European Molecular Biology Laboratory & European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton CB10 1SD, U.K.
Department of Food Chemistry and Toxicology, University of Vienna, 1090 Vienna, Austria.
Environ Sci Technol. 2024 Apr 30;58(17):7256-7269. doi: 10.1021/acs.est.3c07961. Epub 2024 Apr 19.
Through investigating the combined impact of the environmental exposures experienced by an individual throughout their lifetime, exposome research provides opportunities to understand and mitigate negative health outcomes. While current exposome research is driven by epidemiological studies that identify associations between exposures and effects, new frameworks integrating more substantial population-level metadata, including electronic health and administrative records, will shed further light on characterizing environmental exposure risks. Molecular biology offers methods and concepts to study the biological and health impacts of exposomes in experimental and computational systems. Of particular importance is the growing use of omics readouts in epidemiological and clinical studies. This paper calls for the adoption of mechanistic molecular biology approaches in exposome research as an essential step in understanding the genotype and exposure interactions underlying human phenotypes. A series of recommendations are presented to make the necessary and appropriate steps to move from exposure association to causation, with a huge potential to inform precision medicine and population health. This includes establishing hypothesis-driven laboratory testing within the exposome field, supported by appropriate methods to read across from model systems research to human.
通过研究个体一生中所经历的环境暴露的综合影响,暴露组研究提供了理解和减轻负面健康结果的机会。虽然当前的暴露组研究是由识别暴露与效应之间关联的流行病学研究驱动的,但新的框架整合了更实质性的人群水平元数据,包括电子健康和行政记录,将进一步阐明环境暴露风险的特征。分子生物学提供了方法和概念,可用于在实验和计算系统中研究暴露组的生物学和健康影响。特别重要的是,在流行病学和临床研究中越来越多地使用组学读数。本文呼吁在暴露组研究中采用机制分子生物学方法,这是理解人类表型中基因型和暴露相互作用的必要步骤。提出了一系列建议,以采取必要和适当的步骤,从暴露关联转向因果关系,这有很大的潜力为精准医学和人群健康提供信息。这包括在暴露组领域内建立假设驱动的实验室测试,并得到适当的方法的支持,以从模型系统研究跨越到人类。