Functional connectivity between the habenula and posterior default mode network contributes to the response of the duloxetine effect in major depressive disorder.

This study aims to investigate the functional connectivity (FC) changes of the habenula (Hb) among patients with major depressive disorder (MDD) after 12 weeks of duloxetine treatment (MDD12). Patients who were diagnosed with MDD for the first time and were drug-naïve were recruited at baseline as cases. Healthy controls (HCs) matched for sex, age, and education level were also recruited at the same time. At baseline, all participants underwent resting-state functional MRI. FC analyses were performed using the Hb seed region of interest, and three groups including HCs, MDD group and MDD12 group were compared using whole-brain voxel-wise comparisons. Compared to the HCs, the MDD group had decreased FC between the Hb and the right anterior cingulate cortex at baseline. Compared to the HCs, the FC between the Hb and the left medial superior frontal gyrus decreased in the MDD12 group. Additionally, the FC between the left precuneus, bilateral cuneus and Hb increased in the MDD12 group than that in the MDD group. No significant correlation was found between HDRS-17 and the FC between the Hb, bilateral cuneus, and the left precuneus in the MDD12 group. Our study suggests that the FC between the post-default mode network and Hb may be the treatment mechanism of duloxetine and the treatment mechanisms and the pathogenesis of depression may be independent of each other.

Reduced gray matter volume of the hippocampal tail in melancholic depression: evidence from an MRI study.

BACKGROUND: Melancholic depression (MD) is one of the most prevalent and severe subtypes of major depressive disorder (MDD). Previous studies have revealed inconsistent results regarding alterations in grey matter volume (GMV) of the hippocampus and amygdala of MD patients, possibly due to overlooking the complexity of their internal structure. The hippocampus and amygdala consist of multiple and functionally distinct subregions, and these subregions may play different roles in MD. This study aims to investigate the volumetric alterations of each subregion of the hippocampus and amygdala in patients with MD and non-melancholic depression (NMD). METHODS: A total of 146 drug-naïve, first-episode MDD patients (72 with MD and 74 with NMD) and 81 gender-, age-, and education-matched healthy controls (HCs) were included in the study. All participants underwent magnetic resonance imaging (MRI) scans. The subregional segmentation of hippocampus and amygdala was performed using the FreeSurfer 6.0 software. The multivariate analysis of covariance (MANCOVA) was used to detect GMV differences of the hippocampal and amygdala subregions between three groups. Partial correlation analysis was conducted to explore the relationship between hippocampus or amygdala subfields and clinical characteristics in the MD group. Age, gender, years of education and intracranial volume (ICV) were included as covariates in both MANCOVA and partial correlation analyses. RESULTS: Patients with MD exhibited a significantly lower GMV of the right hippocampal tail compared to HCs, which was uncorrelated with clinical characteristics of MD. No significant differences were observed among the three groups in overall and subregional GMV of amygdala. CONCLUSIONS: Our findings suggest that specific hippocampal subregions in MD patients are more susceptible to volumetric alterations than the entire hippocampus. The reduced right hippocampal tail may underlie the unique neuropathology of MD. Future longitudinal studies are required to better investigate the associations between reduced right hippocampal tail and the onset and progression of MD.

Subcortical neural mechanisms of childhood trauma impacts on personality traits.

This study aims to explore the relationships between childhood trauma (CT), personality traits, and subcortical structures. 171 healthy individuals completed the Childhood Trauma Questionnaire (CTQ), the Neuroticism-Extraversion-Openness Five-Factor Inventory (NEO-FFI), and underwent 3D T1-weighted MRI scans. Linear regression analyses indicated the complex relationship between CT, personality traits, and subcortical gray matter volume (GMV). Mediation analyses revealed that the right hippocampal GMV partially mediated the effects of CT on neuroticism. These findings suggest that CT affects the development of the Big Five personality traits, and alterations in subcortical structures are closely related to this process. Altered GMV in the right hippocampus may be a key neural mechanism for CT-induced neuroticism.

Cross-Domain Identification of Multisite Major Depressive Disorder Using End-to-End Brain Dynamic Attention Network.

Establishing objective and quantitative imaging markers at individual level can assist in accurate diagnosis of Major Depressive Disorder (MDD). However, the clinical heterogeneity of MDD and the shift to multisite data decreased identification accuracy. To address these issues, the Brain Dynamic Attention Network (BDANet) is innovatively proposed, and analyzed bimodal scans from 2055 participants of the Rest-meta-MDD consortium. The end-to-end BDANet contains two crucial components. The Dynamic BrainGraph Generator dynamically focuses and represents topological relationships between Regions of Interest, overcoming limitations of static methods. The Ensemble Classifier is constructed to obfuscate domain sources to achieve inter-domain alignment. Finally, BDANet dynamically generates sample-specific brain graphs by downstream recognition tasks. The proposed BDANet achieved an accuracy of 81.6%. The regions with high attribution for classification were mainly located in the insula, cingulate cortex and auditory cortex. The level of brain connectivity in p24 region was negatively correlated ( [Formula: see text]) with the severity of MDD. Additionally, sex differences in connectivity strength were observed in specific brain regions and functional subnetworks ( [Formula: see text] or [Formula: see text]). These findings based on a large multisite dataset support the conclusion that BDANet can better solve the problem of the clinical heterogeneity of MDD and the shift of multisite data. It also illustrates the potential utility of BDANet for personalized accurate identification, treatment and intervention of MDD.

Changes of cortical thickness in the first episode, drug-naive depression patients with and without melancholic features.

Melancholic depression (MD) is a more severe type of major depressive disorder (MDD) with a core feature of anhedonia. However, its pathophysiology remains unclear. The current study aims to investigate whether there is a significant difference in cortical thickness (CT) that can be used to differentiate MD patients from non-melancholic depression (NMD) patients. We recruited 137 first-episode drug-naive MDD patients and 75 healthy controls (HCs) for structural magnetic resonance imaging, analyzed using the Surface-based morphometry approach. Meanwhile, the MDD patients were divided into the MD and NMD subgroups according to their scores on the Montgomery-Asberg Depression Rating Scale and Hamilton Depression Rating Scale. No significant CT differences among the three groups were found. We also did not find significant CT changes between the NMD and the HCs groups or between the MD and NMD groups. However, the CT of the left postcentral gyrus and right precuneus among MD patients were larger than HCs. Moreover, the CT of the left postcentral gyrus and right precuneus were not correlated with the severity of the disease and illness duration. The findings suggest that the CT alterations of the left postcentral gyrus and the right precuneus are distinct pathological mechanisms for MD.

Atrophy of bilateral nucleus accumbens in melancholic depression.

Evidence from previous literature suggests that the nucleus accumbens (NAc), hippocampus, and amygdala play critical roles in the reward circuit. Meanwhile, it was also suggested that abnormalities in the reward circuit might be closely associated with the symptom of anhedonia of depression. However, few studies have investigated the structural alterations of the NAc, hippocampus, and amygdala in depression with anhedonia as the main clinical manifestation. Thus, the current study aimed to explore the structural changes of the subcortical regions among melancholic depression (MD) patients, especially in the NAc, hippocampus, and amygdala, to provide a theoretical basis for understanding the pathological mechanisms of MD. Seventy-two MD patients, 74 nonmelancholic depression (NMD) patients, and 81 healthy controls (HCs) matched for sex, age, and years of education were included in the study. All participants underwent T1-weighted MRI scans. Subcortical structure segmentation was performed using the FreeSurfer software. MD and NMD patients had reduced left hippocampal volume compared with HCs. Meanwhile, only MD patients had reduced bilateral NAc volumes. Moreover, correlation analyses showed correlations between left NAc volume and late insomnia and lassitude in MD patients. The reduced hippocampal volume may be related to the pathogenesis of major depressive disorder (MDD), and the reduced volume of the NAc may be the unique neural mechanism of MD. The findings of the current study suggest that future studies should investigate the different pathogenic mechanisms of different subtypes of MDD further to contribute to the development of individualized diagnostic and treatment protocols.

White Matter Network Disruption Is Associated With Melancholic Features in Major Depressive Disorder.

Background: The efficacy and prognosis of major depressive disorder (MDD) are limited by its heterogeneity. MDD with melancholic features is an important subtype of MDD. The present study aimed to reveal the white matter (WM) network changes in melancholic depression. Materials and Methods: Twenty-three first-onset, untreated melancholic MDD, 59 non-melancholic MDD patients and 63 health controls underwent diffusion tensor imaging (DTI) scans. WM network analysis based on graph theory and support vector machine (SVM) were used for image data analysis. Results: Compared with HC, small-worldness was reduced and abnormal node attributes were in the right orbital inferior frontal gyrus, left orbital superior frontal gyrus, right caudate nucleus, right orbital superior frontal gyrus, right orbital middle frontal gyrus, left rectus gyrus, and left median cingulate and paracingulate gyrus of MDD patients. Compared with non-melancholic MDD, small-worldness was reduced and abnormal node attributes were in right orbital inferior frontal gyrus, left orbital superior frontal gyrus and right caudate nucleus of melancholic MDD. For correlation analysis, the 7th item score of the HRSD-17 (work and interest) was positively associated with increased node betweenness centrality (aBC) values in right orbital inferior frontal gyrus, while negatively associated with the decreased aBC in left orbital superior frontal gyrus. SVM analysis results showed that abnormal aBC in right orbital inferior frontal gyrus and left orbital superior frontal gyrus showed the highest accuracy of 81.0% (69/83), the sensitivity of 66.3%, and specificity of 85.2% for discriminating MDD patients with or without melancholic features. Conclusion: There is a significant difference in WM network changes between MDD patients with and without melancholic features.

Identifying Changes of Brain Regional Homogeneity and Cingulo-Opercular Network Connectivity in First-Episode, Drug-Naïve Depressive Patients With Suicidal Ideation.

Objective: Adult patients with major depressive disorder (MDD) may not actively reveal their suicidal ideation (SI). Therefore, this study is committed to finding the alterations in the cingulo-opercular network (CON) that are closely related to SI with multi-imaging methods, thus providing neuroimaging basis for SI. Method: A total of 198 participants (129 MDD patients and 69 healthy controls) were recruited and evaluated with the Montgomery-Asberg Depression Rating Scale (MADRS). The healthy individuals formed the HC group, while the MDD patients were subdivided into no SI MDD (NSI, n = 32), mild SI MDD (MSI, n = 64), and severe SI MDD (SSI, n = 33) according to their MADRS item 10. We obtained MRI data of all participants and applied regional homogeneity (ReHo) analysis to verify a previous finding that links CON abnormality to SI. In addition, we employed the structural covariance network (SCN) analysis to investigate the correlation between abnormal structural connectivity of CON and SI severity. Results: Compared to those of the HC group, MDD ReHo values and gray matter volume (GMV) were consistently found abnormal in CON. ReHo values and GMV of the right orbital inferior frontal gyrus (ORBinf.R) in the MDD group decreased with the increase of SI. Compared to the HC group, the MDD patients showed enhanced structural connectivity of three pairs of brain regions in CON [ACC.L-left superior frontal gyrus (SFG.L), SFG.L-left middle temporal gyrus (MTG.L), and the SFG.L-left post-central gyrus (PoCG.L)]. Compared with that of the NSI and MSI groups, the structural connectivity of three pairs of brain regions in CON is enhanced in the SSI groups [ORBinf.L-right ventral posterior cingulate gyrus (VPCC.R), VPCC.R-SFG.R, and SFG.R-PoCG.R]. Conclusion: Our findings showed the distinctive ReHo, GMV, and SCN pattern of CON in MDD patients with SI; and with the severity of suicide, abnormal brain regions increased. Our finding suggested that MDD patients with different severity of SI have different neuroimaging changes.

Disrupted default mode network and executive control network are associated with depression severity on structural network.

OBJECTIVE: Major depressive disorder (MDD) is a psychiatric disorder with a relatively limited response to treatment. It is necessary to better understand the neuroanatomical mechanisms of structural networks. METHODS: The current study recruited 181 first-onset, untreated adult MDD patients: slight MDD (SD, N = 23), moderate MDD (MD, N = 77), Heavy MDD (HD, N = 81) groups; along with a healthy control group (HC, N = 81) with matched general clinical data. FreeSurfer was used to preprocess T1 images for gray matter volume (GMV), and the default mode network (DMN) and the execution control network (ECN) were analyzed by structural covariance network (SCN). RESULTS: Present study found that the GMV of brain regions reduced with the severity of the disease. Specifically, the GMV of the left anterior cingulate gyrus (ACC.L) is negatively correlated with MDD severity. In addition, the SCN connectivity of the whole-brain network increases with the increase of severity in MDD. ACC.L is a key brain region with increased connectivity between the left orbitofrontal in DMN and between the right orbitofrontal in ECN, which leads to damage to the balance of neural circuits. CONCLUSIONS: Patients with smaller GMV of ACC.L are more likely to develop severe MDD, and as a key region in both networks which have distinct structural network models in DMN and ECN. MDD patients with different severity have different neuroimaging changes in DMN and ECN.