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

Benjamin J. Grady, Marylyn Deriggi Ritchie

Research output: Contribution to journalReview article

7 Citations (Scopus)

Abstract

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 throughput of genotyping technology and reduction of its cost have 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. With new technology and methodology regularly becoming available for use in genetic studies, a discussion on the application of such tools becomes necessary. In particular, quality control criteria have evolved with the use of genome wide association studies (GWAS) as we have come to understand potential systematic errors which can be introduced into the data during high throughput genotyping. There have been several replicated pharmacogenomic associations, some of which have moved to the clinic to enact change in treatment decisions. These examples of translation illustrate the pertinence of systematic evidence from welldesigned studies to successfully and effectively translate a genetic discovery. In this paper, the design of pharmacogenomic association studies is examined with the goal of optimizing the downstream impact and utility of this research in clinical and public health practice. Issues of ascertainment, genotyping, quality control, analysis and interpretation are also considered.

Original languageEnglish (US)
Pages (from-to)41-66
Number of pages26
JournalCurrent Pharmacogenomics and Personalized Medicine
Volume9
Issue number1
StatePublished - Mar 23 2011

Fingerprint

Pharmacogenetics
Quality Control
Public Health Practice
Technology
Precision Medicine
Molecular Epidemiology
Genome-Wide Association Study
Medical Genetics
Genetic Polymorphisms
Genetic Markers
Research
Pharmacokinetics
Genome
Costs and Cost Analysis
Therapeutics
Pharmacogenomic Testing

All Science Journal Classification (ASJC) codes

  • Molecular Medicine
  • Molecular Biology
  • Genetics
  • Pharmacology
  • Genetics(clinical)

Cite this

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Statistical Optimization Of Pharmacogenomics Association Studies : Key Considerations from Study Design to Analysis. / Grady, Benjamin J.; Ritchie, Marylyn Deriggi.

In: Current Pharmacogenomics and Personalized Medicine, Vol. 9, No. 1, 23.03.2011, p. 41-66.

Research output: Contribution to journalReview article

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