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Pharmacogenomics (a portmanteau of pharmacology and genomics) is the study of the role of genetics in drug response. It deals with the influence of genetic variation on drug response in patients by correlating gene expression or single-nucleotide polymorphisms with drug absorption, distribution, metabolism and elimination, as well as drug receptor target effects. Pharmacogenomics may be used interchangeably with the term pharmacogenetics, which focuses on the effects of candidate genes in drug response.[1][2] Pharmacogenomics aims to develop rational means to optimize drug therapy, with respect to the patients' genotype, to ensure maximum efficacy with minimal adverse effects.[3] Such approaches promise the advent of "personalized medicine"; in which drugs and drug combinations are optimized for each individual's unique genetic makeup.[4][5] In order to provide pharmacogenomic based recommendations for a given drug, two possible types of input can be used: genotyping or exome or whole genome sequencing.[6] Sequencing provides many more data points, including detection of mutations that prematurely terminate the synthesized protein (early stop codon).[6]

Drug metabolism[edit]

There are several known genes which are largely responsible for variances in drug metabolism and response. The most common are the cytochrome P450 (CYP) genes, which encode enzymes that influence the metabolism of more than 80 percent of current prescription drugs.[7][8] Codeine, clopidogrel, tamoxifen, and warfarin are examples of medications that follow this metabolic pathway. Patient genotypes are usually categorized into predicted phenotypes. For example, if a person receives one *1 allele each from mother and father to code for the CYP2D6 gene, then that person is considered to have an extensive metabolizer (EM) phenotype. An extensive metabolizer is considered normal. Other CYP metabolism phenotypes include: intermediate, ultra-rapid, and poor. In theory, each phenotype is based upon the allelic variation within the individual genotype. However, several genetic events can influence a same phenotypic trait, and establishing genotype-to-phenotype relationships can thus be far from consensual with many enzymatic patterns. For instance, the influence of the CYP2D6*1/*4 allelic variant on the clinical outcome in patients treated with Tamoxifen remains debated today. In oncology, genes coding for DPD, UGT1A1, TPMT, CDA involved in the pharmacokinetics of 5-FU/capecitabine, irinotecan, 6-mercaptopurine and gemcitabine/cytarabine, respectively, have all been described as being highly polymorphic. A strong body of evidence suggests that patients affected by these genetic polymorphisms will experience severe/lethal toxicities upon drug intake, and that pre-therapeutic screening does help to reduce the risk of treatment-related toxicities through adaptive dosing strategies.[9]

Identification of the genetic basis for polymorphic expression of a gene is done through intronic or exomic SNPs which abolishes the need for different mechanisms for explaining the variability in drug metabolism. The SNPs based variations in membrane receptors lead to multidrug resistance (MDR) and the drug–drug interactions. Even drug induced toxicity and many adverse effects can be explained by genome-wide association studies (GWAS).[10]


Pharmacogenomics has applications in illnesses like cancer, cardiovascular disorders, depression, bipolar disorder, attention deficit disorders, HIV, tuberculosis, asthma, and diabetes.

In cancer treatment, pharmacogenomics tests are used to identify which patients are most likely to respond to certain cancer drugs. In behavioral health, pharmacogenomic tests provide tools for physicians and care givers to better manage medication selection and side effect amelioration. Pharmacogenomics is also known as companion diagnostics, meaning tests being bundled with drugs. Examples include KRAS test with cetuximab and EGFR test with gefitinib. Beside efficacy, germline pharmacogenetics can help to identify patients likely to undergo severe toxicities when given cytotoxics showing impaired detoxification in relation with genetic polymorphism, such as canonical 5-FU.[11]

In cardio vascular disorders, the main concern is response to drugs including warfarin, clopidogrel, beta blockers, and statins.[6]

There are currently over 120 U.S. Food and Drug Administration approved drugs that include pharmacogenomic biomarkers in their labels.[12]


Some alleles that vary in frequency between specific populations have been shown to be associated with differential responses to specific drugs. The beta blocker Atenolol is an anti-hypertensive medication that is shown to more significantly lower the blood pressure of Caucasian patients than African American patients in the United States. This observation suggests that Caucasian and African American populations have different alleles governing oleic acid biochemistry, which react differentially with Atenolol.[13] Similarly, hypersensitivity to the antiretroviral drug abacavir is strongly associated with a single-nucleotide polymorphism that varies in frequency between populations.[14]

The FDA approval of the drug BiDil with a label specifying African-Americans with congestive heart failure, produced a storm of controversy over race-based medicine[15] and fears of genetic stereotyping, even though the label for BiDil did not specify any genetic variants but was based on racial self-identification.[16][17]

See also[edit]


  1. ^ "Center for Pharmacogenomics and Individualized Therapy". Retrieved 2014-06-25. 
  2. ^ "overview of pharmacogenomics". Up-to-Date. May 16, 2014. Retrieved 2014-06-25. 
  3. ^ Becquemont L (June 2009). "Pharmacogenomics of adverse drug reactions: practical applications and perspectives". Pharmacogenomics 10 (6): 961–9. doi:10.2217/pgs.09.37. PMID 19530963. 
  4. ^ "Guidance for Industry Pharmacogenomic Data Submissions" (PDF). U.S. Food and Drug Administration. March 2005. Retrieved 2008-08-27. 
  5. ^ Squassina A, Manchia M, Manolopoulos VG, Artac M, Lappa-Manakou C, Karkabouna S, Mitropoulos K, Del Zompo M, Patrinos GP (August 2010). "Realities and expectations of pharmacogenomics and personalized medicine: impact of translating genetic knowledge into clinical practice". Pharmacogenomics 11 (8): 1149–67. doi:10.2217/pgs.10.97. PMID 20712531. 
  6. ^ a b c Huser, V.; Cimino, J. J. (2013). "Providing pharmacogenomics clinical decision support using whole genome sequencing data as input". AMIA Summits on Translational Science proceedings AMIA Summit on Translational Science 2013: 81. PMC 3814493. PMID 24303303.  edit
  7. ^ Hart SN, Wang S, Nakamoto K, Wesselman C, Li Y, Zhong XB (January 2008). "Genetic polymorphisms in cytochrome P450 oxidoreductase influence microsomal P450-catalyzed drug metabolism". Pharmacogenet. Genomics 18 (1): 11–24. doi:10.1097/FPC.0b013e3282f2f121. PMID 18216718. 
  8. ^ Gomes AM, Winter S, Klein K, Turpeinen M, Schaeffeler E, Schwab M, Zanger UM (April 2009). "Pharmacogenomics of human liver cytochrome P450 oxidoreductase: multifactorial analysis and impact on microsomal drug oxidation". Pharmacogenomics 10 (4): 579–99. doi:10.2217/pgs.09.7. PMID 19374516. 
  9. ^ Lee SY, McLeod HL (January 2011). "Pharmacogenetic tests in cancer chemotherapy: what physicians should know for clinical application". J Pathol 223 (1): 15–27. doi:10.1002/path.2766. PMID 20818641. 
  10. ^ Fareed M, Afzal M (2013). "Single nucleotide polymorphism in genome-wide association of human population: A tool for broad spectrum service". Egyptian Journal of Medical Human Genetics 14: 123–134. doi:10.1016/j.ejmhg.2012.08.001. 
  11. ^ Ciccolini J, Gross E, Dahan L, Lacarelle B, Mercier C (October 2010). "Routine dihydropyrimidine dehydrogenase testing for anticipating 5-fluorouracil-related severe toxicities: hype or hope?". Clin Colorectal Cancer 9 (4): 224–8. doi:10.3816/CCC.2010.n.033. PMID 20920994. 
  12. ^ "Table of Pharmacogenomic Biomarkers in Drug Labels". United States Food and Drug Administration. 2013-06-19. 
  13. ^ Wikoff WR, Frye RF, Zhu H, Gong Y, Boyle S, Churchill E, Cooper-Dehoff RM, Beitelshees AL, Chapman AB, Fiehn O, Johnson JA, Kaddurah-Daouk R (2013). "Pharmacometabolomics reveals racial differences in response to atenolol treatment". PLoS ONE 8 (3): e57639. doi:10.1371/journal.pone.0057639. PMC 3594230. PMID 23536766. 
  14. ^ Rotimi CN, Jorde LB (2010). "Ancestry and disease in the age of genomic medicine". N. Engl. J. Med. 363 (16): 1551–8. doi:10.1056/NEJMra0911564. PMID 20942671. 
  15. ^ Bloche, G.M. (2004). Race-based therapeutics. The New England Journal of Medicine, 351, 2035-2037.
  16. ^ Frank R (March 30 – April 1, 2006). "Back with a Vengeance: the Reemergence of a Biological Conceptualization of Race in Research on Race/Ethnic Disparities in Health". Annual Meeting of the Population Association of America. Los Angeles, California. Retrieved 2008-11-20. 
  17. ^ Crawley L (2007). "The paradox of race in the Bidil debate". J Natl Med Assoc 99 (7): 821–2. PMC 2574363. PMID 17668653. 

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