Common Variants in 6 Lipid-Related Genes Discovered by High-Resolution DNA Melting Analysis and Their Association with Plasma Lipids.

BACKGROUND: Total cholesterol was among the earliest identified risk factors for coronary heart disease (CHD). We sought to identify genetic variants in six genes associated with lipid metabolism and estimate their respective contribution to risk for CHD. METHODS: For 6 lipid-associated genes (LCAT, CETP, LIPC, LPL, SCARB1, and ApoF) we scanned exons, 5' and 3' untranslated regions, and donor and acceptor splice sites for variants using Hi-Res Melting® curve analysis (HRMCA) with confirmation by cycle sequencing. Healthy subjects were used for SNP discovery (n=64), haplotype determination/tagging SNP discovery (n=339), and lipid association testing (n=786). RESULTS: In 17,840 bases of interrogated sequence, 90 variant SNPs were identified; 19 (21.1%) previously unreported. Thirty-four variants (37.8%) were exonic(16 non-synonymous), 28 (31.1%) in intron-exon boundaries, and 28 (31.1%) in the 5' and 3' untranslated regions. Compared to cycle sequencing, HRMCA had sensitivity of 99.4% and specificity of 97.7%. Tagging SNPs (n=38) explained >90% of the variation in the 6 genes and identified linkage disequilibrium (LD) groups. Significant beneficial lipid profiles were observed for CETP LD group 2, LIPC LD groups 1 and 7, and SCARB1 LD groups 1, 3 and 4. Risk profiles worsened for CETP LD group 3, LPL LD group 4. CONCLUSIONS: These findings demonstrate the feasibility, sensitivity, and specificity of HRMCA for SNP discovery. Variants identified in these genes may be used to predict lipid-associated risk and reclassification of clinical CHD risk.

Joint effects of common genetic variants from multiple genes and pathways on the risk of premature coronary artery disease.

OBJECTIVE: The aim of this study is to discover common variants in 6 lipid metabolic genes and construct and validate a genetic risk score (GRS) based on the joint effects of genetic variants in multiple genes from lipid and other pathobiologic pathways. BACKGROUND: Explaining the genetic basis of coronary artery disease (CAD) is incomplete. Discovery and aggregation of genetic variants from multiple pathways may advance this objective. METHODS: Premature CAD cases (n = 1,947) and CAD-free controls (n = 1,036) were selected from our angiographic registry. In a discovery phase, single nucleotide polymorphisms (SNPs) at 56 loci from internal discovery and external reports were tested for associations with biomarkers and CAD: 28 promising SNPs were then tested jointly for CAD associations, and a GRS consisting of SNPs contributing independently was constructed and validated in a replication set of familial cases and population-based controls (n = 1,320). RESULTS: Five variants contributed jointly to CAD prediction in a multigenic GRS model: odds ratio 1.24 (95% CI 1.16-1.33) per risk allele, P = 8.2 x 10(-11), adjusted OR 2.03 (1.53-2.70), fourth versus first quartile. 5-SNP genetic risk score had minor impact on area under the receiver operating characteristic curve (P > .05) but resulted in substantial net reclassification improvement: 0.16 overall, 0.28 in intermediate-risk patients (both P < .0001). GRS(5) predicted familial CAD with similar magnitude in the validation set. CONCLUSIONS: The Intermountain Healthcare's Coronary Genetics study demonstrates the ability of a multigenic, multipathway GRS to improve discrimination of angiographic CAD. Genetic risk scores promise to increase understanding of the genetic basis of CAD and improve identification of individuals at increased CAD risk.

Rapid melting curve analysis for genetic variants that underlie inter-individual variability in stable warfarin dosing.

Warfarin anticoagulation therapy is complicated by its narrow therapeutic index and by wide inter-individual differences in dosing requirements arising, in part, from genetic factors. The present report describes the development, validation and feasibility testing of a rapid genotyping assay that concurrently detects the CYP2C9*2 and *3 variants along with the VKORC1 C1173T polymorphism. The study employed melting curve analysis using labeled probes and compared two detection instruments (the HR-1 and the R.A.P.I.D. LT) to two previously validated methods, 5' nuclease allelic discrimination (Taqman) assay and cycle sequencing. The HR-1 detected 189 true negatives and 113 true positives; 1 wild-type sample was mistyped as a heterozygote by both instruments. Sequencing of that sample confirmed it to be a CC homozygote; however, a rare C > T polymorphism was discovered 1 base 5' from the *2 polymorphic site, presumably causing the mistaken genotype by melting curve. Both methods had sensitivity = 1.00 and specificity > 0.99. Combined with a method for rapid buccal swab DNA extraction, genotyping results were obtained in a median of 59 min. These methods should facilitate genotype-driven warfarin dosing in "real-time" clinical practice.

Associations with myocardial infarction of six polymorphisms selected from a three-stage genome-wide association study.

BACKGROUND: Coronary heart disease, including its clinical manifestation, myocardial infarction (MI), is a common, complex disease with a substantive genetic component. State-of-the-art genetic epidemiology evaluates thousands of single nucleotide polymorphisms (SNPs) in association with disease cases and controls. In an independent but demographically similar population, this study tested 6 SNPs that were previously reported to be associated with MI. METHODS: Patients hospitalized for an acute MI (n = 413) at an early age (men < 55 years, women < 65 years) were compared with age-discordant (men > or = 65 years, women > or = 70 years) control patients (n = 792) who had no MI history and no hospitalization for MI at index angiography or during longitudinal follow-up. Six SNPs were genotyped in the genes palladin, ROS1, TAS2R50, OR13G1, and ZNF627. RESULTS: Findings were not different from the null hypothesis, with ZNF627 (AG vs. GG: odds ratio [OR] 1.47, P = .16; AA vs. GG: OR 1.20, P = .50) and both ROS1 SNPs (GG vs AA: OR 0.72, P = .21; CC vs GG: OR 0.74, P = .24) showing potentially interesting ORs but nonsignificant probabilities. After full adjustment for all SNPs and covariables, only the ZNF627 heterozygote genotype had OR > 1.5 (P = .14). Comparison of MI cases with controls without obstructive coronary artery disease and analyses stratified by sex provided similar findings. CONCLUSIONS: Six SNPs previously reported to be associated with MI were not validated, suggesting that further investigation is needed to verify the applicability of those SNPs to cardiovascular medicine. These findings emphasize the high potential for false-positive results even in staged genome-wide association studies and further emphasize the need for continued refinement of cardiovascular genetic methodologies for clinical application.

Multiple-polymorphism associations of 7 matrix metalloproteinase and tissue inhibitor metalloproteinase genes with myocardial infarction and angiographic coronary artery disease.

BACKGROUND: Single nucleotide polymorphisms (SNPs) in matrix metalloproteinase (MMP) genes may be associated with myocardial infarction (MI) and coronary artery disease (CAD), but studies of multiple MMP genes and their tissue inhibitors (TIMPs) are scarce. Furthermore, differentiation of predictive ability by end point (MI vs CAD) has not been addressed. This study evaluated the association with MI of SNPs in genes encoding MMPs 1, 2, 3, and 9 and TIMPs 1, 2, and 3. METHODS: Genotypes of patients (N = 5148) with MI (n = 1693) and angiographically defined CAD (> or = 1 lesion of > or = 70% stenosis, n = 1967) were compared with MI-free (n = 3455) and non-CAD patients (n = 1122), respectively. Because of linkage disequilibrium, MMP-1 and MMP-3 SNPs (chromosome 11) were combined, as were the 2 MMP-9 SNPs. RESULTS: For MI, only MMP-9 group CT/RQ (odds ratio [OR] 1.25, P = .007 vs wild-type CC/RR) had greater MI risk, with TT/QQ having a weak trend (OR 1.43, P = .10). These findings remained (CT/RQ) or were strengthened (TT/QQ) after full adjustment. For CAD, association was found for MMP-1/MMP-3 groups 2G1G/6A6A (OR 1.45, P = .022), 2G1G/6A5A (OR = 1.49, P = .001), 2G1G/5A5A (OR 1.64, P = .003), and 1G1G/5A5A (OR 1.35, P = .035) compared to wild type. CONCLUSIONS: Composite MMP-9 genotypes but not other SNPs were associated with MI, whereas MMP-1/MMP-3 genotypes were CAD-associated. The largest MMP/TIMP gene study to date, this study suggests care in selection and definition of clinical phenotypes. Furthermore, this suggests that the evaluated SNPs only approximately account for intragenic variation in these genes and that comprehensive evaluation of all variations in these genes should better elucidate associations with MI and CAD phenotypes.