ArticleFrontiers in psychiatry2022
White Matter Network Disruption Is Associated With Melancholic Features in Major Depressive Disorder.
Article in Frontiers in psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 18 citations in OpenAlex.
- Childhood chronic stress associated with abnormal brain white matter networks in first-episode, drug-naïve MDD adolescents: a machine learning study.Frontiers in psychiatry · 2026Article
- Cortical high-threshold and low-activation characteristics in adolescent depression: a cross-age differential analysis.Frontiers in psychiatry · 2026Article
- Investigating mood and cognition in people with multiple sclerosis: a prospective cross-sectional study protocol.BMJ open · 2025Article
- Investigating Mood and Cognition in People with Multiple Sclerosis: A Prospective Study Protocol.medRxiv : the preprint server for health sciences · 2024Article
- Multimodal abnormalities of brain structures in adolescents and young adults with major depressive disorder: An activation likelihood estimation meta-analysis.World journal of psychiatry · 2024Article
- Reduced gray matter volume of the hippocampal tail in melancholic depression: evidence from an MRI study.BMC psychiatry · 2024Article
- White matter-based brain network topological properties associated with individual impulsivity.Scientific reports · 2023Article
- Altered White Matter Network Topology in Panic Disorder.Journal of personalized medicine · 2023Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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