A comparison of genetic sampling methodologies for candidate-gene analyses

Much of the recent gains in knowledge regarding the influence of patient genetics on medication pharmacokinetics (drug absorption, distribution, metabolism and elimination) how patients process medications) and pharmacodynamics (drug response) have been attributed to the technologic advances in genetic testing methodologies and the involvement of large clinical data sets and biobanks. Indeed, Genome Wide Association Studies (GWAS) and Phenome Wide Association Studies (PWAS) along with ever-evolving biomedical informatics techniques and the expansion of the -omics sciences (e.g., transcriptomics, metabolomics, proteomics) have brought about unprecedented advances in precision medicine. Although the simpler candidate-gene analysis technique is not considered cutting-edge, it is reliable and important to the translation of pharmacogenomic research and the advancement of precision medicine. Leveraging the knowledge of biological plausibility (i.e., genetic mutation → altered function of protein product → altered drug pharmacokinetics/dynamics) to appropriately select genes for inclusion, the candidate-gene analysis technique does not necessitate large patient cohorts nor extensive multi-gene genetic analysis arrays. It is often the ideal method for clinicians to begin evaluating whether genetic information might improve their pharmacologic treatment strategies for their patients. Having access to specific patient populations and expertise regarding their medical subspecialty, physician scientists can implement a candidate-gene analysis in small cohorts. Even with less than 100 patients, results can often be used to determine whether further investigation is warranted and to inform future studies. Herein, we present a comparison of select contemporary methodologies regarding collection, processing and genotype testing applicable to the efficient implementation of candidate-gene studies.