@article{fleming_house_chappel_motsinger-reif_reif_2024, title={Guided optimization of ToxPi model weights using a Semi-Automated approach}, volume={29}, ISSN={["2468-1113"]}, DOI={10.1016/j.comtox.2023.100294}, abstractNote={The Toxicological Prioritization Index (ToxPi) is a visual analysis and decision support tool for dimension reduction and visualization of high throughput, multi-dimensional feature data. ToxPi was originally developed for assessing the relative toxicity of multiple chemicals or stressors by synthesizing complex toxicological data to provide a single comprehensive view of the potential health effects. It continues to be used for profiling chemicals and has since been applied to other types of “sample” entities, including geospatial (e.g. county-level Covid-19 risk and sites of historical PFAS exposure) and other profiling applications. For any set of features (data collected on a set of sample entities), ToxPi integrates the data into a set of weighted slices that provide a visual profile and a score metric for comparison. This scoring system is highly dependent on user-provided feature weights, yet users often lack knowledge of how to define these feature weights. Common methods for predicting feature weights are generally unusable due to inappropriate statistical assumptions and lack of global distributional expectation. However, users often have an inherent understanding of expected results for a small subset of samples. For example, in chemical toxicity, prior knowledge can often place subsets of chemicals into categories of low, moderate or high toxicity (reference chemicals). Ordinal regression can be used to predict weights based on these response levels that are applicable to the entire feature set, analogous to using positive and negative controls to contextualize an empirical distribution. We propose a semi-supervised method utilizing ordinal regression to predict a set of feature weights that produces the best fit for the known response (“reference”) data and subsequently fine-tunes the weights via a customized genetic algorithm. We conduct a simulation study to show when this method can improve the results of ordinal regression, allowing for accurate feature weight prediction and sample ranking in scenarios with minimal response data. To ground-truth the guided weight optimization, we test this method on published data to build a ToxPi model for comparison against expert-knowledge-driven weight assignments.}, journal={COMPUTATIONAL TOXICOLOGY}, author={Fleming, Jonathon F. and House, John S. and Chappel, Jessie R. and Motsinger-Reif, Alison A. and Reif, David M.}, year={2024}, month={Mar} }
 @article{kirkwood-donelson_chappel_tobin_dodds_reif_dewitt_baker_2024, title={Investigating mouse hepatic lipidome dysregulation following exposure to emerging per- and polyfluoroalkyl substances (PFAS)}, url={https://doi.org/10.1016/j.chemosphere.2024.141654}, DOI={10.1016/j.chemosphere.2024.141654}, abstractNote={Per- and polyfluoroalkyl substances (PFAS) are environmental pollutants that have been associated with adverse health effects including liver damage, decreased vaccine responses, cancer, developmental toxicity, thyroid dysfunction, and elevated cholesterol. The specific molecular mechanisms impacted by PFAS exposure to cause these health effects remain poorly understood, however there is some evidence of lipid dysregulation. Thus, lipidomic studies that go beyond clinical triglyceride and cholesterol tests are greatly needed to investigate these perturbations. Here, we have utilized a platform coupling liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) separations to simultaneously evaluate PFAS bioaccumulation and lipid metabolism disruptions. For the study, liver samples collected from C57BL/6 mice exposed to either of the emerging PFAS hexafluoropropylene oxide dimer acid (HFPO-DA or "GenX") or Nafion byproduct 2 (NBP2) were assessed. Sex-specific differences in PFAS accumulation and liver size were observed for both PFAS, in addition to disturbed hepatic liver lipidomic profiles. Interestingly, GenX resulted in less hepatic bioaccumulation than NBP2 yet gave a higher number of significantly altered lipids when compared to the control group, implying that the accumulation of substances in the liver may not be a reliable measure of the substance's capacity to disrupt the liver's natural metabolic processes. Specifically, phosphatidylglycerols, phosphatidylinositols, and various specific fatty acyls were greatly impacted, indicating alteration of inflammation, oxidative stress, and cellular signaling processes due to emerging PFAS exposure. Overall, these results provide valuable insight into the liver bioaccumulation and molecular mechanisms of GenX- and NBP2-induced hepatotoxicity.}, journal={Chemosphere}, author={Kirkwood-Donelson, Kaylie I. and Chappel, Jessie and Tobin, Emma and Dodds, James N. and Reif, David M. and DeWitt, Jamie C. and Baker, Erin S.}, year={2024}, month={Apr} }
 @article{chappel_king_fleming_eberlin_reif_baker_2023, title={Aggregated Molecular Phenotype Scores: Enhancing Assessment and Visualization of Mass Spectrometry Imaging Data for Tissue-Based Diagnostics}, volume={8}, ISSN={["1520-6882"]}, DOI={10.1021/acs.analchem.3c02389}, abstractNote={Mass spectrometry imaging (MSI) has gained increasing popularity for tissue-based diagnostics due to its ability to identify and visualize molecular characteristics unique to different phenotypes within heterogeneous samples. Data from MSI experiments are often assessed and visualized using various supervised and unsupervised statistical approaches. However, these approaches tend to fall short in identifying and concisely visualizing subtle, phenotype-relevant molecular changes. To address these shortcomings, we developed aggregated molecular phenotype (AMP) scores. AMP scores are generated using an ensemble machine learning approach to first select features differentiating phenotypes, weight the features using logistic regression, and combine the weights and feature abundances. AMP scores are then scaled between 0 and 1, with lower values generally corresponding to class 1 phenotypes (typically control) and higher scores relating to class 2 phenotypes. AMP scores, therefore, allow the evaluation of multiple features simultaneously and showcase the degree to which these features correlate with various phenotypes. Due to the ensembled approach, AMP scores are able to overcome limitations associated with individual models, leading to high diagnostic accuracy and interpretability. Here, AMP score performance was evaluated using metabolomic data collected from desorption electrospray ionization MSI. Initial comparisons of cancerous human tissues to their normal or benign counterparts illustrated that AMP scores distinguished phenotypes with high accuracy, sensitivity, and specificity. Furthermore, when combined with spatial coordinates, AMP scores allow visualization of tissue sections in one map with distinguished phenotypic borders, highlighting their diagnostic utility.}, journal={ANALYTICAL CHEMISTRY}, author={Chappel, Jessie R. and King, Mary E. and Fleming, Jonathon and Eberlin, Livia S. and Reif, David M. and Baker, Erin S.}, year={2023}, month={Aug} }
 @article{jin_dunson_rager_reif_engel_herring_2023, title={Bayesian matrix completion for hypothesis testing}, volume={3}, ISSN={["1467-9876"]}, url={https://doi.org/10.1093/jrsssc/qlac005}, DOI={10.1093/jrsssc/qlac005}, abstractNote={Abstract}, journal={JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS}, author={Jin, Bora and Dunson, David B. and Rager, Julia E. and Reif, David M. and Engel, Stephanie M. and Herring, Amy H.}, year={2023}, month={Mar} }
 @article{green_truong_thunga_leong_hancock_tanguay_reif_2023, title={Deep autoencoder-based behavioral pattern recognition outperforms standard statistical methods in high-dimensional zebrafish studies}, url={https://doi.org/10.1101/2023.09.13.557544}, DOI={10.1101/2023.09.13.557544}, abstractNote={Abstract}, author={Green, Adrian J. and Truong, Lisa and Thunga, Preethi and Leong, Connor and Hancock, Melody and Tanguay, Robyn L. and Reif, David M.}, year={2023}, month={Sep} }
 @article{wallis_kotlarz_knappe_collier_lea_reif_mccord_strynar_dewitt_hoppin_2023, title={Estimation of the Half-Lives of Recently Detected Per- and Polyfluorinated Alkyl Ethers in an Exposed Community}, volume={57}, ISSN={["1520-5851"]}, url={https://doi.org/10.1021/acs.est.2c08241}, DOI={10.1021/acs.est.2c08241}, abstractNote={To estimate half-lives for novel fluoroethers, the GenX Exposure Study obtained two serum measurements for per- and polyfluoroalkyl substances (PFAS) for 44 participants of age 12-86 years from North Carolina, collected 5 and 11 months after fluoroether discharges into the drinking water source were controlled. The estimated half-lives for these compounds were 127 days (95% confidence interval (95% CI) = 86, 243 days) for perfluorotetraoxadecanoic acid (PFO4DA), 296 days for Nafion byproduct 2 (95% CI = 176, 924 days), and 379 days (95% CI = 199, 3870 days) for perfluoro-3,5,7,9,11-pentaoxadodecanoic acid (PFO5DoA). Using these estimates and the literature values, a model was built that predicted PFAS half-lives using structural properties. Three chemical properties predicted 55% of the variance of PFAS half-lives based on 15 PFAS. A model with only molecular weight predicted 69% of the variance. Some properties can predict the half-lives of PFAS, but a deeper understanding is needed. These fluoroethers had biological half-lives longer than published half-lives for PFHxA and PFHpA (30-60 days) but shorter than those for PFOA and PFOS (800-1200 days). These are the first and possibly only estimates of human elimination half-lives of these fluoroethers.}, number={41}, journal={ENVIRONMENTAL SCIENCE & TECHNOLOGY}, author={Wallis, Dylan J. and Kotlarz, Nadine and Knappe, Detlef R. U. and Collier, David N. and Lea, C. Suzanne and Reif, David and McCord, James and Strynar, Mark and DeWitt, Jamie C. and Hoppin, Jane A.}, year={2023}, month={Oct}, pages={15348–15355} }
 @article{chappel_kirkwood-donelson_reif_baker_2023, title={From big data to big insights: statistical and bioinformatic approaches for exploring the lipidome}, volume={10}, ISSN={["1618-2650"]}, DOI={10.1007/s00216-023-04991-2}, journal={ANALYTICAL AND BIOANALYTICAL CHEMISTRY}, author={Chappel, Jessie R. and Kirkwood-Donelson, Kaylie I. and Reif, David M. and Baker, Erin S.}, year={2023}, month={Oct} }
 @article{phelps_palekar_conley_ferrero_driggers_linder_kullman_reif_sheats_dewitt_et al._2023, title={Legacy and emerging per- and polyfluoroalkyl substances suppress the neutrophil respiratory burst}, volume={20}, ISSN={["1547-6901"]}, url={https://doi.org/10.1080/1547691X.2023.2176953}, DOI={10.1080/1547691X.2023.2176953}, abstractNote={Abstract Per- and polyfluoroalkyl substances (PFASs) are used in a multitude of processes and products, including nonstick coatings, food wrappers, and fire-fighting foams. These chemicals are environmentally-persistent, ubiquitous, and can be detected in the serum of 98% of Americans. Despite evidence that PFASs alter adaptive immunity, few studies have investigated their effects on innate immunity. The report here presents results of studies that investigated the impact of nine environmentally-relevant PFASs [e.g. perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid potassium salt (PFOS-K), perfluorononanoic acid (PFNA), perfluorohexanoic acid (PFHxA), perfluorohexane sulfonic acid (PFHxS), perfluorobutane sulfonic acid (PFBS), ammonium perfluoro(2-methyl-3-oxahexanoate) (GenX), 7H-perfluoro-4-methyl-3,6-dioxa-octane sulfonic acid (Nafion byproduct 2), and perfluoromethoxyacetic acid sodium salt (PFMOAA-Na)] on one component of the innate immune response, the neutrophil respiratory burst. The respiratory burst is a key innate immune process by which microbicidal reactive oxygen species (ROS) are rapidly induced by neutrophils in response to pathogens; defects in the respiratory burst can increase susceptibility to infection. The study here utilized larval zebrafish, a human neutrophil-like cell line, and primary human neutrophils to ascertain whether PFAS exposure inhibits ROS production in the respiratory burst. It was observed that exposure to PFHxA and GenX suppresses the respiratory burst in zebrafish larvae and a human neutrophil-like cell line. GenX also suppressed the respiratory burst in primary human neutrophils. This report is the first to demonstrate that these PFASs suppress neutrophil function and support the utility of employing zebrafish larvae and a human cell line as screening tools to identify chemicals that may suppress human immune function.}, number={1}, journal={JOURNAL OF IMMUNOTOXICOLOGY}, author={Phelps, Drake W. and Palekar, Anika I. and Conley, Haleigh E. and Ferrero, Giuliano and Driggers, Jacob H. and Linder, Keith E. and Kullman, Seth W. and Reif, David M. and Sheats, M. Katie and DeWitt, Jamie C. and et al.}, year={2023}, month={Dec} }
 @article{gonzalez_small_green_akhtari_motsinger-reif_quintanilha_havener_reif_mcleod_wiltshire_2023, title={MKX-AS1 Gene Expression Associated with Variation in Drug Response to Oxaliplatin and Clinical Outcomes in Colorectal Cancer Patients}, volume={16}, ISSN={["1424-8247"]}, url={https://doi.org/10.3390/ph16050757}, DOI={10.3390/ph16050757}, abstractNote={Oxaliplatin (OXAL) is a commonly used chemotherapy for treating colorectal cancer (CRC). A recent genome wide association study (GWAS) showed that a genetic variant (rs11006706) in the lncRNA gene MKX-AS1 and partnered sense gene MKX could impact the response of genetically varied cell lines to OXAL treatment. This study found that the expression levels of MKX-AS1 and MKX in lymphocytes (LCLs) and CRC cell lines differed between the rs11006706 genotypes, indicating that this gene pair could play a role in OXAL response. Further analysis of patient survival data from the Cancer Genome Atlas (TCGA) and other sources showed that patients with high MKX-AS1 expression status had significantly worse overall survival (HR = 3.2; 95%CI = (1.17–9); p = 0.024) compared to cases with low MKX-AS1 expression status. Alternatively, high MKX expression status had significantly better overall survival (HR = 0.22; 95%CI = (0.07–0.7); p = 0.01) compared to cases with low MKX expression status. These results suggest an association between MKX-AS1 and MKX expression status that could be useful as a prognostic marker of response to OXAL and potential patient outcomes in CRC.}, number={5}, journal={PHARMACEUTICALS}, author={Gonzalez, Ricardo D. and Small, George W. and Green, Adrian J. and Akhtari, Farida S. and Motsinger-Reif, Alison A. and Quintanilha, Julia C. F. and Havener, Tammy M. and Reif, David M. and McLeod, Howard L. and Wiltshire, Tim}, year={2023}, month={May} }
 @article{small_akhtari_green_havener_sikes_quintanhila_gonzalez_reif_motsinger-reif_mcleod_et al._2023, title={Pharmacogenomic Analyses Implicate B Cell Developmental Status and MKL1 as Determinants of Sensitivity toward Anti-CD20 Monoclonal Antibody Therapy}, volume={12}, ISSN={["2073-4409"]}, url={https://doi.org/10.3390/cells12121574}, DOI={10.3390/cells12121574}, abstractNote={Monoclonal antibody (mAb) therapy directed against CD20 is an important tool in the treatment of B cell disorders. However, variable patient response and acquired resistance remain important clinical challenges. To identify genetic factors that may influence sensitivity to treatment, the cytotoxic activity of three CD20 mAbs: rituximab; ofatumumab; and obinutuzumab, were screened in high-throughput assays using 680 ethnically diverse lymphoblastoid cell lines (LCLs) followed by a pharmacogenomic assessment. GWAS analysis identified several novel gene candidates. The most significant SNP, rs58600101, in the gene MKL1 displayed ethnic stratification, with the variant being significantly more prevalent in the African cohort and resulting in reduced transcript levels as measured by qPCR. Functional validation of MKL1 by shRNA-mediated knockdown of MKL1 resulted in a more resistant phenotype. Gene expression analysis identified the developmentally associated TGFB1I1 as the most significant gene associated with sensitivity. qPCR among a panel of sensitive and resistant LCLs revealed immunoglobulin class-switching as well as differences in the expression of B cell activation markers. Flow cytometry showed heterogeneity within some cell lines relative to surface Ig isotype with a shift to more IgG+ cells among the resistant lines. Pretreatment with prednisolone could partly reverse the resistant phenotype. Results suggest that the efficacy of anti-CD20 mAb therapy may be influenced by B cell developmental status as well as polymorphism in the MKL1 gene. A clinical benefit may be achieved by pretreatment with corticosteroids such as prednisolone followed by mAb therapy.}, number={12}, journal={CELLS}, author={Small, George W. and Akhtari, Farida S. and Green, Adrian J. and Havener, Tammy M. and Sikes, Michael and Quintanhila, Julia and Gonzalez, Ricardo D. and Reif, David M. and Motsinger-Reif, Alison A. and McLeod, Howard L. and et al.}, year={2023}, month={Jun} }
 @article{gonzalez_small_green_akhtari_havener_quintanilha_cipriani_reif_mcleod_motsinger-reif_et al._2023, title={RYK Gene Expression Associated with Drug Response Variation of Temozolomide and Clinical Outcomes in Glioma Patients}, volume={16}, ISSN={["1424-8247"]}, url={https://doi.org/10.3390/ph16050726}, DOI={10.3390/ph16050726}, abstractNote={Temozolomide (TMZ) chemotherapy is an important tool in the treatment of glioma brain tumors. However, variable patient response and chemo-resistance remain exceptionally challenging. Our previous genome-wide association study (GWAS) identified a suggestively significant association of SNP rs4470517 in the RYK (receptor-like kinase) gene with TMZ drug response. Functional validation of RYK using lymphocytes and glioma cell lines resulted in gene expression analysis indicating differences in expression status between genotypes of the cell lines and TMZ dose response. We conducted univariate and multivariate Cox regression analyses using publicly available TCGA and GEO datasets to investigate the impact of RYK gene expression status on glioma patient overall (OS) and progression-free survival (PFS). Our results indicated that in IDH mutant gliomas, RYK expression and tumor grade were significant predictors of survival. In IDH wildtype glioblastomas (GBM), MGMT status was the only significant predictor. Despite this result, we revealed a potential benefit of RYK expression in IDH wildtype GBM patients. We found that a combination of RYK expression and MGMT status could serve as an additional biomarker for improved survival. Overall, our findings suggest that RYK expression may serve as an important prognostic or predictor of TMZ response and survival for glioma patients.}, number={5}, journal={PHARMACEUTICALS}, author={Gonzalez, Ricardo D. and Small, George W. and Green, Adrian J. and Akhtari, Farida S. and Havener, Tammy M. and Quintanilha, Julia C. F. and Cipriani, Amber B. and Reif, David M. and McLeod, Howard L. and Motsinger-Reif, Alison A. and et al.}, year={2023}, month={May} }
 @article{marinello_gillera_huang_rollman_reif_patisaul_2023, title={Uncovering the common factors of chemical exposure and behavior: Evaluating behavioral effects across a testing battery using factor analysis}, volume={99}, ISSN={["1872-9711"]}, DOI={10.1016/j.neuro.2023.10.012}, abstractNote={Although specific environmental chemical exposures, including flame retardants, are known risk factors for neurodevelopmental disorders (NDDs), direct experimental evidence linking specific chemicals to NDDs is limited. Studies focusing on the mechanisms by which the social processing systems are vulnerable to chemical exposure are underrepresented in the literature, even though social impairments are defining characteristics of many NDDs. We have repeatedly demonstrated that exposure to Firemaster 550 (FM 550), a prevalent flame retardant mixture used in foam-based furniture and infant products, can adversely impact a variety of behavioral endpoints. Our recent work in prairie voles (Microtus ochrogaster), a prosocial animal model, demonstrated that perinatal exposure to FM 550 sex specifically impacts socioemotional behavior. Here, we utilized a factor analysis approach on a battery of behavioral data from our prior study to extract underlying factors that potentially explain patterns within the FM 550 behavior data. This approach identified which aspects of the behavioral battery are most robust and informative, an outcome critical for future study designs. Pearson’s correlation identified behavioral endpoints associated with distance and stranger interactions that were highly correlated across 5 behavioral tests. Using these behavioral endpoints, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) extracted 2 factors that could explain the data: Activity (distance traveled endpoints) and Sociability (time spent with a novel conspecific). Exposure to FM 550 significantly decreased Activity and decreased Sociability. This factor analysis approach to behavioral data offers the advantages of modeling numerous measured variables and simplifying the data set by presenting the data in terms of common, overarching factors in terms of behavioral function.}, journal={NEUROTOXICOLOGY}, author={Marinello, William P. and Gillera, Sagi Enicole A. and Huang, Lynn and Rollman, John and Reif, David M. and Patisaul, Heather B.}, year={2023}, month={Dec}, pages={264–273} }
 @article{chappel_king_fleming_eberlin_reif_baker_2023, title={Utilizing Aggregated Molecular Phenotype (AMP) Scores to Visualize Simultaneous Molecular Changes in Mass Spectrometry Imaging Data}, url={https://doi.org/10.1101/2023.06.01.543306}, DOI={10.1101/2023.06.01.543306}, abstractNote={ABSTRACT}, author={Chappel, Jessie R. and King, Mary E. and Fleming, Jonathon and Eberlin, Livia S. and Reif, David M. and Baker, Erin S.}, year={2023}, month={Jun} }
 @article{wolkin_collier_house_reif_motsinger-reif_duca_sharpe_2022, title={Comparison of National Vulnerability Indices Used by the Centers for Disease Control and Prevention for the COVID-19 Response}, volume={137}, ISSN={0033-3549 1468-2877}, url={http://dx.doi.org/10.1177/00333549221090262}, DOI={10.1177/00333549221090262}, abstractNote={Objective: Vulnerability indices use quantitative indicators and geospatial data to examine the level of vulnerability to morbidity in a community. The Centers for Disease Control and Prevention (CDC) uses 3 indices for the COVID-19 response: the CDC Social Vulnerability Index (CDC-SVI), the US COVID-19 Community Vulnerability Index (CCVI), and the Pandemic Vulnerability Index (PVI). The objective of this review was to describe these tools and explain the similarities and differences between them. }, number={4}, journal={Public Health Reports}, publisher={SAGE Publications}, author={Wolkin, Amy and Collier, Sarah and House, John S. and Reif, David and Motsinger-Reif, Alison and Duca, Lindsey and Sharpe, J. Danielle}, year={2022}, month={May}, pages={803–812} }
 @article{hubal_deluca_mullikin_slover_little_reif_2022, title={Demonstrating a systems approach for integrating disparate data streams to inform decisions on children's environmental health}, volume={22}, ISSN={["1471-2458"]}, DOI={10.1186/s12889-022-12682-3}, abstractNote={Abstract}, number={1}, journal={BMC PUBLIC HEALTH}, author={Hubal, Elaine A. Cohen and DeLuca, Nicole M. and Mullikin, Ashley and Slover, Rachel and Little, John C. and Reif, David M.}, year={2022}, month={Feb} }
 @article{truong_rericha_thunga_marvel_wallis_simonich_field_cao_reif_tanguay_2022, title={Systematic developmental toxicity assessment of a structurally diverse library of PFAS in zebrafish}, volume={431}, ISSN={["1873-3336"]}, url={http://dx.doi.org/10.1016/j.jhazmat.2022.128615}, DOI={10.1016/j.jhazmat.2022.128615}, abstractNote={Per- and polyfluoroalkyl substances (PFAS) are a class of widely used chemicals with limited human health effects data relative to the diversity of structures manufactured. To help fill this data gap, an extensive in vivo developmental toxicity screen was performed on 139 PFAS provided by the US EPA. Dechorionated embryonic zebrafish were exposed to 10 nominal water concentrations of PFAS (0.015–100 µM) from 6 to 120 h post-fertilization (hpf). The embryos were assayed for embryonic photomotor response (EPR), larval photomotor response (LPR), and 13 morphological endpoints. A total of 49 PFAS (35%) were bioactive in one or more assays (11 altered EPR, 25 altered LPR, and 31 altered morphology). Perfluorooctanesulfonamide (FOSA) was the only structure that was bioactive in all 3 assays, while Perfluorodecanoic acid (PFDA) was the most potent teratogen. Low PFAS volatility was associated with developmental toxicity (p < 0.01), but no association was detected between bioactivity and five other physicochemical parameters. The bioactive PFAS were enriched for 6 supergroup chemotypes. The results illustrate the power of a multi-dimensional in vivo platform to assess the developmental (neuro)toxicity of diverse PFAS and in the acceleration of PFAS safety research.}, journal={JOURNAL OF HAZARDOUS MATERIALS}, publisher={Elsevier BV}, author={Truong, Lisa and Rericha, Yvonne and Thunga, Preethi and Marvel, Skylar and Wallis, Dylan and Simonich, Michael T. and Field, Jennifer A. and Cao, Dunping and Reif, David M. and Tanguay, Robyn L.}, year={2022}, month={Jun} }
 @article{watson_carmona baez_jima_reif_ding_roberts_kullman_2022, title={TCDD alters essential transcriptional regulators of osteogenic differentiation in multipotent mesenchymal stem cells}, volume={11}, ISSN={["1096-0929"]}, url={https://doi.org/10.1093/toxsci/kfac120}, DOI={10.1093/toxsci/kfac120}, abstractNote={Abstract}, journal={TOXICOLOGICAL SCIENCES}, author={Watson, AtLee T. D. and Carmona Baez, Aldo and Jima, Dereje and Reif, David and Ding, Jun and Roberts, Reade and Kullman, Seth W.}, year={2022}, month={Nov} }
 @article{shankar_garcia_ladu_sullivan_dunham_goodale_waters_stanisheuski_maier_thunga_et al._2022, title={The Ahr2-Dependent wfikkn1 Gene Influences Zebrafish Transcriptome, Proteome, and Behavior}, volume={4}, ISSN={["1096-0929"]}, DOI={10.1093/toxsci/kfac037}, abstractNote={Abstract}, journal={TOXICOLOGICAL SCIENCES}, author={Shankar, Prarthana and Garcia, Gloria R. and LaDu, Jane K. and Sullivan, Christopher M. and Dunham, Cheryl L. and Goodale, Britton C. and Waters, Katrina M. and Stanisheuski, Stanislau and Maier, Claudia S. and Thunga, Preethi and et al.}, year={2022}, month={Apr} }
 @article{fleming_marvel_supak_motsinger-reif_reif_2022, title={ToxPi*GIS Toolkit: creating, viewing, and sharing integrative visualizations for geospatial data using ArcGIS}, volume={4}, ISSN={["1559-064X"]}, DOI={10.1038/s41370-022-00433-w}, abstractNote={Abstract}, journal={JOURNAL OF EXPOSURE SCIENCE AND ENVIRONMENTAL EPIDEMIOLOGY}, author={Fleming, Jonathon and Marvel, Skylar W. and Supak, Stacy and Motsinger-Reif, Alison A. and Reif, David M.}, year={2022}, month={Apr} }
 @article{kirkwood_fleming_nguyen_reif_baker_belcher_2022, title={Utilizing Pine Needles to Temporally and Spatially Profile Per- and Polyfluoroalkyl Substances (PFAS)}, volume={56}, ISSN={["1520-5851"]}, url={https://doi.org/10.1021/acs.est.1c06483}, DOI={10.1021/acs.est.1c06483}, abstractNote={As concerns over exposure to per- and polyfluoroalkyl substances (PFAS) are continually increasing, novel methods to monitor their presence and modifications are greatly needed, as some have known toxic and bioaccumulative characteristics while most have unknown effects. This task however is not simple, as the Environmental Protection Agency (EPA) CompTox PFAS list contains more than 9000 substances as of September 2020 with additional substances added continually. Nontargeted analyses are therefore crucial to investigating the presence of this immense list of possible PFAS. Here, we utilized archived and field-sampled pine needles as widely available passive samplers and a novel nontargeted, multidimensional analytical method coupling liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) to evaluate the temporal and spatial presence of numerous PFAS. Over 70 PFAS were detected in the pine needles from this study, including both traditionally monitored legacy perfluoroalkyl acids (PFAAs) and their emerging replacements such as chlorinated derivatives, ultrashort chain PFAAs, perfluoroalkyl ether acids including hexafluoropropylene oxide dimer acid (HFPO-DA, "GenX") and Nafion byproduct 2, and a cyclic perfluorooctanesulfonic acid (PFOS) analog. Results from this study provide critical insight related to PFAS transport, contamination, and reduction efforts over the past six decades.}, number={6}, journal={ENVIRONMENTAL SCIENCE & TECHNOLOGY}, publisher={American Chemical Society (ACS)}, author={Kirkwood, Kaylie I and Fleming, Jonathon and Nguyen, Helen and Reif, David M. and Baker, Erin S. and Belcher, Scott M.}, year={2022}, month={Mar}, pages={3441–3451} }
 @article{thunga_truong_rericha_du_morshead_tanguay_reif_2022, title={Utilizing a Population-Genetic Framework to Test for Gene-Environment Interactions between Zebrafish Behavior and Chemical Exposure}, volume={10}, ISSN={["2305-6304"]}, url={https://doi.org/10.3390/toxics10120769}, DOI={10.3390/toxics10120769}, abstractNote={Individuals within genetically diverse populations display broad susceptibility differences upon chemical exposures. Understanding the role of gene-environment interactions (GxE) in differential susceptibility to an expanding exposome is key to protecting public health. However, a chemical’s potential to elicit GxE is often not considered during risk assessment. Previously, we’ve leveraged high-throughput zebrafish (Danio rerio) morphology screening data to reveal patterns of potential GxE effects. Here, using a population genetics framework, we apportioned variation in larval behavior and gene expression in three different PFHxA environments via mixed-effect modeling to assess significance of GxE term. We estimated the intraclass correlation (ICC) between full siblings from different families using one-way random-effects model. We found a significant GxE effect upon PFHxA exposure in larval behavior, and the ICC of behavioral responses in the PFHxA exposed population at the lower concentration was 43.7%, while that of the control population was 14.6%. Considering global gene expression data, a total of 3746 genes showed statistically significant GxE. By showing evidence that heritable genetics are directly affecting gene expression and behavioral susceptibility of individuals to PFHxA exposure, we demonstrate how standing genetic variation in a heterogeneous population such as ours can be leveraged to test for potential GxE.}, number={12}, journal={TOXICS}, author={Thunga, Preethi and Truong, Lisa and Rericha, Yvonne and Du, Jane La and Morshead, Mackenzie and Tanguay, Robyn L. and Reif, David M.}, year={2022}, month={Dec} }
 @article{carberry_koval_payton_hartwell_kim_smith_reif_jaspers_gilmour_rager_2022, title={Wildfires and extracellular vesicles: Exosomal MicroRNAs as mediators of cross-tissue cardiopulmonary responses to biomass smoke}, volume={167}, ISSN={["1873-6750"]}, DOI={10.1016/j.envint.2022.107419}, abstractNote={Wildfires are a threat to public health world-wide that are growing in intensity and prevalence. The biological mechanisms that elicit wildfire-associated toxicity remain largely unknown. The potential involvement of cross-tissue communication via extracellular vesicles (EVs) is a new mechanism that has yet to be evaluated. Female CD-1 mice were exposed to smoke condensate samples collected from the following biomass burn scenarios: flaming peat; smoldering peat; flaming red oak; and smoldering red oak, representing lab-based simulations of wildfire scenarios. Lung tissue, bronchoalveolar lavage fluid (BALF) samples, peripheral blood, and heart tissues were collected 4 and 24 h post-exposure. Exosome-enriched EVs were isolated from plasma, physically characterized, and profiled for microRNA (miRNA) expression. Pathway-level responses in the lung and heart were evaluated through RNA sequencing and pathway analyses. Markers of cardiopulmonary tissue injury and inflammation from BALF samples were significantly altered in response to exposures, with the greatest changes occurring from flaming biomass conditions. Plasma EV miRNAs relevant to cardiovascular disease showed exposure-induced expression alterations, including miR-150, miR-183, miR-223-3p, miR-30b, and miR-378a. Lung and heart mRNAs were identified with differential expression enriched for hypoxia and cell stress-related pathways. Flaming red oak exposure induced the greatest transcriptional response in the heart, a large portion of which were predicted as regulated by plasma EV miRNAs, including miRNAs known to regulate hypoxia-induced cardiovascular injury. Many of these miRNAs had published evidence supporting their transfer across tissues. A follow-up analysis of miR-30b showed that it was increased in expression in the heart of exposed mice in the absence of changes to its precursor molecular, pri-miR-30b, suggesting potential transfer from external sources (e.g., plasma). This study posits a potential mechanism through which wildfire exposures induce cardiopulmonary responses, highlighting the role of circulating plasma EVs in intercellular and systems-level communication between tissues.}, journal={ENVIRONMENT INTERNATIONAL}, author={Carberry, Celeste K. and Koval, Lauren E. and Payton, Alexis and Hartwell, Hadley and Kim, Yong Ho and Smith, Gregory J. and Reif, David M. and Jaspers, Ilona and Gilmour, M. Ian and Rager, Julia E.}, year={2022}, month={Sep} }
 @article{thunga_truong_tanguay_reif_2021, title={Concurrent Evaluation of Mortality and Behavioral Responses: A Fast and Efficient Testing Approach for High-Throughput Chemical Hazard Identification}, volume={3}, url={http://dx.doi.org/10.3389/ftox.2021.670496}, DOI={10.3389/ftox.2021.670496}, abstractNote={The continual introduction of new chemicals into the market necessitates fast, efficient testing strategies for evaluating their toxicity. Ideally, these high-throughput screening (HTS) methods should capture the entirety of biological complexity while minimizing reliance on expensive resources that are required to assess diverse phenotypic endpoints. In recent years, the zebrafish (Danio rerio) has become a preferred vertebrate model to conduct rapid in vivo toxicity tests. Previously, using HTS data on 1060 chemicals tested as part of the ToxCast program, we showed that early, 24 h post-fertilization (hpf), behavioral responses of zebrafish embryos are predictive of later, 120 h post-fertilization, adverse developmental endpoints—indicating that embryonic behavior is a useful endpoint related to observable morphological effects. Here, our goal was to assess the contributions (i.e., information gain) from multiple phenotypic data streams and propose a framework for efficient identification of chemical hazards. We systematically swept through analysis parameters for data on 24 hpf behavior, 120 hpf behavior, and 120 hpf morphology to optimize settings for each of these assays. We evaluated the concordance of data from behavioral assays with that from morphology. We found that combining information from behavioral and mortality assessments captures early signals of potential chemical hazards, obviating the need to evaluate a comprehensive suite of morphological endpoints in initial screens for toxicity. We have demonstrated that such a screening strategy is useful for detecting compounds that elicit adverse morphological responses, in addition to identifying hazardous compounds that do not disrupt the underlying morphology. The application of this design for rapid preliminary toxicity screening will accelerate chemical testing and aid in prioritizing chemicals for risk assessment.}, journal={Frontiers in Toxicology}, publisher={Frontiers Media SA}, author={Thunga, Preethi and Truong, Lisa and Tanguay, Robyn L. and Reif, David M.}, year={2021}, month={Jun} }
 @article{gilchrist_alexander_green_sanders_hooker_reif_2021, title={Development of a Pandemic Awareness STEM Outreach Curriculum: Utilizing a Computational Thinking Taxonomy Framework}, volume={11}, ISSN={["2227-7102"]}, url={https://doi.org/10.3390/educsci11030109}, DOI={10.3390/educsci11030109}, abstractNote={Computational thinking is an essential skill in the modern global workforce. The current public health crisis has highlighted the need for students and educators to have a deeper understanding of epidemiology. While existing STEM curricula has addressed these topics in the past, current events present an opportunity for new curricula that can be designed to present epidemiology, the science of public health, as a modern topic for students that embeds the problem-solving and mathematics skills of computational thinking practices authentically. Using the Computational Thinking Taxonomy within the informal education setting of a STEM outreach program, a curriculum was developed to introduce middle school students to epidemiological concepts while developing their problem-solving skills, a subset of their computational thinking and mathematical thinking practices, in a contextually rich environment. The informal education setting at a Research I Institution provides avenues to connect diverse learners to visually engaging computational thinking and data science curricula to understand emerging teaching and learning approaches. This paper documents the theory and design approach used by researchers and practitioners to create a Pandemic Awareness STEM Curriculum and future implications for teaching and learning computational thinking practices through engaging with data science.}, number={3}, journal={EDUCATION SCIENCES}, author={Gilchrist, Pamela O. and Alexander, Alonzo B. and Green, Adrian J. and Sanders, Frieda E. and Hooker, Ashley Q. and Reif, David M.}, year={2021}, month={Mar} }
 @article{green_anchang_akhtari_reif_motsinger-reif_2021, title={Extending the lymphoblastoid cell line model for drug combination pharmacogenomics}, volume={22}, ISSN={["1744-8042"]}, url={https://doi.org/10.2217/pgs-2020-0160}, DOI={10.2217/pgs-2020-0160}, abstractNote={ Combination drug therapies have become an integral part of precision oncology, and while evidence of clinical effectiveness continues to grow, the underlying mechanisms supporting synergy are poorly understood. Immortalized human lymphoblastoid cell lines (LCLs) have been proven as a particularly useful, scalable and low-cost model in pharmacogenetics research, and are suitable for elucidating the molecular mechanisms of synergistic combination therapies. In this review, we cover the advantages of LCLs in synergy pharmacogenomics and consider recent studies providing initial evidence of the utility of LCLs in synergy research. We also discuss several opportunities for LCL-based systems to address gaps in the research through the expansion of testing regimens, assessment of new drug classes and higher-order combinations, and utilization of integrated omics technologies. }, number={9}, journal={PHARMACOGENOMICS}, publisher={Future Medicine Ltd}, author={Green, Adrian J. and Anchang, Benedict and Akhtari, Farida S. and Reif, David M. and Motsinger-Reif, Alison}, year={2021}, month={May} }
 @article{akhtari_green_small_havener_house_roell_reif_mcleod_wiltshire_motsinger-reif_2021, title={High-throughput screening and genome-wide analyses of 44 anticancer drugs in the 1000 Genomes cell lines reveals an association of the NQO1 gene with the response of multiple anticancer drugs}, volume={17}, ISSN={["1553-7404"]}, url={https://doi.org/10.1371/journal.pgen.1009732}, DOI={10.1371/journal.pgen.1009732}, abstractNote={Cancer patients exhibit a broad range of inter-individual variability in response and toxicity to widely used anticancer drugs, and genetic variation is a major contributor to this variability. To identify new genes that influence the response of 44 FDA-approved anticancer drug treatments widely used to treat various types of cancer, we conducted high-throughput screening and genome-wide association mapping using 680 lymphoblastoid cell lines from the 1000 Genomes Project. The drug treatments considered in this study represent nine drug classes widely used in the treatment of cancer in addition to the paclitaxel + epirubicin combination therapy commonly used for breast cancer patients. Our genome-wide association study (GWAS) found several significant and suggestive associations. We prioritized consistent associations for functional follow-up using gene-expression analyses. The NAD(P)H quinone dehydrogenase 1 (NQO1) gene was found to be associated with the dose-response of arsenic trioxide, erlotinib, trametinib, and a combination treatment of paclitaxel + epirubicin. NQO1 has previously been shown as a biomarker of epirubicin response, but our results reveal novel associations with these additional treatments. Baseline gene expression of NQO1 was positively correlated with response for 43 of the 44 treatments surveyed. By interrogating the functional mechanisms of this association, the results demonstrate differences in both baseline and drug-exposed induction.}, number={8}, journal={PLOS GENETICS}, publisher={Public Library of Science (PLoS)}, author={Akhtari, Farida S. and Green, Adrian J. and Small, George W. and Havener, Tammy M. and House, John S. and Roell, Kyle R. and Reif, David M. and McLeod, Howard L. and Wiltshire, Timothy and Motsinger-Reif, Alison A.}, editor={Vazquez, FranciscaEditor}, year={2021}, month={Aug} }
 @article{green_mohlenkamp_das_chaudhari_truong_tanguay_reif_2021, title={Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology}, volume={17}, ISSN={["1553-7358"]}, url={https://doi.org/10.1371/journal.pcbi.1009135}, DOI={10.1371/journal.pcbi.1009135}, abstractNote={There are currently 85,000 chemicals registered with the Environmental Protection Agency (EPA) under the Toxic Substances Control Act, but only a small fraction have measured toxicological data. To address this gap, high-throughput screening (HTS) and computational methods are vital. As part of one such HTS effort, embryonic zebrafish were used to examine a suite of morphological and mortality endpoints at six concentrations from over 1,000 unique chemicals found in the ToxCast library (phase 1 and 2). We hypothesized that by using a conditional generative adversarial network (cGAN) or deep neural networks (DNN), and leveraging this large set of toxicity data we could efficiently predict toxic outcomes of untested chemicals. Utilizing a novel method in this space, we converted the 3D structural information into a weighted set of points while retaining all information about the structure. In vivo toxicity and chemical data were used to train two neural network generators. The first was a DNN (Go-ZT) while the second utilized cGAN architecture (GAN-ZT) to train generators to produce toxicity data. Our results showed that Go-ZT significantly outperformed the cGAN, support vector machine, random forest and multilayer perceptron models in cross-validation, and when tested against an external test dataset. By combining both Go-ZT and GAN-ZT, our consensus model improved the SE, SP, PPV, and Kappa, to 71.4%, 95.9%, 71.4% and 0.673, respectively, resulting in an area under the receiver operating characteristic (AUROC) of 0.837. Considering their potential use as prescreening tools, these models could provide in vivo toxicity predictions and insight into the hundreds of thousands of untested chemicals to prioritize compounds for HT testing.}, number={7}, journal={PLOS COMPUTATIONAL BIOLOGY}, publisher={Public Library of Science (PLoS)}, author={Green, Adrian J. and Mohlenkamp, Martin J. and Das, Jhuma and Chaudhari, Meenal and Truong, Lisa and Tanguay, Robyn L. and Reif, David M.}, editor={Hatzimanikatis, VassilyEditor}, year={2021}, month={Jul} }
 @article{odenkirk_reif_baker_2021, title={Multiomic Big Data Analysis Challenges: Increasing Confidence in the Interpretation of Artificial Intelligence Assessments}, volume={93}, ISSN={["1520-6882"]}, DOI={10.1021/acs.analchem.0c04850}, abstractNote={The need for holistic molecular measurements to better understand disease initiation, development, diagnosis, and therapy has led to an increasing number of multiomic analyses. The wealth of information available from multiomic assessments, however, requires both the evaluation and interpretation of extremely large data sets, limiting analysis throughput and ease of adoption. Computational methods utilizing artificial intelligence (AI) provide the most promising way to address these challenges, yet despite the conceptual benefits of AI and its successful application in singular omic studies, the widespread use of AI in multiomic studies remains limited. Here, we discuss present and future capabilities of AI techniques in multiomic studies while introducing analytical checks and balances to validate the computational conclusions.}, number={22}, journal={ANALYTICAL CHEMISTRY}, author={Odenkirk, Melanie T. and Reif, David M. and Baker, Erin S.}, year={2021}, month={Jun}, pages={7763–7773} }
 @misc{marvel_house_wheeler_song_zhou_wright_chiu_rusyn_motsinger-reif_reif_2021, title={The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning}, volume={129}, ISSN={["1552-9924"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85099420902&partnerID=MN8TOARS}, DOI={10.1289/EHP8690}, abstractNote={Vol. 129, No. 1 Research LetterOpen AccessThe COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning Skylar W. Marvel, John S. House, Matthew Wheeler, Kuncheng Song, Yi-Hui Zhou, Fred A. Wright, Weihsueh A. Chiu, Ivan Rusyn, Alison Motsinger-Reif, and David M. Reif Skylar W. Marvel Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University (NCSU), Raleigh, North Carolina, USA Search for more papers by this author , John S. House Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA Search for more papers by this author , Matthew Wheeler Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA Search for more papers by this author , Kuncheng Song Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University (NCSU), Raleigh, North Carolina, USA Search for more papers by this author , Yi-Hui Zhou Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University (NCSU), Raleigh, North Carolina, USA Search for more papers by this author , Fred A. Wright Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University (NCSU), Raleigh, North Carolina, USA Department of Statistics, NCSU, Raleigh, North Carolina, USA Search for more papers by this author , Weihsueh A. Chiu Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA Search for more papers by this author , Ivan Rusyn Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA Search for more papers by this author , Alison Motsinger-Reif Address correspondence to Alison Motsinger-Reif, 111 T.W. Alexander Dr., Rall Building, Research Triangle Park, NC 27709 USA. Email: E-mail Address: [email protected], or David M. Reif, Box 7566, 1 Lampe Dr., Raleigh NC 27695 USA. Email: E-mail Address: [email protected] Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA Search for more papers by this author , and David M. Reif Address correspondence to Alison Motsinger-Reif, 111 T.W. Alexander Dr., Rall Building, Research Triangle Park, NC 27709 USA. Email: E-mail Address: [email protected], or David M. Reif, Box 7566, 1 Lampe Dr., Raleigh NC 27695 USA. Email: E-mail Address: [email protected] Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University (NCSU), Raleigh, North Carolina, USA Search for more papers by this author Published:5 January 2021CID: 017701https://doi.org/10.1289/EHP8690AboutSectionsPDF ToolsDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InReddit IntroductionExpert groups have coalesced around a roadmap to address the current COVID-19 pandemic centered on social distancing, monitoring case counts and health care capacity, and, eventually, moving to pharmaceutical interventions. However, responsibility for navigating the pandemic response falls largely on state and local officials. To make equitable decisions on allocating resources, caring for vulnerable subpopulations, and implementing local- and state-level interventions, access to current pandemic data and key vulnerabilities at the community level are essential (National Academies of Sciences, Engineering, and Medicine 2020). Although numerous predictive models and interactive monitoring applications have been developed using pandemic-related data sets (Wynants et al. 2020), their capacity to aid in dynamic, community-level decision-making is limited. We developed the interactive COVID-19 Pandemic Vulnerability Index (PVI) Dashboard ( https://covid19pvi.niehs.nih.gov/) to address this need by presenting a visual synthesis of dynamic information at the county level to monitor disease trajectories, communicate local vulnerabilities, forecast key outcomes, and guide informed responses (Figure 1).Figure 1. COVID-19 PVI Dashboard. Dashboard screenshot displaying PVI profiles atop a choropleth map layer indicating overall COVID-19 PVI rank. The PVI Scorecard and associated data for Clarendon County, South Carolina, has been selected. The scorecard summarizes the overall PVI score and rank compared with all 3,142 U.S. counties on each indicator slice. The scrollable score distributions at left compare the selected county PVI to the distributions of overall and slice-wise scores across the United States. The panels below the map are populated with county-specific information on observed trends in cases and deaths, cumulative numbers for the county, historical timelines (for cumulative cases, cumulative deaths, PVI, and PVI rank), daily case and death counts for the most recent 14-d period, and a 14-d forecast of predicted cases and deaths. The information displayed for both observed COVID-19 data and PVI layers is scrollable back through March 2020. Documentation of additional features and usage, including advanced options (accessible via the collapsed menu at the upper left), is provided in a Quick Start Guide (linked at the upper right corner). Note: Pop, population; PVI, Pandemic Vulnerability Index.MethodsThe current PVI model integrates multiple data streams into an overall score derived from 12 key indicators—including well-established, general vulnerability factors for public health, plus emerging factors relevant to the pandemic—distributed across four domains: current infection rates, baseline population concentration, current interventions, and health and environmental vulnerabilities. The PVI profiles translate numerical results into visual representations, with each vulnerability factor represented as a component slice of a radar chart (Figure 2). The PVI profile for each county is calculated using the Toxicological Prioritization Index (ToxPi) framework for data integration within a geospatial context (Marvel et al. 2018; Bhandari et al. 2020). Data sources in the current model (version 11.2.1) include the Social Vulnerability Index (SVI) of the Centers for Disease Control and Prevention (CDC) for emergency response and hazard mitigation planning (Horney et al. 2017), testing rates from the COVID Tracking Project (Atlantic Monthly Group 2020), social distancing metrics from mobile device data ( https://www.unacast.com/covid19/social-distancing-scoreboard), and dynamic measures of disease spread and case numbers ( https://usafacts.org/issues/coronavirus/). Methodological details concerning the integration of data streams—plus the complete, daily time series of all source data since February 2020 and resultant PVI scores—are maintained on the public Github project page (COVID19PVI 2020). Over this period, the PVI has been strongly associated with key vulnerability-related outcome metrics (by rank-correlation), with updates of its performance assessment posted with model updates alongside data at the Github project page (COVID19PVI 2020).Figure 2. Translation of data into COVID-19 PVI profiles. Information from all 3,142 U.S. counties is translated into PVI slices. The illustration shows how air pollution data (average density of fine particulate matterPM2.5 per county) are compared for two example counties. The county with the higher relative measurement (County Y) has a longer air pollution slice than the county with a lower measurement (County X). This procedure is repeated for all slices, resulting in an integrated, overall PVI profile. Note: pop, population; PVI, Pandemic Vulnerability Index.In addition to the PVI itself—which is a summary, human-centric visualization of relative vulnerability drivers—the dashboard is supported by rigorous statistical modeling of the underlying data to enable quantitative analysis and provide short-term, local predictions of cases and deaths [complete methodological details are maintained at the Github project page (COVID19PVI 2020)]. Generalized linear models of cumulative outcome data indicated that, after population size, the most significant predictors were the proportion of Black residents, mean fine particulate matter [particulate matter less than or equal to 2.5 micrometers≤2.5μm in diameter (fine particulate matterPM2.5)], percentage of population with insurance coverage (which was positively associated), and proportion of Hispanic residents. The local predictions of cases and deaths (see the “Predictions” panel in Figure 1) are updated daily using a Bayesian spatiotemporal random-effects model to build forecasts up to 2 weeks out.DiscussionThe PVI Dashboard supports decision-making and dynamic monitoring in several ways. The display can be tailored to add or remove layers of information, filtered by region (e.g., all counties within a state) or clustered by profile shape similarity. The timelines for both PVI models and observed COVID-19 outcomes facilitate tracking the impact of interventions and directing local resource allocations. The “Predictions” panel (Figure 1) connects these historical numbers to local forecasts of cases and deaths. By communicating an integrated concept of vulnerability that considers both dynamic (infection rate and interventions) and static (community population and health care characteristics) drivers, the interactive dashboard can promote buy-in from diverse audiences, which is necessary for effective public health interventions. This messaging can assist in addressing known racial disparities in COVID-19 case and death rates (Tan et al. 2020) or populations, and the PVI Dashboard is part of the “Unique Populations” tab of the CDC’s COVID-19 Data Tracker ( https://covid.cdc.gov/covid-data-tracker). By filtering the display to highlight vulnerability drivers within an overall score context, the dashboard can inform targeted interventions for specific localities.Unfortunately, the pandemic endures across the United States, with broad disparities based on the local environment (Tan et al. 2020). We present the PVI Dashboard as a dynamic container for contextualizing these disparities. It is a modular tool that will evolve to incorporate new data sources and analytics as they emerge (e.g., concurrent flu infections, school and business reopening statistics, heterogeneous public health practices). This flexibility positions it well as a resource for integrated prioritization of eventual vaccine distribution and monitoring its local impact. The PVI Dashboard can empower local and state officials to take informed action to combat the pandemic by communicating interactive, visual profiles of vulnerability atop an underlying statistical framework that enables the comparison of counties and the evaluation of the PVI’s component data.AcknowledgmentsWe thank the information technology and web services staff at the National Institute of Environmental Health Sciences (NIEHS)/National Institutes of Health (NIH) for their help and support, as well as J.K. Cetina and D.J. Reif for their useful technical input and advice. This work was supported by NIEHS/NIH grants (P42 ES027704, P30 ES029067, P42 ES031009, and P30 ES025128) and NIEHS/NIH intramural funds (Z ES103352-01).ReferencesAtlantic Monthly Group.2020. The COVID Tracking Project. https://covidtracking.com/ [accessed 15 November 2020]. Google ScholarBhandari S, Lewis PGT, Craft E, Marvel SW, Reif DM, Chiu WA. 2020. HGBEnviroScreen: enabling community action through data integration in the Houston–Galveston–Brazoria region. Int J Environ Res Public Health 17(4):1130, PMID: 32053902, 10.3390/ijerph17041130. Crossref, Medline, Google ScholarCOVID19PVI.2020. COVID19PVI/data. https://github.com/COVID19PVI/data [accessed 15 November 2020]. Google ScholarHorney J, Nguyen M, Salvesen D, Dwyer C, Cooper J, Berke P. 2017. Assessing the quality of rural hazard mitigation plans in the southeastern United States. J Plan Educ Res 37(1):56–65, 10.1177/0739456X16628605. Crossref, Google ScholarMarvel SW, To K, Grimm FA, Wright FA, Rusyn I, Reif DM. 2018. ToxPi Graphical User Interface 2.0: dynamic exploration, visualization, and sharing of integrated data models. BMC Bioinformatics 19(1):80, PMID: 29506467, 10.1186/s12859-018-2089-2. Crossref, Medline, Google ScholarNational Academies of Sciences, Engineering, and Medicine.2020. Framework for Equitable Allocation of COVID-19 Vaccine. Gayle H, Foege W, Brown L, Kahn B, eds. Washington, DC: National Academies Press. Google ScholarTan TQ, Kullar R, Swartz TH, Mathew TA, Piggott DA, Berthaud V. 2020. Location matters: geographic disparities and impact of coronavirus disease 2019. J Infect Dis 222(12):1951–1954, PMID: 32942299, 10.1093/infdis/jiaa583. Crossref, Medline, Google ScholarWynants L, Van Calster B, Collins GS, Riley RD, Heinze G, Schuit E, et al.2020. Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. BMJ 369:m1328, PMID: 32265220, 10.1136/bmj.m1328. Crossref, Medline, Google ScholarThe authors declare they have no actual or potential competing financial interests.FiguresReferencesRelatedDetails Vol. 129, No. 1 January 2021Metrics About Article Metrics Publication History Manuscript received20 November 2020Manuscript revised14 December 2020Manuscript accepted21 December 2020Originally published5 January 2021 Financial disclosuresPDF download License information EHP is an open-access journal published with support from the National Institute of Environmental Health Sciences, National Institutes of Health. All content is public domain unless otherwise noted. Note to readers with disabilities EHP strives to ensure that all journal content is accessible to all readers. However, some figures and Supplemental Material published in EHP articles may not conform to 508 standards due to the complexity of the information being presented. If you need assistance accessing journal content, please contact [email protected]. Our staff will work with you to assess and meet your accessibility needs within 3 working days.}, number={1}, journal={ENVIRONMENTAL HEALTH PERSPECTIVES}, author={Marvel, Skylar W. and House, John S. and Wheeler, Matthew and Song, Kuncheng and Zhou, Yi-Hui and Wright, Fred A. and Chiu, Weihsueh A. and Rusyn, Ivan and Motsinger-Reif, Alison and Reif, David M.}, year={2021}, month={Jan} }
 @article{fleming_marvel_motsinger-reif_reif_2021, title={ToxPi*GIS Toolkit: Creating, viewing, and sharing integrative visualizations for geospatial data using ArcGIS}, volume={10}, url={https://doi.org/10.1101/2021.10.08.21264756}, DOI={10.1101/2021.10.08.21264756}, abstractNote={Abstract}, publisher={Cold Spring Harbor Laboratory}, author={Fleming, Jonathon and Marvel, Skylar W. and Motsinger-Reif, Alison A. and Reif, David M.}, year={2021}, month={Oct} }
 @misc{wallis_truong_la du_tanguay_reif_2021, title={Uncovering Evidence for Endocrine-Disrupting Chemicals That Elicit Differential Susceptibility through Gene-Environment Interactions}, volume={9}, ISSN={["2305-6304"]}, url={https://doi.org/10.3390/toxics9040077}, DOI={10.3390/toxics9040077}, abstractNote={Exposure to endocrine-disrupting chemicals (EDCs) is linked to myriad disorders, characterized by the disruption of the complex endocrine signaling pathways that govern development, physiology, and even behavior across the entire body. The mechanisms of endocrine disruption involve a complex system of pathways that communicate across the body to stimulate specific receptors that bind DNA and regulate the expression of a suite of genes. These mechanisms, including gene regulation, DNA binding, and protein binding, can be tied to differences in individual susceptibility across a genetically diverse population. In this review, we posit that EDCs causing such differential responses may be identified by looking for a signal of population variability after exposure. We begin by summarizing how the biology of EDCs has implications for genetically diverse populations. We then describe how gene-environment interactions (GxE) across the complex pathways of endocrine signaling could lead to differences in susceptibility. We survey examples in the literature of individual susceptibility differences to EDCs, pointing to a need for research in this area, especially regarding the exceedingly complex thyroid pathway. Following a discussion of experimental designs to better identify and study GxE across EDCs, we present a case study of a high-throughput screening signal of putative GxE within known endocrine disruptors. We conclude with a call for further, deeper analysis of the EDCs, particularly the thyroid disruptors, to identify if these chemicals participate in GxE leading to differences in susceptibility.}, number={4}, journal={TOXICS}, publisher={MDPI AG}, author={Wallis, Dylan J. and Truong, Lisa and La Du, Jane and Tanguay, Robyn L. and Reif, David M.}, year={2021}, month={Apr} }
 @article{kirkwood_fleming_nguyen_reif_baker_belcher_2021, title={Utilizing Pine Needles to Temporally and Spatially Profile Per- and Polyfluoroalkyl Substances}, volume={8}, url={https://doi.org/10.1101/2021.08.24.457570}, DOI={10.1101/2021.08.24.457570}, abstractNote={Abstract}, publisher={Cold Spring Harbor Laboratory}, author={Kirkwood, Kaylie I. and Fleming, Jonathon and Nguyen, Helen and Reif, David M. and Baker, Erin S. and Belcher, Scott M.}, year={2021}, month={Aug} }
 @article{bayesian matrix completion for hypothesis testing_2020, year={2020}, month={Sep} }
 @article{hubal_reif_slover_mullikin_little_2020, title={Children’s Environmental Health: A Systems Approach for Anticipating Impacts from Chemicals}, volume={17}, url={https://doi.org/10.3390/ijerph17228337}, DOI={10.3390/ijerph17228337}, abstractNote={Increasing numbers of chemicals are on the market and present in consumer products. Emerging evidence on the relationship between environmental contributions and prevalent diseases suggests associations between early-life exposure to manufactured chemicals and a wide range of children’s health outcomes. Using current assessment methodologies, public health and chemical management decisionmakers face challenges in evaluating and anticipating the potential impacts of exposure to chemicals on children’s health in the broader context of their physical (built and natural) and social environments. Here, we consider a systems approach to address the complexity of children’s environmental health and the role of exposure to chemicals during early life, in the context of nonchemical stressors, on health outcomes. By advancing the tools for integrating this more complex information, the scope of considerations that support chemical management decisions can be extended to include holistic impacts on children’s health.}, number={22}, journal={International Journal of Environmental Research and Public Health}, publisher={MDPI AG}, author={Hubal, Elaine A. Cohen and Reif, David M. and Slover, Rachel and Mullikin, Ashley and Little, John C.}, year={2020}, month={Nov}, pages={8337} }
 @article{kosnik_strickland_marvel_wallis_wallace_richard_reif_shafer_2020, title={Concentration-response evaluation of ToxCast compounds for multivariate activity patterns of neural network function}, volume={94}, ISSN={["1432-0738"]}, DOI={10.1007/s00204-019-02636-x}, abstractNote={The US Environmental Protection Agency’s ToxCast program has generated toxicity data for thousands of chemicals but does not adequately assess potential neurotoxicity. Networks of neurons grown on microelectrode arrays (MEAs) offer an efficient approach to screen compounds for neuroactivity and distinguish between compound effects on firing, bursting, and connectivity patterns. Previously, single concentrations of the ToxCast Phase II library were screened for effects on mean firing rate (MFR) in rat primary cortical networks. Here, we expand this approach by retesting 384 of those compounds (including 222 active in the previous screen) in concentration–response across 43 network activity parameters to evaluate neural network function. Using hierarchical clustering and machine learning methods on the full suite of chemical-parameter response data, we identified 15 network activity parameters crucial in characterizing activity of 237 compounds that were response actives (“hits”). Recognized neurotoxic compounds in this network function assay were often more potent compared to other ToxCast assays. Of these chemical-parameter responses, we identified three k-means clusters of chemical-parameter activity (i.e., multivariate MEA response patterns). Next, we evaluated the MEA clusters for enrichment of chemical features using a subset of ToxPrint chemotypes, revealing chemical structural features that distinguished the MEA clusters. Finally, we assessed distribution of neurotoxicants with known pharmacology within the clusters and found that compounds segregated differentially. Collectively, these results demonstrate that multivariate MEA activity patterns can efficiently screen for diverse chemical activities relevant to neurotoxicity, and that response patterns may have predictive value related to chemical structural features.}, number={2}, journal={ARCHIVES OF TOXICOLOGY}, author={Kosnik, Marissa B. and Strickland, Jenna D. and Marvel, Skylar W. and Wallis, Dylan J. and Wallace, Kathleen and Richard, Ann M. and Reif, David M. and Shafer, Timothy J.}, year={2020}, month={Feb}, pages={469–484} }
 @article{bhandari_lewis_craft_marvel_reif_chiu_2020, title={HGBEnviroScreen: Enabling Community Action through Data Integration in the Houston–Galveston–Brazoria Region}, volume={17}, url={https://doi.org/10.3390/ijerph17041130}, DOI={10.3390/ijerph17041130}, abstractNote={The Houston–Galveston–Brazoria (HGB) region faces numerous environmental and public health challenges from both natural disasters and industrial activity, but the historically disadvantaged communities most often impacted by such risks have limited ability to access and utilize big data for advocacy efforts. We developed HGBEnviroScreen to identify and prioritize regions of heightened vulnerability, in part to assist communities in understanding risk factors and developing environmental justice action plans. While similar in objectives to existing environmental justice tools, HGBEnviroScreen is unique in its ability to integrate and visualize national and local data to address regional concerns. For the 1090 census tracts in the HGB region, we accrued data into five domains: (i) social vulnerability, (ii) baseline health, (iii) environmental exposures and risks, (iv) environmental sources, and (v) flooding. We then integrated and visualized these data using the Toxicological Prioritization Index (ToxPi). We found that the highest vulnerability census tracts have multifactorial risk factors, with common drivers being flooding, social vulnerability, and proximity to environmental sources. Thus, HGBEnviroScreen is not only helping identify communities of greatest overall vulnerability but is also providing insights into which domains would most benefit from improved planning, policy, and action in order to reduce future vulnerability.}, number={4}, journal={International Journal of Environmental Research and Public Health}, publisher={MDPI AG}, author={Bhandari, Sharmila and Lewis, P. Grace Tee and Craft, Elena and Marvel, Skylar W. and Reif, David M. and Chiu, Weihsueh A.}, year={2020}, month={Feb}, pages={1130} }
 @article{phelps_fletcher_rodriguez-nunez_balik-meisner_tokarz_reif_germolec_yoder_2020, title={In vivo assessment of respiratory burst inhibition by xenobiotic exposure using larval zebrafish}, volume={17}, url={https://doi.org/10.1080/1547691X.2020.1748772}, DOI={10.1080/1547691X.2020.1748772}, abstractNote={Abstract Currently, assessment of the potential immunotoxicity of a given agent involves a tiered approach for hazard identification and mechanistic studies, including observational studies, evaluation of immune function, and measurement of susceptibility to infectious and neoplastic diseases. These studies generally use costly low-throughput mammalian models. Zebrafish, however, offer an excellent alternative due to their rapid development, ease of maintenance, and homology to mammalian immune system function and development. Larval zebrafish also are a convenient model to study the innate immune system with no interference from the adaptive immune system. In this study, a respiratory burst assay (RBA) was utilized to measure reactive oxygen species (ROS) production after developmental xenobiotic exposure. Embryos were exposed to non-teratogenic doses of chemicals and at 96 h post-fertilization, the ability to produce ROS was measured. Using the RBA, 12 compounds with varying immune-suppressive properties were screened. Seven compounds neither suppressed nor enhanced the respiratory burst; five reproducibly suppressed global ROS production, but with varying potencies: benzo[a]pyrene, 17β-estradiol, lead acetate, methoxychlor, and phenanthrene. These five compounds have all previously been reported as immunosuppressive in mammalian innate immunity assays. To evaluate whether the suppression of ROS by these compounds was a result of decreased immune cell numbers, flow cytometry with transgenic zebrafish larvae was used to count the numbers of neutrophils and macrophages after chemical exposure. With this assay, benzo[a]pyrene was found to be the only chemical that induced a change in the number of immune cells by increasing macrophage but not neutrophil numbers. Taken together, this work demonstrates the utility of zebrafish larvae as a vertebrate model for identifying compounds that impact innate immune function at non-teratogenic levels and validates measuring ROS production and phagocyte numbers as metrics for monitoring how xenobiotic exposure alters the innate immune system.}, number={1}, journal={Journal of Immunotoxicology}, publisher={Informa UK Limited}, author={Phelps, Drake W. and Fletcher, Ashley A. and Rodriguez-Nunez, Ivan and Balik-Meisner, Michele R. and Tokarz, Debra A. and Reif, David M. and Germolec, Dori R. and Yoder, Jeffrey A.}, year={2020}, month={Jan}, pages={94–104} }
 @article{reif_chanock_edwards_crowe_2020, title={Inappropriate Citation of Vaccine Article}, volume={222}, url={https://doi.org/10.1093/infdis/jiz287}, DOI={10.1093/infdis/jiz287}, number={8}, journal={The Journal of Infectious Diseases}, publisher={Oxford University Press (OUP)}, author={Reif, David M and Chanock, Stephen J and Edwards, Kathryn M and Crowe, James E}, year={2020}, month={Sep}, pages={1413–1414} }
 @article{odenkirk_zin_ash_reif_fourches_baker_2020, title={Structural-based connectivity and omic phenotype evaluations (SCOPE): a cheminformatics toolbox for investigating lipidomic changes in complex systems}, volume={145}, ISSN={["1364-5528"]}, DOI={10.1039/d0an01638a}, abstractNote={SCOPE is a toolbox for expanding upon lipid data interpretation capabilities. Herein we utilize SCOPE to explore how lipid structure, biological connections and metadata linkages contribute to the results observed from lipidomic experiments.}, number={22}, journal={ANALYST}, author={Odenkirk, Melanie T. and Zin, Phyo Phyo K. and Ash, Jeremy R. and Reif, David M. and Fourches, Denis and Baker, Erin S.}, year={2020}, month={Nov}, pages={7197–7209} }
 @article{marvel_house_wheeler_song_zhou_wright_chiu_rusyn_motsinger-reif_reif_2020, title={The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: monitoring county level vulnerability}, volume={8}, url={https://doi.org/10.1101/2020.08.10.20169649}, DOI={10.1101/2020.08.10.20169649}, abstractNote={Abstract}, journal={medRxiv}, publisher={Cold Spring Harbor Laboratory}, author={Marvel, Skylar W. and House, John S. and Wheeler, Matthew and Song, Kuncheng and Zhou, Yihui and Wright, Fred A. and Chiu, Weihsueh A. and Rusyn, Ivan and Motsinger-Reif, Alison and Reif, David M.}, year={2020}, month={Aug} }
 @article{truong_marvel_reif_thomas_pande_dasgupta_simonich_waters_tanguay_2020, title={The multi-dimensional embryonic zebrafish platform predicts flame retardant bioactivity}, volume={96}, ISSN={["0890-6238"]}, DOI={10.1016/j.reprotox.2020.08.007}, abstractNote={Flame retardant chemicals (FRCs) commonly added to many consumer products present a human exposure burden associated with adverse health effects. Under pressure from consumers, FRC manufacturers have adopted some purportedly safer replacements for first-generation brominated diphenyl ethers (BDEs). In contrast, second and third-generation organophosphates and other alternative chemistries have limited bioactivity data available to estimate their hazard potential. In order to evaluate the toxicity of existing and potential replacement FRCs, we need efficient screening methods. We built a 61-FRC library in which we systemically assessed developmental toxicity and potential neurotoxicity effects in the embryonic zebrafish model. Data were compared to publicly available data generated in a battery of cell-based in vitro assays from ToxCast, Tox21, and other alternative models. Of the 61 FRCs, 19 of 45 that were tested in the ToxCast assays were bioactive in our zebrafish model. The zebrafish assays detected bioactivity for 10 of the 12 previously classified developmental neurotoxic FRCs. Developmental zebrafish were sufficiently sensitive at detecting FRC structure-bioactivity impacts that we were able to build a classification model using 13 physicochemical properties and 3 embryonic zebrafish assays that achieved a balanced accuracy of 91.7%. This work illustrates the power of a multi-dimensional in vivo platform to expand our ability to predict the hazard potential of new compounds based on structural relatedness, ultimately leading to reliable toxicity predictions based on chemical structure.}, journal={REPRODUCTIVE TOXICOLOGY}, author={Truong, Lisa and Marvel, Skylar and Reif, David M. and Thomas, Dennis G. and Pande, Paritosh and Dasgupta, Subham and Simonich, Michael T. and Waters, Katrina M. and Tanguay, Robyn L.}, year={2020}, month={Sep}, pages={359–369} }
 @article{kosnik_reif_lobdell_astell-burt_feng_hader_hoppin_2019, title={Associations between access to healthcare, environmental quality, and end-stage renal disease survival time: Proportional-hazards models of over 1,000,000 people over 14 years}, volume={14}, ISSN={["1932-6203"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85063354945&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0214094}, abstractNote={Prevalence of end-stage renal disease (ESRD) in the US increased by 74% from 2000 to 2013. To investigate the role of the broader environment on ESRD survival time, we evaluated average distance to the nearest hospital by county (as a surrogate for access to healthcare) and the Environmental Quality Index (EQI), an aggregate measure of ambient environmental quality composed of five domains (air, water, land, built, and sociodemographic), at the county level across the US. Associations between average hospital distance, EQI, and survival time for 1,092,281 people diagnosed with ESRD between 2000 and 2013 (age 18+, without changes in county residence) from the US Renal Data System were evaluated using proportional-hazards models adjusting for gender, race, age at first ESRD service date, BMI, alcohol and tobacco use, and rurality. The models compared the average distance to the nearest hospital (<10, 10–20, >20 miles) and overall EQI percentiles [0–5), [5–20), [20–40), [40–60), [60–80), [80–95), and [95–100], where lower percentiles are interpreted as better EQI. In the full, non-stratified model with both distance and EQI, there was increased survival for patients over 20 miles from a hospital compared to those under 10 miles from a hospital (hazard ratio = 1.14, 95% confidence interval = 1.12–1.15) and no consistent direction of association across EQI strata. In the full model stratified by average hospital distance, under 10 miles from a hospital had increased survival in the worst EQI strata (median survival 3.0 vs. 3.5 years for best vs. worst EQI, respectively), however for people over 20 miles from a hospital, median survival was higher in the best (4.2 years) vs worst (3.4 years) EQI. This association held across different rural/urban categories and age groups. These results demonstrate the importance of considering multiple factors when studying ESRD survival and future efforts should consider additional components of the broader environment.}, number={3}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Kosnik, Marissa B. and Reif, David M. and Lobdell, Danelle T. and Astell-Burt, Thomas and Feng, Xiaoqi and Hader, John D. and Hoppin, Jane A.}, editor={Cheungpasitporn, WisitEditor}, year={2019}, month={Mar} }
 @article{kosnik_reif_2019, title={Determination of chemical-disease risk values to prioritize connections between environmental factors, genetic variants, and human diseases}, volume={379}, url={https://doi.org/10.1016/j.taap.2019.114674}, DOI={10.1016/j.taap.2019.114674}, abstractNote={Traditional methods for chemical risk assessment are too time-consuming and resource-intensive to characterize either the diversity of chemicals to which humans are exposed or how that diversity may manifest in population susceptibility differences. The advent of novel toxicological data sources and their integration with bioinformatic databases affords opportunities for modern approaches that consider gene-environment (GxE) interactions in population risk assessment. Here, we present an approach that systematically links multiple data sources to relate chemical risk values to diseases and gene-disease variants. These data sources include high-throughput screening (HTS) results from Tox21/ToxCast, chemical-disease relationships from the Comparative Toxicogenomics Database (CTD), hazard data from resources like the Integrated Risk Information System, exposure data from the ExpoCast initiative, and gene-variant-disease information from the DisGeNET database. We use these integrated data to identify variants implicated in chemical-disease enrichments and develop a new value that estimates the risk of these associations toward differential population responses. Finally, we use this value to prioritize chemical-disease associations by exploring the genomic distribution of variants implicated in high-risk diseases. We offer this modular approach, termed DisQGOS (Disease Quotient Genetic Overview Score), for relating overall chemical-disease risk to potential for population variable responses, as a complement to methods aiming to modernize aspects of risk assessment.}, journal={Toxicology and Applied Pharmacology}, publisher={Elsevier BV}, author={Kosnik, Marissa B. and Reif, David M.}, year={2019}, month={Sep}, pages={114674} }
 @article{kosnik_planchart_marvel_reif_mattingly_2019, title={Integration of curated and high-throughput screening data to elucidate environmental influences on disease pathways}, volume={12}, ISSN={2468-1113}, url={http://dx.doi.org/10.1016/j.comtox.2019.100094}, DOI={10.1016/j.comtox.2019.100094}, abstractNote={Addressing the complex relationship between public health and environmental exposure requires multiple types and sources of data. An important source of chemical data derives from high-throughput screening (HTS) efforts, such as the Tox21/ToxCast program, which aim to identify chemical hazard using primarily in vitro assays to probe toxicity. While most of these assays target specific genes, assessing the disease-relevance of these assays remains challenging. Integration with additional data sets may help to resolve these questions by providing broader context for individual assay results. The Comparative Toxicogenomics Database (CTD), a publicly available database that builds networks of chemical, gene, and disease information from manually curated literature sources, offers a promising solution for contextual integration with HTS data. Here, we tested the value of integrating data across Tox21/ToxCast and CTD by linking elements common to both databases (i.e., assays, genes, and chemicals). Using polymarcine and Parkinson’s disease as a case study, we found that their union significantly increased chemical-gene associations and disease-pathway coverage. Integration also enabled new disease associations to be made with HTS assays, expanding coverage of chemical-gene data associated with diseases. We demonstrate how integration enables development of predictive adverse outcome pathways using 4-nonylphenol, branched as an example. Thus, we demonstrate enhancements to each data source through database integration, including scenarios where HTS data can efficiently probe chemical space that may be understudied in the literature, as well as how CTD can add biological context to those results.}, journal={Computational Toxicology}, publisher={Elsevier BV}, author={Kosnik, Marissa B. and Planchart, Antonio and Marvel, Skylar W. and Reif, David M. and Mattingly, Carolyn J.}, year={2019}, month={Nov}, pages={100094} }
 @article{to_truong_edwards_tanguay_reif_2019, title={Multivariate modeling of engineered nanomaterial features associated with developmental toxicity}, volume={16}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85074781270&partnerID=MN8TOARS}, DOI={10.1016/j.impact.2019.100185}, abstractNote={Despite the increasing prevalence of engineered nanomaterials (ENMs) in consumer products, their toxicity profiles remain to be elucidated. ENM physicochemical characteristics (PCC) are known to influence ENM behavior, however the mechanisms of these effects have not been quantified. Further confounding the question of how the PCC influence behavior is the inclusion of structural and molecular descriptors in modeling schema that minimize the effects of PCC on the toxicological endpoints. In this work, we analyze ENM physico-chemical measurements that have not previously been studied within a developmental toxicity framework using an embryonic zebrafish model. In testing a panel of diverse ENMs to build a consensus model, we found nonlinear relationships between any singular PCC and bioactivity. By using a machine learning (ML) method to characterize the information content of combinatorial PCC sets, we found that concentration, surface area, shape, and polydispersity can accurately capture the developmental toxicity profile of ENMs with consideration to whole-organism effects.}, journal={NanoImpact}, author={To, K.T. and Truong, L. and Edwards, S. and Tanguay, R.L. and Reif, D.M.}, year={2019} }
 @article{burnett_blanchette_grimm_house_reif_wright_chiu_rusyn_2019, title={Population-based toxicity screening in human induced pluripotent stem cell-derived cardiomyocytes}, volume={381}, url={http://dx.doi.org/10.1016/j.taap.2019.114711}, DOI={10.1016/j.taap.2019.114711}, abstractNote={The potential for cardiotoxicity is carefully evaluated for pharmaceuticals, as it is a major safety liability. However, environmental chemicals are seldom tested for their cardiotoxic potential. Moreover, there is a large variability in both baseline and drug-induced cardiovascular risk in humans, but data are lacking on the degree to which susceptibility to chemically-induced cardiotoxicity may also vary. Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes have become an important in vitro model for drug screening. Thus, we hypothesized that a population-based model of iPSC-derived cardiomyocytes from a diverse set of individuals can be used to assess potential hazard and inter-individual variability in chemical effects on these cells. We conducted concentration-response screening of 134 chemicals (pharmaceuticals, industrial and environmental chemicals and food constituents) in iPSC-derived cardiomyocytes from 43 individuals, comprising both sexes and diverse ancestry. We measured kinetic calcium flux and conducted high-content imaging following chemical exposure, and utilized a panel of functional and cytotoxicity parameters in concentration-response for each chemical and donor. We show reproducible inter-individual variability in both baseline and chemical-induced effects on iPSC-derived cardiomyocytes. Further, chemical-specific variability in potency and degree of population variability were quantified. This study shows the feasibility of using an organotypic population-based human in vitro model to quantitatively assess chemicals for which little cardiotoxicity information is available. Ultimately, these results advance in vitro toxicity testing methodologies by providing an innovative tool for population-based cardiotoxicity screening, contributing to the paradigm shift from traditional animal models of toxicity to in vitro toxicity testing methods.}, journal={Toxicology and Applied Pharmacology}, author={Burnett, S.D. and Blanchette, A.D. and Grimm, F.A. and House, J.S. and Reif, D.M. and Wright, F.A. and Chiu, W.A. and Rusyn, I.}, year={2019}, month={Oct} }
 @article{gillera_marinello_horman_phillips_ruis_stapleton_reif_patisaul_2019, title={Sex-specific effects of perinatal FireMaster® 550 (FM 550) exposure on socioemotional behavior in prairie voles}, volume={79}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85075415752&partnerID=MN8TOARS}, DOI={10.1016/j.ntt.2019.106840}, abstractNote={The rapidly rising incidence of neurodevelopmental disorders with social deficits is raising concern that developmental exposure to environmental contaminants may be contributory. Firemaster 550 (FM 550) is one of the most prevalent flame-retardant (FR) mixtures used in foam-based furniture and baby products and contains both brominated and organophosphate components. We and others have published evidence of developmental neurotoxicity and sex specific effects of FM 550 on anxiety-like and exploratory behaviors. Using a prosocial animal model, we investigated the impact of perinatal FM 550 exposure on a range of socioemotional behaviors including anxiety, attachment, and memory. Virtually unknown to toxicologists, but widely used in the behavioral neurosciences, the prairie vole (Microtus ochrogaster) is a uniquely valuable model organism for examining environmental factors on sociality because this species is spontaneously prosocial, biparental, and displays attachment behaviors including pair bonding. Dams were exposed to 0, 500, 1000, or 2000 μg of FM 550 via subcutaneous (sc) injections throughout gestation, and pups were directly exposed beginning the day after birth until weaning. Adult offspring of both sexes were then subjected to multiple tasks including open field, novel object recognition, and partner preference. Effects were dose responsive and sex-specific, with females more greatly affected. Exposure-related outcomes in females included elevated anxiety, decreased social interaction, decreased exploratory motivation, and aversion to novelty. Exposed males also had social deficits, with males in all three dose groups failing to show a partner preference. Our studies demonstrate the utility of the prairie vole for investigating the impact of chemical exposures on social behavior and support the hypothesis that developmental FR exposure impacts the social brain. Future studies will probe the possible mechanisms by which these effects arise.}, journal={Neurotoxicology and Teratology}, publisher={Elsevier BV}, author={Gillera, Sagi Enicole A. and Marinello, William P. and Horman, Brian M. and Phillips, Allison L. and Ruis, Matthew T. and Stapleton, Heather M. and Reif, David M. and Patisaul, Heather B.}, year={2019}, pages={106840} }
 @article{roell_havener_reif_jack_mcleod_wiltshire_motsinger-reif_2019, title={Synergistic Chemotherapy Drug Response Is a Genetic Trait in Lymphoblastoid Cell Lines}, volume={10}, ISSN={["1664-8021"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85074258240&partnerID=MN8TOARS}, DOI={10.3389/fgene.2019.00829}, abstractNote={Lymphoblastoid cell lines (LCLs) are a highly successful model for evaluating the genetic etiology of cancer drug response, but applications using this model have typically focused on single drugs. Combination therapy is quite common in modern chemotherapy treatment since drugs often work synergistically, and it is an important progression in the use of the LCL model to expand work for drug combinations. In the present work, we demonstrate that synergy occurs and can be quantified in LCLs across a range of clinically important drug combinations. Lymphoblastoid cell lines have been commonly employed in association mapping in cancer pharmacogenomics, but it is so far untested as to whether synergistic effects have a genetic etiology. Here we use cell lines from extended pedigrees to demonstrate that there is a substantial heritable component to synergistic drug response. Additionally, we perform linkage mapping in these pedigrees to identify putative regions linked to this important phenotype. This demonstration supports the premise of expanding the use of the LCL model to perform association mapping for combination therapies.}, journal={FRONTIERS IN GENETICS}, author={Roell, Kyle R. and Havener, Tammy M. and Reif, David M. and Jack, John and McLeod, Howard L. and Wiltshire, Tim and Motsinger-Reif, Alison A.}, year={2019}, month={Oct} }
 @article{truong_zaikova_baldock_balik-meisner_to_reif_kennedy_hutchison_tanguay_2019, title={Systematic determination of the relationship between nanoparticle core diameter and toxicity for a series of structurally analogous gold nanoparticles in zebrafish}, volume={4}, url={https://doi.org/10.1080/17435390.2019.1592259}, DOI={10.1080/17435390.2019.1592259}, abstractNote={Abstract Predictive models for the impact of nanomaterials on biological systems remain elusive. Although there is agreement that physicochemical properties (particle diameter, shape, surface chemistry, and core material) influence toxicity, there are limited and often contradictory, data relating structure to toxicity, even for core diameter. Given the importance of size in determining nanoscale properties, we aimed to address this data gap by examining the biological effects of a defined series of gold nanoparticles (AuNPs) on zebrafish embryos. Five AuNPs samples with narrowly spaced core diameters (0.8–5.8 nm) were synthesized and functionalized with positively charged N,N,N-trimethylammonium ethanethiol (TMAT) ligands. We assessed the bioactivity of these NPs in a high-throughput developmental zebrafish assay at eight concentrations (0.5–50 µg/mL) and observed core diameter-dependent bioactivity. The smaller diameter AuNPs were the most toxic when expressing exposures based on an equal mass. However, when expressing exposures based on total surface area, toxicity was independent of the core diameter. When holding the number of nanoparticles per volume constant (at 6.71 × 1013/mL) in the exposure medium across AuNPs diameters, only the 5.8 nm AuNPs exhibited toxic effects. Under these exposure conditions, the uptake of AuNPs in zebrafish was only weakly associated with core diameter, suggesting that differential uptake of TMAT-AuNPs was not responsible for toxicity associated with the 5.8 nm core diameter. Our results indicate that larger NPs may be the most toxic on a per particle basis and highlight the importance of using particle number and surface area, in addition to mass, when evaluating the size-dependent bioactivity of NPs.}, journal={Nanotoxicology}, author={Truong, Lisa and Zaikova, Tatiana and Baldock, Brandi L and Balik-Meisner, Michele and To, Kimberly and Reif, David M and Kennedy, Zachary C and Hutchison, James E and Tanguay, Robert L}, year={2019}, pages={1—15} }
 @article{to_fry_reif_2018, title={Characterizing the effects of missing data and evaluating imputation methods for chemical prioritization applications using ToxPi}, volume={11}, ISSN={["1756-0381"]}, url={https://doi.org/10.1186/s13040-018-0169-5}, DOI={10.1186/s13040-018-0169-5}, abstractNote={The Toxicological Priority Index (ToxPi) is a method for prioritization and profiling of chemicals that integrates data from diverse sources. However, individual data sources ("assays"), such as in vitro bioassays or in vivo study endpoints, often feature sections of missing data, wherein subsets of chemicals have not been tested in all assays. In order to investigate the effects of missing data and recommend solutions, we designed simulation studies around high-throughput screening data generated by the ToxCast and Tox21 programs on chemicals highlighted by the Agency for Toxic Substances and Disease Registry's (ATSDR) Substance Priority List (SPL), which helps prioritize environmental research and remediation resources.Our simulations explored a wide range of scenarios concerning data (0-80% assay data missing per chemical), modeling (ToxPi models containing from 160-700 different assays), and imputation method (k-Nearest-Neighbor, Max, Mean, Min, Binomial, Local Least Squares, and Singular Value Decomposition). We find that most imputation methods result in significant changes to ToxPi score, except for datasets with a small number of assays. If we consider rank change conditional on these significant changes to ToxPi score, we find that ranks of chemicals in the minimum value imputation, SVD imputation, and kNN imputation sets are more sensitive to the score changes.We found that the choice of imputation strategy exerted significant influence over both scores and associated ranks, and the most sensitive scenarios were those involving fewer assays plus higher proportions of missing data. By characterizing the effects of missing data and the relative benefit of imputation approaches across real-world data scenarios, we can augment confidence in the robustness of decisions regarding the health and ecological effects of environmental chemicals.}, number={1}, journal={BIODATA MINING}, publisher={Springer Science and Business Media LLC}, author={To, Kimberly T. and Fry, Rebecca C. and Reif, David M.}, year={2018}, month={Jun} }
 @article{mahapatra_franzosa_roell_kuenemann_houck_reif_fourches_kullman_2018, title={Confirmation of high-throughput screening data and novel mechanistic insights into VDR-xenobiotic interactions by orthogonal assays}, volume={8}, ISSN={2045-2322}, url={http://dx.doi.org/10.1038/S41598-018-27055-3}, DOI={10.1038/s41598-018-27055-3}, abstractNote={Abstract}, number={1}, journal={Scientific Reports}, publisher={Springer Science and Business Media LLC}, author={Mahapatra, Debabrata and Franzosa, Jill A. and Roell, Kyle and Kuenemann, Melaine Agnes and Houck, Keith A. and Reif, David M. and Fourches, Denis and Kullman, Seth W.}, year={2018}, month={Jun} }
 @article{balik-meisner_truong_scholl_la_tanguay_reif_2018, title={Elucidating Gene-by-Environment Interactions Associated with Differential Susceptibility to Chemical Exposure.}, volume={6}, url={http://europepmc.org/abstract/med/29968567}, DOI={10.1289/ehp2662}, abstractNote={Background: Modern societies are exposed to vast numbers of potentially hazardous chemicals. Despite demonstrated linkages between chemical exposure and severe health effects, there are limited, often conflicting, data on how adverse health effects of exposure differ across individuals. Objectives: We tested the hypothesis that population variability in response to certain chemicals could elucidate a role for gene–environment interactions (GxE) in differential susceptibility. Methods: High-throughput screening (HTS) data on thousands of chemicals in genetically heterogeneous zebrafish were leveraged to identify a candidate chemical (Abamectin) with response patterns indicative of population susceptibility differences. We tested the prediction by generating genome-wide sequence data for 276 individual zebrafish displaying susceptible (Affected) vs. resistant (Unaffected) phenotypes following identical chemical exposure. Results: We found GxE associated with differential susceptibility in the sox7 promoter region and then confirmed gene expression differences between phenotypic response classes. Conclusions: The results for Abamectin in zebrafish demonstrate that GxE associated with naturally occurring, population genetic variation play a significant role in mediating individual response to chemical exposure. https://doi.org/10.1289/EHP2662}, number={6}, journal={Environmental health perspectives}, author={Balik-Meisner, M and Truong, L and Scholl, EH and La, Du JK and Tanguay, RL and Reif, DM}, year={2018}, month={Jun} }
 @article{baptissart_lamb_to_bradish_tehrani_reif_cowley_2018, title={Neonatal mice exposed to a high-fat diet in utero influence the behaviour of their nursing dam}, volume={285}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85056612433&partnerID=MN8TOARS}, DOI={10.1098/rspb.2018.1237}, abstractNote={
            The behaviour of a nursing dam influences the development, physiology, and behaviour of her offspring. Maternal behaviours can be modulated both by environmental factors, including diet, and by physical or behavioural characteristics of the offspring. In most studies of the effects of the environment on maternal behaviour, F
            0
            dams nurse their own F
            1
            offspring. Because the F
            1
            are indirectly exposed to the environmental stressor
            in utero
            in these studies, it is not possible to differentiate between effects on maternal behaviour from direct exposure of the dam and those mediated by changes in the F
            1
            as a consequence of
            in utero
            exposure. In this study, we used a mouse model of high-fat (HF) diet feeding, which has been shown to influence maternal behaviours, combined with cross-fostering to discriminate between these effects. We tested whether the diet of the F
            0
            dam or the exposure experienced by the F
            1
            pups
            in utero
            is the most significant predictor of maternal behaviour. Neither factor significantly influenced pup retrieval behaviours. However, strikingly, F
            1
            in utero
            exposure was a significant predictor of maternal behaviour in the 15 min immediately following pup retrieval while F
            0
            diet had no discernable effect. Our findings suggest that
            in utero
            exposure to HF diet programmes physiological changes in the offspring which influence the maternal behaviours of their dam after birth.
          }, number={1891}, journal={Proceedings of the Royal Society B: Biological Sciences}, publisher={The Royal Society}, author={Baptissart, M. and Lamb, H.E. and To, K. and Bradish, C. and Tehrani, J. and Reif, David and Cowley, M.}, year={2018}, pages={20181237} }
 @article{balik-meisner_truong_scholl_tanguay_reif_2018, title={Population genetic diversity in zebrafish lines}, volume={29}, ISSN={["1432-1777"]}, url={https://doi.org/10.1007/s00335-018-9735-x}, DOI={10.1007/s00335-018-9735-x}, abstractNote={Toxicological and pharmacological researchers have seized upon the many benefits of zebrafish, including the short generation time, well-characterized development, and early maturation as clear embryos. A major difference from many model organisms is that standard husbandry practices in zebrafish are designed to maintain population diversity. While this diversity is attractive for translational applications in human and ecological health, it raises critical questions on how interindividual genetic variation might contribute to chemical exposure or disease susceptibility differences. Findings from pooled samples of zebrafish support this supposition of diversity yet cannot directly measure allele frequencies for reference versus alternate alleles. Using the Tanguay lab Tropical 5D zebrafish line (T5D), we performed whole genome sequencing on a large group (n = 276) of individual zebrafish embryos. Paired-end reads were collected on an Illumina 3000HT, then aligned to the most recent zebrafish reference genome (GRCz10). These data were used to compare observed population genetic variation across species (humans, mice, zebrafish), then across lines within zebrafish. We found more single nucleotide polymorphisms (SNPs) in T5D than have been reported in SNP databases for any of the WIK, TU, TL, or AB lines. We theorize that some subset of the novel SNPs may be shared with other zebrafish lines but have not been identified in other studies due to the limitations of capturing population diversity in pooled sequencing strategies. We establish T5D as a model that is representative of diversity levels within laboratory zebrafish lines and demonstrate that experimental design and analysis can exert major effects when characterizing genetic diversity in heterogeneous populations.}, number={1-2}, journal={MAMMALIAN GENOME}, publisher={Springer Science and Business Media LLC}, author={Balik-Meisner, Michele and Truong, Lisa and Scholl, Elizabeth H. and Tanguay, Robert L. and Reif, David M.}, year={2018}, month={Feb}, pages={90–100} }
 @article{marvel_to_grimm_wright_rusyn_reif_2018, title={ToxPi Graphical User Interface 2.0: Dynamic exploration, visualization, and sharing of integrated data models.}, volume={3}, url={http://europepmc.org/abstract/med/29506467}, DOI={10.1186/s12859-018-2089-2}, abstractNote={Drawing integrated conclusions from diverse source data requires synthesis across multiple types of information. The ToxPi (Toxicological Prioritization Index) is an analytical framework that was developed to enable integration of multiple sources of evidence by transforming data into integrated, visual profiles. Methodological improvements have advanced ToxPi and expanded its applicability, necessitating a new, consolidated software platform to provide functionality, while preserving flexibility for future updates.We detail the implementation of a new graphical user interface for ToxPi (Toxicological Prioritization Index) that provides interactive visualization, analysis, reporting, and portability. The interface is deployed as a stand-alone, platform-independent Java application, with a modular design to accommodate inclusion of future analytics. The new ToxPi interface introduces several features, from flexible data import formats (including legacy formats that permit backward compatibility) to similarity-based clustering to options for high-resolution graphical output.We present the new ToxPi interface for dynamic exploration, visualization, and sharing of integrated data models. The ToxPi interface is freely-available as a single compressed download that includes the main Java executable, all libraries, example data files, and a complete user manual from http://toxpi.org .}, number={1}, journal={BMC bioinformatics}, author={Marvel, SW and To, K and Grimm, FA and Wright, FA and Rusyn, I and Reif, DM}, year={2018}, month={Mar} }
 @article{chiu_guyton_martin_reif_rusyn_2018, title={Use of high-throughput in vitro toxicity screening data in cancer hazard evaluations by IARC Monograph Working Groups.}, volume={35}, url={http://europepmc.org/abstract/med/28738424}, DOI={10.14573/altex.1703231}, abstractNote={Evidence regarding carcinogenic mechanisms serves a critical role in International Agency for Research on Cancer (IARC) Monograph evaluations. Three recent IARC Working Groups pioneered inclusion of the US Environmental Protection Agency (EPA) ToxCast program high-throughput screening (HTS) data to supplement other mechanistic evidence. In Monograph V110, HTS profiles were compared between perfluorooctanoic acid (PFOA) and prototypical activators across multiple nuclear receptors. For Monograph V112-113, HTS assays were mapped to 10 key characteristics of carcinogens identified by an IARC expert group, and systematically considered as an additional mechanistic data stream. Both individual assay results and ToxPi-based rankings informed mechanistic evaluations. Activation of multiple nuclear receptors in HTS assays showed that PFOA targets not only peroxisome proliferator activated receptors, but also other receptors. ToxCast assays substantially covered 5 of 10 key characteristics, corroborating literature evidence of "induces oxidative stress" and "alters cell proliferation, cell death or nutrient supply" and filling gaps for "modulates receptor-mediated effects." Thus, ToxCast HTS data were useful both in evaluating specific mechanistic hypotheses and in contributing to the overall evaluation of mechanistic evidence. However, additional HTS assays are needed to provide more comprehensive coverage of the 10 key characteristics of carcinogens that form the basis of current IARC mechanistic evaluations.}, number={1}, journal={ALTEX}, author={Chiu, WA and Guyton, KZ and Martin, MT and Reif, DM and Rusyn, I}, year={2018}, pages={51–64} }
 @article{zhang_truong_tanguay_reif_2017, title={A New Statistical Approach to Characterize Chemical-Elicited Behavioral Effects in High-Throughput Studies Using Zebrafish}, volume={12}, ISSN={["1932-6203"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85010006539&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0169408}, abstractNote={Zebrafish have become an important alternative model for characterizing chemical bioactivity, partly due to the efficiency at which systematic, high-dimensional data can be generated. However, these new data present analytical challenges associated with scale and diversity. We developed a novel, robust statistical approach to characterize chemical-elicited effects in behavioral data from high-throughput screening (HTS) of all 1,060 Toxicity Forecaster (ToxCast™) chemicals across 5 concentrations at 120 hours post-fertilization (hpf). Taking advantage of the immense scale of data for a global view, we show that this new approach reduces bias introduced by extreme values yet allows for diverse response patterns that confound the application of traditional statistics. We have also shown that, as a summary measure of response for local tests of chemical-associated behavioral effects, it achieves a significant reduction in coefficient of variation compared to many traditional statistical modeling methods. This effective increase in signal-to-noise ratio augments statistical power and is observed across experimental periods (light/dark conditions) that display varied distributional response patterns. Finally, we integrated results with data from concomitant developmental endpoint measurements to show that appropriate statistical handling of HTS behavioral data can add important biological context that informs mechanistic hypotheses.}, number={1}, journal={PLOS ONE}, author={Zhang, Guozhu and Truong, Lisa and Tanguay, Robert L. and Reif, David M.}, editor={Neuhauss, Stephan C.F.Editor}, year={2017}, month={Jan} }
 @article{zhang_roell_truong_tanguay_reif_2017, title={A data-driven weighting scheme for multivariate phenotypic endpoints recapitulates zebrafish developmental cascades}, volume={314}, ISSN={["1096-0333"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85006964010&partnerID=MN8TOARS}, DOI={10.1016/j.taap.2016.11.010}, abstractNote={Zebrafish have become a key alternative model for studying health effects of environmental stressors, partly due to their genetic similarity to humans, fast generation time, and the efficiency of generating high-dimensional systematic data. Studies aiming to characterize adverse health effects in zebrafish typically include several phenotypic measurements (endpoints). While there is a solid biomedical basis for capturing a comprehensive set of endpoints, making summary judgments regarding health effects requires thoughtful integration across endpoints. Here, we introduce a Bayesian method to quantify the informativeness of 17 distinct zebrafish endpoints as a data-driven weighting scheme for a multi-endpoint summary measure, called weighted Aggregate Entropy (wAggE). We implement wAggE using high-throughput screening (HTS) data from zebrafish exposed to five concentrations of all 1060 ToxCast chemicals. Our results show that our empirical weighting scheme provides better performance in terms of the Receiver Operating Characteristic (ROC) curve for identifying significant morphological effects and improves robustness over traditional curve-fitting approaches. From a biological perspective, our results suggest that developmental cascade effects triggered by chemical exposure can be recapitulated by analyzing the relationships among endpoints. Thus, wAggE offers a powerful approach for analysis of multivariate phenotypes that can reveal underlying etiological processes.}, journal={TOXICOLOGY AND APPLIED PHARMACOLOGY}, publisher={Elsevier BV}, author={Zhang, Guozhu and Roell, Kyle R. and Truong, Lisa and Tanguay, Robert L. and Reif, David M.}, year={2017}, month={Jan}, pages={109–117} }
 @article{roell_reif_motsinger-reif_2017, title={An introduction to terminology and methodology of chemical synergy-perspectives from across disciplines}, volume={8}, url={https://doi.org/10.3389/fphar.2017.00158}, DOI={10.3389/fphar.2017.00158}, abstractNote={The idea of synergistic interactions between drugs and chemicals has been an important issue in the biomedical world for over a century. As complex diseases, especially cancer, are being treated with various drug cocktails, understanding the interactions among these drugs is increasingly vital to ensuring successful treatment regimens. However, the idea of synergy is not limited to only the biomedical realm and these ideas have developed across many different disciplines, as well. In this review, we first discuss the various terminology surrounding the idea of synergy, providing a comprehensive list of terms defined across numerous disciplines. We then review the most common methodology for detection and quantification of synergy, including the two most prominent reference models for describing additive interactions: Loewe Additivity and Bliss Independence. We also discuss advantages and limitations to each method, with a focus on the Chou-Talalay Combination Index method. Finally, we describe how methods development and terminology have developed among disciplines outside of biomedicine and pharmacology, to synthesize the literature for readers.}, number={APR}, journal={Frontiers in Pharmacology}, publisher={Frontiers Media SA}, author={Roell, Kyle R. and Reif, David M. and Motsinger-Reif, Alison A.}, year={2017}, month={Apr} }
 @misc{roell_reif_motsinger-reif_2017, title={An introduction to terminology and methodology of chemical synergy-perspectives from across disciplines}, volume={8}, journal={Frontiers in Pharmacology}, author={Roell, K. R. and Reif, D. M. and Motsinger-Reif, A. A.}, year={2017} }
 @article{tilley_reif_fry_2017, title={Incorporating ToxCast and Tox21 datasets to rank biological activity of chemicals at Superfund sites in North Carolina}, volume={101}, ISSN={["1873-6750"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85011060806&partnerID=MN8TOARS}, DOI={10.1016/j.envint.2016.10.006}, abstractNote={The Superfund program of the Environmental Protection Agency (EPA) was established in 1980 to address public health concerns posed by toxic substances released into the environment in the United States. Forty-two of the 1328 hazardous waste sites that remain on the Superfund National Priority List are located in the state of North Carolina.We set out to develop a database that contained information on both the prevalence and biological activity of chemicals present at Superfund sites in North Carolina. A chemical characterization tool, the Toxicological Priority Index (ToxPi), was used to rank the biological activity of these chemicals based on their predicted bioavailability, documented associations with biological pathways, and activity in in vitro assays of the ToxCast and Tox21 programs.The ten most prevalent chemicals found at North Carolina Superfund sites were chromium, trichloroethene, lead, tetrachloroethene, arsenic, benzene, manganese, 1,2-dichloroethane, nickel, and barium. For all chemicals found at North Carolina Superfund sites, ToxPi analysis was used to rank their biological activity. Through this data integration, residual pesticides and organic solvents were identified to be some of the most highly-ranking predicted bioactive chemicals. This study provides a novel methodology for creating state or regional databases of biological activity of contaminants at Superfund sites.These data represent a novel integrated profile of the most prevalent chemicals at North Carolina Superfund sites. This information, and the associated methodology, is useful to toxicologists, risk assessors, and the communities living in close proximity to these sites.}, journal={ENVIRONMENT INTERNATIONAL}, publisher={Elsevier BV}, author={Tilley, Sloane K. and Reif, David M. and Fry, Rebecca C.}, year={2017}, month={Apr}, pages={19–26} }
 @article{zhang_truong_tanguay_reif_2017, title={Integrating Morphological and Behavioral Phenotypes in Developing Zebrafish}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85019952490&partnerID=MN8TOARS}, DOI={10.1007/978-3-319-33774-6_12}, journal={The rights and wrongs of zebrafish: Behavioral phenotyping of zebrafish}, publisher={Springer International Publishing}, author={Zhang, Guozhu and Truong, Lisa and Tanguay, Robert L. and Reif, David M.}, year={2017}, pages={259–272} }
 @article{knecht_truong_marvel_reif_garcia_lu_simbnich_teeguarden_tanguay_2017, title={Transgenerational inheritance of neurobehavioral and physiological deficits from developmental exposure to benzo[a]pyrene in zebrafish}, volume={329}, ISSN={["1096-0333"]}, url={http://europepmc.org/abstract/med/28583304}, DOI={10.1016/j.taap.2017.05.033}, abstractNote={Benzo[a]pyrene (B[a]P) is a well-known genotoxic polycylic aromatic compound whose toxicity is dependent on signaling via the aryl hydrocarbon receptor (AHR). It is unclear to what extent detrimental effects of B[a]P exposures might impact future generations and whether transgenerational effects might be AHR-dependent. This study examined the effects of developmental B[a]P exposure on 3 generations of zebrafish. Zebrafish embryos were exposed from 6 to 120 h post fertilization (hpf) to 5 and 10 μM B[a]P and raised in chemical-free water until adulthood (F0). Two generations were raised from F0 fish to evaluate transgenerational inheritance. Morphological, physiological and neurobehavioral parameters were measured at two life stages. Juveniles of the F0 and F2 exhibited hyper locomotor activity, decreased heartbeat and mitochondrial function. B[a]P exposure during development resulted in decreased global DNA methylation levels and generally reduced expression of DNA methyltransferases in wild type zebrafish, with the latter effect largely reversed in an AHR2-null background. Adults from the F0 B[a]P exposed lineage displayed social anxiety-like behavior. Adults in the F2 transgeneration manifested gender-specific increased body mass index (BMI), increased oxygen consumption and hyper-avoidance behavior. Exposure to benzo[a]pyrene during development resulted in transgenerational inheritance of neurobehavioral and physiological deficiencies. Indirect evidence suggested the potential for an AHR2-dependent epigenetic route.}, journal={TOXICOLOGY AND APPLIED PHARMACOLOGY}, author={Knecht, Andrea L. and Truong, Lisa and Marvel, Skylar W. and Reif, David M. and Garcia, Abraham and Lu, Catherine and Simbnich, Michael T. and Teeguarden, Justin G. and Tanguay, Robert L.}, year={2017}, month={Aug}, pages={148–157} }
 @article{grimm_iwata_sirenko_chappell_wright_reif_braisted_gerhold_yeakley_shepard_et al._2016, title={A chemical-biological similarity-based grouping of complex substances as a prototype approach for evaluating chemical alternatives}, volume={18}, ISSN={["1463-9270"]}, url={http://europepmc.org/abstract/med/28035192}, DOI={10.1039/c6gc01147k}, abstractNote={An experimental and computational approach to categorizing UVCBs according to chemical and biological similarities.}, number={16}, journal={GREEN CHEMISTRY}, author={Grimm, Fabian A. and Iwata, Yasuhiro and Sirenko, Oksana and Chappell, Grace A. and Wright, Fred A. and Reif, David M. and Braisted, John and Gerhold, David L. and Yeakley, Joanne M. and Shepard, Peter and et al.}, year={2016}, pages={4407–4419} }
 @article{grondin_davis_wiegers_king_wiegers_reif_hoppin_mattingly_2016, title={Advancing Exposure Science through Chemical Data Curation and Integration in the Comparative Toxicogenomics Database}, volume={124}, ISSN={0091-6765 1552-9924}, url={http://dx.doi.org/10.1289/EHP174}, DOI={10.1289/ehp174}, abstractNote={Background: Exposure science studies the interactions and outcomes between environmental stressors and human or ecological receptors. To augment its role in understanding human health and the exposome, we aimed to centralize and integrate exposure science data into the broader biological framework of the Comparative Toxicogenomics Database (CTD), a public resource that promotes understanding of environmental chemicals and their effects on human health. Objectives: We integrated exposure data within the CTD to provide a centralized, freely available resource that facilitates identification of connections between real-world exposures, chemicals, genes/proteins, diseases, biological processes, and molecular pathways. Methods: We developed a manual curation paradigm that captures exposure data from the scientific literature using controlled vocabularies and free text within the context of four primary exposure concepts: stressor, receptor, exposure event, and exposure outcome. Using data from the Agricultural Health Study, we have illustrated the benefits of both centralization and integration of exposure information with CTD core data. Results: We have described our curation process, demonstrated how exposure data can be accessed and analyzed in the CTD, and shown how this integration provides a broad biological context for exposure data to promote mechanistic understanding of environmental influences on human health. Conclusions: Curation and integration of exposure data within the CTD provides researchers with new opportunities to correlate exposures with human health outcomes, to identify underlying potential molecular mechanisms, and to improve understanding about the exposome. Citation: Grondin CJ, Davis AP, Wiegers TC, King BL, Wiegers JA, Reif DM, Hoppin JA, Mattingly CJ. 2016. Advancing exposure science through chemical data curation and integration in the Comparative Toxicogenomics Database. Environ Health Perspect 124:1592–1599; http://dx.doi.org/10.1289/EHP174}, number={10}, journal={Environmental Health Perspectives}, publisher={Environmental Health Perspectives}, author={Grondin, Cynthia J. and Davis, Allan Peter and Wiegers, Thomas C. and King, Benjamin L. and Wiegers, Jolene A. and Reif, David M. and Hoppin, Jane A. and Mattingly, Carolyn J.}, year={2016}, month={Oct}, pages={1592–1599} }
 @article{grondin_davis_wiegers_king_wiegers_reif_hoppin_mattingly_2016, title={Advancing Exposure Science through Chemical Data Curation and Integration in the Comparative Toxicogenomics Database.}, volume={10}, url={http://europepmc.org/abstract/med/27170236}, journal={Environmental health perspectives}, author={Grondin, CJ and Davis, AP and Wiegers, TC and King, BL and Wiegers, JA and Reif, DM and Hoppin, JA and Mattingly, CJ}, year={2016}, month={Oct} }
 @article{planchart_mattingly_allen_ceger_casey_hinton_kanungo_kullman_tal_bondesson_et al._2016, title={Advancing toxicology research using in vivo high throughput toxicology with small fish models}, volume={33}, ISSN={1868-596X}, url={http://dx.doi.org/10.14573/altex.1601281}, DOI={10.14573/altex.1601281}, abstractNote={Summary Small freshwater fish models, especially zebrafish, offer advantages over traditional rodent models, including low maintenance and husbandry costs, high fecundity, genetic diversity, physiology similar to that of traditional biomedical models, and reduced animal welfare concerns. The Collaborative Workshop on Aquatic Models and 21st Century Toxicology was held at North Carolina State University on May 5-6, 2014, in Raleigh, North Carolina, USA. Participants discussed the ways in which small fish are being used as models to screen toxicants and understand mechanisms of toxicity. Workshop participants agreed that the lack of standardized protocols is an impediment to broader acceptance of these models, whereas development of standardized protocols, validation, and subsequent regulatory acceptance would facilitate greater usage. Given the advantages and increasing application of small fish models, there was widespread interest in follow-up workshops to review and discuss developments in their use. In this article, we summarize the recommendations formulated by workshop participants to enhance the utility of small fish species in toxicology studies, as well as many of the advances in the field of toxicology that resulted from using small fish species, including advances in developmental toxicology, cardiovascular toxicology, neurotoxicology, and immunotoxicology. We also review many emerging issues that will benefit from using small fish species, especially zebrafish, and new technologies that will enable using these organisms to yield results unprecedented in their information content to better understand how toxicants affect development and health.}, number={4}, journal={ALTEX}, publisher={ALTEX Edition}, author={Planchart, Antonio and Mattingly, Carolyn J. and Allen, David and Ceger, Patricia and Casey, Warren and Hinton, David and Kanungo, Jyotshna and Kullman, Seth W. and Tal, Tamara and Bondesson, Maria and et al.}, year={2016}, pages={435–452} }
 @article{zhang_marvel_truong_tanguay_reif_2016, title={Aggregate entropy scoring for quantifying activity across endpoints with irregular correlation structure}, volume={62}, ISSN={["0890-6238"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84965025830&partnerID=MN8TOARS}, DOI={10.1016/j.reprotox.2016.04.012}, abstractNote={Robust computational approaches are needed to characterize systems-level responses to chemical perturbations in environmental and clinical toxicology applications. Appropriate characterization of response presents a methodological challenge when dealing with diverse phenotypic endpoints measured using in vivo systems. In this article, we propose an information-theoretic method named Aggregate Entropy (AggE) and apply it to scoring multiplexed, phenotypic endpoints measured in developing zebrafish (Danio rerio) across a broad concentration-response profile for a diverse set of 1060 chemicals. AggE accurately identified chemicals with significant morphological effects, including single-endpoint effects and multi-endpoint responses that would have been missed by univariate methods, while avoiding putative false-positives that confound traditional methods due to irregular correlation structure. By testing AggE in a variety of high-dimensional real and simulated datasets, we have characterized its performance and suggested implementation parameters that can guide its application across a wide range of experimental scenarios.}, journal={REPRODUCTIVE TOXICOLOGY}, author={Zhang, Guozhu and Marvel, Skylar and Truong, Lisa and Tanguay, Robert L. and Reif, David M.}, year={2016}, month={Jul}, pages={92–99} }
 @article{judson_houck_martin_richard_knudsen_shah_little_wambaugh_setzer_kothiya_et al._2016, title={Analysis of the Effects of Cell Stress and Cytotoxicity on In Vitro Assay Activity Across a Diverse Chemical and Assay Space.}, volume={10}, url={http://europepmc.org/abstract/med/27605417}, DOI={10.1093/toxsci/kfw148}, abstractNote={Chemical toxicity can arise from disruption of specific biomolecular functions or through more generalized cell stress and cytotoxicity-mediated processes. Here, responses of 1060 chemicals including pharmaceuticals, natural products, pesticidals, consumer, and industrial chemicals across a battery of 815 in vitro assay endpoints from 7 high-throughput assay technology platforms were analyzed in order to distinguish between these types of activities. Both cell-based and cell-free assays showed a rapid increase in the frequency of responses at concentrations where cell stress/cytotoxicity responses were observed in cell-based assays. Chemicals that were positive on at least 2 viability/cytotoxicity assays within the concentration range tested (typically up to 100 l M) activated a median of 12% of assay endpoints whereas those that were not cytotoxic in this concentration range activated 1.3% of the assays endpoints. The results suggest that activity can be broadly divided into: (1) specific biomolecular interactions against one or more targets (eg, receptors or enzymes) at concentrations below which overt cytotoxicity-associated activity is observed; and (2) activity associated with cell stress or cytotoxicity, which may result from triggering specific cell stress pathways, chemical reactivity, physico-chemical disruption of proteins or membranes, or broad low-affinity non-covalent interactions. Chemicals showing a greater number of specific biomolecular interactions are generally designed to be bioactive (pharmaceuticals or pesticidal active ingredients), whereas intentional food-use chemicals tended to show the fewest specific interactions. The analyses presented here provide context for use of these data in ongoing studies to predict in vivo toxicity from chemicals lacking extensive hazard assessment.}, number={2}, journal={Toxicological sciences : an official journal of the Society of Toxicology}, author={Judson, R. and Houck, K. and Martin, M. and Richard, A.M. and Knudsen, T.B. and Shah, I. and Little, S. and Wambaugh, J. and Setzer, R.W. and Kothiya, P. and et al.}, year={2016}, month={Oct}, pages={409–409} }
 @article{saggu_mineeva_arif_cory_haun_heacock_huber_li_nsofini_sarenac_et al._2016, title={Decoupling of a neutron interferometer from temperature gradients}, volume={87}, ISSN={0034-6748 1089-7623}, url={http://dx.doi.org/10.1063/1.4971851}, DOI={10.1063/1.4971851}, abstractNote={Neutron interferometry enables precision measurements that are typically operated within elaborate, multi-layered facilities which provide substantial shielding from environmental noise. These facilities are necessary to maintain the coherence requirements in a perfect crystal neutron interferometer which is extremely sensitive to local environmental conditions such as temperature gradients across the interferometer, external vibrations, and acoustic waves. The ease of operation and breadth of applications of perfect crystal neutron interferometry would greatly benefit from a mode of operation which relaxes these stringent isolation requirements. Here, the INDEX Collaboration and National Institute of Standards and Technology demonstrates the functionality of a neutron interferometer in vacuum and characterize the use of a compact vacuum chamber enclosure as a means to isolate the interferometer from spatial temperature gradients and time-dependent temperature fluctuations. The vacuum chamber is found to have no depreciable effect on the performance of the interferometer (contrast) while improving system stability, thereby showing that it is feasible to replace large temperature isolation and control systems with a compact vacuum enclosure for perfect crystal neutron interferometry.}, number={12}, journal={Review of Scientific Instruments}, publisher={AIP Publishing}, author={Saggu, P. and Mineeva, T. and Arif, M. and Cory, D. G. and Haun, R. and Heacock, B. and Huber, M. G. and Li, K. and Nsofini, J. and Sarenac, D. and et al.}, year={2016}, month={Dec}, pages={123507} }
 @article{judson_houck_martin_richard_knudsen_shah_little_wambaugh_setzer_kothya_et al._2016, title={Editor's Highlight: Analysis of the Effects of Cell Stress and Cytotoxicity on In Vitro Assay Activity Across a Diverse Chemical and Assay Space.}, volume={8}, url={http://europepmc.org/abstract/med/27208079}, DOI={10.1093/toxsci/kfw092}, abstractNote={Chemical toxicity can arise from disruption of specific biomolecular functions or through more generalized cell stress and cytotoxicity-mediated processes. Here, responses of 1060 chemicals including pharmaceuticals, natural products, pesticidals, consumer, and industrial chemicals across a battery of 815 in vitro assay endpoints from 7 high-throughput assay technology platforms were analyzed in order to distinguish between these types of activities. Both cell-based and cell-free assays showed a rapid increase in the frequency of responses at concentrations where cell stress/cytotoxicity responses were observed in cell-based assays. Chemicals that were positive on at least 2 viability/cytotoxicity assays within the concentration range tested (typically up to 100 μM) activated a median of 12% of assay endpoints whereas those that were not cytotoxic in this concentration range activated 1.3% of the assays endpoints. The results suggest that activity can be broadly divided into: (1) specific biomolecular interactions against one or more targets (eg, receptors or enzymes) at concentrations below which overt cytotoxicity-associated activity is observed; and (2) activity associated with cell stress or cytotoxicity, which may result from triggering specific cell stress pathways, chemical reactivity, physico-chemical disruption of proteins or membranes, or broad low-affinity non-covalent interactions. Chemicals showing a greater number of specific biomolecular interactions are generally designed to be bioactive (pharmaceuticals or pesticidal active ingredients), whereas intentional food-use chemicals tended to show the fewest specific interactions. The analyses presented here provide context for use of these data in ongoing studies to predict in vivo toxicity from chemicals lacking extensive hazard assessment.}, number={2}, journal={Toxicological sciences : an official journal of the Society of Toxicology}, author={Judson, R. and Houck, K. and Martin, M. and Richard, A.M. and Knudsen, T.B. and Shah, I. and Little, S. and Wambaugh, J. and Setzer, R.W. and Kothya, P. and et al.}, year={2016}, month={Aug}, pages={323–339} }
 @article{chialvo_che_reif_motsinger-reif_reed_2016, title={Eigenvector metabolite analysis reveals dietary effects on the association among metabolite correlation patterns, gene expression, and phenotypes}, volume={12}, ISSN={["1573-3890"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84988377963&partnerID=MN8TOARS}, DOI={10.1007/s11306-016-1117-3}, abstractNote={‘Multi-omics’ datasets obtained from an organism of interest reared under different environmental treatments are increasingly common. Identifying the links among metabolites and transcripts can help to elucidate our understanding of the impact of environment at different levels within the organism. However, many methods for characterizing physiological connections cannot address unidentified metabolites. Here, we use Eigenvector Metabolite Analysis (EvMA) to examine links between metabolomic, transcriptomic, and phenotypic variation data and to assess the impact of environmental factors on these associations. Unlike other methods, EvMA can be used to analyze datasets that include unidentified metabolites and unannotated transcripts. To demonstrate the utility of EvMA, we analyzed metabolomic, transcriptomic, and phenotypic datasets produced from 20 Drosophila melanogaster genotypes reared on four dietary treatments. We used a hierarchical distance-based method to cluster the metabolites. The links between metabolite clusters, gene expression, and overt phenotypes were characterized using the eigenmetabolite (first principal component) of each cluster. EvMA recovered chemically related groups of metabolites within the clusters. Using the eigenmetabolite, we identified genes and phenotypes that significantly correlated with each cluster. EvMA identifies new connections between the phenotypes, metabolites, and gene transcripts. EvMA provides a simple method to identify correlations between metabolites, gene expression, and phenotypes, which can allow us to partition multivariate datasets into meaningful biological modules and identify under-studied metabolites and unannotated gene transcripts that may be central to important biological processes. This can be used to inform our understanding of the effect of environmental mechanisms underlying physiological states of interest.}, number={11}, journal={METABOLOMICS}, publisher={Springer Nature}, author={Chialvo, Clare H. Scott and Che, Ronglin and Reif, David and Motsinger-Reif, Alison and Reed, Laura K.}, year={2016}, month={Nov} }
 @article{kollitz_zhang_hawkins_whitfield_reif_kullman_2016, title={Evolutionary and Functional Diversification of the Vitamin D Receptor-Lithocholic Acid Partnership}, volume={11}, ISSN={["1932-6203"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85005987339&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0168278}, abstractNote={The evolution, molecular behavior, and physiological function of nuclear receptors are of particular interest given their diverse roles in regulating essential biological processes. The vitamin D receptor (VDR) is well known for its canonical roles in calcium homeostasis and skeletal maintenance. Additionally, VDR has received an increased amount of attention due to the discovery of numerous non-calcemic functions, including the detoxification of lithocholic acid. Lithocholic acid is a toxic metabolite of chenodeoxycholic acid, a primary bile acid. The partnership between the VDR and lithocholic acid has been hypothesized to be a recent adaptation that evolved to mediate the detoxification and elimination of lithocholic acid from the gut. This partnership is speculated to be limited to higher vertebrates (birds and mammals), as lower vertebrates do not synthesize the parent compound of lithocholic acid. However, the molecular functions associated with the observed insensitivity of basal VDRs to lithocholic acid have not been explored. Here we characterize canonical nuclear receptor functions of VDRs from select species representing key nodes in vertebrate evolution and span a range of bile salt phenotypes. Competitive ligand binding assays revealed that the receptor’s affinity for lithocholic acid is highly conserved across species, suggesting that lithocholic acid affinity is an ancient and non-adaptive trait. However, transient transactivation assays revealed that lithocholic acid-mediated VDR activation might have evolved more recently, as the non-mammalian receptors did not respond to lithocholic acid unless exogenous coactivator proteins were co-expressed. Subsequent functional assays indicated that differential lithocholic acid-mediated receptor activation is potentially driven by differential protein-protein interactions between VDR and nuclear receptor coregulator proteins. We hypothesize that the vitamin D receptor-lithocholic acid partnership evolved as a by-product of natural selection on the ligand-receptor partnership between the vitamin D receptor and the native VDR ligand: 1α,25-dihydroxyvitamin D3, the biologically active metabolite of vitamin D3.}, number={12}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Kollitz, Erin M. and Zhang, Guozhu and Hawkins, Mary Beth and Whitfield, G. Kerr and Reif, David M. and Kullman, Seth W.}, editor={Zhang, ChiEditor}, year={2016}, month={Dec} }
 @article{watson_planchart_mattingly_winkler_reif_kullman_2016, title={From the Cover: Embryonic Exposure to TCDD Impacts Osteogenesis of the Axial Skeleton in Japanese medaka,Oryzias latipes}, volume={155}, ISSN={1096-6080 1096-0929}, url={http://dx.doi.org/10.1093/toxsci/kfw229}, DOI={10.1093/toxsci/kfw229}, abstractNote={Recent studies from mammalian, fish, and in vitro models have identified bone and cartilage development as sensitive targets for dioxins and other aryl hydrocarbon receptor ligands. In this study, we assess how embryonic 2,3,7,8-tetrachlorochlorodibenzo-p-dioxin (TCDD) exposure impacts axial osteogenesis in Japanese medaka (Oryzias latipes), a vertebrate model of human bone development. Embryos from inbred wild-type Orange-red Hd-dR and 3 transgenic medaka lines (twist:EGFP, osx/sp7:mCherry, col10a1:nlGFP) were exposed to 0.15 nM and 0.3 nM TCDD and reared until 20 dpf. Individuals were stained for mineralized bone and imaged using confocal microscopy to assess skeletal alterations in medial vertebrae in combination with a qualitative spatial analysis of osteoblast and osteoblast progenitor cell populations. Exposure to TCDD resulted in an overall attenuation of vertebral ossification characterized by truncated centra, and reduced neural and hemal arch lengths. Effects on mineralization were consistent with modifications in cell number and cell localization of transgene-labeled osteoblast and osteoblast progenitor cells. Endogenous expression of osteogenic regulators runt-related transcription factor 2 (runx2) and osterix (osx/sp7), and extracellular matrix genes osteopontin (spp1), collagen type I alpha I (col1), collagen type X alpha I (col10a1), and osteocalcin (bglap/osc) was significantly diminished at 20 dpf following TCDD exposure as compared with controls. Through global transcriptomic analysis more than 590 differentially expressed genes were identified and mapped to select pathological states including inflammatory disease, connective tissue disorders, and skeletal and muscular disorders. Taken together, results from this study suggest that TCDD exposure inhibits axial bone formation through dysregulation of osteoblast differentiation. This approach highlights the advantages and sensitivity of using small fish models to investigate how xenobiotic exposure may impact skeletal development.}, number={2}, journal={Toxicological Sciences}, publisher={Oxford University Press (OUP)}, author={Watson, AtLee T. D. and Planchart, Antonio and Mattingly, Carolyn J. and Winkler, Christoph and Reif, David M. and Kullman, Seth W.}, year={2016}, month={Nov}, pages={485–496} }
 @article{reif_truong_mandrell_marvel_zhang_tanguay_2016, title={High-throughput characterization of chemical-associated embryonic behavioral changes predicts teratogenic outcomes}, volume={90}, ISSN={["1432-0738"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84934783723&partnerID=MN8TOARS}, DOI={10.1007/s00204-015-1554-1}, abstractNote={New strategies are needed to address the data gap between the bioactivity of chemicals in the environment versus existing hazard information. We address whether a high-throughput screening (HTS) system using a vertebrate organism (embryonic zebrafish) can characterize chemical-elicited behavioral responses at an early, 24 hours post-fertilization (hpf) stage that predict teratogenic consequences at a later developmental stage. The system was used to generate full concentration-response behavioral profiles at 24 hpf across 1060 ToxCast™ chemicals. Detailed, morphological evaluation of all individuals was performed as experimental follow-up at 5 days post-fertilization (dpf). Chemicals eliciting behavioral responses were also mapped against external HTS in vitro results to identify specific molecular targets and neurosignalling pathways. We found that, as an integrative measure of normal development, significant alterations in movement highlighted active chemicals representing several modes of action. These early behavioral responses were predictive for 17 specific developmental abnormalities and mortality measured at 5 dpf, often at lower (i.e., more potent) concentrations than those at which morphological effects were observed. Therefore, this system can provide rapid characterization of chemical-elicited behavioral responses at an early developmental stage that are predictive of observable adverse effects later in life.}, number={6}, journal={ARCHIVES OF TOXICOLOGY}, publisher={Springer Science and Business Media LLC}, author={Reif, David M. and Truong, Lisa and Mandrell, David and Marvel, Skylar and Zhang, Guozhu and Tanguay, Robert L.}, year={2016}, month={Jun}, pages={1459–1470} }
 @article{prevatt_desmarais_janssen_2016, title={Lifetime substance use as a predictor of postpartum mental health}, volume={20}, ISSN={1434-1816 1435-1102}, url={http://dx.doi.org/10.1007/S00737-016-0694-5}, DOI={10.1007/s00737-016-0694-5}, abstractNote={Postpartum mood disorders (PPMD) affect approximately 10-20% of women and have adverse consequences for both mom and baby. Lifetime substance use has received limited attention in relation to PPMD. The present study examined associations of lifetime alcohol and drug use with postpartum mental health problems. Women (n = 100) within approximately 3 months postpartum (M = 2.01, SD = 1.32) participated in semi-structured interviews querying lifetime substance use, mental health history, and postpartum symptoms of anxiety, stress, posttraumatic stress disorder (PTSD), depression, and obsessive compulsive disorder. The study was conducted in an urban Canadian city from 2009 to 2010. Analyses revealed that lifetime substance use increased the variability explained in postpartum PTSD (p = .011), above and beyond sociodemographic characteristics and mental health history. The same trend, though not significant, was observed for stress (p = .059) and anxiety (p = .070). Lifetime drug use, specifically, was associated with postpartum stress (p = .021) and anxiety (p = .041), whereas lifetime alcohol use was not (ps ≥ .128). Findings suggest that lifetime drug use is associated with PPMD. Future research should examine whether screening for lifetime drug use during antenatal and postpartum care improves identification of women experiencing PPMD.}, number={1}, journal={Archives of Women's Mental Health}, publisher={Springer Nature}, author={Prevatt, Betty-Shannon and Desmarais, Sarah L. and Janssen, Patricia A.}, year={2016}, month={Dec}, pages={189–199} }
 @misc{auerbach_filer_reif_walker_holloway_schlezinger_srinivasan_svoboda_judson_bucher_et al._2016, title={Prioritizing Environmental Chemicals for Obesity and Diabetes Outcomes Research: A Screening Approach Using ToxCast (TM) High-Throughput Data}, volume={124}, ISSN={["1552-9924"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84980316460&partnerID=MN8TOARS}, DOI={10.1289/ehp.1510456}, abstractNote={Background: Diabetes and obesity are major threats to public health in the United States and abroad. Understanding the role that chemicals in our environment play in the development of these conditions is an emerging issue in environmental health, although identifying and prioritizing chemicals for testing beyond those already implicated in the literature is challenging. This review is intended to help researchers generate hypotheses about chemicals that may contribute to diabetes and to obesity-related health outcomes by summarizing relevant findings from the U.S. Environmental Protection Agency (EPA) ToxCast™ high-throughput screening (HTS) program. Objectives: Our aim was to develop new hypotheses around environmental chemicals of potential interest for diabetes- or obesity-related outcomes using high-throughput screening data. Methods: We identified ToxCast™ assay targets relevant to several biological processes related to diabetes and obesity (insulin sensitivity in peripheral tissue, pancreatic islet and β cell function, adipocyte differentiation, and feeding behavior) and presented chemical screening data against those assay targets to identify chemicals of potential interest. Discussion: The results of this screening-level analysis suggest that the spectrum of environmental chemicals to consider in research related to diabetes and obesity is much broader than indicated by research papers and reviews published in the peer-reviewed literature. Testing hypotheses based on ToxCast™ data will also help assess the predictive utility of this HTS platform. Conclusions: More research is required to put these screening-level analyses into context, but the information presented in this review should facilitate the development of new hypotheses. Citation: Auerbach S, Filer D, Reif D, Walker V, Holloway AC, Schlezinger J, Srinivasan S, Svoboda D, Judson R, Bucher JR, Thayer KA. 2016. Prioritizing environmental chemicals for obesity and diabetes outcomes research: a screening approach using ToxCast™ high-throughput data. Environ Health Perspect 124:1141–1154; http://dx.doi.org/10.1289/ehp.1510456}, number={8}, journal={ENVIRONMENTAL HEALTH PERSPECTIVES}, publisher={Environmental Health Perspectives}, author={Auerbach, Scott and Filer, Dayne and Reif, David and Walker, Vickie and Holloway, Alison C. and Schlezinger, Jennifer and Srinivasan, Supriya and Svoboda, Daniel and Judson, Richard and Bucher, John R. and et al.}, year={2016}, month={Aug}, pages={1141–1154} }
 @article{shah_setzer_jack_houck_judson_knudsen_liu_martin_reif_richard_et al._2016, title={Using toxcast™ data to reconstruct dynamic cell state trajectories and estimate toxicological points of departure}, volume={124}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84977090943&partnerID=MN8TOARS}, DOI={10.1289/ehp.1409029}, abstractNote={Background: High-content imaging (HCI) allows simultaneous measurement of multiple cellular phenotypic changes and is an important tool for evaluating the biological activity of chemicals. Objectives: Our goal was to analyze dynamic cellular changes using HCI to identify the “tipping point” at which the cells did not show recovery towards a normal phenotypic state. Methods: HCI was used to evaluate the effects of 967 chemicals (in concentrations ranging from 0.4 to 200 μM) on HepG2 cells over a 72-hr exposure period. The HCI end points included p53, c-Jun, histone H2A.x, α-tubulin, histone H3, alpha tubulin, mitochondrial membrane potential, mitochondrial mass, cell cycle arrest, nuclear size, and cell number. A computational model was developed to interpret HCI responses as cell-state trajectories. Results: Analysis of cell-state trajectories showed that 336 chemicals produced tipping points and that HepG2 cells were resilient to the effects of 334 chemicals up to the highest concentration (200 μM) and duration (72 hr) tested. Tipping points were identified as concentration-dependent transitions in system recovery, and the corresponding critical concentrations were generally between 5 and 15 times (25th and 75th percentiles, respectively) lower than the concentration that produced any significant effect on HepG2 cells. The remaining 297 chemicals require more data before they can be placed in either of these categories. Conclusions: These findings show the utility of HCI data for reconstructing cell state trajectories and provide insight into the adaptation and resilience of in vitro cellular systems based on tipping points. Cellular tipping points could be used to define a point of departure for risk-based prioritization of environmental chemicals. Citation: Shah I, Setzer RW, Jack J, Houck KA, Judson RS, Knudsen TB, Liu J, Martin MT, Reif DM, Richard AM, Thomas RS, Crofton KM, Dix DJ, Kavlock RJ. 2016. Using ToxCast™ data to reconstruct dynamic cell state trajectories and estimate toxicological points of departure. Environ Health Perspect 124:910–919; http://dx.doi.org/10.1289/ehp.1409029}, number={7}, journal={Environmental Health Perspectives}, author={Shah, I. and Setzer, R. Woodrow and Jack, J. and Houck, K.A. and Judson, R.S. and Knudsen, T.B. and Liu, J. and Martin, M.T. and Reif, David and Richard, A.M. and et al.}, year={2016}, pages={910–919} }
 @article{loomis_guyton_grosse_el_bouvard_benbrahim-tallaa_guha_mattock_straif_france_2015, title={Carcinogenicity of lindane, DDT, and 2,4-dichlorophenoxyacetic acid.}, volume={8}, url={http://europepmc.org/abstract/med/26111929}, DOI={10.1016/s1470-2045(15)00081-9}, abstractNote={Lancet Oncology, The - In Press.Proof corrected by the author Available online since mercredi 24 juin 2015}, journal={The Lancet. Oncology}, author={Loomis, D and Guyton, K and Grosse, Y and El, Ghissasi F and Bouvard, V and Benbrahim-Tallaa, L and Guha, N and Mattock, H and Straif, K and France}, year={2015}, month={Aug} }
 @article{ducharme_reif_gustafsson_bondesson_2015, title={Comparison of toxicity values across zebrafish early life stages and mammalian studies: Implications for chemical testing}, volume={55}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84939415843&partnerID=MN8TOARS}, DOI={10.1016/j.reprotox.2014.09.005}, abstractNote={With the high cost and slow pace of toxicity testing in mammals, the vertebrate zebrafish has become a tractable model organism for high throughput toxicity testing. We present here a meta-analysis of 600 chemicals tested for toxicity in zebrafish embryos and larvae. Nineteen aggregated and 57 individual toxicity endpoints were recorded from published studies yielding 2695 unique data points. These data points were compared to lethality and reproductive toxicology endpoints analyzed in rodents and rabbits and to exposure values for humans. We show that although many zebrafish endpoints did not correlate to rodent or rabbit acute toxicity data, zebrafish could be used to accurately predict relative acute toxicity through the rat inhalation, rabbit dermal, and rat oral exposure routes. Ranking of the chemicals based on toxicity and teratogenicity in zebrafish, as well as human exposure levels, revealed that 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), benzo(a)pyrene, and chlorpyrifos ranked in the top nine of all chemicals for these three categories, and as such should be considered high priority chemicals for testing in higher vertebrates.}, journal={Reproductive Toxicology}, author={Ducharme, N.A. and Reif, D.M. and Gustafsson, J.-A. and Bondesson, M.}, year={2015}, pages={3–10} }
 @book{meisner_reif_2015, title={Computational Methods Used in Systems Biology}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84940026164&partnerID=MN8TOARS}, DOI={10.1016/B978-0-12-801564-3.00005-5}, abstractNote={The overarching theme of systems biology is that of complex interactions between multiscale systems, so it follows that computational methods used in systems biology aim to integrate data and originate from an interdisciplinary slate of scientific fields. To deal with “omic” data generation discussed in previous chapters, suitable analysis methods for systems biology must account for measurements made across scales of time, space, and biological organization. Importantly, analysis methods must first account for the specifics (and peculiarities) of individual technology platforms. For the more established platforms, such as chip hybridization and sequencing techniques, progress in computational methods research has resulted in a trend toward standardization, where coalescence of statistical methods into powerful software packages handle early stages of analysis in a generally accepted manner. For emerging platforms, computational methods remain diffuse, although popular approaches share many statistical similarities with more mature methods. Once individual data components have been analyzed, integration into a systems framework can begin.}, journal={Systems Biology in Toxicology and Environmental Health}, author={Meisner, M. and Reif, D.M.}, year={2015}, pages={85–115} }
 @article{george_reif_gallagher_williams-devane_heidenfelder_hudgens_jones_neas_cohen hubal_edwards_2015, title={Data-driven asthma endotypes defined from blood biomarker and gene expression data}, volume={10}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84922569392&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0117445}, abstractNote={The diagnosis and treatment of childhood asthma is complicated by its mechanistically distinct subtypes (endotypes) driven by genetic susceptibility and modulating environmental factors. Clinical biomarkers and blood gene expression were collected from a stratified, cross-sectional study of asthmatic and non-asthmatic children from Detroit, MI. This study describes four distinct asthma endotypes identified via a purely data-driven method. Our method was specifically designed to integrate blood gene expression and clinical biomarkers in a way that provides new mechanistic insights regarding the different asthma endotypes. For example, we describe metabolic syndrome-induced systemic inflammation as an associated factor in three of the four asthma endotypes. Context provided by the clinical biomarker data was essential in interpreting gene expression patterns and identifying putative endotypes, which emphasizes the importance of integrated approaches when studying complex disease etiologies. These synthesized patterns of gene expression and clinical markers from our research may lead to development of novel serum-based biomarker panels.}, number={2}, journal={PLoS ONE}, author={George, B.J. and Reif, D.M. and Gallagher, J.E. and Williams-DeVane, C.R. and Heidenfelder, B.L. and Hudgens, E.E. and Jones, W. and Neas, L. and Cohen Hubal, E.A. and Edwards, S.W.}, year={2015} }
 @book{motsinger_reif_2015, title={Embracing complexity: Searching for gene-gene and gene environment interactions in genetic epidemiology}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85053966420&partnerID=MN8TOARS}, DOI={10.1201/b18597}, journal={Genomics and Proteomics: Principles, Technologies, and Applications}, author={Motsinger, A.A. and Reif, D.M.}, year={2015}, pages={19–58} }
 @article{rovida_asakura_daneshian_hofman-huether_leist_meunier_reif_rossi_schmutz_valentin_et al._2015, title={Food for Thought...: Toxicity testing in the 21st century beyond environmental chemicals}, volume={32}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84938603406&partnerID=MN8TOARS}, DOI={10.14573/altex.1506201}, abstractNote={Summary After the publication of the report titled Toxicity Testing in the 21st Century – A Vision and a Strategy, many initiatives started to foster a major paradigm shift for toxicity testing – from apical endpoints in animal-based tests to mechanistic endpoints through delineation of pathways of toxicity (PoT) in human cell based systems. The US EPA has funded an important project to develop new high throughput technologies based on human cell based in vitro technologies. These methods are currently being incorporated into the chemical risk assessment process. In the pharmaceutical industry, the efficacy and toxicity of new drugs are evaluated during preclinical investigations that include drug metabolism, pharmacokinetics, pharmacodynamics and safety toxicology studies. The results of these studies are analyzed and extrapolated to predict efficacy and potential adverse effects in humans. However, due to the high failure rate of drugs during the clinical phases, a new approach for a more predictive assessment of drugs both in terms of efficacy and adverse effects is getting urgent. The food industry faces the challenge of assessing novel foods and food ingredients for the general population, while using animal safety testing for extrapolation purposes is often of limited relevance. The question is whether the latest paradigm shift proposed by the Tox21c report for chemicals may provide a useful tool to improve the risk assessment approach also for drugs and food ingredients.}, number={3}, journal={Altex}, author={Rovida, C. and Asakura, S. and Daneshian, M. and Hofman-Huether, H. and Leist, M. and Meunier, L. and Reif, D. and Rossi, A. and Schmutz, M. and Valentin, J.-P. and et al.}, year={2015}, pages={171–181} }
 @article{rebuli_camacho_adonay_reif_aylor_patisaul_2015, title={Impact of Low-Dose Oral Exposure to Bisphenol A (BPA) on Juvenile and Adult Rat Exploratory and Anxiety Behavior: A CLARITY-BPA Consortium Study}, volume={148}, ISSN={["1096-0929"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84952932385&partnerID=MN8TOARS}, DOI={10.1093/toxsci/kfv163}, abstractNote={Bisphenol A (BPA) is a high volume production chemical and has been identified as an endocrine disruptor, prompting concern that developmental exposure could impact brain development and behavior. Rodent and human studies suggest that early life BPA exposure may result in an anxious, hyperactive phenotype but results are conflicting and data from studies using multiple doses below the no-observed-adverse-effect level are limited. To address this, the present studies were conducted as part of the CLARITY-BPA (Consortium Linking Academic and Regulatory Insights on BPA Toxicity) program. The impact of perinatal BPA exposure (2.5, 25, or 2500 µg/kg body weight (bw)/day) on behaviors related to anxiety and exploratory activity was assessed in juvenile (prepubertal) and adult NCTR Sprague-Dawley rats of both sexes. Ethinyl estradiol (0.5 µg/kg bw/day) was used as a reference estrogen. Exposure spanned gestation and lactation with dams gavaged from gestational day 6 until birth and then the offspring gavaged directly through weaning (n = 12/sex/group). Behavioral assessments included open field, elevated plus maze, and zero maze. Anticipated sex differences in behavior were statistically identified or suggested in most cases. No consistent effects of BPA were observed for any endpoint, in either sex, at either age compared to vehicle controls; however, significant differences between BPA-exposed and ethinyl estradiol-exposed groups were identified for some endpoints. Limitations of this study are discussed and include suboptimal statistical power and low concordance across behavioral tasks. These data do not indicate BPA-related effects on anxiety or exploratory activity in these developmentally exposed rats.}, number={2}, journal={TOXICOLOGICAL SCIENCES}, author={Rebuli, Meghan E. and Camacho, Luisa and Adonay, Maria E. and Reif, David M. and Aylor, David L. and Patisaul, Heather B.}, year={2015}, month={Dec}, pages={341–354} }
 @article{kollitz_zhang_hawkins_whitfield_reif_kullman_2015, title={Molecular Cloning, Functional Characterization, and Evolutionary Analysis of Vitamin D Receptors Isolated from Basal Vertebrates}, volume={10}, ISSN={["1932-6203"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84929469049&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0122853}, abstractNote={The vertebrate genome is a result of two rapid and successive rounds of whole genome duplication, referred to as 1R and 2R. Furthermore, teleost fish have undergone a third whole genome duplication (3R) specific to their lineage, resulting in the retention of multiple gene paralogs. The more recent 3R event in teleosts provides a unique opportunity to gain insight into how genes evolve through specific evolutionary processes. In this study we compare molecular activities of vitamin D receptors (VDR) from basal species that diverged at key points in vertebrate evolution in order to infer derived and ancestral VDR functions of teleost paralogs. Species include the sea lamprey (Petromyzon marinus), a 1R jawless fish; the little skate (Leucoraja erinacea), a cartilaginous fish that diverged after the 2R event; and the Senegal bichir (Polypterus senegalus), a primitive 2R ray-finned fish. Saturation binding assays and gel mobility shift assays demonstrate high affinity ligand binding and classic DNA binding characteristics of VDR has been conserved across vertebrate evolution. Concentration response curves in transient transfection assays reveal EC50 values in the low nanomolar range, however maximum transactivational efficacy varies significantly between receptor orthologs. Protein-protein interactions were investigated using co-transfection, mammalian 2-hybrid assays, and mutations of coregulator activation domains. We then combined these results with our previous study of VDR paralogs from 3R teleosts into a bioinformatics analysis. Our results suggest that 1, 25D3 acts as a partial agonist in basal species. Furthermore, our bioinformatics analysis suggests that functional differences between VDR orthologs and paralogs are influenced by differential protein interactions with essential coregulator proteins. We speculate that we may be observing a change in the pharmacodynamics relationship between VDR and 1, 25D3 throughout vertebrate evolution that may have been driven by changes in protein-protein interactions between VDR and essential coregulators.}, number={4}, journal={PLOS ONE}, author={Kollitz, Erin M. and Zhang, Guozhu and Hawkins, Mary Beth and Whitfield, G. Kerr and Reif, David M. and Kullman, Seth W.}, year={2015}, month={Apr} }
 @article{motsinger-reif_zhu_kling_matson_sharma_fiehn_reif_appleby_doraiswamy_trojanowski_et al._2014, title={Comparing metabolomic and pathologic biomarkers alone and in combination for discriminating Alzheimer's disease from normal cognitive aging}, volume={2}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85005916228&partnerID=MN8TOARS}, DOI={10.1186/2051-5960-1-28}, abstractNote={Abstract}, number={1}, journal={Acta Neuropathologica Communications}, publisher={Springer Science + Business Media}, author={Motsinger-Reif, Alison A and Zhu, Hongjie and Kling, Mitchel A and Matson, Wayne and Sharma, Swati and Fiehn, Oliver and Reif, David M and Appleby, Dina H and Doraiswamy, P Murali and Trojanowski, John Q and et al.}, year={2014}, pages={28} }
 @article{rotroff_wetmore_dix_ferguson_clewell_houck_lecluyse_andersen_judson_smith_et al._2014, title={Erratum to Incorporating human dosimetry and exposure into High-throughput in Vitro Toxicity Screening [Toxicological sciences 137, 2, (2014), 499]}, volume={137}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84893394979&partnerID=MN8TOARS}, DOI={10.1093/toxsci/kft185}, number={2}, journal={Toxicological Sciences}, author={Rotroff, D.M. and Wetmore, B.A. and Dix, D.J. and Ferguson, S.S. and Clewell, H.J. and Houck, K.A. and LeCluyse, E.L. and Andersen, M.E. and Judson, R.S. and Smith, C.M. and et al.}, year={2014} }
 @article{wilson_reif_reich_2014, title={Hierarchical Dose-Response Modeling for High-Throughput Toxicity Screening of Environmental Chemicals}, volume={70}, ISSN={["1541-0420"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84895891991&partnerID=MN8TOARS}, DOI={10.1111/biom.12114}, abstractNote={Summary}, number={1}, journal={BIOMETRICS}, publisher={Wiley-Blackwell}, author={Wilson, Ander and Reif, David M. and Reich, Brian J.}, year={2014}, month={Mar}, pages={237–246} }
 @article{truong_reif_st_geier_truong_tanguay_2014, title={Multidimensional in vivo hazard assessment using zebrafish.}, volume={137}, url={http://europepmc.org/abstract/med/24136191}, DOI={10.1093/toxsci/kft235}, abstractNote={There are tens of thousands of man-made chemicals in the environment; the inherent safety of most of these chemicals is not known. Relevant biological platforms and new computational tools are needed to prioritize testing of chemicals with limited human health hazard information. We describe an experimental design for high-throughput characterization of multidimensional in vivo effects with the power to evaluate trends relating to commonly cited chemical predictors. We evaluated all 1060 unique U.S. EPA ToxCast phase 1 and 2 compounds using the embryonic zebrafish and found that 487 induced significant adverse biological responses. The utilization of 18 simultaneously measured endpoints means that the entire system serves as a robust biological sensor for chemical hazard. The experimental design enabled us to describe global patterns of variation across tested compounds, evaluate the concordance of the available in vitro and in vivo phase 1 data with this study, highlight specific mechanisms/value-added/novel biology related to notochord development, and demonstrate that the developmental zebrafish detects adverse responses that would be missed by less comprehensive testing strategies.}, number={1}, journal={Toxicological Sciences}, author={Truong, L and Reif, DM and St, Mary L and Geier, MC and Truong, HD and Tanguay, RL}, year={2014}, month={Jan}, pages={212–233} }
 @article{kleinstreuer_yang_berg_knudsen_richard_martin_reif_judson_polokoff_dix_et al._2014, title={Phenotypic screening of the ToxCast chemical library to classify toxic and therapeutic mechanisms}, volume={32}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84902166194&partnerID=MN8TOARS}, DOI={10.1038/nbt.2914}, abstractNote={Addressing the safety aspects of drugs and environmental chemicals has historically been undertaken through animal testing. However, the quantity of chemicals in need of assessment and the challenges of species extrapolation require the development of alternative approaches. Our approach, the US Environmental Protection Agency's ToxCast program, utilizes a large suite of in vitro and model organism assays to interrogate important chemical libraries and computationally analyze bioactivity profiles. Here we evaluated one component of the ToxCast program, the use of primary human cell systems, by screening for chemicals that disrupt physiologically important pathways. Chemical-response signatures for 87 endpoints covering molecular functions relevant to toxic and therapeutic pathways were generated in eight cell systems for 641 environmental chemicals and 135 reference pharmaceuticals and failed drugs. Computational clustering of the profiling data provided insights into the polypharmacology and potential off-target effects for many chemicals that have limited or no toxicity information. The endpoints measured can be closely linked to in vivo outcomes, such as the upregulation of tissue factor in endothelial cell systems by compounds linked to the risk of thrombosis in vivo. Our results demonstrate that assaying complex biological pathways in primary human cells can identify potential chemical targets, toxicological liabilities and mechanisms useful for elucidating adverse outcome pathways.}, number={6}, journal={Nature Biotechnology}, author={Kleinstreuer, N.C. and Yang, J. and Berg, E.L. and Knudsen, T.B. and Richard, A.M. and Martin, M.T. and Reif, D.M. and Judson, R.S. and Polokoff, M. and Dix, D.J. and et al.}, year={2014}, pages={583–591} }
 @article{rotroff_martin_dix_filer_houck_knudsen_sipes_reif_xia_huang_et al._2014, title={Predictive endocrine testing in the 21st century using in vitro assays of estrogen receptor signaling responses}, volume={48}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84905638971&partnerID=MN8TOARS}, DOI={10.1021/es502676e}, abstractNote={Thousands of environmental chemicals are subject to regulatory review for their potential to be endocrine disruptors (ED). In vitro high-throughput screening (HTS) assays have emerged as a potential tool for prioritizing chemicals for ED-related whole-animal tests. In this study, 1814 chemicals including pesticide active and inert ingredients, industrial chemicals, food additives, and pharmaceuticals were evaluated in a panel of 13 in vitro HTS assays. The panel of in vitro assays interrogated multiple end points related to estrogen receptor (ER) signaling, namely binding, agonist, antagonist, and cell growth responses. The results from the in vitro assays were used to create an ER Interaction Score. For 36 reference chemicals, an ER Interaction Score >0 showed 100% sensitivity and 87.5% specificity for classifying potential ER activity. The magnitude of the ER Interaction Score was significantly related to the potency classification of the reference chemicals (p < 0.0001). ERα/ERβ selectivity was also evaluated, but relatively few chemicals showed significant selectivity for a specific isoform. When applied to a broader set of chemicals with in vivo uterotrophic data, the ER Interaction Scores showed 91% sensitivity and 65% specificity. Overall, this study provides a novel method for combining in vitro concentration response data from multiple assays and, when applied to a large set of ER data, accurately predicted estrogenic responses and demonstrated its utility for chemical prioritization.}, number={15}, journal={Environmental Science and Technology}, author={Rotroff, D.M. and Martin, M.T. and Dix, D.J. and Filer, D.L. and Houck, K.A. and Knudsen, T.B. and Sipes, N.S. and Reif, D.M. and Xia, M. and Huang, R. and et al.}, year={2014}, pages={8706–8716} }
 @article{huang_sakamuru_martin_reif_judson_houck_casey_hsieh_shockley_ceger_et al._2014, title={Profiling of the Tox21 10K compound library for agonists and antagonists of the estrogen receptor alpha signaling pathway}, volume={4}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84904350064&partnerID=MN8TOARS}, DOI={10.1038/srep05664}, abstractNote={Abstract}, journal={Scientific Reports}, author={Huang, R. and Sakamuru, S. and Martin, M.T. and Reif, D.M. and Judson, R.S. and Houck, K.A. and Casey, W. and Hsieh, J.-H. and Shockley, K.R. and Ceger, P. and et al.}, year={2014} }
 @article{filer_patisaul_schug_reif_thayer_2014, title={Test driving ToxCast: endocrine profiling for 1858 chemicals included in phase II}, volume={19}, ISSN={["1471-4973"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84908151070&partnerID=MN8TOARS}, DOI={10.1016/j.coph.2014.09.021}, abstractNote={Identifying chemicals, beyond those already implicated, to test for potential endocrine disruption is a challenge and high throughput approaches have emerged as a potential tool for this type of screening. This review focused the Environmental Protection Agency's (EPA) ToxCast(TM) high throughput in vitro screening (HTS) program. Utility for identifying compounds was assessed and reviewed by using it to run the recently expanded chemical library (from 309 compounds to 1858) through the ToxPi(TM) prioritization scheme for endocrine disruption. The analysis included metabolic and neuroendocrine targets. This investigative approach simultaneously assessed the utility of ToxCast, and helped identify novel chemicals which may have endocrine activity. Results from this exercise suggest the spectrum of environmental chemicals with potential endocrine activity is much broader than indicated, and that some aspects of endocrine disruption are not fully covered in ToxCast.}, journal={CURRENT OPINION IN PHARMACOLOGY}, author={Filer, Dayne and Patisaul, Heather B. and Schug, Thaddeus and Reif, David and Thayer, Kristina}, year={2014}, month={Dec}, pages={145–152} }
 @article{bushnell_tatum-gibbs_mckee_evansky_higuchi_mlin_oshiro_judson_hester_reif_et al._2014, title={ToxiFly: Can fruit flies be used to identify toxicity pathways for airborne chemicals?}, volume={43}, ISSN={0892-0362}, url={http://dx.doi.org/10.1016/J.NTT.2014.04.045}, DOI={10.1016/J.NTT.2014.04.045}, journal={Neurotoxicology and Teratology}, publisher={Elsevier BV}, author={Bushnell, P.J. and Tatum-Gibbs, R. and McKee, J.M. and Evansky, P.A. and Higuchi, M. and MLin, M.T. and Oshiro, W.M. and Judson, R. and Hester, S. and Reif, D. and et al.}, year={2014}, month={May}, pages={89} }
 @article{kleinstreuer_dix_rountree_baker_sipes_reif_spencer_knudsen_2013, title={A Computational Model Predicting Disruption of Blood Vessel Development}, volume={9}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84876922933&partnerID=MN8TOARS}, DOI={10.1371/journal.pcbi.1002996}, abstractNote={Vascular development is a complex process regulated by dynamic biological networks that vary in topology and state across different tissues and developmental stages. Signals regulating de novo blood vessel formation (vasculogenesis) and remodeling (angiogenesis) come from a variety of biological pathways linked to endothelial cell (EC) behavior, extracellular matrix (ECM) remodeling and the local generation of chemokines and growth factors. Simulating these interactions at a systems level requires sufficient biological detail about the relevant molecular pathways and associated cellular behaviors, and tractable computational models that offset mathematical and biological complexity. Here, we describe a novel multicellular agent-based model of vasculogenesis using the CompuCell3D (http://www.compucell3d.org/) modeling environment supplemented with semi-automatic knowledgebase creation. The model incorporates vascular endothelial growth factor signals, pro- and anti-angiogenic inflammatory chemokine signals, and the plasminogen activating system of enzymes and proteases linked to ECM interactions, to simulate nascent EC organization, growth and remodeling. The model was shown to recapitulate stereotypical capillary plexus formation and structural emergence of non-coded cellular behaviors, such as a heterologous bridging phenomenon linking endothelial tip cells together during formation of polygonal endothelial cords. Molecular targets in the computational model were mapped to signatures of vascular disruption derived from in vitro chemical profiling using the EPA's ToxCast high-throughput screening (HTS) dataset. Simulating the HTS data with the cell-agent based model of vascular development predicted adverse effects of a reference anti-angiogenic thalidomide analog, 5HPP-33, on in vitro angiogenesis with respect to both concentration-response and morphological consequences. These findings support the utility of cell agent-based models for simulating a morphogenetic series of events and for the first time demonstrate the applicability of these models for predictive toxicology.}, number={4}, journal={PLoS Comput Biol}, publisher={Public Library of Science (PLoS)}, author={Kleinstreuer, Nicole and Dix, David and Rountree, Michael and Baker, Nancy and Sipes, Nisha and Reif, David and Spencer, Richard and Knudsen, Thomas}, editor={Peirce, Shayn M.Editor}, year={2013}, month={Apr}, pages={e1002996} }
 @article{williams-devane_reif_cohen hubal_bushel_hudgens_gallagher_edwards_2013, title={Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotypes.}, volume={7}, url={http://europepmc.org/abstract/med/24188919}, DOI={10.1186/1752-0509-7-119}, abstractNote={Complex diseases are often difficult to diagnose, treat and study due to the multi-factorial nature of the underlying etiology. Large data sets are now widely available that can be used to define novel, mechanistically distinct disease subtypes (endotypes) in a completely data-driven manner. However, significant challenges exist with regard to how to segregate individuals into suitable subtypes of the disease and understand the distinct biological mechanisms of each when the goal is to maximize the discovery potential of these data sets. A multi-step decision tree-based method is described for defining endotypes based on gene expression, clinical covariates, and disease indicators using childhood asthma as a case study. We attempted to use alternative approaches such as the Student’s t-test, single data domain clustering and the Modk-prototypes algorithm, which incorporates multiple data domains into a single analysis and none performed as well as the novel multi-step decision tree method. This new method gave the best segregation of asthmatics and non-asthmatics, and it provides easy access to all genes and clinical covariates that distinguish the groups. The multi-step decision tree method described here will lead to better understanding of complex disease in general by allowing purely data-driven disease endotypes to facilitate the discovery of new mechanisms underlying these diseases. This application should be considered a complement to ongoing efforts to better define and diagnose known endotypes. When coupled with existing methods developed to determine the genetics of gene expression, these methods provide a mechanism for linking genetics and exposomics data and thereby accounting for both major determinants of disease.}, journal={BMC Systems Biology}, author={Williams-DeVane, C.R. and Reif, D.M. and Cohen Hubal, E. and Bushel, P.R. and Hudgens, E.E. and Gallagher, J.E. and Edwards, S.W.}, year={2013}, pages={119} }
 @article{wambaugh_setzer_pitruzzello_liu_reif_kleinstreuer_wang_sipes_martin_das_et al._2013, title={Dosimetric anchoring of in vivo and in vitro studies for perfluorooctanoate and perfluorooctanesulfonate.}, volume={136}, url={http://europepmc.org/abstract/med/24046276}, DOI={10.1093/toxsci/kft204}, abstractNote={In order to compare between in vivo toxicity studies, dosimetry is needed to translate study-specific dose regimens into dose metrics such as tissue concentration. These tissue concentrations may then be compared with in vitro bioactivity assays to perhaps identify mechanisms relevant to the lowest observed effect level (LOEL) dose group and the onset of the observed in vivo toxicity. Here, we examine the perfluorinated compounds (PFCs) perfluorooctanoate (PFOA) and perfluorooctanesulfonate (PFOS). We analyzed 9 in vivo toxicity studies for PFOA and 13 in vivo toxicity studies for PFOS. Both PFCs caused multiple effects in various test species, strains, and genders. We used a Bayesian pharmacokinetic (PK) modeling framework to incorporate data from 6 PFOA PK studies and 2 PFOS PK studies (conducted in 3 species) to predict dose metrics for the in vivo LOELs and no observed effect levels (NOELs). We estimated PK parameters for 11 combinations of chemical, species, strain, and gender. Despite divergent study designs and species-specific PK, for a given effect, we found that the predicted dose metrics corresponding to the LOELs (and NOELs where available) occur at similar concentrations. In vitro assay results for PFOA and PFOS from EPA's ToxCast project were then examined. We found that most in vitro bioactivity occurs at concentrations lower than the predicted concentrations for the in vivo LOELs and higher than the predicted concentrations for the in vivo NOELs (where available), for a variety of nonimmunological effects. These results indicate that given sufficient PK data, the in vivo LOELs dose regimens, but not necessarily the effects, could have been predicted from in vitro studies for these 2 PFCs.}, number={2}, journal={Toxicological Sciences}, author={Wambaugh, JF and Setzer, RW and Pitruzzello, AM and Liu, J and Reif, DM and Kleinstreuer, NC and Wang, NC and Sipes, N and Martin, M and Das, K and et al.}, year={2013}, month={Dec}, pages={308–327} }
 @article{wambaugh_setzer_reif_gangwal_mitchell-blackwood_arnot_joliet_frame_rabinowitz_knudsen_et al._2013, title={High-throughput models for exposure-based chemical prioritization in the ExpoCast project.}, volume={47}, url={http://europepmc.org/abstract/med/23758710}, DOI={10.1021/es400482g}, abstractNote={The United States Environmental Protection Agency (U.S. EPA) must characterize potential risks to human health and the environment associated with manufacture and use of thousands of chemicals. High-throughput screening (HTS) for biological activity allows the ToxCast research program to prioritize chemical inventories for potential hazard. Similar capabilities for estimating exposure potential would support rapid risk-based prioritization for chemicals with limited information; here, we propose a framework for high-throughput exposure assessment. To demonstrate application, an analysis was conducted that predicts human exposure potential for chemicals and estimates uncertainty in these predictions by comparison to biomonitoring data. We evaluated 1936 chemicals using far-field mass balance human exposure models (USEtox and RAIDAR) and an indicator for indoor and/or consumer use. These predictions were compared to exposures inferred by Bayesian analysis from urine concentrations for 82 chemicals reported in the National Health and Nutrition Examination Survey (NHANES). Joint regression on all factors provided a calibrated consensus prediction, the variance of which serves as an empirical determination of uncertainty for prioritization on absolute exposure potential. Information on use was found to be most predictive; generally, chemicals above the limit of detection in NHANES had consumer/indoor use. Coupled with hazard HTS, exposure HTS can place risk earlier in decision processes. High-priority chemicals become targets for further data collection.}, number={15}, journal={Environmental Science and Technology}, author={Wambaugh, J.F. and Setzer, R.W. and Reif, D.M. and Gangwal, S. and Mitchell-Blackwood, J. and Arnot, J.A. and Joliet, O. and Frame, A. and Rabinowitz, J. and Knudsen, T.B. and et al.}, year={2013}, month={Aug}, pages={8479–8488} }
 @article{kleinstreuer_dix_houck_kavlock_knudsen_martin_paul_reif_crofton_hamilton_et al._2013, title={In vitro perturbations of targets in cancer hallmark processes predict rodent chemical carcinogenesis.}, volume={131}, url={http://europepmc.org/abstract/med/23024176}, DOI={10.1093/toxsci/kfs285}, abstractNote={Thousands of untested chemicals in the environment require efficient characterization of carcinogenic potential in humans. A proposed solution is rapid testing of chemicals using in vitro high-throughput screening (HTS) assays for targets in pathways linked to disease processes to build models for priority setting and further testing. We describe a model for predicting rodent carcinogenicity based on HTS data from 292 chemicals tested in 672 assays mapping to 455 genes. All data come from the EPA ToxCast project. The model was trained on a subset of 232 chemicals with in vivo rodent carcinogenicity data in the Toxicity Reference Database (ToxRefDB). Individual HTS assays strongly associated with rodent cancers in ToxRefDB were linked to genes, pathways, and hallmark processes documented to be involved in tumor biology and cancer progression. Rodent liver cancer endpoints were linked to well-documented pathways such as peroxisome proliferator-activated receptor signaling and TP53 and novel targets such as PDE5A and PLAUR. Cancer hallmark genes associated with rodent thyroid tumors were found to be linked to human thyroid tumors and autoimmune thyroid disease. A model was developed in which these genes/pathways function as hypothetical enhancers or promoters of rat thyroid tumors, acting secondary to the key initiating event of thyroid hormone disruption. A simple scoring function was generated to identify chemicals with significant in vitro evidence that was predictive of in vivo carcinogenicity in different rat tissues and organs. This scoring function was applied to an external test set of 33 compounds with carcinogenicity classifications from the EPA's Office of Pesticide Programs and successfully (p = 0.024) differentiated between chemicals classified as "possible"/"probable"/"likely" carcinogens and those designated as "not likely" or with "evidence of noncarcinogenicity." This model represents a chemical carcinogenicity prioritization tool supporting targeted testing and functional validation of cancer pathways.}, number={1}, journal={Toxicological Sciences}, author={Kleinstreuer, NC and Dix, DJ and Houck, KA and Kavlock, RJ and Knudsen, TB and Martin, MT and Paul, KB and Reif, DM and Crofton, KM and Hamilton, K and et al.}, year={2013}, month={Jan}, pages={40–55} }
 @article{ducharme_peterson_benfenati_reif_mccollum_jå_bondesson_2013, place={Elmsford, N.Y}, title={Meta-analysis of toxicity and teratogenicity of 133 chemicals from zebrafish developmental toxicity studies.}, volume={41}, url={http://europepmc.org/abstract/med/23796950}, DOI={10.1016/j.reprotox.2013.06.070}, abstractNote={Zebrafish developmental toxicity testing is an emerging field, which faces considerable challenges regarding data meta-analysis and the establishment of standardized test protocols. Here, we present an initial correlation study on toxicity of 133 chemicals based on data in the literature to ascertain predictive developmental toxicity endpoints. We found that the physical properties of chemicals (BCF or logP) did not fully predict lethality or developmental outcomes. Instead, individual outcomes such as pericardial edema and yolk sac edema were more reliable indicators of developmental toxicity. In addition, we ranked the chemicals based on toxicity with the Toxicological Priority Index (ToxPi) program and via a teratogenic ratio, and found that perfluorooctane sulfonate (PFOS) had the highest ToxPi score, triphenyltin acetate had the highest average ToxPi score (corrected for missing data and having more than 4 outcomes), and N-methyl-dithiocarbamate had the highest teratogenic ratio.}, journal={Reproductive Toxicology}, author={Ducharme, NA and Peterson, LE and Benfenati, E and Reif, D and McCollum, CW and JÅ, Gustafsson and Bondesson, M}, year={2013}, month={Nov}, pages={98–108} }
 @article{judson_kavlock_martin_reif_houck_knudsen_richard_tice_whelan_xia_et al._2013, title={Perspectives on validation of high-throughput assays supporting 21st century toxicity testing.}, volume={30}, url={http://europepmc.org/abstract/med/23338806}, number={1}, journal={Altex}, author={Judson, R. and Kavlock, R. and Martin, M. and Reif, D. and Houck, K. and Knudsen, T. and Richard, A. and Tice, R.R. and Whelan, M. and Xia, M. and et al.}, year={2013}, pages={51–66} }
 @article{sipes_martin_kothiya_reif_judson_richard_houck_dix_kavlock_knudsen_2013, title={Profiling 976 ToxCast Chemicals across 331 Enzymatic and Receptor Signaling Assays}, volume={26}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84879179678&partnerID=MN8TOARS}, DOI={10.1021/tx400021f}, abstractNote={Understanding potential health risks is a significant challenge due to the large numbers of diverse chemicals with poorly characterized exposures and mechanisms of toxicities. The present study analyzes 976 chemicals (including failed pharmaceuticals, alternative plasticizers, food additives, and pesticides) in Phases I and II of the U.S. EPA’s ToxCast project across 331 cell-free enzymatic and ligand-binding high-throughput screening (HTS) assays. Half-maximal activity concentrations (AC50) were identified for 729 chemicals in 256 assays (7,135 chemical–assay pairs). Some of the most commonly affected assays were CYPs (CYP2C9 and CYP2C19), transporters (mitochondrial TSPO, norepinephrine, and dopaminergic), and GPCRs (aminergic). Heavy metals, surfactants, and dithiocarbamate fungicides showed promiscuous but distinctly different patterns of activity, whereas many of the pharmaceutical compounds showed promiscuous activity across GPCRs. Literature analysis confirmed >50% of the activities for the most potent chemical–assay pairs (54) but also revealed 10 missed interactions. Twenty-two chemicals with known estrogenic activity were correctly identified for the majority (77%), missing only the weaker interactions. In many cases, novel findings for previously unreported chemical–target combinations clustered with known chemical–target interactions. Results from this large inventory of chemical–biological interactions can inform read-across methods as well as link potential targets to molecular initiating events in adverse outcome pathways for diverse toxicities.}, number={6}, journal={Chem. Res. Toxicol.}, publisher={American Chemical Society (ACS)}, author={Sipes, Nisha S. and Martin, Matthew T. and Kothiya, Parth and Reif, David M. and Judson, Richard S. and Richard, Ann M. and Houck, Keith A. and Dix, David J. and Kavlock, Robert J. and Knudsen, Thomas B.}, year={2013}, month={Jun}, pages={878–895} }
 @article{rotroff_dix_houck_kavlock_knudsen_martin_reif_richard_sipes_abassi_et al._2013, title={Real-time growth kinetics measuring hormone mimicry for ToxCast chemicals in T-47D human ductal carcinoma cells.}, volume={26}, url={http://europepmc.org/abstract/med/23682706}, DOI={10.1021/tx400117y}, abstractNote={High-throughput screening (HTS) assays capable of profiling thousands of environmentally relevant chemicals for in vitro biological activity provide useful information on the potential for disrupting endocrine pathways. Disruption of the estrogen signaling pathway has been implicated in a variety of adverse health effects including impaired development, reproduction, and carcinogenesis. The estrogen-responsive human mammary ductal carcinoma cell line T-47D was exposed to 1815 ToxCast chemicals comprising pesticides, industrial chemicals, pharmaceuticals, personal care products, cosmetics, food ingredients, and other chemicals with known or suspected human exposure potential. Cell growth kinetics were evaluated using real-time cell electronic sensing. T-47D cells were exposed to eight concentrations (0.006-100 μM), and measurements of cellular impedance were repeatedly recorded for 105 h. Chemical effects were evaluated based on potency (concentration at which response occurs) and efficacy (extent of response). A linear growth response was observed in response to prototypical estrogen receptor agonists (17β-estradiol, genistein, bisphenol A, nonylphenol, and 4-tert-octylphenol). Several compounds, including bisphenol A and genistein, induced cell growth comparable in efficacy to that of 17β-estradiol, but with decreased potency. Progestins, androgens, and corticosteroids invoked a biphasic growth response indicative of changes in cell number or cell morphology. Results from this cell growth assay were compared with results from additional estrogen receptor (ER) binding and transactivation assays. Chemicals detected as active in both the cell growth and ER receptor binding assays demonstrated potencies highly correlated with two ER transactivation assays (r = 0.72; r = 0.70). While ER binding assays detected chemicals that were highly potent or efficacious in the T-47D cell growth and transactivation assays, the binding assays lacked sensitivity in detecting weakly active compounds. In conclusion, this cell-based assay rapidly detects chemical effects on T-47D growth and shows potential, in combination with other HTS assays, to detect environmentally relevant chemicals with potential estrogenic activity.}, number={7}, journal={Chemical Research in Toxicology}, author={Rotroff, DM and Dix, DJ and Houck, KA and Kavlock, RJ and Knudsen, TB and Martin, MT and Reif, DM and Richard, AM and Sipes, NS and Abassi, YA and et al.}, year={2013}, month={Jul}, pages={1097–1107} }
 @article{houck_richard_judson_martin_reif_shah_2013, title={ToxCast: Predicting Toxicity Potential Through High-Throughput Bioactivity Profiling}, volume={2}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84887236218&partnerID=MN8TOARS}, DOI={10.1002/9781118538203.ch1}, abstractNote={The field of toxicology is in transition from one based on an in vivo, chemical-by-chemical approach to one utilizing tools of modern molecular, cellular, and systems biology, providing the opportunity for greatly increased testing efficiency and improved modeling capabilities. Such an increase in testing efficiency is necessary to address the lack of toxicity information on the large chemical inventories that present potential human and environmental exposure scenarios, as well as to provide sufficient coverage of chemical and biological space to enable effective modeling of toxicity. Utilizing high-throughput screening methods developed in the drug discovery community, this in vitro-based approach focuses on the mechanisms of chemico-biological interactions by using large chemical libraries to probe key molecular targets and signaling pathways. Computational toxicology has emerged as a critical component in handling the large and complex datasets required for developing and validating this approach. Insight into these interactions will greatly enhance our understanding of the molecular and biological basis of toxicity and result in greater confidence in extrapolations, as well as factors critical to risk assessment such as significant susceptibility factors, subpopulations at risk, and influences on the shape of the dose–response curve.}, journal={High-Throughput Screening Methods in Toxicity Testing}, publisher={John Wiley & Sons, Inc.}, author={Houck, Keith A. and Richard, Ann M. and Judson, Richard S. and Martin, Matthew T. and Reif, David M. and Shah, Imran}, year={2013}, month={Feb}, pages={1–31} }
 @article{reif_sypa_lock_wright_wilson_cathey_judson_rusyn_bioinformatics_2013, title={ToxPi GUI: an interactive visualization tool for transparent integration of data from diverse sources of evidence.}, volume={29}, url={http://europepmc.org/abstract/med/23202747}, DOI={10.1093/bioinformatics/bts686}, abstractNote={Abstract}, number={3}, journal={Bioinformatics}, author={Reif, D.M. and Sypa, M. and Lock, E.F. and Wright, F.A. and Wilson, A. and Cathey, T. and Judson, R.R. and Rusyn, I. and Bioinformatics}, year={2013}, month={Feb}, pages={402–403} }
 @article{rotroff_dix_houck_knudsen_martin_mclaurin_reif_crofton_singh_xia_et al._2013, title={Using in vitro high throughput screening assays to identify potential endocrine-disrupting chemicals.}, volume={121}, url={http://europepmc.org/abstract/med/23052129}, DOI={10.1289/ehp.1205065}, abstractNote={Background: Over the past 20 years, an increased focus on detecting environmental chemicals that pose a risk of adverse effects due to endocrine disruption has driven the creation of the U.S. Environmental Protection Agency (EPA) Endocrine Disruptor Screening Program (EDSP). Thousands of chemicals are subject to the EDSP; thus, processing these chemicals using current test batteries could require millions of dollars and decades. A need for increased throughput and efficiency motivated the development of methods using in vitro high throughput screening (HTS) assays to prioritize chemicals for EDSP Tier 1 screening (T1S). Objective: In this study we used U.S. EPA ToxCast HTS assays for estrogen, androgen, steroidogenic, and thyroid-disrupting mechanisms to classify compounds and compare ToxCast results to in vitro and in vivo data from EDSP T1S assays. Method: We implemented an iterative model that optimized the ability of endocrine-related HTS assays to predict components of EDSP T1S and related results. Balanced accuracy was used as a measure of model performance. Results: ToxCast estrogen receptor and androgen receptor assays predicted the results of relevant EDSP T1S assays with balanced accuracies of 0.91 (p < 0.001) and 0.92 (p < 0.001), respectively. Uterotrophic and Hershberger assay results were predicted with balanced accuracies of 0.89 (p < 0.001) and 1 (p < 0.001), respectively. Models for steroidogenic and thyroid-related effects could not be developed with the currently published ToxCast data. Conclusions: Overall, results suggest that current ToxCast assays can accurately identify chemicals with potential to interact with the estrogenic and androgenic pathways, and could help prioritize chemicals for EDSP T1S assays.}, number={1}, journal={Environmental Health Perspectives}, author={Rotroff, DM and Dix, DJ and Houck, KA and Knudsen, TB and Martin, MT and McLaurin, KW and Reif, DM and Crofton, KM and Singh, AV and Xia, M and et al.}, year={2013}, month={Jan}, pages={7–14} }
 @inproceedings{hoover_marceau_harris_reif_motsinger-reif_2012, title={A comparison of GE optimized neural networks and decision trees}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84865046755&partnerID=MN8TOARS}, DOI={10.1145/2330784.2330885}, abstractNote={Grammatical evolution neural networks (GENN) is a commonly utilized method at identifying difficult to detect gene-gene and gene-environment interactions. It has been shown to be an effective tool in the prediction of common diseases using single nucleotide polymorphisms (SNPs). However, GENN lacks interpretability because it is a black box model. Therefore, grammatical evolution of decision trees (GEDT) is being considered as an alternative, as decision trees are easily interpretable for clinicians. Previously, the most effective parameters for GEDT and GENN were found using parameter sweeps. Since GEDT is much more intuitive and easy to understand, it becomes important to compare its predictive power to that of GENN. We show that it is not as effective as GENN at detecting disease causing polymorphisms especially in more difficult to detect models, but this power trade off may be worth it for interpretability.}, booktitle={Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion - GECCO Companion '12}, publisher={ACM Press}, author={Hoover, Kristopher and Marceau, Rachel and Harris, Tyndall and Reif, David and Motsinger-Reif, Alison}, year={2012}, pages={611–614} }
 @article{gory_sweeney_reif_motsinger-reif_2012, title={A comparison of internal model validation methods for multifactor dimensionality reduction in the case of genetic heterogeneity}, volume={5}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84868248881&partnerID=MN8TOARS}, DOI={10.1186/1756-0500-5-623}, abstractNote={Abstract}, number={1}, journal={BMC Research Notes}, publisher={Springer Science + Business Media}, author={Gory, Jeffrey J and Sweeney, Holly C and Reif, David M and Motsinger-Reif, Alison A}, year={2012}, pages={623} }
 @article{judson_martin_egeghy_gangwal_reif_kothiya_wolf_cathey_transue_smith_et al._2012, title={Aggregating Data for Computational Toxicology Applications: The U.S. Environmental Protection Agency (EPA) Aggregated Computational Toxicology Resource (ACToR) System.}, volume={13}, url={http://europepmc.org/abstract/med/22408426}, DOI={10.3390/ijms13021805}, abstractNote={Computational toxicology combines data from high-throughput test methods, chemical structure analyses and other biological domains (e.g., genes, proteins, cells, tissues) with the goals of predicting and understanding the underlying mechanistic causes of chemical toxicity and for predicting toxicity of new chemicals and products. A key feature of such approaches is their reliance on knowledge extracted from large collections of data and data sets in computable formats. The U.S. Environmental Protection Agency (EPA) has developed a large data resource called ACToR (Aggregated Computational Toxicology Resource) to support these data-intensive efforts. ACToR comprises four main repositories: core ACToR (chemical identifiers and structures, and summary data on hazard, exposure, use, and other domains), ToxRefDB (Toxicity Reference Database, a compilation of detailed in vivo toxicity data from guideline studies), ExpoCastDB (detailed human exposure data from observational studies of selected chemicals), and ToxCastDB (data from high-throughput screening programs, including links to underlying biological information related to genes and pathways). The EPA DSSTox (Distributed Structure-Searchable Toxicity) program provides expert-reviewed chemical structures and associated information for these and other high-interest public inventories. Overall, the ACToR system contains information on about 400,000 chemicals from 1100 different sources. The entire system is built using open source tools and is freely available to download. This review describes the organization of the data repository and provides selected examples of use cases.}, number={2}, journal={International Journal of Molecular Sciences}, author={Judson, R.S. and Martin, M.T. and Egeghy, P. and Gangwal, S. and Reif, D.M. and Kothiya, P. and Wolf, M. and Cathey, T. and Transue, T. and Smith, D. and et al.}, year={2012}, pages={1805–1831} }
 @article{dix_houck_judson_kleinstreuer_knudsen_martin_reif_richard_shah_sipes_et al._2012, title={Incorporating biological, chemical, and toxicological knowledge into predictive models of toxicity.}, volume={130}, url={http://europepmc.org/abstract/med/22982683}, DOI={10.1093/toxsci/kfs281}, abstractNote={Complete List of Authors: Dix, David; US EPA, Nat'l Center for Computational Toxicology Houck, Keith; USEPA, NCCT Judson, Richard S.; US EPA, National Center for Computational Toxicology Knudsen, Thomas; US EPA, NCCT Martin, Matthew; US EPA, Reif, David; US EPA, National Center for Computational Toxicology Richard, Ann; USEPA, MD B143-06 Shah, Imran; USEPA, NCCT Kleinstreuer, Nicole; U.S. Environmental Protection Agency, Office of Research and Development, National Center for Computational Toxicology Sipes, Nisha; U.S. Environmental Protection Agency, Office of Research and Development/National Center for Computational Toxicology Kavlock, Robert; U.S. Environmental Protection Agency, Office of Research and Development, National Center for Computational Toxicology; US EPA, NHEERL, MD-71}, note={author reply 442-3}, number={2}, journal={Toxicological Sciences}, author={Dix, DJ and Houck, KA and Judson, RS and Kleinstreuer, NC and Knudsen, TB and Martin, MT and Reif, DM and Richard, AM and Shah, I and Sipes, NS and et al.}, year={2012}, month={Dec}, pages={440–441} }
 @article{gangwal_reif_mosher_egeghy_wambaugh_judson_hubal_2012, title={Incorporating exposure information into the toxicological prioritization index decision support framework}, volume={435-436}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84864471315&partnerID=MN8TOARS}, DOI={10.1016/j.scitotenv.2012.06.086}, abstractNote={The Toxicological Prioritization Index (ToxPi) decision support framework was previously developed to facilitate incorporation of diverse data to prioritize chemicals based on potential hazard. This ToxPi index was demonstrated by considering results of bioprofiling related to potential for endocrine disruption. However, exposure information is required along with hazard information to prioritize chemicals for further testing. The goal of this analysis is to demonstrate the utility of the ToxPi framework for incorporating exposure information to rank chemicals and improve understanding of key exposure surrogates. The ToxPi tool was applied to common exposure surrogates (i.e., fate parameters, manufacturing volume, and occurrence measurements) and the relationship between resulting rankings and higher-tiered exposure estimates was investigated. As information more directly relevant to human exposure potential is incorporated, relative rank of chemicals changes. Binned ToxPi results are shown to be consistent with chemical priorities based on crude measures of population-level exposure for a limited set of chemicals. However, these bins are not predictive of higher tiered estimates of exposure such as those developed for pesticide registration. Although rankings based on exposure surrogates are used in a variety of contexts, analysis of the relevance of these tools is challenging. The ToxPi framework can be used to gain insight into the factors driving these rankings and aid identification of key exposure metrics. Additional exposure data is required to build confidence in exposure-based chemical prioritization.}, journal={Science of The Total Environment}, publisher={Elsevier BV}, author={Gangwal, Sumit and Reif, David M. and Mosher, Shad and Egeghy, Peter P. and Wambaugh, John F. and Judson, Richard S. and Hubal, Elaine A. Cohen}, year={2012}, month={Oct}, pages={316–325} }
 @article{kavlock_chandler_houck_hunter_judson_kleinstreuer_knudsen_martin_padilla_reif_et al._2012, title={Update on EPA’s ToxCast Program: Providing High Throughput Decision Support Tools for Chemical Risk Management}, volume={25}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84863886918&partnerID=MN8TOARS}, DOI={10.1021/tx3000939}, abstractNote={The field of toxicology is on the cusp of a major transformation in how the safety and hazard of chemicals are evaluated for potential effects on human health and the environment. Brought on by the recognition of the limitations of the current paradigm in terms of cost, time, and throughput, combined with the ever increasing power of modern biological tools to probe mechanisms of chemical-biological interactions at finer and finer resolutions, 21st century toxicology is rapidly taking shape. A key element of the new approach is a focus on the molecular and cellular pathways that are the targets of chemical interactions. By understanding toxicity in this manner, we begin to learn how chemicals cause toxicity, as opposed to merely what diseases or health effects they might cause. This deeper understanding leads to increasing confidence in identifying which populations might be at risk, significant susceptibility factors, and key influences on the shape of the dose-response curve. The U. S. Environmental Protection Agency (EPA) initiated the ToxCast, or "toxicity forecaster", program 5 years ago to gain understanding of the strengths and limitations of the new approach by starting to test relatively large numbers (hundreds) of chemicals against an equally large number of biological assays. Using computational approaches, the EPA is building decision support tools based on ToxCast in vitro screening results to help prioritize chemicals for further investigation, as well as developing predictive models for a number of health outcomes. This perspective provides a summary of the initial, proof of concept, Phase I of ToxCast that has laid the groundwork for the next phases and future directions of the program.}, number={7}, journal={Chem. Res. Toxicol.}, publisher={American Chemical Society (ACS)}, author={Kavlock, Robert and Chandler, Kelly and Houck, Keith and Hunter, Sid and Judson, Richard and Kleinstreuer, Nicole and Knudsen, Thomas and Martin, Matt and Padilla, Stephanie and Reif, David and et al.}, year={2012}, month={Jul}, pages={1287–1302} }
 @article{padilla_corum_padnos_hunter_beam_houck_sipes_kleinstreuer_knudsen_dix_et al._2012, place={Elmsford, N.Y}, title={Zebrafish developmental screening of the ToxCast™ Phase I chemical library.}, volume={33}, url={http://europepmc.org/abstract/med/22182468}, DOI={10.1016/j.reprotox.2011.10.018}, abstractNote={Zebrafish (Danio rerio) is an emerging toxicity screening model for both human health and ecology. As part of the Computational Toxicology Research Program of the U.S. EPA, the toxicity of the 309 ToxCast™ Phase I chemicals was assessed using a zebrafish screen for developmental toxicity. All exposures were by immersion from 6–8 h post fertilization (hpf) to 5 days post fertilization (dpf); nominal concentration range of 1 nM–80 μM. On 6 dpf larvae were assessed for death and overt structural defects. Results revealed that the majority (62%) of chemicals were toxic to the developing zebrafish; both toxicity incidence and potency was correlated with chemical class and hydrophobicity (logP); and inter-and intra-plate replicates showed good agreement. The zebrafish embryo screen, by providing an integrated model of the developing vertebrate, compliments the ToxCast assay portfolio and has the potential to provide information relative to overt and organismal toxicity.}, number={2}, journal={Reproductive Toxicology}, author={Padilla, S and Corum, D and Padnos, B and Hunter, DL and Beam, A and Houck, KA and Sipes, N and Kleinstreuer, N and Knudsen, T and Dix, DJ and et al.}, year={2012}, month={Apr}, pages={174–187} }
 @article{knudsen_houck_sipes_singh_judson_martin_weissman_kleinstreuer_mortensen_reif_et al._2011, title={Activity profiles of 309 ToxCast™ chemicals evaluated across 292 biochemical targets}, volume={282}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-79951574271&partnerID=MN8TOARS}, DOI={10.1016/j.tox.2010.12.010}, abstractNote={Understanding the potential health risks posed by environmental chemicals is a significant challenge elevated by the large number of diverse chemicals with generally uncharacterized exposures, mechanisms, and toxicities. The present study is a performance evaluation and critical analysis of assay results for an array of 292 high-throughput cell-free assays aimed at preliminary toxicity evaluation of 320 environmental chemicals in EPA's ToxCast™ project (Phase I). The chemicals (309 unique, 11 replicates) were mainly precursors or the active agent of commercial pesticides, for which a wealth of in vivo toxicity data is available. Biochemical HTS (high-throughput screening) profiled cell and tissue extracts using semi-automated biochemical and pharmacological methodologies to evaluate a subset of G-protein coupled receptors (GPCRs), CYP450 enzymes (CYPs), kinases, phosphatases, proteases, HDACs, nuclear receptors, ion channels, and transporters. The primary screen tested all chemicals at a relatively high concentration 25 μM concentration (or 10 μM for CYP assays), and a secondary screen re-tested 9132 chemical-assay pairs in 8-point concentration series from 0.023 to 50 μM (or 0.009-20 μM for CYPs). Mapping relationships across 93,440 chemical-assay pairs based on half-maximal activity concentration (AC50) revealed both known and novel targets in signaling and metabolic pathways. The primary dataset, summary data and details on quality control checks are available for download at http://www.epa.gov/ncct/toxcast/.}, number={1-2}, journal={Toxicology}, publisher={Elsevier BV}, author={Knudsen, Thomas B. and Houck, Keith A. and Sipes, Nisha S. and Singh, Amar V. and Judson, Richard S. and Martin, Matthew T. and Weissman, Arthur and Kleinstreuer, Nicole C. and Mortensen, Holly M. and Reif, David M. and et al.}, year={2011}, month={Mar}, pages={1–15} }
 @article{kleinstreuer_judson_reif_sipes_singh_chandler_dewoskin_dix_kavlock_knudsen_2011, title={Environmental Impact on Vascular Development Predicted by High-Throughput Screening}, volume={119}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-80053009778&partnerID=MN8TOARS}, DOI={10.1289/ehp.1103412}, abstractNote={Background: Understanding health risks to embryonic development from exposure to environmental chemicals is a significant challenge given the diverse chemical landscape and paucity of data for most of these compounds. High-throughput screening (HTS) in the U.S. Environmental Protection Agency (EPA) ToxCast™ project provides vast data on an expanding chemical library currently consisting of > 1,000 unique compounds across > 500 in vitro assays in phase I (complete) and Phase II (under way). This public data set can be used to evaluate concentration-dependent effects on many diverse biological targets and build predictive models of prototypical toxicity pathways that can aid decision making for assessments of human developmental health and disease. Objective: We mined the ToxCast phase I data set to identify signatures for potential chemical disruption of blood vessel formation and remodeling. Methods: ToxCast phase I screened 309 chemicals using 467 HTS assays across nine assay technology platforms. The assays measured direct interactions between chemicals and molecular targets (receptors, enzymes), as well as downstream effects on reporter gene activity or cellular consequences. We ranked the chemicals according to individual vascular bioactivity score and visualized the ranking using ToxPi (Toxicological Priority Index) profiles. Results: Targets in inflammatory chemokine signaling, the vascular endothelial growth factor pathway, and the plasminogen-activating system were strongly perturbed by some chemicals, and we found positive correlations with developmental effects from the U.S. EPA ToxRefDB (Toxicological Reference Database) in vivo database containing prenatal rat and rabbit guideline studies. We observed distinctly different correlative patterns for chemicals with effects in rabbits versus rats, despite derivation of in vitro signatures based on human cells and cell-free biochemical targets, implying conservation but potentially differential contributions of developmental pathways among species. Follow-up analysis with antiangiogenic thalidomide analogs and additional in vitro vascular targets showed in vitro activity consistent with the most active environmental chemicals tested here. Conclusions: We predicted that blood vessel development is a target for environmental chemicals acting as putative vascular disruptor compounds (pVDCs) and identified potential species differences in sensitive vascular developmental pathways.}, number={11}, journal={Environ Health Perspect}, publisher={Environmental Health Perspectives}, author={Kleinstreuer, Nicole C. and Judson, Richard S. and Reif, David M. and Sipes, Nisha S. and Singh, Amar V. and Chandler, Kelly J. and DeWoskin, Rob and Dix, David J. and Kavlock, Robert J. and Knudsen, Thomas B.}, year={2011}, month={Jul}, pages={1596–1603} }
 @article{chandler_barrier_jeffay_nichols_kleinstreuer_singh_reif_sipes_judson_dix_et al._2011, title={Evaluation of 309 Environmental Chemicals Using a Mouse Embryonic Stem Cell Adherent Cell Differentiation and Cytotoxicity Assay}, volume={6}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-79958158241&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0018540}, abstractNote={The vast landscape of environmental chemicals has motivated the need for alternative methods to traditional whole-animal bioassays in toxicity testing. Embryonic stem (ES) cells provide an in vitro model of embryonic development and an alternative method for assessing developmental toxicity. Here, we evaluated 309 environmental chemicals, mostly food-use pesticides, from the ToxCast™ chemical library using a mouse ES cell platform. ES cells were cultured in the absence of pluripotency factors to promote spontaneous differentiation and in the presence of DMSO-solubilized chemicals at different concentrations to test the effects of exposure on differentiation and cytotoxicity. Cardiomyocyte differentiation (α,β myosin heavy chain; MYH6/MYH7) and cytotoxicity (DRAQ5™/Sapphire700™) were measured by In-Cell Western™ analysis. Half-maximal activity concentration (AC50) values for differentiation and cytotoxicity endpoints were determined, with 18% of the chemical library showing significant activity on either endpoint. Mining these effects against the ToxCast Phase I assays (∼500) revealed significant associations for a subset of chemicals (26) that perturbed transcription-based activities and impaired ES cell differentiation. Increased transcriptional activity of several critical developmental genes including BMPR2, PAX6 and OCT1 were strongly associated with decreased ES cell differentiation. Multiple genes involved in reactive oxygen species signaling pathways (NRF2, ABCG2, GSTA2, HIF1A) were strongly associated with decreased ES cell differentiation as well. A multivariate model built from these data revealed alterations in ABCG2 transporter was a strong predictor of impaired ES cell differentiation. Taken together, these results provide an initial characterization of metabolic and regulatory pathways by which some environmental chemicals may act to disrupt ES cell growth and differentiation.}, number={6}, journal={PLoS ONE}, publisher={Public Library of Science (PLoS)}, author={Chandler, Kelly J. and Barrier, Marianne and Jeffay, Susan and Nichols, Harriette P. and Kleinstreuer, Nicole C. and Singh, Amar V. and Reif, David M. and Sipes, Nisha S. and Judson, Richard S. and Dix, David J. and et al.}, editor={Cooney, Austin JohnEditor}, year={2011}, month={Jun}, pages={e18540} }
 @article{joubert_reif_edwards_leiner_hudgens_egeghy_gallagher_hubal_2011, title={Evaluation of genetic susceptibility to childhood allergy and asthma in an African American urban population.}, volume={12}, url={http://europepmc.org/abstract/med/21320344}, DOI={10.1186/1471-2350-12-25}, abstractNote={Asthma and allergy represent complex phenotypes, which disproportionately burden ethnic minorities in the United States. Strong evidence for genomic factors predisposing subjects to asthma/allergy is available. However, methods to utilize this information to identify high risk groups are variable and replication of genetic associations in African Americans is warranted. We evaluated 41 single nucleotide polymorphisms (SNP) and a deletion corresponding to 11 genes demonstrating association with asthma in the literature, for association with asthma, atopy, testing positive for food allergens, eosinophilia, and total serum IgE among 141 African American children living in Detroit, Michigan. Independent SNP and haplotype associations were investigated for association with each trait, and subsequently assessed in concert using a genetic risk score (GRS). Statistically significant associations with asthma were observed for SNPs in GSTM1, MS4A2, and GSTP1 genes, after correction for multiple testing. Chromosome 11 haplotype CTACGAGGCC (corresponding to MS4A2 rs574700, rs1441586, rs556917, rs502581, rs502419 and GSTP1 rs6591256, rs17593068, rs1695, rs1871042, rs947895) was associated with a nearly five-fold increase in the odds of asthma (Odds Ratio (OR) = 4.8, p = 0.007). The GRS was significantly associated with a higher odds of asthma (OR = 1.61, 95% Confidence Interval = 1.21, 2.13; p = 0.001). Variation in genes associated with asthma in predominantly non-African ethnic groups contributed to increased odds of asthma in this African American study population. Evaluating all significant variants in concert helped to identify the highest risk subset of this group.}, journal={BMC Medical Genetics}, author={Joubert, BR and Reif, DM and Edwards, SW and Leiner, KA and Hudgens, EE and Egeghy, P and Gallagher, JE and Hubal, EC}, year={2011}, pages={25} }
 @article{gallagher_hudgens_williams_inmon_rhoney_andrews_reif_heidenfelder_neas_williams_et al._2011, title={Mechanistic indicators of childhood asthma (MICA) study: piloting an integrative design for evaluating environmental health.}, volume={11}, url={http://europepmc.org/abstract/med/21595901}, DOI={10.1186/1471-2458-11-344}, abstractNote={Asthma is a common complex disease responsible for considerable morbidity and mortality, particularly in urban minority populations. The Mechanistic Indicators of Childhood Asthma study was designed to pilot an integrative approach in children's health research. The study incorporates exposure metrics, internal dose measures, and clinical indicators to decipher the biological complexity inherent in diseases such as asthma and cardiovascular disease with etiology related to gene-environment interactions. 205 non-asthmatic and asthmatic children, (9-12 years of age) from Detroit, Michigan were recruited. The study includes environmental measures (indoor and outdoor air, vacuum dust), biomarkers of exposure (cotinine, metals, total and allergen specific Immunoglobulin E, polycyclic aromatic hydrocarbons, volatile organic carbon metabolites) and clinical indicators of health outcome (immunological, cardiovascular and respiratory). In addition, blood gene expression and candidate SNP analyses were conducted. Based on an integrative design, the MICA study provides an opportunity to evaluate complex relationships between environmental factors, physiological biomarkers, genetic susceptibility and health outcomes. IRB Number 05-EPA-2637: The human subjects' research protocol was reviewed by the Institutional Review Board (IRB) of the University of North Carolina; the IRB of Westat, Inc., the IRB of the Henry Ford Health System; and EPA's Human Subjects' Research Review Official.}, journal={BMC Public Health}, author={Gallagher, J and Hudgens, E and Williams, A and Inmon, J and Rhoney, S and Andrews, G and Reif, D and Heidenfelder, B and Neas, L and Williams, R and et al.}, year={2011}, pages={344} }
 @inproceedings{hoover_marceau_harris_hardison_reif_motsinger-reif_2011, title={Optimization of grammatical evolution decision trees}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-80051923459&partnerID=MN8TOARS}, DOI={10.1145/2001858.2001879}, abstractNote={The detection of gene-gene and gene-environment interactions in genetic association studies presents a difficult computational and statistical challenge, especially as advances in genotyping technology have rapidly expanded the number of potential genetic predictors in such studies. The scale of these studies makes exhaustive search approaches infeasible, inspiring the application of evolutionary computation algorithms to perform variable selection and build classification models. Recently, an application of grammatical evolution to evolve decision trees (GEDT) has been introduced for detecting interaction models. Initial results were promising, but relied on arbitrary parameter choices for the evolutionary process. In the current study, we present the results of a parameter sweep evaluating the power of GEDT and show that improved parameter choices improves the performance of the method. The results of these experiments are important for the continued optimization, evaluation, and comparison of this and related methods, and for proper application in real data.}, booktitle={Proceedings of the 13th annual conference companion on Genetic and evolutionary computation - GECCO '11}, author={Hoover, Kristopher and Marceau, Rachel and Harris, Tyndall and Hardison, Nicholas and Reif, David and Motsinger-Reif, Alison}, year={2011}, pages={35–36} }
 @article{martin_knudsen_reif_houck_judson_kavlock_dix_2011, title={Predictive model of rat reproductive toxicity from ToxCast high throughput screening.}, volume={85}, url={http://europepmc.org/abstract/med/21565999}, DOI={10.1095/biolreprod.111.090977}, abstractNote={The U.S. Environmental Protection Agency's ToxCast research program uses high throughput screening (HTS) for profiling bioactivity and predicting the toxicity of large numbers of chemicals. ToxCast Phase I tested 309 well-characterized chemicals in more than 500 assays for a wide range of molecular targets and cellular responses. Of the 309 environmental chemicals in Phase I, 256 were linked to high-quality rat multigeneration reproductive toxicity studies in the relational Toxicity Reference Database. Reproductive toxicants were defined here as having achieved a reproductive lowest-observed-adverse-effect level of less than 500 mg kg−1 day−1. Eight-six chemicals were identified as reproductive toxicants in the rat, and 68 of those had sufficient in vitro bioactivity to model. Each assay was assessed for univariate association with the identified reproductive toxicants. Significantly associated assays were linked to gene sets and used for the subsequent predictive modeling. Using linear discriminant analysis and fivefold cross-validation, a robust and stable predictive model was produced capable of identifying rodent reproductive toxicants with 77% ± 2% and 74% ± 5% (mean ± SEM) training and test cross-validation balanced accuracies, respectively. With a 21-chemical external validation set, the model was 76% accurate, further indicating the model's potential for prioritizing the many thousands of environmental chemicals with little to no hazard information. The biological features of the model include steroidal and nonsteroidal nuclear receptors, cytochrome P450 enzyme inhibition, G protein-coupled receptors, and cell signaling pathway readouts—mechanistic information suggesting additional targeted, integrated testing strategies and potential applications of in vitro HTS to risk assessment.}, number={2}, journal={Biology of Reproduction}, author={Martin, MT and Knudsen, TB and Reif, DM and Houck, KA and Judson, RS and Kavlock, RJ and Dix, DJ}, year={2011}, month={Aug}, pages={327–339} }
 @article{sipes_martin_reif_kleinstreuer_judson_singh_chandler_dix_kavlock_knudsen_2011, title={Predictive models of prenatal developmental toxicity from ToxCast high-throughput screening data.}, volume={124}, url={http://europepmc.org/abstract/med/21873373}, DOI={10.1093/toxsci/kfr220}, abstractNote={Environmental Protection Agency's ToxCast project is profiling the in vitro bioactivity of chemicals to assess pathway-level and cell-based signatures that correlate with observed in vivo toxicity. We hypothesized that developmental toxicity in guideline animal studies captured in the ToxRefDB database would correlate with cell-based and cell-free in vitro high-throughput screening (HTS) data to reveal meaningful mechanistic relationships and provide models identifying chemicals with the potential to cause developmental toxicity. To test this hypothesis, we built statistical associations based on HTS and in vivo developmental toxicity data from ToxRefDB. Univariate associations were used to filter HTS assays based on statistical correlation with distinct in vivo endpoint. This revealed 423 total associations with distinctly different patterns for rat (301 associations) and rabbit (122 associations) across multiple HTS assay platforms. From these associations, linear discriminant analysis with cross-validation was used to build the models. Species-specific models of predicted developmental toxicity revealed strong balanced accuracy (> 70%) and unique correlations between assay targets such as transforming growth factor beta, retinoic acid receptor, and G-protein-coupled receptor signaling in the rat and inflammatory signals, such as interleukins (IL) (IL1a and IL8) and chemokines (CCL2), in the rabbit. Species-specific toxicity endpoints were associated with one another through common Gene Ontology biological processes, such as cleft palate to urogenital defects through placenta and embryonic development. This work indicates the utility of HTS assays for developing pathway-level models predictive of developmental toxicity.}, number={1}, journal={Toxicological Sciences}, author={Sipes, NS and Martin, MT and Reif, DM and Kleinstreuer, NC and Judson, RS and Singh, AV and Chandler, KJ and Dix, DJ and Kavlock, RJ and Knudsen, TB}, year={2011}, month={Nov}, pages={109–127} }
 @article{shah_houck_judson_kavlock_martin_reif_wambaugh_dix_2011, title={Using Nuclear Receptor Activity to Stratify Hepatocarcinogens}, volume={6}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-79951900953&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0014584}, abstractNote={Background Nuclear receptors (NR) are a superfamily of ligand-activated transcription factors that control a range of cellular processes. Persistent stimulation of some NR is a non-genotoxic mechanism of rodent liver cancer with unclear relevance to humans. Here we report on a systematic analysis of new in vitro human NR activity data on 309 environmental chemicals in relationship to their liver cancer-related chronic outcomes in rodents. Results The effects of 309 environmental chemicals on human constitutive androstane receptors (CAR/NR1I3), pregnane X receptor (PXR/NR1I2), aryl hydrocarbon receptor (AhR), peroxisome proliferator-activated receptors (PPAR/NR1C), liver X receptors (LXR/NR1H), retinoic X receptors (RXR/NR2B) and steroid receptors (SR/NR3) were determined using in vitro data. Hepatic histopathology, observed in rodents after two years of chronic treatment for 171 of the 309 chemicals, was summarized by a cancer lesion progression grade. Chemicals that caused proliferative liver lesions in both rat and mouse were generally more active for the human receptors, relative to the compounds that only affected one rodent species, and these changes were significant for PPAR (p0.001), PXR (p0.01) and CAR (p0.05). Though most chemicals exhibited receptor promiscuity, multivariate analysis clustered them into relatively few NR activity combinations. The human NR activity pattern of chemicals weakly associated with the severity of rodent liver cancer lesion progression (p0.05). Conclusions The rodent carcinogens had higher in vitro potency for human NR relative to non-carcinogens. Structurally diverse chemicals with similar NR promiscuity patterns weakly associated with the severity of rodent liver cancer progression. While these results do not prove the role of NR activation in human liver cancer, they do have implications for nuclear receptor chemical biology and provide insights into putative toxicity pathways. More importantly, these findings suggest the utility of in vitro assays for stratifying environmental contaminants based on a combination of human bioactivity and rodent toxicity.}, number={2}, journal={PLoS ONE}, author={Shah, Imran and Houck, Keith and Judson, Richard S. and Kavlock, Robert J. and Martin, Matthew T. and Reif, David M. and Wambaugh, John and Dix, David J.}, editor={Wölfl, StefanEditor}, year={2011}, month={Feb} }
 @article{judson_martin_reif_houck_knudsen_rotroff_xia_sakamuru_huang_shinn_et al._2010, title={Analysis of eight oil spill dispersants using rapid, in vitro tests for endocrine and other biological activity.}, volume={44}, url={http://europepmc.org/abstract/med/20602530}, DOI={10.1021/es102150z}, abstractNote={The Deepwater Horizon oil spill has led to the use of >1 M gallons of oil spill dispersants, which are mixtures of surfactants and solvents. Because of this large scale use there is a critical need to understand the potential for toxicity of the currently used dispersant and potential alternatives, especially given the limited toxicity testing information that is available. In particular, some dispersants contain nonylphenol ethoxylates (NPEs), which can degrade to nonylphenol (NP), a known endocrine disruptor. Given the urgent need to generate toxicity data, we carried out a series of in vitro high-throughput assays on eight commercial dispersants. These assays focused on the estrogen and androgen receptors (ER and AR), but also included a larger battery of assays probing other biological pathways. Cytotoxicity in mammalian cells was also quantified. No activity was seen in any AR assay. Two dispersants showed a weak ER signal in one assay (EC50 of 16 ppm for Nokomis 3-F4 and 25 ppm for ZI-400). NPs and NPEs also had a weak signal in this same ER assay. Note that Corexit 9500, the currently used product, does not contain NPEs and did not show any ER activity. Cytotoxicity values for six of the dispersants were statistically indistinguishable, with median LC50 values approximately 100 ppm. Two dispersants, JD 2000 and SAF-RON GOLD, were significantly less cytotoxic than the others with LC50 values approaching or exceeding 1000 ppm.}, number={15}, journal={Environmental Science and Technology}, author={Judson, RS and Martin, MT and Reif, DM and Houck, KA and Knudsen, TB and Rotroff, DM and Xia, M and Sakamuru, S and Huang, R and Shinn, P and et al.}, year={2010}, month={Aug}, pages={5979–5985} }
 @article{reif_martin_tan_houck_judson_richard_knudsen_dix_kavlock_2010, title={Endocrine Profiling and Prioritization of Environmental Chemicals Using ToxCast Data}, volume={118}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-78650284457&partnerID=MN8TOARS}, DOI={10.1289/ehp.1002180}, abstractNote={Background The prioritization of chemicals for toxicity testing is a primary goal of the U.S. Environmental Protection Agency (EPA) ToxCast™ program. Phase I of ToxCast used a battery of 467 in vitro, high-throughput screening assays to assess 309 environmental chemicals. One important mode of action leading to toxicity is endocrine disruption, and the U.S. EPA’s Endocrine Disruptor Screening Program (EDSP) has been charged with screening pesticide chemicals and environmental contaminants for their potential to affect the endocrine systems of humans and wildlife. Objective The goal of this study was to develop a flexible method to facilitate the rational prioritization of chemicals for further evaluation and demonstrate its application as a candidate decision-support tool for EDSP. Methods Focusing on estrogen, androgen, and thyroid pathways, we defined putative endocrine profiles and derived a relative rank or score for the entire ToxCast library of 309 unique chemicals. Effects on other nuclear receptors and xenobiotic metabolizing enzymes were also considered, as were pertinent chemical descriptors and pathways relevant to endocrine-mediated signaling. Results Combining multiple data sources into an overall, weight-of-evidence Toxicological Priority Index (ToxPi) score for prioritizing further chemical testing resulted in more robust conclusions than any single data source taken alone. Conclusions Incorporating data from in vitro assays, chemical descriptors, and biological pathways in this prioritization schema provided a flexible, comprehensive visualization and ranking of each chemical’s potential endocrine activity. Importantly, ToxPi profiles provide a transparent visualization of the relative contribution of all information sources to an overall priority ranking. The method developed here is readily adaptable to diverse chemical prioritization tasks.}, number={12}, journal={Environ Health Perspect}, publisher={Environmental Health Perspectives}, author={Reif, David M. and Martin, Matthew T. and Tan, Shirlee W. and Houck, Keith A. and Judson, Richard S. and Richard, Ann M. and Knudsen, Thomas B. and Dix, David J. and Kavlock, Robert J.}, year={2010}, month={Sep}, pages={1714–1720} }
 @article{martin_dix_judson_kavlock_reif_richard_rotroff_romanov_medvedev_poltoratskaya_et al._2010, title={Impact of environmental chemicals on key transcription regulators and correlation to toxicity end points within EPA's ToxCast program.}, volume={23}, url={http://europepmc.org/abstract/med/20143881}, DOI={10.1021/tx900325g}, abstractNote={Exposure to environmental chemicals adds to the burden of disease in humans and wildlife to a degree that is difficult to estimate and, thus, mitigate. The ability to assess the impact of existing chemicals for which little to no toxicity data are available or to foresee such effects during early stages of chemical development and use, and before potential exposure occurs, is a pressing need. However, the capacity of the current toxicity evaluation approaches to meet this demand is limited by low throughput and high costs. In the context of EPA's ToxCast project, we have evaluated a novel cellular biosensor system (Factorial (1) ) that enables rapid, high-content assessment of a compound's impact on gene regulatory networks. The Factorial biosensors combined libraries of cis- and trans-regulated transcription factor reporter constructs with a highly homogeneous method of detection enabling simultaneous evaluation of multiplexed transcription factor activities. Here, we demonstrate the application of the technology toward determining bioactivity profiles by quantitatively evaluating the effects of 309 environmental chemicals on 25 nuclear receptors and 48 transcription factor response elements. We demonstrate coherent transcription factor activity across nuclear receptors and their response elements and that Nrf2 activity, a marker of oxidative stress, is highly correlated to the overall promiscuity of a chemical. Additionally, as part of the ToxCast program, we identify molecular targets that associate with in vivo end points and represent modes of action that can serve as potential toxicity pathway biomarkers and inputs for predictive modeling of in vivo toxicity.}, number={3}, journal={Chemical Research in Toxicology}, author={Martin, MT and Dix, DJ and Judson, RS and Kavlock, RJ and Reif, DM and Richard, AM and Rotroff, DM and Romanov, S and Medvedev, A and Poltoratskaya, N and et al.}, year={2010}, month={Mar}, pages={578–590} }
 @article{judson_houck_kavlock_knudsen_martin_mortensen_reif_rotroff_shah_richard_et al._2010, title={In vitro screening of environmental chemicals for targeted testing prioritization: The toxcast project}, volume={118}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-77951675220&partnerID=MN8TOARS}, DOI={10.1289/ehp.0901392}, abstractNote={Background Chemical toxicity testing is being transformed by advances in biology and computer modeling, concerns over animal use, and the thousands of environmental chemicals lacking toxicity data. The U.S. Environmental Protection Agency’s ToxCast program aims to address these concerns by screening and prioritizing chemicals for potential human toxicity using in vitro assays and in silico approaches. Objectives This project aims to evaluate the use of in vitro assays for understanding the types of molecular and pathway perturbations caused by environmental chemicals and to build initial prioritization models of in vivo toxicity. Methods We tested 309 mostly pesticide active chemicals in 467 assays across nine technologies, including high-throughput cell-free assays and cell-based assays, in multiple human primary cells and cell lines plus rat primary hepatocytes. Both individual and composite scores for effects on genes and pathways were analyzed. Results Chemicals displayed a broad spectrum of activity at the molecular and pathway levels. We saw many expected interactions, including endocrine and xenobiotic metabolism enzyme activity. Chemicals ranged in promiscuity across pathways, from no activity to affecting dozens of pathways. We found a statistically significant inverse association between the number of pathways perturbed by a chemical at low in vitro concentrations and the lowest in vivo dose at which a chemical causes toxicity. We also found associations between a small set of in vitro assays and rodent liver lesion formation. Conclusions This approach promises to provide meaningful data on the thousands of untested environmental chemicals and to guide targeted testing of environmental contaminants.}, number={4}, journal={Environmental Health Perspectives}, publisher={Environmental Health Perspectives}, author={Judson, Richard S. and Houck, Keith A. and Kavlock, Robert J. and Knudsen, Thomas B. and Martin, Matthew T. and Mortensen, Holly M. and Reif, David M. and Rotroff, Daniel M. and Shah, Imran and Richard, Ann M. and et al.}, year={2010}, pages={485–492} }
 @article{rotroff_wetmore_dix_ferguson_clewell_houck_lecluyse_andersen_judson_smith_et al._2010, title={Incorporating human dosimetry and exposure into high-throughput in vitro toxicity screening.}, volume={117}, url={http://europepmc.org/abstract/med/20639261}, DOI={10.1093/toxsci/kfq220}, abstractNote={Many chemicals in commerce today have undergone limited or no safety testing. To reduce the number of untested chemicals and prioritize limited testing resources, several governmental programs are using high-throughput in vitro screens for assessing chemical effects across multiple cellular pathways. In this study, metabolic clearance and plasma protein binding were experimentally measured for 35 ToxCast phase I chemicals. The experimental data were used to parameterize a population-based in vitro-to-in vivo extrapolation model for estimating the human oral equivalent dose necessary to produce a steady-state in vivo concentration equivalent to in vitro AC(50) (concentration at 50% of maximum activity) and LEC (lowest effective concentration) values from the ToxCast data. For 23 of the 35 chemicals, the range of oral equivalent doses for up to 398 ToxCast assays was compared with chronic aggregate human oral exposure estimates in order to assess whether significant in vitro bioactivity occurred within the range of maximum expected human oral exposure. Only 2 of the 35 chemicals, triclosan and pyrithiobac-sodium, had overlapping oral equivalent doses and estimated human oral exposures. Ranking by the potencies of the AC(50) and LEC values, these two chemicals would not have been at the top of a prioritization list. Integrating both dosimetry and human exposure information with the high-throughput toxicity screening efforts provides a better basis for making informed decisions on chemical testing priorities and regulatory attention. Importantly, these tools are necessary to move beyond hazard rankings to estimates of possible in vivo responses based on in vitro screens.}, number={2}, journal={Toxicological Sciences}, author={Rotroff, DM and Wetmore, BA and Dix, DJ and Ferguson, SS and Clewell, HJ and Houck, KA and Lecluyse, EL and Andersen, ME and Judson, RS and Smith, CM and et al.}, year={2010}, month={Oct}, pages={348–358} }
 @article{sanchez_deener_hubal_knowlton_reif_segal_2010, title={Research needs for community-based risk assessment: findings from a multi-disciplinary workshop}, volume={20}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-77149156693&partnerID=MN8TOARS}, DOI={10.1038/jes.2009.8}, abstractNote={Communities face exposures to multiple environmental toxicants and other non-chemical stressors. In addition, communities have unique activities and norms that influence exposure and vulnerability. Yet, few studies quantitatively consider the role of cumulative exposure and additive impacts. Community-based risk assessment (CBRA) is a new approach for risk assessment that aims to address the cumulative stressors faced by a particular community, while incorporating a community-based participatory research framework. This paper summarizes an Environmental Protection Agency (EPA) sponsored workshop, “Research Needs for Community-Based Risk Assessment.” This workshop brought together environmental and public health scientists and practitioners for fostering an innovative discussion about tools, methods, models, and approaches for CBRA. This workshop was organized around three topics: (1) Data and Measurement Methods; (2) The Biological Impact of Non-Chemical Stressors and Interaction with Environmental Exposures; and (3) Statistical and Mathematical Modeling. This report summarizes the workshop discussions, presents identified research needs, and explores future research opportunities in this emerging field.}, number={2}, journal={J Expos Sci Environ Epidemiol}, publisher={Nature Publishing Group}, author={Sanchez, Yolanda Anita and Deener, Kacee and Hubal, Elaine Cohen and Knowlton, Carrie and Reif, David and Segal, Deborah}, year={2010}, month={Mar}, pages={186–195} }
 @article{rotroff_beam_dix_farmer_freeman_houck_judson_lecluyse_martin_reif_et al._2010, title={Xenobiotic-metabolizing enzyme and transporter gene expression in primary cultures of human hepatocytes modulated by ToxCast chemicals.}, volume={13}, url={http://europepmc.org/abstract/med/20574906}, DOI={10.1080/10937404.2010.483949}, abstractNote={Primary human hepatocyte cultures are useful in vitro model systems of human liver because when cultured under appropriate conditions the hepatocytes retain liver-like functionality such as metabolism, transport, and cell signaling. This model system was used to characterize the concentration- and time-response of the 320 ToxCast chemicals for changes in expression of genes regulated by nuclear receptors. Fourteen gene targets were monitored in quantitative nuclease protection assays: six representative cytochromes P-450, four hepatic transporters, three Phase II conjugating enzymes, and one endogenous metabolism gene involved in cholesterol synthesis. These gene targets are sentinels of five major signaling pathways: AhR, CAR, PXR, FXR, and PPARα. Besides gene expression, the relative potency and efficacy for these chemicals to modulate cellular health and enzymatic activity were assessed. Results demonstrated that the culture system was an effective model of chemical-induced responses by prototypical inducers such as phenobarbital and rifampicin. Gene expression results identified various ToxCast chemicals that were potent or efficacious inducers of one or more of the 14 genes, and by inference the 5 nuclear receptor signaling pathways. Significant relative risk associations with rodent in vivo chronic toxicity effects are reported for the five major receptor pathways. These gene expression data are being incorporated into the larger ToxCast predictive modeling effort.}, number={2-4}, journal={Journal of Toxicology and Environmental Health - Part B: Critical Reviews}, author={Rotroff, DM and Beam, AL and Dix, DJ and Farmer, A and Freeman, KM and Houck, KA and Judson, RS and LeCluyse, EL and Martin, MT and Reif, DM and et al.}, year={2010}, month={Feb}, pages={329–346} }
 @article{motsinger-reif_reif_fanelli_ritchie_2009, title={A Comparison of Analytical Methods for Genetic Association Studies (vol 32, pg 767, 2008)}, volume={33}, ISSN={["0741-0395"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-71249125696&partnerID=MN8TOARS}, DOI={10.1002/gepi.20420}, abstractNote={Genetic EpidemiologyVolume 33, Issue 8 p. 751-751 ErratumFree Access A comparison of analytical methods for genetic association studies Alison A. Motsinger-Reif, Alison A. Motsinger-Reif Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, North CarolinaSearch for more papers by this authorDavid M. Reif, David M. Reif National Center for Computational Toxicology, US Environmental Protection Agency, Research Triangle Park, North CarolinaSearch for more papers by this authorTheresa J. Fanelli, Theresa J. Fanelli Center for Human Genetics Research and Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TennesseeSearch for more papers by this authorMarylyn D. Ritchie, Marylyn D. Ritchie Center for Human Genetics Research and Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TennesseeSearch for more papers by this author Alison A. Motsinger-Reif, Alison A. Motsinger-Reif Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, North CarolinaSearch for more papers by this authorDavid M. Reif, David M. Reif National Center for Computational Toxicology, US Environmental Protection Agency, Research Triangle Park, North CarolinaSearch for more papers by this authorTheresa J. Fanelli, Theresa J. Fanelli Center for Human Genetics Research and Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TennesseeSearch for more papers by this authorMarylyn D. Ritchie, Marylyn D. Ritchie Center for Human Genetics Research and Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TennesseeSearch for more papers by this author First published: 17 March 2009 https://doi.org/10.1002/gepi.20420AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume33, Issue8December 2009Pages 751-751 RelatedInformation}, number={8}, journal={GENETIC EPIDEMIOLOGY}, publisher={Wiley-Blackwell}, author={Motsinger-Reif, Alison A. and Reif, David M. and Fanelli, Theresa J. and Ritchie, Marylyn D.}, year={2009}, month={Dec}, pages={751–751} }
 @article{heidenfelder_reif_harkema_cohen hubal_hudgens_bramble_wagner_morishita_keeler_edwards_et al._2009, title={Comparative microarray analysis and pulmonary changes in Brown Norway rats exposed to ovalbumin and concentrated air particulates.}, volume={108}, url={http://europepmc.org/abstract/med/19176365}, DOI={10.1093/toxsci/kfp005}, abstractNote={The interaction between air particulates and genetic susceptibility has been implicated in the pathogenesis of asthma. The overall objective of this study was to determine the effects of inhalation exposure to environmentally relevant concentrated air particulates (CAPs) on the lungs of ovalbumin (ova) sensitized and challenged Brown Norway rats. Changes in gene expression were compared with lung tissue histopathology, morphometry, and biochemical and cellular parameters in bronchoalveolar lavage fluid (BALF). Ova challenge was responsible for the preponderance of gene expression changes, related largely to inflammation. CAPs exposure alone resulted in no significant gene expression changes, but CAPs and ova-exposed rodents exhibited an enhanced effect relative to ova alone with differentially expressed genes primarily related to inflammation and airway remodeling. Gene expression data was consistent with the biochemical and cellular analyses of the BALF, the pulmonary pathology, and morphometric changes when comparing the CAPs-ova group to the air-saline or CAPs-saline group. However, the gene expression data were more sensitive than the BALF cell type and number for assessing the effects of CAPs and ova versus the ova challenge alone. In addition, the gene expression results provided some additional insight into the TGF-beta-mediated molecular processes underlying these changes. The broad-based histopathology and functional genomic analyses demonstrate that exposure to CAPs exacerbates rodents with allergic inflammation induced by an allergen and suggests that asthmatics may be at increased risk for air pollution effects.}, number={1}, journal={Toxicological Sciences}, author={Heidenfelder, B.L. and Reif, D.M. and Harkema, J.R. and Cohen Hubal, E.A. and Hudgens, E.E. and Bramble, L.A. and Wagner, J.G. and Morishita, M. and Keeler, G.J. and Edwards, S.W. and et al.}, year={2009}, month={Mar}, pages={207–221} }
 @article{reif_motsinger-reif_mckinney_rock_crowe_moore_2009, title={Integrated analysis of genetic and proteomic data identifies biomarkers associated with adverse events following smallpox vaccination}, volume={10}, ISSN={["1476-5470"]}, url={http://europepmc.org/abstract/med/18923431}, DOI={10.1038/gene.2008.80}, abstractNote={Complex clinical outcomes, such as adverse reaction to vaccination, arise from the concerted interactions among the myriad components of a biological system. Therefore, comprehensive etiological models can be developed only through the integrated study of multiple types of experimental data. In this study, we apply this paradigm to high-dimensional genetic and proteomic data collected to elucidate the mechanisms underlying the development of adverse events (AEs) in patients after smallpox vaccination. As vaccination was successful in all of the patients under study, the AE outcomes reported likely represent the result of interactions among immune system components that result in excessive or prolonged immune stimulation. In this study, we examined 1442 genetic variables (single nucleotide polymorphisms) and 108 proteomic variables (serum cytokine concentrations) to model AE risk. To accomplish this daunting analytical task, we employed the Random Forests (RF) method to filter the most important attributes, then we used the selected attributes to build a final decision tree model. This strategy is well suited to integrated analysis, as relevant attributes may be selected from categorical or continuous data. Importantly, RF is a natural approach for studying the type of gene–gene, gene–protein and protein–protein interactions we hypothesize to be involved in the development of clinical AEs. RF importance scores for particular attributes take interactions into account, and there may be interactions across data types. Combining information from previous studies on AEs related to smallpox vaccination with the genetic and proteomic attributes identified by RF, we built a comprehensive model of AE development that includes the cytokines intercellular adhesion molecule-1 (ICAM-1 or CD54), interleukin-10 (IL-10), and colony stimulating factor-3 (CSF-3 or G-CSF) and a genetic polymorphism in the cyokine gene interleukin-4 (IL4). The biological factors included in the model support our hypothesized mechanism for the development of AEs involving prolonged stimulation of inflammatory pathways and an imbalance of normal tissue damage repair pathways. This study shows the utility of RF for such analytical tasks, while both enhancing and reinforcing our working model of AE development after smallpox vaccination.}, number={2}, journal={GENES AND IMMUNITY}, author={Reif, D. M. and Motsinger-Reif, A. A. and McKinney, B. A. and Rock, M. T. and Crowe, J. E., Jr. and Moore, J. H.}, year={2009}, month={Mar}, pages={112–119} }
 @article{martin_judson_reif_kavlock_dix_2009, title={Profiling Chemicals Based on Chronic Toxicity Results from the U.S. EPA ToxRef Database}, volume={117}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-64049119418&partnerID=MN8TOARS}, DOI={10.1289/ehp.0800074}, abstractNote={Background Thirty years of pesticide registration toxicity data have been historically stored as hardcopy and scanned documents by the U.S. Environmental Protection Agency (EPA). A significant portion of these data have now been processed into standardized and structured toxicity data within the EPA’s Toxicity Reference Database (ToxRefDB), including chronic, cancer, developmental, and reproductive studies from laboratory animals. These data are now accessible and mineable within ToxRefDB and are serving as a primary source of validation for U.S. EPA’s ToxCast research program in predictive toxicology. Objectives We profiled in vivo toxicities across 310 chemicals as a model application of ToxRefDB, meeting the need for detailed anchoring end points for development of ToxCast predictive signatures. Methods Using query and structured data-mining approaches, we generated toxicity profiles from ToxRefDB based on long-term rodent bioassays. These chronic/cancer data were analyzed for suitability as anchoring end points based on incidence, target organ, severity, potency, and significance. Results Under conditions of the bioassays, we observed pathologies for 273 of 310 chemicals, with greater preponderance (> 90%) occurring in the liver, kidney, thyroid, lung, testis, and spleen. We observed proliferative lesions for 225 chemicals, and 167 chemicals caused progression to cancer-related pathologies. Conclusions Based on incidence, severity, and potency, we selected 26 primarily tissue-specific pathology end points to uniformly classify the 310 chemicals. The resulting toxicity profile classifications demonstrate the utility of structuring legacy toxicity information and facilitating the computation of these data within ToxRefDB for ToxCast and other applications.}, number={3}, journal={Environ Health Perspect}, publisher={Environmental Health Perspectives}, author={Martin, Matthew T. and Judson, Richard S. and Reif, David M. and Kavlock, Robert J. and Dix, David J.}, year={2009}, month={Mar}, pages={392–399} }
 @article{motsinger-reif_reif_fanelli_ritchie_2008, title={A Comparison of Analytical Methods for Genetic Association Studies}, volume={32}, ISSN={["1098-2272"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-58149346724&partnerID=MN8TOARS}, DOI={10.1002/gepi.20345}, abstractNote={Abstract}, number={8}, journal={GENETIC EPIDEMIOLOGY}, publisher={Wiley-Blackwell}, author={Motsinger-Reif, Alison A. and Reif, David M. and Fanelli, Theresa J. and Ritchie, Marylyn D.}, year={2008}, month={Dec}, pages={767–778} }
 @inproceedings{hardison_fanelli_dudek_reif_ritchie_motsinger-reif_2008, title={A balanced accuracy fitness function leads to robust analysis using grammatical evolution neural networks in the case of class imbalance}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-57349087730&partnerID=MN8TOARS}, DOI={10.1145/1389095.1389159}, abstractNote={Grammatical Evolution Neural Networks (GENN) is a computational method designed to detect gene-gene interactions in genetic epidemiology, but has so far only been evaluated in situations with balanced numbers of cases and controls. Real data, however, rarely has such perfectly balanced classes. In the current study, we test the power of GENN to detect interactions in data with a range of class imbalance using two fitness functions (classification error and balanced error), as well as data re-sampling. We show that when using classification error, class imbalance greatly decreases the power of GENN. Re-sampling methods demonstrated improved power, but using balanced accuracy resulted in the highest power. Based on the results of this study, balanced error has replaced classification error in the GENN algorithm}, booktitle={Proceedings of the 10th annual conference on Genetic and evolutionary computation - GECCO '08}, publisher={ACM Press}, author={Hardison, Nicholas E. and Fanelli, Theresa J. and Dudek, Scott M. and Reif, David M. and Ritchie, Marylyn D. and Motsinger-Reif, Alison A.}, year={2008}, pages={353–354} }
 @article{reif_mckinney_motsinger_chanock_edwards_rock_moore_crowe, jr._2008, title={Genetic Basis for Adverse Events after Smallpox Vaccination}, volume={198}, ISSN={0022-1899 1537-6613}, url={http://dx.doi.org/10.1086/588670}, DOI={10.1086/588670}, abstractNote={Identifying genetic factors associated with the development of adverse events might allow screening before vaccinia virus administration. Two independent clinical trials of the smallpox vaccine (Aventis Pasteur) were conducted in healthy, vaccinia virus-naive adult volunteers. Volunteers were assessed repeatedly for local and systemic adverse events (AEs) associated with the receipt of vaccine and underwent genotyping for 1,442 singlenucleotide polymorphisms (SNPs). In the first study, 36 SNPs in 26 genes were associated with systemic AEs (P <or= .05); these 26 genes were tested in the second study. In the final analysis, 3 SNPs were consistently associated with AEs in both studies. The presence of a nonsynonymous SNP in the methylenetetrahydrofolate reductase (MTHFR)gene was associated with the risk ofAEin both trials (odds ratio [OR], 2.3 [95% confidence interval {CI}, 1.1-5.2] [P = .04] and OR, 4.1 [95% CI, 1.4 -11.4] [P<.01]). Two SNPs in the interferon regulatory factor-1 (IRF1) gene were associated with the risk of AE in both sample sets (OR, 3.2 [95% CI, 1.1-9.8] [P = .03] andOR, 3.0 [95% CI, 1.1- 8.3] [P = .03]). Genetic polymorphisms in genes expressing an enzyme previously associated with adverse reactions to a variety of pharmacologic agents (MTHFR) and an immunological transcription factor (IRF1) were associated with AEs after smallpox vaccination in 2 independent study samples.}, number={1}, journal={The Journal of Infectious Diseases}, publisher={Oxford University Press (OUP)}, author={Reif, David M. and McKinney, Brett A. and Motsinger, Alison A. and Chanock, Stephen J. and Edwards, Kathryn M. and Rock, Michael T. and Moore, Jason H. and Crowe, Jr., James E.}, year={2008}, month={Jul}, pages={16–22} }
 @article{reif_mckinney_motsinger_2008, title={Genetic basis for adverse events after smallpox vaccination (Journal of Infectious Diseases (2008) 198, (16-22))}, volume={198}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-50949110273&partnerID=MN8TOARS}, DOI={10.1086/590918}, abstractNote={In the 1 July 2008 issue of the Journal, in the article by Reif et al. (Reif DM, McKinney BA, Motsinger AA, et al. Genetic basis for adverse events after smallpox vaccination. J Infect Dis 2008; 198:16–22), there are labeling errors in table 3: for both the 839 SNP of gene IRF1 and the 2243290 SNP of gene IL4, the genotype labels for the second and third rows should be transposed; the corrected genotype labels are as follows (note that, although the labels have been transposed, the frequencies remain the same):}, number={5}, journal={Journal of Infectious Diseases}, author={Reif, D.M. and McKinney, B.A. and Motsinger, A.A.}, year={2008} }
 @article{mckinney_reif_white_je_moore_bioinformatics_2007, title={Evaporative cooling feature selection for genotypic data involving interactions.}, volume={23}, url={http://europepmc.org/abstract/med/17586549}, DOI={10.1093/bioinformatics/btm317}, abstractNote={Abstract}, number={16}, journal={Bioinformatics}, author={McKinney, B.A. and Reif, D.M. and White, B.C. and Je, Crowe and Moore, J.H. and Bioinformatics}, year={2007}, month={Aug}, pages={2113–2120} }
 @article{reif_israel_moore_2007, title={Exploratory Visual Analysis of statistical results from microarray experiments comparing high and low grade glioma.}, volume={5}, url={http://europepmc.org/abstract/med/19390666}, journal={Cancer Informatics}, author={Reif, DM and Israel, MA and Moore, JH}, year={2007}, pages={19–24} }
 @article{motsinger_reif_fanelli_davis_ritchie_2007, title={Linkage Disequilibrium in Genetic Association Studies Improves the Performance of Grammatical Evolution Neural Networks.}, volume={2007}, url={http://europepmc.org/abstract/med/21572972}, journal={Proceedings of the ... IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology}, author={Motsinger, A.A. and Reif, D.M. and Fanelli, T.J. and Davis, A.C. and Ritchie, M.D.}, year={2007}, month={Apr}, pages={1–8} }
 @inproceedings{motsinger_reif_fanelli_davis_ritchie_2007, title={Linkage disequilibrium in genetic association studies improves the performance of grammatical evolution neural networks}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-67650698880&partnerID=MN8TOARS}, booktitle={2007 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology, CIBCB 2007}, author={Motsinger, A.A. and Reif, D.M. and Fanelli, T.J. and Davis, A.C. and Ritchie, M.D.}, year={2007}, pages={1–8} }
 @article{motsinger_ritchie_reif_2007, title={Novel methods for detecting epistasis in pharmacogenomics studies}, volume={8}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-35348900731&partnerID=MN8TOARS}, DOI={10.2217/14622416.8.9.1229}, abstractNote={The importance of gene–gene and gene–environment interactions in the underlying genetic architecture of common, complex phenotypes is gaining wide recognition in the field of pharmacogenomics. In epidemiological approaches to mapping genetic variants that predict drug response, it is important that researchers investigate potential epistatic interactions. In the current review, we discuss data-mining tools available in genetic epidemiology to detect such interactions and appropriate applications. We survey several classes of novel methods available and present an organized collection of successful applications in the literature. Finally, we provide guidance as to how to incorporate these novel methods into a genetic analysis. The overall goal of this paper is to aid researchers in developing an analysis plan that accounts for gene–gene and gene–environment in their own work.}, number={9}, journal={Pharmacogenomics}, publisher={Future Medicine Ltd}, author={Motsinger, Alison A and Ritchie, Marylyn D and Reif, David M}, year={2007}, month={Sep}, pages={1229–1241} }
 @article{mckinney_reif_rock_edwards_kingsmore_moore_je_2006, title={Cytokine expression patterns associated with systemic adverse events following smallpox immunization.}, volume={194}, url={http://europepmc.org/abstract/med/16845627}, DOI={10.1086/505503}, abstractNote={Vaccinia virus is reactogenic in a significant number of vaccinees, with the most common adverse events being fever, lymphadenopathy, and rash. Although the inoculation is given in the skin, these adverse events suggest a robust systemic inflammatory response. To elucidate the cytokine response signature of systemic adverse events, we used a protein microarray technique to precisely quantitate 108 serum cytokines and chemokines in vaccine recipients before and 1 week after primary immunization with Aventis Pasteur smallpox vaccine. We studied 74 individuals after vaccination, of whom 22 experienced a systemic adverse event and 52 did not. The soluble factors most associated with adverse events were selected on the basis of voting among a committee of machine-learning methods and statistical procedures, and the selected cytokines were used to build a final decision-tree model. On the basis of changes in protein expression, we identified 6 cytokines that accurately discriminate between individuals on the basis of adverse event status: granulocyte colony-stimulating factor, stem cell factor, monokine induced by interferon-gamma (CXCL9), intercellular adhesion molecule-1, eotaxin, and tissue inhibitor of metalloproteinases-2. This cytokine signature is characteristic of particular inflammatory response pathways and suggests that the secretion of cytokines by fibroblasts plays a central role in systemic adverse events.}, number={4}, journal={Journal of Infectious Diseases}, author={McKinney, BA and Reif, DM and Rock, MT and Edwards, KM and Kingsmore, SF and Moore, JH and JE, Crowe, Jr}, year={2006}, month={Aug}, pages={444–453} }
 @inproceedings{feature selection using a random forests classifier for the integrated analysis of multiple data types_2006, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-50249116072&partnerID=MN8TOARS}, DOI={10.1109/CIBCB.2006.330987}, abstractNote={Complex clinical phenotypes arise from the concerted interactions among the myriad components of a biological system. Therefore, comprehensive models can only be developed through the integrated study of multiple types of experimental data gathered from the system in question. The Random Foreststrade(RF) method is adept at identifying relevant features having only slight main effects in high-dimensional data. This method is well-suited to integrated analysis, as relevant attributes may be selected from categorical or continuous data, and there may be interactions across data types. RF is a natural approach for studying gene-gene, gene-protein, or protein-protein interactions because importance scores for particular attributes take interactions into account. Thus, Random Forests is a promising solution to the analysis challenge posed by high-dimensional datasets including interactions among attributes of different types. In this study, we characterize the performance of RF on a range of simulated genetic and/or proteomic datasets. We compare the performance of RF in identifying relevant attributes when given genetic data alone, proteomic data alone, or a combined dataset of genetic plus proteomic data. Our results indicate that utilizing multiple data types is beneficial when the disease model is complex and the phenotypic outcome-associated data type is unknown. The results of this study also show that RF is adept at identifying relevant features in high-dimensional data with small main effects and low heritability}, booktitle={Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06}, year={2006}, pages={171–178} }
 @article{reif_libraries_2006, title={Integrated analysis of genetic and proteomic data.}, url={http://europepmc.org/theses/ETH/7299}, author={Reif, D.M. and Libraries, Vanderbilt University}, year={2006} }
 @article{mckinney_reif_ritchie_moore_2006, title={Machine Learning for Detecting Gene-Gene Interactions}, volume={5}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-33744937046&partnerID=MN8TOARS}, DOI={10.2165/00822942-200605020-00002}, abstractNote={Complex interactions among genes and environmental factors are known to play a role in common human disease aetiology. There is a growing body of evidence to suggest that complex interactions are 'the norm' and, rather than amounting to a small perturbation to classical Mendelian genetics, interactions may be the predominant effect. Traditional statistical methods are not well suited for detecting such interactions, especially when the data are high dimensional (many attributes or independent variables) or when interactions occur between more than two polymorphisms. In this review, we discuss machine-learning models and algorithms for identifying and characterising susceptibility genes in common, complex, multifactorial human diseases. We focus on the following machine-learning methods that have been used to detect gene-gene interactions: neural networks, cellular automata, random forests, and multifactor dimensionality reduction. We conclude with some ideas about how these methods and others can be integrated into a comprehensive and flexible framework for data mining and knowledge discovery in human genetics.}, number={2}, journal={Applied Bioinformatics}, publisher={Springer Science + Business Media}, author={McKinney, Brett A and Reif, David M and Ritchie, Marylyn D and Moore, Jason H}, year={2006}, pages={77–88} }
 @inproceedings{motsinger_reif_dudek_ritchie_2006, title={Understanding the evolutionary process of grammatical evolution neural networks for feature selection in genetic epidemiology}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-50249087395&partnerID=MN8TOARS}, DOI={10.1109/CIBCB.2006.330945}, abstractNote={The identification of genetic factors/features that predict complex diseases is an important goal of human genetics. The commonality of gene-gene interactions in the underlying genetic architecture of common diseases presents a daunting analytical challenge. Previously, we introduced a grammatical evolution neural network (GENN) approach that has high power to detect such interactions in the absence of any marginal main effects. While the success of this method is encouraging, it elicits questions regarding the evolutionary process of the algorithm itself and the feasibility of scaling the method to account for the immense dimensionality of datasets with enormous numbers of features. When the features of interest show no main effects, how is GENN able to build correct models? How and when should evolutionary parameters be adjusted according to the scale of a particular dataset? In the current study, we monitor the performance of GENN during its evolutionary process using different population sizes and numbers of generations. We also compare the evolutionary characteristics of GENN to that of a random search neural network strategy to better understand the benefits provided by the evolutionary learning process - including advantages with respect to chromosome size and the representation of functional versus non-functional features within the models generated by the two approaches. Finally, we apply lessons from the characterization of GENN to analyses of datasets containing increasing numbers of features to demonstrate the scalability of the method}, booktitle={Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06}, publisher={IEEE}, author={Motsinger, Alison A. and Reif, David M. and Dudek, Scott M. and Ritchie, Marylyn D.}, year={2006}, pages={263–270} }
 @article{reif_moore_2006, title={Visual analysis of statistical results from microarray studies of human breast cancer}, volume={4}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-33645789817&partnerID=MN8TOARS}, DOI={10.3892/or.15.4.1043}, abstractNote={Computational and statistical analysis of microarray data is a daunting challenge. Perhaps even more daunting is the biological interpretation of microarray data analysis results. We have previously developed the exploratory visual analysis (EVA) software and database for exploring data analysis results in the context of biological information on each gene available in public databases such as Entrez Gene. EVA brings a flexible combination of statistics and biological annotation to the user's desktop in a straightforward visual interface. Using a publicly available microarray dataset of gene expression response to chemotherapeutic agents in human breast cancer cell lines, we demonstrate the usefulness of the EVA system for interpreting statistical results. EVA can extend previous analyses as well as aid in making novel discoveries. Thus, we anticipate EVA will prove a useful addition to the repertoire of computational methods for microarray data analysis. The EVA software is freely available to academic users.}, number={4}, journal={Oncol Rep}, publisher={Spandidos Publications}, author={Reif, David and Moore, Jason}, year={2006}, month={Apr}, pages={1043–1047} }
 @article{reif_moore_2006, title={Visual analysis of statistical results from microarray studies of human breast cancer.}, volume={c}, url={http://europepmc.org/abstract/med/16525698}, journal={Oncology reports}, author={Reif, DM and Moore, JH}, year={2006}, pages={1043–1047} }
 @inproceedings{white_gilbert_reif_moore_2005, title={A statistical comparison of grammatical evolution strategies in the domain of human genetics}, volume={1}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-27144535907&partnerID=MN8TOARS}, booktitle={2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings}, author={White, B.C. and Gilbert, J.C. and Reif, D.M. and Moore, J.H.}, year={2005}, pages={676–682} }
 @article{wilke_reif_moore_2005, title={Combinatorial Pharmacogenetics}, volume={4}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-27844492326&partnerID=MN8TOARS}, DOI={10.1038/nrd1874}, abstractNote={Combinatorial pharmacogenetics seeks to characterize genetic variations that affect reactions to potentially toxic agents within the complex metabolic networks of the human body. Polymorphic drug-metabolizing enzymes are likely to represent some of the most common inheritable risk factors associated with common 'disease' phenotypes, such as adverse drug reactions. The relatively high concordance between polymorphisms in drug-metabolizing enzymes and clinical phenotypes indicates that research into this class of polymorphisms could benefit patients in the near future. Characterization of other genes affecting drug disposition (absorption, distribution, metabolism and elimination) will further enhance this process. As with most questions concerning biological systems, the complexity arises out of the combinatorial magnitude of all the possible interactions and pathways. The high-dimensionality of the resulting analysis problem will often overwhelm traditional analysis methods. Novel analysis techniques, such as multifactor dimensionality reduction, offer viable options for evaluating such data.}, number={11}, journal={Nat Rev Drug Discov}, publisher={Nature Publishing Group}, author={Wilke, Russell A. and Reif, David M. and Moore, Jason H.}, year={2005}, month={Nov}, pages={911–918} }
 @inproceedings{reif_dudek_shaffer_wang_moore_2005, title={Exploratory visual analysis of pharmacogenomic results}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-15944408038&partnerID=MN8TOARS}, booktitle={Proceedings of the Pacific Symposium on Biocomputing 2005, PSB 2005}, author={Reif, D.M. and Dudek, S.M. and Shaffer, C.M. and Wang, J. and Moore, J.H.}, year={2005}, pages={296–307} }
 @article{reif_dudek_shaffer_wang_moore_2005, title={Exploratory visual analysis of pharmacogenomic results.}, url={http://europepmc.org/abstract/med/15759635}, journal={Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing}, author={Reif, DM and Dudek, SM and Shaffer, CM and Wang, J and Moore, JH}, year={2005} }
 @article{knabe_stiller_berger_reif_gildenhaar_howlett_zreiqat_2005, title={The effect of bioactive glass ceramics on the expression of bone-related genes and proteins in vitro.}, volume={16}, url={http://europepmc.org/abstract/med/15642039}, DOI={10.1111/j.1600-0501.2004.01066.x}, abstractNote={Abstract:  Using biodegradable bone substitutes in alveolar ridge augmentation avoids second‐site surgery for autograft harvesting. Considerable efforts have been undertaken to develop rapidly resorbable bone substitute materials with a higher degree of biodegradability than tricalcium phosphate (TCP). This study examines the effect of novel biodegradable glass ceramics on the expression of bone‐related genes and proteins by human bone‐derived cells (HBDC) and compares this behavior with that of TCP. Test materials used were α‐TCP, a surface‐treated glass ceramic GB9N with crystalline phase Ca2KNa(PO4)2 and a small amount of amorphous silica phosphate; AP40 – a glass ceramic based on crystalline phases of apatite and wollastonite; and a glass ceramic Mg5 composed of 20.6% CaO, 58.5% P2O5, 14.4% Na2O, 4.1% MgO and 2.4% CaF2 (wt%). HBDC were grown on the substrata for 3, 5, 7, 14 and 21 days, counted and probed for various bone‐related mRNAs and proteins (type I collagen (Col I), osteocalcin (OC), osteopontin (OP), osteonectin (ON), alkaline phosphatase (ALP) and bone sialoprotein (BSP)). The substrata supported continuous cellular growth for 21 days. By day 21, GB9N had the highest number of HBDC. GB9N induced significantly enhanced expression of Col I, ALP, OP, OC and ON mRNA at 3 days; of OP, OC and ON mRNA and protein at 7 and 14 days; and of ALP, OP and OC mRNA and Col I, ALP, BSP, ON and OP protein at 21 days. Since all novel glass ceramics supported cellular proliferation together with expression of bone‐related genes and proteins at least as much as TCP, these ceramics can be regarded as potential bone substitutes. GB9N had the most effect on osteoblastic differentiation, thus suggesting that this material may possess a higher potency to enhance osteogenesis than TCP.}, number={1}, journal={Clinical oral implants research}, author={Knabe, C and Stiller, M and Berger, G and Reif, D and Gildenhaar, R and Howlett, CR and Zreiqat, H}, year={2005}, month={Feb}, pages={119–127} }
 @article{reif_white_moore_2004, title={Integrated analysis of genetic, genomic and proteomic data}, volume={1}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-12844275916&partnerID=MN8TOARS}, DOI={10.1586/14789450.1.1.67}, abstractNote={The rapid expansion of methods for measuring biological data ranging from DNA sequence variations to mRNA expression and protein abundance presents the opportunity to utilize multiple types of information jointly in the study of human health and disease. Organisms are complex systems that integrate inputs at myriad levels to arrive at an observable phenotype. Therefore, it is essential that questions concerning the etiology of phenotypes as complex as common human diseases take the systemic nature of biology into account, and integrate the information provided by each data type in a manner analogous to the operation of the body itself. While limited in scope, the initial forays into the joint analysis of multiple data types have yielded interesting results that would not have been reached had only one type of data been considered. These early successes, along with the aforementioned theoretical appeal of data integration, provide impetus for the development of methods for the parallel, high-throughput analysis of multiple data types. The idea that the integrated analysis of multiple data types will improve the identification of biomarkers of clinical endpoints, such as disease susceptibility, is presented as a working hypothesis.}, number={1}, journal={Expert Review of Proteomics}, publisher={Informa Healthcare}, author={Reif, David M and White, Bill C and Moore, Jason H}, year={2004}, month={Jun}, pages={67–75} }
 @article{reif_white_olsen_aune_moore_2003, title={Complex Function Sets Improve Symbolic Discriminant Analysis of Microarray Data}, DOI={10.1007/3-540-45110-2_121}, abstractNote={Our ability to simultaneously measure the expression levels of thousands of genes in biological samples is providing important new opportunities for improving the diagnosis, prevention, and treatment of common diseases. However, new technologies such as DNA microarrays are generating new challenges for variable selection and statistical modeling. In response to these challenges, a genetic programming-based strategy called symbolic discriminant analysis (SDA) for the automatic selection of gene expression variables and mathematical functions for statistical modeling of clinical endpoints has been developed. The initial development and evaluation of SDA has focused on a function set consisting of only the four basic arithmetic operators. The goal of the present study is to evaluate whether adding more complex operators such as square root to the function set improves SDA modeling of microarray data. The results presented in this paper demonstrate that adding complex functions to the terminal set significantly improves SDA modeling by reducing model size and, in some cases, reducing classification error and runtime. We anticipate SDA will be an important new evolutionary computation tool to be added to the repertoire of methods for the analysis of microarray data.}, journal={Genetic and Evolutionary Computation — GECCO 2003}, publisher={Springer Science + Business Media}, author={Reif, David M. and White, Bill C. and Olsen, Nancy and Aune, Thomas and Moore, Jason H.}, year={2003}, pages={2277–2287} }
 @book{reif_white_olsen_aune_moore_2003, title={Complex function sets improve symbolic discriminant analysis of microarray data}, volume={2724}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-33744780676&partnerID=MN8TOARS}, journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, author={Reif, D.M. and White, B.C. and Olsen, N. and Aune, T. and Moore, J.H.}, year={2003}, pages={2277–2287} }
 @inproceedings{reif_dudek_shaffer_wang_moore, title={EXPLORATORY VISUAL ANALYSIS OF PHARMACOGENOMIC RESULTS}, DOI={10.1142/9789812702456_0028}, abstractNote={Comprehensive analysis of expansive pharmacogenomic datasets is a daunting challenge. A thorough exploration of experimental results requires both statistical and annotative information. Therefore, appropriate analysis tools must bring a readily-accessible, flexible combination of statistics and biological annotation to the user's desktop. We present the Exploratory Visual Analysis (EVA) software and database as such a tool and demonstrate its utility in replicating the findings of an earlier pharmacogenomic study as well as elucidating novel biologically plausible hypotheses. EVA brings all of the often disparate pieces of analysis together in an infinitely flexible visual display that is amenable to any type of statistical result and biological question. Here, we describe the motivations for developing EVA, detail the database and custom graphical user interface (GUI), provide an example of its application to a publicly available pharmacogenomic dataset, and discuss the broad utility of the EVA tool for the pharmacogenomics community.}, booktitle={Biocomputing 2005 - Proceedings of the Pacific Symposium}, publisher={World Scientific Publishing Co. Pte. Ltd.}, author={REIF, DAVID M. and DUDEK, SCOTT M. and SHAFFER, CHRISTIAN M. and WANG, JANEY and MOORE, JASON H.} }