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Towards a molecular systems model of coronary artery disease

Gad Abraham, Oneil G. Bhalala, Paul I.W. de Bakker, Samuli Ripatti, Michael Inouye
doi: https://doi.org/10.1101/003525
Gad Abraham
1Medical Systems Biology, Department of Pathology and Department of Microbiology & Immunology, The University of Melbourne, Parkville, Victoria 3010, Australia
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Oneil G. Bhalala
1Medical Systems Biology, Department of Pathology and Department of Microbiology & Immunology, The University of Melbourne, Parkville, Victoria 3010, Australia
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Paul I.W. de Bakker
2Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
3Department of Epidemiology, University Medical Center Utrecht, Utrecht, The Netherlands
4Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
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Samuli Ripatti
5Institute of Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
6Hjelt Institute, University of Helsinki, Helsinki, Finland
7Department of Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom
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Michael Inouye
1Medical Systems Biology, Department of Pathology and Department of Microbiology & Immunology, The University of Melbourne, Parkville, Victoria 3010, Australia
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  • For correspondence: minouye@unimelb.edu.au
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Abstract

Coronary artery disease (CAD) is a complex disease driven by myriad interactions of genetics and environmental factors. Traditionally, studies have analyzed only one disease factor at a time, providing useful but limited understanding of the underlying etiology. Recent advances in cost-effective and high-throughput technologies, such as single nucleotide polymorphism (SNP) genotyping, exome/genome sequencing, gene expression microarrays and metabolomics assays have enabled the collection of millions of data points in many thousands of individuals. In order to make sense of such ‘omics’ data, effective analytical methods are needed. We review and highlight some of the main results in this area, focusing on integrative approaches that consider multiple modalities simultaneously. Such analyses have the potential to uncover the genetic basis of CAD, produce genomic risk scores (GRS) for disease prediction, disentangle the complex interactions underlying disease, and predict response to treatment.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted March 23, 2014.
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Towards a molecular systems model of coronary artery disease
Gad Abraham, Oneil G. Bhalala, Paul I.W. de Bakker, Samuli Ripatti, Michael Inouye
bioRxiv 003525; doi: https://doi.org/10.1101/003525
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Towards a molecular systems model of coronary artery disease
Gad Abraham, Oneil G. Bhalala, Paul I.W. de Bakker, Samuli Ripatti, Michael Inouye
bioRxiv 003525; doi: https://doi.org/10.1101/003525

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