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REVIEW ARTICLE
Year : 2010  |  Volume : 132  |  Issue : 5  |  Page : 567-578

Genomic approaches to coronary artery disease


1 Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom
2 Centre for Chronic Disease Control, New Delhi, India

Correspondence Address:
Sandosh Padmanabhan
Dr Sandosh Padmanabhan, Institute of Cardiovascular and Medical Sciences, University of Glasgow, 126 University Place, Glasgow G12 8TA
United Kingdom
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Source of Support: None, Conflict of Interest: None


PMID: 21150009

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Coronary artery disease (CAD) is a leading cause of death and disability worldwide. In addition to lifestyle and environmental factors which are major aetiologic determinants, there is considerable familial clustering of the disease indicating a genetic component in its causation. Although the total genetic contribution to CAD risk can be quantified, the determination of the size and number of contributing effects is impossible without identifying all CAD susceptibility genes. However, despite extensive studies, strong evidence of a molecular genetic association with coronary artery disease or myocardial infarction remains elusive. Genome wide association studies have been successful in identifying robust associations of single nucleotide polymorphisms (SNP) with CAD. Identifying the causal variant and dissecting pathways linking these variants to disease process is a major challenge. Technologies from whole genome sequencing, proteomics, transcriptomics and metabolomics are now available to extend analysis to a more complete range of potential susceptibility variants, and to support more explicit modelling of the joint effects of genes and environment. The availability of these high throughput technologies does not diminish the importance of rigorous phenotyping and appropriate study designs in all the endeavours to understand the aetiopathogenesis of CAD. Combining classical epidemiology with modern genomics will require collaborative efforts within the cardiovascular disease community at both bench and bedside and this will have the potential to expand our understanding of CAD and translate discoveries into clinically useful applications that will have a major impact on public health.


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