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Elife. 2019 Mar 5;8. pii: e40538. doi: 10.7554/eLife.40538.

Genetic and environmental perturbations lead to regulatory decoherence.

Author information

1
Department of Ecology and Evolution, Princeton University, Princeton, United States.
2
Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, United States.
3
Department of Medicine, Lung Biology Center, University of California, San Francisco, San Francisco, United States.
4
Department of Medicine, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, United States.
5
Department of Clinical Chemistry, Fimlab Laboratories, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
6
Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
7
Department of Clinical Physiology, Tampere University, Tampere University Hospital, Tampere, Finland.
8
Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.
9
Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland.
10
Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Australia.
11
Computational Medicine, Faculty of Medicine, Biocenter Oulu, University of Oulu, Oulu, Finland.
12
NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland.
13
Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
14
Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.
15
Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, Australia.
16
Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, United States.
#
Contributed equally

Abstract

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).

KEYWORDS:

co-expression; decanalization; decoherence; genetics; genomics; human; human biology; medicine; metabolic syndrome

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