RESUMEN
OBJECTIVE: The capacity of the Affymetrix drug metabolism enzymes and transporters (DMET) Plus pharmacogenomics genotyping chip to estimate population substructure and cryptic relatedness was evaluated. The results were compared with estimates using genome-wide HapMap data for the same individuals. METHODS: For 301 unrelated individuals, spanning three continental populations and one admixed population, genotypic data were collected using the Affymetrix DMET Plus microarray. Genome-wide data on these individuals were obtained from HapMap release 3. Population substructure was assessed using Eigenstrat and ADMIXTURE software for both platforms. Cryptic relatedness was explored by inbreeding coefficient estimation. Nonparametric tests were used to determine correlations of the analytical results of the two genotyping platforms. RESULTS: Principal components analysis identified population substructure for both datasets, with 15.8 and 16.6% of the total variance explained in the first two principal components for DMET Plus and HapMap data, respectively. ADMIXTURE results correctly identified four subpopulations within each dataset. Nonparametric rank correlations indicated significant associations between analyses with an average ρ=0.7272 (P<10) across the three continental populations and ρ=0.4888 for the admixed population. Concordance correlation coefficients (average ρc=0.9693 across all four subpopulations) strongly indicate concordance between ADMIXTURE results. Inbreeding coefficients were slightly inflated (16 individuals>0.15) using DMET Plus data and no cryptic relatedness was indicated using HapMap data. The inflated inbreeding estimation could be because of the limited number of markers provided by DMET as a random sample of 1832 markers from HapMap also yielded inflated estimates of cryptic relatedness (39 individuals>0.15). Furthermore, use of single nucleotide polymorphisms located in genes involved in metabolism and transport may have different allele frequencies in subpopulations than single nucleotide polymorphisms sampled from the whole genome. CONCLUSION: The DMET Plus pharmacogenomics genotyping chip is effective in quantifying population substructure across the three continental populations and inferring the presence of an admixed population. On the basis of our results, these microarrays offer sufficient depth for covariate adjustment of population substructure in genomic association studies.
RESUMEN
The Institute for Pharmacogenomics and Individualized Therapy (IPIT) at the University of North Carolina at Chapel Hill (NC, USA) is a collaborative, multidisciplinary unit that brings together faculty from different disciplines and crosses the traditional departmental/school structure to perform pharmacogenomics research. IPIT investigators work together towards the goal of developing therapies to enable the delivery of individualized medical care. The NIH-supported Comprehensive Research on Expressed Alleles in Therapeutic Evaluation (CREATE) group leads the field in the evaluation of pathways regulating drug activity, and also provides a foundation for future IPIT research. IPIT members perform bench research, clinical cohort analysis and prospective clinical intervention studies, research on the integration of pharmacogenomic therapy into practice and research to foster global health pharmacogenomics application through the Pharmacogenetics for Every Nation Initiative. IPIT Investigators are actively incorporating a pharmacogenomics curriculum into existing teaching programs at all levels.
