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Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4423836/ https://www.ncbi.nlm.nih.gov/pubmed/25951190 http://dx.doi.org/10.1371/journal.pone.0125876 |
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author | Drenos, Fotios Grossi, Enzo Buscema, Massimo Humphries, Steve E. |
author_facet | Drenos, Fotios Grossi, Enzo Buscema, Massimo Humphries, Steve E. |
author_sort | Drenos, Fotios |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4423836 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-44238362015-05-13 Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology Drenos, Fotios Grossi, Enzo Buscema, Massimo Humphries, Steve E. PLoS One Research Article 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. Public Library of Science 2015-05-07 /pmc/articles/PMC4423836/ /pubmed/25951190 http://dx.doi.org/10.1371/journal.pone.0125876 Text en © 2015 Drenos et al http://creativecommons.org/licenses/by/4.0/ 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 properly credited. |
spellingShingle | Research Article Drenos, Fotios Grossi, Enzo Buscema, Massimo Humphries, Steve E. Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology |
title | Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology |
title_full | Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology |
title_fullStr | Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology |
title_full_unstemmed | Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology |
title_short | Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology |
title_sort | networks in coronary heart disease genetics as a step towards systems epidemiology |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4423836/ https://www.ncbi.nlm.nih.gov/pubmed/25951190 http://dx.doi.org/10.1371/journal.pone.0125876 |
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