Interactive data sharing for multiple questionnaire-based exposome-wide association studies and exposome correlations in the Personalized Environment and Genes Study.

Exposome Pub Date : 2024-02-12 eCollection Date: 2024-01-01 DOI:10.1093/exposome/osae003
Dillon Lloyd, John S House, Farida S Akhtari, Charles P Schmitt, David C Fargo, Elizabeth H Scholl, Jason Phillips, Shail Choksi, Ruchir Shah, Janet E Hall, Alison A Motsinger-Reif
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Abstract

The correlations among individual exposures in the exposome, which refers to all exposures an individual encounters throughout life, are important for understanding the landscape of how exposures co-occur, and how this impacts health and disease. Exposome-wide association studies (ExWAS), which are analogous to genome-wide association studies (GWAS), are increasingly being used to elucidate links between the exposome and disease. Despite increased interest in the exposome, tools and publications that characterize exposure correlations and their relationships with human disease are limited, and there is a lack of data and results sharing in resources like the GWAS catalog. To address these gaps, we developed the PEGS Explorer web application to explore exposure correlations in data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS) that were rigorously calculated to account for differing data types and previously published results from ExWAS. Through globe visualizations, PEGS Explorer allows users to explore correlations between exposures found to be associated with complex diseases. The exposome data used for analysis includes not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The web application addresses the lack of accessible data and results sharing, a major challenge in the field, and enables users to put results in context, generate hypotheses, and, importantly, replicate findings in other cohorts. PEGS Explorer will be updated with additional results as they become available, ensuring it is an up-to-date resource in exposome science.

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个性化环境与基因研究中基于多份问卷的暴露组关联研究和暴露组相关性的交互式数据共享。
暴露组是指个体一生中接触到的所有暴露,暴露组中个体暴露之间的相关性对于了解暴露如何共存以及如何影响健康和疾病非常重要。全暴露体关联研究(ExWAS)类似于全基因组关联研究(GWAS),越来越多地被用于阐明暴露体与疾病之间的联系。尽管人们对暴露组的兴趣与日俱增,但描述暴露相关性及其与人类疾病关系的工具和出版物却十分有限,而且缺乏像 GWAS 目录这样的数据和结果共享资源。为了填补这些空白,我们开发了 PEGS Explorer 网络应用程序,以探索来自北卡罗来纳州个性化环境与基因研究(PEGS)的各种数据中的暴露相关性,这些数据经过严格计算,考虑到了不同的数据类型和以前发表的 ExWAS 结果。通过全球可视化,PEGS Explorer 允许用户探索发现与复杂疾病相关的暴露之间的相关性。用于分析的暴露组数据不仅包括点源污染和臭氧水平等标准环境暴露,还包括饮食、药物、生活方式因素、压力和职业等暴露。该网络应用程序解决了该领域面临的主要挑战--缺乏可访问的数据和结果共享的问题,使用户能够将结果置于上下文中,提出假设,更重要的是,在其他队列中复制研究结果。PEGS Explorer 将在有更多结果时及时更新,确保它成为暴露组科学的最新资源。
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Exposomics: perfection not required. A long and winding road: Culture change on data sharing in exposomics Interactive data sharing for multiple questionnaire-based exposome-wide association studies and exposome correlations in the Personalized Environment and Genes Study. Questionnaire-based exposome-wide association studies for common diseases in the Personalized Environment and Genes Study. Decoding the exposome: Data science methodologies and implications in Exposome-Wide association studies (ExWASs)
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