2017 Progress Report: Cardiotoxicity Adverse Outcome Pathway: Organotypic Culture Model andinvitro-to-in vivo Extrapolation for High-throughput Hazard,Dose-responseand Variability Assessments

EPA Grant Number: R835802
Center: Organotypic Culture Models For Predictive Toxicology Center
Center Director: Rusyn, Ivan
Title: Cardiotoxicity Adverse Outcome Pathway: Organotypic Culture Model andinvitro-to-in vivo Extrapolation for High-throughput Hazard,Dose-responseand Variability Assessments
Investigators: Rusyn, Ivan , Threadgill, David W. , Wright, Fred A.
Institution: Texas A & M University , North Carolina State University , The Hamner Institutes
EPA Project Officer: Klieforth, Barbara I
Project Period: June 1, 2015 through May 31, 2019 (Extended to May 31, 2020)
Project Period Covered by this Report: June 1, 2017 through May 31,2018
Project Amount: $6,000,000
RFA: Organotypic Culture Models for Predictive Toxicology Center (2013) RFA Text |  Recipients Lists
Research Category: Human Health , Health , Safer Chemicals

Objective:

The WHO estimates that up to 23% of the global burden of cardiovascular diseases, a leading cause of death, is attributable to environmental chemicals. Methods for assessment of cardiac safety of non-pharmaceutical agents lag behind the traditional health hazards of concern to human health (carcinogenicity, mutagenicity, reproductive toxicity, etc.). The long-term objective of the Center is to advance chemical risk assessment by establishing and validating effective, accurate and fiscally responsible means for identifying/characterizing cardiac chemical hazards.

Recent advances in stem cell research and establishment of robust protocols for culturing, distribution and phenotyping holds promise for development of a functional cardiac OCM for modeling cardiovascular disease and testing for chemical hazards. The central hypotheses of this proposal are that: (i) stem cell-derived cardiomyocyte cultures constitute an effective OCM for predictive toxicity screening of environmental chemicals; (ii) a population-based experimental design utilizing a panel of human iPSCs and mouse Collaborative Cross (CC) can assess variation in toxicity to better characterize uncertainties; and (iii) integration of dosimetry with screening provides an in vivocontext to in vitro data and improves human health assessments. Project 1 will conduct population-based concentration-response high-content/-throughput in vitro screening of up to 200 ToxCast chemicals in iPSC-derived cardiomyocytes from 100 humans, and will collect pharmacokinetic data using hepatocytes. Project 2 will conduct mouse population-based in vitro screening of these chemicals in CC-derived cardiomyocytes followed by in vivo validation in the CC strains. Project 3 will conduct dose-response modeling to establish appropriate point of departure, genome-wide association analyses and in vitro-to-in vivo extrapolation modeling.

Progress Summary:

Project 1 work was focused on using multi-plexed assays for high-content imaging and high-throughput transcriptomic analyses using iCell cardiomyocyte organotypic culture model and other cell types derived from iPS cells. We are using human iPSC-derived cardiomyocytes from up to 50 normal human donors and examine effects of 140 drugs and chemicals in concentration-response on cardiomyocyte beating and cellular and mitochondrial toxicity. We are collecting data on ~15 new donors and analyzing data acquired from screening of the first batch of population-wide iCell cardiomyocytes from 27 donors. Transcriptomic analyses were conducted in samples from four representative donors that were selected to reflect the greatest degree of variability in basal cardiac phenotypes and data analyses were completed in collaboration with Project 3. We have also collected data for in vitro-to-in vivo extrapolation and the computational pipeline for reverse toxicokinetic analyses. We have completed analyses on human in vivo to human in vitro concordance in arrhythmia-inducing changes in QT interval and demonstrated that the in vitro model is highly reproducible of the population variability in the clinical trials.


Project 2 investigators continue to derive iPS from the CC lines. These lines are now being expanded and in vitro screening will focus on those chemicals identified in Project 1 as candidate cardiotoxicants. To investigate the in vitro-to-in vivo predictive ability of OCM, we have acquired two ECGenies for recording electrocardiograms in vivo. These instruments are being used to screen eight CC lines (the same ones currently under focus for the in vitro OCM study) for cardiotoxicity of several chemicals identified in Project 1. Additionally, each of these lines (exposed and unexposed mice) are also being characterized by high-frequency ultrasound followed by Spectral Tracking analysis for detailed cardiovascular function. Two chemicals have been completed (chloroquine and isoproterenol) and the data is being analyzed, which is very time intensive. With Project 1, we have begun to collect baseline measures of embryoid body derived cardiomyocytes using high content imaging

Project 3 investigators have maintained a consistent focus on relevant computational and statistical approaches to serve the goals of profiling cardiomyocytes. The pipeline for handling high-throughput transcriptomic data (e.g., TempO-Seq technology) has been published, and includes a series of vetted steps to move from sequencing data to final results. The steps include automatic read calling from sequence data, quality controlling the data, filtering of low-expressed transcripts, robust testing for differential expression, fitting concentration-response functions and pathway analyses.  The methods were presented by Wright as a member of the NIEHS peer-review panel on high-throughput transcriptomics in October 2017, and the experience informed his service on the panel, which included representation and presentations from the U.S. EPA. This work has been followed by additional consultation with EPA personnel in the National Center for Computational Toxicology to ensure continuing relevance to toxicogenomic efforts by the agency.  The methods are being used in manuscripts that have been published for the current grant, and in preparation. The new version of ToxPi (2.0) has been released and published in 2018. The release includes new options for statistical analyses and grouping, and was completely rewritten to enhance ease of use. The new ToxPi code also includes numerous improved steps in handling missing and irregular data, and with enhanced means to save and trade datasets for sharing and collaboration. Finally, analysis of transcriptomic dose-response data has also been enhanced by new capabilities in comparing clustering algorithms. We have worked extensively on Foulkes-Mallows index and its variants as a means of quantifying similarities of clustering, which is useful in evaluating the similarity of clustering algorithms, but has been relatively little used in toxicology.

Future Activities:

Project 1 will finalize data analyses on the first 140 chemicals in all ~50 individuals screened. We also plan to conduct screening of 1000 chemicals in cells from 5 donors and collect samples for transcriptomic analyses in one of those cell lines. We will work closely with Project 3 staff to analyze data from high-content screening and high-throughput transcriptomics. We will work with Project 2 staff to conduct screening of mouse-derived embryoid bodies. We will continue experiments for reverse toxicokinetics based on the data for 140 chemicals that are screened.

Project 2 will use existing iPS lines to screen chemicals from Project 1 to OCM toxicity. An additional six chemicals beyond the two already screened also will be screened in vivo using 8 CC lines. The data will be used to confirm whether the in vitro to in vivo translation of cardiomyocyte function is an accurate representation at the individual level. This was the overarching goal of Project 2.

The Project 3 pipeline for dose-response analysis has been finalized, and next steps include down-sampling analysis to investigate the effect of sample size and various data handling techniques on final inferences. In particular, pathway analyses are thought to be more robust than inferences for individual transcripts, but empirical data to demonstrate the phenomenon in a toxicological setting has been scarce. 


Journal Articles: 35 Displayed | Download in RIS Format

Other center views: All 192 publications 35 publications in selected types All 35 journal articles
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Journal Article Auerbach S, Filer D, Reif D, Walker V, Holloway AC, Schlezinger J, Srinivasan S, Svoboda D, Judson R, Bucher JR, Thayer KA. Prioritizing environmental chemicals for obesity and diabetes outcomes research: a screening approach using ToxCastTM high-throughput data. Environmental Health Perspectives 2016;124(8):1141-1154. R835802 (2015)
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  • Journal Article Barton-Maclaren TS, Westphal M, Sarwar E, Mattison D, Chiu WA, Dix D, Kavlock R, Krewski D. Challenges and opportunities in the risk assessment of existing substances in Canada: lessons learned from the international community. International Journal of Risk Assessment and Management 2017;20;(1-3):261-283. R835802 (2016)
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  • Journal Article Blanchette AD, Grimm FA, Dalaijamts C, Hsieh NH, Ferguson K, Luo YS, Anson B, Rusyn I, Chiu WA. Thorough QT/QTc in a dish:An in vitro human model that accurately predicts clinical concentration-QTc relationships. Clinical Pharmacology and Therapeutics 2019;105:1175-1186. R835802 (2018)
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  • Journal Article Bokkers BGH, Mengelers MJ, Bakker MI, Chiu WA, Slob W. APROBA-Plus: a probabilistic tool to evaluate and express uncertainty in hazard characterization and exposure assessment of substances. Food and Chemical Toxicology. 2017;110:408-417. R835802 (2017)
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  • Journal Article Chiu WA, Wright FA, Rusyn I. A tiered, Bayesian approach to estimating population variability for regulatory decision-making. ALTEX 2017;34(3):377-388. R835802 (2016)
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  • Journal Article Chiu WA, Axelrad DA, Dalaijamts C, Dockins C, Shao K, Shapiro AJ, Paoli G. Beyond the RfD:Broad application of a probabilistic approach to improve chemical dose-response assessments for noncancer effects. Environmental Health Perspective 2018;126(6):067009. R835802 (2018)
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  • Journal Article Chiu WA, Guyton KZ, Martin MT, Reif DM, Rusyn I. Use of high-throughput in vitro toxicity screening data in cancer hazard evaluations by IARC Monograph Working Groups. ALTEX 2018;35(1):51-64. R835802 (2017)
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  • Journal Article Chiu WA, Rusyn I. Advancing chemical risk assessment decision-making with population variability data: challenges and opportunities. Mammalian Genome 2018;29(1-2):182-189. R835802 (2017)
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  • Journal Article Cote I, Andersen ME, Ankley GT, Barone S, Birnbaum LS, Boekelheide K, Bois FY, Burgoon LD, Chiu WA, Crawford-Brown D, Crofton KM, DeVito M, Devlin RB, Edwards SW, Guyton KZ, Hattis D, Judson RS, Knight D, Krewski D, Lambert J, Maull EA, Mendrick D, Paoli GM, Patel CJ, Perkins EJ, Poje G, Portier CJ, Rusyn I, Schulte PA, Simeonov A, Smith MT, Thayer KA, Thomas RS, Thomas R, Tice RR, Vandenberg JJ, Villeneuve DL, Wesselkamper S, Whelan M, Whittaker C, White R, Xia M, Yauk C, Zeise L, Zhao J, DeWoskin RS. The next generation of risk assessment multi-year study--highlights of findings, applications to risk assessment, and future directions. Environmental Health Perspectives 2016;124(11):1671-1682. R835802 (2015)
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  • Journal Article Fantke P, Aylward L, Bare J, Chiu WA, Dodson R, Dwyer R, Ernstoff A, Howard B, Jantunen M, Jolliet O, Judson R, Kirchhübel N, Li D, Miller A, Paoli G, Price P, Rhomberg L, Shen B, Shin HM, Teeguarden J, Vallero D, Wambaugh J, Wetmore BA, Zaleski R, McKone TE. Advancements in life cycle human exposure and toxicity characterization. Environmetnal Health Perspective 2018;126:125001. R835802 (2018)
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  • Journal Article Garbutt TA, Konneker TI, Konganti K, Hillhouse AE, Swift-Haire F, Jones A, Phelps D, Aylor DL, Threadgill D. Permissiveness to form pluripotent stem cells may be an evolutionarily derived characteristic in Mus musculus. Scientific Reports 2018;8:14706. R835802 (2018)
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  • Journal Article Grimm FA, Iwata Y, Sirenko O, Bittner M, Rusyn I. High-content assay multiplexing for toxicity screening in induced pluripotent stem cell-derived cardiomyocytes and hepatocytes. Assay and Drug Development Technologies 2015;13(9):529-546. R835802 (2015)
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  • Journal Article Grimm FA, Iwata Y, Sirenko O, Chappell GA, Wright FA, Reif DM, Braisted J, Gerhold DL, Yeakley JM, Shepard P, Seligmann B, Roy T, Boogaard PJ, Ketelslegers HB, Rohde AM, Rusyn I. A chemical-biological similarity-based grouping of complex substances as a prototype approach for evaluating chemical alternatives. Green Chemistry 2016;18(16):4407-4419. R835802 (2015)
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  • Journal Article Grimm FA, Blanchette A, House JS, Ferguson K, Hsieh NH, Dalaijamts C, Wright AA, Anson B, Wright FA, Chiu WA, Rusyn I. A human population-based organotypic in vitro model for cardiotoxicity screening. ALTEX 2018;35:441-452. R835802 (2018)
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  • Journal Article Grimm FA, House JS, Wilson MR, Sirenko O, Iwata Y, Wright FA, Ball N, Rusyn I. Multi-Dimensional in Vitro Bioactivity Profiling for Grouping of Glycol Ethers. Regulatory Toxicology and Pharmacology 2019;101:91-102. R835802 (2018)
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  • Journal Article Grondin CJ, Davis AP, Wiegers TC, King BL, Wiegers JA, Reif DM, Hoppin JA, Mattingly CJ. Advancing exposure science through chemical data curation and integration in the Comparative Toxicogenomics Database. Environmental Health Perspectives 2016;124(10):1592-1599. R835802 (2015)
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  • Journal Article Guyton KZ, Rusyn I, Chiu WA, Corpet DE, van den Berg M, Ross MK, Christiani DC, Beland FA, Smith MT. Application of the key characteristics of carcinogens in cancer hazard identification. Carcinogenesis 2018;39(4):614-622. R835802 (2017)
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  • Journal Article House JS, Grimm FA, Jima DD, Zhou Y-H, Rusyn I, Wright FA. A pipeline for high-throughput concentration response modeling of gene expression for toxicogenomics. Frontiers in Genetics 2017;8:168 (11 pp.). R835802 (2017)
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  • Journal Article Iwata Y, Klaren WD, Lebakken CS, Grimm FA, Rusyn I. High-content assay multiplexing for vascular toxicity screening in induced pluripotent stem cell-derived endothelial cells and human umbilical vein endothelial cells. Assay and Drug Development Technologies 2017;15(6):267-279. R835802 (2017)
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  • Journal Article Judson R, Houck K, Martin M, Richard AM, Knudsen TB, Shah I, Little S, Wambaugh J, Woodrow Setzer R, Kothya P, Phuong J, Filer D, Smith D, Reif D, Rotroff D, Kleinstreuer N, Sipes N, Xia M, Huang R, Crofton K, Thomas RS. Editor's highlight: Analysis of the effects of cell stress and cytotoxicity on in vitro assay activity across a diverse chemical and assay space. Toxicological Sciences 2016;152(2):323-339. R835802 (2015)
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  • Journal Article Konganti K, Ehrlich A, Rusyn I, Threadgill DW. gQTL:a web application for QTL analysis using the collaborative cross mouse genetic reference population. G3:Genes, Genomes, Genetics 2018;8(8):2559-2562 R835802 (2017)
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  • Journal Article Li G, Shabalin AA, Rusyn I, Wright FA, Nobel AB. An empirical Bayes approach for multiple tissue eQTL analysis. Biostatistics 2018;19(3):391-406. R835802 (2017)
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  • Journal Article Marvel SW, To K, Grimm FA, Wright FA, Rusyn I, Reif DM. ToxPi Graphical User Interface 2.0: dynamic exploration, visualization, and sharing of integrated data models. BMC Bioinformatics 2018;19(1):80 (7 pp.). R835802 (2017)
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  • Journal Article Rusyn I, Greene N. The impact of novel assessment methodologies in toxicology on green chemistry and chemical alternatives. Toxicological Sciences 2018;161(2):276-284. R835802 (2017)
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  • Journal Article 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. Using ToxCast™ data to reconstruct dynamic cell state trajectories and estimate toxicological points of departure. Environmental Health Perspectives 2016;124(7):910-919. R835802 (2015)
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  • Journal Article Sirenko O, Grimm FA, Ryan KR, Iwata Y, Chiu WA, Parham F, Wignall JA, Anson B, Cromwell EF, Behl M, Rusyn I, Tice RR. In vitro cardiotoxicity assessment of environmental chemicals using an organotypic human induced pluripotent stem cell-derived model. Toxicology and Applied Pharmacology 2017;322:60-74. R835802 (2016)
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  • Journal Article Tilley SK, Reif DM, Fry RC. Incorporating ToxCast and Tox21 datasets to rank biological activity of chemicals at Superfund sites in North Carolina. Environment International 2017;101:19-26. R835802 (2017)
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  • Journal Article Wignall JA, Muratov E, Sedykh A, Guyton KZ, Tropsha A, Rusyn I, Chiu WA. Conditional Toxicity Value (CTV) predictor: an in silico approach for generating quantitative risk estimates for chemicals. Environmental Health Perspectives 2018;126(5):057008 (13 pp.). R835802 (2017)
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  • Journal Article Zhang G, Marvel S, Truong L, Tanguay RL, Reif DM. Aggregate entropy scoring for quantifying activity across endpoints with irregular correlation structure. Reproductive Toxicology 2016;62:92-99. R835802 (2015)
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  • Journal Article Zhang G, Roell KR, Truong L, Tanguay RL, Reif DM. A data-driven weighting scheme for multivariate phenotypic endpoints recapitulates zebrafish developmental cascades. Toxicology and Applied Pharmacology 2017;314:109-117. R835802 (2016)
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  • Journal Article Zhou Y-H, Marron JS, Wright FA. Computation of ancestry scores with mixed families and unrelated individuals. Biometrics 2018;74(1):155-164. R835802 (2016)
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  • Journal Article Li G, Jima D, Wright FA, Nobel AB. HT-eQTL:integrative expression quantitative trait loci analysis in a large number of human tissues. BMC Bioinformatics 2018;19:95. R835802 (2018)
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  • Journal Article Kosnik MB, Reif DM. Determination of chemical-disease risk values to prioritize connections between environmental factors, genetic variants, and human diseases. Toxicology and Applied Pharmacology2019;379:114674. R835802C003 (2018)
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  • Journal Article Kosnik MB, Planchart A, Marvel SW, Reif DM, Mattingly CJ. Integration of curated and high-throughput screening data to elucidate environmental influences on disease pathways. Computational Toxicology2019;12:100094. R835802C003 (2018)
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  • Journal Article Hsieh NH, Reisfeld, B, Bois FY, Chiu WA. Applying a global sensitivity analysis workflow to improve the computational efficiencies in physiologically-based pharmacokinetic modeling. Frontiers in Pharmacology 2018 9:588. R835802 (2018)
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  • Progress and Final Reports:

    Original Abstract
  • 2015 Progress Report
  • 2016 Progress Report
  • 2018 Progress Report
  • Final Report
  • Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
    R835802C001 High-throughput Hazard,Dose-responseandPopulationVariabilityAssessmentof Cardiotoxicity in aHumanInducedPluripotentStem Cell(iPSC)-derivedin vitro Culture Model
    R835802C002 Linking in vitro-to-in vivoToxicity Testing Using Genetically-matchedOrganoids and Mice from a Novel Genetic Reference Population
    R835802C003 A Pipeline for in vitro-to-in vivo Extrapolation, Population Modeling, & Prioritization