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Dovolou E, Nanas I, Giannoulis T, Fytsilli A, Ntemka A, Anifandis G, Tsakmakidis I, Amiridis GS. The effects of a glyphosate-based herbicide on the bovine gametes during an in vitro embryo production model. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 350:123967. [PMID: 38631452 DOI: 10.1016/j.envpol.2024.123967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 03/19/2024] [Accepted: 04/10/2024] [Indexed: 04/19/2024]
Abstract
Roundup® (R), while it is the most used herbicide globally, and its residues are ubiquitous in urban and suburban areas, its impact on vertebrates' safety remains highly debated. Here, in three in vitro experiments, we investigated the effects of a very low dose (1 ppm) of R on the fertilization capacity and embryo development in cattle. In the first experiment, frozen-thawed bull semen exposed to R for 1 h exhibited reduced motility parameters but unaffected fertilization ability. However, after in vitro fertilization, the rates of embryo formation were significantly lower compared to the untreated controls. In the second experiment, oocytes exposed to R during in vitro maturation showed reduced cleavage rates, and the embryo yield on days 7, 8, and 9 of embryo culture was significantly lower than that of the controls. In the third experiment, oocytes were matured in the presence of R and in a medium containing both R and Zinc, chosen to offer antioxidant protection to the oocytes. Day-7 blastocysts were analyzed for the expression of genes associated with oxidative stress, apoptosis, and epigenetic reprogramming. Exposure to R markedly suppressed embryo formation rates compared to the controls. The combination of R with Zinc restored the blastocyst yield, which on days 8 and 9 was comparable to that of the controls and higher than the groups exposed only to R on all days. The gene expression analysis revealed that R promotes oxidative stress development, triggers apoptosis, and induces epigenetic changes in developing embryos, while zinc presence alleviates these adverse effects of R. These findings imply that even at very low doses, R could be highly toxic, leading to functional abnormalities in both gametes, potentially affecting fertility in both genders.
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Affiliation(s)
- E Dovolou
- Department of Animal Science, University of Thessaly, Larissa, Greece.
| | - I Nanas
- Department of Obstetrics & Reproduction, Faculty of Veterinary Science, University of Thessaly, Karditsa, Greece
| | - T Giannoulis
- Department of Animal Science, University of Thessaly, Larissa, Greece
| | - A Fytsilli
- Department of Biochemistry & Biotechnology, Laboratory of Genetics, Comparative and Evolutionary Biology, Larissa, Greece
| | - A Ntemka
- Department of Animal Science, University of Thessaly, Larissa, Greece; Clinic of Farm Animals, Faculty of Veterinary Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - G Anifandis
- Department of Obstetrics and Gynaecology, ART Unit, Faculty of Medicine, University of Thessaly, Larissa, Greece
| | - I Tsakmakidis
- Clinic of Farm Animals, Faculty of Veterinary Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - G S Amiridis
- Department of Obstetrics & Reproduction, Faculty of Veterinary Science, University of Thessaly, Karditsa, Greece
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Chiu WA. Invited Perspective: Uneven Progress Addressing Population Variability in Human Health Risk Assessment. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:31305. [PMID: 38498339 PMCID: PMC10947099 DOI: 10.1289/ehp13461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 08/03/2023] [Accepted: 02/06/2024] [Indexed: 03/20/2024]
Affiliation(s)
- Weihsueh A. Chiu
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas, USA
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas, USA
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3
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Lu EH, Grimm FA, Rusyn I, De Saeger S, De Boevre M, Chiu WA. Advancing probabilistic risk assessment by integrating human biomonitoring, new approach methods, and Bayesian modeling: A case study with the mycotoxin deoxynivalenol. ENVIRONMENT INTERNATIONAL 2023; 182:108326. [PMID: 38000237 PMCID: PMC10898272 DOI: 10.1016/j.envint.2023.108326] [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: 06/12/2023] [Revised: 10/17/2023] [Accepted: 11/11/2023] [Indexed: 11/26/2023]
Abstract
Deoxynivalenol (DON) is a mycotoxin frequently observed in cereals and cereal-based foods, with reported toxicological effects including reduced body weight, immunotoxicity and reproductive defects. The European Food Safety Authority used traditional risk assessment approaches to derive a deterministic Tolerable Daily Intake (TDI) of 1 μg/kg-day, however data from human biomarkers studies indicate widespread and variable exposure worldwide, necessitating more sophisticated and advanced methods to quantify population risk. The World Health Organization/International Programme on Chemical Safety (WHO/IPCS) has previously used DON as a case example in replacing the TDI with a probabilistic toxicity value, using default uncertainty and variability distributions to derive the Human Dose corresponding to an effect size M in the Ith percentile of the population (HDMI) for M = 5 % decrease in body weight and I = 1 %. In this study, we extend this case study by incorporating (1) Bayesian modeling approaches, (2) using both in vivo data and in vitro population new approach methods to replace default distributions for interspecies toxicokinetic (TK) differences and intraspecies TK and toxicodynamic (TD) variability, and (3) integrating biomonitoring data and probabilistic dose-response functions to characterize population risk distributions. We first derive an HDMI of 5.5 [1.4-24] μg/kg-day, also using TK modeling to converted the HDMI to Biomonitoring Equivalents, BEMI for comparison with biomonitoring data, with a blood BEMI of 0.53 [0.17-1.6] μg/L and a urinary excretion BEMI of 3.9 [1.0-16] μg/kg-day. We then illustrate how this integrative approach can advance quantitative risk characterization using two human biomonitoring datasets, estimating both the fraction of population with an effect size M ≥ 5 % as well as the distribution of effect sizes. Overall, we demonstrate that integration of Bayesian modeling, human biomonitoring data, and in vitro population-based TD data within the WHO/IPCS probabilistic framework yields more accurate, precise, and comprehensive risk characterization.
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Affiliation(s)
- En-Hsuan Lu
- Interdisciplinary Faculty of Toxicology and Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, United States
| | - Fabian A Grimm
- Interdisciplinary Faculty of Toxicology and Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, United States.
| | - Ivan Rusyn
- Interdisciplinary Faculty of Toxicology and Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, United States
| | - Sarah De Saeger
- Centre of Excellence in Mycotoxicology and Public Health, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, B-9000 Ghent, Belgium
| | - Marthe De Boevre
- Centre of Excellence in Mycotoxicology and Public Health, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, B-9000 Ghent, Belgium
| | - Weihsueh A Chiu
- Interdisciplinary Faculty of Toxicology and Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, United States.
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Kalia V, Baccarelli AA, Happel C, Hollander JA, Jukic AM, McAllister KA, Menon R, Merrick BA, Milosavljevic A, Ravichandran LV, Roth ME, Subramanian A, Tyson FL, Worth L, Shaughnessy DT. Seminar: Extracellular Vesicles as Mediators of Environmental Stress in Human Disease. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:104201. [PMID: 37861803 PMCID: PMC10588739 DOI: 10.1289/ehp12980] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 09/27/2023] [Accepted: 09/28/2023] [Indexed: 10/21/2023]
Abstract
BACKGROUND Extracellular vesicles (EVs), membrane-bound particles containing a variety of RNA types, DNA, proteins, and other macromolecules, are now appreciated as an important means of communication between cells and tissues, both in normal cellular physiology and as a potential indicator of cellular stress, environmental exposures, and early disease pathogenesis. Extracellular signaling through EVs is a growing field of research for understanding fundamental mechanisms of health and disease and for the potential for biomarker discovery and therapy development. EVs are also known to play important roles in mediating the effects of exposure to environmental stress. OBJECTIVES This seminar addresses the application of new tools and approaches for EV research, developed in part through the National Institutes of Health (NIH) Extracellular RNA Communication Program, and reflects presentations and discussions from a workshop held 27-28 September 2021 by the National Institute of Environmental Health Sciences (NIEHS) and the National Center for Advancing Translational Sciences (NCATS) on "Extracellular Vesicles, Exosomes, and Cell-Cell Signaling in Response to Environmental Stress." The panel of experts discussed current research on EVs and environmental exposures, highlighted recent advances in EV isolation and characterization, and considered research gaps and opportunities toward identifying and characterizing the roles for EVs in environmentally related diseases, as well as the current challenges and opportunities in this field. DISCUSSION The authors discuss the application of new experimental models, particularly organ-on-chip (OOC) systems and in vitro approaches and how these have the potential to extend findings in population-based studies of EVs in exposure-related diseases. Given the complex challenges of identifying cell-specific EVs related to environmental exposures, as well as the general heterogeneity and variability in EVs in blood and other accessible biological samples, there is a critical need for rigorous reporting of experimental methods and validation studies. The authors note that these efforts, combined with cross-disciplinary approaches, would ensure that future research efforts in environmental health studies on EV biomarkers are rigorous and reproducible. https://doi.org/10.1289/EHP12980.
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Affiliation(s)
- Vrinda Kalia
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Andrea A. Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Christine Happel
- National Center for Advancing Translational Sciences, National Institutes of Health (NIH), U.S. Department of Health and Human Services (DHHS), Bethesda, Maryland, USA
| | - Jonathan A. Hollander
- Division of Extramural Research and Training, National Institute of Environmental Health Sciences (NIEHS), NIH, DHHS, Research Triangle Park, North Carolina, USA
| | - Anne Marie Jukic
- Division of Intramural Research, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, USA
| | - Kimberly A. McAllister
- Division of Extramural Research and Training, National Institute of Environmental Health Sciences (NIEHS), NIH, DHHS, Research Triangle Park, North Carolina, USA
| | - Ramkumar Menon
- Department of Obstetrics and Gynecology, Division of Basic Science and Translational Research, University of Texas Medical Branch at Galveston, Galveston, Texas, USA
| | - Bruce A. Merrick
- Division of Translational Toxicology, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, USA
| | | | - Lingamanaidu V. Ravichandran
- Division of Extramural Research and Training, National Institute of Environmental Health Sciences (NIEHS), NIH, DHHS, Research Triangle Park, North Carolina, USA
| | - Matthew E. Roth
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | - Anita Subramanian
- Division of Intramural Research, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, USA
| | - Frederick L. Tyson
- Division of Extramural Research and Training, National Institute of Environmental Health Sciences (NIEHS), NIH, DHHS, Research Triangle Park, North Carolina, USA
| | - Leroy Worth
- Division of Extramural Research and Training, National Institute of Environmental Health Sciences (NIEHS), NIH, DHHS, Research Triangle Park, North Carolina, USA
| | - Daniel T. Shaughnessy
- Division of Extramural Research and Training, National Institute of Environmental Health Sciences (NIEHS), NIH, DHHS, Research Triangle Park, North Carolina, USA
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Cuomo D, Nitcher M, Barba E, Feinberg AP, Rusyn I, Chiu WA, Threadgill DW. Refining risk estimates for lead in drinking water based on the impact of genetics and diet on blood lead levels using the Collaborative Cross mouse population. Toxicol Sci 2023; 194:226-234. [PMID: 37243727 PMCID: PMC10375319 DOI: 10.1093/toxsci/kfad054] [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] [Indexed: 05/29/2023] Open
Abstract
Blood lead (Pb) level (BLL) is a commonly used biomarker to evaluate associations with health effects. However, interventions to reduce the adverse effects of Pb require relating BLL to external exposure. Moreover, risk mitigation actions need to ensure protection of more susceptible individuals with a greater tendency to accumulate Pb. Because little data is available to quantify inter-individual variability in biokinetics of Pb, we investigated the influence of genetics and diet on BLL in the genetically diverse Collaborative Cross (CC) mouse population. Adult female mice from 49 CC strains received either a standard mouse chow or a chow mimicking the American diet while being provided water ad libitum with 1000 ppm Pb for 4 weeks. In both arms of the study, inter-strain variability was observed; however, in American diet-fed animals, the BLL was greater and more variable. Importantly, the degree of variation in BLL among strains on the American diet was greater (2.3) than the default variability estimate (1.6) used in setting the regulatory standards. Genetic analysis identified suggestive diet-associated haplotypes that were associated with variation in BLL, largely contributed by the PWK/PhJ strain. This study quantified the variation in BLL that is due to genetic background, diet, and their interactions, and observed that it may be greater than that assumed for current regulatory standards for Pb in drinking water. Moreover, this work highlights the need of characterizing inter-individual variation in BLL to ensure adequate public health interventions aimed at reducing human health risks from Pb.
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Affiliation(s)
- Danila Cuomo
- Department of Cell Biology and Genetics, Texas A&M University, College Station, Texas, USA
| | - Megan Nitcher
- Department of Cell Biology and Genetics, Texas A&M University, College Station, Texas, USA
| | - Estefania Barba
- Department of Cell Biology and Genetics, Texas A&M University, College Station, Texas, USA
| | - Andrew P Feinberg
- Center for Epigenetics, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
- Center for Epigenetics, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
- Center for Epigenetics, Department of Mental Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Ivan Rusyn
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas, USA
| | - Weihsueh A Chiu
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas, USA
| | - David W Threadgill
- Department of Cell Biology and Genetics, Texas A&M University, College Station, Texas, USA
- Department of Nutrition, Texas A&M University, College Station, Texas, USA
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Suciu I, Pamies D, Peruzzo R, Wirtz PH, Smirnova L, Pallocca G, Hauck C, Cronin MTD, Hengstler JG, Brunner T, Hartung T, Amelio I, Leist M. G × E interactions as a basis for toxicological uncertainty. Arch Toxicol 2023; 97:2035-2049. [PMID: 37258688 PMCID: PMC10256652 DOI: 10.1007/s00204-023-03500-9] [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: 03/15/2023] [Accepted: 04/17/2023] [Indexed: 06/02/2023]
Abstract
To transfer toxicological findings from model systems, e.g. animals, to humans, standardized safety factors are applied to account for intra-species and inter-species variabilities. An alternative approach would be to measure and model the actual compound-specific uncertainties. This biological concept assumes that all observed toxicities depend not only on the exposure situation (environment = E), but also on the genetic (G) background of the model (G × E). As a quantitative discipline, toxicology needs to move beyond merely qualitative G × E concepts. Research programs are required that determine the major biological variabilities affecting toxicity and categorize their relative weights and contributions. In a complementary approach, detailed case studies need to explore the role of genetic backgrounds in the adverse effects of defined chemicals. In addition, current understanding of the selection and propagation of adverse outcome pathways (AOP) in different biological environments is very limited. To improve understanding, a particular focus is required on modulatory and counter-regulatory steps. For quantitative approaches to address uncertainties, the concept of "genetic" influence needs a more precise definition. What is usually meant by this term in the context of G × E are the protein functions encoded by the genes. Besides the gene sequence, the regulation of the gene expression and function should also be accounted for. The widened concept of past and present "gene expression" influences is summarized here as Ge. Also, the concept of "environment" needs some re-consideration in situations where exposure timing (Et) is pivotal: prolonged or repeated exposure to the insult (chemical, physical, life style) affects Ge. This implies that it changes the model system. The interaction of Ge with Et might be denoted as Ge × Et. We provide here general explanations and specific examples for this concept and show how it could be applied in the context of New Approach Methodologies (NAM).
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Affiliation(s)
- Ilinca Suciu
- In Vitro Toxicology and Biomedicine, Department Inaugurated By the Doerenkamp-Zbinden Foundation, University of Konstanz, Universitaetsstr. 10, 78457, Constance, Germany
| | - David Pamies
- Department of Biological Sciences, University of Lausanne, 1005, Lausanne, Switzerland
| | - Roberta Peruzzo
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, 94720, USA
| | - Petra H Wirtz
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, 78457, Constance, Germany
- Biological Work and Health Psychology, Department of Psychology, University of Konstanz, 78457, Constance, Germany
| | - Lena Smirnova
- Center for Alternatives to Animal Testing (CAAT), Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | | | - Christof Hauck
- Department of Cell Biology, University of Konstanz, 78457, Constance, Germany
| | - Mark T D Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK
| | - Jan G Hengstler
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, 44139, Dortmund, Germany
| | - Thomas Brunner
- Biochemical Pharmacology, Department of Biology, University of Konstanz, 78457, Constance, Germany
| | - Thomas Hartung
- Center for Alternatives to Animal Testing (CAAT), Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, 21205, USA
- CAAT Europe, University of Konstanz, 78457, Constance, Germany
| | - Ivano Amelio
- Division for Systems Toxicology, Department of Biology, University of Konstanz, 78457, Constance, Germany
| | - Marcel Leist
- In Vitro Toxicology and Biomedicine, Department Inaugurated By the Doerenkamp-Zbinden Foundation, University of Konstanz, Universitaetsstr. 10, 78457, Constance, Germany.
- CAAT Europe, University of Konstanz, 78457, Constance, Germany.
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7
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To KT, Kleinstreuer N, Vasiliou V, Hogberg HT. New approach methodologies to address population variability and susceptibility. Hum Genomics 2023; 17:56. [PMID: 37381067 DOI: 10.1186/s40246-023-00502-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 06/13/2023] [Indexed: 06/30/2023] Open
Affiliation(s)
| | - Nicole Kleinstreuer
- NIH/NIEHS/DTT/NICEATM, RTP, Morrisville, NC, 27709, USA
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, 06520, USA
| | - Vasilis Vasiliou
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, 06520, USA
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Allegra S, Chiara F, Di Grazia D, Gaspari M, De Francia S. Evaluation of Sex Differences in Preclinical Pharmacology Research: How Far Is Left to Go? Pharmaceuticals (Basel) 2023; 16:786. [PMID: 37375734 DOI: 10.3390/ph16060786] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 05/10/2023] [Accepted: 05/23/2023] [Indexed: 06/29/2023] Open
Abstract
Until the last quarter of the 20th century, sex was not recognized as a variable in health research, nor was it believed to be a factor that could affect health and illness. Researchers preferred studying male models for a variety of reasons, such as simplicity, lower costs, hormone confounding effects, and fear of liability from perinatal exposure in case of pregnancy. Equitable representation is imperative for determining the safety, effectiveness, and tolerance of therapeutic agents for all consumers. Decades of female models' underrepresentation in preclinical studies has resulted in inequality in the understanding, diagnosis, and treatment of disease between the sexes. Sex bias has been highlighted as one of the contributing factors to the poor translation and replicability of preclinical research. There have been multiple calls for action, and the inclusion of sex as a biological variable is increasingly supported. However, although there has been substantial progress in the efforts to include more female models in preclinical studies, disparities today remain. In the present review, we consider the current standard practice of the preclinical research setting, why the sex bias exists, why there is the need to include female models, and what risks may arise from continuing this exclusion from experimental design.
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Affiliation(s)
- Sarah Allegra
- Department of Biological and Clinical Sciences, University of Turin, S. Luigi Gonzaga Hospital, 10043 Orbassano, Italy
| | - Francesco Chiara
- Department of Biological and Clinical Sciences, University of Turin, S. Luigi Gonzaga Hospital, 10043 Orbassano, Italy
| | - Daniela Di Grazia
- Department of Biological and Clinical Sciences, University of Turin, S. Luigi Gonzaga Hospital, 10043 Orbassano, Italy
| | - Marco Gaspari
- Department of Biological and Clinical Sciences, University of Turin, S. Luigi Gonzaga Hospital, 10043 Orbassano, Italy
| | - Silvia De Francia
- Department of Biological and Clinical Sciences, University of Turin, S. Luigi Gonzaga Hospital, 10043 Orbassano, Italy
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Risk Assessment of Transgender People: Development of Rodent Models Mimicking Gender-Affirming Hormone Therapies and Identification of Sex-Dimorphic Liver Genes as Novel Biomarkers of Sex Transition. Cells 2023; 12:cells12030474. [PMID: 36766819 PMCID: PMC9913858 DOI: 10.3390/cells12030474] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/19/2023] [Accepted: 01/25/2023] [Indexed: 02/05/2023] Open
Abstract
Transgender (TG) describes individuals whose gender identity differs from the social norms. TG people undergoing gender-affirming hormone therapy (HT) may be considered a sub-group of the population susceptible to environmental contaminants for their targets and modes of action. The aim of this study is to set appropriate HT doses and identify specific biomarkers to implement TG animal models. Four adult rats/group/sex were subcutaneously exposed to three doses of HT (plus control) selected starting from available data. The demasculinizing-feminizing models (dMF) were β-estradiol plus cyproterone acetate, at 0.09 + 0.33, 0.09 + 0.93 and 0.18 + 0.33 mg, respectively, five times/week. The defeminizing-masculinizing models (dFM) were testosterone (T) at 0.45, 0.95 and 2.05 mg, two times/week. Clitoral gain and sperm count, histopathological analysis of reproductive organs and liver, hormone serum levels and gene expression of sex-dimorphic CYP450 were evaluated. In the dMF model, the selected doses-leading to T serum levels at the range of the corresponding cisgender-induced strong general toxicity and cannot be used in long-term studies. In the dFM model, 0.45 mg of T represents the correct dose. In addition, the endpoints selected are considered suitable and reliable to implement the animal model. The sex-specific CYP expression is a suitable biomarker to set proper (de)masculinizing/(de)feminizing HT and to implement TG animal models.
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Jang S, Ford LC, Rusyn I, Chiu WA. Cumulative Risk Meets Inter-Individual Variability: Probabilistic Concentration Addition of Complex Mixture Exposures in a Population-Based Human In Vitro Model. TOXICS 2022; 10:toxics10100549. [PMID: 36287830 PMCID: PMC9611413 DOI: 10.3390/toxics10100549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 09/03/2022] [Accepted: 09/16/2022] [Indexed: 05/16/2023]
Abstract
Although humans are continuously exposed to complex chemical mixtures in the environment, it has been extremely challenging to investigate the resulting cumulative risks and impacts. Recent studies proposed the use of “new approach methods,” in particular in vitro assays, for hazard and dose−response evaluation of mixtures. We previously found, using five human cell-based assays, that concentration addition (CA), the usual default approach to calculate cumulative risk, is mostly accurate to within an order of magnitude. Here, we extend these findings to further investigate how cell-based data can be used to quantify inter-individual variability in CA. Utilizing data from testing 42 Superfund priority chemicals separately and in 8 defined mixtures in a human cell-based population-wide in vitro model, we applied CA to predict effective concentrations for cytotoxicity for each individual, for “typical” (median) and “sensitive” (first percentile) members of the population, and for the median-to-sensitive individual ratio (defined as the toxicodynamic variability factor, TDVF). We quantified the accuracy of CA with the Loewe Additivity Index (LAI). We found that LAI varies more between different mixtures than between different individuals, and that predictions of the population median are generally more accurate than predictions for the “sensitive” individual or the TDVF. Moreover, LAI values were generally <1, indicating that the mixtures were more potent than predicted by CA. Together with our previous studies, we posit that new approach methods data from human cell-based in vitro assays, including multiple phenotypes in diverse cell types and studies in a population-wide model, can fill critical data gaps in cumulative risk assessment, but more sophisticated models of in vitro mixture additivity and bioavailability may be needed. In the meantime, because simple CA models may underestimate potency by an order of magnitude or more, either whole-mixture testing in vitro or, alternatively, more stringent benchmarks of cumulative risk indices (e.g., lower hazard index) may be needed to ensure public health protection.
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Affiliation(s)
- Suji Jang
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Lucie C. Ford
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Ivan Rusyn
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Weihsueh A. Chiu
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Correspondence: ; Tel.: +1-(979)-845-4106
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Ford LC, Jang S, Chen Z, Zhou YH, Gallins PJ, Wright FA, Chiu WA, Rusyn I. A Population-Based Human In Vitro Approach to Quantify Inter-Individual Variability in Responses to Chemical Mixtures. TOXICS 2022; 10:toxics10080441. [PMID: 36006120 PMCID: PMC9413237 DOI: 10.3390/toxics10080441] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 07/25/2022] [Accepted: 07/29/2022] [Indexed: 02/01/2023]
Abstract
Human cell-based population-wide in vitro models have been proposed as a strategy to derive chemical-specific estimates of inter-individual variability; however, the utility of this approach has not yet been tested for cumulative exposures in mixtures. This study aimed to test defined mixtures and their individual components and determine whether adverse effects of the mixtures were likely to be more variable in a population than those of the individual chemicals. The in vitro model comprised 146 human lymphoblastoid cell lines from four diverse subpopulations of European and African descent. Cells were exposed, in concentration−response, to 42 chemicals from diverse classes of environmental pollutants; in addition, eight defined mixtures were prepared from these chemicals using several exposure- or hazard-based scenarios. Points of departure for cytotoxicity were derived using Bayesian concentration−response modeling and population variability was quantified in the form of a toxicodynamic variability factor (TDVF). We found that 28 chemicals and all mixtures exhibited concentration−response cytotoxicity, enabling calculation of the TDVF. The median TDVF across test substances, for both individual chemicals or defined mixtures, ranged from a default assumption (101/2) of toxicodynamic variability in human population to >10. The data also provide a proof of principle for single-variant genome-wide association mapping for toxicity of the chemicals and mixtures, although replication would be necessary due to statistical power limitations with the current sample size. This study demonstrates the feasibility of using a set of human lymphoblastoid cell lines as an in vitro model to quantify the extent of inter-individual variability in hazardous properties of both individual chemicals and mixtures. The data show that population variability of the mixtures is unlikely to exceed that of the most variable component, and that similarity in genome-wide associations among components may be used to accrue additional evidence for grouping of constituents in a mixture for cumulative assessments.
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Affiliation(s)
- Lucie C. Ford
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA; (L.C.F.); (S.J.); (Z.C.); (W.A.C.)
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Suji Jang
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA; (L.C.F.); (S.J.); (Z.C.); (W.A.C.)
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Zunwei Chen
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA; (L.C.F.); (S.J.); (Z.C.); (W.A.C.)
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Yi-Hui Zhou
- Departments of Biological Sciences and Statistics, North Carolina State University, Raleigh, NC 27695, USA; (Y.-H.Z.); (F.A.W.)
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA;
| | - Paul J. Gallins
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA;
| | - Fred A. Wright
- Departments of Biological Sciences and Statistics, North Carolina State University, Raleigh, NC 27695, USA; (Y.-H.Z.); (F.A.W.)
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA;
| | - Weihsueh A. Chiu
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA; (L.C.F.); (S.J.); (Z.C.); (W.A.C.)
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Ivan Rusyn
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA; (L.C.F.); (S.J.); (Z.C.); (W.A.C.)
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Correspondence: ; Tel.: +979-458-9866
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