Gene x environment interactions as dynamical systems: clinical implications

Sarah S. Knox; Sarah S. Knox

doi:10.3934/molsci.2016.1.1

AIMS Molecular Science

2016, Volume 3, Issue 1: 1-11. doi: 10.3934/molsci.2016.1.1

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Gene x environment interactions as dynamical systems: clinical implications

Sarah S. Knox ^,

Department of Epidemiology, School of Public Health, West Virginia University Box 9190, Morgantown, WV 26506, USA

Received: 29 October 2015 Accepted: 21 December 2015 Published: 28 December 2015

The etiology and progression of the chronic diseases that account for the highest rates of mortality in the US, namely, cardiovascular diseases and cancers, involve complex gene x environment interactions. Yet despite the general agreement in the medical community given to this concept, there is a widespread lack of clarity as to what the term ‘interaction’ actually means. The consequence is the use of linear statistical methods to describe processes that are biologically nonlinear, resulting in clinical applications that are often not optimal. Gene x environment interactions are characterized by dynamic, nonlinear molecular networks that change and evolve over time; and by emergent properties that cannot be deduced from the characteristics of their individual subcomponents. Given the nature of these systemic properties, reductionist methods are insufficient for fully providing the information relevant to improving therapeutic outcomes. The purpose of this article is to provide an overview of these concepts and their relevance to prevention and interventions.
- genes,
- environment,
- dynamical systems,
- clinical care
Citation: Sarah S. Knox. Gene x environment interactions as dynamical systems: clinical implications[J]. AIMS Molecular Science, 2016, 3(1): 1-11. doi: 10.3934/molsci.2016.1.1

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Abstract

The etiology and progression of the chronic diseases that account for the highest rates of mortality in the US, namely, cardiovascular diseases and cancers, involve complex gene x environment interactions. Yet despite the general agreement in the medical community given to this concept, there is a widespread lack of clarity as to what the term ‘interaction’ actually means. The consequence is the use of linear statistical methods to describe processes that are biologically nonlinear, resulting in clinical applications that are often not optimal. Gene x environment interactions are characterized by dynamic, nonlinear molecular networks that change and evolve over time; and by emergent properties that cannot be deduced from the characteristics of their individual subcomponents. Given the nature of these systemic properties, reductionist methods are insufficient for fully providing the information relevant to improving therapeutic outcomes. The purpose of this article is to provide an overview of these concepts and their relevance to prevention and interventions.

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