For many patients with depression, it can take months of "trial-and-error" to find the antidepressant treatment that works for them. However, new research on biomarkers may be the key to getting patients the right antidepressant right on the first try, Theresa Gaffney writes for STAT.

The difficulty of finding the right antidepressant

According to Gaffney, when patients are diagnosed with depression, physicians often prescribe a selective serotonin reuptake inhibitor (SSRI) as treatment. However, it can take weeks for the SSRI to work, and if it is not effective, patients will have to be weaned off the medication before they can try a different medication to help manage their symptoms.

"This trial-and-error approach can exhaust and discourage patients, and too many failed trials could lead some to stop seeking treatment altogether," Gaffney writes.

For example, Marin Moore, a 22-year-old public school teacher, has been on and off several different medications since being diagnosed with depression at 16. Even when she was able to find an effective antidepressant relatively quickly, the side effects, including intense nausea or temporary vision loss, could be quite severe.

"It was such an overwhelming, time-consuming, and sometimes physically painful process to get through that I would rather find ways to cope with my depression — like really bad depression — than trying to go back on medication," Moore said.

"The process of finding that right dosage takes months, and that time when you're not taking any enjoyment, when you’re not able to focus, you're not able to really be a person — it disrupts your life," she added.

Could biomarkers help predict the effectiveness of antidepressants?

Currently, researchers are studying biological identifiers of depression that could potentially help clinicians better determine the most effective treatment for patients.

Diego Pizzagalli, director of the Center for Depression, Anxiety, and Stress Research at McLean Hospital, and his team have identified biomarkers for anhedonia, a classic symptom of depression in which patients are unable to feel pleasure.

In a study published in Biological Psychiatry, Pizzagalli and his team analyzed patients who were taking either sertraline (an SSRI) or bupropion (an atypical antidepressant that targets dopamine and norepinephrine).

Overall, the researchers found that patients who had stronger connections between two specific nodes in the brain's reward system were more likely to have a response to the atypical antidepressant than the SSRI. A related behavioral task also showed that patients who had a higher sensitivity to reward had a better response to the atypical antidepressant.

Now, Pizzagalli and his team are building on this research with a new study, which is currently recruiting patients. In this new study, the researchers will use MRI scans and other technology to identify biomarkers in the brain's reward systems and see if they can help predict whether an SSRI or an atypical antidepressant will work better for patients with anhedonia. Participants will also perform a behavioral task to back-up the prediction made by the MRI scans.

After having their brains scanned and performing the task, participants will go through eight weeks of treatment. Some participants will receive an "intended" antidepressant, which is aligned with the prediction made by their biomarkers, while others will not. In the end, the researchers will evaluate whether those who received the "intended" treatment showed more improvement than those who did not.

So far, research into precision psychiatry is in the early stages, but experts in the field say that Pizzagalli's study gives them hope that clinicians will be able to use predictive technology to treat patients with depression in the future.

"They're doing a wonderful job of developing an approach where you can treat one of these types of depression that is not responding to the current standard antidepressant agents," said Leanne Williams, who leads similar research into predictive biomarkers for cognitive-based subtypes of depression at the Stanford Center for Precision Mental Health and Wellness

"I don't think that we are that far away from [clinical action with predictive biomarkers for depression] being possible," she added. (Gaffney, STAT, 1/24)