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Brain Scan Predicts Best Treatment Approach for Depression

Biomarker Could Avoid Treatment Inefficiencies

To be ill with depression any longer than necessary can be perilous. As a neuroscientist, I’m devoted to finding better, safer treatments for patients with mood disorders and other mental illness. Research into the brain’s circuitry can lead us to a better understanding of depression including new, personalized treatment selection strategies. These strategies would match a patient to a treatment that is most likely to be beneficial while also avoiding treatments unlikely to provide benefit.

Towards this future goal, we have taken a small step in this direction: a recent study in my lab at Emory University showed that a simple brain scan may offer a way to predict which people being treated for depression will respond to drugs, and which will respond to psychotherapy. The research suggests that we may be able to improve success rates in depression treatment; at present less than 40% of people with depression experience remission with the treatment originally selected.

Our study was published in JAMA Psychiatry and was based on a fundamental question; what can an individual’s brain activity as measured by a PET Scan tell us about that patient? Can brain activity be used as a biomarker to make critical treatment decisions?

To answer this question, my research team measured brain glucose metabolism (the brain’s primary energy source and an index of regional brain function) using PET scans in two groups of participants during a span of 12 weeks. Half of the participants received an antidepressant medication (a commonly-used SSRI), and the other half was given cognitive behavioral therapy (CBT). In the end, the study demonstrated that less activity in the brain’s anterior insula (an area involved in emotional processing and critically interoceptive awareness; i.e. having knowledge of sensations from the body) indicated the patient would respond better to CBT. Alternatively, more activity indicated response to medication.

This data suggests that if doctors treat based on a patient’s brain type, we can increase the chance of recovery. We are now in the midst of second study to test whether or not use of a patient’s ‘insula type’ to select a first-line treatment for an individual patient improves their clinical outcome. Such studies are the first step towards a biologically based reclassification of depression subtypes based on a brain biomarker. If successful, this will lay foundation for similar strategies in patients who fail to respond to these first line options.

Helen Mayberg, M.D., a professor at Emory University School of Medicine, is a researcher with the Hope for Depression Research Foundation.