Brain connectomic and transcriptional signatures of suicidal thoughts and behaviors in major depressive disorder

Motivation: Suicide-related connectomic signatures in depression and underlying transcriptional patterns have been poorly understood, most previous findings were limited by small-sample and single-site design. Goal(s): To identify robust brain structural network deficits associated with suicidal thoughts and behaviors (STB) in major depressive disorder (MDD) and to determine related transcriptional profiles. Approach: Based on mutlicenter MRI data of over 700 individuals, group-level connectomic comparisons and connectome-transcriptome association were analyzed. Results: Robust structural connectomic alterations associated with STB in MDD were distributed in the prefrontal, limbic and temporal areas. STB-related connectomic alterations were spatially correlated with genes enriched for cellular metabolism and synaptic signaling. Impact: These findings reveal a robust pattern of brain structural deficits at network level and demonstrate its linkage to gene expression patterns, which provides novel insights into the neurobiological underpinnings and potential markers for prediction and prevention of STB.

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Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/1242
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
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article

Brain connectomic and transcriptional signatures of suicidal thoughts and behaviors in major depressive disorder

Wen Chen, Chunhong Kong, Zhiyun Jia, Qiyong Gong et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Mental Health Research Topics
article

Brain connectomic and transcriptional signatures of suicidal thoughts and behaviors in major depressive disorder

Wen Chen, Chunhong Kong, Zhiyun Jia, Qiyong Gong, Kun Qin, Lisha Zhang, Huiru Li, Rui Hu
article en

Abstract

Motivation: Suicide-related connectomic signatures in depression and underlying transcriptional patterns have been poorly understood, most previous findings were limited by small-sample and single-site design. Goal(s): To identify robust brain structural network deficits associated with suicidal thoughts and behaviors (STB) in major depressive disorder (MDD) and to determine related transcriptional profiles. Approach: Based on mutlicenter MRI data of over 700 individuals, group-level connectomic comparisons and connectome-transcriptome association were analyzed. Results: Robust structural connectomic alterations associated with STB in MDD were distributed in the prefrontal, limbic and temporal areas. STB-related connectomic alterations were spatially correlated with genes enriched for cellular metabolism and synaptic signaling. Impact: These findings reveal a robust pattern of brain structural deficits at network level and demonstrate its linkage to gene expression patterns, which provides novel insights into the neurobiological underpinnings and potential markers for prediction and prevention of STB.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Good health and well-being
Openalex Percentile: Top 74%
Mental Health Research Topics
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Brain connectomic and transcriptional signatures of suicidal thoughts and behaviors in major depressive disorder — Wen Chen, Chunhong Kong, et al. · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2024) | TGRS Research Map | TGRS