An integrative data-centric approach to derivation and characterization of an adverse outcome pathway network for cadmium-induced toxicity.

Autor: Sahoo AK; The Institute of Mathematical Sciences (IMSc), Chennai, India; Homi Bhabha National Institute (HBNI), Mumbai, India., Chivukula N; The Institute of Mathematical Sciences (IMSc), Chennai, India; Homi Bhabha National Institute (HBNI), Mumbai, India., Ramesh K; The Institute of Mathematical Sciences (IMSc), Chennai, India., Singha J; National Centre for Coastal Research, Ministry of Earth Sciences, Government of India, Pallikaranai, Chennai, India., Marigoudar SR; National Centre for Coastal Research, Ministry of Earth Sciences, Government of India, Pallikaranai, Chennai, India., Sharma KV; National Centre for Coastal Research, Ministry of Earth Sciences, Government of India, Pallikaranai, Chennai, India., Samal A; The Institute of Mathematical Sciences (IMSc), Chennai, India; Homi Bhabha National Institute (HBNI), Mumbai, India. Electronic address: asamal@imsc.res.in.
Jazyk: angličtina
Zdroj: The Science of the total environment [Sci Total Environ] 2024 Apr 10; Vol. 920, pp. 170968. Date of Electronic Publication: 2024 Feb 16.
DOI: 10.1016/j.scitotenv.2024.170968
Abstrakt: Cadmium is a prominent toxic heavy metal that contaminates both terrestrial and aquatic environments. Owing to its high biological half-life and low excretion rates, cadmium causes a variety of adverse biological outcomes. Adverse outcome pathway (AOP) networks were envisioned to systematically capture toxicological information to enable risk assessment and chemical regulation. Here, we leveraged AOP-Wiki and integrated heterogeneous data from four other exposome-relevant resources to build the first AOP network relevant for inorganic cadmium-induced toxicity. From AOP-Wiki, we filtered 309 high confidence AOPs, identified 312 key events (KEs) associated with inorganic cadmium from five exposome-relevant databases using a data-centric approach, and thereafter, curated 30 cadmium relevant AOPs (cadmium-AOPs). By constructing the undirected AOP network, we identified a large connected component of 18 cadmium-AOPs. Further, we analyzed the directed network of 59 KEs and 82 key event relationships (KERs) in the largest component using graph-theoretic approaches. Subsequently, we mined published literature using artificial intelligence-based tools to provide auxiliary evidence of cadmium association for all KEs in the largest component. Finally, we performed case studies to verify the rationality of cadmium-induced toxicity in humans and aquatic species. Overall, cadmium-AOP network constructed in this study will aid ongoing research in systems toxicology and chemical exposome.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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