Metabolomics for exposure assessment and toxicity effects of occupational pollutants: current status and future perspectives

代谢组学 毒物 毒理基因组学 职业暴露 疾病 组学 毒理 计算生物学 医学 生物信息学 生物 毒性 环境卫生 病理 基因表达 内科学 基因 生物化学
作者
Fatemeh Dehghani,Saeed Yousefinejad,Douglas I. Walker,Fariborz Omidi
出处
期刊:Metabolomics [Springer Science+Business Media]
卷期号:18 (9): 73-73 被引量:22
标识
DOI:10.1007/s11306-022-01930-7
摘要

Work-related exposures to harmful agents or factors are associated with an increase in incidence of occupational diseases. These exposures often represent a complex mixture of different stressors, challenging the ability to delineate the mechanisms and risk factors underlying exposure-disease relationships. The use of omics measurement approaches that enable characterization of biological marker patterns provide internal indicators of molecular alterations, which could be used to identify bioeffects following exposure to a toxicant. Metabolomics is the comprehensive analysis of small molecule present in biological samples, and allows identification of potential modes of action and altered pathways by systematic measurement of metabolites.The aim of this study is to review the application of metabolomics studies for use in occupational health, with a focus on applying metabolomics for exposure monitoring and its relationship to occupational diseases.PubMed, Web of Science, Embase and Scopus electronic databases were systematically searched for relevant studies published up to 2021.Most of reviewed studies included worker populations exposed to heavy metals such as As, Cd, Pb, Cr, Ni, Mn and organic compounds such as tetrachlorodibenzo-p-dioxin, trichloroethylene, polyfluoroalkyl, acrylamide, polyvinyl chloride. Occupational exposures were associated with changes in metabolites and pathways, and provided novel insight into the relationship between exposure and disease outcomes. The reviewed studies demonstrate that metabolomics provides a powerful ability to identify metabolic phenotypes and bioeffect of occupational exposures.Continued application to worker populations has the potential to enable characterization of thousands of chemical signals in biological samples, which could lead to discovery of new biomarkers of exposure for chemicals, identify possible toxicological mechanisms, and improved understanding of biological effects increasing disease risk associated with occupational exposure.
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