Integrated Management of Multiple Sclerosis Spasticity and Associated Symptoms Using the Spasticity-Plus Syndrome Concept: Results of a Structured Specialists’ Discussion Using the Workmat® Methodology

Esclerosi múltiple; Espasticitat; CannabinoidesMúltiple esclerosis; Espasticidad; CannabidiolMultiple sclerosis; Muscle spasticity; CannabidiolBackground: Multiple sclerosis (MS) treatment has radically improved over the last years; however, MS symptom management is still challenging. The novel Spasticity-Plus syndrome was conceptualized to frame several spasticity-related symptoms that can be addressed together with broad-spectrum medication, such as certain cannabinoid-based drugs. The aim of this project was to gain insight into Spanish neurologists' clinical experience on MS spasticity and associated symptoms, and to assess the acknowledgment and applicability of the Spasticity-Plus syndrome concept in patients with MS. Methods: Ten online meetings were conducted using the Workmat® methodology to allow structured discussions. Fifty-five Spanish neurologists, experts in MS management, completed and discussed a set of predefined exercises comprising MS symptom assessment and its management in clinical practice, MS symptoms clustering in clinical practice, and their perception of the Spasticity-Plus syndrome concept. This document presents the quantitative and qualitative results of these discussions. Results: The specialists considered that polytherapy is a common concern in MS and that simplifying the management of MS spasticity and associated manifestations could be useful. They generally agreed that MS spasticity should be diagnosed before moderate or severe forms appear. According to the neurologists' clinical experience, symptoms commonly associated with MS spasticity included spasms/cramps (100% of the specialists), pain (85%), bladder dysfunction (62%), bowel dysfunction (42%), sleep disorders (42%), and sexual dysfunction (40%). The multiple correspondence analysis revealed two main symptom clusters: spasticity-spasms/cramps-pain, and ataxia-instability-vertigo. Twelve out of 16 symptoms (75%) were scored >7 in a 0-10 QoL impact scale by the specialists, representing a moderate-high impact. The MS specialists considered that pain, spasticity, spasms/cramps, bladder dysfunction, and depression should be a treatment priority given their frequency and chance of therapeutic success. The neurologists agreed on the usefulness of the new Spasticity-Plus syndrome concept to manage spasticity and associated symptoms together, and their experience with treatments targeting the cannabinoid system was satisfactory. Conclusions: The applicability of the new concept of Spasticity-Plus in MS clinical practice seems possible and may lead to an integrated management of several MS symptoms, thus reducing the treatment burden of disease symptoms.The study was funded by an investigational grant from Almirall S

Sera from Patients with NMOSD Reduce the Differentiation Capacity of Precursor Cells in the Central Nervous System

Introduction: AQP4 (aquaporin-4)–immunoglobulin G (IgG)-mediated neuromyelitis optica spectrum disorder (NMOSD) is an inflammatory demyelinating disease that affects the central nervous system, particularly the spinal cord and optic nerve; remyelination capacity in neuromyelitis optica is yet to be determined, as is the role of AQP4–IgG in cell differentiation. Material and Methods: We included three groups—a group of patients with AQP4–IgG-positive neuromyelitis optica, a healthy group, and a sham group. We analyzed differentiation capacity in cultures of neurospheres from the subventricular zone of mice by adding serum at two different times: early and advanced stages of differentiation. We also analyzed differentiation into different cell lines. Results and Conclusions: The effect of sera from patients with NMOSD on precursor cells differs according to the degree of differentiation, and probably affects oligodendrocyte progenitor cells from NG2 cells to a lesser extent than cells from the subventricular zone; however, the resulting oligodendrocytes may be compromised in terms of maturation and possibly limited in their ability to generate myelin. Furthermore, these cells decrease in number with age. It is very unlikely that the use of drugs favoring the migration and differentiation of oligodendrocyte progenitor cells in multiple sclerosis would be effective in the context of neuromyelitis optica, but cell therapy with oligodendrocyte progenitor cells seems to be a potential alternative

Intranasal Administration of Undifferentiated Oligodendrocyte Lineage Cells as a Potential Approach to Deliver Oligodendrocyte Precursor Cells into Brain

Oligodendrocyte precursor cell (OPC) migration is a mechanism involved in remyelination; these cells migrate from niches in the adult CNS. However, age and disease reduce the pool of OPCs; as a result, the remyelination capacity of the CNS decreases over time. Several experimental studies have introduced OPCs to the brain via direct injection or intrathecal administration. In this study, we used the nose-to brain pathway to deliver oligodendrocyte lineage cells (human oligodendroglioma (HOG) cells), which behave similarly to OPCs in vitro. To this end, we administered GFP-labelled HOG cells intranasally to experimental animals, which were subsequently euthanised at 30 or 60 days. Our results show that the intranasal route is a viable route to the CNS and that HOG cells administered intranasally migrate preferentially to niches of OPCs (clusters created during embryonic development and adult life). Our study provides evidence, albeit limited, that HOG cells either form clusters or adhere to clusters of OPCs in the brains of experimental animals

Detecting Motor Impairment in Early Parkinson’s Disease via Natural Typing Interaction With Keyboards: Validation of the neuroQWERTY Approach in an Uncontrolled At-Home Setting

Background: Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease and one of the most common forms of movement disorder. Although there is no known cure for PD, existing therapies can provide effective symptomatic relief. However, optimal titration is crucial to avoid adverse effects. Today, decision making for PD management is challenging because it relies on subjective clinical evaluations that require a visit to the clinic. This challenge has motivated recent research initiatives to develop tools that can be used by nonspecialists to assess psychomotor impairment. Among these emerging solutions, we recently reported the neuroQWERTY index, a new digital marker able to detect motor impairment in an early PD cohort through the analysis of the key press and release timing data collected during a controlled in-clinic typing task. Objective: The aim of this study was to extend the in-clinic implementation to an at-home implementation by validating the applicability of the neuroQWERTY approach in an uncontrolled at-home setting, using the typing data from subjects’ natural interaction with their laptop to enable remote and unobtrusive assessment of PD signs. Methods: We implemented the data-collection platform and software to enable access and storage of the typing data generated by users while using their computer at home. We recruited a total of 60 participants; of these participants 52 (25 people with Parkinson’s and 27 healthy controls) provided enough data to complete the analysis. Finally, to evaluate whether our in-clinic-built algorithm could be used in an uncontrolled at-home setting, we compared its performance on the data collected during the controlled typing task in the clinic and the results of our method using the data passively collected at home. Results: Despite the randomness and sparsity introduced by the uncontrolled setting, our algorithm performed nearly as well in the at-home data (area under the receiver operating characteristic curve [AUC] of 0.76 and sensitivity/specificity of 0.73/0.69) as it did when used to evaluate the in-clinic data (AUC 0.83 and sensitivity/specificity of 0.77/0.72). Moreover, the keystroke metrics presented a strong correlation between the 2 typing settings, which suggests a minimal influence of the in-clinic typing task in users’ normal typing. Conclusions: The finding that an algorithm trained on data from an in-clinic setting has comparable performance with that tested on data collected through naturalistic at-home computer use reinforces the hypothesis that subtle differences in motor function can be detected from typing behavior. This work represents another step toward an objective, user-convenient, and quasi-continuous monitoring tool for PD

Detecting motor impairment in early Parkinson's disease via natural typing interaction with keyboards: Validation of the neuroQWERTY approach in an uncontrolled at-home setting

Background: Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease and one of the most common forms of movement disorder. Although there is no known cure for PD, existing therapies can provide effective symptomatic relief. However, optimal titration is crucial to avoid adverse effects. Today, decision making for PD management is challenging because it relies on subjective clinical evaluations that require a visit to the clinic. This challenge has motivated recent research initiatives to develop tools that can be used by nonspecialists to assess psychomotor impairment. Among these emerging solutions, we recently reported the neuroQWERTY index, a new digital marker able to detect motor impairment in an early PD cohort through the analysis of the key press and release timing data collected during a controlled in-clinic typing task. Objective: The aim of this study was to extend the in-clinic implementation to an at-home implementation by validating the applicability of the neuroQWERTY approach in an uncontrolled at-home setting, using the typing data from subjects’ natural interaction with their laptop to enable remote and unobtrusive assessment of PD signs. Methods: We implemented the data-collection platform and software to enable access and storage of the typing data generated by users while using their computer at home. We recruited a total of 60 participants; of these participants 52 (25 people with Parkinson’s and 27 healthy controls) provided enough data to complete the analysis. Finally, to evaluate whether our in-clinic-built algorithm could be used in an uncontrolled at-home setting, we compared its performance on the data collected during the controlled typing task in the clinic and the results of our method using the data passively collected at home. Results: Despite the randomness and sparsity introduced by the uncontrolled setting, our algorithm performed nearly as well in the at-home data (area under the receiver operating characteristic curve [AUC] of 0.76 and sensitivity/specificity of 0.73/0.69) as it did when used to evaluate the in-clinic data (AUC 0.83 and sensitivity/specificity of 0.77/0.72). Moreover, the keystroke metrics presented a strong correlation between the 2 typing settings, which suggests a minimal influence of the in-clinic typing task in users’ normal typing. Conclusions: The finding that an algorithm trained on data from an in-clinic setting has comparable performance with that tested on data collected through naturalistic at-home computer use reinforces the hypothesis that subtle differences in motor function can be detected from typing behavior. This work represents another step toward an objective, user-convenient, and quasi-continuous monitoring tool for PD

Cognitive Processes Underlying Verbal Fluency in Multiple Sclerosis

Background: Verbal fluency (VF) has been associated with several cognitive functions, but the cognitive processes underlying verbal fluency deficits in Multiple Sclerosis (MS) are controversial. Further knowledge about VF could be useful in clinical practice, because these tasks are brief, applicable, and reliable in MS patients. In this study, we aimed to evaluate the cognitive processes related to VF and to develop machine-learning algorithms to predict those patients with cognitive deficits using only VF-derived scores. Methods: Two hundred participants with MS were enrolled and examined using a comprehensive neuropsychological battery, including semantic and phonemic fluencies. Automatic linear modeling was used to identify the neuropsychological test predictors of VF scores. Furthermore, machine-learning algorithms (support vector machines, random forest) were developed to predict those patients with cognitive deficits using only VF-derived scores. Results: Neuropsychological tests associated with attention-executive functioning, memory, and language were the main predictors of the different fluency scores. However, the importance of memory was greater in semantic fluency and clustering scores, and executive functioning in phonemic fluency and switching. Machine learning algorithms predicted general cognitive impairment and executive dysfunction, with F1-scores over 67–71%. Conclusions: VF was influenced by many other cognitive processes, mainly including attention-executive functioning, episodic memory, and language. Semantic fluency and clustering were more explained by memory function, while phonemic fluency and switching were more related to executive functioning. Our study supports that the multiple cognitive components underlying VF tasks in MS could serve for screening purposes and the detection of executive dysfunction.Depto. de Psicobiología y Metodología en Ciencias del ComportamientoFac. de PsicologíaTRUEpu

Detection of motor impairment in Parkinson's disease via mobile touchscreen typing

Mobile technology is opening a wide range of opportunities for transforming the standard of care for chronic disorders. Using smartphones as tools for longitudinally tracking symptoms could enable personalization of drug regimens and improve patient monitoring. Parkinson's disease (PD) is an ideal candidate for these tools. At present, evaluation of PD signs requires trained experts to quantify motor impairment in the clinic, limiting the frequency and quality of the information available for understanding the status and progression of the disease. Mobile technology can help clinical decision making by completing the information of motor status between hospital visits. This paper presents an algorithm to detect PD by analyzing the typing activity on smartphones independently of the content of the typed text. We propose a set of touchscreen typing features based on a covariance, skewness, and kurtosis analysis of the timing information of the data to capture PD motor signs. We tested these features, both independently and in a multivariate framework, in a population of 21 PD and 23 control subjects, achieving a sensitivity/specificity of 0.81/0.81 for the best performing feature and 0.73/0.84 for the best multivariate method. The results of the alternating finger-tapping, an established motor test, measured in our cohort are 0.75/0.78. This paper contributes to the development of a home-based, high-compliance, and high-frequency PD motor test by analysis of routine typing on touchscreens

Nose-to-Brain: The Next Step for Stem Cell and Biomaterial Therapy in Neurological Disorders

Neurological disorders are a leading cause of morbidity worldwide, giving rise to a growing need to develop treatments to revert their symptoms. This review highlights the great potential of recent advances in cell therapy for the treatment of neurological disorders. Through the administration of pluripotent or stem cells, this novel therapy may promote neuroprotection, neuroplasticity, and neuroregeneration in lesion areas. The review also addresses the administration of these therapeutic molecules by the intranasal route, a promising, non-conventional route that allows for direct access to the central nervous system without crossing the blood–brain barrier, avoiding potential adverse reactions and enabling the administration of large quantities of therapeutic molecules to the brain. Finally, we focus on the need to use biomaterials, which play an important role as nutrient carriers, scaffolds, and immune modulators in the administration of non-autologous cells. Little research has been conducted into the integration of biomaterials alongside intranasally administered cell therapy, a highly promising approach for the treatment of neurological disorders