Disrupted intrinsic functional brain topology in patients with major depressive disorder

Abstract

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.

Fig. 1. Group differences in network topological properties between major depressive disorder (MDD) patients and normal controls (NCs).

a Violin plots illustrating the area under the curve (AUC) parameters of the global efficiency (E_glob) and local efficiency (E_loc) for MDD patients and NCs. Means and standard deviations are depicted. b E_glob and E_loc across a density range between 10% and 34%. Each point and error bar denote the mean and standard deviation at each density level, respectively. Asterisks indicate a significant difference at this density threshold. c Group differences in efficiency, degree and betweenness at the nodal level. Insignificant nodes are shown as green spheres, whereas blue (MDD < NC) and red (MDD > NC) spheres denote significant differences after FDR correction. The size of the significant nodes reflects the effect sizes of group differences. **: p < 0.01.

Fig. 2. Subgroup differences in network topological properties (efficiency, E_glob, and local efficiency, E_loc).

Distributions of areas under the curve (AUCs) are depicted. a First episode drug naïve (FEDN) patients with major depressive disorder (MDD) vs. normal controls (NCs). b Patients with recurrent MDD vs. NCs. c recurrent patients with MDD vs. FEDN patients. **: p < 0.01, ***: p < 0.001.

Fig. 3. Subgroup differences in efficiency, degree and betweenness at the nodal level.

Nonsignificant nodes are shown as green spheres. Blue (a: FEDN < NC; b: recurrent MDD < NC; c: recurrent MDD < FEDN) and red (a: FEDN > NC; b: recurrent MDD > NC; c: recurrent MDD > FEDN) spheres denote significant differences after FDR correction. The sizes of the significant nodes reflect the effect sizes of group differences. NC normal control, FEDN first-episode drug naïve.

Fig. 4. L_p and C_p differences between major depressive disorder (MDD) patients and normal controls (NCs) as well as subgroup contrasts.

Distributions of areas under the curve (AUCs) are depicted. a MDD vs. NCs. b First-episode drug naïve (FEDN) patients with major depressive disorder (MDD) vs. normal controls (NCs). c Patients with recurrent MDD vs. NCs. d patients with recurrent MDD vs. FEDN patients. *: p < 0.05, **: p < 0.01, ***: p < 0.001.