User:Dolleyj

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Introduction[edit]

Pharmacogenomics (a combination of pharmacology and genomics) is the study of how genetic makeup influences an individual’s response to drugs. [1] It deals with the influence of genetic variation on drug response in patients by correlating gene expression or single-nucleotide polymorphisms with a drug's efficacy or toxicity. [2] By doing so, 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, or even avoided, based on each individual's unique genetic makeup. [4][5] Since the advent of medicine, itself, it has been well-established that no two individuals respond exactly the same to any given drug. Also, it is known that while a drug may work well in the vast amount of a population, it may be ineffective, or even harmful, to a select subset of the population. Pharmacogenomics seeks to explain the mechanisms behind these occurrences and provide better and safer patient care. In order to provide pharmacogenomic based recommendations for a given drug, several possible types of input can be used: genotyping, exome sequencing, or wholegenome sequencing. [6]

Pharmacodynamic Genes[edit]

A pharmacodynamic gene is the gene that encodes the protein which is the target of a drug [7]. These genes can code for cell surface receptors, enzymes, or nuclear hormone receptors. Drugs directly interact with these proteins to produce the drug’s therapeutic effects. These interactions divide drugs into two basic mechanisms of action: agonist or antagonist.


An agonist drug binds to the target protein, and activates a cellular pathway to produce the desired therapeutic effect.


An antagonist drug binds to the target protein, and inhibits the binding of that protein’s activator. This prevents the activation of a cellular pathway to produce the desired therapeutic effect.



Examples of Agonist & Antagonist Drugs[edit]

An example of an agonist drug would be the dopamine agonists drugs (bromocriptine, pergolide, pramipexole, ropinirole, piribedil, cabergoline, apomorphine, and lisuride) used to treat Parkinson’s Disease patients. These drugs bind to the dopaminergic postsynaptic receptors in the brain to activate the signaling pathways necessary for gene transcription and production of dopamine.

An example of an antagonist drug would be trastuzumab (brand name Herceptin). Trastuzumab targets the receptor tyrosine-protein kinase ERBB-2. ERBB-2, also called HER2 (from its name human epidermal growth factor receptor 2), promotes cell growth and division under normal conditions; however, when ERBB-2 is expressed, it is carcinogenic and found in 20% of early stage breast cancers [8]. When administered, trastuzumab binds to the ERBB-2 receptor, thus inhibiting carcinogenesis.


Genetic variation in pharmacodynamic genes[edit]

Single nucleotide polymorphisms (SNPs) are genetic variations where a single nucleotide is found to persist in different allelic forms across members of a human population[8]. While not all SNPs may affect genes, or downstream proteins, many result in variation of pharmacodynamic genes that greatly impact the structure or chemistry of the drug targeted proteins. In turn, this affects the interaction of the drug with its target protein, and result in the drug exhibiting an undesired effect.

Example[edit]

Warfarin (Brand name: Coumadin) is an anticoagulant drug prescribed to patients with prosthetic heart valves or atrial fibrillation to prevent systemic embolism. Warfarin’s mechanism of action is to act as a vitamin K antagonist. Warfarin enters the body as a prodrug; therefore it must be first metabolized before it is able to produce its therapeutic effect. It is oxidized by the CYP2C9 enzyme in the liver becoming active. Then it inhibits the vitamin K epoxide reductase complex, subunit 1 (VKORC1) to exhibit its anticoagulant effect. While an effective drug, warfarin unfortunately has a narrow window for maintaining a therapeutic INR, which is between 2.0 to 3.0. An INR greater than 4.0 is supratherapeutic and greatly increases the risk for bleeding. Because of this narrow therapeutic window, it takes time to achieve a stable therapy [9].

Three SNPs have been discovered to impact the metabolism and effectiveness of warfarin. Identification of these SNPs in carriers greatly influences the dosage for those individuals and aids in safer start dosages when beginning a regular warfarin therapy regimen. Two SNPs are located in the CYP2P9 gene and one SNP is in the VKORC1 gene. For purposes of the article, VKORC1 SNP will be detailed, as VKORC1 is the primary pharmacodynamic gene of warfarin.

At the 1639 SNP loci in the VKORC1 gene, the common allele, G, is replaced by the A allele, resulting in a decreased production of the VKORC1 protein. A dose of warfarin (considered normal or typical for a G allele person) in the presence of a decreased concentration of VKORC1 protein would result in an increased therapeutic effect (increased anticoagulation). Therefore, people carrying an A allele need a lower warfarin dose to produce appropriate anticoagulation. The prevalence of the A allele is found in 37% of Caucasians and 14% of Africans[10].

Clinically, this sensitivity to warfarin translates into individualized dosages for aberrant SNP carriers. People carrying an A allele generally require 28% less warfarin dose per allele than non-A allele carriers. Similar dosage adjustments are made for carriers of the CYP2C9*2 and CYP2C9*3 alleles, 19% and 33% dose reduction, respectively[10]. The table below illustrates the recommended dosages for carriers of the warfarin SNP alleles.


References[edit]

Dudley, Joel T, Karczewski, Konrad J. Exploring Personal Genomics. First Edition. Oxford University Press. pp 140,143, 151-158. Shah, Svati H, and Voora, Deepak. Warfarin Dosing and VKORC1/CYP2C9. Medscape, WebMD, LLC. Last updated: Nov 11, 2013. Accessed: April 5, 2014. http://emedicine.medscape.com/article/1733331-overview#a1

  1. ^ Ermak G. Modern Science & Future Medicine (second ed.). pp. 164 year = 2013. ISBN 1-4823-0885-1. {{cite book}}: Missing pipe in: |pages= (help)
  2. ^ Wang L (2010). "Pharmacogenomics: a systems approach". Wiley Interdiscip Rev Syst Biol Med. 2 (1): 3–22. doi:10.1002/wsbm.42. PMID 20836007.
  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.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  6. ^ 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.
  7. ^ al.], Joel T. Dudley ... [et (2013). Exploring personal genomics. Oxford: Oxford University Press. pp. 139–159. ISBN 978-0-19-964448-3.
  8. ^ a b Cite error: The named reference dudley was invoked but never defined (see the help page).
  9. ^ "Warfarin Dosing and VKORC1/CYP2C9". Retrieved April 5, 2014.
  10. ^ a b Cite error: The named reference medscape was invoked but never defined (see the help page).
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