Perceived fatigability, quantifying an individual's vulnerability to fatigue anchored to measurable activities, is a sensitive clinical indicator of cognitive decline (Salerno et al., 2020), functional decline (Simonsick et al., 2018b) and even all-cause mortality in older adults (Glynn et al., 2022). Thus, understanding the neurobiological mechanism of fatigability is important due to its high prevalence in older adults (30-90%) (LaSorda et al., 2020) and also helps us elucidate aging process more.

However, greater fatigability has been associated with depression, which may confound analyses (LaSorda et al., 2020). The correlation of mental fatigability with depression was stronger than that with cognitive function and global fatigue (Renner et al., 2021). Furthermore, mitochondrial dysfunction and inflammation have been postulated to be the common underlying biological pathway to fatigability and depressive symptoms (Brown et al., 2016), implying that depression should be taken into account when examining fatigability. 

One can speculate on the neural correlates of fatigability by referring to prior neuroimaging studies on fatigue. Multiple sclerosis (MS) is the most frequently studied disease in this context, where individuals with fatigue exhibited abnormal activation in the thalamus and sensorimotor network compared to those without fatigue (Barbi et al., 2022). Specifically, fatigue in MS has been associated with white matter lesions in the cortico-striatal-thalamo-cortical (CSTC) loop, which can be examined through diffusion tensor imaging (DTI) (Alshehri et al., 2024; Hechenberger et al., 2023). Diffusion imaging has also demonstrated white matter changes in the left superolateral medial forebrain bundle, part of the mesocorticolimbic reward pathway, in patients with MS comorbid with fatigue and depression (Palotai et al., 2021), highlighting the intertwined relationship between fatigue and depression. White matter lesions have also been found to underlie post-stroke fatigue (Schaechter et al., 2023). Aberrant diffusion markers in the thalamus and right pallidum have been found to correlate with post-COVID fatigue, as well as memory and concentration deficits (Heine et al., 2023). Moreover, higher perceived fatigue was associated with disrupted small-worldness structure in diffusion imaging data in patients with mild cognitive impairment, a phenomenon also observed in the aging or neurodegenerative brain (Kukla et al., 2022). These prior studies suggest that specific white matter lesions could underlie the trans-diagnostic shared neuronal substrate for perceived fatigue. To date, using neuroimaging to explore fatigability is still in its infancy. Recent work in older adults found lower grey matter volume in the hippocampus, putamen, and thalamus in those with greater physical fatigability (Wasson et al., 2019). Connectome analysis on data of diffusion tensor imaging (DTI) revealed a greater connected surface area in striatal-frontal-parietal network, which was associated with lower cognitive and physical fatigue (Baran et al., 2020). However, DTI analysis is known for its incapability to resolve the fiber crossing phenomenon in white matter tracts. Measuring perceived fatigability ameliorates the traditional measurement of fatigue by accounting for the “slowing down” or “self-pacing” in the older adults (Glynn and Qiao, 2023). To better understand the pathophysiology of fatigability in older adults, studies using advanced diffusing modalities can help us reveal the underlying affected white matter structures.

To account for the limitations in prior studies, we used more advanced diffusion spectrum imaging (DSI) to study perceived fatigability in a group of older adults with and without late-life depression (LLD). Recruiting those with and without LLD helps tease out separate and overlapping neural mechanisms of fatigability and depression. Second, myelin plasticity is hypothesized to underly the brain function, which is reflected in the white matter structural differences (Gibson et al., 2018). DTI analysis has traditionally been used to study white matter tracts. However, its single low diffusion sensitization and ∼30 sampling directions has shown to be insufficient in detecting early neuronal change (Yeh et al., 2019b). Using an advanced white matter tracking method, such as DSI, can help us delineate sophisticated white matter differences. Finding brain areas specific to fatigability will help us better understand the mechanism and guides us in developing interventions to reduce fatigability. In this study, we used state-of-the-art diffusion techniques to explore the overlapping and differential associations of fatigability and depression on white matter tracts. Based on past studies, we hypothesize that fatigability will be associated with white matter tracts among cortico-subcortical loops, particularly connecting basal ganglia, thalamus and hippocampus (Angioni et al., 2021). Given the high fatigability prevalence in chronic medical illness (Kluger et al., 2013), we hypothesize that these brain features also correlate with shared or differential clinical laboratory markers.