Resting-State Brain Dynamics Unique to Anxiety in Major Depressive Disorder

Abstract

Background. Major depressive disorder with anxiety (MDD-A) is considered as a clinical subphenotype of major depressive disorder (MDD). There continues to be debate regarding the legitimacy of differentiating between the two diagnoses and their neurobiological foundations, given that the symptoms of MDD and MDD-A overlap. However, there is still a dearth of research that delineates the dynamic alteration in the brain activity unique to anxiety in MDD with resting-state functional magnetic resonance imaging (R-fMRI). Methods. 30 patients with MDD, 45 patients with MDD-A, and 46 healthy controls completed R-fMRI scans. Dynamic analysis was utilized to generate many widely used measures, such as voxel-mirrored homotopic connectivity, global signal correlation, regional homogeneity, amplitude of low-frequency fluctuations, and network degree centrality. Concordance between these indices was assessed with Kendall’s W coefficient for both volume and voxel-wise concordance. Finally, the differences in voxel-wise concordance among the groups were looked at, and their relationship to clinical factors was assessed. Results. Compared to the healthy control group, both MDD and MDD-A exhibited decreased dynamic R-fMRI indices in the bilateral calcarine, left postcentral gyrus, inferior parietal lobe, right lingual gyrus, and middle occipital gyrus. In comparison to the MDD group, the MDD-A group displayed a reduction in voxel-wise concordance in the left medial superior frontal gyrus. Furthermore, it was observed that the MDD and MDD-A groups both exhibited a negative correlation between anxiety levels and voxel-wise concordance in the left medial superior frontal gyrus. Conclusions. The aberrant voxel-wise concordance of the left medial superior frontal gyrus may differentiate the neurobiological aspects of MDD with anxiety symptom from MDD. These findings indicate the underlying mechanisms implicated in MDD with anxiety symptom while highlighting the significance of accounting for heterogeneity in depression research.