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Metabolomics in epidemiology: from metabolite concentrations to integrative reaction networks

Metabolomics is becoming feasible for population-scale studies of human disease. In this review, we survey epidemiological studies that leverage metabolomics and multi-omics to gain insight into disease mechanisms. We outline key practical, technological and analytical limitations while also highlig...

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Detalles Bibliográficos
Autores principales: Fearnley, Liam G, Inouye, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5100607/
https://www.ncbi.nlm.nih.gov/pubmed/27118561
http://dx.doi.org/10.1093/ije/dyw046
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author Fearnley, Liam G
Inouye, Michael
author_facet Fearnley, Liam G
Inouye, Michael
author_sort Fearnley, Liam G
collection PubMed
description Metabolomics is becoming feasible for population-scale studies of human disease. In this review, we survey epidemiological studies that leverage metabolomics and multi-omics to gain insight into disease mechanisms. We outline key practical, technological and analytical limitations while also highlighting recent successes in integrating these data. The use of multi-omics to infer reaction rates is discussed as a potential future direction for metabolomics research, as a means of identifying biomarkers as well as inferring causality. Furthermore, we highlight established analysis approaches as well as simulation-based methods currently used in single- and multi-cell levels in systems biology.
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spelling pubmed-51006072016-11-10 Metabolomics in epidemiology: from metabolite concentrations to integrative reaction networks Fearnley, Liam G Inouye, Michael Int J Epidemiol Reviews Metabolomics is becoming feasible for population-scale studies of human disease. In this review, we survey epidemiological studies that leverage metabolomics and multi-omics to gain insight into disease mechanisms. We outline key practical, technological and analytical limitations while also highlighting recent successes in integrating these data. The use of multi-omics to infer reaction rates is discussed as a potential future direction for metabolomics research, as a means of identifying biomarkers as well as inferring causality. Furthermore, we highlight established analysis approaches as well as simulation-based methods currently used in single- and multi-cell levels in systems biology. Oxford University Press 2016-10 2016-04-26 /pmc/articles/PMC5100607/ /pubmed/27118561 http://dx.doi.org/10.1093/ije/dyw046 Text en © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Reviews
Fearnley, Liam G
Inouye, Michael
Metabolomics in epidemiology: from metabolite concentrations to integrative reaction networks
title Metabolomics in epidemiology: from metabolite concentrations to integrative reaction networks
title_full Metabolomics in epidemiology: from metabolite concentrations to integrative reaction networks
title_fullStr Metabolomics in epidemiology: from metabolite concentrations to integrative reaction networks
title_full_unstemmed Metabolomics in epidemiology: from metabolite concentrations to integrative reaction networks
title_short Metabolomics in epidemiology: from metabolite concentrations to integrative reaction networks
title_sort metabolomics in epidemiology: from metabolite concentrations to integrative reaction networks
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5100607/
https://www.ncbi.nlm.nih.gov/pubmed/27118561
http://dx.doi.org/10.1093/ije/dyw046
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