Webinar Recap: Teasing out Different Subtypes of Depression

Recent brain scan analysis suggests four distinct kinds of depression, says Conor Liston, M.D., Ph.D., Assistant Professor of Neuroscience and Psychiatry at Weill Cornell Medicine’s Feil Family Brain & Mind Research Institute.

In a webinar broadcast by the Foundation on September 12, 2017, Dr. Liston, recipient of a 2013 Young Investigator grant, described how identifying subtypes of depression based on “underlying biology” could help target treatment. For example, preliminary evidence suggests that patients in two of the four depression subtypes his team found were more likely to respond to transcranial magnetic stimulation (TMS).

Seeing into the Brain. MRI brain scans of people with depression look normal. However, brain imaging does show areas of the brain becoming brighter and dimmer. When more blood flows to an area, it lights up, a sign of activity. It’s also possible to see which areas tend to fluctuate together—indicating “functional connectivity,” Dr. Liston explained. These activity signals provide a window into the activity of the synapses within a depressed brain. Synapses are the tiny gaps across which neighboring neurons communicate.

Dr. Liston gathered brain scan data from researchers around the country, some of it still unpublished. The webinar talk makes reference to scans made at five universities of 333 patients with active major depression (all had unipolar, as opposed to bipolar depression, which is the form of depression that occurs in bipolar disorder). When it came time to replicate that work, his team used a second set of scans of 215 depressed patients. Both sets also included healthy controls.

Extracting what’s called a “BOLD signal” from each of many brain regions, Dr. Liston’s team created color-coded maps of shared fluctuations. (BOLD stands for blood-oxygen-level dependent contrast imaging.) Around 33,000 unique “connectivity features” emerged, most of which had nothing to do with depression.

A “Map” of Depression. What does depression look like in a connectivity map? Some abnormal features showed up in all of the brain scans of depressed patients. Variations in those features predicted the severity of the classic symptoms of depression: low energy, fatigue, and anhedonia, a loss of interest in once enjoyable activities.

Using a statistical method to parse the data, Dr. Liston’s team looked deeper for combinations of features that correlated with different symptoms—symptom-sets that were present only in some depressed patients, not all. The goal: to create distinct “clusters” of patients within the overall group defined by the Diagnostic and Statistical Manual of Mental Disorders (the famous “DSM manual” used by doctors to diagnose patients).

Different depressed people often seem to have different illnesses. As Dr. Liston put it, “Someone who’s suffering from weight loss, no appetite, only able to sleep four or five hours a night, very agitated, very anxious, is probably not suffering from exactly the same biological problem as someone who has gained a lot of weight because they have an increased appetite, they’re craving carbohydrates all the time; they’re sleeping 19 hours a day, can’t get out of bed, and they feel slowed and lethargic and can barely move.”

Consistent with that observation, in the brain scan analysis, four subtypes appeared. In two of the subtypes, patients suffer more anxiety than the rest; in the other two subtypes, they have more severe anhedonia.

The scientists were pleased that the results were stable: When scanned on separate occasions 4 or 5 weeks apart, most participants landed in the same “biotype.”

It was also notable that in a sample of 75 patients diagnosed with schizophrenia, almost none fit into the four proposed depression subtypes. These and other tests convinced the researchers that they were headed toward a potentially useful tool for clinicians.

A Potential Tool. When they tested their biotype insights on scans from people who had received TMS therapy, it turned out that people in subtype 1, an anxious group, were most likely to respond, followed by those in subtype 3, a more anhedonic group. In fact, the subtypes, along with other clues from the scans, were more predictive of treatment response than any of the clinical symptoms of depression that individual patients reported.

Another intriguing discovery is that brain scans from people diagnosed with anxiety, but not depression, fit the more anxious subtypes. Reasoning that some “altered connectivity features” are likely to be “stable features of the person’s brain,” Dr. Liston suggested that “they might precede the onset of symptoms…and be…a sign of risk for developing depression.”

Dr. Liston also hopes to tease out subtypes that would distinguish people who have bipolar depression, saying he might have progress to report in the next year. People with bipolar disorder often lose time taking standard antidepressants, so a tool to identify them early would go a long way to enhance lives.

Dr. Liston stressed that many colleagues were part of the research discussed in his webinar. These include: Scientific Council Member, 2015 Ruane Prizewinner BJ Casey, Ph.D.; 2010 Young Investigator Marc J. Dubin, M.D., Ph.D.; 2016 Young Investigator Amit Etkin, M.D., Ph.D.; 2012 and 2009 Young Investigator Jennifer Keller, Ph.D.; Scientific Council Member, 1995 Independent Investigator and 1991 Young Investigator Helen S. Mayberg, M.D.; 2016 Young Investigator Desmond Jay Oathes, Ph.D.; 2002 Distinguished Investigator and 1998 Independent Investigator Alvaro Pascual-Leone, M.D., Ph.D.; and Scientific Council Member, 2005 Falcone Prizewinner Alan F. Schatzberg, M.D.

Written by Temma Ehrenfeld