Introduction to the Special Issue: Genome-Wide Association Studies

Introduction to the Special Issue: Genome-Wide Association StudiesComment: Published in at http://dx.doi.org/10.1214/09-STS310 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Selection of single-nucleotide polymorphisms in disease association data

We studied several methods for selecting single-nucleotide polymorphisms (SNPs) in a disease association study. Two major categories for analytical strategy are the univariate and the set selection approaches. The univariate approach evaluates each SNP marker one at a time, while the set selection approach tests disease association of a set of SNP markers simultaneously. We examined various test statistics that can be utilized in testing disease association and also reviewed several multiple testing procedures that can properly control the family-wise error rates when the univariate approach is applied to multiple markers. The set association methods were then briefly reviewed. Finally, we applied these methods to the data from Collaborative Study on the Genetics of Alcoholism (COGA)

Heart failure as an endpoint in heart failure and non-heart failure cardiovascular clinical trials: the need for a consensus definition

Specific criteria have been established to define the occurrence of myocardial infarction (MI) and stroke in cardiovascular clinical trials, but there is not a consistent definition for heart failure. Heart failure events appear to occur at a rate that is similar to stroke and MI in trials of hypertension, hyperlipidaemia, diabetes, and coronary heart disease, yet a consistent approach to defining heart failure events has not yet been realized. The wide range of definitions used in clinical trials makes it difficult to interpret new data in the context of existing literature. This inconsistency has led to challenges in determining the incidence of heart failure in cardiovascular studies and the effects of interventions on these endpoints. This paper examines issues related to defining heart failure events in cardiovascular clinical trials and presents a definition to formally address this issu

Time course analysis of gene expression identifies multiple genes with differential expression in patients with in-stent restenosis

Abstract Background The vascular disease in-stent restenosis (ISR) is characterized by formation of neointima and adverse inward remodeling of the artery after injury by coronary stent implantation. We hypothesized that the analysis of gene expression in peripheral blood mononuclear cells (PBMCs) would demonstrate differences in transcript expression between individuals who develop ISR and those who do not. Methods and Results We determined and investigated PBMC gene expression of 358 patients undergoing an index procedure to treat in de novo coronary artery lesions with bare metallic stents, using a novel time-varying intercept model to optimally assess the time course of gene expression across a time course of blood samples. Validation analyses were conducted in an independent sample of 97 patients with similar time-course blood sampling and gene expression data. We identified 47 probesets with differential expression, of which 36 were validated upon independent replication testing. The genes identified have varied functions, including some related to cellular growth and metabolism, such as the NAB2 and LAMP genes. Conclusions In a study of patients undergoing bare metallic stent implantation, we have identified and replicated differential gene expression in peripheral blood mononuclear cells, studied across a time series of blood samples. The genes identified suggest alterations in cellular growth and metabolism pathways, and these results provide the basis for further specific functional hypothesis generation and testing of the mechanisms of ISR.http://deepblue.lib.umich.edu/bitstream/2027.42/112500/1/12920_2010_Article_214.pd

Designing comparative effectiveness trials of surgical ablation for atrial fibrillation: Experience of the Cardiothoracic Surgical Trials Network

ObjectiveSince the introduction of the cut-and-sew Cox maze procedure for atrial fibrillation, there has been substantial innovation in techniques for ablation. Use of alternative energy sources for ablation simplified the procedure and has resulted in dramatic increase in the number of patients with atrial fibrillation treated by surgical ablation. Despite its increasingly widespread adoption, there is lack of rigorous clinical evidence to establish this procedure as an effective clinical therapy.MethodsThis article describes a comparative effectiveness randomized trial, supported by the Cardiothoracic Surgical Clinical Trials Network, of surgical ablation with left atrial appendage closure versus left atrial appendage closure alone in patients with persistent and long-standing persistent atrial fibrillation undergoing mitral valve surgery. Nested within this trial is a further randomized comparison of 2 different lesions sets: pulmonary vein isolation and the full maze lesion set.ResultsThis article addresses trial design challenges, including how best to characterize the target population, operationalize freedom from atrial fibrillation as a primary end point, account for the impact of antiarrhythmic drugs, and measure and analyze secondary end points, such as postoperative atrial fibrillation load.ConclusionsThis article concludes by discussing how insights that emerge from this trial may affect surgical practice and guide future research in this area

Effect of high-dose plerixafor on CD34+ cell mobilization in healthy stem cell donors: results of a randomized crossover trial

Hematopoietic stem cells can be mobilized from healthy donors using single-agent plerixafor without granulocyte colony-stimulating factor and, following allogeneic transplantation, can result in sustained donor-derived hematopoiesis. However, when a single dose of plerixafor is administered at a conventional 240 μg/kg dose, approximately one-third of donors will fail to mobilize the minimally acceptable dose of CD34+ cells needed for allogeneic transplantation. We conducted an open-label, randomized trial to assess the safety and activity of high-dose (480 μg/kg) plerixafor in CD34+ cell mobilization in healthy donors. Subjects were randomly assigned to receive either a high dose or a conventional dose (240 μg/kg) of plerixafor, given as a single subcutaneous injection, in a two-sequence, two-period, crossover design. Each treatment period was separated by a 2-week minimum washout period. The primary endpoint was the peak CD34+ count in the blood, with secondary endpoints of CD34+ cell area under the curve (AUC), CD34+ count at 24 hours, and time to peak CD34+ following the administration of plerixafor. We randomized 23 subjects to the two treatment sequences and 20 subjects received both doses of plerixafor. Peak CD34+ count in the blood was significantly increased (mean 32.2 versus 27.8 cells/μL, P=0.0009) and CD34+ cell AUC over 24 hours was significantly increased (mean 553 versus 446 h cells/μL,

Nine-Year Effects of 3.7 Years of Intensive Glycemic Control on Cardiovascular Outcomes

In the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, ∼4 years of intensive versus standard glycemic control in participants with type 2 diabetes and other cardiovascular risk factors had a neutral effect on the composite cardiovascular outcome, increased cardiovascular and total mortality, and reduced nonfatal myocardial infarction. Effects of the intervention during prolonged follow-up were analyzed

Statistical design of personalized medicine interventions: The Clarification of Optimal Anticoagulation through Genetics (COAG) trial

<p>Abstract</p> <p>Background</p> <p>There is currently much interest in pharmacogenetics: determining variation in genes that regulate drug effects, with a particular emphasis on improving drug safety and efficacy. The ability to determine such variation motivates the application of personalized drug therapies that utilize a patient's genetic makeup to determine a safe and effective drug at the correct dose. To ascertain whether a genotype-guided drug therapy improves patient care, a personalized medicine intervention may be evaluated within the framework of a randomized controlled trial. The statistical design of this type of personalized medicine intervention requires special considerations: the distribution of relevant allelic variants in the study population; and whether the pharmacogenetic intervention is equally effective across subpopulations defined by allelic variants.</p> <p>Methods</p> <p>The statistical design of the Clarification of Optimal Anticoagulation through Genetics (COAG) trial serves as an illustrative example of a personalized medicine intervention that uses each subject's genotype information. The COAG trial is a multicenter, double blind, randomized clinical trial that will compare two approaches to initiation of warfarin therapy: genotype-guided dosing, the initiation of warfarin therapy based on algorithms using clinical information and genotypes for polymorphisms in <it>CYP2C9 </it>and <it>VKORC1</it>; and clinical-guided dosing, the initiation of warfarin therapy based on algorithms using only clinical information.</p> <p>Results</p> <p>We determine an absolute minimum detectable difference of 5.49% based on an assumed 60% population prevalence of zero or multiple genetic variants in either <it>CYP2C9 </it>or <it>VKORC1 </it>and an assumed 15% relative effectiveness of genotype-guided warfarin initiation for those with zero or multiple genetic variants. Thus we calculate a sample size of 1238 to achieve a power level of 80% for the primary outcome. We show that reasonable departures from these assumptions may decrease statistical power to 65%.</p> <p>Conclusions</p> <p>In a personalized medicine intervention, the minimum detectable difference used in sample size calculations is not a known quantity, but rather an unknown quantity that depends on the genetic makeup of the subjects enrolled. Given the possible sensitivity of sample size and power calculations to these key assumptions, we recommend that they be monitored during the conduct of a personalized medicine intervention.</p> <p>Trial Registration</p> <p>clinicaltrials.gov: NCT00839657</p