A new study finds that pharmacogenomic testing could avoid over-prescribing antidepressant medications.
A US Department of Veterans Affairs study has discovered that pharmacogenomic testing could help healthcare providers determine whether antidepressant medications are suitable for the patient. Pharmacogenomic testing analyses how genes affect the body’s response to drugs.
Research suggests that antidepressant medications can be helpful for patients with moderate to severe depression; however, some side effects are undesirable including indigestion, dizziness, insomnia and reduced sex drive. Some patients may experience an adverse reaction to antidepressants and pharmacogenomic testing could help avoid this.
Dr David Oslin, director of VA’s VISN 4 Mental Illness, Research, Education, and Clinical Center (MIRECC), led the study and published the findings in the Journal of the American Medical Association.
Personalising medication with pharmacogenomic testing
Pharmacogenomic testing has been growing in popularity, especially in the personalised medication sector. It is used for health conditions such as cancer but has not been used widely for major depressive disorder.
Currently, most pharmacogenomic tests focus on a variant in the genes that encode hepatic CYP450 enzymes, a pathway that metabolises drugs in the liver. Oslin and his research team employed a commercial battery of genes that concentrated on the CYP450 system, testing eight genes with six enzymes from the liver.
What is the link between genes and antidepressants?
“The genes we tested don’t actually relate to depression,” Oslin said. “They relate to how a person metabolises the drugs once they are in the body. Some of these genes will cause the medications to metabolise much faster than normal. Others will cause the drugs to metabolise much slower than normal, which means you’ll end up with a lot of medication in your body.”
Nearly 2000 patients from 22 VA medical institutes were enrolled in the study as they were either starting or switching their antidepressant medication. Half of the participants received pharmacogenomic testing, and the other half received usual care. The team aimed to discover if this testing could help patients improve their reaction to medications and understand drug-gene interactions.
Using the data on gene-drug interactions, the researchers found that 59% of the patients in the pharmacogenomic testing group received medication with no predicted drug-gene interaction, compared with 26% in the control group. The researchers concluded that this difference was “statistically significant and clinically meaningful”.’
Oslin said he went into the study thinking the research team would not see such a dramatic effect in predicted drug-gene interactions. He was “somewhat surprised” by the result. “There was essentially a major shift in avoiding medicines that had a predicted drug-gene interaction,” he commented.
How were the patients affected by their medication?
The researchers interviewed about their depression outcomes, which included depression remission, depression response and symptom improvement. They found that the pharmacogenetic testing group had an improved experience across all three outcomes. The results were statistically significant over 24 weeks, with a peak at 12 weeks; the depression outcomes were not significant at the 24-week point.
“We were not powered to look specifically at 24 weeks,” Oslin explained. “That wasn’t part of our primary hypothesis. Our primary hypothesis was an overall effect. And we showed an overall effect in all three of the ways that we measured outcomes. So, it’s a glass half full, glass half empty kind of thing. Another way to think about the results is the group that had the pharmacogenetic test results had a faster response. That also was not something that we tested. But clearly, if you look at 12 weeks in all three outcomes, the group that got the genetic test showed a better improvement in remission, response, and symptom improvement.
“It’s important to realise that the test is not telling you whether the patient is going to respond to the treatment or not,” he added. “It’s telling you something about how the patient metabolises the medication. So it’s not telling me that this is good medicine for the patient. It’s telling me not to prescribe this medicine, or perhaps to adjust the dosing because the patient doesn’t metabolise it well.”
