Disentangling pain and fatigue in [CFS]: a resting state connectivity study before and after cognitive behavioral therapy 2024 van der Schaaf et al

Abstract
Background
Fatigue is a central feature of myalgic encephalomyelitis or chronic fatigue syndrome (ME/CFS), but many ME/CFS patients also report comorbid pain symptoms. It remains unclear whether these symptoms are related to similar or dissociable brain networks. This study used resting-state fMRI to disentangle networks associated with fatigue and pain symptoms in ME/CFS patients, and to link changes in those networks to clinical improvements following cognitive behavioral therapy (CBT).

Methods
Relationships between pain and fatigue symptoms and cortico-cortical connectivity were assessed within ME/CFS patients at baseline (N = 72) and after CBT (N = 33) and waiting list (WL, N = 18) and compared to healthy controls (HC, N = 29). The analyses focused on four networks previously associated with pain and/or fatigue, i.e. the fronto-parietal network (FPN), premotor network (PMN), somatomotor network (SMN), and default mode network (DMN).

Results
At baseline, variation in pain and fatigue symptoms related to partially dissociable brain networks. Fatigue was associated with higher SMN-PMN connectivity and lower SMN-DMN connectivity. Pain was associated with lower PMN-DMN connectivity. CBT improved SMN-DMN connectivity, compared to WL. Larger clinical improvements were associated with larger increases in frontal SMN-DMN connectivity. No CBT effects were observed for PMN-DMN or SMN-PMN connectivity.

Conclusions
These results provide insight into the dissociable neural mechanisms underlying fatigue and pain symptoms in ME/CFS and how they are affected by CBT in successfully treated patients. Further investigation of how and in whom behavioral and biomedical treatments affect these networks is warranted to improve and individualize existing or new treatments for ME/CFS.

Disentangling pain and fatigue in chronic fatigue syndrome: a resting state connectivity study before and after cognitive behavioral therapy | Psychological Medicine | Cambridge Core

 

Knoop is one of the authors.

Participants

Ninety-four female ME/CFS patients, between 18 and 65 years old, that met U.S. Centers for Disease Control (CDC)-criteria for ME/CFS (revised in 2003) (Fukuda et al., Reference Fukuda, Straus, Hickie, Sharpe, Dobbins and Komaroff1994; Reeves, Lloyd, & Vernon, Reference Reeves, Lloyd and Vernon2003) and scored ⩾40 on the subscale fatigue of the checklist individual strength (CIS-fatigue) (Vercoulen et al., Reference Vercoulen, Swanink, Fennis, Galama, van der Meer and Bleijenberg1994; Worm-Smeitink et al., Reference Worm-Smeitink, Gielissen, Bloot, van Laarhoven, van Engelen, van Riel and Knoop2017), and ⩾700 on the Sickness Impact Profile-8 (SIP8total) (Bergner, Bobbitt, Carter, & Gilson, Reference Bergner, Bobbitt, Carter and Gilson1981) and thirty gender, age and education-matched healthy controls (HC)(<35 on CIS-fatigue, and no chronic medical condition) were included. For a complete list of in- and exclusion criteria see Supplement.

 

They argue that CBT increased the connectivity between the sensorimotor network (SMN) and posterior default mode network (DMN) compared to the waiting list. It seems that it was mostly the connectivity that decreased in the waiting list condition, rather than improvements in the CBT group.

They used FDR-correction for multiple comparisons, which is less stringent than for example Bonferonni corrections. Given the large amount of tests they performed in this study, I wonder if this wasn't simply a false positive.

Table 6 shows that SMN-DMN connectivity wasn't significantly correlated with changes in pain or fatigue.