Predicting anhedonia and negative cognitive processing changes after 8-week SSRIs treatment in depression from...

Emerging findings have highlighted that the individual neural characteristics of patients with major depressive disorder (MDD) were correlated with treatment response. However, the associations between the individual differential structural covariance network (IDSCN) of MDD patients and dimensional symptoms changes (i.e., anhedonia and negative cognitive processing bias) after antidepressant treatment remain less investigated. T1-weighted structural images were collected from 144 unmedicated patients with first-episode MDD and 161 healthy controls. IDSCN analyses were conducted to get the individual structural covariance network of each MDD patient. Among 144 MDD patients, 92 patients completed both baseline and 8-week follow-up assessments after selective serotonin reuptake inhibitors (SSRIs) treatment. Connectome-based predictive modeling (CPM) was used to test the predictive effect of IDSCNs of MDD patients on changes in anhedonia and negative cognitive processing bias following treatment. Significant individual heterogeneity in the IDSCN was observed among MDD patients. Baseline IDSCN edges significantly predicted post-treatment changes in anhedonia (r = 0.358, P < 0.001) and negative cognitive processing bias (r = 0.264, P = 0.011). Specifically, predictive edges for anhedonia changes were primarily distributed between caudate and temporal regions, whereas those for negative cognitive processing bias were predominantly distributed between the subcortical and frontal/parietal regions, as well as between visual network and medial prefrontal regions. Individual differential structural covariance networks can predict changes in anhedonia and negative cognitive processing bias after treatment with SSRIs, but the neural characteristics that demonstrate their predictive effect vary and should be validated in independent external datasets.