To investigate the role in coronary heart disease (CHD) of intragenic variation in a network of six genes affecting lipoprotein transport and metabolism.

BACKGROUND:

In recent years, a number of candidate genetic variants (e.g., single nucleotide polymorphisms, SNPs) have been reported to be associated with coronary heart disease (CHD). However, these association studies have suffered from variability and failures of replication. This may result in part from selection of marker SNPs in linkage disequilibrium (LD) with true disease-related SNPs or with other effect-modulating genetic variants. Other issues include the play of chance in samples of limited size, population stratification artifacts, and small effect size for single SNPs. A recent discovery is that the genome is organized into largely invariant DNA fragments at the population level characterized by infrequent recombination events interspersed with "hotspots" of recombination and designated "haplotype blocks". These haplotype blocks can be determined by creating a dense map of SNPs across the gene of interest and analyzing population level LD. A few SNPs then can be chosen that designate ("tag") each haplotype block and used to comprehensively assess disease associations across the entire gene. Applying this approach to multiple genes in pathways critical to vascular health and assessing combinations of genes is likely to increase the power to discover genetic associations with CHD risk.

DESIGN NARRATIVE:

The study will establish high density SNP maps across exons, splice regions, and 5' and 3' regulatory regions of 6 genes that play key roles in lipoprotein transport and metabolism (ABCA1, CETP, LCAT, HL, LPL, SRB1); introns will be examined for 2 of the genes (CETP, LPL). By analyzing combinations of haplotype-tagging (ht) SNPs, "genetic burden" can be scored and correlated with CHD risk at 4 levels: 1) biomarker (lipid/lipoprotein levels), 2) anatomic (angiographic) CHD, 3) clinical outcome (death/MI), and 4) (exploratory) response to lipid-lowering. Testing will be performed in 3 large, distinct, but complementary Utah populations at primary or secondary risk of premature CHD. Testing will occur in 2 stages to establish reproducibility: an initial screening phase followed by a confirmation phase (for genetic markers and combinations showing promise) in a larger, independent sample. The study will employ novel methods that combine high-throughput SNP discovery and genotyping capability with genetic epidemiological methods to identify the haplotype blocks within and surrounding the genes of interest, identify htSNPs, and assess disease associations with individual and combinations of htSNPs ("genetic burden"). To this, the study brings large, well characterized databases, assembled and followed for up to 9 years, which will be further expanded under the current project.

Men aged ≤60 years and women ≤70 years. Approximately 3,000 subjects (∼2,000 CAD cases and ∼1,000 angiographically normal controls, matched 2:1 for sex, age, and date of registry entry) were selected. A separate set of cases with highly familial premature CAD (first-degree relative with CHD onset <55 in men, <65 in women) from the University of Utah Cardiovascular Genetics Family Tree Registry and a separate set of controls (randomly invited from a public records database) were enrolled as a replication set.

Study subjects for the primary association study were selected from Intermountain Healthcare's ongoing Angiographic Registry and DNA Bank.