Chrissa P. Mower

A Randomized and Clinical Effectiveness Trial Comparing Two Pharmacogenetic Algorithms and Standard Care for Individualizing Warfarin Dosing (CoumaGen-II)

Background— Warfarin is characterized by marked variations in individual dose requirements and a narrow therapeutic window. Pharmacogenetics (PG) could improve dosing efficiency and safety, but clinical trials evidence is meager. Methods and Results— A Randomized and Clinical Effectiveness Trial Comparing Two Pharmacogenetic Algorithms and Standard Care for Individualizing Warfarin Dosing (CoumaGen-II) comprised 2 comparisons: (1) a blinded, randomized comparison of a modified 1-step (PG-1) with a 3-step algorithm (PG-2) (N=504), and (2) a clinical effectiveness comparison of PG guidance with use of either algorithm with standard dosing in a parallel control group (N=1866). A rapid method provided same-day CYP2C9 and VKORC1 genotyping. Primary outcomes were percentage of out-of-range international normalized ratios at 1 and 3 months and percentage of time in therapeutic range. Primary analysis was modified intention to treat. In the randomized comparison, PG-2 was noninferior but not superior to PG-1 for percentage of out-of-range international normalized ratios at 1 month and 3 months and for percentage of time in therapeutic range at 3 months. However, the combined PG cohort was superior to the parallel controls (percentage of out-of-range international normalized ratios 31% versus 42% at 1 month; 30% versus 42% at 3 months; percentage of time in therapeutic range 69% versus 58%, 71% versus 59%, respectively, all P<0.001). Differences persisted after adjustment for age, sex, and clinical indication. There were fewer percentage international normalized ratios ≥4 and ⩽1.5 and serious adverse events at 3 months (4.5% versus 9.4% of patients, P<0.001) with PG guidance. Conclusions— These findings suggest that PG dosing should be considered for broader clinical application, a proposal that is being tested further in 3 major randomized trials. The simpler 1-step PG algorithm provided equivalent results and may be preferable for clinical application. Clinical Trial Registration— URL: http://www.clinicaltrials.gov. Unique identifier: NCT00927862.

Genetic variation at the 9p21 locus predicts angiographic coronary artery disease prevalence but not extent and has clinical utility

BACKGROUND Variants at the 9p21 locus have been associated with coronary heart disease, but their precise disease phenotype and utility for clinical risk assessment are uncertain. METHODS Consenting patients with early-onset angiographic coronary artery disease (CAD) (n = 1,011) were compared with matched subjects (n = 545) free of angiographic disease and with a random population sample (n = 565). Cases and controls were genotyped for 4 variants, and ORs for angio-CAD were determined. Findings were validated in a separate set of cases and controls (n = 1,452). RESULTS Alleles were highly correlated (r(2) > or = 0.9), and all predicted angio-CAD compared with both control groups. Genotype at rs2383206 (minor allele frequency 45.9%), the most predictive (P < .0001), was associated with an adjusted odds ratio for angio-CAD of 1.39 (95% CI, 1.05-1.85) for heterozygote and 1.73 (1.26-2.37) for homozygote risk-allele carriers and explained 21% of population attributable risk and was independent of traditional risk factors and myocardial infarction. For the comparison of combined cases versus combined control samples (N = 3,573), CAD was predicted by high-risk allele homozygosity at P = 9 x 10(-8). Despite this, extent of disease was not increased. Applied to patients with intermediate Framingham risk scores, 9p21 genotyping modified risk classification in 24%. CONCLUSIONS Variants at the 9p21 locus robustly predict angiographic CAD prevalence, independent of standard risk factors, but not CAD extent or myocardial infarction; provide pathophysiological insights; and may be clinically useful in refining coronary heart disease risk classification.

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 Healthcares 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.