Wang Chengyi, Wu Meitao, Wang Ziyang, Wu Xiaoliang, Yuan Hao, Jiang Shuo, Li Gen, Lan Rifang, Wang Qiuping, Zhang Guangde, Lv Yingli, Shi Hongbo
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Department of Cardiology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Cell Mol Neurobiol. 2024 Dec 4;45(1):2. doi: 10.1007/s10571-024-01510-4.
The neuroendocrine-immune (NEI) network is fundamental for maintaining body's homeostasis and health. While the roles of microRNAs (miRNAs) and transcription factors (TFs) in disease processes are well-established, their synergistic regulation within the NEI network has yet to be elucidated. In this study, we constructed a background NEI-related miRNA-TF regulatory network (NEI-miRTF-N) by integrating NEI signaling molecules (including miRNAs, genes, and TFs) and identifying miRNA-TF feed-forward loops. Our analysis reveals that the number of immune signaling molecules is the highest and suggests potential directions for signal transduction, primarily from the nervous system to both the endocrine and immune systems, as well as from the endocrine system to the immune system. Furthermore, disease-specific NEI-miRTF-Ns for depression, Alzheimer's disease (AD) and dilated cardiomyopathy (DCM) were constructed based on the known disease molecules and significantly differentially expressed (SDE) molecules. Additionally, we proposed a novel method using depth-first-search algorithm for identifying significantly dysregulated NEI-related miRNA-TF regulatory pathways (NEI-miRTF-Ps) and verified their reliability from multiple perspectives. Our study provides an effective approach for identifying disease-specific NEI-miRTF-Ps and offers new insights into the synergistic regulation of miRNAs and TFs within the NEI network. Our findings provide information for new therapeutic strategies targeting these regulatory pathways.
神经内分泌-免疫（NEI）网络对于维持机体的稳态和健康至关重要。虽然微小RNA（miRNA）和转录因子（TF）在疾病过程中的作用已得到充分证实，但它们在NEI网络中的协同调节作用尚未阐明。在本研究中，我们通过整合NEI信号分子（包括miRNA、基因和TF）并识别miRNA-TF前馈环，构建了一个背景NEI相关的miRNA-TF调控网络（NEI-miRTF-N）。我们的分析表明，免疫信号分子的数量最多，并提示了信号转导的潜在方向，主要是从神经系统到内分泌和免疫系统，以及从内分泌系统到免疫系统。此外，基于已知的疾病分子和显著差异表达（SDE）分子，构建了抑郁症、阿尔茨海默病（AD）和扩张型心肌病（DCM）的疾病特异性NEI-miRTF-N。此外，我们提出了一种使用深度优先搜索算法识别显著失调的NEI相关miRNA-TF调控途径（NEI-miRTF-P）的新方法，并从多个角度验证了它们的可靠性。我们的研究为识别疾病特异性NEI-miRTF-P提供了一种有效的方法，并为NEI网络中miRNA和TF的协同调节提供了新的见解。我们的研究结果为针对这些调控途径的新治疗策略提供了信息。
