Brain scans may finally end the guesswork in depression treatment: Study
Major depressive disorder (MDD) is a widespread and serious mental health condition that affects how people think, feel, and function in daily life. It is already a leading cause of disability, and researchers expect it to become the most common and costly illness worldwide by 2030. While many medications are available to treat depression, finding the right one remains difficult. Nearly one-third of patients do not improve after trying their first antidepressant, often leading to months of trial and error.
One reason for this challenge is the lack of clear, objective tools that can help doctors predict which treatment will work best for a specific person. Most treatment decisions are still based on symptoms, medical history, and experience rather than biological markers. A recent study published in General Psychiatry set out to explore whether traditional Chinese medicine (TCM) could offer new insights into treating MDD and whether brain imaging could help predict treatment response.
Testing a Traditional Remedy Against a Standard Antidepressant
The researchers conducted a randomized, double-blind, placebo-controlled clinical trial involving 28 outpatients diagnosed with MDD at the Fourth People's Hospital of Taizhou. In a randomized trial, participants are assigned to treatment groups by chance. Double-blind means neither the patients nor the researchers knew who received which treatment, helping reduce bias. A placebo-controlled design allows scientists to compare real treatment effects against inactive substitutes.
Participants were divided into two groups. One group received Yueju Pill, a traditional Chinese herbal medicine, along with a placebo for escitalopram. The second group received escitalopram, a commonly prescribed antidepressant, along with a placebo for Yueju Pill. This design allowed researchers to directly compare the two treatments under similar conditions.
To track outcomes, the team measured depression severity using the 24-item Hamilton Depression Scale (HAMD-24), a widely used clinical questionnaire. They also collected peripheral blood samples and performed MRI brain scans to examine changes in brain structure and biology.
Brain Chemistry and Structural Networks Tell Different Stories
After treatment, both groups showed improvements in their depression symptoms, suggesting that Yueju Pill and escitalopram were similarly effective at reducing clinical signs of depression. However, a key biological difference emerged. Only patients in the Yueju Pill group experienced a significant increase in serum brain-derived neurotrophic factor (BDNF), a protein that supports brain cell growth, connectivity, and mood regulation. Lower BDNF levels have previously been linked to depression, making this finding especially notable.
The brain imaging data revealed even deeper insights. Researchers found that specific networks formed by brain structures could predict changes in depression scores in both treatment groups. These networks reflect how different brain regions are organized and connected.
More strikingly, certain brain patterns were only predictive in patients taking Yueju Pill. These patterns were based on sulcus depth and cortical thickness, which describe the folding of the brain surface and the thickness of the brain's outer layer. Both features are linked to brain development and function. Additional analysis showed that the brain's visual network played a particularly important role in predicting improvements in both depression symptoms and BDNF levels among those treated with Yueju Pill.
Toward Personalized Treatment for Major Depression
Taken together, the findings suggest that brain network patterns identified through MRI scans could help predict how individual patients with MDD respond to Yueju Pill treatment. This approach moves beyond symptom-based decision-making and points toward more personalized antidepressant therapy.
If validated in larger studies, this strategy could allow clinicians to match patients with treatments that are more likely to work for them, reducing delays and improving outcomes. As Dr. Zhang, the study's leading author, explained, "The brain networks can then be fed to the predictive models constructed in this study to predict patients' responses to Yueju Pill treatment. Based on the predicted responses, we can then determine whether the patient is suitable for Yueju Pill treatment."
This research highlights how combining traditional medicine with modern brain imaging may open new paths toward precision care for depression.
Reference::
Yuxuan Zhang, Yiwei Ren, Gang Chen, Haosen Wang, Jinlin Miao, Bo Cui, Zhilu Zou, Jin Feng, Chunkou Hong, Mingzhi Han, Jinhui Wang. Brain network predictors of changes in symptoms and serum BDNF following antidepressant treatment with escitalopram and Yueju Pill in major depressive disorder: a randomised, double-blind, placebo-controlled pilot study. General Psychiatry, 2025; 38 (5): e102041 DOI: 10.1136/gpsych-2025-102041
