Dataset Information

Multimetric structural covariance in first-episode major depressive disorder: a graph theoretical analysis.

ABSTRACT:

Background

Abnormalities of cortical morphology have been consistently reported in major depressive disorder (MDD), with widespread focal alterations in cortical thickness, surface area and gyrification. However, it is unclear whether these distributed focal changes disrupt the system-level architecture (topology) of brain morphology in MDD. If present, such a topological disruption might explain the mechanisms that underlie altered cortical morphology in MDD.

Methods

Seventy-six patients with first-episode MDD (33 male, 43 female) and 66 healthy controls (32 male, 34 female) underwent structural MRI scans. We calculated cortical indices, including cortical thickness, surface area and local gyrification index, using FreeSurfer. We constructed morphological covariance networks using the 3 cortical indices separately, and we analyzed the topological properties of these group-level morphological covariance networks using graph theoretical approaches.

Results

Topological differences between patients with first-episode MDD and healthy controls were restricted to the thickness-based network. We found a significant decrease in global efficiency but an increase in local efficiency of the left superior frontal gyrus and the right paracentral lobule in patients with first-episode MDD. When we simulated targeted lesions affecting the most highly connected nodes, the thickness-based networks in patients with first-episode MDD disintegrated more rapidly than those in healthy controls.

Limitations

Our sample of patients with first-episode MDD has limited generalizability to patients with chronic and recurrent MDD.

Conclusion

A systems-level disruption in cortical thickness (but not surface area or gyrification) occurs in patients with first-episode MDD.

SUBMITTER: Chen C

PROVIDER: S-EPMC9074807 | biostudies-literature | 2022 May-Jun

REPOSITORIES: biostudies-literature

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Publications

Multimetric structural covariance in first-episode major depressive disorder: a graph theoretical analysis.

Chen Chujun C Liu Zhening Z Xi Chang C Tan Wenjian W Fan Zebin Z Cheng Yixin Y Yang Jun J Palaniyappan Lena L Yang Jie J

Journal of psychiatry & neuroscience : JPN 20220504 3

<h4>Background</h4>Abnormalities of cortical morphology have been consistently reported in major depressive disorder (MDD), with widespread focal alterations in cortical thickness, surface area and gyrification. However, it is unclear whether these distributed focal changes disrupt the system-level architecture (topology) of brain morphology in MDD. If present, such a topological disruption might explain the mechanisms that underlie altered cortical morphology in MDD.<h4>Methods</h4>Seventy-six ...[more]

PMID: 35508328

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Project description:Complex networks inside the hippocampus could provide new insights into hippocampal abnormalities in various psychiatric disorders and dementia. However, evaluating intra-networks in the hippocampus using MRI is challenging. Here, we employed a high spatial resolution of conventional structural imaging and independent component analysis to investigate intra-networks structural covariance in the hippocampus. We extracted the intra-networks based on the intrinsic connectivity of each 0.9 mm isotropic voxel to every other voxel using a data-driven approach. With a total volume of 3 cc, the hippocampus contains 4115 voxels for a 0.9 mm isotropic voxel size or 375 voxels for a 2 mm isotropic voxel of high-resolution functional or diffusion tensor imaging. Therefore, the novel method presented in the current study could evaluate the hippocampal intra-networks in detail. Furthermore, we investigated the abnormality of the intra-networks in major depressive disorders. A total of 77 patients with first-episode drug-naïve major depressive disorder and 79 healthy subjects were recruited. The independent component analysis extracted seven intra-networks from hippocampal structural images, which were divided into four bilateral networks and three networks along the longitudinal axis. A significant difference was observed in the bilateral hippocampal tail network between patients with major depressive disorder and healthy subjects. In the logistic regression analysis, two bilateral networks were significant predictors of major depressive disorder, with an accuracy of 78.1%. In conclusion, we present a novel method for evaluating intra-networks in the hippocampus. One advantage of this method is that a detailed network can be estimated using conventional structural imaging. In addition, we found novel bilateral networks in the hippocampus that were disturbed in patients with major depressive disorders, and these bilateral networks could predict major depressive disorders.

Project description:ObjectiveIt is known that cytokines play a role in both depression and anxiety. This study aimed to compare the levels of multiple cytokines in patients with first-episode drug-naive major depressive disorder (MDD) with or without anxiety and analyze the correlation between the level of depression or anxiety and the serum cytokine levels.MethodsThe study involved 55 patients with first-episode drug-naive MDD. To assess anxiety symptoms, the 14-item HAMA was used. MDD patients were divided into two groups: 23 MDD patients without anxiety and 32 MDD patients with anxiety. The measurement of 37 cytokines was conducted. Serum cytokine levels between patients with MDD without anxiety and anxiety were compared. In multiple linear regression models, the relationship between the group and abnormal cytokines was explored. The receiver operating characteristic (ROC) curve analysis was performed to estimate diagnostic performance of serum cytokines in discriminating MDD patients with anxiety from MDD patients without anxiety. A correlation was evaluated between the scores of HAMD or HAMA and the serum cytokine levels.ResultsIn MDD patients with anxiety, IL-17 C and CCL17 levels were significantly lower than in MDD patients without anxiety (all P < 0.05). Multiple measurements were corrected with Benjamini-Hochberger corrections, but none of these differences persisted (all P > 0.05). The results of multiple linear regression models revealed that after controlling for other independent variables, group was not a significant independent predictor of serum IL-17 C or CCL17 (all P > 0.05). The AUC values of IL-17 C and CCL17 were 0.643 and 0.637, respectively, in discriminating MDD patients with anxiety from MDD patients without anxiety. The results of partial correlation analyses showed the scores of HAMD were negatively correlated with the IL-17 C (r = -0.314, P = 0.021) levels with sex as a covariate.ConclusionsThe findings suggest that there is a potential absence of disparity in the levels of circulating cytokines among individuals diagnosed with first-episode drug-naïve MDD, regardless of the presence or absence of comorbid anxiety.

Project description:Major depressive disorder (MDD) has been associated with disruptions in the topological organization of brain morphological networks in group-level data. Such disruptions have not yet been identified in single-patients, which is needed to show relations with symptom severity and to evaluate their potential as biomarkers for illness. To address this issue, we conducted a cross-sectional structural brain network study of 33 treatment-naive, first-episode MDD patients and 33 age-, gender-, and education-matched healthy controls (HCs). Weighted graph-theory based network models were used to characterize the topological organization of brain networks between the two groups. Compared with HCs, MDD patients exhibited lower normalized global efficiency and higher modularity in their whole-brain morphological networks, suggesting impaired integration and increased segregation of morphological brain networks in the patients. Locally, MDD patients exhibited lower efficiency in anatomic organization for transferring information predominantly in default-mode regions including the hippocampus, parahippocampal gyrus, precuneus and superior parietal lobule, and higher efficiency in the insula, calcarine and posterior cingulate cortex, and in the cerebellum. Morphological connectivity comparisons revealed two subnetworks that exhibited higher connectivity strength in MDD mainly involving neocortex-striatum-thalamus-cerebellum and thalamo-hippocampal circuitry. MDD-related alterations correlated with symptom severity and differentiated individuals with MDD from HCs with a sensitivity of 87.9% and specificity of 81.8%. Our findings indicate that single subject grey matter morphological networks are often disrupted in clinically relevant ways in treatment-naive, first episode MDD patients. Circuit-specific changes in brain anatomic network organization suggest alterations in the efficiency of information transfer within particular brain networks in MDD. Hum Brain Mapp 38:2482-2494, 2017. © 2017 Wiley Periodicals, Inc.

Dataset Information

Multimetric structural covariance in first-episode major depressive disorder: a graph theoretical analysis.

Background

Methods

Results

Limitations

Conclusion

Publications

Multimetric structural covariance in first-episode major depressive disorder: a graph theoretical analysis.

Similar Datasets

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