Integrating Clinical and Genomic Analyses of Hippocampal-Prefrontal Circuit Disorder in Depression.
Integrating Clinical and Genomic Analyses of Hippocampal-Prefrontal Circuit Disorder in Depression.
复制标题
抑郁症中海马-前额叶环路障碍的临床和基因组分析相结合
DOI：
10.3389/fgene.2020.565749
复制
发表时间：
2020
影响因子：
3.7
通讯作者：
Chen J
中科院分区：
文献类型：
--
作者：
Yuan N;Tang K;Da X;Gan H;He L;Li X;Ma Q;Chen J
重性抑郁症（Major Depression Disorder，MDD）是一种流行性、破坏性和反复发作的精神疾病。海马（HIP）-前额叶皮层（PFC）神经回路异常已被证实存在于MDD中;然而，抑郁症背景下该回路的基因相关分子特征仍不清楚。为了澄清这个问题，我们进行了基因集富集分析（GSEA），以全面分析两个大脑区域的遗传特征，并使用加权基因相关网络分析（WGCNA），以确定HIP-PFC网络中的主要抑郁相关基因模块。为了阐明MDD的区域差异和一致性，我们还比较了两个脑区的关键模块的表达模式和分子功能。结果显示，与HIP和PFC临床MDD相关的候选模块分别包含363个和225个基因。在HIP候选模块中鉴定了95个差异表达基因（DEG），在PFC候选模块中鉴定了51个DEG，在这两个区域模块中只有11个重叠的DEG。结合富集结果，虽然抑郁症的HIP-PFC网络分子功能存在异质性，但MAPK级联、Ras蛋白信号转导和Ephrin信号转导的调控在两个脑区均显著富集，表明这些生物学通路在MDD发病中起重要作用。此外，通过STRING构建高系数蛋白质-蛋白质相互作用（PPI）网络，并通过cytoHubba算法将前10个系数基因识别为枢纽基因。总之，本研究揭示了MDD的基因表达特征，并确定了HIP-PFC网络中共同和独特的分子特征和模式。本研究结果可能从基因功能的角度为解释抑郁症的发病机制和药物开发提供新的线索。需要进一步的研究来证实这些发现，并探讨抑郁症中不同神经网络的遗传调控机制。
Major depressive disorder (MDD) is a prevalent, devastating and recurrent mental disease. Hippocampus (HIP)-prefrontal cortex (PFC) neural circuit abnormalities have been confirmed to exist in MDD; however, the gene-related molecular features of this circuit in the context of depression remain unclear. To clarify this issue, we performed gene set enrichment analysis (GSEA) to comprehensively analyze the genetic characteristics of the two brain regions and used weighted gene correlation network analysis (WGCNA) to determine the main depression-related gene modules in the HIP-PFC network. To clarify the regional differences and consistency for MDD, we also compared the expression patterns and molecular functions of the key modules from the two brain regions. The results showed that candidate modules related to clinical MDD of HIP and PFC, which contained with 363 genes and 225 genes, respectively. Ninety-five differentially expressed genes (DEGs) were identified in the HIP candidate module, and 51 DEGs were identified in the PFC candidate module, with only 11 overlapping DEGs in these two regional modules. Combined with the enrichment results, although there is heterogeneity in the molecular functions in the HIP-PFC network of depression, the regulation of the MAPK cascade, Ras protein signal transduction and Ephrin signaling were significantly enriched in both brain regions, indicating that these biological pathways play important roles in MDD pathogenesis. Additionally, the high coefficient protein–protein interaction (PPI) network was constructed via STRING, and the top-10 coefficient genes were identified as hub genes via the cytoHubba algorithm. In summary, the present study reveals the gene expression characteristics of MDD and identifies common and unique molecular features and patterns in the HIP-PFC network. Our results may provide novel clues from the gene function perspective to explain the pathogenic mechanism of depression and to aid drug development. Further research is needed to confirm these findings and to investigate the genetic regulation mechanisms of different neural networks in depression.