* To identify probands with early onset coronary artery disease from existing epidemiological and clinical trial databases, and prospectively from those attending coronary care units.
* To evaluate family history of coronary artery disease and identify siblings and first degree relatives with confirmed coronary artery disease.
* To recruit probands and their relatives who meet the selection criteria for the study, and take blood and plasma/serum samples for isolation of genomic DNA and intermediate phenotype analysis respectively.
* To construct a database containing pertinent patient information and data on intermediate phenotypes.
* To genotype these individual using a panel of microsatellite markers and carry out linkage analyses to identify regions of the genome predisposing to precocious coronary artery disease.
It has been known for a long time that the pathogenesis of coronary artery disease (CAD) includes a significant genetic component, and that the effect of genes in determining susceptibility to CAD is particularly strong in young age groups. However, because CAD is clearly not inherited as a simple Mendelian fashion, but is instead an example of a complex multifactorial disorder where the phenotype is heavily influenced by environmental factors, dissection of the genetic contribution is complicated. Studies on the genetics of CAD as a complex trait until now have adopted the candidate gene approach, but this type of analysis poses problems, not least because much of the information on pathogenetic mechanisms is derived from consideration of late or end-stage disease. Equally, only those candidates that are readily identifiable in complex biochemical pathways (e.g. lipid metabolism) or processes (e.g. vascular matrix turnover) can be used, with the likely possibility that other, unidentified candidates may be missed, which may be as important. Genes operating in common complex traits can now be mapped without the need to consider function or specific disease mechanisms. Anonymous, highly informative markers spaced throughout the genome, are now being used with increasing frequency to carry out systematic scans of the entire human genome for linkage to common phenotypes using large collections of sibling-pairs and families. Genome-wide searches have revolutionized the identification of susceptibility loci in a wide range of common human diseases such as diabetes, asthma and inflammatory bowel disease by academic groups and commercial enterprises alike. We propose to recruit 2,000 affected sibling-pairs with precocious CAD together with surviving and any additional siblings through a European collaborative network, and to apply similar molecular genetic screening techniques to identify chromosomal regions which are linked to the susceptibility of early onset CAD. We envisage that this approach will facilitate the identification of novel candidate genes which may provide new insights into the pathogenesis of atherosclerosis.
Atherosclerosis, genes, myocardial infarction, coronary artery disease, genetic risk factors, genome screen, sibling-pairs, linkage disequilibrium analysis.