Predicting Long-term Disability in Multiple Sclerosis: A Narrative Review of Current Evidence and Future Directions

Weak grip strength among persons with multiple sclerosis having minimal disability is not related to agility or integrity of the corticospinal tract

INTRODUCTION

Mobility impairment is common in multiple sclerosis (MS); however, agility has received less attention. Agility requires strength and neuromuscular coordination to elicit controlled propulsive rapid whole-body movement. Grip strength is a common method to assess whole body force production, but also reflects neuromuscular integrity and global brain health. Impaired agility may be linked to loss of neuromuscular integrity (reflected by grip strength or corticospinal excitability).

OBJECTIVES

We aimed to determine whether grip strength would be associated with agility and transcranial magnetic stimulation (TMS)-based indices of corticospinal excitability and inhibition in persons with MS having low disability. We hypothesized that low grip strength would predict impaired agility and reflect low corticospinal excitability.

METHODS

We recruited 34 persons with relapsing MS (27 females; median [range] age 45.5 [21.0-65.0] years) and mild disability (median [range] Expanded Disability Status Scale 2.0 [0-3.0]), as well as a convenience sample of age- and sex-matched apparently healthy controls. Agility was tested by measuring hop length during bipedal hopping on an instrumented walkway. Grip strength was measured using a calibrated dynamometer. Corticospinal excitability and inhibition were examined using TMS-based motor evoked potential (MEP) and corticospinal silent period (CSP) recruitment curves, respectively.

RESULTS

MS participants had significantly lower grip strength than controls independent of sex. Females with and without MS had weaker grip strength than males. There were no statistically significant sex or group differences in agility. After controlling for sex, weaker grip strength was associated with shorter hop length in controls only (r = 0.645, p < .05). Grip strength did not significantly predict agility in persons with MS, nor was grip strength predicted by corticospinal excitability or inhibition.

CONCLUSIONS

In persons with MS having low disability, grip strength (normalized to body mass) was reduced despite having intact agility and walking performance. Grip strength was not associated with corticospinal excitability or inhibition, suggesting peripheral neuromuscular function, low physical activity or fitness, or other psychosocial factors may be related to weakness. Low grip strength is a putative indicator of early neuromuscular aging in persons with MS having mild disability and normal mobility.

Relevance of Multiple Sclerosis Severity Genotype in Predicting Disease Course: A Real-World Cohort

OBJECTIVE

Currently, 233 genetic loci are known to be associated with susceptibility to multiple sclerosis (MS). Two independent pivotal severity genome-wide association studies recently found the first genome-wide significant single-nucleotide variant (SNV; rs10191329A ) and several other suggestive loci associated with overall disability outcomes. It is now important to understand if these findings can influence individual patient management.

METHODS

We assessed whether these progression SNVs are associated with detailed clinical phenotypes in a well-characterized prospective cohort of 1,455 MS patients. We used logistic regression, survival analysis, and propensity score matching to predict relevant long-term clinical outcomes.

RESULTS

We were unable to detect any association between rs10191329A and a range of clinically relevant outcomes (eg, time to Expanded Disability Status Scale milestones, age-related MS severity score, anatomical localization at onset or during subsequent relapses, annualized relapse rate). In addition, an extremes of outcome case-control analysis using a propensity score matching for genotype detected no association between disease severity and rs10191329A . However, we were able to replicate the association of two suggestive SNVs (rs7289446G and rs868824C ) with the development of fixed disability, albeit with modest effect sizes, and the association of HLA-DRB1*1501 with age at onset.

INTERPRETATION

Identification of rs10191329A and other suggestive SNVs are of considerable importance in understanding pathophysiological processes associated with MS severity. However, it is unlikely that individual genotyping can currently be used in a clinical setting to guide disease management. This study shows the importance of independent replication of genome-wide association studies associated with disease progression in neurodegenerative disorders. ANN NEUROL 2024;95:459-470.

Neuroimaging to monitor worsening of multiple sclerosis: advances supported by the grant for multiple sclerosis innovation

Key unmet needs in multiple sclerosis (MS) include detection of early pathology, disability worsening independent of relapses, and accurate monitoring of treatment response. Collaborative approaches to address these unmet needs have been driven in part by industry-academic networks and initiatives such as the Grant for Multiple Sclerosis Innovation (GMSI) and Multiple Sclerosis Leadership and Innovation Network (MS-LINK™) programs. We review the application of recent advances, supported by the GMSI and MS-LINK™ programs, in neuroimaging technology to quantify pathology related to central pathology and disease worsening, and potential for their translation into clinical practice/trials. GMSI-supported advances in neuroimaging methods and biomarkers include developments in magnetic resonance imaging, positron emission tomography, ocular imaging, and machine learning. However, longitudinal studies are required to facilitate translation of these measures to the clinic and to justify their inclusion as endpoints in clinical trials of new therapeutics for MS. Novel neuroimaging measures and other biomarkers, combined with artificial intelligence, may enable accurate prediction and monitoring of MS worsening in the clinic, and may also be used as endpoints in clinical trials of new therapies for MS targeting relapse-independent disease pathology.

Progression risk stratification with six-minute walk gait speed trajectory in multiple sclerosis

Background

Multiple Sclerosis (MS) disease progression has notable heterogeneity among patients and over time. There is no available single method to predict the risk of progression, which represents a significant and unmet need in MS.

Methods

MS and healthy control (HC) participants were recruited for a 2-year observational study. A latent-variable growth mixture model (GMM) was applied to cluster baseline 6-min walk gait speed trajectories (6MWGST). MS patients within different 6 MWGST clusters were identified and stratified. The group membership of these MS patients was compared against 2-year confirmed-disease progression (CDP). Clinical and patient-reported outcome (PRO) measures were compared between HC and MS subgroups over 2 years.

Results

62 MS and 41 HC participants completed the 2-year study. Within the MS cohort, 90% were relapsing MS. Two distinct patterns of baseline 6 MWGST emerged, with one cluster displaying a faster gait speed and a typical "U" shape, and the other showing a slower gait speed and a "flattened" 6 MWGST curve. We stratified MS participants in each cluster as low- and high-risk progressors (LRP and HRP, respectively). When compared against 2-year CDP, our 6 MWGST approach had 71% accuracy and 60% positive predictive value. Compared to the LRP group, those MS participants stratified as HRP (15 out of 62 MS participants), were on average 3.8 years older, had longer MS disease duration and poorer baseline performance on clinical outcomes and PROs scores. Over the subsequent 2 years, only the HRP subgroup showed a significant worsened performance on 6 MW, clinical measures and PROs from baseline.

Conclusion

Baseline 6 MWGST was useful for stratifying MS participants with high or low risks for progression over the subsequent 2 years. Findings represent the first reported single measure to predict MS disease progression with important potential applications in both clinical trials and care in MS.

The rate of force relaxation scaling factor is highly sensitive to detect upper and lower extremity motor deficiencies in mildly affected people with multiple sclerosis

BACKGROUND

The motor symptoms affecting upper and lower extremity functioning in people with multiple sclerosis (PwMS) are considered the cardinal symptoms of multiple sclerosis. There is still a need for outcome measures that can sensitively evaluate these symptoms. We aimed to investigate the sensitivity of the isometric outcomes (maximum force; Fmax, maximum rate of force development; RFDmax, rate of force development scaling factor; RFD-SF, and rate of force relaxation scaling factor; RFR-SF) and standard clinical tests (9-hole peg test; 9HPT and timed 25-feet walk test; T25FW) in detecting the upper and lower extremity motor deficiencies in PwMS and also in a subgroup of mildly affected PwMS whose performance in standard clinical tests were similar to controls.

METHODS

Twenty-nine PwMS (age: 47.9 (8.6) years, relapsing-remitting type, expanded disability status scale: 2.5 (1.5)) and their age- and gender-matched controls completed an identical testing protocol in the upper (grip force muscles) and lower (knee extensors) extremities. For each extremity, we assessed Fmax, RFDmax, RFD-SF, and RFR-SF. Additionally, participants completed standard clinical tests for the evaluation of upper- (9HPT) and lower-extremity (T25FW) function. Comparisons were made between controls and PwMS 1) using all study participants and 2) including only mildly affected PwMS whose performance in standard functional tests was comparable to controls. Independent sample t-tests were utilized to compare groups, with a p-value set at 0.01 to correct for multiple comparisons. P-values and effect sizes were used to evaluate the sensitivity of the outcome measures in detecting group differences.

RESULTS

Our results indicate that most isometric outcomes and standard functional tests were sensitive in detecting motor deficiencies in both upper and lower extremities between groups (p<0.001). Among participants, 16 PwMS in 9HPT and 11 PwMS in T25FW demonstrated performance similar to that of the control group (9HPT: 18.85 (2.20) s vs 17.81 (2.19) s; p=0.19) and (T25FW: 3.60 (0.42) s vs 3.58 (0.29) s; p=0.92). The results of the comparisons between mildly affected PwMS and their controls indicate that RFR-SF is the only sensitive isometric outcome to detect differences between groups in the upper (-8.24 (0.76) 1/s vs -8.93 (0.6) 1/s; p=0.008) and lower extremity (-5.86 (1.13) 1/s vs -7.71 (1.11) 1/s; p<0.001).

CONCLUSION

The rate of force relaxation scaling factor, which assesses the ability to rapidly relax muscle forces after quick contractions, demonstrates high sensitivity in detecting motor deficiencies in PwMS, even when the current standard clinical outcomes fail to detect these differences. Our findings emphasize the importance of future randomized controlled trials focusing on rehabilitative and therapeutic interventions that specifically target muscle force relaxation to enhance motor functioning in PwMS.

The impact of relapse definition and measures of durability on MS clinical trial outcomes

BACKGROUND

Definitions of trial measures are consequential to accurately capturing outcomes and cross-trial comparability, particularly for derivative measures.

OBJECTIVE

Using CombiRx, examine the impact of relapse definition on endpoints and evaluate the durability of progression measures in Relapsing Remitting Multiple Sclerosis (RRMS).

METHODS

CombiRx relapse types were distinguished by the presence or timing of Expanded Disability Status Scale (EDSS) increase. Using the broadest definition of relapse, progression endpoints were assessed in patients without relapses on trial. Durability compared EDSS at study end and time of worsening.

RESULTS

Broadening relapse definition to the most inclusive definition increased annualized relapse rate (ARR) threefold in all arms and decreased progression independent of relapse activity (PIRA), defined as 6-month confirmed disability worsening (6M CDW) without relapse, by 44%. Neither PIRA nor PIA (progression independent of any inflammatory activity) guaranteed durable worsening, with 43% and 40%, respectively, improving by end of study. Multivariate analysis showed two CDW events, not relapse, predicted durability among patients meeting 6M CDW.

CONCLUSIONS

The stringency of relapse definition impacted absolute ARR and composite endpoints in RRMS. Despite the most generous relapse definition, 43% of patients meeting PIRA on trial did not have durable worsening suggesting that relapse definition and durability should be considered to avoid overestimating progression in RRMS trials.

Towards Multimodal Machine Learning Prediction of Individual Cognitive Evolution in Multiple Sclerosis

Multiple sclerosis (MS) manifests heterogeneously among persons suffering from it, making its disease course highly challenging to predict. At present, prognosis mostly relies on biomarkers that are unable to predict disease course on an individual level. Machine learning is a promising technique, both in terms of its ability to combine multimodal data and through the capability of making personalized predictions. However, most investigations on machine learning for prognosis in MS were geared towards predicting physical deterioration, while cognitive deterioration, although prevalent and burdensome, remained largely overlooked. This review aims to boost the field of machine learning for cognitive prognosis in MS by means of an introduction to machine learning and its pitfalls, an overview of important elements for study design, and an overview of the current literature on cognitive prognosis in MS using machine learning. Furthermore, the review discusses new trends in the field of machine learning that might be adopted for future studies in the field.