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Genetic variants associated with chronic fatigue syndrome predict population-level fatigue severity and actigraphic measurements
Genetic variants associated with chronic fatigue syndrome predict population-level fatigue severity and actigraphic measurements
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Genetic variants associated with chronic fatigue syndrome predict population-level fatigue severity and actigraphic measurements
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Genetic variants associated with chronic fatigue syndrome predict population-level fatigue severity and actigraphic measurements
Genetic variants associated with chronic fatigue syndrome predict population-level fatigue severity and actigraphic measurements

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Genetic variants associated with chronic fatigue syndrome predict population-level fatigue severity and actigraphic measurements
Genetic variants associated with chronic fatigue syndrome predict population-level fatigue severity and actigraphic measurements
Journal Article

Genetic variants associated with chronic fatigue syndrome predict population-level fatigue severity and actigraphic measurements

2025
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Overview
Abstract Study Objectives The diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome (CFS) is based on a constellation of symptoms which center around fatigue. However, fatigue is commonly reported in the general population by people without CFS. Does the biology underlying fatigue in patients with CFS also drive fatigue experienced by individuals without CFS? Methods We used UK Biobank actigraphy data to characterize differences in physical activity patterns and daily temperature rhythms between participants diagnosed with CFS compared to controls. We then tested if single nucleotide variants (SNVs) previously associated with CFS are also associated with the variation of these actigraphic CFS correlates and/or subjective fatigue symptoms in the general population. Results Participants diagnosed with CFS (n = 295) had significantly decreased overall movement (Cohen’s d = 0.220, 95% CI of −0.335 to −0.106, p-value = 2.42 × 10−15), lower activity amplitudes (Cohen’s d = -0.377, 95% CI of −0.492 to −0.262, p-value = 1.74 × 10−6), and lower wrist temperature amplitudes (Cohen’s d = −0.173, 95% CI of -0.288 to -0.059, p-value = .002) compared to controls (n = 63,133). Of 30 tested SNVs associated in the literature with CFS, one was associated in the control population with subjective fatigue and one with actigraphic measurements (FDR < 0.05). Conclusions The genetic overlap of CFS risk with actigraphy and subjective fatigue phenotypes suggests that some biological mechanisms underlying pathologic fatigue in patients with CFS also underlie fatigue symptoms at a broader population level. Therefore, understanding the biology of fatigue in general may inform our understanding of CFS pathophysiology. Graphical Abstract Graphical Abstract