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Omics for prediction of environmental health effects: Blood leukocyte-based cross-omic profiling reliably predicts diseases associated with tobacco smoking

The utility of blood-based omic profiles for linking environmental exposures to their potential health effects was evaluated in 649 individuals, drawn from the general population, in relation to tobacco smoking, an exposure with well-characterised health effects. Using disease connectivity analysis,...

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Autores principales: Georgiadis, Panagiotis, Hebels, Dennie G., Valavanis, Ioannis, Liampa, Irene, Bergdahl, Ingvar A., Johansson, Anders, Palli, Domenico, Chadeau-Hyam, Marc, Chatziioannou, Aristotelis, Jennen, Danyel G. J., Krauskopf, Julian, Jetten, Marlon J., Kleinjans, Jos C. S., Vineis, Paolo, Kyrtopoulos, Soterios A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4738297/
https://www.ncbi.nlm.nih.gov/pubmed/26837704
http://dx.doi.org/10.1038/srep20544
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author Georgiadis, Panagiotis
Hebels, Dennie G.
Valavanis, Ioannis
Liampa, Irene
Bergdahl, Ingvar A.
Johansson, Anders
Palli, Domenico
Chadeau-Hyam, Marc
Chatziioannou, Aristotelis
Jennen, Danyel G. J.
Krauskopf, Julian
Jetten, Marlon J.
Kleinjans, Jos C. S.
Vineis, Paolo
Kyrtopoulos, Soterios A.
author_facet Georgiadis, Panagiotis
Hebels, Dennie G.
Valavanis, Ioannis
Liampa, Irene
Bergdahl, Ingvar A.
Johansson, Anders
Palli, Domenico
Chadeau-Hyam, Marc
Chatziioannou, Aristotelis
Jennen, Danyel G. J.
Krauskopf, Julian
Jetten, Marlon J.
Kleinjans, Jos C. S.
Vineis, Paolo
Kyrtopoulos, Soterios A.
author_sort Georgiadis, Panagiotis
collection PubMed
description The utility of blood-based omic profiles for linking environmental exposures to their potential health effects was evaluated in 649 individuals, drawn from the general population, in relation to tobacco smoking, an exposure with well-characterised health effects. Using disease connectivity analysis, we found that the combination of smoking-modified, genome-wide gene (including miRNA) expression and DNA methylation profiles predicts with remarkable reliability most diseases and conditions independently known to be causally associated with smoking (indicative estimates of sensitivity and positive predictive value 94% and 84%, respectively). Bioinformatics analysis reveals the importance of a small number of smoking-modified, master-regulatory genes and suggest a central role for altered ubiquitination. The smoking-induced gene expression profiles overlap significantly with profiles present in blood cells of patients with lung cancer or coronary heart disease, diseases strongly associated with tobacco smoking. These results provide proof-of-principle support to the suggestion that omic profiling in peripheral blood has the potential of identifying early, disease-related perturbations caused by toxic exposures and may be a useful tool in hazard and risk assessment.
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spelling pubmed-47382972016-02-09 Omics for prediction of environmental health effects: Blood leukocyte-based cross-omic profiling reliably predicts diseases associated with tobacco smoking Georgiadis, Panagiotis Hebels, Dennie G. Valavanis, Ioannis Liampa, Irene Bergdahl, Ingvar A. Johansson, Anders Palli, Domenico Chadeau-Hyam, Marc Chatziioannou, Aristotelis Jennen, Danyel G. J. Krauskopf, Julian Jetten, Marlon J. Kleinjans, Jos C. S. Vineis, Paolo Kyrtopoulos, Soterios A. Sci Rep Article The utility of blood-based omic profiles for linking environmental exposures to their potential health effects was evaluated in 649 individuals, drawn from the general population, in relation to tobacco smoking, an exposure with well-characterised health effects. Using disease connectivity analysis, we found that the combination of smoking-modified, genome-wide gene (including miRNA) expression and DNA methylation profiles predicts with remarkable reliability most diseases and conditions independently known to be causally associated with smoking (indicative estimates of sensitivity and positive predictive value 94% and 84%, respectively). Bioinformatics analysis reveals the importance of a small number of smoking-modified, master-regulatory genes and suggest a central role for altered ubiquitination. The smoking-induced gene expression profiles overlap significantly with profiles present in blood cells of patients with lung cancer or coronary heart disease, diseases strongly associated with tobacco smoking. These results provide proof-of-principle support to the suggestion that omic profiling in peripheral blood has the potential of identifying early, disease-related perturbations caused by toxic exposures and may be a useful tool in hazard and risk assessment. Nature Publishing Group 2016-02-03 /pmc/articles/PMC4738297/ /pubmed/26837704 http://dx.doi.org/10.1038/srep20544 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Georgiadis, Panagiotis
Hebels, Dennie G.
Valavanis, Ioannis
Liampa, Irene
Bergdahl, Ingvar A.
Johansson, Anders
Palli, Domenico
Chadeau-Hyam, Marc
Chatziioannou, Aristotelis
Jennen, Danyel G. J.
Krauskopf, Julian
Jetten, Marlon J.
Kleinjans, Jos C. S.
Vineis, Paolo
Kyrtopoulos, Soterios A.
Omics for prediction of environmental health effects: Blood leukocyte-based cross-omic profiling reliably predicts diseases associated with tobacco smoking
title Omics for prediction of environmental health effects: Blood leukocyte-based cross-omic profiling reliably predicts diseases associated with tobacco smoking
title_full Omics for prediction of environmental health effects: Blood leukocyte-based cross-omic profiling reliably predicts diseases associated with tobacco smoking
title_fullStr Omics for prediction of environmental health effects: Blood leukocyte-based cross-omic profiling reliably predicts diseases associated with tobacco smoking
title_full_unstemmed Omics for prediction of environmental health effects: Blood leukocyte-based cross-omic profiling reliably predicts diseases associated with tobacco smoking
title_short Omics for prediction of environmental health effects: Blood leukocyte-based cross-omic profiling reliably predicts diseases associated with tobacco smoking
title_sort omics for prediction of environmental health effects: blood leukocyte-based cross-omic profiling reliably predicts diseases associated with tobacco smoking
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4738297/
https://www.ncbi.nlm.nih.gov/pubmed/26837704
http://dx.doi.org/10.1038/srep20544
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