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By Mayo Clinic staffBy testing a DNA sample from your blood or skin cells, your doctor may be able to predict whether a particular antidepressant is likely to relieve your symptoms and if it's likely to cause bothersome side effects.
Medications for depression are usually prescribed based on symptoms and medical history without cytochrome P450 testing. For some people, the first antidepressant tried relieves depression symptoms and has tolerable side effects. For many others, however, finding the right medication takes trial and error. For some people, it can take several months or longer to find the right antidepressant. Genotyping tests such as cytochrome P450 tests may speed up the process of identifying the medications likely to work best.
Cytochrome P450 tests are generally used only when initial antidepressant treatment isn't successful. However, as they become more established — and new tests are developed — cytochrome P450 tests and other genotyping tests may become a standard tool used in treating depression and other conditions.
Genotyping tests also show promise for predicting risk factors for depression and a number of other conditions such as cancer and heart disease. Cytochrome P450 tests are already being used to determine whether certain cancer medications are likely to be effective.
- Mrazek DA. Psychiatric pharmacogenomic testing in clinical practice. Dialogues in Clinical Neuroscience. 2010;12:69.
- Li X, et al. Clinical utility of microarrays: Current status, existing challenges and future outlook. Current Genomics. 2008;9:466.
- Zandi PP, et al. The promise and reality of pharmacogenetics in psychiatry. Psychiatry Clinics of North America. 2010;33:181.
- Black JL (expert opinion). Mayo Clinic, Rochester, Minn. May 4, 2010.
- Evaluation of genomic applications in practice and prevention (EGAPP) working group. Recommendations from the EGAPP Working Group: Testing for cytochrome P450 polymorphisms in adults with nonpsychotic depression treated with selective serotonin reuptake inhibitors. Genetics in Medicine. 2007;9:819.
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