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Aids in determining therapeutic strategies for drugs that are metabolized by CYP3A4, including atorvastatin, simvastatin and lovastatin
Genotyping patients who prefer not to have venipuncture done
The cytochrome P450 (CYP) 3A4 enzyme is responsible for the metabolism of approximately 50% of drugs that undergo hepatic metabolism and first-pass metabolism in intestinal epithelial cells, including lipid-lowering drugs. The CYP3A4 enzyme activity is highly variable. Interindividual differences in enzyme expression may be due to several factors including: variable homeostatic control mechanisms, disease states that alter homeostasis, up- or down-regulation by environmental stimuli, and genetic variation.(1) A CYP3A4 intron 6 variant, CYP3A4*22 (c.522-191C->T), affects hepatic expression of CYP3A4 and response to statin drugs. The CYP3A4*22 allele is associated with reduced CYP3A4 activity, which may result in a better response to lipid-lowering drugs, such as simvastatin, atorvastatin, or lovastatin. However, reduced CYP3A4 activity may also be associated with statin-induced myopathy, especially for simvastatin. Studies show that in livers with the wild-type genotype (homozygous C or CC) the CYP3A4 mRNA level and enzyme activity were 1.7- and 2.5-fold greater than in heterozygous CYP3A4*22 (CT) and homozygous CYP3A4*22 (TT) carriers, respectively. In 235 patients taking stable doses of drugs for lipid control, carriers of the T allele required significantly lower statin doses for optimal lipid control than did non-T carriers.(2) These results indicate that CYP3A4*22 markedly affects expression of CYP3A4 and could serve as a biomarker for CYP3A4 metabolizer phenotype. The reported allele frequency of CYP3A4*22 in Caucasians was 5% to 8%. The allele frequency is 4.3% in African Americans and in Chinese.
An interpretive report will be provided.
The CYP3A4*22 allele was not detected. Therefore, this patient is expected to be an extensive metabolizer. Rapid metabolism of drugs that are inactivated or activated by CYP3A4 is expected. Coadministration of CYP3A4 inhibitors may increase the risk of toxicity for drugs inactivated by CYP3A4, or may cause lack of efficacy for drugs activated by CYP3A4.
Intermediate to extensive metabolizer:
One copy of the CYP3A4*22 allele was detected. Therefore, this patient is expected to be an intermediate to extensive metabolizer.
Reduced metabolism of drugs that are inactivated or activated by CYP3A4 is expected when compared to patients who are *1/*1. Coadministration of CYP3A4 inhibitors may increase the risk of toxicity for drugs inactivated by CYP3A4, or may cause lack of efficacy for drugs activated by CYP3A4.
Two copies of the CYP3A4*22 allele were detected. Therefore, this patient is expected to be an intermediate metabolizer. Drugs that are inactivated or activated by CYP3A4 are metabolized at reduced rate when compared to patients who are *1/*1. Coadministration of CYP3A4 inhibitors may increase the risk of toxicity for drugs inactivated by CYP3A4, or may cause lack of efficacy for drugs activated by CYP3A4.
Absence of the *22 allele does not rule out the possibility that a patient harbors another variant that can impact the function of this enzyme, drug response, or drug side effects. The CYP3A4 genotype is only one factor that should be taken into consideration for drug dosing.
For additional information regarding pharmacogenomic genes and their associated drugs, please see the Pharmacogenomics Associations Tables in Special Instructions. This resource also includes information regarding enzyme inhibitors and inducers, as well as potential alternate drug choices.
Saliva samples may contain donor DNA if obtained from patients who received heterologous blood transfusions or allogeneic blood or marrow transplantation. Results from samples obtained under these circumstances may not accurately reflect the recipient’s genotype. For individuals who have received blood transfusions, the genotype usually reverts to that of the recipient within 6 weeks. For individuals who have received allogeneic blood or marrow transplantation, a pretransplant DNA specimen is recommended for testing.
CYP3A4 genetic test results in patients who have undergone liver transplantation may not accurately reflect the patient's CYP3A4 status.
This test does not detect variants other than the specific intron 6 *22 variant (c.522-191C>T). Therefore, absence of a detectable gene variant does not rule out the possibility that a patient has an altered CYP3A4 metabolism due to other CYP3A4 variants that cannot be detected with this method..
This test is not indicated for stand-alone diagnostic purposes.
Drug-drug interactions and drug-metabolite inhibition must be considered.
Drug-metabolite inhibition can occur, resulting in inhibition of CYP3A4 catalytic activity.
Patients may also develop toxicity problems if liver and kidney function are impaired.
CYP3A4 genotyping should not be ordered for managing patients receiving fluvastatin, rosuvastatin, or pravastatin since these drugs are not metabolized appreciably by CYP3A4.
Rare variants exist that could lead to false-negative or false-positive results. If results obtained do not match the clinical findings, additional testing could be considered.
1. Evans WE, Relling RV: Pharmacogenomics: translating functional genomics into rational therapeutics. Science 1999;486:487-491
2. Wang D, Guo Y, Wrighton SA, et al: Intronic polymorphism in CYP3A4 affects hepatic expression and response to statin drugs. Pharmacogenomics J 2011;11:274-286
3. Lamba JK, Lin YS, Schuetz EG, Thummel KE: Genetic contribution to variable human CYP3A-mediated metabolism. Adv Drug Deliv Rev 2002;18:1271-1294
4. Elens L, Becker ML, Haufroid V, et al: Novel CYP3A4 intron 6 single nucleotide polymorphism is associated with simvastatin-mediated cholesterol reduction in the Rotterdam study. Pharmacogenet Genomics 2011;21(12):861-866
5. Elens L, Van Schaik RH, Panin N, et al: Effect of a new functional CYP3A4 polymorphism on calcineurin inhibitor' dose requirements and trough blood levels in stable renal transplant patients. Pharmacogenomics 2011;12(10):1383-1396