Japanese researchers have identified three types of depression, one of which is untreatable with the use of selective serotonin reuptake inhibitors (SSRIs), the most commonly prescribed medication for the condition.
Specifically, the brain’s functional connectivity in regions involving the angular gyrus — associated with processing language and numbers, spatial cognition and attention — played a large role in determining whether SSRIs were effective in treating depression.
Patients with increased functional connectivity between the brain’s different regions who had also experienced childhood trauma had a subtype of depression that was non-responsive to treatment by SSRIs drugs.
On the other hand, the other two subtypes — where the participants’ brains did not show increased connectivity among its different regions or where participants had not experienced childhood trauma — tended to respond positively to treatments using SSRIs drugs.
The findings are published in the journal Scientific Reports.
For the study, scientists from the Neural Computational Unit at the Okinawa Institute of Science and Technology Graduate University (OIST), in collaboration with their colleagues at Nara Institute of Science and Technology and clinicians at Hiroshima University, collected clinical, biological, and life history data from 134 individuals.
Half of the participants were newly diagnosed with depression and the other half who had no depression diagnosis. All were asked about their sleep patterns, whether or not they had stressful issues, or other mental health conditions.
Using magnetic resonance imaging (MRI), the researchers mapped the participants’ brain activity patterns in different regions. The technique they used allowed them to examine 78 regions covering the entire brain, to identify how its activities in different regions are correlated.
“It has always been speculated that different types of depression exist, and they influence the effectiveness of the drug. But there has been no consensus,” says Professor Kenji Doya. “This is the first study to identify depression sub-types from life history and MRI data.”
With over 3,000 measurable factors, including whether or not participants had experienced trauma, the scientists were faced with the dilemma of finding a way to analyze such a large data set accurately.
“The major challenge in this study was to develop a statistical tool that could extract relevant information for clustering similar subjects together,” says Dr. Tomoki Tokuda, a statistician and the lead author of the study.
He designed a novel method that would help detect multiple ways of data clustering and the features responsible for it. Using this technique, the researchers identified a group of closely-placed data clusters, which consisted of measurable features essential for accessing the mental health of an individual. Three out of the five data clusters were found to represent different subtypes of depression.
This study not only identifies sub-types of depression for the first time, but also identifies some underlying factors and points to the need to explore new treatment techniques.
“It provides scientists studying neurobiological aspects of depression a promising direction in which to pursue their research,” says Doya.
In time, the researchers hope that these findings will help psychiatrists and therapists improve diagnoses and treat their patients more effectively.