1
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Deere JR, Jankowski MD, Primus A, Phelps NBD, Ferrey M, Borucinska J, Chenaux-Ibrahim Y, Isaac EJ, Singer RS, Travis DA, Moore S, Wolf TM. Health of wild fish exposed to contaminants of emerging concern in freshwater ecosystems utilized by a Minnesota Tribal community. INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT 2024; 20:846-863. [PMID: 37526115 DOI: 10.1002/ieam.4822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 07/29/2023] [Accepted: 07/31/2023] [Indexed: 08/02/2023]
Abstract
Fish serve as indicators of exposure to contaminants of emerging concern (CECs)-chemicals such as pharmaceuticals, hormones, and personal care products-which are often designed to impact vertebrates. To investigate fish health and CECs in situ, we evaluated the health of wild fish exposed to CECs in waterbodies across northeastern Minnesota with varying anthropogenic pressures and CEC exposures: waterbodies with no human development along their shorelines, those with development, and those directly receiving treated wastewater effluent. Then, we compared three approaches to evaluate the health of fish exposed to CECs in their natural environment: a refined fish health assessment index, a histopathological index, and high-throughput (ToxCast) in vitro assays. Lastly, we mapped adverse outcome pathways (AOPs) associated with identified ToxCast assays to determine potential impacts across levels of biological organization within the aquatic system. These approaches were applied to subsistence fish collected from the Grand Portage Indian Reservation and 1854 Ceded Territory in 2017 and 2019. Overall, 24 CECs were detected in fish tissues, with all but one of the sites having at least one detection. The combined implementation of these tools revealed that subsistence fish exposed to CECs had histological and macroscopic tissue and organ abnormalities, although a direct causal link could not be established. The health of fish in undeveloped sites was as poor, or sometimes poorer, than fish in developed and wastewater effluent-impacted sites based on gross and histologic tissue lesions. Adverse outcome pathways revealed potential hazardous pathways of individual CECs to fish. A better understanding of how the health of wild fish harvested for consumption is affected by CECs may help prioritize risk management research efforts and can ultimately be used to guide fishery management and public health decisions. Integr Environ Assess Manag 2024;20:846-863. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
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Affiliation(s)
- Jessica R Deere
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota, USA
| | - Mark D Jankowski
- United States Environmental Protection Agency, Seattle, Washington, USA
| | | | - Nicholas B D Phelps
- Department of Fisheries, Wildlife and Conservation Biology, College of Food, Agricultural and Natural Resource Sciences, University of Minnesota, St. Paul, Minnesota, USA
| | - Mark Ferrey
- Minnesota Pollution Control Agency, St. Paul, Minnesota, USA
| | - Joanna Borucinska
- Department of Biology, University of Hartford, West Hartford, Connecticut, USA
| | - Yvette Chenaux-Ibrahim
- Grand Portage Band of Lake Superior Chippewa, Biology and Environment, Grand Portage, Minnesota, USA
| | - Edmund J Isaac
- Grand Portage Band of Lake Superior Chippewa, Biology and Environment, Grand Portage, Minnesota, USA
| | - Randall S Singer
- Department of Veterinary and Biomedical Sciences, College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota, USA
| | | | - Seth Moore
- Grand Portage Band of Lake Superior Chippewa, Biology and Environment, Grand Portage, Minnesota, USA
| | - Tiffany M Wolf
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota, USA
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2
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Foreman AL, Warth B, Hessel EVS, Price EJ, Schymanski EL, Cantelli G, Parkinson H, Hecht H, Klánová J, Vlaanderen J, Hilscherova K, Vrijheid M, Vineis P, Araujo R, Barouki R, Vermeulen R, Lanone S, Brunak S, Sebert S, Karjalainen T. Adopting Mechanistic Molecular Biology Approaches in Exposome Research for Causal Understanding. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:7256-7269. [PMID: 38641325 PMCID: PMC11064223 DOI: 10.1021/acs.est.3c07961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 03/25/2024] [Accepted: 03/27/2024] [Indexed: 04/21/2024]
Abstract
Through investigating the combined impact of the environmental exposures experienced by an individual throughout their lifetime, exposome research provides opportunities to understand and mitigate negative health outcomes. While current exposome research is driven by epidemiological studies that identify associations between exposures and effects, new frameworks integrating more substantial population-level metadata, including electronic health and administrative records, will shed further light on characterizing environmental exposure risks. Molecular biology offers methods and concepts to study the biological and health impacts of exposomes in experimental and computational systems. Of particular importance is the growing use of omics readouts in epidemiological and clinical studies. This paper calls for the adoption of mechanistic molecular biology approaches in exposome research as an essential step in understanding the genotype and exposure interactions underlying human phenotypes. A series of recommendations are presented to make the necessary and appropriate steps to move from exposure association to causation, with a huge potential to inform precision medicine and population health. This includes establishing hypothesis-driven laboratory testing within the exposome field, supported by appropriate methods to read across from model systems research to human.
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Affiliation(s)
- Amy L. Foreman
- European
Molecular Biology Laboratory & European Bioinformatics Institute
(EMBL-EBI), Wellcome Trust Genome Campus, Hinxton CB10 1SD, U.K.
| | - Benedikt Warth
- Department
of Food Chemistry and Toxicology, University
of Vienna, 1090 Vienna, Austria
| | - Ellen V. S. Hessel
- National
Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan 9, 3721 MA Bilthoven, The Netherlands
| | - Elliott J. Price
- RECETOX,
Faculty of Science, Masaryk University, Kotlarska 2, Brno 60200, Czech Republic
| | - Emma L. Schymanski
- Luxembourg
Centre for Systems Biomedicine, University
of Luxembourg, 6 avenue
du Swing, L-4367 Belvaux, Luxembourg
| | - Gaia Cantelli
- European
Molecular Biology Laboratory & European Bioinformatics Institute
(EMBL-EBI), Wellcome Trust Genome Campus, Hinxton CB10 1SD, U.K.
| | - Helen Parkinson
- European
Molecular Biology Laboratory & European Bioinformatics Institute
(EMBL-EBI), Wellcome Trust Genome Campus, Hinxton CB10 1SD, U.K.
| | - Helge Hecht
- RECETOX,
Faculty of Science, Masaryk University, Kotlarska 2, Brno 60200, Czech Republic
| | - Jana Klánová
- RECETOX,
Faculty of Science, Masaryk University, Kotlarska 2, Brno 60200, Czech Republic
| | - Jelle Vlaanderen
- Institute
for Risk Assessment Sciences, Division of Environmental Epidemiology, Utrecht University, Heidelberglaan 8 3584 CS Utrecht, The Netherlands
| | - Klara Hilscherova
- RECETOX,
Faculty of Science, Masaryk University, Kotlarska 2, Brno 60200, Czech Republic
| | - Martine Vrijheid
- Institute
for Global Health (ISGlobal), Barcelona
Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain
- Universitat
Pompeu Fabra, Carrer
de la Mercè, 12, Ciutat Vella, 08002 Barcelona, Spain
- Centro de Investigación Biomédica en Red
Epidemiología
y Salud Pública (CIBERESP), Av. Monforte de Lemos, 3-5. Pebellón 11, Planta 0, 28029 Madrid, Spain
| | - Paolo Vineis
- Department
of Epidemiology and Biostatistics, School of Public Health, Imperial College, London SW7 2AZ, U.K.
| | - Rita Araujo
- European Commission, DG Research and Innovation, Sq. Frère-Orban 8, 1000 Bruxelles, Belgium
| | | | - Roel Vermeulen
- Institute
for Risk Assessment Sciences, Division of Environmental Epidemiology, Utrecht University, Heidelberglaan 8 3584 CS Utrecht, The Netherlands
| | - Sophie Lanone
- Univ Paris Est Creteil, INSERM, IMRB, F-94010 Creteil, France
| | - Søren Brunak
- Novo
Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Blegdamsvej 3B, 2200 København, Denmark
| | - Sylvain Sebert
- Research
Unit of Population Health, University of
Oulu, P.O. Box 8000, FI-90014 Oulu, Finland
| | - Tuomo Karjalainen
- European Commission, DG Research and Innovation, Sq. Frère-Orban 8, 1000 Bruxelles, Belgium
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3
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Li R, Zhang Z, Xuan Y, Wang Y, Zhong Y, Zhang L, Zhang J, Chen Q, Yu S, Yuan J. HNF4A as a potential target of PFOA and PFOS leading to hepatic steatosis: Integrated molecular docking, molecular dynamic and transcriptomic analyses. Chem Biol Interact 2024; 390:110867. [PMID: 38199259 DOI: 10.1016/j.cbi.2024.110867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 12/30/2023] [Accepted: 01/08/2024] [Indexed: 01/12/2024]
Abstract
Perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) are indeed among the most well known and extensively studied Per- and polyfluoroalkyl substances (PFASs), and increasing evidence confirm their effects on human health, especially liver steatosis. Nonetheless, the molecular mechanisms of their initiation of hepatic steatosis is still elusive. Therefore, potential targets of PFOA/PFOS must be explored to ameliorate its adverse consequences. This research aims to investigate the molecular mechanisms of PFOA and PFOS-induced liver steatosis, with emphasis on identifying a potential target that links these PFASs to liver steatosis. The potential target that causes PFOA and PFOS-induced liver steatosis have been explored and determined based on molecular docking, molecular dynamics (MD) simulation, and transcriptomics analysis. In silico results show that PFOA/PFOS can form a stable binding conformation with HNF4A, and PFOA/PFOS may interact with HNF4A to affect the downstream conduction mechanism. Transcriptome data from PFOA/PFOS-induced human stem cell spheres showed that HNF4A was inhibited, suggesting that PFOA/PFOS may constrain its function. PFOS mainly down-regulated genes related to cholesterol synthesis while PFOA mainly up-regulated genes related to fatty acid β-oxidation. This study explored the toxicological mechanism of liver steatosis caused by PFOA/PFOS. These compounds might inhibit and down-regulate HNF4A, which is the molecular initiation events (MIE) that induces liver steatosis.
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Affiliation(s)
- Rui Li
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Zijing Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Yuxin Xuan
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Yulu Wang
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Yuyan Zhong
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Lingyin Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Jinrui Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Qian Chen
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Shuling Yu
- Key Laboratory of Natural Medicine and Immune-Engineering of Henan Province, Henan University, Kaifeng, Henan, 475004, PR China
| | - Jintao Yuan
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China.
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4
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Schumann P, Rivetti C, Houghton J, Campos B, Hodges G, LaLone C. Combination of computational new approach methodologies for enhancing evidence of biological pathway conservation across species. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168573. [PMID: 37981146 PMCID: PMC10926110 DOI: 10.1016/j.scitotenv.2023.168573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 11/09/2023] [Accepted: 11/12/2023] [Indexed: 11/21/2023]
Abstract
The ability to predict which chemicals are of concern for environmental safety is dependent, in part, on the ability to extrapolate chemical effects across many species. This work investigated the complementary use of two computational new approach methodologies to support cross-species predictions of chemical susceptibility: the US Environmental Protection Agency Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool and Unilever's recently developed Genes to Pathways - Species Conservation Analysis (G2P-SCAN) tool. These stand-alone tools rely on existing biological knowledge to help understand chemical susceptibility and biological pathway conservation across species. The utility and challenges of these combined computational approaches were demonstrated using case examples focused on chemical interactions with peroxisome proliferator activated receptor alpha (PPARα), estrogen receptor 1 (ESR1), and gamma-aminobutyric acid type A receptor subunit alpha (GABRA1). Overall, the biological pathway information enhanced the weight of evidence to support cross-species susceptibility predictions. Through comparisons of relevant molecular and functional data gleaned from adverse outcome pathways (AOPs) to mapped biological pathways, it was possible to gain a toxicological context for various chemical-protein interactions. The information gained through this computational approach could ultimately inform chemical safety assessments by enhancing cross-species predictions of chemical susceptibility. It could also help fulfill a core objective of the AOP framework by potentially expanding the biologically plausible taxonomic domain of applicability of relevant AOPs.
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Affiliation(s)
- Peter Schumann
- Oak Ridge Institute for Science and Education, Duluth, MN, USA
| | - Claudia Rivetti
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire, UK
| | - Jade Houghton
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire, UK
| | - Bruno Campos
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire, UK
| | - Geoff Hodges
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire, UK
| | - Carlie LaLone
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Great Lakes Toxicology and Ecology Division, Duluth, MN, USA.
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5
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Amos JD, Zhang Z, Tian Y, Lowry GV, Wiesner MR, Hendren CO. Knowledge and Instance Mapping: architecture for premeditated interoperability of disparate data for materials. Sci Data 2024; 11:173. [PMID: 38321063 PMCID: PMC10847415 DOI: 10.1038/s41597-024-03006-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 01/26/2024] [Indexed: 02/08/2024] Open
Abstract
Predicting and elucidating the impacts of materials on human health and the environment is an unending task that has taken on special significance in the context of nanomaterials research over the last two decades. The properties of materials in environmental and physiological media are dynamic, reflecting the complex interactions between materials and these media. This dynamic behavior requires special consideration in the design of databases and data curation that allow for subsequent comparability and interrogation of the data from potentially diverse sources. We present two data processing methods that can be integrated into the experimental process to encourage pre-mediated interoperability of disparate material data: Knowledge Mapping and Instance Mapping. Originally developed as a framework for the NanoInformatics Knowledge Commons (NIKC) database, this architecture and associated methods can be used independently of the NIKC and applied across multiple subfields of nanotechnology and material science.
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Affiliation(s)
- Jaleesia D Amos
- Center for the Environmental Implications of Nano Technology (CEINT), Durham, USA
- Civil & Environmental Engineering, Duke University, Durham, North Carolina, 2770y8, USA
| | - Zhao Zhang
- Center for the Environmental Implications of Nano Technology (CEINT), Durham, USA
- Civil & Environmental Engineering, Duke University, Durham, North Carolina, 2770y8, USA
- Lucideon M+P, Morrisville, North Carolina, 27560, USA
| | - Yuan Tian
- Center for the Environmental Implications of Nano Technology (CEINT), Durham, USA
- Civil & Environmental Engineering, Duke University, Durham, North Carolina, 2770y8, USA
| | - Gregory V Lowry
- Center for the Environmental Implications of Nano Technology (CEINT), Durham, USA
- Civil & Environmental Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, 15213, USA
| | - Mark R Wiesner
- Center for the Environmental Implications of Nano Technology (CEINT), Durham, USA.
- Civil & Environmental Engineering, Duke University, Durham, North Carolina, 2770y8, USA.
| | - Christine Ogilvie Hendren
- Center for the Environmental Implications of Nano Technology (CEINT), Durham, USA
- Civil & Environmental Engineering, Duke University, Durham, North Carolina, 2770y8, USA
- Department of Geological and Environmental Sciences, Appalachian State University, Boone, North Carolina, 28608, USA
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6
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Haigis AC, Vergauwen L, LaLone CA, Villeneuve DL, O'Brien JM, Knapen D. Cross-species applicability of an adverse outcome pathway network for thyroid hormone system disruption. Toxicol Sci 2023; 195:1-27. [PMID: 37405877 DOI: 10.1093/toxsci/kfad063] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/07/2023] Open
Abstract
Thyroid hormone system disrupting compounds are considered potential threats for human and environmental health. Multiple adverse outcome pathways (AOPs) for thyroid hormone system disruption (THSD) are being developed in different taxa. Combining these AOPs results in a cross-species AOP network for THSD which may provide an evidence-based foundation for extrapolating THSD data across vertebrate species and bridging the gap between human and environmental health. This review aimed to advance the description of the taxonomic domain of applicability (tDOA) in the network to improve its utility for cross-species extrapolation. We focused on the molecular initiating events (MIEs) and adverse outcomes (AOs) and evaluated both their plausible domain of applicability (taxa they are likely applicable to) and empirical domain of applicability (where evidence for applicability to various taxa exists) in a THSD context. The evaluation showed that all MIEs in the AOP network are applicable to mammals. With some exceptions, there was evidence of structural conservation across vertebrate taxa and especially for fish and amphibians, and to a lesser extent for birds, empirical evidence was found. Current evidence supports the applicability of impaired neurodevelopment, neurosensory development (eg, vision) and reproduction across vertebrate taxa. The results of this tDOA evaluation are summarized in a conceptual AOP network that helps prioritize (parts of) AOPs for a more detailed evaluation. In conclusion, this review advances the tDOA description of an existing THSD AOP network and serves as a catalog summarizing plausible and empirical evidence on which future cross-species AOP development and tDOA assessment could build.
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Affiliation(s)
- Ann-Cathrin Haigis
- Zebrafishlab, Veterinary Physiology and Biochemistry, Department of Veterinary Sciences, University of Antwerp, 2610 Wilrijk, Belgium
| | - Lucia Vergauwen
- Zebrafishlab, Veterinary Physiology and Biochemistry, Department of Veterinary Sciences, University of Antwerp, 2610 Wilrijk, Belgium
| | - Carlie A LaLone
- Great Lakes Toxicology and Ecology Division, United States Environmental Protection Agency, Duluth, Minnesota 55804, USA
| | - Daniel L Villeneuve
- Great Lakes Toxicology and Ecology Division, United States Environmental Protection Agency, Duluth, Minnesota 55804, USA
| | - Jason M O'Brien
- Ecotoxicology and Wildlife Health Division, Environment and Climate Change Canada, Carleton University, Ottawa, Ontario K1S 5B6, Canada
| | - Dries Knapen
- Zebrafishlab, Veterinary Physiology and Biochemistry, Department of Veterinary Sciences, University of Antwerp, 2610 Wilrijk, Belgium
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7
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Srivathsa AV, Sadashivappa NM, Hegde AK, Radha S, Mahesh AR, Ammunje DN, Sen D, Theivendren P, Govindaraj S, Kunjiappan S, Pavadai P. A Review on Artificial Intelligence Approaches and Rational Approaches in Drug Discovery. Curr Pharm Des 2023; 29:1180-1192. [PMID: 37132148 DOI: 10.2174/1381612829666230428110542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/06/2023] [Accepted: 02/27/2023] [Indexed: 05/04/2023]
Abstract
Artificial intelligence (AI) speeds up the drug development process and reduces its time, as well as the cost which is of enormous importance in outbreaks such as COVID-19. It uses a set of machine learning algorithms that collects the available data from resources, categorises, processes and develops novel learning methodologies. Virtual screening is a successful application of AI, which is used in screening huge drug-like databases and filtering to a small number of compounds. The brain's thinking of AI is its neural networking which uses techniques such as Convoluted Neural Network (CNN), Recursive Neural Network (RNN) or Generative Adversial Neural Network (GANN). The application ranges from small molecule drug discovery to the development of vaccines. In the present review article, we discussed various techniques of drug design, structure and ligand-based, pharmacokinetics and toxicity prediction using AI. The rapid phase of discovery is the need of the hour and AI is a targeted approach to achieve this.
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Affiliation(s)
- Anjana Vidya Srivathsa
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, M.S. Ramaiah University of Applied Sciences, M.S.R. Nagar, Bengaluru, 560054, India
| | - Nandini Markuli Sadashivappa
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, M.S. Ramaiah University of Applied Sciences, M.S.R. Nagar, Bengaluru, 560054, India
| | - Apeksha Krishnamurthy Hegde
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, M.S. Ramaiah University of Applied Sciences, M.S.R. Nagar, Bengaluru, 560054, India
| | - Srimathi Radha
- Department of Pharmaceutical Chemistry, SRM College of Pharmacy, Faculty of Medicine and Health Sciences, SRM Institute of Science and Technology, Chengalpattu District, Kattankulathur, Tamil Nadu, 603203, India
| | - Agasa Ramu Mahesh
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, M.S. Ramaiah University of Applied Sciences, M.S.R. Nagar, Bengaluru, 560054, India
| | - Damodar Nayak Ammunje
- Department of Pharmacology, Faculty of Pharmacy, M.S. Ramaiah University of Applied Sciences, M.S.R. Nagar, Bengaluru, 560054, India
| | - Debanjan Sen
- Department of Pharmaceutical Chemistry, BCDA College of Pharmacy & Technology, Hridaypur, Kolkata, 700127, West Bengal, India
| | - Panneerselvam Theivendren
- Department of Pharmaceutical Chemistry, Swamy Vivekanandha College of Pharmacy, Elayampalayam, Tiruchengode, 637205, India
| | - Saravanan Govindaraj
- Department of Pharmaceutical Chemistry, MNR College of Pharmacy, Fasalwadi, Sangareddy, 502 001, India
| | - Selvaraj Kunjiappan
- Department of Biotechnology, Kalasalingam Academy of Research and Education, Krishnankoil, 626126, India
| | - Parasuraman Pavadai
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, M.S. Ramaiah University of Applied Sciences, M.S.R. Nagar, Bengaluru, 560054, India
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8
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Jaylet T, Coustillet T, Jornod F, Margaritte-Jeannin P, Audouze K. AOP-helpFinder 2.0: Integration of an event-event searches module. ENVIRONMENT INTERNATIONAL 2023; 177:108017. [PMID: 37295163 DOI: 10.1016/j.envint.2023.108017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 04/25/2023] [Accepted: 06/01/2023] [Indexed: 06/12/2023]
Abstract
To support the use of alternative methods in regulatory assessment of chemical risks, the concept of adverse outcome pathway (AOP) constitutes an important toxicological tool. AOP represents a structured representation of existing knowledge, linking molecular initiating event (MIE) initiated by a prototypical stressor that leads to a cascade of biological key event (KE) to an adverse outcome (AO). Biological information to develop such AOP is very dispersed in various data sources. To increase the chance of capturing relevant existing data to develop a new AOP, the AOP-helpFinder tool was recently implemented to assist researchers to design new AOP. Here, an updated version of AOP-helpFinder proposes novel functionalities. The main one being the implementation of an automatic screening of the abstracts from the PubMed database to identify and extract event-event associations. In addition, a new scoring system was created to classify the identified co-occurred terms (stressor-event or event-event (which represent key event relationships) to help prioritization and support the weight of evidence approach, allowing a global assessment of the strength and reliability of the AOP. Moreover, to facilitate interpretation of the results, visualization options are also proposed. The AOP-helpFinder source code are fully accessible via GitHub, and searches can be performed via a web interface at http://aop-helpfinder-v2.u-paris-sciences.fr/.
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Affiliation(s)
- Thomas Jaylet
- Université Paris Cité, Inserm U1124, 45 rue des Saints Pères, 75006 Paris, France
| | - Thibaut Coustillet
- Université Paris Cité, Inserm U1124, 45 rue des Saints Pères, 75006 Paris, France
| | - Florence Jornod
- Université Paris Cité, Inserm U1124, 45 rue des Saints Pères, 75006 Paris, France
| | | | - Karine Audouze
- Université Paris Cité, Inserm U1124, 45 rue des Saints Pères, 75006 Paris, France.
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9
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Kim M, Kim SH, Choi JY, Park YJ. Investigating fatty liver disease-associated adverse outcome pathways of perfluorooctane sulfonate using a systems toxicology approach. Food Chem Toxicol 2023; 176:113781. [PMID: 37059384 DOI: 10.1016/j.fct.2023.113781] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 04/04/2023] [Accepted: 04/11/2023] [Indexed: 04/16/2023]
Abstract
Adverse outcome pathway (AOP) frameworks help elucidate toxic mechanisms and support chemical regulation. AOPs link a molecular initiating event (MIE), key events (KEs), and an adverse outcome by key event relationships (KERs), which assess the biological plausibility, essentiality, and empirical evidence involved. Perfluorooctane sulfonate (PFOS), a hazardous poly-fluoroalkyl substance, demonstrates hepatotoxicity in rodents. PFOS may induce fatty liver disease (FLD) in humans; however, the underlying mechanism remains unclear. In this study, we evaluated the toxic mechanisms of PFOS-associated FLD by developing an AOP using publicly available data. We identified MIE and KEs by performing GO enrichment analysis on PFOS- and FLD-associated target genes collected from public databases. The MIEs and KEs were then prioritized by PFOS-gene-phenotype-FLD networks, AOP-helpFinder, and KEGG pathway analyses. Following a comprehensive literature review, an AOP was then developed. Finally, six KEs for the AOP of FLD were identified. This AOP indicated that toxicological processes initiated by SIRT1 inhibition led to SREBP-1c activation, de novo fatty acid synthesis, and fatty acid and triglyceride accumulation, culminating in liver steatosis. Our study provides insights into the toxic mechanism of PFOS-induced FLD and suggests approaches to assessing the risk of toxic chemicals.
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Affiliation(s)
- Moosoo Kim
- College of Pharmacy, Kyungsung University, Busan, 48434, Republic of Korea
| | - Sang Heon Kim
- College of Pharmacy, Kyungsung University, Busan, 48434, Republic of Korea
| | - Jun Yeong Choi
- College of Pharmacy, Kyungsung University, Busan, 48434, Republic of Korea
| | - Yong Joo Park
- College of Pharmacy, Kyungsung University, Busan, 48434, Republic of Korea.
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10
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Bozic D, Živančević K, Baralić K, Miljaković EA, Djordjević AB, Ćurčić M, Bulat Z, Antonijević B, Đukić-Ćosić D. Conducting bioinformatics analysis to predict sulforaphane-triggered adverse outcome pathways in healthy human cells. Biomed Pharmacother 2023; 160:114316. [PMID: 36731342 DOI: 10.1016/j.biopha.2023.114316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 01/17/2023] [Accepted: 01/26/2023] [Indexed: 02/04/2023] Open
Abstract
Sulforaphane (SFN) is a naturally occurring molecule present in plants from Brassica family. It becomes bioactive after hydrolytic reaction mediated by myrosinase or human gastrointestinal microbiota. Sulforaphane gained scientific popularity due to its antioxidant and anti-cancer properties. However, its toxicity profile and potential to cause adverse effects remain largely unidentified. Thus, this study aimed to generate SFN-triggered adverse outcome pathway (AOP) by looking at the relationship between SFN-chemical structure and its toxicity, as well as SFN-gene interactions. Quantitative structure-activity relationship (QSAR) analysis identified 2 toxophores (Derek Nexus software) that have the potential to cause chromosomal damage and skin sensitization in mammals or mutagenicity in bacteria. Data extracted from Comparative Toxicogenomics Database (CTD) linked SFN with previously proposed outcomes via gene interactions. The total of 11 and 146 genes connected SFN with chromosomal damage and skin diseases, respectively. However, network analysis (NetworkAnalyst tool) revealed that these genes function in wider networks containing 490 and 1986 nodes, respectively. The over-representation analysis (ExpressAnalyst tool) pointed out crucial biological pathways regulated by SFN-interfering genes. These pathways are uploaded to AOP-helpFinder tool which found the 2321 connections between 19 enriched pathways and SFN which were further considered as key events. Two major, interconnected AOPs were generated: first starting from disruption of biological pathways involved in cell cycle and cell proliferation leading to increased apoptosis, and the second one connecting activated immune system signaling pathways to inflammation and apoptosis. In both cases, chromosomal damage and/or skin diseases such as dermatitis or psoriasis appear as adverse outcomes.
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Affiliation(s)
- Dragica Bozic
- Department of Toxicology "Akademik Danilo Soldatović", Toxicological Risk Assessment Center, University of Belgrade - Faculty of Pharmacy, Vojvode Stepe 450, 11221 Belgrade, Serbia.
| | - Katarina Živančević
- Department of Toxicology "Akademik Danilo Soldatović", Toxicological Risk Assessment Center, University of Belgrade - Faculty of Pharmacy, Vojvode Stepe 450, 11221 Belgrade, Serbia; University of Belgrade - Faculty of Biology, Institute of Physiology and Biochemistry "Ivan Djaja", Center for Laser Microscopy, Studentski trg 16, 11158 Belgrade, Serbia
| | - Katarina Baralić
- Department of Toxicology "Akademik Danilo Soldatović", Toxicological Risk Assessment Center, University of Belgrade - Faculty of Pharmacy, Vojvode Stepe 450, 11221 Belgrade, Serbia
| | - Evica Antonijević Miljaković
- Department of Toxicology "Akademik Danilo Soldatović", Toxicological Risk Assessment Center, University of Belgrade - Faculty of Pharmacy, Vojvode Stepe 450, 11221 Belgrade, Serbia
| | - Aleksandra Buha Djordjević
- Department of Toxicology "Akademik Danilo Soldatović", Toxicological Risk Assessment Center, University of Belgrade - Faculty of Pharmacy, Vojvode Stepe 450, 11221 Belgrade, Serbia
| | - Marijana Ćurčić
- Department of Toxicology "Akademik Danilo Soldatović", Toxicological Risk Assessment Center, University of Belgrade - Faculty of Pharmacy, Vojvode Stepe 450, 11221 Belgrade, Serbia
| | - Zorica Bulat
- Department of Toxicology "Akademik Danilo Soldatović", Toxicological Risk Assessment Center, University of Belgrade - Faculty of Pharmacy, Vojvode Stepe 450, 11221 Belgrade, Serbia
| | - Biljana Antonijević
- Department of Toxicology "Akademik Danilo Soldatović", Toxicological Risk Assessment Center, University of Belgrade - Faculty of Pharmacy, Vojvode Stepe 450, 11221 Belgrade, Serbia
| | - Danijela Đukić-Ćosić
- Department of Toxicology "Akademik Danilo Soldatović", Toxicological Risk Assessment Center, University of Belgrade - Faculty of Pharmacy, Vojvode Stepe 450, 11221 Belgrade, Serbia
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Abdullahi M, Li X, Abdallah MAE, Stubbings W, Yan N, Barnard M, Guo LH, Colbourne JK, Orsini L. Daphnia as a Sentinel Species for Environmental Health Protection: A Perspective on Biomonitoring and Bioremediation of Chemical Pollution. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:14237-14248. [PMID: 36169655 PMCID: PMC9583619 DOI: 10.1021/acs.est.2c01799] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Despite available technology and the knowledge that chemical pollution damages human and ecosystem health, chemical pollution remains rampant, ineffectively monitored, rarely prevented, and only occasionally mitigated. We present a framework that helps address current major challenges in the monitoring and assessment of chemical pollution by broadening the use of the sentinel species Daphnia as a diagnostic agent of water pollution. And where prevention has failed, we propose the application of Daphnia as a bioremediation agent to help reduce hazards from chemical mixtures in the environment. By applying "omics" technologies to Daphnia exposed to real-world ambient chemical mixtures, we show improvements at detecting bioactive components of chemical mixtures, determining the potential effects of untested chemicals within mixtures, and identifying targets of toxicity. We also show that using Daphnia strains that naturally adapted to chemical pollution as removal agents of ambient chemical mixtures can sustainably improve environmental health protection. Expanding the use of Daphnia beyond its current applications in regulatory toxicology has the potential to improve both the assessment and the remediation of environmental pollution.
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Affiliation(s)
- Muhammad Abdullahi
- Environmental
Genomics Group, School of Biosciences, the
University of Birmingham, Birmingham B15 2TT, U.K.
| | - Xiaojing Li
- Environmental
Genomics Group, School of Biosciences, the
University of Birmingham, Birmingham B15 2TT, U.K.
| | | | - William Stubbings
- School
of Geography, Earth and Environmental Sciences, the University of Birmingham, Birmingham B15 2TT, U.K.
| | - Norman Yan
- Department
of Biology, York University, and Friends of the Muskoka Watershed, Bracebridge, Ontario P1L 1T7, Canada
| | - Marianne Barnard
- Environmental
Genomics Group, School of Biosciences, the
University of Birmingham, Birmingham B15 2TT, U.K.
| | - Liang-Hong Guo
- Institute
of Environmental and Health Sciences, China
Jiliang University, 258 Xueyuan Street, Hangzhou, Zhejiang 310018, People’s Republic of China
| | - John K. Colbourne
- Environmental
Genomics Group, School of Biosciences, the
University of Birmingham, Birmingham B15 2TT, U.K.
| | - Luisa Orsini
- Environmental
Genomics Group, School of Biosciences, the
University of Birmingham, Birmingham B15 2TT, U.K.
- The
Alan Turing Institute, British Library, 96 Euston Road, London NW1 2DB, U.K.
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12
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Ilić K, Krce L, Rodriguez-Ramos J, Rico F, Kalčec N, Aviani I, Turčić P, Pavičić I, Vinković Vrček I. Cytotoxicity of nanomixture: Combined action of silver and plastic nanoparticles on immortalized human lymphocytes. J Trace Elem Med Biol 2022; 73:127004. [PMID: 35617720 DOI: 10.1016/j.jtemb.2022.127004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 04/09/2022] [Accepted: 05/17/2022] [Indexed: 11/25/2022]
Abstract
BACKGROUND Silver nanoparticles (AgNP) are one of the most commercialized types of nanomaterials, with a wide range of applications owing to their antimicrobial activity. They are particularly important in hospitals and other healthcare settings, where they are used to maintain sterility of surfaces, textiles, catheters, medical implants, and more. However, AgNP can not only harm bacteria, but also damage mammalian cells and tissue. While the potential toxicity of AgNP is an understood risk, there is a lack of data on their toxicity in combination with polymeric materials, especially plastic nanoparticles such as polystyrene nanoparticles (PSNP) that can be released from surfaces of polystyrene devices during their medical use. AIM This study aimed to investigate combined effect of AgNP and nanoplastics on human immune response. METHODS Cells were treated with a range of PSNP and AgNP concentrations, either applied alone or in combination. Cytotoxicity, induction of apoptosis, generation of oxidative stress, uptake efficiency, intracellular localization and nanomechanical cell properties were selected as exposure biomarkers. RESULTS Collected experimental data showed that nanomixture induced oxidative stress, apoptosis and mortality of Jurkat cells stronger than its individual components. Cell treatment with AgNP/PSNP mixture also significantly changed cell mechanical properties, evidenced by reduction of cells' Young Modulus. CONCLUSION AgNP and PSNP showed additive toxic effects on immortalized human lymphocytes, evidenced by increase in cellular oxidative stress, induction of apoptosis, and reduction of cell stiffness. These results have important implications for using AgNP and PSNP in medical contexts, particularly for long-term medical implants.
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Affiliation(s)
- Krunoslav Ilić
- Institute for Medical Research and Occupational Health, Zagreb, Croatia
| | - Lucija Krce
- University of Split, Faculty of Science, Department of Physics, Split, Croatia
| | | | - Felix Rico
- Aix-Marseille University, INSERM, CNRS, LAI, 13009 Marseille, France
| | - Nikolina Kalčec
- Institute for Medical Research and Occupational Health, Zagreb, Croatia
| | - Ivica Aviani
- University of Split, Faculty of Science, Department of Physics, Split, Croatia
| | - Petra Turčić
- University of Zagreb, Faculty of Pharmacy and Biochemistry, Zagreb, Croatia
| | - Ivan Pavičić
- Institute for Medical Research and Occupational Health, Zagreb, Croatia
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13
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Chauhan V, Hamada N, Wilkins R, Garnier-Laplace J, Laurier D, Beaton D, Tollefsen KE. A high-level overview of the Organisation for Economic Co-operation and Development Adverse Outcome Pathway Programme. Int J Radiat Biol 2022; 98:1704-1713. [PMID: 35938955 DOI: 10.1080/09553002.2022.2110311] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Background The Organisation for Economic Co-operation and Development (OECD), through its Chemical Safety Programme, is delegated to ensure the safety of humans and wildlife from harmful toxicants. To support these needs, initiatives to increase the efficiency of hazard identification and risk management are under way. Amongst these, the adverse outcome pathway (AOP) approach integrates information on biological knowledge and test methodologies (both established and new) to support regulatory decision making. AOPs collate biological knowledge from different sources, assess lines of evidence through considerations of causality and undergo rigorous peer-review before being subsequently endorsed by the OECD. It is envisioned that the OECD AOP Development Programme will transform the toxicity testing paradigm by leveraging the strengths of mechanistic and modelling based approaches and enhance the utility of high throughput screening assays. Since its launch, in 2012, the AOP Development Programme has matured with a greater number of AOPs endorsed since inception, and the attraction of new scientific disciplines (e.g. the radiation field). Recently, a Radiation and Chemical (Rad/Chem) AOP Joint Topical Group has been formed by the OECD Nuclear Energy Agency High-Level Group on Low-Dose Research (HLG-LDR) under the auspices of the Committee on Radiological Protection and Public Health (CRPPH). The topical group will work to evolve the development and use of the AOP framework in radiation research and regulation. As part of these efforts, the group will bring awareness and understanding on the programme, as it has matured from the chemical perspective. In this context, this paper provides the radiation community with a high-level overview of the OECD AOP Development Programme, including examples of application using knowledge gleaned from the field of chemical toxicology, and their work towards regulatory implementation. Conclusion: Although the drivers for developing AOPs in chemical sector differ from that of the radiation field, the principles and transparency of the approach can benefit both scientific disciplines. By providing perspectives and an understanding of the evolution of the OECD AOP Development Programme including case examples and work towards quantitative AOP development, it may motivate the expansion and implementation of AOPs in the radiation field.
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Affiliation(s)
- Vinita Chauhan
- Environmental Health Science Research Bureau, Health Canada, Ottawa, Ontario, Canada
| | - Nobuyuki Hamada
- Biology and Environmental Chemistry Division, Sustainable System Research Laboratory, Central Research Institute of Electric Power Industry (CRIEPI), Komae, Tokyo, Japan
| | - Ruth Wilkins
- Environmental Health Science Research Bureau, Health Canada, Ottawa, Ontario, Canada
| | | | - Dominique Laurier
- Institute for Radiological Protection and Nuclear Safety (IRSN), Health and Environment Division, Fontenay-aux-Roses, F-92262, France
| | | | - Knut Erik Tollefsen
- Norwegian Institute for Water Research (NIVA), Oslo, Norway.,Norwegian University of Life Sciences (NMBU), Ås, Norway.,Centre for Environmental Radioactivity, Norwegian University of Life Sciences (NMBU), Ås, Norway
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14
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Chauhan V, Hamada N, Garnier-Laplace J, Laurier D, Beaton D, Tollefsen KE, Locke PA. Establishing a Communication and Engagement Strategy to Facilitate the Adoption of the Adverse Outcome Pathways in Radiation Research and Regulation. Int J Radiat Biol 2022; 98:1714-1721. [PMID: 35666945 DOI: 10.1080/09553002.2022.2086716] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
BACKGROUND Studies on human health and ecological effects of ionizing radiation are rapidly evolving as innovative technologies arise and the body of scientific knowledge grows. Structuring this information could effectively support the development of decision making tools and health risk models to complement current system of radiation protection. To this end, the adverse outcome pathway (AOP) approach is being explored as a means to consolidate the most relevant research to identify causation between exposure to a chemical or non-chemical stressor and disease or adverse effect progression. This tool is particularly important for low dose and low dose rate radiation exposures because of the latency and uncertainties in the biological responses at these exposure levels. To progress this aspect, it is essential to build a community of developers, facilitators, risk assessors (in the private sector and in government), policy-makers, and regulators who understand the strengths and weaknesses of, and how to appropriately utilize AOPs for consolidating our knowledge on the impact of low dose ionizing radiation. Through co-ordination with the Organisation of Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) High-Level Group on Low-Dose Research (HLG-LDR) and OECD's AOP Programme, initiatives are under way to demonstrate this approach in radiation research and regulation. Among these, a robust communications strategy and stakeholder engagement will be essential. It will help establish best practices for AOPs in institutional project development and aid in dissemination for more efficient and timely uptake and use of AOPs. In this regard, on June 1, 2021, the Radiation and Chemical (Rad/Chem) AOP Joint Topical Group was formed as part of the initiative from the NEA's HLG-LDR. The topical group will work to develop a communication and engagement strategy to define the target audiences, establish the clear messages and identify the delivery and engagement platforms. CONCLUSION The incorporation of the best science and better decision-making should motive the radiation protection community to develop, refine and use AOPs, recognizing that their incorporation into radiation health risk assessments is critical for public health and environmental protection in the 21st century.
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Affiliation(s)
- Vinita Chauhan
- Environmental Health Science Research Bureau, Health Canada, Ottawa, Ontario, Canada
| | - Nobuyuki Hamada
- Environmental Chemistry Division, Sustainable System Research Laboratory, Central Research Institute of Electric Power Industry (CRIEPI), Komae, Tokyo, Japan
| | | | - Dominique Laurier
- Institute for Radiological Protection and Nuclear Safety (IRSN), Health and Environment Division, Fontenay-aux-Roses, F-92262, France
| | | | - Knut Erik Tollefsen
- Norwegian Institute for Water Research (NIVA), Oslo, Norway.,Norwegian University of Life Sciences (NMBU), Ås, Norway.,Centre for Environmental Radioactivity, Norwegian University of Life Sciences (NMBU), Ås, Norway
| | - Paul A Locke
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA
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15
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Baldwin AK, Corsi SR, Stefaniak OM, Loken LC, Villeneuve DL, Ankley GT, Blackwell BR, Lenaker PL, Nott MA, Mills MA. Risk-Based Prioritization of Organic Chemicals and Locations of Ecological Concern in Sediment From Great Lakes Tributaries. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2022; 41:1016-1041. [PMID: 35170813 PMCID: PMC9306483 DOI: 10.1002/etc.5286] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 12/28/2021] [Accepted: 12/31/2021] [Indexed: 05/24/2023]
Abstract
With improved analytical techniques, environmental monitoring studies are increasingly able to report the occurrence of tens or hundreds of chemicals per site, making it difficult to identify the most relevant chemicals from a biological standpoint. For the present study, organic chemical occurrence was examined, individually and as mixtures, in the context of potential biological effects. Sediment was collected at 71 Great Lakes (USA/Canada) tributary sites and analyzed for 87 chemicals. Multiple risk-based lines of evidence were used to prioritize chemicals and locations, including comparing sediment concentrations and estimated porewater concentrations with established whole-organism benchmarks (i.e., sediment and water quality criteria and screening values) and with high-throughput toxicity screening data from the US Environmental Protection Agency's ToxCast database, estimating additive effects of chemical mixtures on common ToxCast endpoints, and estimating toxic equivalencies for mixtures of alkylphenols and polycyclic aromatic hydrocarbons (PAHs). This multiple-lines-of-evidence approach enabled the screening of more chemicals, mitigated the uncertainties of individual approaches, and strengthened common conclusions. Collectively, at least one benchmark/screening value was exceeded for 54 of the 87 chemicals, with exceedances observed at all 71 of the monitoring sites. Chemicals with the greatest potential for biological effects, both individually and as mixture components, were bisphenol A, 4-nonylphenol, indole, carbazole, and several PAHs. Potential adverse outcomes based on ToxCast gene targets and putative adverse outcome pathways relevant to individual chemicals and chemical mixtures included tumors, skewed sex ratios, reproductive dysfunction, hepatic steatosis, and early mortality, among others. The results provide a screening-level prioritization of chemicals with the greatest potential for adverse biological effects and an indication of sites where they are most likely to occur. Environ Toxicol Chem 2022;41:1016-1041. Published 2022. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
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16
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Ramšak Ž, Modic V, Li RA, vom Berg C, Zupanic A. From Causal Networks to Adverse Outcome Pathways: A Developmental Neurotoxicity Case Study. FRONTIERS IN TOXICOLOGY 2022; 4:815754. [PMID: 35295214 PMCID: PMC8915909 DOI: 10.3389/ftox.2022.815754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 01/31/2022] [Indexed: 11/15/2022] Open
Abstract
The last decade has seen the adverse outcome pathways (AOP) framework become one of the most powerful tools in chemical risk assessment, but the development of new AOPs remains a slow and manually intensive process. Here, we present a faster approach for AOP generation, based on manually curated causal toxicological networks. As a case study, we took a recently published zebrafish developmental neurotoxicity network, which contains causally connected molecular events leading to neuropathologies, and developed two new adverse outcome pathways: Inhibition of Fyna (Src family tyrosine kinase A) leading to increased mortality via decreased eye size (AOP 399 on AOP-Wiki) and GSK3beta (Glycogen synthase kinase 3 beta) inactivation leading to increased mortality via defects in developing inner ear (AOP 410). The approach consists of an automatic separation of the toxicological network into candidate AOPs, filtering the AOPs according to available evidence and length as well as manual development of new AOPs and weight-of-evidence evaluation. The semiautomatic approach described here provides a new opportunity for fast and straightforward AOP development based on large network resources.
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Affiliation(s)
- Živa Ramšak
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
| | - Vid Modic
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
- Faculty of Chemistry and Chemical Technology, University of Ljubljana, Ljubljana, Slovenia
| | - Roman A. Li
- Department of Environmental Toxicology, Eawag—Swiss Federal Institute of Aquatic Science and Technology, Duebendorf, Switzerland
| | - Colette vom Berg
- Department of Environmental Toxicology, Eawag—Swiss Federal Institute of Aquatic Science and Technology, Duebendorf, Switzerland
| | - Anze Zupanic
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
- *Correspondence: Anze Zupanic,
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Martens M, Evelo CT, Willighagen EL. Providing Adverse Outcome Pathways from the AOP-Wiki in a Semantic Web Format to Increase Usability and Accessibility of the Content. APPLIED IN VITRO TOXICOLOGY 2022; 8:2-13. [PMID: 35388368 DOI: 10.26434/chemrxiv.13524191] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
INTRODUCTION The AOP-Wiki is the main platform for the development and storage of adverse outcome pathways (AOPs). These AOPs describe mechanistic information about toxicodynamic processes and can be used to develop effective risk assessment strategies. However, it is challenging to automatically and systematically parse, filter, and use its contents. We explored solutions to better structure the AOP-Wiki content, and to link it with chemical and biological resources. Together, this allows more detailed exploration, which can be automated. MATERIALS AND METHODS We converted the complete AOP-Wiki content into resource description framework (RDF) triples. We used >20 ontologies for the semantic annotation of property-object relations, including the Chemical Information Ontology, Dublin Core, and the AOP Ontology. RESULTS The resulting RDF contains >122,000 triples describing 158 unique properties of >15,000 unique subjects. Furthermore, >3500 link-outs were added to 12 chemical databases, and >7500 link-outs to 4 gene and protein databases. The AOP-Wiki RDF has been made available at https://aopwiki.rdf.bigcat-bioinformatics.org. DISCUSSION SPARQL queries can be used to answer biological and toxicological questions, such as listing measurement methods for all Key Events leading to an Adverse Outcome of interest. The full power that the use of this new resource provides becomes apparent when combining the content with external databases using federated queries. CONCLUSION Overall, the AOP-Wiki RDF allows new ways to explore the rapidly growing AOP knowledge and makes the integration of this database in automated workflows possible, making the AOP-Wiki more FAIR.
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Affiliation(s)
- Marvin Martens
- Department of Bioinformatics-BiGCaT, NUTRIM, and Maastricht University, Maastricht, The Netherlands
| | - Chris T Evelo
- Department of Bioinformatics-BiGCaT, NUTRIM, and Maastricht University, Maastricht, The Netherlands
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands
| | - Egon L Willighagen
- Department of Bioinformatics-BiGCaT, NUTRIM, and Maastricht University, Maastricht, The Netherlands
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18
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Martens M, Evelo CT, Willighagen EL. Providing Adverse Outcome Pathways from the AOP-Wiki in a Semantic Web Format to Increase Usability and Accessibility of the Content. APPLIED IN VITRO TOXICOLOGY 2022; 8:2-13. [PMID: 35388368 PMCID: PMC8978481 DOI: 10.1089/aivt.2021.0010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
Introduction: The AOP-Wiki is the main platform for the development and storage of adverse outcome pathways (AOPs). These AOPs describe mechanistic information about toxicodynamic processes and can be used to develop effective risk assessment strategies. However, it is challenging to automatically and systematically parse, filter, and use its contents. We explored solutions to better structure the AOP-Wiki content, and to link it with chemical and biological resources. Together, this allows more detailed exploration, which can be automated. Materials and Methods: We converted the complete AOP-Wiki content into resource description framework (RDF) triples. We used >20 ontologies for the semantic annotation of property–object relations, including the Chemical Information Ontology, Dublin Core, and the AOP Ontology. Results: The resulting RDF contains >122,000 triples describing 158 unique properties of >15,000 unique subjects. Furthermore, >3500 link-outs were added to 12 chemical databases, and >7500 link-outs to 4 gene and protein databases. The AOP-Wiki RDF has been made available at https://aopwiki.rdf.bigcat-bioinformatics.org Discussion: SPARQL queries can be used to answer biological and toxicological questions, such as listing measurement methods for all Key Events leading to an Adverse Outcome of interest. The full power that the use of this new resource provides becomes apparent when combining the content with external databases using federated queries. Conclusion: Overall, the AOP-Wiki RDF allows new ways to explore the rapidly growing AOP knowledge and makes the integration of this database in automated workflows possible, making the AOP-Wiki more FAIR.
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Affiliation(s)
- Marvin Martens
- Department of Bioinformatics—BiGCaT, NUTRIM, and Maastricht University, Maastricht, The Netherlands
| | - Chris T. Evelo
- Department of Bioinformatics—BiGCaT, NUTRIM, and Maastricht University, Maastricht, The Netherlands
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands
| | - Egon L. Willighagen
- Department of Bioinformatics—BiGCaT, NUTRIM, and Maastricht University, Maastricht, The Netherlands
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Paini A, Campia I, Cronin MTD, Asturiol D, Ceriani L, Exner TE, Gao W, Gomes C, Kruisselbrink J, Martens M, Meek MEB, Pamies D, Pletz J, Scholz S, Schüttler A, Spînu N, Villeneuve DL, Wittwehr C, Worth A, Luijten M. Towards a qAOP framework for predictive toxicology - Linking data to decisions. COMPUTATIONAL TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2022; 21:100195. [PMID: 35211660 PMCID: PMC8850654 DOI: 10.1016/j.comtox.2021.100195] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 07/23/2021] [Accepted: 10/09/2021] [Indexed: 12/22/2022]
Abstract
Chemical toxicity assessment depends on the quantification of kinetics and dynamics. Quantitative AOPs (qAOPs) are toxicodynamic models based on Adverse Outcome Pathways. Existing e-resources could form the basis of an e-infrastructure for qAOP modelling. Best practices for qAOP development, assessment and application are needed. Three qAOP case studies are presented to illustrate a modelling workflow.
The adverse outcome pathway (AOP) is a conceptual construct that facilitates organisation and interpretation of mechanistic data representing multiple biological levels and deriving from a range of methodological approaches including in silico, in vitro and in vivo assays. AOPs are playing an increasingly important role in the chemical safety assessment paradigm and quantification of AOPs is an important step towards a more reliable prediction of chemically induced adverse effects. Modelling methodologies require the identification, extraction and use of reliable data and information to support the inclusion of quantitative considerations in AOP development. An extensive and growing range of digital resources are available to support the modelling of quantitative AOPs, providing a wide range of information, but also requiring guidance for their practical application. A framework for qAOP development is proposed based on feedback from a group of experts and three qAOP case studies. The proposed framework provides a harmonised approach for both regulators and scientists working in this area.
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Affiliation(s)
- Alicia Paini
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Ivana Campia
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | | | - David Asturiol
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | | | - Thomas E Exner
- Edelweiss Connect GmbH, Technology Park Basel, Basel, Switzerland
| | - Wang Gao
- Institut National de l'Environnement Industriel et des Risques (INERIS), Verneuil-en-Halatte, France
| | | | | | | | | | - David Pamies
- Department of Physiology, Lausanne and Swiss Centre for Applied Human Toxicology (SCAHT), University of Lausanne, Lausanne, Switzerland
| | - Julia Pletz
- Liverpool John Moores University, Liverpool, United Kingdom
| | - Stefan Scholz
- Helmholtz Centre for Environmental Research GmbH - UFZ, Leipzig, Germany
| | - Andreas Schüttler
- Helmholtz Centre for Environmental Research GmbH - UFZ, Leipzig, Germany
| | - Nicoleta Spînu
- Liverpool John Moores University, Liverpool, United Kingdom
| | - Daniel L Villeneuve
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Duluth, MN, USA
| | | | - Andrew Worth
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Mirjam Luijten
- National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
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20
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Mortensen HM, Martens M, Senn J, Levey T, Evelo CT, Willighagen EL, Exner T. The AOP-DB RDF: Applying FAIR Principles to the Semantic Integration of AOP Data Using the Research Description Framework. FRONTIERS IN TOXICOLOGY 2022; 4:803983. [PMID: 35295213 PMCID: PMC8915825 DOI: 10.3389/ftox.2022.803983] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 01/13/2022] [Indexed: 01/12/2023] Open
Abstract
Computational toxicology is central to the current transformation occurring in toxicology and chemical risk assessment. There is a need for more efficient use of existing data to characterize human toxicological response data for environmental chemicals in the US and Europe. The Adverse Outcome Pathway (AOP) framework helps to organize existing mechanistic information and contributes to what is currently being described as New Approach Methodologies (NAMs). AOP knowledge and data are currently submitted directly by users and stored in the AOP-Wiki (https://aopwiki.org/). Automatic and systematic parsing of AOP-Wiki data is challenging, so we have created the EPA Adverse Outcome Pathway Database. The AOP-DB, developed by the US EPA to assist in the biological and mechanistic characterization of AOP data, provides a broad, systems-level overview of the biological context of AOPs. Here we describe the recent semantic mapping efforts for the AOP-DB, and how this process facilitates the integration of AOP-DB data with other toxicologically relevant datasets through a use case example.
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Affiliation(s)
- Holly M. Mortensen
- United States Environmental Protection Agency, Office of Research and Development, Center for Public Health and Environmental Assessment, Research Triangle Park, Durham, NC, United States
- *Correspondence: Holly M. Mortensen,
| | - Marvin Martens
- Department of Bioinformatics (BiGCaT), Maastricht University, Maastricht, Netherlands
| | - Jonathan Senn
- Oak Ridge Associated Universities, Oak Ridge, TN, United States
| | - Trevor Levey
- Oak Ridge Associated Universities, Oak Ridge, TN, United States
- SAS Institute, Cary, NC, United States
| | - Chris T. Evelo
- Department of Bioinformatics (BiGCaT), Maastricht University, Maastricht, Netherlands
- Maastricht Centre for Systems Biology, Maastricht University, Maastricht, Netherlands
| | - Egon L. Willighagen
- Department of Bioinformatics (BiGCaT), Maastricht University, Maastricht, Netherlands
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21
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Scholz S, Nichols JW, Escher BI, Ankley GT, Altenburger R, Blackwell B, Brack W, Burkhard L, Collette TW, Doering JA, Ekman D, Fay K, Fischer F, Hackermüller J, Hoffman JC, Lai C, Leuthold D, Martinovic-Weigelt D, Reemtsma T, Pollesch N, Schroeder A, Schüürmann G, von Bergen M. The Eco-Exposome Concept: Supporting an Integrated Assessment of Mixtures of Environmental Chemicals. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2022; 41:30-45. [PMID: 34714945 PMCID: PMC9104394 DOI: 10.1002/etc.5242] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 10/20/2021] [Accepted: 10/26/2021] [Indexed: 05/04/2023]
Abstract
Organisms are exposed to ever-changing complex mixtures of chemicals over the course of their lifetime. The need to more comprehensively describe this exposure and relate it to adverse health effects has led to formulation of the exposome concept in human toxicology. Whether this concept has utility in the context of environmental hazard and risk assessment has not been discussed in detail. In this Critical Perspective, we propose-by analogy to the human exposome-to define the eco-exposome as the totality of the internal exposure (anthropogenic and natural chemicals, their biotransformation products or adducts, and endogenous signaling molecules that may be sensitive to an anthropogenic chemical exposure) over the lifetime of an ecologically relevant organism. We describe how targeted and nontargeted chemical analyses and bioassays can be employed to characterize this exposure and discuss how the adverse outcome pathway concept could be used to link this exposure to adverse effects. Available methods, their limitations, and/or requirement for improvements for practical application of the eco-exposome concept are discussed. Even though analysis of the eco-exposome can be resource-intensive and challenging, new approaches and technologies make this assessment increasingly feasible. Furthermore, an improved understanding of mechanistic relationships between external chemical exposure(s), internal chemical exposure(s), and biological effects could result in the development of proxies, that is, relatively simple chemical and biological measurements that could be used to complement internal exposure assessment or infer the internal exposure when it is difficult to measure. Environ Toxicol Chem 2022;41:30-45. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
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Affiliation(s)
- Stefan Scholz
- Helmholtz Centre for Environmental Research—UFZ, Leipzig, Germany
- Address correspondence to
| | - John W. Nichols
- Office of Research and Development, Great Lakes Ecology and Toxicology Division, US Environmental Protection Agency, Duluth, Minnesota
| | - Beate I. Escher
- Helmholtz Centre for Environmental Research—UFZ, Leipzig, Germany
- Environmental Toxicology, Center for Applied Geoscience, Eberhard Karls University Tubingen, Tubingen, Germany
| | - Gerald T. Ankley
- Office of Research and Development, Great Lakes Ecology and Toxicology Division, US Environmental Protection Agency, Duluth, Minnesota
| | - Rolf Altenburger
- Helmholtz Centre for Environmental Research—UFZ, Leipzig, Germany
- Institute for Environmental Research, Biologie V, RWTH Aachen University, Aachen, Germany
| | - Brett Blackwell
- Office of Research and Development, Great Lakes Ecology and Toxicology Division, US Environmental Protection Agency, Duluth, Minnesota
| | - Werner Brack
- Helmholtz Centre for Environmental Research—UFZ, Leipzig, Germany
- Department of Evolutionary Ecology and Environmental Toxicology, Faculty of Biological Sciences, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Lawrence Burkhard
- Office of Research and Development, Great Lakes Ecology and Toxicology Division, US Environmental Protection Agency, Duluth, Minnesota
| | - Timothy W. Collette
- Office of Research and Development, Ecosystem Processes Division, US Environmental Protection Agency, Athens, Georgia
| | - Jon A. Doering
- National Research Council, US Environmental Protection Agency, Duluth, Minnesota
| | - Drew Ekman
- Office of Research and Development, Ecosystem Processes Division, US Environmental Protection Agency, Athens, Georgia
| | - Kellie Fay
- Office of Pollution Prevention and Toxics, Risk Assessment Division, US Environmental Protection Agency, Washington, DC
| | - Fabian Fischer
- Helmholtz Centre for Environmental Research—UFZ, Leipzig, Germany
| | | | - Joel C. Hoffman
- Office of Research and Development, Great Lakes Ecology and Toxicology Division, US Environmental Protection Agency, Duluth, Minnesota
| | - Chih Lai
- College of Arts and Sciences, University of Saint Thomas, St. Paul, Minnesota, USA
| | - David Leuthold
- Helmholtz Centre for Environmental Research—UFZ, Leipzig, Germany
| | | | | | - Nathan Pollesch
- Office of Research and Development, Great Lakes Ecology and Toxicology Division, US Environmental Protection Agency, Duluth, Minnesota
| | | | - Gerrit Schüürmann
- Helmholtz Centre for Environmental Research—UFZ, Leipzig, Germany
- Institute of Organic Chemistry, Technische Universitat Bergakademie Freiberg, Freiberg, Germany
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22
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Chauhan V, Beaton D, Hamada N, Wilkins R, Burtt J, Leblanc J, Cool D, Garnier-Laplace J, Laurier D, Le Y, Yamada Y, Tollefsen KE. Adverse Outcome Pathway: A Path towards better Data Consolidation and Global Co-ordination of Radiation Research. Int J Radiat Biol 2021; 98:1694-1703. [PMID: 34919011 DOI: 10.1080/09553002.2021.2020363] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Background The purpose of toxicology is to protect human health and the environment. To support this, the Organisation for Economic Co-operation and Development (OECD), operating via its Extended Advisory Group for Molecular Screening and Toxicogenomics (EAGMST), has been developing the Adverse Outcome Pathway (AOP) approach to consolidate evidence for chemical toxicity spanning multiple levels of biological organization. The knowledge transcribed into AOPs provides a structured framework to transparently organize data, examine the weight of evidence of the AOP, and identify causal relationships between exposure to stressors and adverse effects of regulatory perspective. The AOP framework has undergone substantial maturation in the field of hazard characterization of chemicals over the last decade, and has also recently gained attention from the radiation community as a means to advance the mechanistic understanding of human and ecological health effects from exposure to ionizing radiation at low dose and low dose-rates. To fully exploit the value of such approaches for facilitating risk assessment and management in the field of radiation protection, solicitation of experiences and active cooperation between chemical and radiation communities are needed. As a result, the Radiation and Chemical (Rad/Chem) AOP joint topical group was formed on June 1, 2021 as part of the initiative from the High Level Group on Low Dose Research (HLG-LDR). HLG-LDR is overseen by the OECD Nuclear Energy Agency (NEA) Committee on Radiation Protection and Public Health (CRPPH). The main aims of the joint AOP topical group are to advance the use of AOPs in radiation research and foster broader implementation of AOPs into hazard and risk assessment. With global representation, it serves as a forum to discuss, identify and develop joint initiatives that support research and take on regulatory challenges. Conclusion: The Rad/Chem AOP joint topical group will specifically engage, promote, and implement the use of the AOP framework to: a) organize and evaluate mechanistic knowledge relevant to the protection of human and ecosystem health from radiation; b) identify data gaps and research needs pertinent to expanding knowledge of low dose and low dose-rate radiation effects; and c) demonstrate utility to support risk assessment by developing radiation-relevant case studies. It is envisioned that the Rad/Chem AOP joint topical group will actively liaise with the OECD EAGMST AOP developmental program to collectively advance areas of common interest and, specifically, provide recommendations for harmonization of the AOP framework to accommodate non-chemical stressors, such as radiation.
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Affiliation(s)
- Vinita Chauhan
- Environmental Health Science Research Bureau, Health Canada, Ottawa, Ontario, Canada
| | | | - Nobuyuki Hamada
- Radiation Safety Unit, Biology and Environmental Chemistry Division, Sustainable System Research Laboratory, Central Research Institute of Electric Power Industry (CRIEPI), Komae, Tokyo, Japan
| | - Ruth Wilkins
- Environmental Health Science Research Bureau, Health Canada, Ottawa, Ontario, Canada
| | - Julie Burtt
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ontario, Canada
| | - Julie Leblanc
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ontario, Canada
| | - Donald Cool
- Electric Power Research Institute, Charlotte, North Carolina, US
| | | | - Dominque Laurier
- Institute for Radiological Protection and Nuclear Safety (IRSN), Health and Environment Division, Fontenay-aux-Roses, F-92262, France
| | - Yevgeniya Le
- CANDU Owners Group Inc., Toronto, Ontario, Canada
| | - Yukata Yamada
- Department of Radiation Effects Research, National Institute of Radiological Sciences, National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Knut Erik Tollefsen
- Norwegian Institute for Water Research (NIVA), Gaustadalléen 21, Oslo, Norway.,Norwegian University of Life Sciences (NMBU), Ås, Norway.,Centre for Environmental Radioactivity, Norwegian University of Life Sciences (NMBU), Ås, Norway
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23
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Wu Q, Bagdad Y, Taboureau O, Audouze K. Capturing a Comprehensive Picture of Biological Events From Adverse Outcome Pathways in the Drug Exposome. Front Public Health 2021; 9:763962. [PMID: 34976924 PMCID: PMC8718398 DOI: 10.3389/fpubh.2021.763962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 11/16/2021] [Indexed: 11/13/2022] Open
Abstract
Background: The chemical part of the exposome, including drugs, may explain the increase of health effects with outcomes such as infertility, allergies, metabolic disorders, which cannot be only explained by the genetic changes. To better understand how drug exposure can impact human health, the concepts of adverse outcome pathways (AOPs) and AOP networks (AONs), which are representations of causally linked events at different biological levels leading to adverse health, could be used for drug safety assessment.Methods: To explore the action of drugs across multiple scales of the biological organization, we investigated the use of a network-based approach in the known AOP space. Considering the drugs and their associations to biological events, such as molecular initiating event and key event, a bipartite network was developed. This bipartite network was projected into a monopartite network capturing the event–event linkages. Nevertheless, such transformation of a bipartite network to a monopartite network had a huge risk of information loss. A way to solve this problem is to quantify the network reduction. We calculated two scoring systems, one measuring the uncertainty and a second one describing the loss of coverage on the developed event–event network to better investigate events from AOPs linked to drugs.Results: This AON analysis allowed us to identify biological events that are highly connected to drugs, such as events involving nuclear receptors (ER, AR, and PXR/SXR). Furthermore, we observed that the number of events involved in a linkage pattern with drugs is a key factor that influences information loss during monopartite network projection. Such scores have the potential to quantify the uncertainty of an event involved in an AON, and could be valuable for the weight of evidence assessment of AOPs. A case study related to infertility, more specifically to “decrease, male agenital distance” is presented.Conclusion: This study highlights that computational approaches based on network science may help to understand the complexity of drug health effects, with the aim to support drug safety assessment.
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Affiliation(s)
- Qier Wu
- INSERM U1124, CNRS ERL3649, Université de Paris, Paris, France
| | - Youcef Bagdad
- INSERM U1124, CNRS ERL3649, Université de Paris, Paris, France
| | | | - Karine Audouze
- INSERM U1124, CNRS ERL3649, Université de Paris, Paris, France
- *Correspondence: Karine Audouze
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24
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Bassan A, Alves VM, Amberg A, Anger LT, Auerbach S, Beilke L, Bender A, Cronin MT, Cross KP, Hsieh JH, Greene N, Kemper R, Kim MT, Mumtaz M, Noeske T, Pavan M, Pletz J, Russo DP, Sabnis Y, Schaefer M, Szabo DT, Valentin JP, Wichard J, Williams D, Woolley D, Zwickl C, Myatt GJ. In silico approaches in organ toxicity hazard assessment: current status and future needs in predicting liver toxicity. COMPUTATIONAL TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2021; 20:100187. [PMID: 35340402 PMCID: PMC8955833 DOI: 10.1016/j.comtox.2021.100187] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/15/2023]
Abstract
Hepatotoxicity is one of the most frequently observed adverse effects resulting from exposure to a xenobiotic. For example, in pharmaceutical research and development it is one of the major reasons for drug withdrawals, clinical failures, and discontinuation of drug candidates. The development of faster and cheaper methods to assess hepatotoxicity that are both more sustainable and more informative is critically needed. The biological mechanisms and processes underpinning hepatotoxicity are summarized and experimental approaches to support the prediction of hepatotoxicity are described, including toxicokinetic considerations. The paper describes the increasingly important role of in silico approaches and highlights challenges to the adoption of these methods including the lack of a commonly agreed upon protocol for performing such an assessment and the need for in silico solutions that take dose into consideration. A proposed framework for the integration of in silico and experimental information is provided along with a case study describing how computational methods have been used to successfully respond to a regulatory question concerning non-genotoxic impurities in chemically synthesized pharmaceuticals.
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Affiliation(s)
- Arianna Bassan
- Innovatune srl, Via Giulio Zanon 130/D, 35129 Padova, Italy
| | - Vinicius M. Alves
- The National Institute of Environmental Health Sciences, Division of the National Toxicology, Program, Research Triangle Park, NC 27709, USA
| | - Alexander Amberg
- Sanofi, R&D Preclinical Safety Frankfurt, Industriepark Hoechst, D-65926 Frankfurt am Main, Germany
| | | | - Scott Auerbach
- The National Institute of Environmental Health Sciences, Division of the National Toxicology, Program, Research Triangle Park, NC 27709, USA
| | - Lisa Beilke
- Toxicology Solutions Inc., San Diego, CA, USA
| | - Andreas Bender
- AI and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW
| | - Mark T.D. Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, L3 3AF, UK
| | | | - Jui-Hua Hsieh
- The National Institute of Environmental Health Sciences, Division of the National Toxicology, Program, Research Triangle Park, NC 27709, USA
| | - Nigel Greene
- Data Science and AI, DSM, IMED Biotech Unit, AstraZeneca, Boston, USA
| | - Raymond Kemper
- Nuvalent, One Broadway, 14th floor, Cambridge, MA, 02142, USA
| | - Marlene T. Kim
- US Food and Drug Administration, Center for Drug Evaluation and Research, Silver Spring, MD, 20993, USA
| | - Moiz Mumtaz
- Office of the Associate Director for Science (OADS), Agency for Toxic Substances and Disease, Registry, US Department of Health and Human Services, Atlanta, GA, USA
| | - Tobias Noeske
- Imaging and Data Analytics, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Gothenburg, Sweden
| | - Manuela Pavan
- Innovatune srl, Via Giulio Zanon 130/D, 35129 Padova, Italy
| | - Julia Pletz
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, L3 3AF, UK
| | - Daniel P. Russo
- Department of Chemistry, Rutgers University, Camden, NJ 08102, USA
- The Rutgers Center for Computational and Integrative Biology, Camden, NJ 08102, USA
| | - Yogesh Sabnis
- UCB Biopharma SRL, Chemin du Foriest – B-1420 Braine-l’Alleud, Belgium
| | - Markus Schaefer
- Sanofi, R&D Preclinical Safety Frankfurt, Industriepark Hoechst, D-65926 Frankfurt am Main, Germany
| | | | | | - Joerg Wichard
- Bayer AG, Genetic Toxicology, Müllerstr. 178, 13353 Berlin, Germany
| | - Dominic Williams
- Functional & Mechanistic Safety, Clinical Pharmacology & Safety Sciences, AstraZeneca, Darwin Building 310, Cambridge Science Park, Milton Rd, Cambridge CB4 0FZ, UK
| | - David Woolley
- ForthTox Limited, PO Box 13550, Linlithgow, EH49 7YU, UK
| | - Craig Zwickl
- Transendix LLC, 1407 Moores Manor, Indianapolis, IN 46229, USA
| | - Glenn J. Myatt
- Instem, 1393 Dublin Road, Columbus, OH 43215. USA
- Corresponding author. (G.J. Myatt)
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25
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Bassan A, Alves VM, Amberg A, Anger LT, Beilke L, Bender A, Bernal A, Cronin MT, Hsieh JH, Johnson C, Kemper R, Mumtaz M, Neilson L, Pavan M, Pointon A, Pletz J, Ruiz P, Russo DP, Sabnis Y, Sandhu R, Schaefer M, Stavitskaya L, Szabo DT, Valentin JP, Woolley D, Zwickl C, Myatt GJ. In silico approaches in organ toxicity hazard assessment: Current status and future needs for predicting heart, kidney and lung toxicities. COMPUTATIONAL TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2021; 20:100188. [PMID: 35721273 PMCID: PMC9205464 DOI: 10.1016/j.comtox.2021.100188] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
The kidneys, heart and lungs are vital organ systems evaluated as part of acute or chronic toxicity assessments. New methodologies are being developed to predict these adverse effects based on in vitro and in silico approaches. This paper reviews the current state of the art in predicting these organ toxicities. It outlines the biological basis, processes and endpoints for kidney toxicity, pulmonary toxicity, respiratory irritation and sensitization as well as functional and structural cardiac toxicities. The review also covers current experimental approaches, including off-target panels from secondary pharmacology batteries. Current in silico approaches for prediction of these effects and mechanisms are described as well as obstacles to the use of in silico methods. Ultimately, a commonly accepted protocol for performing such assessment would be a valuable resource to expand the use of such approaches across different regulatory and industrial applications. However, a number of factors impede their widespread deployment including a lack of a comprehensive mechanistic understanding, limited in vitro testing approaches and limited in vivo databases suitable for modeling, a limited understanding of how to incorporate absorption, distribution, metabolism, and excretion (ADME) considerations into the overall process, a lack of in silico models designed to predict a safe dose and an accepted framework for organizing the key characteristics of these organ toxicants.
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Affiliation(s)
- Arianna Bassan
- Innovatune srl, Via Giulio Zanon 130/D, 35129 Padova, Italy
| | - Vinicius M. Alves
- The National Institute of Environmental Health Sciences, Division of the National Toxicology Program, Research Triangle Park, NC 27709, United States
| | - Alexander Amberg
- Sanofi, R&D Preclinical Safety Frankfurt, Industriepark Hoechst, D-65926 Frankfurt am Main, Germany
| | - Lennart T. Anger
- Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, United States
| | - Lisa Beilke
- Toxicology Solutions Inc., San Diego, CA, United States
| | - Andreas Bender
- AI and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United States
| | | | - Mark T.D. Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, L3 3AF, UK
| | - Jui-Hua Hsieh
- The National Institute of Environmental Health Sciences, Division of the National Toxicology Program, Research Triangle Park, NC 27709, United States
| | | | - Raymond Kemper
- Nuvalent, One Broadway, 14th floor, Cambridge, MA 02142, United States
| | - Moiz Mumtaz
- Agency for Toxic Substances and Disease Registry, US Department of Health and Human Services, Atlanta, GA, United States
| | - Louise Neilson
- Broughton Nicotine Services, Oak Tree House, West Craven Drive, Earby, Lancashire BB18 6JZ UK
| | - Manuela Pavan
- Innovatune srl, Via Giulio Zanon 130/D, 35129 Padova, Italy
| | - Amy Pointon
- Functional and Mechanistic Safety, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Julia Pletz
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, L3 3AF, UK
| | - Patricia Ruiz
- Agency for Toxic Substances and Disease Registry, US Department of Health and Human Services, Atlanta, GA, United States
| | - Daniel P. Russo
- The Rutgers Center for Computational and Integrative Biology, Camden, NJ 08102, United States
- Department of Chemistry, Rutgers University, Camden, NJ 08102, United States
| | - Yogesh Sabnis
- UCB Biopharma SRL, Chemin du Foriest, B-1420 Braine-l’Alleud, Belgium
| | - Reena Sandhu
- SafeDose Ltd., 20 Dundas Street West, Suite 921, Toronto, Ontario M5G2H1, Canada
| | - Markus Schaefer
- Sanofi, R&D Preclinical Safety Frankfurt, Industriepark Hoechst, D-65926 Frankfurt am Main, Germany
| | - Lidiya Stavitskaya
- US Food and Drug Administration, Center for Drug Evaluation and Research, Silver Spring, MD 20993, USA
| | | | | | - David Woolley
- ForthTox Limited, PO Box 13550, Linlithgow, EH49 7YU, UK
| | - Craig Zwickl
- Transendix LLC, 1407 Moores Manor, Indianapolis, IN 46229, United States
| | - Glenn J. Myatt
- Instem, 1393 Dublin Road, Columbus, OH 43215, United States
- Corresponding author: (G.J. Myatt)
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26
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Schneider MR, Oelgeschlaeger M, Burgdorf T, van Meer P, Theunissen P, Kienhuis AS, Piersma AH, Vandebriel RJ. Applicability of organ-on-chip systems in toxicology and pharmacology. Crit Rev Toxicol 2021; 51:540-554. [PMID: 34463591 DOI: 10.1080/10408444.2021.1953439] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Organ-on-chip (OoC) systems are microfabricated cell culture devices designed to model functional units of human organs by harboring an in vitro generated organ surrogate. In the present study, we reviewed issues and opportunities related to the application of OoC in the safety and efficacy assessment of chemicals and pharmaceuticals, as well as the steps needed to achieve this goal. The relative complexity of OoC over simple in vitro assays provides advantages and disadvantages in the context of compound testing. The broader biological domain of OoC potentially enhances their predictive value, whereas their complexity present issues with throughput, standardization and transferability. Using OoCs for regulatory purposes requires detailed and standardized protocols, providing reproducible results in an interlaboratory setting. The extent to which interlaboratory standardization of OoC is feasible and necessary for regulatory application is a matter of debate. The focus of applying OoCs in safety assessment is currently directed to characterization (the biology represented in the test) and qualification (the performance of the test). To this aim, OoCs are evaluated on a limited scale, especially in the pharmaceutical industry, with restricted sets of reference substances. Given the low throughput of OoC, it is questionable whether formal validation, in which many reference substances are extensively tested in different laboratories, is feasible for OoCs. Rather, initiatives such as open technology platforms, and collaboration between OoC developers and risk assessors may prove an expedient strategy to build confidence in OoCs for application in safety and efficacy assessment.
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Affiliation(s)
- Marlon R Schneider
- German Centre for the Protection of Laboratory Animals (Bf3R), German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Michael Oelgeschlaeger
- German Centre for the Protection of Laboratory Animals (Bf3R), German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Tanja Burgdorf
- German Centre for the Protection of Laboratory Animals (Bf3R), German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Peter van Meer
- Section on Pharmacology, Toxicology and Kinetics, Medicines Evaluation Board, Utrecht, The Netherlands.,Department of Pharmaceutics, Utrecht Institute of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Peter Theunissen
- Section on Pharmacology, Toxicology and Kinetics, Medicines Evaluation Board, Utrecht, The Netherlands
| | - Anne S Kienhuis
- Laboratory for Health Protection, National Institute of Public Health and the Environment, Bilthoven, The Netherlands
| | - Aldert H Piersma
- Laboratory for Health Protection, National Institute of Public Health and the Environment, Bilthoven, The Netherlands
| | - Rob J Vandebriel
- Laboratory for Health Protection, National Institute of Public Health and the Environment, Bilthoven, The Netherlands
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27
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Alvarez DA, Corsi SR, De Cicco LA, Villeneuve DL, Baldwin AK. Identifying Chemicals and Mixtures of Potential Biological Concern Detected in Passive Samplers from Great Lakes Tributaries Using High-Throughput Data and Biological Pathways. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2021; 40:2165-2182. [PMID: 34003517 PMCID: PMC8361951 DOI: 10.1002/etc.5118] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 02/09/2021] [Accepted: 05/12/2021] [Indexed: 05/24/2023]
Abstract
Waterborne contaminants were monitored in 69 tributaries of the Laurentian Great Lakes in 2010 and 2014 using semipermeable membrane devices (SPMDs) and polar organic chemical integrative samplers (POCIS). A risk-based screening approach was used to prioritize chemicals and chemical mixtures, identify sites at greatest risk for biological impacts, and identify potential hazards to monitor at those sites. Analyses included 185 chemicals (143 detected) including polycyclic aromatic hydrocarbons (PAHs), legacy and current-use pesticides, fire retardants, pharmaceuticals, and fragrances. Hazard quotients were calculated by dividing detected concentrations by biological effect concentrations reported in the ECOTOX Knowledgebase (toxicity quotients) or ToxCast database (exposure-activity ratios [EARs]). Mixture effects were estimated by summation of EAR values for chemicals that influence ToxCast assays with common gene targets. Nineteen chemicals-atrazine, N,N-diethyltoluamide, di(2-ethylhexyl)phthalate, dl-menthol, galaxolide, p-tert-octylphenol, 3 organochlorine pesticides, 3 PAHs, 4 pharmaceuticals, and 3 phosphate flame retardants-had toxicity quotients >0.1 or EARs for individual chemicals >10-3 at 10% or more of the sites monitored. An additional 4 chemicals (tributyl phosphate, triethyl citrate, benz[a]anthracene, and benzo[b]fluoranthene) were present in mixtures with EARs >10-3 . To evaluate potential apical effects and biological endpoints to monitor in exposed wildlife, in vitro bioactivity data were compared to adverse outcome pathway gene ontology information. Endpoints and effects associated with endocrine disruption, alterations in xenobiotic metabolism, and potentially neuronal development would be relevant to monitor at the priority sites. The EAR threshold exceedance for many chemical classes was correlated with urban land cover and wastewater effluent influence, whereas herbicides and fire retardants were also correlated to agricultural land cover. Environ Toxicol Chem 2021;40:2165-2182. Published 2021. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
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Affiliation(s)
- David A. Alvarez
- Columbia Environmental Research CenterUS Geological SurveyColumbiaMissouri
| | - Steven R. Corsi
- Upper Midwest Science CenterUS Geological SurveyMiddletonWisconsin
| | | | - Daniel L. Villeneuve
- Center for Computational Toxicology and Exposure, Great Lakes Toxicology and Ecology DivisionUS Environmental Protection AgencyDuluthMinnesota
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The 2021 update of the EPA's adverse outcome pathway database. Sci Data 2021; 8:169. [PMID: 34253739 PMCID: PMC8275694 DOI: 10.1038/s41597-021-00962-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 05/13/2021] [Indexed: 11/22/2022] Open
Abstract
The EPA developed the Adverse Outcome Pathway Database (AOP-DB) to better characterize adverse outcomes of toxicological interest that are relevant to human health and the environment. Here we present the most recent version of the EPA Adverse Outcome Pathway Database (AOP-DB), version 2. AOP-DB v.2 introduces several substantial updates, which include automated data pulls from the AOP-Wiki 2.0, the integration of tissue-gene network data, and human AOP-gene data by population, semantic mapping and SPARQL endpoint creation, in addition to the presentation of the first publicly available AOP-DB web user interface. Potential users of the data may investigate specific molecular targets of an AOP, the relation of those gene/protein targets to other AOPs, cross-species, pathway, or disease-AOP relationships, or frequencies of AOP-related functional variants in particular populations, for example. Version updates described herein help inform new testable hypotheses about the etiology and mechanisms underlying adverse outcomes of environmental and toxicological concern. Measurement(s) | adverse outcome pathway • gene interactions • Orthologous Gene • chemical gene interactions • molecular pathway • disease gene associations • SNP | Technology Type(s) | digital curation |
Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14737557
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Chauhan V, Wilkins RC, Beaton D, Sachana M, Delrue N, Yauk C, O’Brien J, Marchetti F, Halappanavar S, Boyd M, Villeneuve D, Barton-Maclaren TS, Meek B, Anghel C, Heghes C, Barber C, Perkins E, Leblanc J, Burtt J, Laakso H, Laurier D, Lazo T, Whelan M, Thomas R, Cool D. Bringing together scientific disciplines for collaborative undertakings: a vision for advancing the adverse outcome pathway framework. Int J Radiat Biol 2021; 97:431-441. [PMID: 33539251 PMCID: PMC10711570 DOI: 10.1080/09553002.2021.1884314] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 01/25/2021] [Accepted: 01/26/2021] [Indexed: 01/04/2023]
Abstract
BACKGROUND Decades of research to understand the impacts of various types of environmental occupational and medical stressors on human health have produced a vast amount of data across many scientific disciplines. Organizing these data in a meaningful way to support risk assessment has been a significant challenge. To address this and other challenges in modernizing chemical health risk assessment, the Organisation for Economic Cooperation and Development (OECD) formalized the adverse outcome pathway (AOP) framework, an approach to consolidate knowledge into measurable key events (KEs) at various levels of biological organisation causally linked to disease based on the weight of scientific evidence (http://oe.cd/aops). Currently, AOPs have been considered predominantly in chemical safety but are relevant to radiation. In this context, the Nuclear Energy Agency's (NEA's) High-Level Group on Low Dose Research (HLG-LDR) is working to improve research co-ordination, including radiological research with chemical research, identify synergies between the fields and to avoid duplication of efforts and resource investments. To this end, a virtual workshop was held on 7 and 8 October 2020 with experts from the OECD AOP Programme together with the radiation and chemical research/regulation communities. The workshop was a coordinated effort of Health Canada, the Electric Power Research Institute (EPRI), and the Nuclear Energy Agency (NEA). The AOP approach was discussed including key issues to fully embrace its value and catalyze implementation in areas of radiation risk assessment. CONCLUSIONS A joint chemical and radiological expert group was proposed as a means to encourage cooperation between risk assessors and an initial vision was discussed on a path forward. A global survey was suggested as a way to identify priority health outcomes of regulatory interest for AOP development. Multidisciplinary teams are needed to address the challenge of producing the appropriate data for risk assessments. Data management and machine learning tools were highlighted as a way to progress from weight of evidence to computational causal inference.
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Affiliation(s)
- Vinita Chauhan
- Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Ruth C. Wilkins
- Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | | | - Magdalini Sachana
- Environment Health and Safety Division, Environment Directorate, Organisation for Economic Co-operation and Development (OECD), Paris, France
| | - Nathalie Delrue
- Environment Health and Safety Division, Environment Directorate, Organisation for Economic Co-operation and Development (OECD), Paris, France
| | - Carole Yauk
- Department of Biology, University of Ottawa, Ottawa, Canada
| | - Jason O’Brien
- Ecotoxicology and Wildlife Health Division, Environment and Climate Change Canada, Ottawa, Canada
| | - Francesco Marchetti
- Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Sabina Halappanavar
- Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Michael Boyd
- U.S. Environmental Protection Agency, Office of Air and Radiation, Washington, DC, USA
| | - Daniel Villeneuve
- U.S. Environmental Protection Agency, Office of Research and Development, Duluth, MN, USA
| | | | - Bette Meek
- McLaughlin Centre, University of Ottawa, Ottawa, Canada
| | | | | | | | - Edward Perkins
- US Army Engineer Research and Development Center Jackson, Vicksburg, MS, USA
| | - Julie Leblanc
- Directorate of Environment and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Julie Burtt
- Directorate of Environment and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Holly Laakso
- Canadian Nuclear Laboratories, Chalk River, Canada
| | - Dominique Laurier
- Health and Environment Division, Institute for Radiological Protection and Nuclear Safety (IRSN), Fontenay-aux-Roses, France
| | - Ted Lazo
- Radiological Protection and Human Aspects of Nuclear Safety Division, OECD Nuclear Energy Agency, Paris, France
| | - Maurice Whelan
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Russell Thomas
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Donald Cool
- Electric Power Research Institute, Charlotte, NC, USA
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Sapounidou M, Ebbrell DJ, Bonnell MA, Campos B, Firman JW, Gutsell S, Hodges G, Roberts J, Cronin MTD. Development of an Enhanced Mechanistically Driven Mode of Action Classification Scheme for Adverse Effects on Environmental Species. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:1897-1907. [PMID: 33478211 DOI: 10.1021/acs.est.0c06551] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
This study developed a novel classification scheme to assign chemicals to a verifiable mechanism of (eco-)toxicological action to allow for grouping, read-across, and in silico model generation. The new classification scheme unifies and extends existing schemes and has, at its heart, direct reference to molecular initiating events (MIEs) promoting adverse outcomes. The scheme is based on three broad domains of toxic action representing nonspecific toxicity (e.g., narcosis), reactive mechanisms (e.g., electrophilicity and free radical action), and specific mechanisms (e.g., associated with enzyme inhibition). The scheme is organized at three further levels of detail beyond broad domains to separate out the mechanistic group, specific mechanism, and the MIEs responsible. The novelty of this approach comes from the reference to taxonomic diversity within the classification, transparency, quality of supporting evidence relating to MIEs, and that it can be updated readily.
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Affiliation(s)
- Maria Sapounidou
- School of Pharmacy and Bimolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, U.K
| | - David J Ebbrell
- School of Pharmacy and Bimolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, U.K
| | - Mark A Bonnell
- Science and Risk Assessment Directorate, Environment & Climate Change Canada, 351 St. Joseph Blvd, Gatineau, Quebec K1A 0H3, Canada
| | - Bruno Campos
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - James W Firman
- School of Pharmacy and Bimolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, U.K
| | - Steve Gutsell
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Geoff Hodges
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Jayne Roberts
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Mark T D Cronin
- School of Pharmacy and Bimolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, U.K
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Chauhan V, Villeneuve D, Cool D. Collaborative efforts are needed among the scientific community to advance the adverse outcome pathway concept in areas of radiation risk assessment. Int J Radiat Biol 2021; 97:815-823. [PMID: 33253609 PMCID: PMC8312481 DOI: 10.1080/09553002.2020.1857456] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 11/05/2020] [Accepted: 11/23/2020] [Indexed: 12/21/2022]
Abstract
Disease prevention and prediction have led to the generation of phenotypically based methods for deriving the limits of safety across toxicological disciplines. In the ionizing radiation field, human data has formed the basis of the linear-no-threshold (LNT) model for risk estimates. However, uncertainties around its accuracy at low doses and low dose-rates have led to passionate debates on its effectiveness to derive radiation risk estimates under these conditions. Concerns arise from the linear extrapolation of data from high doses to low doses, below 0.1 Gy where there is considerable variability in the scientific literature. Efforts to address these controversies have led to a mountain of mechanistic data to improve the understanding of molecular and cellular effects related to phenotypic changes. These data provide fragments of information that have yet to be combined and used effectively to improve modeling, reduce uncertainties, and update radiation protection approaches. This paper suggests a better consolidation of mechanistic research may serve to guide priority research and facilitate translation to risk assessment. An effective approach that may be implemented is the organization of data using the adverse outcome pathway (AOP) framework, a programme that has been launched by the Organization for Economic Cooperation and Development in the chemical toxicology field. The AOP concept has proved beneficial to human health and ecological toxicological fields, demonstrating possibilities for better linkages of mechanistic data to phenotypic effects. A similar approach may be beneficial to the field of radiation research. However, for this to work effectively, collaborative efforts are needed among the scientific communities in the area of AOP development and documentation. Studies will need to be evaluated, re-organized and integrated into AOPs. Here, details of the AOP approach and areas it could support in the radiation field are discussed. In addition, challenges are highlighted and steps to integration are outlined. Organizing studies in this manner will facilitate a better understanding of our current knowledge in the radiation field and help identify areas where more focused work can be undertaken. This will, in turn, allow for improved linkage of mechanistic data to human relevance and better support radiation risk assessments.
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Affiliation(s)
- Vinita Chauhan
- Environmental Health Science Research Bureau, Health Canada, Ottawa, ON, Canada
| | - Daniel Villeneuve
- U.S. Environmental Protection Agency, Center for Computational Toxicology and Exposure, Great Lakes Toxicology and Ecology Division, Duluth, MN 55804, USA
| | - Donald Cool
- Electric Power Research Institute, Charlotte, NC, US
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Wang MWH, Goodman JM, Allen TEH. Machine Learning in Predictive Toxicology: Recent Applications and Future Directions for Classification Models. Chem Res Toxicol 2020; 34:217-239. [PMID: 33356168 DOI: 10.1021/acs.chemrestox.0c00316] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
In recent times, machine learning has become increasingly prominent in predictive toxicology as it has shifted from in vivo studies toward in silico studies. Currently, in vitro methods together with other computational methods such as quantitative structure-activity relationship modeling and absorption, distribution, metabolism, and excretion calculations are being used. An overview of machine learning and its applications in predictive toxicology is presented here, including support vector machines (SVMs), random forest (RF) and decision trees (DTs), neural networks, regression models, naïve Bayes, k-nearest neighbors, and ensemble learning. The recent successes of these machine learning methods in predictive toxicology are summarized, and a comparison of some models used in predictive toxicology is presented. In predictive toxicology, SVMs, RF, and DTs are the dominant machine learning methods due to the characteristics of the data available. Lastly, this review describes the current challenges facing the use of machine learning in predictive toxicology and offers insights into the possible areas of improvement in the field.
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Affiliation(s)
- Marcus W H Wang
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - Jonathan M Goodman
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - Timothy E H Allen
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom.,MRC Toxicology Unit, University of Cambridge, Hodgkin Building, Lancaster Road, Leicester LE1 7HB, United Kingdom
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Ghulam A, Lei X, Guo M, Bian C. A Review of Pathway Databases and Related Methods Analysis. Curr Bioinform 2020. [DOI: 10.2174/1574893614666191018162505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Pathway analysis integrates most of the computational tools for the investigation of
high-level and complex human diseases. In the field of bioinformatics research, biological pathways
analysis is an important part of systems biology. The molecular complexities of biological
pathways are difficult to understand in human diseases, which can be explored through pathway
analysis. In this review, we describe essential information related to pathway databases and their
mechanisms, algorithms and methods. In the pathway database analysis, we present a brief introduction
on how to gain knowledge from fundamental pathway data in regard to specific human
pathways and how to use pathway databases and pathway analysis to predict diseases during an
experiment. We also provide detailed information related to computational tools that are used in
complex pathway data analysis, the roles of these tools in the bioinformatics field and how to store
the pathway data. We illustrate various methodological difficulties that are faced during pathway
analysis. The main ideas and techniques for the pathway-based examination approaches are presented.
We provide the list of pathway databases and analytical tools. This review will serve as a
helpful manual for pathway analysis databases.
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Affiliation(s)
- Ali Ghulam
- School of Computer Science, Shaanxi Normal University, Xian, China
| | - Xiujuan Lei
- School of Computer Science, Shaanxi Normal University, Xian, China
| | - Min Guo
- School of Computer Science, Shaanxi Normal University, Xian, China
| | - Chen Bian
- School of Computer Science, Shaanxi Normal University, Xian, China
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Taboureau O, El M'Selmi W, Audouze K. Integrative systems toxicology to predict human biological systems affected by exposure to environmental chemicals. Toxicol Appl Pharmacol 2020; 405:115210. [DOI: 10.1016/j.taap.2020.115210] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 07/01/2020] [Accepted: 08/20/2020] [Indexed: 12/20/2022]
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Muratov EN, Bajorath J, Sheridan RP, Tetko IV, Filimonov D, Poroikov V, Oprea TI, Baskin II, Varnek A, Roitberg A, Isayev O, Curtarolo S, Fourches D, Cohen Y, Aspuru-Guzik A, Winkler DA, Agrafiotis D, Cherkasov A, Tropsha A. QSAR without borders. Chem Soc Rev 2020; 49:3525-3564. [PMID: 32356548 PMCID: PMC8008490 DOI: 10.1039/d0cs00098a] [Citation(s) in RCA: 305] [Impact Index Per Article: 76.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Prediction of chemical bioactivity and physical properties has been one of the most important applications of statistical and more recently, machine learning and artificial intelligence methods in chemical sciences. This field of research, broadly known as quantitative structure-activity relationships (QSAR) modeling, has developed many important algorithms and has found a broad range of applications in physical organic and medicinal chemistry in the past 55+ years. This Perspective summarizes recent technological advances in QSAR modeling but it also highlights the applicability of algorithms, modeling methods, and validation practices developed in QSAR to a wide range of research areas outside of traditional QSAR boundaries including synthesis planning, nanotechnology, materials science, biomaterials, and clinical informatics. As modern research methods generate rapidly increasing amounts of data, the knowledge of robust data-driven modelling methods professed within the QSAR field can become essential for scientists working both within and outside of chemical research. We hope that this contribution highlighting the generalizable components of QSAR modeling will serve to address this challenge.
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Affiliation(s)
- Eugene N Muratov
- UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
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Spinu N, Cronin MTD, Enoch SJ, Madden JC, Worth AP. Quantitative adverse outcome pathway (qAOP) models for toxicity prediction. Arch Toxicol 2020; 94:1497-1510. [PMID: 32424443 PMCID: PMC7261727 DOI: 10.1007/s00204-020-02774-7] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 05/04/2020] [Indexed: 01/06/2023]
Abstract
The quantitative adverse outcome pathway (qAOP) concept is gaining interest due to its potential regulatory applications in chemical risk assessment. Even though an increasing number of qAOP models are being proposed as computational predictive tools, there is no framework to guide their development and assessment. As such, the objectives of this review were to: (i) analyse the definitions of qAOPs published in the scientific literature, (ii) define a set of common features of existing qAOP models derived from the published definitions, and (iii) identify and assess the existing published qAOP models and associated software tools. As a result, five probabilistic qAOPs and ten mechanistic qAOPs were evaluated against the common features. The review offers an overview of how the qAOP concept has advanced and how it can aid toxicity assessment in the future. Further efforts are required to achieve validation, harmonisation and regulatory acceptance of qAOP models.
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Affiliation(s)
- Nicoleta Spinu
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK
| | - Mark T D Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK
| | - Steven J Enoch
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK
| | - Judith C Madden
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK
| | - Andrew P Worth
- European Commission, Joint Research Centre (JRC), Ispra, Italy.
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Modernization of chemical risk assessment to make use of novel toxicological data. Toxicol Appl Pharmacol 2020; 394:114951. [DOI: 10.1016/j.taap.2020.114951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Corsi SR, De Cicco LA, Villeneuve DL, Blackwell BR, Fay KA, Ankley GT, Baldwin AK. Prioritizing chemicals of ecological concern in Great Lakes tributaries using high-throughput screening data and adverse outcome pathways. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 686:995-1009. [PMID: 31412529 DOI: 10.1016/j.scitotenv.2019.05.457] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 05/28/2019] [Accepted: 05/30/2019] [Indexed: 04/15/2023]
Abstract
Chemical monitoring data were collected in surface waters from 57 Great Lakes tributaries from 2010 to 13 to identify chemicals of potential biological relevance and sites at which these chemicals occur. Traditional water-quality benchmarks for aquatic life based on in vivo toxicity data were available for 34 of 67 evaluated chemicals. To expand evaluation of potential biological effects, measured chemical concentrations were compared to chemical-specific biological activities determined in high-throughput (ToxCast) in vitro assays. Resulting exposure-activity ratios (EARs) were used to prioritize the chemicals of greatest potential concern: 4‑nonylphenol, bisphenol A, metolachlor, atrazine, DEET, caffeine, tris(2‑butoxyethyl) phosphate, tributyl phosphate, triphenyl phosphate, benzo(a)pyrene, fluoranthene, and benzophenone. Water-quality benchmarks were unavailable for five of these chemicals, but for the remaining seven, EAR-based prioritization was consistent with that based on toxicity quotients calculated from benchmarks. Water-quality benchmarks identified three additional PAHs (anthracene, phenanthrene, and pyrene) not prioritized using EARs. Through this analysis, an EAR of 10-3 was identified as a reasonable threshold above which a chemical might be of potential concern. To better understand apical hazards potentially associated with biological activities captured in ToxCast assays, in vitro bioactivity data were matched with available adverse outcome pathway (AOP) information. The 49 ToxCast assays prioritized via EAR analysis aligned with 23 potentially-relevant AOPs present in the AOP-Wiki. Mixture effects at monitored sites were estimated by summation of EAR values for multiple chemicals by individual assay or individual AOP. Commonly predicted adverse outcomes included impacts on reproduction and mitochondrial function. The EAR approach provided a screening-level assessment for evidence-based prioritization of chemicals and sites with potential for adverse biological effects. The approach aids prioritization of future monitoring activities and provides testable hypotheses to help focus those efforts. This also expands the fraction of detected chemicals for which biologically-based benchmark concentrations are available to help contextualize chemical monitoring results.
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Affiliation(s)
- Steven R Corsi
- U.S. Geological Survey, Middleton, WI 53562, United States.
| | | | - Daniel L Villeneuve
- U.S. Environmental Protection Agency, Office of Research and Development, Duluth, MN 55804, United States
| | - Brett R Blackwell
- U.S. Environmental Protection Agency, Office of Research and Development, Duluth, MN 55804, United States
| | - Kellie A Fay
- General Dynamics Information Technology, Duluth, MN 55804, United States
| | - Gerald T Ankley
- U.S. Environmental Protection Agency, Office of Research and Development, Duluth, MN 55804, United States
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Watford S, Edwards S, Angrish M, Judson RS, Paul Friedman K. Progress in data interoperability to support computational toxicology and chemical safety evaluation. Toxicol Appl Pharmacol 2019; 380:114707. [PMID: 31404555 PMCID: PMC7705611 DOI: 10.1016/j.taap.2019.114707] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 07/29/2019] [Accepted: 08/06/2019] [Indexed: 12/20/2022]
Abstract
New approach methodologies (NAMs) in chemical safety evaluation are being explored to address the current public health implications of human environmental exposures to chemicals with limited or no data for assessment. For over a decade since a push toward "Toxicity Testing in the 21st Century," the field has focused on massive data generation efforts to inform computational approaches for preliminary hazard identification, adverse outcome pathways that link molecular initiating events and key events to apical outcomes, and high-throughput approaches to risk-based ratios of bioactivity and exposure to inform relative priority and safety assessment. Projects like the interagency Tox21 program and the US EPA ToxCast program have generated dose-response information on thousands of chemicals, identified and aggregated information from legacy systems, and created tools for access and analysis. The resulting information has been used to develop computational models as viable options for regulatory applications. This progress has introduced challenges in data management that are new, but not unique, to toxicology. Some of the key questions require critical thinking and solutions to promote semantic interoperability, including: (1) identification of bioactivity information from NAMs that might be related to a biological process; (2) identification of legacy hazard information that might be related to a key event or apical outcomes of interest; and, (3) integration of these NAM and traditional data for computational modeling and prediction of complex apical outcomes such as carcinogenesis. This work reviews a number of toxicology-related efforts specifically related to bioactivity and toxicological data interoperability based on the goals established by Findable, Accessible, Interoperable, and Reusable (FAIR) Data Principles. These efforts are essential to enable better integration of NAM and traditional toxicology information to support data-driven toxicology applications.
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Affiliation(s)
- Sean Watford
- Booz Allen Hamilton, Rockville, MD 20852, USA; National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Stephen Edwards
- Research Triangle Institute International, Research Triangle Park, NC 27709, USA
| | - Michelle Angrish
- National Center for Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Richard S Judson
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Katie Paul Friedman
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
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Corton JC, Kleinstreuer NC, Judson RS. Identification of potential endocrine disrupting chemicals using gene expression biomarkers. Toxicol Appl Pharmacol 2019; 380:114683. [DOI: 10.1016/j.taap.2019.114683] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Revised: 07/05/2019] [Accepted: 07/15/2019] [Indexed: 02/07/2023]
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Hill T, Conolly RB. Development of a Novel AOP for Cyp2F2-Mediated Lung Cancer in Mice. Toxicol Sci 2019; 172:1-10. [PMID: 31407013 DOI: 10.1093/toxsci/kfz185] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 06/26/2019] [Accepted: 08/07/2019] [Indexed: 12/14/2022] Open
Abstract
Abstract
Traditional methods for carcinogenicity testing rely heavily on the rodent bioassay as the standard for identification of tumorigenic risk. As such, identification of species-specific outcomes and/or metabolism are a frequent argument for regulatory exemption. One example is the association of tumor formation in the mouse lung after exposure to Cyp2F2 ligands. The adverse outcome pathway (AOP) framework offers a theoretical platform to address issues of species specificity that is consistent, transparent, and capable of integrating data from new approach methodologies as well as traditional data streams. A central premise of the AOP concept is that pathway progression from the molecular initiating event (MIE) implies a definable “response-response” (R-R) relationship between each key event (KE) that drives the pathway towards a specific adverse outcome (AO). This article describes an AOP for lung cancer in the mouse from an MIE of Cyp2F2-specific reactive metabolite formation, advancing through KE that include protein and/or nucleic acid adducts, diminished Club Cell 10 kDa (CC10) protein expression, hyperplasia of CC10 deficient Club cells, and culminating in the AO of mixed-cell tumor formation in the distal airways. This tumor formation is independent of route of exposure and our AOP construct is based on overlapping mechanistic events for naphthalene, styrene, ethyl benzene, isoniazid, and fluensulfone in the mouse. This AOP is intended to accelerate the explication of an apparent mouse-specific outcome and serve as a starting point for a quantitative analysis of mouse-human differences in susceptibility to the tumorigenic effects of Cyp2F2 ligands.
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Affiliation(s)
- Thomas Hill
- Oak Ridge Institute for Science and Education Fellow at the National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709
| | - Rory B Conolly
- National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709
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Davis AP, Wiegers J, Wiegers TC, Mattingly CJ. Public data sources to support systems toxicology applications. CURRENT OPINION IN TOXICOLOGY 2019; 16:17-24. [PMID: 33604492 PMCID: PMC7889036 DOI: 10.1016/j.cotox.2019.03.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Public databases provide a wealth of freely available information about chemicals, genes, proteins, biological networks, phenotypes, diseases, and exposure science that can be integrated to construct pathways for systems toxicology applications. Relating this disparate information from public repositories, however, can be challenging since databases use a variety of ways to represent, describe, and make available their content. The use of standard vocabularies to annotate key data concepts, however, allows the information to be more easily exchanged and combined for discovery of new findings. We explore some of the many public data sources currently available to support systems toxicology, and demonstrate the value of standardizing data to help construct chemical-induced outcome pathways.
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Affiliation(s)
- Allan Peter Davis
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Jolene Wiegers
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Thomas C Wiegers
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Carolyn J Mattingly
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, United States
- Center for Human Health and the Environment, North Carolina State University, Raleigh, North Carolina 27695, United States
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Balik-Meisner MR, Mav D, Phadke DP, Everett LJ, Shah RR, Tal T, Shepard PJ, Merrick BA, Paules RS. Development of a Zebrafish S1500+ Sentinel Gene Set for High-Throughput Transcriptomics. Zebrafish 2019; 16:331-347. [PMID: 31188086 PMCID: PMC6685209 DOI: 10.1089/zeb.2018.1720] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Sentinel gene sets have been developed with the purpose of maximizing the information from targeted transcriptomic platforms. We recently described the development of an S1500+ sentinel gene set, which was built for the human transcriptome, utilizing a data- and knowledge-driven hybrid approach to select a small subset of genes that optimally capture transcriptional diversity, correlation with other genes based on large-scale expression profiling, and known pathway annotation within the human genome. While this detailed bioinformatics approach for gene selection can in principle be applied to other species, the reliability of the resulting gene set depends on availability of a large body of transcriptomics data. For the model organism zebrafish, we aimed to create a similar sentinel gene set (Zf S1500+ gene set); however, there is insufficient standardized expression data in the public domain to train the gene correlation model. Therefore, our strategy was to use human-zebrafish ortholog mapping of the human S1500+ genes and nominations from experts in the zebrafish scientific community. In this study, we present the bioinformatics curation and refinement process to produce the final Zf S1500+ gene set, explore whole transcriptome extrapolation using this gene set, and assess pathway-level inference. This gene set will add value to targeted high-throughput transcriptomics in zebrafish for toxicogenomic screening and other research domains.
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Affiliation(s)
| | - Deepak Mav
- 1Sciome, LLC, Research Triangle Park, North Carolina
| | | | | | - Ruchir R Shah
- 1Sciome, LLC, Research Triangle Park, North Carolina
| | - Tamara Tal
- 2National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
| | | | - B Alex Merrick
- 4Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina
| | - Richard S Paules
- 4Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina
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Piersma AH, van Benthem J, Ezendam J, Staal YCM, Kienhuis AS. The virtual human in chemical safety assessment. CURRENT OPINION IN TOXICOLOGY 2019. [DOI: 10.1016/j.cotox.2019.03.009] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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45
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Aguayo-Orozco A, Taboureau O, Brunak S. The use of systems biology in chemical risk assessment. CURRENT OPINION IN TOXICOLOGY 2019. [DOI: 10.1016/j.cotox.2019.03.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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Pollesch NL, Villeneuve DL, O’Brien JM. Extracting and Benchmarking Emerging Adverse Outcome Pathway Knowledge. Toxicol Sci 2019; 168:349-364. [PMID: 30715536 PMCID: PMC10545168 DOI: 10.1093/toxsci/kfz006] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023] Open
Abstract
As the community of toxicological researchers, risk assessors, and risk managers adopt the adverse outcome pathway (AOP) framework for organizing toxicological knowledge, the number and diversity of AOPs in the online AOP knowledgebase (KB) continues to grow. To track and investigate this growth, AOPs in the AOP-KB were assembled into a single network. Summary measures on the current state of the AOP-KB and the overall connectivity and structural features of the resulting network were calculated. Our results show that networking the 187 user-defined AOPs currently described in the AOP-KB resulted in the emergence of 9405 unique, previously undescribed, linear AOPs (LAOPs). To investigate patterns in this emerging knowledge, we assembled the AOP-KB network retrospectively by sequentially adding each of the 187 user-defined AOPs and found that the creation of new AOPs that borrowed components from previously existing AOPs in the KB most described emergence of new LAOPs. However, the introduction of nonadjacent key event relationships and cycles among KEs also play key roles in emergent LAOPs. We provide examples of how to identify application-specific critical paths from this large number of LAOPs. Our research shows that the global AOP network may have considerable value as a source of emergent toxicological knowledge. These findings are not only helpful for understanding the nature of this emergent information but can also be used to manage and guide future development of the AOP-KB, and how to tailor this wealth of information to specific applications.
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Affiliation(s)
- Nathan L. Pollesch
- United States Environmental Protection Agency, Mid-Continent Ecology Division, Duluth, MN, USA 55804
| | - Daniel L. Villeneuve
- United States Environmental Protection Agency, Mid-Continent Ecology Division, Duluth, MN, USA 55804
| | - Jason M. O’Brien
- Environment and Climate Change Canada, Ecotoxicology and Wildlife Health Division, Ottawa, ON, Canada
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Rao MS, Van Vleet TR, Ciurlionis R, Buck WR, Mittelstadt SW, Blomme EAG, Liguori MJ. Comparison of RNA-Seq and Microarray Gene Expression Platforms for the Toxicogenomic Evaluation of Liver From Short-Term Rat Toxicity Studies. Front Genet 2019; 9:636. [PMID: 30723492 PMCID: PMC6349826 DOI: 10.3389/fgene.2018.00636] [Citation(s) in RCA: 116] [Impact Index Per Article: 23.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Accepted: 11/27/2018] [Indexed: 12/12/2022] Open
Abstract
Gene expression profiling is a useful tool to predict and interrogate mechanisms of toxicity. RNA-Seq technology has emerged as an attractive alternative to traditional microarray platforms for conducting transcriptional profiling. The objective of this work was to compare both transcriptomic platforms to determine whether RNA-Seq offered significant advantages over microarrays for toxicogenomic studies. RNA samples from the livers of rats treated for 5 days with five tool hepatotoxicants (α-naphthylisothiocyanate/ANIT, carbon tetrachloride/CCl4, methylenedianiline/MDA, acetaminophen/APAP, and diclofenac/DCLF) were analyzed with both gene expression platforms (RNA-Seq and microarray). Data were compared to determine any potential added scientific (i.e., better biological or toxicological insight) value offered by RNA-Seq compared to microarrays. RNA-Seq identified more differentially expressed protein-coding genes and provided a wider quantitative range of expression level changes when compared to microarrays. Both platforms identified a larger number of differentially expressed genes (DEGs) in livers of rats treated with ANIT, MDA, and CCl4 compared to APAP and DCLF, in agreement with the severity of histopathological findings. Approximately 78% of DEGs identified with microarrays overlapped with RNA-Seq data, with a Spearman’s correlation of 0.7 to 0.83. Consistent with the mechanisms of toxicity of ANIT, APAP, MDA and CCl4, both platforms identified dysregulation of liver relevant pathways such as Nrf2, cholesterol biosynthesis, eiF2, hepatic cholestasis, glutathione and LPS/IL-1 mediated RXR inhibition. RNA-Seq data showed additional DEGs that not only significantly enriched these pathways, but also suggested modulation of additional liver relevant pathways. In addition, RNA-Seq enabled the identification of non-coding DEGs that offer a potential for improved mechanistic clarity. Overall, these results indicate that RNA-Seq is an acceptable alternative platform to microarrays for rat toxicogenomic studies with several advantages. Because of its wider dynamic range as well as its ability to identify a larger number of DEGs, RNA-Seq may generate more insight into mechanisms of toxicity. However, more extensive reference data will be necessary to fully leverage these additional RNA-Seq data, especially for non-coding sequences.
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Affiliation(s)
- Mohan S Rao
- Investigative Toxicology and Pathology, Global Preclinical Safety, AbbVie, North Chicago, IL, United States
| | - Terry R Van Vleet
- Investigative Toxicology and Pathology, Global Preclinical Safety, AbbVie, North Chicago, IL, United States
| | - Rita Ciurlionis
- Investigative Toxicology and Pathology, Global Preclinical Safety, AbbVie, North Chicago, IL, United States
| | - Wayne R Buck
- Investigative Toxicology and Pathology, Global Preclinical Safety, AbbVie, North Chicago, IL, United States
| | - Scott W Mittelstadt
- Investigative Toxicology and Pathology, Global Preclinical Safety, AbbVie, North Chicago, IL, United States
| | - Eric A G Blomme
- Investigative Toxicology and Pathology, Global Preclinical Safety, AbbVie, North Chicago, IL, United States
| | - Michael J Liguori
- Investigative Toxicology and Pathology, Global Preclinical Safety, AbbVie, North Chicago, IL, United States
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Darden L, Kundu K, Pal LR, Moult J. Harnessing formal concepts of biological mechanism to analyze human disease. PLoS Comput Biol 2018; 14:e1006540. [PMID: 30586388 PMCID: PMC6306204 DOI: 10.1371/journal.pcbi.1006540] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Mechanism is a widely used concept in biology. In 2017, more than 10% of PubMed abstracts used the term. Therefore, searching for and reasoning about mechanisms is fundamental to much of biomedical research, but until now there has been almost no computational infrastructure for this purpose. Recent work in the philosophy of science has explored the central role that the search for mechanistic accounts of biological phenomena plays in biomedical research, providing a conceptual basis for representing and analyzing biological mechanism. The foundational categories for components of mechanisms—entities and activities—guide the development of general, abstract types of biological mechanism parts. Building on that analysis, we have developed a formal framework for describing and representing biological mechanism, MecCog, and applied it to describing mechanisms underlying human genetic disease. Mechanisms are depicted using a graphical notation. Key features are assignment of mechanism components to stages of biological organization and classes; visual representation of uncertainty, ignorance, and ambiguity; and tight integration with literature sources. The MecCog framework facilitates analysis of many aspects of disease mechanism, including the prioritization of future experiments, probing of gene−drug and gene−environment interactions, identification of possible new drug targets, personalized drug choice, analysis of nonlinear interactions between relevant genetic loci, and classification of diseases based on mechanism.
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Affiliation(s)
- Lindley Darden
- Department of Philosophy, University of Maryland College Park, College Park, Maryland, United States of America
| | - Kunal Kundu
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland, United States of America
- Computational Biology, Bioinformatics and Genomics, Biological Sciences Graduate Program, University of Maryland College Park, College Park, Maryland, United States of America
| | - Lipika R. Pal
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland, United States of America
| | - John Moult
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland, United States of America
- Department of Cell Biology and Molecular Genetics, University of Maryland College Park, College Park, Maryland, United States of America
- * E-mail:
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49
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Martens M, Verbruggen T, Nymark P, Grafström R, Burgoon LD, Aladjov H, Torres Andón F, Evelo CT, Willighagen EL. Introducing WikiPathways as a Data-Source to Support Adverse Outcome Pathways for Regulatory Risk Assessment of Chemicals and Nanomaterials. Front Genet 2018; 9:661. [PMID: 30622555 PMCID: PMC6308971 DOI: 10.3389/fgene.2018.00661] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2018] [Accepted: 12/04/2018] [Indexed: 01/18/2023] Open
Abstract
A paradigm shift is taking place in risk assessment to replace animal models, reduce the number of economic resources, and refine the methodologies to test the growing number of chemicals and nanomaterials. Therefore, approaches such as transcriptomics, proteomics, and metabolomics have become valuable tools in toxicological research, and are finding their way into regulatory toxicity. One promising framework to bridge the gap between the molecular-level measurements and risk assessment is the concept of adverse outcome pathways (AOPs). These pathways comprise mechanistic knowledge and connect biological events from a molecular level toward an adverse effect outcome after exposure to a chemical. However, the implementation of omics-based approaches in the AOPs and their acceptance by the risk assessment community is still a challenge. Because the existing modules in the main repository for AOPs, the AOP Knowledge Base (AOP-KB), do not currently allow the integration of omics technologies, additional tools are required for omics-based data analysis and visualization. Here we show how WikiPathways can serve as a supportive tool to make omics data interoperable with the AOP-Wiki, part of the AOP-KB. Manual matching of key events (KEs) indicated that 67% could be linked with molecular pathways. Automatic connection through linkage of identifiers between the databases showed that only 30% of AOP-Wiki chemicals were found on WikiPathways. More loose linkage through gene names in KE and Key Event Relationships descriptions gave an overlap of 70 and 71%, respectively. This shows many opportunities to create more direct connections, for example with extended ontology annotations, improving its interoperability. This interoperability allows the needed integration of omics data linked to the molecular pathways with AOPs. A new AOP Portal on WikiPathways is presented to allow the community of AOP developers to collaborate and populate the molecular pathways that underlie the KEs of AOP-Wiki. We conclude that the integration of WikiPathways and AOP-Wiki will improve risk assessment because omics data will be linked directly to KEs and therefore allow the comprehensive understanding and description of AOPs. To make this assessment reproducible and valid, major changes are needed in both WikiPathways and AOP-Wiki.
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Affiliation(s)
- Marvin Martens
- Department of Bioinformatics – BiGCaT, NUTRIM, Maastricht University, Maastricht, Netherlands
| | - Tim Verbruggen
- Department of Bioinformatics – BiGCaT, NUTRIM, Maastricht University, Maastricht, Netherlands
| | - Penny Nymark
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Toxicology, Misvik Biology, Turku, Finland
| | - Roland Grafström
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Toxicology, Misvik Biology, Turku, Finland
| | - Lyle D. Burgoon
- U.S. Army Engineer Research and Development Center, Vicksburg, MS, United States
| | - Hristo Aladjov
- Organisation for Economic Co-operation and Development Environment Directorate, Paris, France
| | - Fernando Torres Andón
- Laboratory of Cellular Immunology, Humanitas Clinical and Research Institute, Rozzano, Italy
- Center for Research in Molecular Medicine and Chronic Diseases, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Chris T. Evelo
- Department of Bioinformatics – BiGCaT, NUTRIM, Maastricht University, Maastricht, Netherlands
- Maastricht Centre for Systems Biology, Maastricht University, Maastricht, Netherlands
| | - Egon L. Willighagen
- Department of Bioinformatics – BiGCaT, NUTRIM, Maastricht University, Maastricht, Netherlands
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50
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Leveraging human genetic and adverse outcome pathway (AOP) data to inform susceptibility in human health risk assessment. Mamm Genome 2018; 29:190-204. [DOI: 10.1007/s00335-018-9738-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Accepted: 01/31/2018] [Indexed: 12/19/2022]
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