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Updated: May 16, 2025

Long-term Behavioral and Reproductive Consequences of Embryonic Exposure to Low-dose Toxicants
Published on: March 6, 2018
Implications of petrochemical exposure and epigenetic alterations on human health
Selvaraj Jayaraman1, Anupriya Eswaran1, Vishnu Priya Veeraraghavan1
1Centre of Molecular Medicine and Diagnostics (COMManD), Department of Biochemistry, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India.
Abstract:
The petrochemical industry and automobiles contribute significantly to hazardous waste, which contains a broad array of organic and inorganic compounds posing serious health risks. Identifying biomarkers of exposure and creating predictive models for toxicity characterization necessitate a thorough understanding of the underlying epigenetic mechanisms. The development of disease is intricately linked to epigenetic processes, such as DNA methylation, histone modifications, and microRNA (mi-RNA) regulation, which mediate gene-environment interactions. While previous studies have investigated these alterations as markers for petrochemical-induced changes, there is still a need for deeper exploration in this area, with particular emphasis on advanced gene-editing technologies. This review highlights the specific epigenetic processes, especially gene-specific DNA methylation changes, associated with prolonged petrochemical exposure. Notably, the demethylation of long interspersed nuclear element 1 (LINE-1), Alu elements, and forkhead box P3 (FOXP3), as well as hypermethylation of interferon gamma (IFN-γ) and hypomethylation of interleukin-4 (IL-4) promoter regions, are discussed. These alterations in DNA methylation patterns serve as valuable biomarkers, potentially offering insights into early detection and personalized treatment options for diseases caused by long-term exposure to petrochemicals. Furthermore, CRISPR-based gene editing techniques, while underexplored, present a promising approach for correcting petrochemical-induced mutations. In addition, AI-driven radiomics holds promise for early disease detection, though it is currently limited by its lack of integration with multi-omics data. In conclusion, it is crucial to refine disease modelling, develop comprehensive risk assessment models, and innovate targeted therapeutic strategies. Future research should focus on enhancing exposure evaluation, incorporating computational tools to analyze molecular changes, and improving our understanding of how these modifications influence disease prevention and treatment.
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