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Transcriptional Patterns of Brain Structural Covariance Network Abnormalities Associated with Suicidal Thoughts and Behaviors in Major Depressive Disorder

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收录情况： ◇ SCIE

作者：
Qin Kun[1,2,3,7] * ; Li Huiru[1,3,4] * ; Zhang Huawei[1] ; Yin Li[5] ; Wu Baolin[1] ; Pan Nanfang[1,3] ; Chen Taolin[1,3] ; Roberts Neil[6] ; Sweeney John A[1,7] ; Huang Xiaoqi[1,3] ; Gong Qiyong[1,8] ; Jia Zhiyun[3,9] ;
机构： [1]Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China [2]Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, China [3]Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China [4]Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China. [5]Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China [6]The Queens Medical Research Institute (QMRI), School of Clinical Sciences, University of Edinburgh, Edinburgh, UK [7]Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA [8]Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China [9]Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
出处：
DOI： 10.1016/j.biopsych.2024.01.026
ISSN：

关键词： Magnetic resonance imaging Suicide Graph theory Allen Human Brain Atlas Cortical thickness Multicenter

摘要：
Although brain structural covariance network (SCN) abnormalities were associated with suicidal thoughts and behaviors (STB) in individuals with major depressive disorder (MDD), previous studies reported inconsistent findings based on small sample size and underlying transcriptional patterns remained poorly understood.Using a multicenter MRI dataset including 218 MDD patients with STB (MDD-STB), 230 MDD patients without STB (MDD-nSTB) and 263 healthy controls (HC), we established individualized SCN 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 STB at the individual level. Brain-wide relationship between STB-related connectomic alterations and gene expression were examined using partial least square regression.Group comparisons revealed that SCN topological deficits associated with STB were identified in the prefrontal, anterior cingulate, and lateral temporal cortices. Combining morphometric and topological features allowed for individual-level characterization of MDD and STB. Topological features exhibited greater contribution to distinguishing between patients with and without STB. STB-related connectomic alterations were spatially correlated with the expression of genes enriched for cellular metabolism and synaptic signaling.These findings revealed robust brain structural deficits at network level, highlight the importance of SCN topological measures in characterizing individual suicidality, and demonstrate its linkage to molecular function and cell types, providing novel insights into the neurobiological underpinnings and potential markers for prediction and prevention of suicide.Copyright © 2024. Published by Elsevier Inc.

基金：
National Natural Science Foundation of China (Grant Nos. 82271947, 81971595, 81820108018 and 81621003), the CAMS Innovation Fund for Medical Sciences (CIFMS) (No. 2022-I2M-C&T-B-104), the Key Program of Natural Science Foundation of Sichuan Province (Grant No. 2022NSFSC0047), and the 1·3·5 Project for Disciplines of Excellence–Clinical Research Incubation Project, West China Hospital, Sichuan University (Grant No. 2020HXFH005).
语种：
外文
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中科院(CAS)分区：
出版当年[2025]版：
无
最新[2023]版：
大类 | 1 区 医学
小类 | 1 区 神经科学 1 区 精神病学
JCR分区：
出版当年[2024]版：
无
最新[2023]版：
Q1 NEUROSCIENCES Q1 PSYCHIATRY

影响因子： 最新[2023版] 最新五年平均 出版当年[2024版] 出版当年五年平均 出版前一年[2023版]

第一作者：
第一作者机构： [1]Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China [2]Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, China [3]Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China [7]Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
共同第一作者：
通讯作者：
通讯机构： [1]Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China [3]Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China [8]Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China [9]Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
推荐引用方式(GB/T 7714)：
Qin Kun,Li Huiru,Zhang Huawei,et al.Transcriptional Patterns of Brain Structural Covariance Network Abnormalities Associated with Suicidal Thoughts and Behaviors in Major Depressive Disorder[J].Biological Psychiatry.2024,96(6):435-444.doi:10.1016/j.biopsych.2024.01.026.
APA：
Qin Kun,Li Huiru,Zhang Huawei,Yin Li,Wu Baolin...&Jia Zhiyun.(2024).Transcriptional Patterns of Brain Structural Covariance Network Abnormalities Associated with Suicidal Thoughts and Behaviors in Major Depressive Disorder.Biological Psychiatry,96,(6)
MLA：
Qin Kun,et al."Transcriptional Patterns of Brain Structural Covariance Network Abnormalities Associated with Suicidal Thoughts and Behaviors in Major Depressive Disorder".Biological Psychiatry 96..6(2024):435-444

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