As many of us know, not all depression is the same. So, researchers at Stanford Medicine have combined brain imaging with machine learning to study this. The results reveal six subtypes of depression, potentially revolutionizing depression treatment. The study proposes a future where a quick brain scan could guide doctors to the most effective treatment for each patient.
Traditional methods of treating depression rely heavily on trial and error, often leading to prolonged periods of ineffective treatment. About 30% of patients experience treatment-resistant depression, where multiple medications and therapies fail. Additionally, for up to two-thirds of those affected, treatments do not fully alleviate symptoms.
Dr. Leanne Williams of Stanford Medicine aims to change this.
“The goal of our work is figuring out how we can get it right the first time,” Williams said. “It’s very frustrating to be in the field of depression and not have a better alternative to this one-size-fits-all approach.”
Tailoring Treatments
Dr. Williams and her team used functional MRI (fMRI) to scan the brains of 801 participants diagnosed with depression or anxiety. The scans were conducted both at rest and during tasks designed to test cognitive and emotional function. Using machine learning, a subfield of artificial intelligence that gives computers the ability to learn without explicitly being programmed, the researchers identified distinct patterns of brain activity and connectivity corresponding to different biotypes of depression.
The study also explored how these biotypes respond to various treatments by randomly assigning 250 of the participants to receive one of three commonly used antidepressants or behavioral talk therapy. As expected, each subtype responded to treatment very differently. Patients with overactivity in cognitive regions of the brain, for example, showed the best response to the antidepressant venlafaxine. On the other hand, those with high activity in three specific brain regions associated with depression and problem-solving responded better to behavioral talk therapy.
Meanwhile, individuals with lower activity in brain circuits controlling attention were less likely to benefit from talk therapy. This suggests that trying a pharmaceutical treatment first to address this lower activity could make patients in this subtype more responsive to talk therapy.
“To our knowledge, this is the first time we’ve been able to demonstrate that depression can be explained by different disruptions to the functioning of the brain,” Williams said. “In essence, it’s a demonstration of a personalized medicine approach for mental health based on objective measures of brain function.”
A Complex Condition
The researchers note that these findings align with our understanding of brain function and depression. These insights could pave the way for a personalized medicine approach in mental health, where treatments are tailored to an individual’s brain activity patterns.
The study also found that these biotypes align with distinct symptom patterns and task performance differences among participants. For instance, individuals with overactive cognitive regions exhibited higher levels of anhedonia, which is the inability to experience pleasure. This group also struggled more with executive function tasks compared to others. Conversely, participants who responded best to talk therapy made errors in executive tasks but excelled in cognitive challenges. Executive tasks and functions involve mental processes like planning, focusing attention, and managing multiple tasks at once.
While the study marks a significant advancement, it also highlights the complexity of depression. Notably, one of the six identified biotypes showed no noticeable differences from non-depressed individuals in the studied brain regions. This indicates that other areas of brain function might be involved. Scientists just haven’t yet explored the full biology of the brain in all its richness and complexity to properly dissect this particular subtype of depression.
The Road Ahead
The researchers are currently expanding their study to include more participants and are testing a broader range of treatments.
Dr. Laura Hack, one of the study’s collaborators, has already begun using this imaging technique in her clinical practice through an experimental protocol. The team aims to establish standardized methods for broader clinical use, hoping to enable more precise treatment prescriptions across the field of psychiatry. By moving away from the one-size-fits-all approach and towards treatments informed by detailed brain function assessments, doctors could significantly improve outcomes for patients with depression.
“To really move the field toward precision psychiatry, we need to identify treatments most likely to be effective for patients and get them on that treatment as soon as possible,” said Dr. Jun Ma, professor of medicine at the University of Illinois Chicago. “Having information on their brain function, in particular the validated signatures we evaluated in this study, would help inform more precise treatment and prescriptions for individuals.”
The findings appeared in the journal Nature Medicine.
The six biotypes of depression and anxiety identified by the new study include:
Biotype DC+SC+AC+:
- Characteristics: Hyperconnectivity in the default mode, salience, and attention circuits.
- Clinical Correlates: Slowed emotional and attentional responses.
- Best Treatment: Responded better to behavioral interventions.
Biotype AC−:
- Characteristics: Hypoconnectivity in the attention circuit.
- Clinical Correlates: Lapses in concentration, impulsivity.
- Best Treatment: Less responsive to behavioral treatments.
Biotype NSA+PA+:
- Characteristics: Heightened activation in emotional processing regions.
- Clinical Correlates: Prominent anhedonia.
- Best Treatment: Required targeted emotional regulation therapies.
Biotype CA+:
- Characteristics: Increased cognitive control circuit activity.
- Clinical Correlates: Threat-related symptoms, negative bias.
- Best Treatment: Showed a better response to the antidepressant venlafaxine.
Biotype NTCC−CA−:
- Characteristics: Reduced connectivity and activation in cognitive control during threat processing.
- Clinical Correlates: Impaired cognitive control, faster reaction times to sad stimuli.
- Best Treatment: Requires further investigation.
Biotype DXSXAXNXPXCX:
- Characteristics: No prominent circuit dysfunction.
- Clinical Correlates: Slower reaction times to implicit threat priming.
- Best Treatment: Needs more research to determine optimal therapies.
