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Genetic and environmental perturbations lead to regulatory decoherence
Correlation among traits is a fundamental feature of biological systems that remains difficult to study. To address this problem, we developed a flexible approach that allows us to identify factors associated with inter-individual variation in correlation. We use data from three human cohorts to stu...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6400502/ https://www.ncbi.nlm.nih.gov/pubmed/30834892 http://dx.doi.org/10.7554/eLife.40538 |
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author | Lea, Amanda Subramaniam, Meena Ko, Arthur Lehtimäki, Terho Raitoharju, Emma Kähönen, Mika Seppälä, Ilkka Mononen, Nina Raitakari, Olli T Ala-Korpela, Mika Pajukanta, Päivi Zaitlen, Noah Ayroles, Julien F |
author_facet | Lea, Amanda Subramaniam, Meena Ko, Arthur Lehtimäki, Terho Raitoharju, Emma Kähönen, Mika Seppälä, Ilkka Mononen, Nina Raitakari, Olli T Ala-Korpela, Mika Pajukanta, Päivi Zaitlen, Noah Ayroles, Julien F |
author_sort | Lea, Amanda |
collection | PubMed |
description | Correlation among traits is a fundamental feature of biological systems that remains difficult to study. To address this problem, we developed a flexible approach that allows us to identify factors associated with inter-individual variation in correlation. We use data from three human cohorts to study the effects of genetic and environmental variation on correlations among mRNA transcripts and among NMR metabolites. We first show that environmental exposures (infection and disease) lead to a systematic loss of correlation, which we define as 'decoherence'. Using longitudinal data, we show that decoherent metabolites are better predictors of whether someone will develop metabolic syndrome than metabolites commonly used as biomarkers of this disease. Finally, we demonstrate that correlation itself is under genetic control by mapping hundreds of 'correlation quantitative trait loci (QTLs)'. Together, this work furthers our understanding of how and why coordinated biological processes break down, and points to a potential role for decoherence in disease. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter). |
format | Online Article Text |
id | pubmed-6400502 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-64005022019-03-06 Genetic and environmental perturbations lead to regulatory decoherence Lea, Amanda Subramaniam, Meena Ko, Arthur Lehtimäki, Terho Raitoharju, Emma Kähönen, Mika Seppälä, Ilkka Mononen, Nina Raitakari, Olli T Ala-Korpela, Mika Pajukanta, Päivi Zaitlen, Noah Ayroles, Julien F eLife Genetics and Genomics Correlation among traits is a fundamental feature of biological systems that remains difficult to study. To address this problem, we developed a flexible approach that allows us to identify factors associated with inter-individual variation in correlation. We use data from three human cohorts to study the effects of genetic and environmental variation on correlations among mRNA transcripts and among NMR metabolites. We first show that environmental exposures (infection and disease) lead to a systematic loss of correlation, which we define as 'decoherence'. Using longitudinal data, we show that decoherent metabolites are better predictors of whether someone will develop metabolic syndrome than metabolites commonly used as biomarkers of this disease. Finally, we demonstrate that correlation itself is under genetic control by mapping hundreds of 'correlation quantitative trait loci (QTLs)'. Together, this work furthers our understanding of how and why coordinated biological processes break down, and points to a potential role for decoherence in disease. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter). eLife Sciences Publications, Ltd 2019-03-05 /pmc/articles/PMC6400502/ /pubmed/30834892 http://dx.doi.org/10.7554/eLife.40538 Text en © 2019, Lea et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Genetics and Genomics Lea, Amanda Subramaniam, Meena Ko, Arthur Lehtimäki, Terho Raitoharju, Emma Kähönen, Mika Seppälä, Ilkka Mononen, Nina Raitakari, Olli T Ala-Korpela, Mika Pajukanta, Päivi Zaitlen, Noah Ayroles, Julien F Genetic and environmental perturbations lead to regulatory decoherence |
title | Genetic and environmental perturbations lead to regulatory decoherence |
title_full | Genetic and environmental perturbations lead to regulatory decoherence |
title_fullStr | Genetic and environmental perturbations lead to regulatory decoherence |
title_full_unstemmed | Genetic and environmental perturbations lead to regulatory decoherence |
title_short | Genetic and environmental perturbations lead to regulatory decoherence |
title_sort | genetic and environmental perturbations lead to regulatory decoherence |
topic | Genetics and Genomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6400502/ https://www.ncbi.nlm.nih.gov/pubmed/30834892 http://dx.doi.org/10.7554/eLife.40538 |
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