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Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology

Drenos, F; Grossi, E; Buscema, M; Humphries, SE; (2015) Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology. PLoS One , 10 (5) , Article e0125876. 10.1371/journal.pone.0125876. Green open access

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Abstract

We present the use of innovative machine learning techniques in the understanding of Coronary Heart Disease (CHD) through intermediate traits, as an example of the use of this class of methods as a first step towards a systems epidemiology approach of complex diseases genetics. Using a sample of 252 middle-aged men, of which 102 had a CHD event in 10 years follow-up, we applied machine learning algorithms for the selection of CHD intermediate phenotypes, established markers, risk factors, and their previously associated genetic polymorphisms, and constructed a map of relationships between the selected variables. Of the 52 variables considered, 42 were retained after selection of the most informative variables for CHD. The constructed map suggests that most selected variables were related to CHD in a context dependent manner while only a small number of variables were related to a specific outcome. We also observed that loss of complexity in the network was linked to a future CHD event. We propose that novel, non-linear, and integrative epidemiological approaches are required to combine all available information, in order to truly translate the new advances in medical sciences to gains in preventive measures and patients care.

Type: Article
Title: Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pone.0125876
Publisher version: http://dx.doi.org/10.1371/journal.pone.0125876
Language: English
Additional information: © 2015 Drenos et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Cardiovascular Science
URI: https://discovery.ucl.ac.uk/id/eprint/1471726
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