Pharmacogenetic polymorphisms in Brazilian-born, first-generation Japanese descendants

Brazil hosts the largest Japanese community outside Japan, estimated at 1.5 million individuals, one third of whom are first-generation, Brazilian-born with native Japanese parents. This large community provides a unique opportunity for comparative studies of the distribution of pharmacogenetic polymorphisms in native Japanese versus their Brazilian-born descendants. Functional polymorphisms in genes that modulate drug disposition (CYP2C9, CYP2C19 and GSTM3) or response (VKORC1) and that differ significantly in frequency in native Japanese versus Brazilians with no Japanese ancestry were selected for the present study. Healthy subjects (200 native Japanese and 126 first-generation Japanese descendants) living in agricultural colonies were enrolled. Individual DNA was genotyped using RFLP (GSTM3*A/B) or TaqMan Detection System assays (CYP2C9*2 and *3; CYP2C19*2 and *3; VKORC1 3673G>A, 5808T>G, 6853G>C, and 9041G>A). No difference was detected in the frequency of these pharmacogenetic polymorphisms between native Japanese and first-generation Japanese descendants. In contrast, significant differences in the frequency of each polymorphism were observed between native or first-generation Japanese and Brazilians with no Japanese ancestry. The VKORC1 3673G>A, 6853G>C and 9041G>A single nucleotide polymorphisms were in linkage disequilibrium in both native and first-generation Japanese living in Brazil. The striking similarity in the frequency of clinically relevant pharmacogenetic polymorphisms between Brazilian-born Japanese descendants and native Japanese suggests that the former may be recruited for clinical trials designed to generate bridging data for the Japanese population in the context of the International Conference on Harmonization

Applying Mean-Field Approximation to Continuous Time Markov Chains

The mean-field analysis technique is used to perform analysis of a system with a large number of components to determine the emergent deterministic behaviour and how this behaviour modifies when its parameters are perturbed. The computer science performance modelling and analysis community has found the mean-field method useful for modelling large-scale computer and communication networks. Applying mean-field analysis from the computer science perspective requires the following major steps: (1) describing how the agent populations evolve by means of a system of differential equations, (2) finding the emergent deterministic behaviour of the system by solving such differential equations, and (3) analysing properties of this behaviour. Depending on the system under analysis, performing these steps may become challenging. Often, modifications of the general idea are needed. In this tutorial we consider illustrating examples to discuss how the mean-field method is used in different application areas. Starting from the application of the classical technique, moving to cases where additional steps have to be used, such as systems with local communication. Finally, we illustrate the application of existing model checking analysis techniques