Juarez Paul D, Matthews-Juarez Patricia
Family and Community Medicine, Meharry Medical College, Nashville, TN, United States.
Front Oncol. 2018 Aug 27;8:313. doi: 10.3389/fonc.2018.00313. eCollection 2018.
Traditional research approaches, including genome-wide association studies (GWAS), epigenome-wide association studies (EWAS) and Gene × Environment (G × E) studies are limited in their ability to handle the multiplicity of chemical and non-chemical toxicants to which people are exposed in the real world, over their life course, their impact on epigenomics and other biological systems, and their relationship to cancer onset, progression, and outcomes. Exposome-wide association study (ExWAS) provides a new approach for conceptualizing the roles and relationships of multiple chemical and non-chemical exposures in the etiology and progression of cancer at key developmental periods, over the life course, and across generations. ExWAS challenges us to consider the influence of both internal and external environment, chemical and non-chemical stressors, risk and protective factors, and spatial and temporal dimensions of exposures in our models of cancer incidence, outcomes, and disparities. Applying an ExWAS approach to cancer and cancer disparities research supports robust computational models and methods that will allow for analysis of the dynamic and complex interactions between genetics, epigenetics, and exposomics factors. In the coming months, we will spatially and temporally align environmental exposures with SCCS participant data from time of enrollment forward to move us closer to identifying complete exposure pathways that lead to cancer. In the future, we hope to link external sources of exposure to biomarkers of exposure, biomarkers of disease, disease phenotypes, and population level disparities.
传统的研究方法,包括全基因组关联研究(GWAS)、全表观基因组关联研究(EWAS)以及基因×环境(G×E)研究,在处理人们在现实世界中一生所接触的多种化学和非化学毒物方面,在其对表观基因组学和其他生物系统的影响方面,以及在其与癌症发生、发展和转归的关系方面,能力有限。全暴露组关联研究(ExWAS)为在关键发育时期、一生过程以及多代人中概念化多种化学和非化学暴露在癌症病因学和发展中的作用及关系提供了一种新方法。ExWAS促使我们在癌症发病率、转归和差异模型中考虑内部和外部环境、化学和非化学应激源、风险和保护因素以及暴露的时空维度的影响。将ExWAS方法应用于癌症及癌症差异研究,支持强大的计算模型和方法,这将有助于分析遗传学、表观遗传学和暴露组学因素之间动态而复杂的相互作用。在未来几个月里,我们将在空间和时间上把环境暴露与自入组时间起的SCCS参与者数据进行比对,以使我们更接近确定导致癌症的完整暴露途径。未来,我们希望将外部暴露源与暴露生物标志物、疾病生物标志物、疾病表型以及人群水平差异联系起来。