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基于网络的方法识别抑郁自杀者大脑中的分子特征。

Network-based approach to identify molecular signatures in the brains of depressed suicides.

作者信息

Zeng Duan, He Shen, Ma Changlin, Wen Yi, Song Weichen, Xu Qingqing, Zhao Nan, Wang Qiang, Yu Yimin, Shen Yifeng, Huang Jingjing, Li Huafang

机构信息

Department of Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.

Shanghai Jiading District Mental Health Center, Shanghai, PR China.

出版信息

Psychiatry Res. 2020 Dec;294:113513. doi: 10.1016/j.psychres.2020.113513. Epub 2020 Oct 18.


DOI:10.1016/j.psychres.2020.113513
PMID:33137553
Abstract

BACKGROUND: Suicide is a serious and global health problem that has a strong association with major depressive disorder (MDD). Weighted gene co-expression network analysis (WGCNA) was performed for the construction of a co-expression network to get important gene modules associated with depressed suicide. METHODS: Transcriptome sequencing data from dorsolateral prefrontal cortex was used, which included 29 non-psychiatric controls (CON), 21 MDD suicides (MDD-S) and 9 MDD non-suicides (MDD-NS) of medication-free sudden death individuals. RESULTS: The highest correlation in the module-traits relationship was discovered between the black module and suicide (r = -0.30, p = 0.024) as well as MDD (r = -0.34, p = 0.010).Furthermore, the expression levels of genes decreased progressively across the three groups (CON>MDD-NS>MDD-S). Therefore, the genes in the black module was selected for subsequent analyses. Protein-Protein Interaction Network found that the top 10 hub genes were somehow involved in depressed suicide including JUN, FOS, ATF3, MYC, EGR1, FOSB, DUSP1, NFKBIA, TLR2, NR4A1. Most of the GO terms were enriched in cell death and apoptosis and KEGG was mainly enriched in MAPK pathway. Cell Type-Specific Analysis found these genes were significantly enriched in endothelial and microglia (p<0.000) cell types. In addition, 92 genes in this module had at least one highly significant differentially methylated positions between MDD-S and controls. CONCLUSION: Cell death and apoptosis may participate in the interplay between depressed suicide and neuro-inflammation system.

摘要

背景:自杀是一个严重的全球性健康问题,与重度抑郁症(MDD)密切相关。进行加权基因共表达网络分析(WGCNA)以构建共表达网络,从而获得与抑郁自杀相关的重要基因模块。 方法:使用来自背外侧前额叶皮层的转录组测序数据,其中包括29名无精神疾病对照者(CON)、21名MDD自杀者(MDD-S)和9名MDD非自杀者(MDD-NS),这些个体均为无药物治疗的猝死患者。 结果:发现黑色模块与自杀(r = -0.30,p = 0.024)以及MDD(r = -0.34,p = 0.010)之间在模块-性状关系中具有最高相关性。此外,三组之间基因表达水平逐渐降低(CON>MDD-NS>MDD-S)。因此,选择黑色模块中的基因进行后续分析。蛋白质-蛋白质相互作用网络发现,前10个枢纽基因在某种程度上参与了抑郁自杀,包括JUN、FOS、ATF3、MYC、EGR1、FOSB、DUSP1、NFKBIA、TLR2、NR4A1。大多数基因本体(GO)术语富集在细胞死亡和凋亡方面,京都基因与基因组百科全书(KEGG)主要富集在丝裂原活化蛋白激酶(MAPK)途径。细胞类型特异性分析发现这些基因在内皮细胞和小胶质细胞类型中显著富集(p<0.000)。此外,该模块中的92个基因在MDD-S与对照之间至少有一个高度显著的差异甲基化位点。 结论:细胞死亡和凋亡可能参与了抑郁自杀与神经炎症系统之间的相互作用。

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引用本文的文献

[1]
Deconvolution-Based Transcriptomic Analysis in the Hippocampus Reveals Cell Type-Specific Risk Genes and Pathways Associated With Depression and Suicide.

Biol Psychiatry Glob Open Sci. 2025-5-8

[2]
Toll-like Receptors in Immuno-Metabolic Regulation of Emotion and Memory.

Cells. 2025-6-19

[3]
Immune-related gene characterization and biological mechanisms in major depressive disorder revealed based on transcriptomics and network pharmacology.

Front Psychiatry. 2024-12-6

[4]
Genome-wide methylome-based molecular pathologies associated with depression and suicide.

Neuropsychopharmacology. 2025-3

[5]
Integrated network pharmacology and transcriptomics to reveal the mechanism of Passiflora against depressive disorder: An observational study.

Medicine (Baltimore). 2024-10-11

[6]
A twin analysis to estimate genetic and environmental factors contributing to variation in weighted gene co-expression network module eigengenes.

Am J Med Genet B Neuropsychiatr Genet. 2025-1

[7]
Glial Markers of Suicidal Behavior in the Human Brain-A Systematic Review of Postmortem Studies.

Int J Mol Sci. 2024-5-25

[8]
Brain and blood transcriptome profiles delineate common genetic pathways across suicidal ideation and suicide.

Mol Psychiatry. 2024-5

[9]
Implementing Evidence-Based Suicide Prevention Strategies for Greatest Impact.

Focus (Am Psychiatr Publ). 2023-4

[10]
Identification and validation of key genes associated with atrial fibrillation in the elderly.

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