Novel rare variants in congenital cardiac arrhythmia genes are frequent in drug-induced torsades de pointes.

Marked prolongation of the QT interval and polymorphic ventricular tachycardia following medication (drug-induced long QT syndrome, diLQTS) is a severe adverse drug reaction (ADR) that phenocopies congenital long QT syndrome (cLQTS) and is one of the leading causes for drug withdrawal and relabeling. We evaluated the frequency of rare non-synonymous variants in genes contributing to the maintenance of heart rhythm in cases of diLQTS using targeted capture coupled to next-generation sequencing. Eleven of 31 diLQTS subjects (36%) carried a novel missense mutation in genes with known congenital arrhythmia associations or with a known cLQTS mutation. In the 26 Caucasian subjects, 23% carried a highly conserved rare variant predicted to be deleterious to protein function in these genes compared with only 2-4% in public databases (P<0.003). We conclude that the rare variation in genes responsible for congenital arrhythmia syndromes is frequent in diLQTS. Our findings demonstrate that diLQTS is a pharmacogenomic syndrome predisposed by rare genetic variants.

Operational implementation of prospective genotyping for personalized medicine: the design of the Vanderbilt PREDICT project.

The promise of "personalized medicine" guided by an understanding of each individual's genome has been fostered by increasingly powerful and economical methods to acquire clinically relevant information. We describe the operational implementation of prospective genotyping linked to an advanced clinical decision-support system to guide individualized health care in a large academic health center. This approach to personalized medicine entails engagement between patient and health-care provider, identification of relevant genetic variations for implementation, assay reliability, point-of-care decision support, and necessary institutional investments. In one year, approximately 3,000 patients, most of whom were scheduled for cardiac catheterization, were genotyped on a multiplexed platform that included genotyping for CYP2C19 variants that modulate response to the widely used antiplatelet drug clopidogrel. These data are deposited into the electronic medical record (EMR), and point-of-care decision support is deployed when clopidogrel is prescribed for those with variant genotypes. The establishment of programs such as this is a first step toward implementing and evaluating strategies for personalized medicine.

Predicting clopidogrel response using DNA samples linked to an electronic health record.

Variants in ABCB1 and CYP2C19 have been identified as predictors of cardiac events during clopidogrel therapy initiated after myocardial infarction (MI) or percutaneous coronary intervention (PCI). In addition, PON1 has recently been associated with stent thrombosis. The reported effects of these variants have not yet been replicated in a real-world setting. We used BioVU, the Vanderbilt DNA repository linked to de-identified electronic health records (EHRs), to find data on patients who were on clopidogrel treatment after an MI and/or a PCI; among these, we identified those who had experienced one or more recurrent cardiac events while on treatment (cases, n = 225) and those who had not experienced any cardiac event while on treatment (controls, n = 468). We found that CYP2C19*2 (hazard ratio (HR) 1.54, 95% confidence interval (CI) 1.16-2.06, P = 0.003) and ABCB1 (HR 1.28, 95% CI 1.04-1.57, P = 0.018), but not PON1 (HR 0.91, 95% CI 0.73-1.12, P = 0.370), were associated with recurrent events. In this population, genetic signals for clopidogrel resistance in ABCB1 and CYP2C19 were replicated, supporting the use of EHRs for pharmacogenomic studies. Our data do not show an association between PON1 and recurrent cardiovascular events.

Patterns of unions' successes in hospital elections.

When data from NLRB-conducted hospital elections since 1974 are placed in several environmental, hospital-related, and election-related categories, variations in outcome exist. Although the data do not explain why variations in unions' success occur, they show that the patterns are not random.