Can brain connectivity predict who benefits from depression treatment?

Depression in teens and young adults is highly heterogeneous, making it hard to predict who will respond well to certain treatments. A new study published in General Psychiatry suggests that analyzing brain network activity and inflammation levels could help tailor more effective therapies for this age group.

Researchers from the Affiliated Brain Hospital of Guangzhou Medical University investigated the effectiveness of intermittent theta burst stimulation (iTBS), a fast 3-minute brain stimulation treatment for depression. Despite its potential benefits, patient responses to iTBS vary significantly. To understand these differences, they examined two key factors: the function of the default mode network (DMN), which is involved in self-focused thinking and emotion regulation, and the levels of inflammatory markers such as interleukin-6 (IL-6) and C-reactive protein (CRP).

The study involved 82 individuals aged 12–25 with depression. By combining brain scans and blood tests, the study identified two distinct brain network patterns:

Subgroup 1: The group showed more varied connections and stronger activity in brain regions linked to mental flexibility. These participants improved significantly in processing speed after receiving iTBS.

Subgroup 2: This group had more uniform connectivity but showed no cognitive benefits from the treatment.

Crucially, for Subgroup 1, higher levels of IL-6 and CRP before treatment were linked to better cognitive improvements after receiving active stimulation. Specifically, those in the active treatment group within Subgroup 1 showed significantly greater improvements in symbol coding compared to the sham group. This indicates that elevated levels of IL-6 and CRP may be useful predictors of how well individuals will respond to iTBS treatment in terms of cognitive function.

“Brain structure and inflammation levels might help identify who benefits most from this treatment,” the authors noted.

While both groups saw similar reductions in depression symptoms, the study’s findings imply that using data-driven network analyses could offer new insights into clinical outcomes of iTBS treatment and provide clues for predicting cognitive improvements from an inflammatory perspective.