The exposome and health: where chemistry meets biology
By R. Vermeulen, Emma L. Schymanski, Albert-László Barabási, G. Miller. Science, 2020
834 citations recorded by the source corpus.
Despite extensive evidence showing that exposure to specific chemicals can lead to disease, current research approaches and regulatory policies fail to address the chemical complexity of our world. To safeguard current and future generations from the increasing number of chemicals polluting our environment, a systematic and agnostic approach is needed. The “exposome” concept strives to capture the diversity and range of exposures to synthetic chemicals, dietary constituents, psychosocial stressors, and physical factors, as well as their corresponding biological responses. Technological advances such as high-resolution mass spectrometry and network science have allowed us to take the first steps toward a comprehensive assessment of the exposome. Given the increased recognition of the dominant role that nongenetic factors play in disease, an effort to characterize the exposome at a scale comparable to that of the human genome is warranted.
Subfields: Health, Toxicology and Mutagenesis, Molecular Biology, Public Health, Environmental and Occupational Health
View Paper: https://www.semanticscholar.org/paper/b0ebb2757d45adb9e4e78c026ebdb03da502730c
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Citations in the corpus
- How Machine Learning will Transform Biomedicine (2020, neutral): “These prototype applications suggest a role for machine learning where wearables, home devices, and smartphones are used to capture all kinds of data, including biometric measurements, photos, dietary intake, and even environmental information (i.e., the “exposome” (Vermeulen et al., 2020)).”
- Using MetaboAnalyst 5.0 for LC–HRMS spectra processing, multi-omics integration and covariate adjustment of global metabolomics data (2022, methodology): “Several key features of MetaboAnalyst are illustrated here: (1) the navigation tree allowing users to access different pages, (2) the results (files and images) generated during analysis, (3) the R Command History containing the underlying R commands executed, (4) the analysis report documenting all”
- MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights (2021, background): “It also plays a leading role in dissecting host-environment interactions (3) and has become an essential component in deep phenotyping for precision medicine (4–7).”
- Networks beyond pairwise interactions: structure and dynamics (2020, background): “[680] Roel Vermeulen, Emma L Schymanski, Albert-László Barabási, and Gary W Miller.”