Highlights
- •Lower extremity neuromuscular function is impaired in multiple sclerosis (MS).
- •Rate of force development (RFD) is preferentially impaired.
- •Impairments in RFD is associated with disability status (i.e. EDSS score).
- •RFD (comparable to maximal muscle strength) is associated with physical function.
Abstract
Background
Neurodegeneration is an inevitable consequence of multiple sclerosis (MS) leading to impaired neuromuscular function, especially of the lower extremities. Whilst maximal muscle strength (or force; Fmax) is the most examined feature of neuromuscular function, the ability to rapidly increase muscle force (= rate of force development; RFD) appear to be preferentially sensitive towards neurodegeneration and potentially also of great importance for physical function. The purpose of the present study was to comprehensively examine and compare different outcome measures of neuromuscular function (with specific emphasis given to RFD) across disability status in persons with MS (pwMS), and in comparison, to age- and sex-matched healthy controls (HC).
Methods
A total of n=34 HC and n=99 pwMS were enrolled in the study, with the latter being divided into Expanded Disability Status Scale (EDSS) subgroups: MSmild (EDSS 0–2.5, n=51), MSmoderate (EDSS 3.0-4.5, n=33), and MSsevere (EDSS 5-6.5, n=15). Knee extensor neuromuscular function was assessed by Fmax and RFD (RFD50ms and RFD200ms, respectively; calculated in the interval 0–50 ms and 0–200 ms relative to the onset of contraction) with simultaneous electromyography (maximal EMG (EMGFmax) and rate of EMG rise (rEMG50ms and rEMG200ms, respectively)). Voluntary muscle activation derived from the interpolated twitch technique was also determined during additional Fmax trials. Lastly, physical function was assessed by the 5 x sit-to-stand test (5STS), the timed 25-foot walk test (T25FWT), and the 2-min walking test (2MWT).
Results
Substantial differences (∼deficits) (p<0.05) were observed for all pwMS subgroups compared to HC across all neuromuscular function outcome measures; RFD50ms (MSmild -22%, MSmoderate -36%, MSsevere -66%), RFD200ms (-12%, -21%, -51%), and Fmax (-11%, -14%, -33%). Somewhat comparable differences (∼deficits) (p<0.05) were observed for voluntary muscle activation (rEMG50ms, rEMG200ms, EMGFmax, and activation) and for physical function (5STS, T25FWT, and 2MT). Deficits in neuromuscular function were strongly associated with EDSS (p<0.05) (RFD50ms: slope steepness -13% per 1 point increase in EDSS, r2=0.79; RFD200ms: slope steepness -10%, r2=0.84; Fmax: slope steepness -6%, r2=0.82). Fmax and RFD were associated with physical function outcome measures (p<0.05) to a comparable extent (r2-values ranging from 0.21 to 0.35).
Conclusion
Lower extremity neuromuscular function is impaired in pwMS compared to HC with differences (∼deficits) becoming greater with increasing disability status. RFD was preferentially sensitive in capturing differences (∼deficits) across disability status and by showing strong associations with EDSS. Altogether, knee extensor RFD could serve as a simple objective marker of disability status or even progression in pwMS, that may be helpful to both researchers and clinicians.
Graphical abstract
Graphical Abstract
Keywords
1. Introduction
Multiple sclerosis (MS) is a chronic, inflammatory, and neurodegenerative disease of the central nervous system (CNS) causing structural demyelination along with axonal injury and loss (
Compston and Coles, 2008
; Noseworthy et al., 2000
). Such neurodegeneration, argued to affect the lower extremities preferentially (Giovannoni et al., 2017
; Kurtzke, 2015
), inevitably has deleterious consequences for the generation and transmission of nerve signals within the nervous system (Mamoei et al., 2020
; - Mamoei S.
- Hvid L.G.
- Boye Jensen H.
- Zijdewind I.
- Stenager E.
- Dalgas U.
Neurophysiological impairments in multiple sclerosis-Central and peripheral motor pathways.
Acta Neurol. Scand. 2020; (May 31)https://doi.org/10.1111/ane.13289
Snow et al., 2019
), and thus also for neuromuscular function (i.e. the interaction between the nervous system and the muscular system) as well as physical function. Indeed, numerous studies comparing persons with MS (pwMS) and healthy controls (HC), have reported impaired neuromuscular activity / muscle activation that overall represent suboptimal motor unit recruitment and discharge rate (- Snow N.J.
- Wadden K.P.
- Chaves A.R.
- Ploughman M.
Transcranial magnetic stimulation as a potential biomarker in multiple sclerosis: a systematic review with recommendations for future research.
Neural Plast. 2019; 20196430596https://doi.org/10.1155/2019/6430596
Scott et al., 2011
; - Scott S.M.
- Hughes A.R.
- Galloway S.D.
- Hunter AM.
Surface EMG characteristics of people with multiple sclerosis during static contractions of the knee extensors.
Clin. Physiol. Funct. Imaging. 2011; 31 (Jan): 11-17https://doi.org/10.1111/j.1475-097X.2010.00972.x
Ng et al., 2004
; Rice et al., 1992
; de Haan et al., 2000
), impaired muscle strength and power (- de Haan A.
- de Ruiter C.J.
- van Der Woude L.H.
- Jongen P.J.
Contractile properties and fatigue of quadriceps muscles in multiple sclerosis.
Muscle Nerve. 2000; 23 (Oct): 1534-1541https://doi.org/10.1002/1097-4598(200010)23:10<1534::aid-mus9>3.0.co;2-d
Scott et al., 2011
; - Scott S.M.
- Hughes A.R.
- Galloway S.D.
- Hunter AM.
Surface EMG characteristics of people with multiple sclerosis during static contractions of the knee extensors.
Clin. Physiol. Funct. Imaging. 2011; 31 (Jan): 11-17https://doi.org/10.1111/j.1475-097X.2010.00972.x
Ng et al., 2004
; Schwid et al., 1999
; Fritz et al., 2017
; Jørgensen et al., 2017
; Stagsted et al., 2021
; - Stagsted R.A.W.
- Ramari C.
- Skjerbaek A.G.
- Thrue C.
- Dalgas U.
- Hvid L.G.
Lower extremity muscle power - a critical determinant of physical function in aging and multiple sclerosis.
Exp. Gerontol. 2021; 150 (Apr 16)111347https://doi.org/10.1016/j.exger.2021.111347
Sieljacks et al., 2020
), and impaired physical function (e.g. walking capacity) (- Sieljacks P.S.
- Soberg C.A.
- Michelsen A.S.
- Dalgas U.
- Hvid L.G.
Lower extremity muscle strength across the adult lifespan in multiple sclerosis: implications for walking and stair climbing capacity.
Exp. Gerontol. 2020; 139 (Oct 1)111025https://doi.org/10.1016/j.exger.2020.111025
Stagsted et al., 2021
; - Stagsted R.A.W.
- Ramari C.
- Skjerbaek A.G.
- Thrue C.
- Dalgas U.
- Hvid L.G.
Lower extremity muscle power - a critical determinant of physical function in aging and multiple sclerosis.
Exp. Gerontol. 2021; 150 (Apr 16)111347https://doi.org/10.1016/j.exger.2021.111347
Sieljacks et al., 2020
; - Sieljacks P.S.
- Soberg C.A.
- Michelsen A.S.
- Dalgas U.
- Hvid L.G.
Lower extremity muscle strength across the adult lifespan in multiple sclerosis: implications for walking and stair climbing capacity.
Exp. Gerontol. 2020; 139 (Oct 1)111025https://doi.org/10.1016/j.exger.2020.111025
Peterson and Fling, 2018
; Rocca et al., 2017
; Ramari et al., 2020
) in pwMS.As for lower extremity neuromuscular function, the most examined feature in pwMS is maximal muscle strength also known as maximal muscle force (Fmax; representing the maximal plateau phase of a muscle contraction) (
Jørgensen et al., 2017
). However, the ability to rapidly increase muscle force (= rate of force development (RFD); representing the ascending or rising phase of a maximal muscle contraction) may be just as important as Fmax for a number of reasons. First, existing yet so far sparse data suggest that RFD is impaired to a greater extent than Fmax when comparing pwMS with HC (Scott et al., 2011
; - Scott S.M.
- Hughes A.R.
- Galloway S.D.
- Hunter AM.
Surface EMG characteristics of people with multiple sclerosis during static contractions of the knee extensors.
Clin. Physiol. Funct. Imaging. 2011; 31 (Jan): 11-17https://doi.org/10.1111/j.1475-097X.2010.00972.x
Jørgensen et al., 2017
; Chen et al., 1987
; Lomborg et al., 2022
). A plausible explanation for this observation, so far based on studies involving HC only, is that RFD is mainly attributed to neurological factors such as motor unit recruitment and discharge rate, whereas Fmax is attributed to both neurological factors and muscular factors such as muscle size, fiber type composition, muscle contractile properties, and musculotendinous stiffness (Folland et al., 2014
; Maffiuletti et al., 2016
; Del Vecchio et al., 2019
; Enoka and Duchateau, 2017
). The attribution to neurological factors appear even more important in the early (≤ 100 ms) vs. late (≥ 200 ms) ascending phase (termed early and late RFD, respectively) (- Enoka R.M.
- Duchateau J.
Rate coding and the control of muscle force.
Cold Spring Harb. Perspect. Med. 2017; 7 (Oct 3)https://doi.org/10.1101/cshperspect.a029702
Folland et al., 2014
; Maffiuletti et al., 2016
; Del Vecchio et al., 2019
; Enoka and Duchateau, 2017
). Compared to Fmax, RFD may thus be preferentially sensitive towards neurodegeneration in pwMS as previously suggested (- Enoka R.M.
- Duchateau J.
Rate coding and the control of muscle force.
Cold Spring Harb. Perspect. Med. 2017; 7 (Oct 3)https://doi.org/10.1101/cshperspect.a029702
Lomborg et al., 2022
), and might therefore serve as a simple marker of disability status and perhaps even progression. Findings reported by Uygur and colleagues assessing hand function support this notion, despite applying a less common approach when calculating RFD (RFD scaling factor; termed ‘neuromuscular quickness’) (Uygur et al., 2020
). Second, RFD has been shown to be associated with physical function in pwMS, such as walking and chair rise capacity, at a level comparable to that of Fmax (- Uygur M.
- de Freitas P.B.
- Barone DA.
Rate of force development and relaxation scaling factors are highly sensitive to detect upper extremity motor impairments in multiple sclerosis.
J. Neurol. Sci. 2020; 408 (Jan 15)116500https://doi.org/10.1016/j.jns.2019.116500
Kjølhede et al., 2015
; Osawa et al., 2018
). Yet, RFD has been argued to be of specific importance for tasks requiring fast limb or body movement (e.g. ability to counteract unexpected perturbations and thus avoiding falling) (Pijnappels et al., 2008
; Palmer et al., 2015
). RFD and Fmax may thus complement each other when linking neuromuscular function to physical function.To the best of our knowledge, no studies have comprehensively examined and compared different outcome measures of lower extremity neuromuscular function (with specific emphasis given to RFD) across disability status in pwMS and in comparison to HC. Therefore, the primary purposes of the present study were to evaluate (1) knee extensor neuromuscular function (Fmax, early and late phase RFD) alongside proxy measures of the predominant underlying mechanistic factors (muscle activation and muscle contractile properties), and (2) lower extremity physical function in HC and ambulatory pwMS subgrouped according to their expanded disability status scale (EDSS) scores (mild, moderate, and severe) (
Kurtzke, 1983
). The secondary purposes were to evaluate to what extent knee extensor Fmax and RFD, respectively, were associated with lower extremity functional tasks and EDSS. We hypothesized that the level of impairments in neuromuscular function - yet preferentially in RFD - would increase with higher disability status (i.e. higher EDSS), and that these impairments would be associated with physical function.2. Methods
The present cross-sectional study comprise data from n=99 pwMS and n=34 age- and sex-matched HC enrolled in previous studies examining fatigue and fatigability in pwMS (pwMS n=47, HC n=15) (
Taul-Madsen et al., 2020
; Gaemelke et al., 2021
) as well as the effects of aging and/or disease progression on neuromuscular function and physical function in pwMS (pwMS n=52, HC n=19) (Sieljacks et al., 2020
; - Sieljacks P.S.
- Soberg C.A.
- Michelsen A.S.
- Dalgas U.
- Hvid L.G.
Lower extremity muscle strength across the adult lifespan in multiple sclerosis: implications for walking and stair climbing capacity.
Exp. Gerontol. 2020; 139 (Oct 1)111025https://doi.org/10.1016/j.exger.2020.111025
Rooney et al., 2019
). For further details, we refer to these previously published papers (see references Sieljacks et al., 2020
; - Sieljacks P.S.
- Soberg C.A.
- Michelsen A.S.
- Dalgas U.
- Hvid L.G.
Lower extremity muscle strength across the adult lifespan in multiple sclerosis: implications for walking and stair climbing capacity.
Exp. Gerontol. 2020; 139 (Oct 1)111025https://doi.org/10.1016/j.exger.2020.111025
Taul-Madsen et al., 2020
; Gaemelke et al., 2021
; Rooney et al., 2019
).2.1 Participants
Recruitment of participants were carried out from December 2015 to June 2018, through information posted on the website of The Danish MS Society (“Scleroseforeningen”) and provided during events in local branches of The Danish MS Society. Based on the most recent neurological examination (within the past 6 months), data on MS type, EDSS score, and time since diagnosis (TSD) were collected from all interested and eligible pwMS. Participants were included if they were 18 years or older, had a definite MS diagnosis according to the McDonald criteria (
Thompson et al., 2018
), had an EDSS score ≤ 6.5, and were able to independently attend the laboratory for testing. PwMS were excluded if they had a relapse within the past 2 months. HC were recruited through contact to enrolled pwMS (spouses, relatives, acquaintances) and through information delivered to local civic associations (offering cultural events, sports etc.), and were included if they were 18 years or older. For all participants (pwMS and HC) the following exclusion criteria applied; had any serious medical comorbidities affecting the nervous and/or muscular system (e.g. neuropathy), were pregnant, were hypertensive (systolic/diastolic > 160/100) or had a pacemaker. The pwMS were divided into three groups based on their EDSS scores (i.e. disability status): MSmild (EDSS 0-2.5, n=51), MSmoderate (EDSS 3.0–4.5, n=33), and MSsevere (EDSS 5–6.5, n=15). This subgrouping was chosen to align with the terminology of the original EDSS (Kurtzke, 1983
).All participants were reimbursed for their travel costs, yet no other compensation was offered. All participants provided written informed consent prior to enrolment, and all studies were conducted in accordance with the Declaration of Helsinki, and were approved by the Local Ethics Committee of Region Midtjylland (1-10-72-206-17; 1-10-72-287-15). The Danish Data Protection Agency oversaw the study, with data being handled according to GDPR.
2.2 Test procedures
All particpants followed the same order of testing, starting with assessment of body weight (TANITA SC220, Tokyo, Japan) and height (height stature meter), then assessment of neuromuscular function, and finally assessement of physical function.
Neuromuscular function was assessed by maximum voluntary isometric contractions (Fmax) of the knee extensors (KE) using an isokinetic dynamometer (Humac NORM, CSMi, MA, USA) (
Sieljacks et al., 2020
). The self-reported weaker leg (in most cases corresponding to the self-reported affected leg) was tested. To evaluate voluntary muscle activation, simultaneous electromyography (EMG) was recorded during all knee extensor trials along with application of the interpolated twitch technique during some trials (- Sieljacks P.S.
- Soberg C.A.
- Michelsen A.S.
- Dalgas U.
- Hvid L.G.
Lower extremity muscle strength across the adult lifespan in multiple sclerosis: implications for walking and stair climbing capacity.
Exp. Gerontol. 2020; 139 (Oct 1)111025https://doi.org/10.1016/j.exger.2020.111025
Hvid et al., 2016
). The latter also enabled us to evaluate electrically evoked muscle contractile properties. Participants were seated in an upright position adjusted to individual anatomical dimensions, with a hip joint angle of 85° and a knee joint angle of 70° (0° being fully extended). Percutaneous surface stimulation electrodes (ValuTrode Lite, 5 × 10 cm, Axelgaard Manufacturing Co Ltd, CA, USA) were placed over the distal (10 cm above patella) and proximal part (15 cm below anterior superior illiac spine) of the quadriceps belly. Stimulations were delievered as single square-wave pulses of 100 μs duration by a direct current stimulator (DS7A and DG2A, Digitimer Ltd, UK) to the resting muscle. Stepwise increments in stimulation current were given every 30s until maximal single twitch force response was achieved (i.e. until no further increase was observed in twitch force amplitude). Following a 5-min break, each participant performed 2 submaximal trials (approx. 50 and 80%, respectively, of maximal effort) and 3 Fmax trials interspersed by 1 min rest periods. Participants were instructed to contract as fast and forcefully as possible and maintain maximal knee extrensor force exertion until a plateau in force production was reached. Following another 5-min break, the interpolated twitch technique was carried out. The participants performed 2–4 additional Fmax trials, yet this time a doublet twitch stimulation (i.e. a paired single twitch stimulation separated by a 10 ms interval) was manually delivered at the plateu of the maximal force production and approximately 2 s after in the rested yet potentiated muscle. The voluntary muscle activation level was calculated by using the adjusted equation (Strojnik and Komi, 1998
): activation level (%) = 100 − ((Fdiff·(Fstim/Fmax)/Fstimrest)·100) where Fdiff is the difference between Fstim (voluntary force at stimulation) and total force (Fstim + electrically evoked force response), Fmax is maximal voluntary force, and Fstimrest is electrically evoked force response in the rested muscle. From Fstimrest, doublet twitch peak force (PF) and time to ½ doublet twitch PF were also identified.Force and electromyography (EMG) data were sampled using TeleMyo Direct Transmission System and MyoResearch Software (Noraxon, Scottsdale, AZ, USA) at 1500 Hz. Subsequent analyses were performed using custom-made software (MathWorks, MatLab 2017, MA, USA). Force data was 6Hz low-pass filtered. Onset of contraction was defined as the time at which force exceeded the baseline level by 2%. From that, RFD was derived as the average tangential slope of the ascending force–time curve calculated in the interval 0–50ms and 0–200ms relative to the onset of contraction (RFD50ms and RFD200ms, respectively; corresponding to early and late phase RFD, respectively). Fmax was determined as the highest force value attained. RFD and Fmax are presented as values normalized to body mass (Nm.s−1.kg−1 and Nm.kg−1, respectively), and RFD values were furthermore normalized to Fmax (%Fmax.s−1) to provide insight into differences in qualitative neuromuscular factors (i.e., muscle activation and muscle contractile properties; see below) (
Folland et al., 2014
; Maffiuletti et al., 2016
). Surface EMG (sEMG) signals were recorded from the distal part of the Vastus Lateralis during all knee extension trials. After careful skin preparation (shaving, abrasion with sandpaper, cleaning with alcohol), two sEMG electrodes (Ambu BlueSensor N, Medicotest A/S, Ballerup, Denmark) were placed on the distal lateral part of the vastus lateralis muscle according to SENIAM recommendations (Hermens et al., 2000
). EMG data was also 6Hz low-pass filtered and subsequently full-wave rectified resulting in a linear envelope, from which mean average voltage was calculated in a 250 ms interval (maximal EMG, EMGFmax) preceding the time at which Fmax was determined to occur. Onset of EMG was defined as the time at which EMG increased 2 standard deviations (SD) above baseline. From that, rate of EMG rise was calculated as the slope of the EMG-time curve (ΔEMG/Δtime), in the intervals of 0–50 and 0–200 ms relative to the onset of EMG (rEMG50ms and rEMG200ms, respectively). rEMG and EMGFmax are presented as raw values (µV) normalized to Fmax (%Fmax.s−1 and %Fmax, respectively) (Farina et al., 2010
).During all trials, participants were provided with real-time visual feedback along with strong verbal support. Trials with initial countermovement (identified by a visible drop in the force response) were discarded, and a new trial was performed. All force trials were gravity corrected.
To help provide a simpler overview of the included mechanistic outcome measures, we have chosen to use the umbrella terms neuromuscular function (comprising RFD50ms, RFD200ms, and Fmax), muscle activation (comprising rEMG50ms, rEMG200ms, EMGFmax and activation level), and contractile muscle properties (comprising doublet twitch PF and time to ½ doublet twitch PF).
Assessment of physical function comprised the timed 5 x sit-to-stand test (5STS) on a chair without arm support (width 42cm, depth 43cm, height 47cm) (
Møller et al., 2012
), the timed 25-foot walk test (T25FWT) (Kieseier and Pozzilli, 2012
), and the 2-min maximal walk test (2MWT) as a measure of walking endurance (Wade, 1992
). For participants from the study examining fatigue and fatigability, 2MWT was derived from the first two minutes of their six-minute walk, previously shown to have no influence on the result (Gijbels et al., 2011
). The 5STS and T25FWT were performed twice, and the better result was selected for analyses.2.3 Statistics
Statistical analyses were performed using linear mixed model in STATA (IC 16, StataCorp, College Station, TX, USA). All data, i.e. outcomes related to participant characteristics, neuromuscular function, muscle activation, muscle contractile properties, and physical function, followed a normal distribution. Participant ID was set as a random effect and group (HC, MSmild, MSmoderate, MSsevere) as a fixed effect, enabling us to examine group effects (HC vs. MSmild vs. MSmoderate vs. MSsevere). In addition, overall group effects (HC vs. MS) are shown in Supplementary Table 1. To accentuate the differences between pwMS and HC across neuromuscular function, muscle activation as well as muscle contractile properties, percentage deficits were calculated as individual values for each pwMS expressed in relation to the mean HC value. To examine proportions of MS types in pwMS along with proportions of sex in pwMS and HC, fisher's exact test was used. Simple linear regression was performed to examine associations between neuromuscular function and physical function as well as between deficits in neuromuscular function (group mean data summarized across those pwMS having a given EDSS score) and disability status. In addition, we also analyzed data adjusted for the common confounders sex and age. The level of statistical significance was set at p<0.05. Data in text and tables are presented as mean±SD unless otherwise stated, and in figures as mean±95%CI.
3. Results
3.1 Participant characteristics
Table 1 as well as Supplementary Table 1 contain information on participant characteristics. Of the included pwMS (n=99), 68% had relapsing-remitting MS, 18% secondary progressive MS, and 14% primary progressive MS. Participants were mostly female (pwMS 70%, HC 71%). No group differences were observed for sex, age, height, or weight, whereas differences in EDSS, time since diagnosis, and MS phenotype was observed between the MS groups (Table 1). These group differences generally followed disease progression (i.e. the a priori group allocation), with MSmild < MSmoderate < MSsevere for EDSS, time since diagnosis, and MS phenotype (proportion being progressive).
Table 1Participant demographics as well as physical, neuromuscular, muscle activation, and muscle contractile properties.
 |
Data are presented as mean±SD. EDSS: Expanded Disability Status Scale, TSD: time since diagnosis, RR: relapsing-remitting, SP: secondary progressive, PP: primary progressive, 5STS: 5 times sit-to-stand, T25FWT: timed 25-foot maximal walk test, 2MWT: 2-min maximal walk test, RFD50ms: rate of force development 0−50ms from force onset, RFD200ms: rate of force development 0−200ms from force onset, Fmax: maximal voluntary isometric contraction of knee extensor muscles, EMGFmax: maximal EMG 200ms preceding Fmax, rEMG50ms: rate of EMG rise 0−50ms after EMG onset, rEMG200ms: rate of EMG rise 0−200ms after EMG onset; PF, peak force.
#group effect for MS only. Statistics (level of significance set at p<0.05; trends set at p<0.10 shown in italic): a=different from HC, b=different from MSmild, c=different from MSmoderate. Displayed in grey text, 5STS, T25FWT, and 2MWT are also reported as absolute median values to enable comparison with previous studies.
3.2 Neuromuscular function, muscle activation, and muscle contractile properties
From the group mean force-time curves shown in Fig. 1, substantial visual differences in neuromuscular function were observed between HC, MSmild, MSmoderate, and MSsevere (i.e. following disability status), especially for RFD. Table 1 and Fig. 2 verify this, with deficits in MS groups relative to HC ranging between 22−66% and 12−51% for RFD50ms and RFD200ms, respectively, and ranging between 11 and 33% for Fmax.
Fig. 1Group mean force–time curves obtained during maximal isometric knee extension in HC (black line, n=34), MSmild (blue line, n=51), MSmoderate (green line, n=33), and MSsevere (red line, n=15). Top figure display a 2 s window, during which both the ascending phase (approximate range 0.00–0.50 s) and the plateau phase (approximate range 1.25–2.00 s) are shown. Bottom figure display a 0.25 s window, during which the steepest part of the ascending/rising phase is shown only, with vertical dotted lines denoting force development after 0.05 and 0.20 s (used to calculate RFD50ms and RFD200ms), relative to onset of contraction (time = 0.00 s). See Table 1 and Fig. 2 for specific values and statistics. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 2Percentage difference in neuromuscular function (RFD50ms, RFD200ms, Fmax), muscle activation (rEMG50ms, rEMG200ms, EMGFmax, Activation level), and muscle contractile properties (time to ½ doublet peak force, doublet peak force) in MSmild (blue bars, n=51), MSmoderate (green bars, n=33), and MSsevere (red bars, n=15) relative to HC (black horizontal zero line, n=34). For all outcomes of neuromuscular function and muscle activation, significant group effects were observed (p<0.05). This was not observed for muscle contractile properties outcomes. Post hoc analyses revealed significant differences (p<0.05) from HC (denoted by a), from MSmild (denoted by b), and from MSmoderate (denoted by c). Italic letters denote statistical trends (0.10>p>0.05). See Table 1 for absolute values and statistics. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Regarding muscle activation, a somewhat comparable magnitude of changes to that of neuromuscular function was observed (Table 1 and Fig. 2), with deficits in pwMS subgroups relative to HC ranging between 19–62% and 17–52% for rEMG50ms and rEMG200ms, respectively, and ranging between 23–41% and 7–18% for EMGFmax and activation, respectively.
3.3 Physical function
Across all physical function outcome measures (5STS, T25FWT, 2MWT), group differences were observed that generally followed disability status, i.e. with HC > MSmild > MSmoderate > MSsevere (Table 1).
3.4 Associations between neuromuscular function deficits and disability status (EDSS)
As visualized in Fig. 3, group mean differences (∼deficits) relative to HC across all neuromuscular function outcome measures increased with higher EDSS scores (i.e. disability status). This was preferentially more evident in early phase RFD vs. late phase RFD vs. Fmax, with linear regression slope steepness corresponding to changes in deficits by -13, -10, and -6 %, respectively, per 1 point increase in EDSS .
Fig. 3Associations between EDSS and difference (∼deficit) in neuromuscular function (RFD50ms, RFD200ms, Fmax) in MSmild (blue dots), MSmoderate (green dots), and MSsevere (red dots) relative to HC (dotted grey horizontal zero line). Each dot represent group mean data summarized across those pwMS having a given EDSS score. Simple linear regression analyses were performed, with slope steepness, determination coefficient (r2), and p-value being displayed. Slope steepness correspond to change in magnitude of deficit when EDSS score increases by a unit of 1. In regards to slope steepness as change in absolute levels when EDSS score increases by a unit of 1, this corresponded to -1.61 [-2.15;-1.06] Nm.s−1.kg−1 for RFD50ms (r2=0.79, p<0.001), -0.73 [-0.94;-0.53] Nm.s−1.kg−1 for RFD200ms (r2=0.85, p<0.001), and -0.15 [-0.22;-0.09] Nm.s−1.kg−1 for Fmax (r2=0.67, p<0.001). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
3.5 Associations between neuromuscular function and physical function
All neuromuscular function outcome measures (RFD50ms, RFD200ms, Fmax) were associated with physical function outcome measures (5STS, T25FWT, 2MWT) in pwMS (r2-values ranging from 0.21 to 0.35, p<0.001), yet with no apparent difference between early phase RFD, late late phase RFD, and Fmax (Table 2). Somewhat similar findings were observed for HC (r2-values ranging from 0.26 to 0.40, p<0.05; except for RFD50ms and 5STS, r2=0.21, p=0.067) (Table 2).
Table 2Associations between lower extremity muscle strength and physical function.
| 5STS | T25FWT | 2MWT | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| RFD50ms | RFD200ms | Fmax | RFD50ms | RFD200ms | Fmax | RFD50ms | RFD200ms | Fmax | ||
| HC n=34 | r2-value | 0.21 | 0.30 | 0.39 | 0.29 | 0.29 | 0.37 | 0.40 | 0.31 | 0.26 |
| p-value | 0.067 | 0.013 | 0.002 | 0.015 | 0.016 | 0.003 | <0.001 | 0.003 | 0.010 | |
| pwMS n=99 | r2-value | 0.21 | 0.22 | 0.30 | 0.32 | 0.35 | 0.33 | 0.23 | 0.26 | 0.29 |
| p-value | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | |
3.6 Adjusted analyses
Adjusting for age and sex did not affect any of the results listed above (data not shown).
4. Discussion
The present cross-sectional study comprehensively examined different outcome measures of lower extremity neuromuscular function (with a specific emphasis on RFD) as well as physical function across disability status in ambulatory pwMS. Overall, the novel results revealed that the differences for most outcome measures followed disability status: HC > MSmild ≥ MSmoderate > MSsevere. Also, our findings demonstrate that the RFD (RFD50ms in particular) distinguishes more effectively across disability status than does Fmax. A comparable magnitude of changes was observed in muscle activation, as opposed to muscle contractile properties where only few changes were observed. Moreover, the association between EDSS scores and deficits in neuromuscular function revealed the steepest slope for RFD50ms (corresponding to 13% point reduction per 1 point increase in EDSS), followed by RFD200ms (10% point reduction) and Fmax (6% point reduction). Lastly, neuromuscular function outcome measures were all associated with physical function outcome measures in pwMS (explaining 21–35 %), yet with no apparent differences between early RFD, late RFD, and Fmax.
4.1 Neuromuscular function, muscle activation, and muscle contractile properties
Muscle weakness is a hallmark of MS, with studies showing that Fmax deteriorates with increased disability (i.e. higher EDSS scores) (
Sieljacks et al., 2020
; - Sieljacks P.S.
- Soberg C.A.
- Michelsen A.S.
- Dalgas U.
- Hvid L.G.
Lower extremity muscle strength across the adult lifespan in multiple sclerosis: implications for walking and stair climbing capacity.
Exp. Gerontol. 2020; 139 (Oct 1)111025https://doi.org/10.1016/j.exger.2020.111025
Broekmans et al., 2013
; Güner et al., 2015
). This has been elaborated in a previous systematic review from our group, reporting that the average deficit in Fmax (pwMS relative to HC) across different lower extremity muscle groups corresponded to 27% (24% in KE), derived from studies having mean EDSS ranging from 2.4 to 6.3 (Jørgensen et al., 2017
). Whilst the overall deficit in KE of the present study was 16% only, it corresponds well with the mean EDSS being 2.9 across the entire sample of pwMS (n=99, EDSS range 0−6.5, EDSS mean 2.9; Supplementary Table 1), and thus in the low end of what was reported in the review. Moreover, the association between EDSS and deficits in Fmax only differed slightly between the present study and the previous review (slope steepness corresponding to changes in deficits per increase in EDSS: -6.4 [-9.1:-3.7] % vs. -8.6 [-14.1:-2.5] %, respectively) (see Fig. 6 in Jørgensen et al., 2017
).Regarding RFD, existing yet so far sparse data suggest that RFD is more impaired than Fmax in pwMS vs. HC (
Scott et al., 2011
; - Scott S.M.
- Hughes A.R.
- Galloway S.D.
- Hunter AM.
Surface EMG characteristics of people with multiple sclerosis during static contractions of the knee extensors.
Clin. Physiol. Funct. Imaging. 2011; 31 (Jan): 11-17https://doi.org/10.1111/j.1475-097X.2010.00972.x
Jørgensen et al., 2017
; Chen et al., 1987
; Lomborg et al., 2022
), i.e. representing the ascending phase vs. the plateau phase of a maximal muscle contraction. Chen and colleagues reported 2.1-fold greater deficits (pwMS relative to HC) in knee extensor RFD vs. Fmax (same in knee flexor), with RFD being derived from force onset to peak force (n=15 pwMS; no details on participant characteristics provided) (Chen et al., 1987
). Scott and colleagues reported data on knee extensor early and late phase RFD as well as Fmax (n=15, EDSS range 4–6) (Scott et al., 2011
), i.e. equivalent to the RFD measures of the present study. They reported 2.1-fold greater deficits in RFD200ms vs. Fmax and 2.4-fold greater deficits in RFD50ms vs. Fmax. In comparison, we reported 1.4-fold greater deficits in RFD200ms vs. Fmax and 2.2-fold greater deficits in RFD50ms vs. Fmax across the entire sample of pwMS (n=99, EDSS range 0–6.5, EDSS mean 2.9; Supplementary Table 1). The findings of the present study, derived from a large and well-characterized cohort of pwMS, substantiate that disability status is associated with preferential deterioration of RFD. The latter is clearly evident from both Figs. 2 and 3, with a greater magnitude of deterioration in RFD50ms vs. RFD200ms vs. Fmax, respectively (slope steepness corresponding to changes in deficits per 1 point increase in EDSS: -13% vs. -10 % vs. -6%, respectively). The fact that relative RFD also differed across disability status (Table 1), albeit less pronounced for the late phase relative RFD (differences only observed between HC and MSsevere), suggest that qualitative factors (such as muscle activation and muscle contractile properties; elaborated below) also contributed to the differences and deficits observed in RFD (- Scott S.M.
- Hughes A.R.
- Galloway S.D.
- Hunter AM.
Surface EMG characteristics of people with multiple sclerosis during static contractions of the knee extensors.
Clin. Physiol. Funct. Imaging. 2011; 31 (Jan): 11-17https://doi.org/10.1111/j.1475-097X.2010.00972.x
Folland et al., 2014
; Maffiuletti et al., 2016
).An interesting observation was that greater differences and deficits were observed in early phase rEMG vs. late phase rEMG vs. EMGFmax / activation level, thus paralleling that observed in neuromuscular function outcome measures. In pwMS, associations between deficits in related outcome measures strongly support this (early phase rEMG and RFD: r2=0.55, p<0.001; late phase rEMG and RFD: r2=0.35, p<0.001; EMGFmax and Fmax: r2=0.19, p=0.012; activation level and Fmax: r2=0.11, p=0.071) (data not shown). Our findings are thus aligned with the notion that RFD is mainly attributed to neurological factors such as motor unit recruitment and discharge rate, whereas Fmax is also attributed to other factors (e.g. muscle size, fiber type composition) (
Folland et al., 2014
; Maffiuletti et al., 2016
; Del Vecchio et al., 2019
; Enoka and Duchateau, 2017
; - Enoka R.M.
- Duchateau J.
Rate coding and the control of muscle force.
Cold Spring Harb. Perspect. Med. 2017; 7 (Oct 3)https://doi.org/10.1101/cshperspect.a029702
Hvid et al., 2017
). Whilst we are unaware of other studies that have reported on muscle activation during the ascending phase of a maximal muscle contraction in pwMS, this has been done during the plateau phase. Specifically, reduced EMGFmax, activation level, and Fmax motor unit discharge rates in pwMS vs. HC have previously been reported (Scott et al., 2011
; - Scott S.M.
- Hughes A.R.
- Galloway S.D.
- Hunter AM.
Surface EMG characteristics of people with multiple sclerosis during static contractions of the knee extensors.
Clin. Physiol. Funct. Imaging. 2011; 31 (Jan): 11-17https://doi.org/10.1111/j.1475-097X.2010.00972.x
Ng et al., 2004
; Rice et al., 1992
; de Haan et al., 2000
). The findings of the present study thus corroborates and expand on previous findings.- de Haan A.
- de Ruiter C.J.
- van Der Woude L.H.
- Jongen P.J.
Contractile properties and fatigue of quadriceps muscles in multiple sclerosis.
Muscle Nerve. 2000; 23 (Oct): 1534-1541https://doi.org/10.1002/1097-4598(200010)23:10<1534::aid-mus9>3.0.co;2-d
In contrast, no major differences were observed in muscle contractile properties (i.e. time to ½ doublet twitch PF and doublet twitch PF), thus aligned with previous reportings (
Ng et al., 2004
; Rice et al., 1992
; de Haan et al., 2000
). Although not examined in the present study, reduced muscle mass especially of the fast type II muscle fibers (- de Haan A.
- de Ruiter C.J.
- van Der Woude L.H.
- Jongen P.J.
Contractile properties and fatigue of quadriceps muscles in multiple sclerosis.
Muscle Nerve. 2000; 23 (Oct): 1534-1541https://doi.org/10.1002/1097-4598(200010)23:10<1534::aid-mus9>3.0.co;2-d
Sieljacks et al., 2020
; - Sieljacks P.S.
- Soberg C.A.
- Michelsen A.S.
- Dalgas U.
- Hvid L.G.
Lower extremity muscle strength across the adult lifespan in multiple sclerosis: implications for walking and stair climbing capacity.
Exp. Gerontol. 2020; 139 (Oct 1)111025https://doi.org/10.1016/j.exger.2020.111025
Zikan et al., 2012
; Wens et al., 2014
; - Wens I.
- Dalgas U.
- Vandenabeele F.
- Krekels M.
- Grevendonk L.
- Eijnde B.O.
Multiple sclerosis affects skeletal muscle characteristics.
PLoS One. 2014; 9e108158https://doi.org/10.1371/journal.pone.0108158
Kent-Braun et al., 1997
) (despite exceptions (Carroll et al., 2005
; Lambert et al., 2002
)) along with a shift towards a faster fiber type composition (Wens et al., 2014
; - Wens I.
- Dalgas U.
- Vandenabeele F.
- Krekels M.
- Grevendonk L.
- Eijnde B.O.
Multiple sclerosis affects skeletal muscle characteristics.
PLoS One. 2014; 9e108158https://doi.org/10.1371/journal.pone.0108158
Kent-Braun et al., 1997
; Carroll et al., 2005
) have been reported in pwMS compared to HC. While the latter theoretically favors RFD, the exact influence of disability progression in pwMS on these outcome measures remains to be established. We nevertheless speculate, that deterioration of muscle mass along with muscle contractile properties is secondary to the MS-induced neurodegeneration (e.g., changes in muscle activation), developing later and perhaps even less pronounced than that observed within the CNS, as also seen with changes in the PNS compared to the CNS (Mamoei et al., 2020
).- Mamoei S.
- Hvid L.G.
- Boye Jensen H.
- Zijdewind I.
- Stenager E.
- Dalgas U.
Neurophysiological impairments in multiple sclerosis-Central and peripheral motor pathways.
Acta Neurol. Scand. 2020; (May 31)https://doi.org/10.1111/ane.13289
4.2 Associations between neuromuscular function and physical function
In contrast to our expectations, early and late RFD did not show superior associations with physical function (5STS, T25FWT, 2MWT) compared to that of Fmax (explaining 21–30%, 32–35%, and 23–29%, respectively). The magnitude of these associations revealed that factors other than RFD and Fmax also contribute to physical function in the involved pwMS, with influence of neuromuscular function of other muscle groups (
Ramari et al., 2020
) along with balance/coordination (Filli et al., 2018
; Callesen et al., 2019
) being obvious candidates. An alternative interpretation is that RFD and Fmax may be associated with different phases of performing a physical functional task. In fact, a large-scale study (n=1089, age range 26–96 years) from Osawa et al. (Osawa et al., 2018
) showed that RFD and Fmax impacted the same physical functional task to a comparable extent yet independently of each other. In a clinical context, the notions outlined above should thus be kept in mind when interpreting the findings of the present study and discussing the importance of RFD vs. Fmax.Despite the greater deficits observed in early RFD vs. late RFD vs. Fmax, the considerable variability in these outcome measures may have ‘contaminated’ the associations with physical function. Across all pwMS, the coefficient of variation (= SD / mean * 100) was substantially larger with early RFD compared to late RFD and Fmax (78% vs. 48% vs. 28%, respectively). The same was observed for HC (55 % vs. 39% vs. 24%, respectively).
4.3 Clinical implications and future perspectives
In addition to verifying that impairments in lower extremity neuromuscular function are hallmarks of MS and differ across disability status, we expand current understanding thereof, by showing that RFD (early phase in particular) is preferentially sensitive towards neurodegeneration, i.e. by adapting earlier and/or more extensively than Fmax. Altogether, RFD could serve as a simple objective marker of disability progression in pwMS. The fact that RFD was only moderately associated with physical function (and comparable to that of Fmax; previously observed in neurodegenerative populations (
Lomborg et al., 2022
)) nevertheless emphasize that other factors are also involved and of clinical relevance. This notion must be taken into account when interpreting the present study findings.Identification of modifiable predictors of physical function and disability is of major clinical relevance to pwMS, particularly as this can help optimize counteractive strategies (e.g. physical rehabilitation and exercise). To achieve improvements in lower extremity neuromuscular function (RFD in particular) along with physical function (e.g. walking capacity), we highly recommend high-intensity resistance or power training in combination with functional tasks as suc exercise modalities have shown to be very effective in pwMS (
Kjølhede et al., 2015
; Dalgas et al., 2013
; Taul-Madsen et al., 2021
). As shown in HC, this should ideally involve rapid maximal muscle contractions in order to elicit optimal adaptations in motoneuron behaviour (i.e., recruitment speed of motoneurons) - a requirement to achieve increases in RFD (Del Vecchio et al., 2021
). Of note, our recommendation may not be applicable to very severely affected pwMS having EDSS ≥ 7, as few resistance/power training studies exist (e.g., - Del Vecchio A.
- Casolo A.
- Dideriksen J.L.
- et al.
Lack of increased rate of force development after strength training is explained by specific neural, not muscular, motor unit adaptations.
J. Appl. Physiol. 2021; (Nov 18)https://doi.org/10.1152/japplphysiol.00218.2021
Filipi et al., 2011
) and with none of these examining RFD.Future studies should help elucidate (1) whether tests of physical function or specific phases thereof preferentially rely on specific muscle groups and/or on specific muscle response times (relating to early RFD, late RFD, or Fmax, respectively), and (2) whether high-intensity resistance or power training in combination with functional tasks can reverse the substantial impairments observed in RFD.
4.4 Methodological considerations
A number of methodological considerations of the study deserve mentioning. The main strength is the moderately large sample size of pwMS along with the comprehensive testing of neuromuscular function. The main limitation is the cross-sectional study design, which contain several sub-optimal aspects possibly affecting the results and interpretation (e.g. lack of causality). Moreover, the study findings should be cautiously interpreted as it may have been affected by factors other than disability status (i.e. neurodegeneration) per se. Changes in lifestyle factors such as low physical activity level / exercise participation, smoking, and suboptimal dietetary habits are all known to be associated with ‘accelerated’ disease progression (
Rooney et al., 2019
; Healy et al., 2009
; D'Hooghe et al., 2012
; Jakimovski et al., 2019
). As for physical activity, our group have previously shown this to be associated with deterioration of Fmax and RFD50ms in pwMS (Rooney et al., 2019
). However, our intention of the present paper was to produce a ‘here-and-now’ picture, displaying the extent of impairments in neuromuscular function in a representative cohort of ambulatory Danish MS patients. Moreover, our data is limited to one muscle group (i.e. knee extensors) assessed during isometric contraction only, contrasting the requirements of performing most daily functional tasks that involve multi-joint dynamic movements (e.g. walking, stair negotiation, chair rise). Yet, current evidence support that associations between neuromuscular function (Fmax) assessed in different lower extremity muscle groups and physical function are comparable (Ramari et al., 2020
), and with slightly greater associations between dynamic contraction muscle strength and physical function compared to isometric contraction muscle strength and physical function (Sieljacks et al., 2020
; - Sieljacks P.S.
- Soberg C.A.
- Michelsen A.S.
- Dalgas U.
- Hvid L.G.
Lower extremity muscle strength across the adult lifespan in multiple sclerosis: implications for walking and stair climbing capacity.
Exp. Gerontol. 2020; 139 (Oct 1)111025https://doi.org/10.1016/j.exger.2020.111025
Ramari et al., 2020
). Also, the use of sEMG amplitude as a proxy measure of muscle activation holds severallimitations (Farina et al., 2010
). Future studies should take the aspects outlined above into account, for instance by examining muscle activation via more advanced methods such as high-density sEMG decomposition (Del Vecchio et al., 2019
Del Vecchio et al., 2021
).- Del Vecchio A.
- Casolo A.
- Dideriksen J.L.
- et al.
Lack of increased rate of force development after strength training is explained by specific neural, not muscular, motor unit adaptations.
J. Appl. Physiol. 2021; (Nov 18)https://doi.org/10.1152/japplphysiol.00218.2021
5. Conclusion
The present study observed that knee extensor neuromuscular function is impaired in ambulatory pwMS compared to HC, with deficits becoming increasingly greater with higher disability status assumed to be driven by neurodegeneration. RFD was preferentially sensitive in capturing differences (∼deficits) across disability status and by showing strong associations with EDSS, whereas RFD and Fmax were associated with physical function to a comparable moderate extent. Furthermore, RFD was paralleled by impairments in muscle activation, but not muscle contractile properties. Altogether, RFD could serve as a simple objective marker of disability status or even progression in pwMS, that may be helpful to both researchers and clinicians.
CRediT authorship contribution statement
Laurits Taul-Madsen: Conceptualization, Methodology, Formal analysis, Writing – original draft. Morten Riemenschneider: Conceptualization, Methodology, Investigation, Writing – review & editing. Marie-Louise K. Jørgensen: Conceptualization, Methodology, Investigation, Writing – review & editing. Ulrik Dalgas: Conceptualization, Methodology, Writing – review & editing. Lars G. Hvid: Conceptualization, Methodology, Investigation, Formal analysis, Writing – original draft.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
We like to thank the study participants their role in the study.
Appendix. Supplementary materials
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Article Info
Publication History
Published online: July 29, 2022
Accepted:
July 28,
2022
Received in revised form:
July 12,
2022
Received:
March 14,
2022
Identification
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