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.

Background

In patients with acute coronary syndrome (ACS), elevated levels of soluble CD40 ligand (sCD40L) are associated with increased risk of cardiovascular events. We evaluated sCD40L levels and future cardiovascular events in patients not experiencing ACS.

Methods

Serum sCD40L levels were measured in 909 patients undergoing angiography. A three-way matching scheme (age, gender and catheterization time period) identified 303 patients with coronary artery disease (CAD) who experienced a cardiac event within 1 year (CAD/event), 303 patients with CAD free of events (CAD/no event) and 303 patients without CAD and free of events (no CAD).

Results

Average age was 64 ± 11 years; 74% were males. Median (± SE) sCD40L levels were higher for no CAD patients (335 ± 60 pg/ml) compared to CAD (248 ± 65 pg/ml, p = 0.01) and to CAD/event (233 ± 63 pg/ml, p < 0.001). There was no significant difference in median sCD40L levels between CAD/no event and CAD/event patients. Higher sCD40L quartiles were associated with a significant decrease in the risk of CAD/event versus no CAD (quartile 4 versus quartile 1: odds ratio = 0.59, p = 0.03). There was a nonsignificant trend towards a decreased risk of CAD as compared to no CAD, and for CAD/event versus CAD.

Conclusions

In non-ACS patients, higher sCD40L levels were associated with a decreased risk of CAD. This novel interaction of sCD40L raises interesting questions for CAD pathogenesis.

Objective

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=1,918) and CAD-free controls (N=1,032) 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 genetic risk score (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 (OR) =1.24 (95% CI 1.16–1.33) per risk allele, p=8.2×10−11, adjusted OR=2.03 (1.53–2.70), 4th vs. 1st quartile. GRS5 had minor impact on area under the receiver-operating characteristic curve (p>0.05) but resulted in substantial net reclassification improvement: 0.16 overall, 0.28 in intermediate risk patients (both p<0.0001). GRS5 predicted familial CAD with similar magnitude in the validation set.

Conclusions

CorGen 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.

Background

A chromosome 9p21 locus is associated with coronary heart disease (CHD) in at least 25 independent populations, but multiple clinically-distinct phenotypes have been evaluated. Utilizing angiographic coronary artery disease (CAD) phenotyping, this study evaluated whether 9p21 single nucleotide polymorphisms (SNPs) predict ischemic events (e.g., myocardial infarction [MI]) among CAD patients.

Methods and Results

Patients undergoing coronary angiography during 1994-2007 (population set 1A: N=1,748; set 1B: N=1,014) were evaluated for association of a 9p21 tagging SNP (rs2383206, A→G) with incident MI and death events among patients with angiographically-significant CAD. Another hypothesis evaluated rs2383206 in two additional angiographic sets of both CAD and non-CAD patients (set 2A: N=2,122; set 2B: N=1,466) for prevalent MI vs. CAD/no MI (and for MI vs. non-CAD and CAD/no MI vs. non-CAD). No association of rs2383206 was found with events in set 1A (OR=0.95 per G allele, p-trend=0.48) and set 1B (OR=0.91 per G allele, p-trend=0.28), or with MI vs. CAD/no MI in set 2A (OR=0.96 per G allele, p-trend=0.57) and set 2B (OR=0.89 per G allele, p-trend=0.21). In contrast, rs2383206 was associated with CAD/no MI compared with non-CAD (set 2A: p-trend=0.0001; set 2B: p-trend=0.0008).

Conclusions

The chromosome 9p21 locus was not associated with incident events or prevalent MI, although it did predict CAD diagnosis. This contradicts reports of a 9p21 association with MI, likely due to differences in phenotype assignment. This suggests that high-quality phenotyping for CAD and MI is required to dissect the specific contributions of genetic variation to each stage of CHD pathophysiology.

Coronary artery disease (CAD) is common and multi-factorial. Members of the Church of Jesus Christ of Latter-day Saints (LDS, or Mormons) in Utah may have lower cardiac mortality than other Utahns and the US population. While the LDS proscription of smoking likely contributes to lower cardiac risk, it is unknown whether other shared behaviors also contribute. This study evaluated potential CAD-associated effects of fasting. Patients (N1=4,629) enrolled in the Intermountain Heart Collaborative Study registry (1994-2002) were evaluated for association of religious preference with CAD diagnosis (≥70% coronary stenosis on angiography) or no CAD (normal coronaries, <10% stenosis). Consequently, another set of patients (N2=448) were surveyed (2004-2006) for association of behavioral factors with CAD, with the primary variable being routine fasting (i.e., abstinence from food and drink). Secondary survey measures included proscription of alcohol, tea, and coffee, social support, and religious worship patterns. In population 1 (initial), 61% of LDS and 66% of all others had CAD (adjusted [including for smoking]: odds ratio [OR]=0.81; p=0.009). In population 2 (survey), fasting was associated with lower risk of CAD (64% vs. 76% CAD; OR=0.55, CI=0.35, 0.87; p=0.010) and this remained after adjustment for traditional risk factors (OR=0.46, CI=0.27, 0.81; p=0.007). Fasting was also associated with lower diabetes prevalence (p=0.048). In regression models entering other secondary behavioral measures, fasting remained significant with similar effect size. In conclusion, not only proscription of tobacco, but also routine periodic fasting was associated with lower risk of CAD.

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. Further, differentiation of predictive ability by endpoint (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=5,148) with MI (n=1,693) and angiographically-defined CAD (=1 lesion of =70% stenosis, n=1,967) were compared to MI-free (n=3,455) and non-CAD patients (n=1,122), respectively. Due to linkage disequilibrium, MMP-1 and MMP-3 SNPs (chromosome 11) were combined, as were the two MMP-9 SNPs.

Results

For MI, only MMP-9 group CT/RQ (OR=1.25, p=0.007 vs. wild-type CC/RR) had greater MI risk, with TT/QQ having a weak trend (OR=1.43, p=0.10). These findings remained (CT/RQ) or were strengthened (TT/QQ) after full adjustment. For CAD, association was found for MMP-1/-3 groups 2G1G/6A6A (OR=1.45, p=0.022), 2G1G/6A5A (OR=1.49, p=0.001), 2G1G/5A5A (OR=1.64, p=0.003), and 1G1G/5A5A (OR=1.35, p=0.035) compared to wild-type.

Conclusions

Composite MMP-9 genotypes but not other SNPs were associated with MI, while MMP-1/-3 genotypes were CAD-associated. The largest MMP/TIMP gene study to date, this study suggests care in selection and definition of clinical phenotypes. Further, this suggests that the evaluated SNPs only approximately account for intra-genic variation in these genes and that comprehensive evaluation of all variation in these genes should better elucidate associations with MI and CAD phenotypes.

Summary

Introduction

By guiding initial warfarin dose, pharmacogenetic (PGx) algorithms may improve the safety of warfarin initiation. However, once INR response is known, the contribution of PGx to dose refinements is uncertain. This study sought to develop and validate clinical and PGx dosing algorithms for warfarin dose refinement on days 6–11 after therapy initiation.

Materials and Methods

An international sample of 2,022 patients at 13 medical centers on 3 continents provided clinical, INR, and genetic data at treatment days 6–11 to predict therapeutic warfarin dose. Independent derivation and retrospective validation samples were composed by randomly dividing the population (80%/20%). Prior warfarin doses were weighted by their expected effect on S-warfarin concentrations using an exponential-decay pharmacokinetic model. The INR divided by that “effective” dose constituted a treatment response index.

Results

Treatment response index, age, amiodarone, body surface area, warfarin indication, and target INR were associated with dose in the derivation sample. A clinical algorithm based on these factors was remarkably accurate: in the retrospective validation cohort its R2 was 61.2% and median absolute error (MAE) was 5.0 mg/week. Accuracy and safety was confirmed in a prospective cohort (N=43). CYP2C9 variants and VKORC1-1639 G→A were significant dose predictors in both the derivation and validation samples. In the retrospective validation cohort, the PGx algorithm had: R2= 69.1% (P<0.05 vs. clinical algorithm), MAE= 4.7 mg/week.

Conclusions

A pharmacogenetic warfarin dose-refinement algorithm based on clinical, INR, and genetic factors can explain at least 69.1% of therapeutic warfarin dose variability after about one week of therapy.