This month, Helen Mayberg and her colleagues published a study suggesting that patterns of brain connectivity may predict which people with depression would respond best to talk therapy and which would do better with a drug. This video clip from Fox5 Atlanta describes the study, and shows what it could mean to people who need help for their depression.
Our first work with Mayberg, now a member of the Dana Alliance for Brain Initiatives, was more than a decade ago, when she was using first positron emission tomography and then deep brain stimulation for treatment-resistant depression (Dana grants in 2006, 2010). She spoke with us about this work in 2012:
My research has long focused on understanding the neurobiology of depression. Our strategy over many years has been to use functional imaging to investigate what brain regions, if any, correlate with ongoing depression symptoms. We took our cues from the work done in Parkinson’s disease, where motor circuits had been well characterized. We wanted to see if depression could be similarly deconstructed, using brain imaging to define a mood circuit—a negative mood circuit, specifically. The goal was to identify how such a system might be hijacked in patients with depression.
We also took advantage of the many evidence-based antidepressant treatments routinely used to treat depressed patients, such as medications and cognitive therapy, to build a circuit model of depression. This provided a flexible framework to evaluate how different treatments affected the brain and, importantly, if different treatments acted in any common ways.
Parallel to our fledgling studies on the depression circuit, DBS for Parkinson’s disease was advancing, along with understandings about how it was working to change the motor circuit. Our hypothesis was that changes in certain critical areas within our depression circuit were necessary for recovery from depression generally. Over time it became clear that brain stimulation within the circuit might work, and the circumstances were right for testing that idea. I guess you could say it was a case of being at the right place at the right time to take advantage of the available DBS technology and consider its potential application to resistant depression.
Deep brain stimulation is a very invasive and expensive procedure, though, requiring serious surgeries and continuing care for the patient and for the implanted stimulator, from changing the modulation to replacing its batteries. These surgeries did help some people who had not been helped in any other way, and they also helped the researchers find areas of brain connectivity that, when they were triggered, seemed to lift the lowest of moods. Perhaps imaging of those areas might show changes when a therapy was taking effect.
For most people with depression, drugs or psychotherapy can work, but it’s unclear from just talking with a person which would work for them. It can take months for a drug or therapy to start affecting mood; if it’s the wrong drug that means at least three months of low-mood living before trying another one. In depression, such failure can cause a person not to try again.
That’s why some people, including Charles Nemeroff writing for Cerebrum, call finding a biomarker for the disorder “the Holy Grail of psychiatry.” From Nemeroff’s essay, published in August 2015:
In 2013, Helen Mayberg and her colleagues published groundbreaking findings that help in this case. … Mayberg’s study sought to identify a biomarker that could predict which type of treatment would benefit a patient based on the individual’s brain activity. Using regional brain glucose metabolism as measured by positron emission tomography (PET) as a proxy for neural activity, her group sought to determine whether baseline resting state activity predicted remission after 12 weeks of treatment with either the selective serotonin reuptake inhibitor escitalopram (10 to 20 mg per day) or 16 sessions of cognitive-behavioral therapy. The study sample initially comprised 82 men and women who were randomized between the two treatments. Of these, 65 patients completed the study and 38 had clear outcomes and acceptable PET data. The 38 patients who comprise the analyzable data set were distributed as follows: 11 who went into remission with escitalopram (six non-responders) and 12 who did so with CBT (nine non-responders).
The major findings were that hypometabolism of glucose in the insula, likely reflecting reduced activity of neurons in this brain region, was associated with remission using CBT, and with poor response to escitalopram. Contrariwise, insula hypermetabolism, reflecting increased activity of neurons in this brain region, was associated with remission using escitalopram and with poor response to CBT.
The authors conclude that baseline insula metabolism is the first objective marker to guide initial treatment selection in depression. Closer scrutiny of their data is worthwhile. First, they eliminated from their primary analysis the responders to CBT or to escitalopram who did not go into remission. More specifically, partial responders to escitalopram or CBT were excluded from the analysis. They did so in order to accentuate the differences between the extremes in the depressed population; the results revealed clear differences in glucose metabolism in six regions: the right anterior insula, right motor cortex, left premotor cortex, right inferior temporal cortex, left amygdala, and precuneus.
The results of the new study also suggest these circuits could be a biomarker, but as Mayberg and Nemeroff point out, these are still early days and proofs of concept. Still, these experimental data offer another reason not to give up if the first treatment doesn’t work.