Baseline Functional Connectivity in Resting State Networks Associated with Depression and Remission Status after 16 Weeks of Pharmacotherapy: A CAN-BIND Report

Abstract

Understanding the neural underpinnings of major depressive disorder (MDD) and its treatment could improve treatment outcomes. So far, findings are variable and large sample replications scarce. We aimed to replicate and extend altered functional connectivity associated with MDD and pharmacotherapy outcomes in a large, multisite sample. Resting-state fMRI data were collected from 129 patients and 99 controls through the Canadian Biomarker Integration Network in Depression. Symptoms were assessed with the Montgomery-Åsberg Depression Rating Scale (MADRS). Connectivity was measured as correlations between four seeds (anterior and posterior cingulate cortex, insula and dorsolateral prefrontal cortex) and all other brain voxels. Partial least squares was used to compare connectivity prior to treatment between patients and controls, and between patients reaching remission (MADRS ≤ 10) early (within 8 weeks), late (within 16 weeks), or not at all. We replicated previous findings of altered connectivity in patients. In addition, baseline connectivity of the anterior/posterior cingulate and insula seeds differentiated patients with different treatment outcomes. The stability of these differences was established in the largest single-site subsample. Our replication and extension of altered connectivity highlighted previously reported and new differences between patients and controls, and revealed features that might predict remission prior to pharmacotherapy. Trial registration:ClinicalTrials.gov: NCT01655706.

Keywords: fMRI; functional connectivity; major depressive disorder; resting state networks.

© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Figures

Figure 1

Results from PLS analyses comparing patients with MDD and controls in terms of (A) connectivity between the ACC ROI (red sphere) and all other voxels, and (B) connectivity between the PCC ROI (red sphere) and all other voxels, projected onto a smoothed cortical surface using BrainNet Viewer (Xia et al. 2013). The ROI consisted of a cube of 27 voxels, centered around the seed voxel (ACC: [0, 48–4]; PCC: [0–60, 28]). The correlation bar graph shows group-dependent differences in the correlation between the ROI voxels and the areas identified in the brain image. The error bars indicate the 95% confidence intervals derived from bootstrap estimation. The brain image illustrates the areas that expressed this contrast most stably across participants, as determined by bootstrapping. Only the 10–15 clusters (>10 voxels) with the highest BSRs (ACC: |BSR| ≥ 2.1; PCC: |BSR| ≥ 2.0) are presented. Subcortical areas are projected onto the nearest surface, if significant. Cerebellar clusters are not illustrated, but they are listed in Supplementary Table 9 (ACC) and Supplementary Table 10 (PCC). Orange clusters indicate stronger, while purple clusters indicate weaker connectivity in patients as compared with controls. C = controls, P = patients with MDD, vmPFC = ventromedial prefrontal cortex.

Figure 2

Results from PLS analyses comparing patients with MDD and controls in terms of (A) connectivity between the insula ROI (left—red sphere) and all other voxels and (B) connectivity between the dlPFC ROI (left—red sphere) and all other voxels, projected onto a smoothed cortical surface using BrainNet Viewer (Xia et al. 2013). The ROI consisted of a cube of 27 voxels around the seed voxel (insula: [−40, 20, 0]; dlPFC: [−48, 16, 32]). The correlation bar graph shows group-dependent differences in the correlation between the ROI voxels and the areas identified in the brain image. The error bars indicate the 95% confidence intervals derived from bootstrap estimation. The brain image illustrates the areas that expressed this contrast most stably across participants, as determined by bootstrapping. Only the 10–15 clusters (>10 voxels) with the highest BSRs (insula: |BSR| ≥ 2.0; dlPFC: |BSR| ≥ 2.0) are presented. Subcortical areas are projected onto the nearest surface, if significant. Cerebellar clusters are not illustrated, but they are listed in Supplementary Table 11 (insula) and Supplementary Table 12 (dlPFC). Orange clusters indicate stronger, while purple clusters indicate weaker connectivity in patients compared with controls. C = controls, P = patients with MDD.

Figure 3

Results from PLS analysis comparing early, late and nonremitters in terms of connectivity between the ACC ROI (red sphere) and all other voxels, projected onto a smoothed cortical surface using BrainNet Viewer (Xia et al. 2013). The ROI consisted of a cube of 27 voxels around the seed voxel [0, 48–4]. The correlation bar graph shows group-dependent differences in the correlation between the ROI voxels and the areas identified in the brain image. The error bars indicate the 95% confidence intervals derived from bootstrap estimation. The brain image illustrates the areas that expressed this contrast most stably across participants, as determined by bootstrapping. Only the 10–15 clusters (>10 voxels) with the highest BSRs (|BSR| ≥ 2.4) are presented. Subcortical areas are projected onto the nearest surface, if significant. Cerebellar clusters are not illustrated, but they are listed in Table 3. Orange clusters indicate stronger, while purple clusters indicate weaker connectivity in early compared with late and NR.

Figure 4

Results from PLS analysis comparing early, late and nonremitters in terms of connectivity between the PCC ROI (red sphere) and all other voxels, projected onto a smoothed cortical surface using BrainNet Viewer (Xia et al. 2013). The ROI consisted of a cube of 27 voxels, centered around the seed voxel [0–60, 28]. The correlation bar graph shows group-dependent differences in the correlation between the ROI voxels and the areas identified in the brain image. The error bars indicate the 95% confidence intervals derived from bootstrap estimation. The brain image illustrates the areas that expressed this contrast most stably across participants, as determined by bootstrapping. Only the 10–15 clusters (>10 voxels) with the highest BSRs (|BSR| ≥ 2.4) are presented. Subcortical areas are projected onto the nearest surface, if significant. Cerebellar clusters are not illustrated, but they are listed in Table 4. Orange clusters indicate stronger, while purple clusters indicate weaker connectivity in ER compared with late and nonremitters, as well as in late compared with nonremitters. pgACC = pregenual anterior cingulate cortex.

Figure 5

Results from PLS analysis comparing early, late and nonremitters in terms of connectivity between the insula ROI (left—red sphere) and all other voxels, projected onto a smoothed cortical surface using BrainNet Viewer (Xia et al. 2013). The ROI consisted of a cube of 27 voxels, centered around the seed voxel [−40, 20, 4]. (A) The contrast and spatial pattern identified in the first LV, (B) contrast and spatial pattern identified for the second LV. The correlation bar graph shows group-dependent differences in the correlation between the ROI voxels and the areas identified in the brain image. The error bars indicate the 95% confidence intervals derived from bootstrap estimation. The brain image illustrates the areas that expressed this contrast most stably across participants, as determined by bootstrapping. Only the 10–15 clusters (>10 voxels) with the highest BSRs (|BSR| ≥ 2.4) are presented. Subcortical areas are projected onto the nearest surface, if significant. Cerebellar clusters are not illustrated, but they are listed in Table 5. In (A), orange clusters indicate stronger, while purple clusters indicate weaker connectivity in ER compared with LR. In (B), orange clusters indicate stronger, while purple clusters indicate weaker connectivity in nonremitters compared with early and LR.