Topological network mechanisms of clinical response to antidepressant treatment in drug-naive major depressive disorder

Functional connectivity between dorsal attention and default mode networks mediates subjective sleep duration and depression in young females

BACKGROUND

Depression prevails throughout the world. Young females are more likely to suffer from depression because of lack of sleep.

METHODS

We recruited 405 young female participants to assess their subjective sleep duration and self-rating depression. The resting-state magnetic resonance imaging (rs-fMRI) data were collected to identify the brain regions related to sleep duration and depression, and a mediating model was established among sleep duration, depression and functional connectivity (FC) of rs-fMRI.

RESULTS

Correlation analysis indicated that subjective sleep duration was negatively associated with self-rating depression in young females (r = -0.22, p < .001). The network connectivity between dorsal attention network (DAN) and default mode network (DMN) positively correlated with self-rating depression (r = 0.13, p < .05), and negatively correlated with subjective sleep duration (r = -0.14, p < .01). Furthermore, the mediation analysis revealed that the FC of DAN-DMN significantly mediated the effect of sleep duration on depression.

LIMITATIONS

The study was a cross-section design and the sleep duration of the participants was subjectively reported. Future studies should consider to track the participants longitudinally and to measure the objective sleep duration by actigraph or polysomnography.

CONCLUSIONS

The participants with less sleep duration are more prone to develop depression feelings. The FC of DAN-DMN mediated the effect of sleep duration on depression. Thus, the FC of DAN-DMN could be consider as a neural target to relieve depression by increasing sleep duration in young females.

Effects of escitalopram therapy on functional brain controllability in major depressive disorder

Antidepressant drugs are the mainstay of treatment for patients with major depressive disorders (MDD). Given the critical role of the underlying neural control mechanism in the physiopathology of depression, this study aims to investigate the effects of escitalopram, a type of antidepressant drug, on the changes of functional brain controllability throughout the escitalopram treatment for MDD. We collected resting-state functional magnetic resonance imaging data from 20 unmedicated major depressive patients at baseline (visit 1, pre-treatment), one week (visit 2, 1-week after the onset of the treatment) and six weeks (visit 3, after the 6-week escitalopram treatment). Our results revealed that the global average and modal controllability of MDD patients were significantly larger and smaller, respectively, compared to healthy subjects (P < 0.01). Furthermore, the modal controllability rank of the frontoparietal network in depression patients was also significantly smaller than the healthy subjects (P < 0.01). However, throughout the escitalopram treatment, the global average and modal controllability, and the controllability of the default mode network and frontoparietal network of MDD patients were consistently changed to the healthy subjects' level. Our results also showed that the changes of global average and modal controllability measures can predict the improvements of clinical scores of the MDD patients as the escitalopram treatment advanced (P < 0.05). In conclusion, this study reveals promising brain controllability-based biomarkers to mechanistically understand and predict the effects of the escitalopram treatment for depression and maybe extended to predict and understand the effects of other interventions for other neurological and psychiatric diseases.