MRI Markers and Functional Performance in Patients With CIS and MS: A Cross-Sectional Study

Age-related differences in finger interdependence during complex hand movements

The well-known decrease in finger dexterity during healthy aging leads to a significant reduction in quality of life. Still, the exact patterns of altered finger kinematics of older adults in daily life are fairly unexplored. Finger interdependence is the unintentional comovement of fingers that are not intended to move, and it is known to vary across the lifespan. Nevertheless, the magnitude and direction of age-related differences in finger interdependence are ambiguous across studies and tasks and have not been explored in the context of daily life finger movements. We investigated five different free and daily-life-inspired finger movements of the right, dominant hand as well as a sequential finger tapping task of the thumb against the other fingers, in 17 younger (22-37 yr) and 17 older (62-80 yr) adults using an exoskeleton data glove for data recording. Using inferential statistics, we found that the unintentional comovement of fingers generally decreases with age in all performed daily-life-inspired movements. Finger tapping, however, showed a trend towards higher finger interdependence for older compared with younger adults. Using machine learning, we predicted the age group of a person from finger interdependence features of single movement trials significantly better than chance level for the daily-life-inspired movements, but not for finger tapping. Taken together, we show that for specific tasks, decreased finger interdependence (i.e., less comovement) could potentially act as a marker of human aging that specifically characterizes older adults' complex finger movements in daily life.NEW & NOTEWORTHY Kinematic finger movement data were analyzed with regard to age-related differences. Extensive analyses of complex and daily-life-inspired movements reveal that the direction of age effects is not uniform but task-dependent: Although older adults generally show more finger interdependence than younger adults in a simple finger tapping task, this effect is reversed for daily-life-inspired movement tasks. For these tasks, finger interdependence indices offer potential new markers to predict the age group of an individual using machine learning approaches.

Predicting disease severity in multiple sclerosis using multimodal data and machine learning

BACKGROUND

Multiple sclerosis patients would benefit from machine learning algorithms that integrates clinical, imaging and multimodal biomarkers to define the risk of disease activity.

METHODS

We have analysed a prospective multi-centric cohort of 322 MS patients and 98 healthy controls from four MS centres, collecting disability scales at baseline and 2 years later. Imaging data included brain MRI and optical coherence tomography, and omics included genotyping, cytomics and phosphoproteomic data from peripheral blood mononuclear cells. Predictors of clinical outcomes were searched using Random Forest algorithms. Assessment of the algorithm performance was conducted in an independent prospective cohort of 271 MS patients from a single centre.

RESULTS

We found algorithms for predicting confirmed disability accumulation for the different scales, no evidence of disease activity (NEDA), onset of immunotherapy and the escalation from low- to high-efficacy therapy with intermediate to high-accuracy. This accuracy was achieved for most of the predictors using clinical data alone or in combination with imaging data. Still, in some cases, the addition of omics data slightly increased algorithm performance. Accuracies were comparable in both cohorts.

CONCLUSION

Combining clinical, imaging and omics data with machine learning helps identify MS patients at risk of disability worsening.

Multiscale networks in multiple sclerosis

Complex diseases such as Multiple Sclerosis (MS) cover a wide range of biological scales, from genes and proteins to cells and tissues, up to the full organism. In fact, any phenotype for an organism is dictated by the interplay among these scales. We conducted a multilayer network analysis and deep phenotyping with multi-omics data (genomics, phosphoproteomics and cytomics), brain and retinal imaging, and clinical data, obtained from a multicenter prospective cohort of 328 patients and 90 healthy controls. Multilayer networks were constructed using mutual information for topological analysis, and Boolean simulations were constructed using Pearson correlation to identified paths within and among all layers. The path more commonly found from the Boolean simulations connects protein MK03, with total T cells, the thickness of the retinal nerve fiber layer (RNFL), and the walking speed. This path contains nodes involved in protein phosphorylation, glial cell differentiation, and regulation of stress-activated MAPK cascade, among others. Specific paths identified were subsequently analyzed by flow cytometry at the single-cell level. Combinations of several proteins (GSK3AB, HSBP1 or RS6) and immune cells (Th17, Th1 non-classic, CD8, CD8 Treg, CD56 neg, and B memory) were part of the paths explaining the clinical phenotype. The advantage of the path identified from the Boolean simulations is that it connects information about these known biological pathways with the layers at higher scales (retina damage and disability). Overall, the identified paths provide a means to connect the molecular aspects of MS with the overall phenotype.

Potential biological contributers to the sex difference in multiple sclerosis progression

Multiple sclerosis (MS) is an immune-mediated disease that targets the myelin sheath of central nervous system (CNS) neurons leading to axon injury, neuronal death, and neurological progression. Though women are more highly susceptible to developing MS, men that develop this disease exhibit greater cognitive impairment and accumulate disability more rapidly than women. Magnetic resonance imaging and pathology studies have revealed that the greater neurological progression seen in males correlates with chronic immune activation and increased iron accumulation at the rims of chronic white matter lesions as well as more intensive whole brain and grey matter atrophy and axon loss. Studies in humans and in animal models of MS suggest that male aged microglia do not have a higher propensity for inflammation, but may become more re-active at the rim of white matter lesions as a result of the presence of pro-inflammatory T cells, greater astrocyte activation or iron release from oligodendrocytes in the males. There is also evidence that remyelination is more efficient in aged female than aged male rodents and that male neurons are more susceptible to oxidative and nitrosative stress. Both sex chromosome complement and sex hormones contribute to these sex differences in biology.

Multiple sclerosis impairment scale and brain MRI in secondary progressive multiple sclerosis

OBJECTIVE

To examine the Multiple Sclerosis Impairment Scale (MSIS) in secondary progressive MS (SPMS) in relation to the Expanded Disability Status Scale (EDSS), magnetic resonance imaging (MRI) outcomes, and mobility.

METHODS

In this observational single-center study, 68 secondary progressive multiple sclerosis (SPMS) patients were examined by MSIS, EDSS, functional mobility tests of upper/lower extremities, and multimodal MRI. Participants had EDSS ≥3.5, a decline in daily activities over the last year unrelated to relapses, and/or 6-month confirmed disability progression.

RESULTS

Mean disease duration was 23.1 ± 8.3 years and mean age 54.4 ± 8.1 years. MSIS, EDSS, and their corresponding motor, cerebellar, and sensory subscores correlated (p < .0001). Motor subscores of MSIS correlated stronger with Timed-25-Foot-Walk (T25FW) than pyramidal functional system score (FSS) (p = .03), but EDSS had a stronger correlation to T25FW than the total MSIS score (p = .01). MSIS cerebellar subscore correlated stronger with 9-Hole Peg Test (9-HPT) than cerebellar FSS (p = .04). The sensory MSIS subscore also showed correlation with 9-HPT in contrast to sensory FSS (p = .006). MSIS subscores had stronger correlations with MRI volumetry measures than FSS scores (lesion volume and putamen, thalamus, corpus callosum volumetry, p = .0001-0.0017).

CONCLUSION

In patients with SPMS, MSIS correlated with functional motor tests. MSIS showed stronger correlations with atrophy of central nervous system areas, and may be more sensitive to scale cerebellar and sensory function than EDSS.

MRI-based thalamic volumetry in multiple sclerosis using FSL-FIRST: Systematic assessment of common error modes

BACKGROUND AND PURPOSE

FSL's FMRIB's Integrated Registration and Segmentation Tool (FSL-FIRST) is a widely used and well-validated tool. Automated thalamic segmentation is a common application and an important longitudinal measure for multiple sclerosis (MS). However, FSL-FIRST's algorithm is based on shape models derived from non-MS groups. As such, the present study sought to systematically assess common thalamic segmentation errors made by FSL-FIRST on MRIs from people with multiple sclerosis (PwMS).

METHODS

FSL-FIRST was applied to generate thalamic segmentation masks for 890 MR images in PwMS. Images and masks were reviewed systematically to classify and quantify errors, as well as associated anatomical variations and MRI abnormalities. For cases with overt errors (n = 362), thalamic masks were corrected and quantitative volumetric differences were calculated.

RESULTS

In the entire quantitative volumetric group, the mean volumetric error of FSL-FIRST was 2.74% (0.360 ml): among only corrected cases, the mean volumetric error was 6.79% (0.894 ml). The average percent volumetric error associated with seven error types, two anatomical variants, and motions artifacts are reported. Additional analyses showed that the presence of motion artifacts or anatomical variations significantly increased the probability of error (χ²  = 18.14, p < .01 and χ²  = 64.89, p < .001, respectively). Finally, thalamus volume error was negatively associated with degree of atrophy, such that smaller thalami were systematically overestimated (r = -.28, p < .001).

CONCLUSIONS

In PwMS, FSL-FIRST thalamic segmentation miscalculates thalamic volumetry in a predictable fashion, and may be biased to overestimate highly atrophic thalami. As such, it is recommended that segmentations be reviewed and corrected manually when appropriate for specific studies.

Sex differences in brain atrophy in multiple sclerosis

BACKGROUND

Women are more susceptible to multiple sclerosis (MS) than men by a ratio of approximately 3:1. However, being male is a risk factor for worse disability progression. Inflammatory genes have been linked to susceptibility, while neurodegeneration underlies disability progression. Thus, there appears to be a differential effect of sex on inflammation versus neurodegeneration. Further, gray matter (GM) atrophy is not uniform across the brain in MS, but instead shows regional variation. Here, we study sex differences in neurodegeneration by comparing regional GM atrophy in a cohort of men and women with MS versus their respective age- and sex-matched healthy controls.

METHODS

Voxel-based morphometry (VBM), deep GM substructure volumetry, and cortical thinning were used to examine regional GM atrophy.

RESULTS

VBM analysis showed deep GM atrophy in the thalamic area in both men and women with MS, whereas men had additional atrophy in the putamen as well as in localized cortical regions. Volumetry confirmed deep GM loss, while localized cortical thinning confirmed GM loss in the cerebral cortex. Further, MS males exhibited worse performance on the 9-hole peg test (9HPT) than MS females. We observed a strong correlation between thalamic volume and 9HPT performance in MS males, but not in MS females.

CONCLUSION

More regional GM atrophy was observed in men with MS than women with MS, consistent with previous observations that male sex is a risk factor for worse disease progression.

Visualizing the Central Nervous System: Imaging Tools for Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders

Multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) are autoimmune central nervous system conditions with increasing incidence and prevalence. While MS is the most frequent inflammatory CNS disorder in young adults, NMOSD is a rare disease, that is pathogenetically distinct from MS, and accounts for approximately 1% of demyelinating disorders, with the relative proportion within the demyelinating CNS diseases varying widely among different races and regions. Most immunomodulatory drugs used in MS are inefficacious or even harmful in NMOSD, emphasizing the need for a timely and accurate diagnosis and distinction from MS. Despite distinct immunopathology and differences in disease course and severity there might be considerable overlap in clinical and imaging findings, posing a diagnostic challenge for managing neurologists. Differential diagnosis is facilitated by positive serology for AQP4-antibodies (AQP4-ab) in NMOSD, but might be difficult in seronegative cases. Imaging of the brain, optic nerve, retina and spinal cord is of paramount importance when managing patients with autoimmune CNS conditions. Once a diagnosis has been established, imaging techniques are often deployed at regular intervals over the disease course as surrogate measures for disease activity and progression and to surveil treatment effects. While the application of some imaging modalities for monitoring of disease course was established decades ago in MS, the situation is unclear in NMOSD where work on longitudinal imaging findings and their association with clinical disability is scant. Moreover, as long-term disability is mostly attack-related in NMOSD and does not stem from insidious progression as in MS, regular follow-up imaging might not be useful in the absence of clinical events. However, with accumulating evidence for covert tissue alteration in NMOSD and with the advent of approved immunotherapies the role of imaging in the management of NMOSD may be reconsidered. By contrast, MS management still faces the challenge of implementing imaging techniques that are capable of monitoring progressive tissue loss in clinical trials and cohort studies into treatment algorithms for individual patients. This article reviews the current status of imaging research in MS and NMOSD with an emphasis on emerging modalities that have the potential to be implemented in clinical practice.

The Impact of Intracortical Lesions on Volumes of Subcortical Structures in Multiple Sclerosis

BACKGROUND AND PURPOSE

Recent studies showed thalamic atrophy in the early stages of MS. We investigated the impact of intracortical lesions on the volumes of subcortical structures (especially the thalamus) compared with other lesions in MS.

MATERIALS AND METHODS

Seventy-one patients with MS were included. The volumes of intracortical lesions and white matter lesions were identified on double inversion recovery and FLAIR, respectively, by using 3D Slicer. Volumes of white matter T1 hypointensities and subcortical gray matter, thalamus, caudate, putamen, and pallidum volumes were calculated using FreeSurfer. Age, MS duration, and the Expanded Disability Status Scale score were assessed.

RESULTS

Patients with intracortical lesions were older (P = .003), had longer disease duration (P < .001), and higher Expanded Disability Status Scale scores (P = .02). The presence of intracortical lesions was associated with a significant decrease of subcortical gray matter volume (P = .02). In our multiple regression model, intracortical lesion volume was the only predictor of thalamic volume (R ² = 0.4, b* = -0.28, P = .03) independent of white matter lesion volume and T1 hypointensity volume. White matter lesion volume showed an impact on subcortical gray matter volume in patients with relapsing-remitting MS (P = .04) and those with disease duration of <5 years (P = .04) and on thalamic volume in patients with Expanded Disability Status Scale scores of <4.0 (P = .01). By contrast, intracortical lesion volume showed an impact on subcortical gray matter and thalamic volumes in the secondary-progressive MS subgroup (P = .02 and P < .001) in patients with a long-standing disease course (P < .001 and P = .001) and more profound disability (P < .001 and P < .001).

CONCLUSIONS

Thalamic atrophy was explained better by intracortical lesions than by white matter lesion and T1 hypointensity volumes, especially in patients with more profound disability.

Technology-enabled comprehensive characterization of multiple sclerosis in clinical practice

BACKGROUND

Objective and longitudinal measurements of disability in patients with multiple sclerosis (MS) are desired in order to monitor disease status and response to disease-modifying and symptomatic therapies. Technology-enabled comprehensive assessment of MS patients, including neuroperformance tests (NPTs), patient-reported outcome measures (PROMs), and MRI, is incorporated into clinical care at our center. The relationships of each NPT with PROMs and MRI measures in a real-world setting are incompletely studied, particularly in larger datasets.

OBJECTIVES

To demonstrate the utility of comprehensive neurological assessment and determine the association between NPTs, PROMs, and quantitative MRI measures in a large MS clinical cohort.

METHODS

NPTs (processing speed [PST], contrast sensitivity [CST], manual dexterity [MDT], and walking speed [WST]) and physical disability-related PROMs (Quality of Life in Neurological Disorders [Neuro-QoL], Patient Determined Disease Steps [PDDS], and Patient-Reported Outcomes Measurement Information System Global-10 [PROMIS-10] physical) were collected as part of routine clinical care. Fully-automated MRI analysis calculated T2-lesion volume (T2LV), whole brain fraction (WBF), thalamic volume (TV), and cervical spinal cord cross-sectional area (CA) for brain MRIs completed within 3 months of a clinic visit during which NPTs and PROMs were assessed. Spearman's rank correlation coefficients evaluated the cross-sectional associations of NPTs with PROMs and MRI measures. Linear regression was utilized to determine which combination of clinical characteristics, patient demographics, MRI measures, and PROMs best cross-sectionally explained each NPT result.

RESULTS

997 unique patients (age 47.7 ± 11.4 years, 71.8% female) who underwent assessments over a 2-year period were included. Correlations among NPTs and PROMs were moderate. PST correlations were strongest for Neuro-QoL upper extremity (NQ-UE) (Spearman's rho = 0.43) and lower extremity (NQ-LE) (0.47). CST correlations were strongest for NQ-UE (0.33), NQ-LE (0.36), and PDDS (-0.31). MDT correlations were strongest for NQ-UE (-0.53), NQ-LE (-0.54), and PDDS (0.53). WST correlations were strongest for PDDS (0.64) and NQ-LE (-0.65). NPTs also had moderate correlations with MRI metrics, the strongest of which were observed with PST (with T2LV (-0.44) and WBF (0.49)). Spearman's rho for other NPT-MRI correlations ranged from 0.23 to 0.36. Linear regression identified age, disease duration, PROMIS-10 physical, NQ-UE, NQ-LE, T2LV and WBF as significant cross-sectional explanatory variables for PST (adjusted R²=0.46). For CST, significant variables included age and NQ-LE (adjusted R² = 0.30). For MDT, significant variables included PDDS, PROMIS-10 physical, NQ-UE, NQ-LE, T2LV, and WBF (adjusted R²=0.37). For WST, significant variables included sex, PDDS, NQ-LE, T2LV, and CA (adjusted R²=0.39).

CONCLUSIONS

Impaired performance on NPTs correlated with worse physical disability-related PROMs and MRI disease severity, but the strongest cross-sectional explanatory variables for each NPT component varied. This study supports the use of comprehensive, objective quantification of MS status in clinical and research settings. Future longitudinal analyses can determine predictors of treatment response and disability worsening.

Transcranial Magnetic Stimulation as a Potential Biomarker in Multiple Sclerosis: A Systematic Review with Recommendations for Future Research

Multiple sclerosis (MS) is a demyelinating disorder of the central nervous system. Disease progression is variable and unpredictable, warranting the development of biomarkers of disease status. Transcranial magnetic stimulation (TMS) is a noninvasive method used to study the human motor system, which has shown potential in MS research. However, few reviews have summarized the use of TMS combined with clinical measures of MS and no work has comprehensively assessed study quality. This review explored the viability of TMS as a biomarker in studies of MS examining disease severity, cognitive impairment, motor impairment, or fatigue. Methodological quality and risk of bias were evaluated in studies meeting selection criteria. After screening 1603 records, 30 were included for review. All studies showed high risk of bias, attributed largely to issues surrounding sample size justification, experimenter blinding, and failure to account for key potential confounding variables. Central motor conduction time and motor-evoked potentials were the most commonly used TMS techniques and showed relationships with disease severity, motor impairment, and fatigue. Short-latency afferent inhibition was the only outcome related to cognitive impairment. Although there is insufficient evidence for TMS in clinical assessments of MS, this review serves as a template to inform future research.

Drug Treatment of Clinically Isolated Syndrome

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) that leads to inflammation, demyelination and ultimately axonal degeneration. In most cases, it is preceded by its precursor, clinically isolated syndrome (CIS) with conversion rates to clinically definite MS (CDMS) of roughly 20-75%. Neurologists are therefore faced with the challenge of initiating a disease-modifying therapy (DMT) as early as possible to favorably influence the course of the disease. During the past 20 years, a multitude of drugs have been incorporated into our therapeutic armamentarium for MS and CIS. Choosing the right drug for an individual patient is complex and should be based not only on the drug's overall efficacy to prevent disease progression but also its specific adverse reaction profile, the severity of individual disease courses and, finally, patient compliance in order to adequately weigh associated risks and benefits. Here, we review the available data on the efficacy, safety and tolerability of DMTs tested for CIS and discuss their value regarding a delay of progression to CDMS.