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Interactive data sharing for multiple questionnaire-based exposome-wide association studies and exposome correlations in the Personalized Environment and Genes Study.
Lloyd, Dillon; House, John S; Akhtari, Farida S; Schmitt, Charles P; Fargo, David C; Scholl, Elizabeth H; Phillips, Jason; Choksi, Shail; Shah, Ruchir; Hall, Janet E; Motsinger-Reif, Alison A.
Afiliação
  • Lloyd D; Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
  • House JS; Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
  • Akhtari FS; Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
  • Schmitt CP; Division of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, NC, USA.
  • Fargo DC; Office of the Director, National Institute of Environmental Health Sciences, Durham, NC, USA.
  • Scholl EH; Sciome LLC, Durham, NC, USA.
  • Phillips J; Sciome LLC, Durham, NC, USA.
  • Choksi S; Sciome LLC, Durham, NC, USA.
  • Shah R; Sciome LLC, Durham, NC, USA.
  • Hall JE; Clinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
  • Motsinger-Reif AA; Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
Exposome ; 4(1): osae003, 2024.
Article em En | MEDLINE | ID: mdl-38425336
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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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article