Zhang Yifei, Zhang Zehan, Yu Qingqian, Jiang Yutong, Fei Chenyu, Wu Fengzhi, Li Feng
School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Fangshan District, Beijing, China.
Periodical Center, Beijing University of Chinese Medicine, Fangshan District, Beijing, China.
J Transl Med. 2025 Mar 7;23(1):293. doi: 10.1186/s12967-025-06284-x.
The relationship between the brain and fatigue is gaining increasing attention, with numerous studies indicating that certain specific brain regions may be closely linked to fatigue. Our study aimed to identify brain regions exhibiting significant causal relationships to fatigue and discover potential neurotherapeutic targets associated with fatigue, in the pursuit of seeking new approaches for fatigue treatment.
A bidirectional two-sample Mendelian randomization (TSMR) method was employed to investigate causal relationships between cortical and subcortical gray matter volumes in 83 regions and fatigue. Then, we utilized frontal cortex expression Quantitative Trait Loci data, employing the methods of Summary-data-based Mendelian Randomization (SMR) and Bayesian colocalization to identify genes that exhibit significant association with fatigue. Finally, the transcription levels of candidate genes were assessed in a central fatigue rat model using RT-qPCR.
The results of the TSMR analysis revealed that an increased in the volume of the right lateral orbitofrontal, left caudal middle frontal, right caudal middle frontal, and right rostral middle frontal cortices may be correlated with a diminished susceptibility to fatigue. The SMR and Bayesian colocalization analysis identified ECE2, GPX1, METTL21EP, RP11-665J16.1, and SNF8 as candidate genes associated with fatigue. RT-qPCR results confirmed significantly elevated transcription levels of Ece2, Gpx1, and Snf8 in the frontal cortex of central fatigue model rats compared to controls.
Our findings afford substantial theoretical support for the connection between the brain and fatigue, while also providing novel insights into the genetic mechanisms and therapeutic targets for fatigue, particularly central fatigue.
大脑与疲劳之间的关系日益受到关注，众多研究表明某些特定脑区可能与疲劳密切相关。我们的研究旨在确定与疲劳存在显著因果关系的脑区，并发现与疲劳相关的潜在神经治疗靶点，以寻求治疗疲劳的新方法。
采用双向双样本孟德尔随机化（TSMR）方法研究83个区域的皮质和皮质下灰质体积与疲劳之间的因果关系。然后，我们利用额叶皮质表达定量性状位点数据，采用基于汇总数据的孟德尔随机化（SMR）方法和贝叶斯共定位方法来识别与疲劳有显著关联的基因。最后，使用RT-qPCR在中枢性疲劳大鼠模型中评估候选基因的转录水平。
TSMR分析结果显示，右侧眶额外侧、左侧额中回后部、右侧额中回后部和右侧额中回前部皮质体积增加可能与疲劳易感性降低相关。SMR和贝叶斯共定位分析确定ECE2、GPX1、METTL21EP、RP11-665J16.1和SNF8为与疲劳相关的候选基因。RT-qPCR结果证实，与对照组相比，中枢性疲劳模型大鼠额叶皮质中Ece2、Gpx1和Snf8的转录水平显著升高。
我们的研究结果为大脑与疲劳之间的联系提供了大量理论支持，同时也为疲劳，尤其是中枢性疲劳的遗传机制和治疗靶点提供了新的见解。
