Aim: The aim of this study was to describe the neuromuscular characteristics of Multiple Sclerosis (MS) patients. To help explain the neuromuscular characteristics physical activity levels, body composition and blood lipid profile were measured. In addition, Vitamin D was measured to determine if this was deficient in MS patients.
Hypothesis: We hypothesised that muscle fibre conduction velocity (MFCV) would be elevated and amplitude would be impaired in Multiple Sclerosis patients compared to an age and sex matched control group. In addition, we hypothesised that physical activity levels would be reduced, body composition would exhibit a higher percentage fat, blood lipid profile would be less favourable and Vitamin D levels would be reduced in the group of MS patients.
Methodology: 15 MS patients (53.8±10.5 years) and 14 age and sex matched control participants (54.6±9.6 years) were recruited for this study. Patients with a disability status (EDSS) (92) of between 4 and 6 were included in this study. All participants provided written informed consent after being fully informed of the procedures.
An array of 4, 8mm Ag-AgCl electrodes was placed in a hard plastic mould in a straight line, leaving 12.5mm between each electrode. The array was positioned on the vastus lateralis between the innervation zone and the distal tendon and was orientated to follow the muscle fibre pennation direction. Electromyographic (EMG) data was collected via the electrodes whilst the participant carried out each contraction. Muscle fibre conduction velocity (MFCV) and root mean square (RMS) were calculated from the raw EMG signal collected during each contraction.
The protocol was carried out on both legs. Isometric knee extensions were standardised using the Bio-Dex Systems 3 Isokinetic Dynamometer and executed with the knee at 60° angle of flexion. Participants were tested under four different contraction intensities; 20, 40, 60 and 80% of the peak value of their maximum voluntary contraction (MVC). Their MVC was established for both legs. For each test condition the participant was required to carry out 3 isometric contractions for 7 seconds; each contraction was separated by 14 seconds rest. During each set of contractions the target force was visible on the Bio-Dex monitor. Participants obtained visual feedback from the Bio-Dex throughout each contraction allowing the participant to adjust the force they were required to produce to maintain their target force.
Whole body composition (fat mass, lean mass and bone mineral content) was measured by Dual-energy X-ray Absorptiometry (DEXA) using a Lunar Prodigy DF+ 13643, GE medical systems scanner. Whole body and thigh composition were extrapolated from the digitalised results of the scan.
Habitual physical activity was measured for 7 days using the GT1M Actigraph accelerometer, which was worn on the participants’ right hip during all waking hours. Data collected by and downloaded from the accelerometer was used to calculate each participant’s total and mean accelerometer counts per day.
A fasted 10ml sample of venous blood was drawn from an antecubital vein using a 10ml syringe and a 15mm gauge needle. The blood samples were analysed for total cholesterol, triglyceride and high density lipoproteins (HDL), low density lipoprotein (LDL) and Vitamin D concentration.
Results: Initial findings revealed that the patient group exhibited a significantly faster (P0.05) in MFCV over all the contractions between the groups. There was no significant difference (P>0.05) in MFCV between the dominant and non-dominant leg within each group.
Analysis of the RMS data revealed that there was no significant difference (P>0.05) over all the contractions between the patient and the control group in either the dominant or the non-dominant leg. However there was a highly significant difference (P<0.001) in RMS between contraction intensity in both legs in both groups.
There was a significant difference (P0.05) was identified between the dominant and non-dominant leg within each group.
There was no significant difference (P>0.05) in absolute lean thigh mass (LTM) between the two groups however the difference in relative lean thigh mass (lean thigh mass/lean body mass*100) between the groups was approaching significance (P=0.077).
The patient group exhibited a significantly (P0.05) in whole body or thigh bone mineral density (BMD) between the groups.
The patient group was significantly (P<0.05) less physically active than the control group; this was evident from their total accelerometer counts/day (patients 167088±113586, control 316401±108982) and mean accelerometer counts/day (patients 206.4±139.5, controls 364.5±120.6).
There was no significant difference (P>0.05) in blood lipid profile (cholesterol, triglycerides, HDL or LDL) between patients and control group. However there was a significant difference (P<0.05) in serum Vitamin D concentration between the patient and the control group.
Conclusion: MS patients exhibited faster MFCV with a similar number of motor units recruited than healthy ages and sex matched controls. However, an increased quantity of subcutaneous fat artificially elevates MFCV (110) and MS patients in this study exhibit higher percentage fat than the controls. Therefore, when accounting for this confounding variable we then showed that there was in fact no difference in MFCV between the groups. However the patients MFCV responded differently to the increased contraction intensity than the controls which suggests altered neuromuscular processing within the patient group.
The MS group had reduced physical activity levels which caused a slight disuse atrophy of the lower limbs which did not compromise muscle quality. Therefore, similar quality of the muscle has resulted in unaltered neuromuscular recruitment in MS patients.
Overall, the results indicate that there was no difference in neuromuscular characteristics of MS patients compared to age and sex matched controls, even in the presence of altered body composition and physical activity levels
