The Thrombin Receptor Antagonist for Clinical Event Reduction in Acute Coronary Syndrome (TRA.CER) trial: study design and rationale

Background The protease-activated receptor 1 (PAR-1), the main platelet receptor for thrombin, represents a novel target for treatment of arterial thrombosis, and SCH 530348 is an orally active, selective, competitive PAR-1 antagonist. We designed TRA.CER to evaluate the efficacy and safety of SCH 530348 compared with placebo in addition to standard of care in patients with non-ST-segment elevation (NSTE) acute coronary syndromes (ACS) and high-risk features. Trial design TRA.CER is a prospective, randomized, double-blind, multicenter, phase III trial with an original estimated sample size of 10,000 subjects. Our primary objective is to demonstrate that SCH 530348 in addition to standard of care will reduce the incidence of the composite of cardiovascular death, myocardial infarction (MI), stroke, recurrent ischemia with rehospitalization, and urgent coronary revascularization compared with standard of care alone. Our key secondary objective is to determine whether SCH 530348 will reduce the composite of cardiovascular death, MI, or stroke compared with standard of care alone. Secondary objectives related to safety are the composite of moderate and severe GUSTO bleeding and clinically significant TIMI bleeding. The trial will continue until a predetermined minimum number of centrally adjudicated primary and key secondary end point events have occurred and all subjects have participated in the study for at least I year. The TRA.CER trial is part of the large phase III SCH 530348 development program that includes a concomitant evaluation in secondary prevention. Conclusion TRA.CER will define efficacy and safety of the novel platelet PAR-1 inhibitor SCH 530348 in the treatment of high-risk patients with NSTE ACS in the setting of current treatment strategies. (Am Heart J 2009; 158:327-34.)

Migration in Afro-Brazilian Rural Communities: Crossing Demographic and Genetic Data

Many studies have used genetic markers to understand global migration patterns of our species. However, there are only few studies of human migration on a local scale. We, therefore, researched migration dynamics in three Afro-Brazilian rural communities, using demographic data and ten Ancestry Informative Markers. In addition to the description of migration and marriage structures, we carried out genetic comparisons between the three populations, as well as between locals and migrants from each community. Genetic admixture analyses were conducted according to the gene-identity method, with Sub-Saharan Africans, Amerindians, and Europeans as parental populations. The three analyzed Afro-Brazilian rural communities consisted of 16% to 30% of migrants, most of them women. The age pyramid revealed a gap in the segment of men aged between 20 to 30 yrs. While endogamous marriages predominated, exogamous marriages were mainly patrilocal. Migration dynamics are apparently associated with matrimonial customs and other social practices of such communities. The impact of migration upon the populations` genetic composition was low but showed an increase in European alleles with a concomitant decrease in the Amerindian contribution. Admixture analysis evidenced a higher African contribution to the gene pool of the studied populations, followed by the contribution of Europeans and Amerindians, respectively.

Inferring population history from microsatellite and enzyme data in serially introduced cane toads, Bufo marinus

Much progress has been made on inferring population history from molecular data. However, complex demographic scenarios have been considered rarely or have proved intractable. The serial introduction of the South-Central American cane Load Bufo marinas in various Caribbean and Pacific islands involves four major phases: a possible genetic admixture during the first introduction, a bottleneck associated with founding, a transitory, population boom, and finally, a demographic stabilization. A large amount of historical and demographic information is available for those introductions and can be combined profitably with molecular data. We used a Bayesian approach to combine this information With microsatellite (10 loci) and enzyme (22 loci) data and used a rejection algorithm to simultaneously estimate the demographic parameters describing the four major phases of the introduction history,. The general historical trends supported by microsatellites and enzymes were similar. However, there was a stronger support for a larger bottleneck at introductions for microsatellites than enzymes and for a more balanced genetic admixture for enzymes than for microsatellites. Verb, little information was obtained from either marker about the transitory population boom observed after each introduction. Possible explanations for differences in resolution of demographic events and discrepancies between results obtained with microsatellites and enzymes were explored. Limits Of Our model and method for the analysis of nonequilibrium populations were discussed.

Estimating Two-Stage Models for Genetic Influences on Alcohol, Tobacco or Drug Use Initiation and Dependence Vulnerability in Twin and Family Data

Genetic research on risk of alcohol, tobacco or drug dependence must make allowance for the partial overlap of risk-factors for initiation of use, and risk-factors for dependence or other outcomes in users. Except in the extreme cases where genetic and environmental risk-factors for initiation and dependence overlap completely or are uncorrelated, there is no consensus about how best to estimate the magnitude of genetic or environmental correlations between Initiation and Dependence in twin and family data. We explore by computer simulation the biases to estimates of genetic and environmental parameters caused by model misspecification when Initiation can only be defined as a binary variable. For plausible simulated parameter values, the two-stage genetic models that we consider yield estimates of genetic and environmental variances for Dependence that, although biased, are not very discrepant from the true values. However, estimates of genetic (or environmental) correlations between Initiation and Dependence may be seriously biased, and may differ markedly under different two-stage models. Such estimates may have little credibility unless external data favor selection of one particular model. These problems can be avoided if Initiation can be assessed as a multiple-category variable (e.g. never versus early-onset versus later onset user), with at least two categories measurable in users at risk for dependence. Under these conditions, under certain distributional assumptions., recovery of simulated genetic and environmental correlations becomes possible, Illustrative application of the model to Australian twin data on smoking confirmed substantial heritability of smoking persistence (42%) with minimal overlap with genetic influences on initiation.