Invited critical reviewCardiovascular diseases and genome-wide association studies
Section snippets
Introduction: cardiovascular diseases: common disorders with important genetic component
Cardiovascular diseases (CVDs) are the leading cause of death in the world. Based on World Health Organization, 17.1 million people died from CVDs in 2004 and it is estimated that by 2030, approximately 23.6 million deaths will be recorded due to CVDs, mainly from heart disease and stroke [1]. The aetiology of CVDs is multifactorial, where a complex combination of environmental, genetic and clinical risk factors seems to play determinant role [2]. In fact, the pathogenesis of coronary heart
Literature search
The GWAS investigator of HuGENavigator engine [21] and the NHGRI Catalog of published GWAS (http://www.genome.gov/gwasstudies, assessed May 2011) [22] were used in order to assess GWAS published between 2007 and 2011, using the keywords of “cardiovascular diseases”, “coronary heart disease”, “coronary artery disease”, “diabetes”, “obesity”, “hypertension”, “blood pressure”, “anthropometric measurements”, “response to medication” and “lipids”. In order to confirm the retrieved findings, we have
Brief overview of GWAS on cardiovascular diseases and their related quantitative traits
To date, a vast number of GWAS focusing on about 150 distinct diseases and QTs have reported several hundreds significant SNP-trait associations. GWAS have been conducted on cardiovascular events (CHD) and specifically to myocardial infraction (MI) and they have reported the association of at least 16 genetic variants found in 15 genes (Supplementary Table 1). They have identified SNPs on chromosomal regions 1p13, 1q41, 2q36, 3q22, 6p24, 6q25, 7q22, 9p21, 10q11, 10q23.2, 10p11.23, 11q22.3,
Current GWAS designs
GWAS involve various tiered designs including case–control and cohort studies for the identification of trait/disease-SNP associations. These strategies allow affordable procedures to be carried out by conducting a genome-wide scan in a discovery set in order to select a core of significantly associated SNPs that will be subsequently genotyped in larger replication sets for confirmation [49]. These intricate designs involve more and more tiers according to the complexity and originality of the
Concluding remarks and perspectives
GWAS have revealed many novel genetic risk variants in CVDs, making it an auspicious era for the better understanding of genetics. For the time being, we need to grasp the unexpected involvement of certain functional and mechanistic pathways identified in CVDs processes involving many QTs. These have to be extensively investigated in parallel with the pathology itself. Future GWAS must also detect low MAF and rare variants, and include GxG, GxE and well-designed candidate gene studies (in term
Disclosures
No conflicts of interest.
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All authors contributed equally to this work.