and regulatory decision making.

Incorporating new technologies into toxicity testing and risk assessment: moving from 21st century vision to a data-driven framework.

Based on existing data and previous work, a series of studies is proposed as a basis toward a pragmatic early step in transforming toxicity testing. These studies were assembled into a data-driven framework that invokes successive tiers of testing with margin of exposure (MOE) as the primary metric. The first tier of the framework integrates data from high-throughput in vitro assays, in vitro-to-in vivo extrapolation (IVIVE) pharmacokinetic modeling, and exposure modeling. The in vitro assays are used to separate chemicals based on their relative selectivity in interacting with biological targets and identify the concentration at which these interactions occur. The IVIVE modeling converts in vitro concentrations into external dose for calculation of the point of departure (POD) and comparisons to human exposure estimates to yield a MOE. The second tier involves short-term in vivo studies, expanded pharmacokinetic evaluations, and refined human exposure estimates. The results from the second tier studies provide more accurate estimates of the POD and the MOE. The third tier contains the traditional animal studies currently used to assess chemical safety. In each tier, the POD for selective chemicals is based primarily on endpoints associated with a proposed mode of action, whereas the POD for nonselective chemicals is based on potential biological perturbation. Based on the MOE, a significant percentage of chemicals evaluated in the first 2 tiers could be eliminated from further testing. The framework provides a risk-based and animal-sparing approach to evaluate chemical safety, drawing broadly from previous experience but incorporating technological advances to increase efficiency.

Predicting the hepatocarcinogenic potential of alkenylbenzene flavoring agents using toxicogenomics and machine learning.

Identification of carcinogenic activity is the primary goal of the 2-year bioassay. The expense of these studies limits the number of chemicals that can be studied and therefore chemicals need to be prioritized based on a variety of parameters. We have developed an ensemble of support vector machine classification models based on male F344 rat liver gene expression following 2, 14 or 90 days of exposure to a collection of hepatocarcinogens (aflatoxin B1, 1-amino-2,4-dibromoanthraquinone, N-nitrosodimethylamine, methyleugenol) and non-hepatocarcinogens (acetaminophen, ascorbic acid, tryptophan). Seven models were generated based on individual exposure durations (2, 14 or 90 days) or a combination of exposures (2+14, 2+90, 14+90 and 2+14+90 days). All sets of data, with the exception of one yielded models with 0% cross-validation error. Independent validation of the models was performed using expression data from the liver of rats exposed at 2 dose levels to a collection of alkenylbenzene flavoring agents. Depending on the model used and the exposure duration of the test data, independent validation error rates ranged from 47% to 10%. The variable with the most notable effect on independent validation accuracy was exposure duration of the alkenylbenzene test data. All models generally exhibited improved performance as the exposure duration of the alkenylbenzene data increased. The models differentiated between hepatocarcinogenic (estragole and safrole) and non-hepatocarcinogenic (anethole, eugenol and isoeugenol) alkenylbenzenes previously studied in a carcinogenicity bioassay. In the case of safrole the models correctly differentiated between carcinogenic and non-carcinogenic dose levels. The models predict that two alkenylbenzenes not previously assessed in a carcinogenicity bioassay, myristicin and isosafrole, would be weakly hepatocarcinogenic if studied at a dose level of 2 mmol/kg bw/day for 2 years in male F344 rats; therefore suggesting that these chemicals should be a higher priority relative to other untested alkenylbenzenes for evaluation in the carcinogenicity bioassay. The results of the study indicate that gene expression-based predictive models are an effective tool for identifying hepatocarcinogens. Furthermore, we find that exposure duration is a critical variable in the success or failure of such an approach, particularly when evaluating chemicals with unknown carcinogenic potency.

Development and evaluation of a genomic signature for the prediction and mechanistic assessment of nongenotoxic hepatocarcinogens in the rat.

Evaluating the risk of chemical carcinogenesis has long been a challenge owing to the protracted nature of the pathology and the limited translatability of animal models. Although numerous short-term in vitro and in vivo assays have been developed, they have failed to reliably predict the carcinogenicity of nongenotoxic compounds. Extending upon previous microarray work (Fielden, M. R., Nie, A., McMillian, M., Elangbam, C. S., Trela, B. A., Yang, Y., Dunn, R. T., II, Dragan, Y., Fransson-Stehen, R., Bogdanffy, M., et al. (2008). Interlaboratory evaluation of genomic signatures for predicting carcinogenicity in the rat. Toxicol. Sci. 103, 28-34), we have developed and extensively evaluated a quantitative PCR-based signature to predict the potential for nongenotoxic compounds to induce liver tumors in the rat as a first step in the safety assessment of potential nongenotoxic carcinogens. The training set was derived from liver RNA from rats treated with 72 compounds and used to develop a 22-gene signature on the TaqMan array platform, providing an economical and standardized assay protocol. Independent testing on over 900 diverse samples (66 compounds) confirmed the interlaboratory precision of the assay and its ability to predict known nongenotoxic hepatocarcinogens (NGHCs). When tested under different experimental designs, strains, time points, dose setting criteria, and other preanalytical processes, the signature sensitivity and specificity was estimated to be 67% (95% confidence interval [CI] = 38-88%) and 59% (95% CI = 44-72%), respectively, with an area under the receiver operating characteristic curve of 0.65 (95% CI = 0.46-0.83%). Compounds were best classified using expression data from short-term repeat dose studies; however, the prognostic expression changes appeared to be preserved after longer term treatment. Exploratory evaluations also revealed that different modes of action for nongenotoxic and genotoxic compounds can be discriminated based on the expression of specific genes. These results support a potential early preclinical testing paradigm to catalyze broader understanding of putative NGHCs.

CAR2 Displays Unique Ligand Binding and RXRα Heterodimerization Characteristics

The constitutive androstane receptor (CAR; NR1I3) regulates the expression of genes involved in xenobiotic metabolism. Alternative splicing of the human CAR gene yields an array of mRNAs that encode structurally diverse proteins. One form of CAR, termed CAR2, contains an additional four amino acids (SPTV) that are predicted to reshape the ligand-binding pocket. The current studies show a marked, ligand-independent, CAR2-mediated transactivation of reporters containing optimal DR-3, DR-4, and DR-5 response elements, and reporters derived from the natural CYP2B6 and CYP3A4 gene promoters. Overexpression of the RXRα ligand binding domain was critical for achieving these effects. CAR2 interaction with SRC-1 was similarly dependent on the coexpression of RXRα. Mutagenesis of Ser233 (SPTV) to an alanine residue yielded a receptor possessing higher constitutive activity. Alternatively, mutating Ser233 to an aspartate residue drastically reduced the transactivation capacity of CAR2. The respective abilities of these mutagenized forms of CAR2 to transactivate a DR-4 × 3 reporter element correlated with their ability to interact with RxRα and to recruit SRC-1 in a ligand-regulated manner. Together, these results demonstrate a robust RXRα-dependent recruitment of coactivators and transactivation by CAR2. In addition, CAR2 displays novel dose responses to clotrimazole and androstanol compared with the reference form of the receptor while at the same time retaining the ability to bind CITCO. This result supports a hypothesis whereby the four-amino-acid insertion in CAR2 structurally modifies its ligand binding pocket, suggesting that CAR2 is regulated by a set of ligands distinct from those governing the activity of reference CAR.

RNA-Seq Profiling Reveals Novel Hepatic Gene Expression Pattern in Aflatoxin B1 Treated Rats

Deep sequencing was used to investigate the subchronic effects of 1 ppm aflatoxin B1 (AFB1), a potent hepatocarcinogen, on the male rat liver transcriptome prior to onset of histopathological lesions or tumors. We hypothesized RNA-Seq would reveal more differentially expressed genes (DEG) than microarray analysis, including low copy and novel transcripts related to AFB1’s carcinogenic activity compared to feed controls (CTRL). Paired-end reads were mapped to the rat genome (Rn4) with TopHat and further analyzed by DESeq and Cufflinks-Cuffdiff pipelines to identify differentially expressed transcripts, new exons and unannotated transcripts. PCA and cluster analysis of DEGs showed clear separation between AFB1 and CTRL treatments and concordance among group replicates. qPCR of eight high and medium DEGs and three low DEGs showed good comparability among RNA-Seq and microarray transcripts. DESeq analysis identified 1,026 differentially expressed transcripts at greater than two-fold change (p<0.005) compared to 626 transcripts by microarray due to base pair resolution of transcripts by RNA-Seq, probe placement within transcripts or an absence of probes to detect novel transcripts, splice variants and exons. Pathway analysis among DEGs revealed signaling of Ahr, Nrf2, GSH, xenobiotic, cell cycle, extracellular matrix, and cell differentiation networks consistent with pathways leading to AFB1 carcinogenesis, including almost 200 upregulated transcripts controlled by E2f1-related pathways related to kinetochore structure, mitotic spindle assembly and tissue remodeling. We report 49 novel, differentially-expressed transcripts including confirmation by PCR-cloning of two unique, unannotated, hepatic AFB1-responsive transcripts (HAfT’s) on chromosomes 1.q55 and 15.q11, overexpressed by 10 to 25-fold. Several potentially novel exons were found and exon refinements were made including AFB1 exon-specific induction of homologous family members, Ugt1a6 and Ugt1a7c. We find the rat transcriptome contains many previously unidentified, AFB1-responsive exons and transcripts supporting RNA-Seq’s capabilities to provide new insights into AFB1-mediated gene expression leading to hepatocellular carcinoma.

Global Gene Profiling of Spontaneous Hepatocellular Carcinoma in B6C3F1 Mice: Similarities in the Molecular Landscape with Human Liver Cancer

Hepatocellular carcinoma (HCC) is an important cause of morbidity and mortality worldwide. Although the risk factors of human HCC are well known, the molecular pathogenesis of this disease is complex, and in general, treatment options remain poor. The use of rodent models to study human cancer has been extensively pursued, both through genetically engineered rodents and rodent models used in carcinogenicity and toxicology studies. In particular, the B6C3F1 mouse used in the National Toxicology Program (NTP) two-year bioassay has been used to evaluate the carcinogenic effects of environmental and occupational chemicals, and other compounds. The high incidence of spontaneous HCC in the B6C3F1 mouse has challenged its use as a model for chemically induced HCC in terms of relevance to the human disease. Using global gene expression profiling, we identify the dysregulation of several mediators similarly altered in human HCC, including re-expression of fetal oncogenes, upregulation of protooncogenes, downregulation of tumor suppressor genes, and abnormal expression of cell cycle mediators, growth factors, apoptosis regulators, and angiogenesis and extracellular matrix remodeling factors. Although major differences in etiology and pathogenesis remain between human and mouse HCC, there are important similarities in global gene expression and molecular pathways dysregulated in mouse and human HCC. These data provide further support for the use of this model in hazard identification of compounds with potential human carcinogenicity risk, and may help in better understanding the mechanisms of tumorigenesis resulting from chemical exposure in the NTP two-year carcinogenicity bioassay.

A Quantitative Approach to Screen for Nephrotoxic Compounds In Vitro

Nephrotoxicity due to drugs and environmental chemicals accounts for significant patient mortality and morbidity, but there is no high throughput in vitro method for predictive nephrotoxicity assessment. We show that primary human proximal tubular epithelial cells (HPTECs) possess characteristics of differentiated epithelial cells rendering them desirable to use in such in vitro systems. To identify a reliable biomarker of nephrotoxicity, we conducted multiplexed gene expression profiling of HPTECs after exposure to six different concentrations of nine human nephrotoxicants. Only overexpression of the gene encoding heme oxygenase-1 (HO-1) significantly correlated with increasing dose for six of the compounds, and significant HO-1 protein deregulation was confirmed with each of the nine nephrotoxicants. Translatability of HO-1 increase across species and platforms was demonstrated by computationally mining two large rat toxicogenomic databases for kidney tubular toxicity and by observing a significant increase in HO-1 after toxicity using an ex vivo three-dimensional microphysiologic system (kidney-on-a-chip). The predictive potential of HO-1 was tested using an additional panel of 39 mechanistically distinct nephrotoxic compounds. Although HO-1 performed better (area under the curve receiver-operator characteristic curve [AUC-ROC]=0.89) than traditional endpoints of cell viability (AUC-ROC for ATP=0.78; AUC-ROC for cell count=0.88), the combination of HO-1 and cell count further improved the predictive ability (AUC-ROC=0.92). We also developed and optimized a homogenous time-resolved fluorescence assay to allow high throughput quantitative screening of nephrotoxic compounds using HO-1 as a sensitive biomarker. This cell-based approach may facilitate rapid assessment of potential nephrotoxic therapeutics and environmental chemicals.

The Importance of the Biological Impact of Exposure to the Concept of the Exposome

Background: The term “exposome” was originally coined in 2005 and defined as the totality of exposures throughout the lifetime. The exposome provides an excellent scientific framework for studying human health and disease. Recently, it has been suggested that how exposures affect our biology and how our bodies respond to such exposures should be part of the exposome. Objectives: The authors describe the biological impact of the exposome and outline many of the targets and processes that can be assessed as part of a comprehensive analysis of the exposome. Discussion: The processes that occur downstream from the initial interactions with exogenous and endogenous compounds determine the biological impact of exposures. If the effects are not considered in the same context as the exposures, it will be difficult to determine cause and effect. The exposome and biology are interactive—changes in biology due to the environment change one’s vulnerability to subsequent exposures. Additionally, highly resilient individuals are able to withstand environmental exposures with minimal effects to their health. We expect that the vast majority of exposures are transient, and chemicals underlying exposures that occurred weeks, months, or years ago are long gone from the body. However, these past chemical exposures often leave molecular fingerprints that may be able to provide information on these past exposures. Conclusions: Through linking exposures to specific biological responses, exposome research could serve to improve understanding of the mechanistic connections between exposures and health to help mitigate adverse health outcomes across the lifespan. Citation: Dennis KK, Auerbach SS, Balshaw DM, Cui Y, Fallin MD, Smith MT, Spira A, Sumner S, Miller GW. 2016. The importance of the biological impact of exposure to the concept of the exposome. Environ Health Perspect 124:1504–1510; http://dx.doi.org/10.1289/EHP140