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A Systematic Review of Toxicological Studies to Identify the Association between Environmental Diseases and Environmental Factors

환경성질환과 환경유해인자의 연관성을 규명하기 위한 독성 연구 고찰

  • Ka, Yujin (Department of Environmental Health, Graduate School at Yongin University) ;
  • Ji, Kyunghee (Department of Environmental Health, Graduate School at Yongin University)
  • 가유진 (용인대학교 일반대학원 환경보건학과) ;
  • 지경희 (용인대학교 일반대학원 환경보건학과)
  • Received : 2021.09.03
  • Accepted : 2021.11.25
  • Published : 2021.12.31

Abstract

Background: The occurrence of environmental disease is known to be associated with chronic exposure to toxic chemicals, including waterborne contaminants, air/indoor pollutants, asbestos, ingredients in humidifier disinfectants, etc. Objectives: In this study, we reviewed toxicological studies related to environmental disease as defined by the Environmental Health Act in Korea and toxic chemicals. We also suggested a direction for future toxicological research necessary for the prevention and management of environmental disease. Methods: Trends in previous studies related to environmental disease were investigated through PubMed and Web of Science. A detailed review was provided on toxicological studies related to the humidifier disinfectants. We identified adverse outcome pathways (AOPs) that can be linked to the induction of environmental diseases, and proposed a chemical screening system that uses AOP, chemical toxicity big data, and deep learning models to select chemicals that induce environmental disease. Results: Research on chemical toxicity is increasing every year, but there is a limitation to revealing a clear causal relationship between exposure to chemicals and the occurrence of environmental disease. It is necessary to develop various exposure- and effect-biomarkers related to disease occurrence and to conduct toxicokinetic studies. A novel chemical screening system that uses AOP and chemical toxicity big data could be useful for selecting chemicals that cause environmental diseases. Conclusions: From a toxicological point of view, developing AOP related to environmental diseases and a deep learning-based chemical screening system will contribute to the prevention of environmental diseases in advance.

Keywords

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