Statistical Optimization of Pharmacogenomics Association Studies: Key Considerations from Study Design to Analysis.

Research in human genetics and genetic epidemiology has grown significantly over the previous decade, particularly in the field of pharmacogenomics. Pharmacogenomics presents an opportunity for rapid translation of associated genetic polymorphisms into diagnostic measures or tests to guide therapy as part of a move towards personalized medicine. Expansion in genotyping technology has cleared the way for widespread use of whole-genome genotyping in the effort to identify novel biology and new genetic markers associated with pharmacokinetic and pharmacodynamic endpoints.

Mitochondrial genomics and CD4 T-cell count recovery after antiretroviral therapy initiation in AIDS clinical trials group study 384.

Background: Mitochondrial DNA (mtDNA) variation has been associated with time to progression to AIDS and adverse effects from antiretroviral therapy (ART). In this study, full mitochondrial DNA (mtDNA) sequence data from US-based adult participants in the AIDS Clinical Trials Group study 384 was used to assess associations between mtDNA variants and CD4 T-cell recovery with ART.

Methods: Full mtDNA sequence was determined using chip-based array sequencing.

The effects of linkage disequilibrium in large scale SNP datasets for MDR.

Background: In the analysis of large-scale genomic datasets, an important consideration is the power of analytical methods to identify accurate predictive models of disease. When trying to assess sensitivity from such analytical methods, a confounding factor up to this point has been the presence of linkage disequilibrium (LD). In this study, we examined the effect of LD on the sensitivity of the Multifactor Dimensionality Reduction (MDR) software package.

Use of biological knowledge to inform the analysis of gene-gene interactions involved in modulating virologic failure with efavirenz-containing treatment regimens in ART-naïve ACTG clinical trials participants.

Personalized medicine is a high priority for the future of health care. The idea of tailoring an individual's wellness plan to their unique genetic code is one which we hope to realize through the use of pharmacogenomics. There have been examples of tremendous success in pharmacogenomic associations however there are many such examples in which only a small proportion of trait variance has been explained by the genetic variation.

Finding unique filter sets in PLATO: a precursor to efficient interaction analysis in GWAS data.

The methods to detect gene-gene interactions between variants in genome-wide association study (GWAS) datasets have not been well developed thus far. PLATO, the Platform for the Analysis, Translation and Organization of large-scale data, is a filter-based method bringing together many analytical methods simultaneously in an effort to solve this problem. PLATO filters a large, genomic dataset down to a subset of genetic variants, which may be useful for interaction analysis.