Assessing the contribution of the chemical exposome to neurodegenerative disease.

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Title: Assessing the contribution of the chemical exposome to neurodegenerative disease.
Authors: Lefèvre-Arbogast, S. (AUTHOR), Chaker, J. (AUTHOR), Mercier, F. (AUTHOR), Barouki, R. (AUTHOR), Coumoul, X. (AUTHOR), Miller, G. W. (AUTHOR), David, A. (AUTHOR), Samieri, C. (AUTHOR)
Source: Nature Neuroscience. May2024, Vol. 27 Issue 5, p812-821. 10p.
Abstract: Over the past few decades, numerous environmental chemicals from solvents to pesticides have been suggested to be involved in the development and progression of neurodegenerative diseases. Most of the evidence has accumulated from occupational or cohort studies in humans or laboratory research in animal models, with a range of chemicals being implicated. What has been missing is a systematic approach analogous to genome-wide association studies, which have identified dozens of genes involved in Alzheimer's disease, Parkinson's disease and other neurodegenerative diseases. Fortunately, it is now possible to study hundreds to thousands of chemical features under the exposome framework. This Perspective explores how advances in mass spectrometry make it possible to generate exposomic data to complement genomic data and thereby better understand neurodegenerative diseases. Nongenetic factors contribute to the onset, progression and severity of neurodegenerative diseases. Here, the authors describe how exposomics, the systematic analysis of environmental factors, can help neuroscientists understand these diseases. [ABSTRACT FROM AUTHOR]
Copyright of Nature Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Assessing the contribution of the chemical exposome to neurodegenerative disease.
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  Data: <searchLink fieldCode="JN" term="%22Nature+Neuroscience%22">Nature Neuroscience</searchLink>. May2024, Vol. 27 Issue 5, p812-821. 10p.
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  Data: Over the past few decades, numerous environmental chemicals from solvents to pesticides have been suggested to be involved in the development and progression of neurodegenerative diseases. Most of the evidence has accumulated from occupational or cohort studies in humans or laboratory research in animal models, with a range of chemicals being implicated. What has been missing is a systematic approach analogous to genome-wide association studies, which have identified dozens of genes involved in Alzheimer's disease, Parkinson's disease and other neurodegenerative diseases. Fortunately, it is now possible to study hundreds to thousands of chemical features under the exposome framework. This Perspective explores how advances in mass spectrometry make it possible to generate exposomic data to complement genomic data and thereby better understand neurodegenerative diseases. Nongenetic factors contribute to the onset, progression and severity of neurodegenerative diseases. Here, the authors describe how exposomics, the systematic analysis of environmental factors, can help neuroscientists understand these diseases. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Nature Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: May2024
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