Table_7_Identification of potential Mitogen-Activated Protein Kinase-related key genes and regulation networks in molecular subtypes of major depressive disorder.XLS
收藏frontiersin.figshare.com2023-06-13 更新2025-01-21 收录
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BackgroundMajor depressive disorder (MDD) is a heterogeneous and prevalent mental disorder associated with increased morbidity, disability, and mortality. However, its underlying mechanisms remain unclear.Materials and methodsAll analyses were conducted based on integrated samples from the GEO database. Differential expression analysis, unsupervised consensus clustering analysis, enrichment analysis, and regulation network analysis were performed.ResultsMitogen-activated protein kinase (MAPK) signaling pathway was identified as an associated pathway in the development of MDD. From transcriptional signatures, we classified the MDD patients into two subgroups using unsupervised clustering and revealed 13 differential expression genes between subgroups, which indicates the probably relative complications. We further illustrated potential molecular mechanisms of MDD, including dysregulation in the neurotrophin signaling pathway, peptidyl-serine phosphorylation, and endocrine resistance. Moreover, we identified hub genes, including MAPK8, TP53, and HRAS in the maintenance of MDD. Furthermore, we demonstrated that the axis of miRNAs-TFs-HRAS/TP53/MAPK8 may play a critical role in MDD.ConclusionTaken together, we demonstrated an overview of MAPK-related key genes in MDD, determined two molecular subtypes, and identified the key genes and core network that may contribute to the procession of MDD.
背景重度抑郁症(MDD)是一种异质性和普遍存在的心理疾病,与发病率、残疾率和死亡率增加密切相关。然而,其潜在的发病机制尚不明确。材料与方法所有分析均基于GEO数据库的综合样本进行。差异表达分析、无监督共识聚类分析、富集分析和调控网络分析均被实施。结果我们确定丝裂原活化蛋白激酶(MAPK)信号通路为与MDD发展相关的通路。通过转录组特征,我们利用无监督聚类将MDD患者分为两组,并揭示了两组之间存在的13个差异表达基因,这表明可能相关的并发症。我们进一步阐述了MDD的潜在分子机制,包括神经营养因子信号通路失调、肽基丝氨酸磷酸化和内分泌抵抗。此外,我们识别了维持MDD的关键基因,包括MAPK8、TP53和HRAS。进一步地,我们证明了miRNAs-TFs-HRAS/TP53/MAPK8轴可能在MDD中发挥关键作用。结论综上所述,我们展示了MDD中与MAPK相关的关键基因概述,确定了两种分子亚型,并识别了可能有助于MDD进程的关键基因和核心网络。
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