Immunotoxicity hazard identification of chemicals aims to evaluate the potential for unintended effects of chemical exposure on the immune system. Perfluorinated alkylate substances (PFAS), such as perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persistent, globally disseminated environmental contaminants known to be immunotoxic. Elevated PFAS exposure is associated with lower antibody responses to vaccinations in children and in adults. In addition, some studies have reported a correlation between PFAS levels in the body and lower resistance to disease, in other words an increased risk of infections or cancers. In this context, modelling and simulation platforms could be used to simulate the human immune system with the aim to evaluate the adverse effects that immunotoxicants may have. Here, we show the conditions under which a mathematical model developed for one purpose and application (e.g., in the pharmaceutical domain) can be successfully translated and transferred to another (e.g., in the chemicals domain) without undergoing significant adaptation. In particular, we demonstrate that the Universal Immune System Simulator was able to simulate the effects of PFAS on the immune system, introducing entities and new interactions that are biologically involved in the phenomenon. This also revealed a potentially exploitable pathway for assessing immunotoxicity through a computational model.

Translatability and transferability of in silico models : Context of use switching to predict the effects of environmental chemicals on the immune system / F. Pappalardo, G. Russo, E. Corsini, A. Paini, A. Worth. - In: COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL. - ISSN 2001-0370. - 20:(2022), pp. 1764-1777. [10.1016/j.csbj.2022.03.024]

Translatability and transferability of in silico models : Context of use switching to predict the effects of environmental chemicals on the immune system

E. Corsini;
2022

Abstract

Immunotoxicity hazard identification of chemicals aims to evaluate the potential for unintended effects of chemical exposure on the immune system. Perfluorinated alkylate substances (PFAS), such as perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persistent, globally disseminated environmental contaminants known to be immunotoxic. Elevated PFAS exposure is associated with lower antibody responses to vaccinations in children and in adults. In addition, some studies have reported a correlation between PFAS levels in the body and lower resistance to disease, in other words an increased risk of infections or cancers. In this context, modelling and simulation platforms could be used to simulate the human immune system with the aim to evaluate the adverse effects that immunotoxicants may have. Here, we show the conditions under which a mathematical model developed for one purpose and application (e.g., in the pharmaceutical domain) can be successfully translated and transferred to another (e.g., in the chemicals domain) without undergoing significant adaptation. In particular, we demonstrate that the Universal Immune System Simulator was able to simulate the effects of PFAS on the immune system, introducing entities and new interactions that are biologically involved in the phenomenon. This also revealed a potentially exploitable pathway for assessing immunotoxicity through a computational model.
English
In silico trials; Immune system; PFAS; Risk-assessment; Vaccines Immunotoxicity
Settore BIO/14 - Farmacologia
Articolo
Esperti anonimi
Pubblicazione scientifica
Goal 3: Good health and well-being
2022
Elsevier
20
1764
1777
14
Pubblicato
Periodico con rilevanza internazionale
crossref
Aderisco
info:eu-repo/semantics/article
Translatability and transferability of in silico models : Context of use switching to predict the effects of environmental chemicals on the immune system / F. Pappalardo, G. Russo, E. Corsini, A. Paini, A. Worth. - In: COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL. - ISSN 2001-0370. - 20:(2022), pp. 1764-1777. [10.1016/j.csbj.2022.03.024]
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262
Article (author)
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F. Pappalardo, G. Russo, E. Corsini, A. Paini, A. Worth
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/923077
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