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Creating and evaluating genetic tests predictive of drug response

Nature Reviews Drug Discovery volume 7, pages 568574 (2008) | Download Citation

Abstract

A key goal of pharmacogenetics — the use of genetic variation to elucidate inter-individual variation in drug treatment response — is to aid the development of predictive genetic tests that could maximize drug efficacy and minimize drug toxicity. The completion of the Human Genome Project and the associated HapMap Project, together with advances in technologies for investigating genetic variation, have greatly advanced the potential to develop such tests; however, many challenges remain. With the aim of helping to address some of these challenges, this article discusses the steps that are involved in the development of predictive tests for drug treatment response based on genetic variation, and factors that influence the development and performance of these tests.

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Acknowledgements

We would like to thank Richard M. Weinshilboum, MD and the White Paper subcommittee of the PGRN network for valuable suggestions. Financial support is also acknowledged: U01 HL065899 (S.T.W.); U01 GM63340 (H.L.M.); UO1 GM061373 (D.A.F.); DA 20830 (N.L.B.); U01 GM074492 (J.A.J.); GM61393 (M.J.R. and M.E.D.); and GM61390 (K.M.G.).

Author information

Affiliations

  1. Scott T. Weiss is at the Channing Laboratory, Brigham and Women's Hospital, 181 Longwood Ave, Boston, Massachusetts 02115, USA.

    • Scott T. Weiss
  2. Howard L. McLeod is at the University of North Carolina, Chapel Hill, Campus Box 7360, 3203 Kerr Hall, Chapel Hill, North Carolina 27599, USA.

    • Howard L. McLeod
  3. David A. Flockhart is at the Indiana University School of Medicine, Wishard Hospital, WD OPW 320, 1001 West 10th Street, Indianapolis, Indianapolis 46202, USA.

    • David A. Flockhart
  4. M. Eileen Dolan is at the Department of Medicine, Committee on Clinical Pharmacology and Pharmacogenomics, 5841 South Maryland Avenue, Box MC2115, University of Chicago, Chicago, Illinois 6063-71470, USA.

    • M. Eileen Dolan
  5. Neal L. Benowitz is at the Division of Clinical Pharmacology and Experimental Therapeutics, University of California, San Francisco, Box 1220, San Francisco, California 94143-1220, USA.

    • Neal L. Benowitz
  6. Julie A. Johnson is at the University of Florida College of Pharmacy, Department of Pharmacy Practice, P.O. Box 100486, Gainesville, Florida 32610-0486, USA.

    • Julie A. Johnson
  7. Mark J. Ratain is at the University of Chicago, 5841 South Maryland Avenue, MC 2115, Chicago, Illinois 60637-1470, USA.

    • Mark J. Ratain
  8. Kathleen M. Giacomini is at the University of California, San Francisco, School of Pharmacy, Box 0446 513 Parnassus Avenue, San Francisco, California 94143-0446, USA.

    • Kathleen M. Giacomini

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Corresponding author

Correspondence to Scott T. Weiss.

Glossary

Environmental phenocopy

A clinical case of a complex trait due solely to environmental factors.

Epistasis

The interaction or interdependence of two or more genes.

Incomplete penetrance

Occurs when less than 100% of a population with an identical mutant genotype display the associated phenotype.

Linkage disequilibrium

The nonrandom association of alleles in the genome.

Mode of inheritance

Dominant mode of inheritance occurs when only one copy of the allele is necessary to produce the phenotype. Recessive mode of inheritance occurs when both copies of the allele are necessary to produce the phenotype.

Pleiotropy

A single mutation that has more than one biological effect or phenotype.

Receiver operating characteristic (ROC) curve

A curve that plots I-sensitivity on the y axis and specificity on the x axis. The area under this curve is a measure of test performance.

Severe adverse event

An event that occurs less than 1 in 10,000 administrations of the medication and is life threatening.

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DOI

https://doi.org/10.1038/nrd2520

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