ArticleJournal of translational medicine2025
Mapping fatigue: discovering brain regions and genes linked to fatigue susceptibility.
Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Article
- Genetic determinants of fatigue up to 2 years after radiotherapy in prostate cancer patients.Nature communications · 2026Article
- Pathophysiological mechanisms of fatigue and multidisciplinary management strategies (Review).Experimental and therapeutic medicine · 2026Review
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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundThe 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.
methodsA 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.
resultsThe 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.
conclusionsOur 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.
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Registered trials
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