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一种用于研究重症肌痛/慢性疲劳综合征(ME/CFS)患者发病机制的网络医学方法:一项初步研究。

A network medicine approach to investigating ME/CFS pathogenesis in severely ill patients: a pilot study.

作者信息

Hung Li-Yuan, Wu Chan-Shuo, Chang Chia-Jung, Li Peng, Hicks Kimberly, Dibble Joshua J, Morrison Braxton, Smith Chimere L, Davis Ronald W, Xiao Wenzhong

机构信息

Computational Research Center for Complex Chronic Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.

ME/CFS Collaborative Research Center, Stanford University School of Medicine, Palo Alto, CA, United States.

出版信息

Front Hum Neurosci. 2025 Feb 10;19:1509346. doi: 10.3389/fnhum.2025.1509346. eCollection 2025.

Abstract

This pilot study harnessed the power of network medicine to unravel the complex pathogenesis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). By utilizing a network analysis on whole genome sequencing (WGS) data from the Severely Ill Patient Study (SIPS), we identified ME/CFS-associated proteins and delineated the corresponding network-level module, termed the SIPS disease module, together with its relevant pathways. This module demonstrated significant overlap with genes implicated in fatigue, cognitive disorders, and neurodegenerative diseases. Our pathway analysis revealed potential associations between ME/CFS and conditions such as COVID-19, Epstein-Barr virus (EBV) infection, neurodegenerative diseases, and pathways involved in cortisol synthesis and secretion, supporting the hypothesis that ME/CFS is a neuroimmune disorder. Additionally, our findings underscore a potential link between ME/CFS and estrogen signaling pathways, which may elucidate the higher prevalence of ME/CFS in females. These findings provide insights into the pathogenesis of ME/CFS from a network medicine perspective and highlight potential therapeutic targets. Further research is needed to validate these findings and explore their implications for improving diagnosis and treatment.

摘要

这项初步研究利用网络医学的力量来揭示肌痛性脑脊髓炎/慢性疲劳综合征(ME/CFS)的复杂发病机制。通过对重症患者研究(SIPS)的全基因组测序(WGS)数据进行网络分析,我们确定了与ME/CFS相关的蛋白质,并描绘了相应的网络水平模块,称为SIPS疾病模块,以及其相关途径。该模块与涉及疲劳、认知障碍和神经退行性疾病的基因有显著重叠。我们的通路分析揭示了ME/CFS与COVID-19、爱泼斯坦-巴尔病毒(EBV)感染、神经退行性疾病以及皮质醇合成和分泌所涉及的通路等病症之间的潜在关联,支持了ME/CFS是一种神经免疫疾病的假说。此外,我们的研究结果强调了ME/CFS与雌激素信号通路之间的潜在联系,这可能解释了ME/CFS在女性中较高的患病率。这些发现从网络医学的角度为ME/CFS的发病机制提供了见解,并突出了潜在的治疗靶点。需要进一步的研究来验证这些发现,并探索它们对改善诊断和治疗的意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9c/11847890/96ceedf0de10/fnhum-19-1509346-g001.jpg

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