Gene-gene interactions between DRD3, MRP4 and CYP2B6 polymorphisms and its influence on the pharmacokinetic parameters of efavirenz in HIV infected patients.

Genetic factors have a significant impact on the PK variability of EFV, much higher than other non-genetic factors, such as demography. In this work we have performed a comprehensive PG analysis of genes encoding the major metabolizing enzymes and transporters of EFV, establishing a clear relationship between the PK parameters and genetic factors, which explain 50% of the variability in EFV PK parameters. The most relevant associations for metabolizing enzymes were found in CYP2B6 (rs3745274), in agreement with previous studies. The influence of transporters on the kinetics of EFV was also proved with significant correlations between the PK parameters of EFV and MRP4 (rs1751034, rs2274407). Analysis of gene-gene interactions with CYP2B6 was particularly useful to reinforce the role of MRP4 and to reveal unknown associations, such as that of DRD3. However, the role of DRD3 cannot be a direct effect but an indirect one due to physical proximity of NAT and the DRD3 locus in the genome.

An overview of STRUCTURE: applications, parameter settings, and supporting software.

OBJECTIVES: We present an up-to-date review of STRUCTURE software: one of the most widely used population analysis tools that allows researchers to assess patterns of genetic structure in a set of samples. STRUCTURE can identify subsets of the whole sample by detecting allele frequency differences within the data and can assign individuals to those sub-populations based on analysis of likelihoods. The review covers STRUCTURE's most commonly used ancestry and frequency models, plus an overview of the main applications of the software in human genetics including case-control association studies (CCAS), population genetics, and forensic analysis. The review is accompanied by supplementary material providing a step-by-step guide to running STRUCTURE. METHODS: With reference to a worked example, we explore the effects of changing the principal analysis parameters on STRUCTURE results when analyzing a uniform set of human genetic data. Use of the supporting software: CLUMPP and distruct is detailed and we provide an overview and worked example of STRAT software, applicable to CCAS. CONCLUSION: The guide offers a simplified view of how STRUCTURE, CLUMPP, distruct, and STRAT can be applied to provide researchers with an informed choice of parameter settings and supporting software when analyzing their own genetic data.

Differentiation of African components of ancestry to stratify groups in a case-control study of a Brazilian urban population.

BACKGROUND: Balancing the subject composition of case and control groups to create homogenous ancestries between each group is essential for medical association studies. METHODS: We explored the applicability of single-tube 34-plex ancestry informative markers (AIM) single nucleotide polymorphisms (SNPs) to estimate the African Component of Ancestry (ACA) to design a future case-control association study of a Brazilian urban sample. RESULTS: One hundred eighty individuals (107 case group; 73 control group) self-described as white, brown-intermediate or black were selected. The proportions of the relative contribution of a variable number of ancestral population components were similar between case and control groups. Moreover, the case and control groups demonstrated similar distributions for ACA <0.25 and >0.50 categories. Notably a high number of outlier values (23 samples) were observed among individuals with ACA <0.25. These individuals presented a high probability of Native American and East Asian ancestral components; however, no individuals originally giving these self-described ancestries were observed in this study. CONCLUSIONS: The strategy proposed for the assessment of ancestry and adjustment of case and control groups for an association study is an important step for the proper construction of the study, particularly when subjects are taken from a complex urban population. This can be achieved using a straight forward multiplexed AIM-SNPs assay of highly discriminatory ancestry markers.

Pharmacogenetics of OATP transporters reveals that SLCO1B1 c.388A>G variant is determinant of increased atorvastatin response.

AIMS: The relationship between variants in SLCO1B1 and SLCO2B1 genes and lipid-lowering response to atorvastatin was investigated. MATERIAL AND METHODS: One-hundred-thirty-six unrelated individuals with hypercholesterolemia were selected and treated with atorvastatin (10 mg/day/4 weeks). They were genotyped with a panel of ancestry informative markers for individual African component of ancestry (ACA) estimation by SNaPshot(®) and SLCO1B1 (c.388A>G, c.463C>A and c.521T>C) and SLCO2B1 (-71T>C) gene polymorphisms were identified by TaqMan(®) Real-time PCR. RESULTS: Subjects carrying SLCO1B1 c.388GG genotype exhibited significantly high low-density lipoprotein (LDL) cholesterol reduction relative to c.388AA+c.388AG carriers (41 vs. 37%, p = 0.034). Haplotype analysis revealed that homozygous of SLCO1B1*15 (c.521C and c.388G) variant had similar response to statin relative to heterozygous and non-carriers. A multivariate logistic regression analysis confirmed that c.388GG genotype was associated with higher LDL cholesterol reduction in the study population (OR: 3.2, CI95%:1.3-8.0, p < 0.05). CONCLUSION: SLCO1B1 c.388A>G polymorphism causes significant increase in atorvastatin response and may be an important marker for predicting efficacy of lipid-lowering therapy.