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Transcriptional Patterns of Brain Structural Covariance Network Abnormalities Associated With Suicidal Thoughts and Behaviors in Major Depressive Disorder.
Qin, Kun; Li, Huiru; Zhang, Huawei; Yin, Li; Wu, Baolin; Pan, Nanfang; Chen, Taolin; Roberts, Neil; Sweeney, John A; Huang, Xiaoqi; Gong, Qiyong; Jia, Zhiyun.
Affiliation
  • Qin K; Department of Radiology and Huaxi MR Research Center, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, China; Research Unit of Psychoradiology,
  • Li H; Department of Radiology and Huaxi MR Research Center, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China; Department of Medical Imaging, Th
  • Zhang H; Department of Radiology and Huaxi MR Research Center, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China.
  • Yin L; Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China.
  • Wu B; Department of Radiology and Huaxi MR Research Center, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China.
  • Pan N; Department of Radiology and Huaxi MR Research Center, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
  • Chen T; Department of Radiology and Huaxi MR Research Center, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
  • Roberts N; Queens Medical Research Institute, School of Clinical Sciences, University of Edinburgh, Edinburgh, United Kingdom.
  • Sweeney JA; Department of Radiology and Huaxi MR Research Center, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, Ohio.
  • Huang X; Department of Radiology and Huaxi MR Research Center, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
  • Gong Q; Department of Radiology and Huaxi MR Research Center, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China. Electronic address: qi
  • Jia Z; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China; Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China. Electronic address: zhiyunjia@hotmail.com.
Biol Psychiatry ; 96(6): 435-444, 2024 Sep 15.
Article in En | MEDLINE | ID: mdl-38316331
ABSTRACT

BACKGROUND:

Although brain structural covariance network (SCN) abnormalities have been associated with suicidal thoughts and behaviors (STBs) in individuals with major depressive disorder (MDD), previous studies have reported inconsistent findings based on small sample sizes, and underlying transcriptional patterns remain poorly understood.

METHODS:

Using a multicenter magnetic resonance imaging dataset including 218 MDD patients with STBs, 230 MDD patients without STBs, and 263 healthy control participants, we established individualized SCNs based on regional morphometric measures and assessed network topological metrics using graph theoretical analysis. Machine learning methods were applied to explore and compare the diagnostic value of morphometric and topological features in identifying MDD and STBs at the individual level. Brainwide relationships between STBs-related connectomic alterations and gene expression were examined using partial least squares regression.

RESULTS:

Group comparisons revealed that SCN topological deficits associated with STBs were identified in the prefrontal, anterior cingulate, and lateral temporal cortices. Combining morphometric and topological features allowed for individual-level characterization of MDD and STBs. Topological features made a greater contribution to distinguishing between patients with and without STBs. STBs-related connectomic alterations were spatially correlated with the expression of genes enriched for cellular metabolism and synaptic signaling.

CONCLUSIONS:

These findings revealed robust brain structural deficits at the network level, highlighting the importance of SCN topological measures in characterizing individual suicidality and demonstrating its linkage to molecular function and cell types, providing novel insights into the neurobiological underpinnings and potential markers for prediction and prevention of suicide.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Brain / Magnetic Resonance Imaging / Depressive Disorder, Major / Suicidal Ideation / Connectome Type of study: Clinical_trials / Prognostic_studies / Risk_factors_studies Limits: Adult / Female / Humans / Male / Middle aged Language: En Journal: Biol Psychiatry Year: 2024 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Brain / Magnetic Resonance Imaging / Depressive Disorder, Major / Suicidal Ideation / Connectome Type of study: Clinical_trials / Prognostic_studies / Risk_factors_studies Limits: Adult / Female / Humans / Male / Middle aged Language: En Journal: Biol Psychiatry Year: 2024 Type: Article