Heart rate variability as a biomarker of autonomic (re)activity and fatigue in multiple sclerosis.
TL;DR
Heart rate variability offers the potential to monitor PNS-SNS-related activity during psychological interventions and to measure reduced autonomic adaptability in MS-related trait fatigue.
Abstract
Fatigue is a debilitating symptom in multiple sclerosis (MS) associated with autonomic nervous system (ANS) dysfunction. Heart rate variability (HRV) provides a non-invasive measure of ANS function; yet the relative sensitivity of linear and nonlinear HRV parameters in capturing specific ANS (dys)function remains unclear. This study investigated the factorial structure of HRV parameters, their response to biopsychological interventions, and their relationship with MS-related fatigue. Data from two clinical trials (N = 78) were pooled. Exploratory factor analysis (EFA) was applied to time-domain, frequency-domain, and nonlinear HRV parameters. Repeated-measures ANOVAs examined the effects of self-alert training (SAT; activating), deep breathing (DB; relaxing), and progressive muscle relaxation (PMR; intermediate) on HRV, controlling for age, depression, and disability. Subsequent regression analyses investigated whether HRV changes during a vigilance task predicted MS-related fatigue. EFA revealed two factors, likely reflecting parasympathetic (PNS) or sympathetic (SNS) activity. SAT decreased HRV parameters loaded onto both factors, DB increased parameters related to the factor interpreted as mainly reflecting SNS activity, and PMR affected both factors. Reduced SDNN change during the vigilance task predicted higher trait fatigue, whereas state fatigue was not associated with HRV. HRV offers the potential to monitor PNS-SNS-related activity during psychological interventions and to measure reduced autonomic adaptability in MS-related trait fatigue.