Differential diagnosis of multiple sclerosis and other inflammatory CNS diseases

Demyelination detection in CSF based on electrochemical monitoring of myelin basic protein in comparison between Apta vs. Immuno sensing strategies

Multiple sclerosis (MS) is a recurrent inflammatory, demyelinating disease of the white matter in central nervous system (CNS). The number of MS patients is increasing, but the diagnostic process is still quite difficult, costly and requires combination of several methods. Myelin basic protein (MBP) makes up to 30 % of the myelin in CNS. It is known that MBP is released into the cerebrospinal fluid (CSF) as MS bioindicator. Herein, myelin specific DNA aptamer earlier developed for possible therapeutic purposes and anti-MBP antibody were applied as bioreceptors for MBP recognition on the same nanomodified sensor surfaces and their performances were compared. Biosensors were developed by using graphene oxide (GO) nanoparticles integrated onto pencil graphite electrodes (PGE) and bioreceptor molecules immobilized to create a bioactive layer for MBP binding. The measurements were run with electrochemical impedance spectroscopy (EIS). Selectivity of the biosensors was evaluated using human serum albumin (HSA). After optimization of binding parameters, biosensors were validated in artificial CSF. It was shown that LJM-5708 based aptasensor had LOD 0.65 ng/mL that was comparable to immunosensor LOD (0.36 ng/mL) in artificial CSF and showed its applicability in the clinical concentration range between 1 and 128 ng/mL.

Unlocking new Frontiers: The cellular and molecular impact of extracorporeal shock wave therapy (ESWT) on central nervous system (CNS) disorders and peripheral nerve injuries (PNI)

Neurological disorders encompassing both central nervous system (CNS) diseases and peripheral nerve injuries (PNI), represent significant challenges in modern clinical practice. Conditions such as stroke, spinal cord injuries, and carpal tunnel syndrome can cause debilitating impairments, leading to reduced quality of life and placing a heavy burden on healthcare systems. Current treatment strategies, including pharmacological interventions and surgical procedures, often yield limited results, and many patients experience suboptimal outcomes or treatment-associated risks. In light of these limitations, there is a growing interest in exploring non-invasive therapeutic alternatives. Among these, extracorporeal shock wave therapy (ESWT) has eme rged as a promising modality, demonstrating efficacy in musculoskeletal conditions and gaining attention for its potential role in neurological disorders. This manuscript aims to provide a comprehensive overview of the cellular and molecular mechanisms underlying ESWT, focusing on its therapeutic applications in CNS diseases and PNI, thereby shedding light on its potential to revolutionize the treatment landscape for neurological conditions.

A density-based MS disease diagnosis model using the capuchin search algorithm and an ensemble of deep neural networks

Multiple sclerosis (MS) is a severe brain disease that permanently destroys brain cells, impacting vision, balance, muscle control, and daily activity. This research employs a weighted combination of deep neural networks and optimization techniques for MS disease diagnosis. This method uses slices of magnetic resonance imaging (MRI) images as input. Then, after the pre-processing operation, the process of segmentation and identification of the region of interest (ROI) is performed using a combination of the fuzzy c-means (FCM) algorithm and the capuchin search algorithm (CapSA) algorithm. When the target view is detected, the features of each ROI are extracted through three techniques: local binary pattern (LBP), multi-linear principal component analysis (MPCA), and gray level co-occurrence matrix (GLCM). Each of these features is then processed by a deep neural network. In each deep neural network, the CapSA algorithm is used to determine the optimal topology structure and adjust the weight vector of the neural network. This means that in this process, the vector and topology of the deep neural network are adjusted using the CapSA algorithm in such a way that the training error is minimized. Finally, after creating the trained models, the weighted combination of the outputs of these three models is used for the final diagnosis. The implementation results showed that our method was successful in achieving 100% precision compared to other comparative methods. Also, in the average accuracy criterion, it showed a performance of 99.51%, which shows the high performance of our method in diagnosing patients.

Utility of Oligoclonal Band Testing in Differentiating Immune-Mediated From Infectious Central Nervous System Disorders

OBJECTIVE

This study aimed to evaluate the clinical utility of oligoclonal bands (OCB) in differentiating between immune and infectious diseases of the central nervous system (CNS).

METHODS

The study enrolled patients hospitalized with suspected autoimmune or infectious CNS disorders between 2021 and 2023. Patients were categorized into diagnostic groups: multiple sclerosis (MS), neuromyelitis optica spectrum disorders (NMOSD), autoimmune encephalitis (AE), and viral encephalitis (VE). Relevant clinical and laboratory data were collected and subjected to comparative analysis.

RESULTS

Comparative analysis among the 4 groups revealed that the immunoglobulin G (IgG) index of patients in the MS group was significantly higher than that of patients in the NMOSD and VE groups (P < 0.05). The 24-hour intrathecal synthesis rate of IgG also differed significantly between the MS and NMOSD groups, the NMOSD and AE groups, as well as the AE and VE groups (P < 0.05). The positive rate of OCB was significantly higher in the MS group than in the other 3 groups (P < 0.05). Functional abilities, measured by scores of the Modified Rankin Scale (mRS) and the Expanded Disability Status Scale (EDSS), were higher in the immune group than in the infection group at 1-week, 1-month, 6-month, and 1-year post-treatment. Among patients with immune diseases, those who were OCB-positive showed significantly smaller ΔmRS and ΔEDSS at 1-month, 6-month, and 1-year post-treatment compared with patients who were OCB-negative (P < 0.05).

CONCLUSION

The IgG index and 24-hour intrathecal synthesis rate of IgG served as valuable early indicators for distinguishing between CNS immune and infectious diseases. Positive OCB findings were more common in patients with MS and often associated with poor prognosis and increased risk of disease recurrence.

Advancements in Single-Cell RNA Sequencing and Spatial Transcriptomics for Central Nervous System Disease

The incidence of central nervous system (CNS) disease has persistently increased over the last several years. There is an urgent need for effective methods to improve the cure rates of CNS disease. However, the precise molecular basis underlying the development and progression of major CNS diseases remains elusive. A complete molecular map will contribute to research on CNS disease treatment strategies. Emerging technologies such as single-cell RNA sequencing (scRNA-seq) and Spatial Transcriptomics (ST) are potent tools for exploring the molecular complexity, cell heterogeneity, and functional specificity of CNS disease. scRNA-seq and ST can provide insights into the disease at cellular and spatial transcription levels. This review presents a survey of scRNA-seq and ST studies on CNS diseases, such as chronic neurodegenerative diseases, acute CNS injuries, and others. These studies offer novel perspectives in treating and diagnosing CNS diseases by discovering new cell types or subtypes associated with the disease, proposing new pathophysiological mechanisms, uncovering novel therapeutic targets, and identifying putative biomarkers.

Bee venom as a promising therapeutic strategy in central nervous system diseases

Central nervous system (CNS) disorders are one of the leading health problems today, accounting for a large proportion of global morbidity and mortality. Most these disorders are characterized by high levels of oxidative stress and intense inflammatory responses in degenerated neuronal tissues. While extensive research has been conducted on CNS diseases, but few breakthroughs have been made in treatment methods. To date, there are no disease-modifying drugs available for CNS treatment, underscoring the urgent need for finding effective medications. Bee venom (BV), which is produced by honeybee workers' stingers, has been a subject of interest and study across various cultures. Over the past few decades, extensive research has focused on BV and its therapeutic potentials. BV consists a variety of substances, mainly proteins and peptides like melittin and phospholipase A2 (PLA2). Research has proven that BV is effective in various medical conditions, including pain, arthritis and inflammation and CNS disorders such as Multiple sclerosis, Alzheimer's disease and Parkinson's disease. This review provides a comprehensive overview of the existing knowledge concerning the therapeutic effects of BV and its primary compounds on various CNS diseases. Additionally, we aim to shed light on the potential cellular and molecular mechanisms underlying these effects.

Sick leave in the prodromal phase of multiple sclerosis and its association with diagnostic delay: A short report

The prodromal features of multiple sclerosis (MS) are non-specific and are prevalent in the general population. Several studies indicate an increased use of healthcare resources by individuals with MS in the years preceding their diagnosis, suggesting a trend of deteriorating health prior to the clinical manifestation of MS. This study aimed to capture the possible associations of sick leave with the timing of the diagnosis of MS. Our findings suggest that sick leave with neurological diagnoses - excluding MS, and other diagnoses during the year before MS onset is associated with a shorter time to MS diagnosis.

Impact of Coping Strategies on Health-Related Quality of Life in Young Adults with Multiple Sclerosis

Multiple sclerosis (MS) is a chronic and progressive neurological disease that affects the central nervous system, resulting in a wide spectrum of cognitive, emotional, and physical deficits. The progressive course of MS poses significant challenges to patients and has a profound impact on health-related quality of life (HRQoL). The style of coping adopted plays a critical role in determining how individuals with MS adapt to and face the challenges of the disease and their overall well-being. This paper aims to examine the impact of coping strategies on HRQoL in young adults un-/minimally impaired (<5 years, EDSS ≤ 2.5) by MS (age 18-35 years). This retrospective cross-sectional cohort study included 98 young adults (33 males and 65 females) with relapsing-remitting MS who underwent neurological assessment using the Expanded Disability Status Scale. Participants completed the Italian version of the Multiple Sclerosis QoL-54 (MSQoL-54), which provides a physical and mental health score, and the Coping Orientation to Problems Experienced Inventory (Brief-COPE). The results showed a significant relationship between COPE scores and physical and mental health. Subjects affected by MS who tend to use more frequent coping strategies such as active planning, personal growth, and acceptance showed a better overall well-being and quality of life. These findings are relevant to clinical practice given the need to understand the coping variable to improve HRQoL. Understanding these relationships is crucial for developing effective interventions to enhance the well-being of MS subjects.

Acute disseminated encephalomyelitis in a young patient: A case report

The diagnosis of acute disseminated encephalomyelitis (ADEM) is challenging due to the existence of other medical conditions that mimic its symptoms and the lack of precise biomarkers. Timely diagnosis is essential for commencing an appropriate treatment, which enhances the clinical trajectory and long-term prognosis. The purpose of the present study was to emphasize significant concerns, specifically for neurologists and radiologists, due to the difficulties involved in identifying this disorder. Neurologists must have an extensive understanding of the clinical manifestations and constraints of current diagnostic tests. Furthermore, this understanding is equally essential for radiologists, as it serves as the foundation for precise diagnostic interpretations derived from imaging findings. The intricate nature of neurological disorders frequently necessitates a cooperative effort between neurologists and radiologists to guarantee precise diagnosis and efficient therapy strategizing. The present study discusses a case of a male patient who was diagnosed with ADEM based on clinical, biological and imaging evaluations.

Diagnosis of multiple sclerosis using optical coherence tomography supported by explainable artificial intelligence

BACKGROUND/OBJECTIVES

Study of retinal structure based on optical coherence tomography (OCT) data can facilitate early diagnosis of relapsing-remitting multiple sclerosis (RRMS). Although artificial intelligence can provide highly reliable diagnoses, the results obtained must be explainable.

SUBJECTS/METHODS

The study included 79 recently diagnosed RRMS patients and 69 age matched healthy control subjects. Thickness (Avg) and inter-eye difference (Diff) features are obtained in 4 retinal layers using the posterior pole protocol. Each layer is divided into six analysis zones. The Support Vector Machine plus Recursive Feature Elimination with Leave-One-Out Cross Validation (SVM-RFE-LOOCV) approach is used to find the subset of features that reduces dimensionality and optimises the performance of the classifier.

RESULTS

SVM-RFE-LOOCV was used to identify OCT features with greatest capacity for early diagnosis, determining the area of the papillomacular bundle to be the most influential. A correlation was observed between loss of layer thickness and increase in functional disability. There was also greater functional deterioration in patients with greater asymmetry between left and right eyes. The classifier based on the top-ranked features obtained sensitivity = 0.86 and specificity = 0.90.

CONCLUSIONS

There was consistency between the features identified as relevant by the SVM-RFE-LOOCV approach and the retinotopic distribution of the retinal nerve fibres and the optic nerve head. This simple method contributes to implementation of an assisted diagnosis system and its accuracy exceeds that achieved with magnetic resonance imaging of the central nervous system, the current gold standard. This paper provides novel insights into RRMS affectation of the neuroretina.

Advanced MRI Techniques: Diagnosis and Follow-Up of Multiple Sclerosis

Brain and spinal cord imaging plays a pivotal role in aiding clinicians with the diagnosis and monitoring of multiple sclerosis. Nevertheless, the significance of magnetic resonance imaging in MS extends beyond its clinical utility. Advanced imaging modalities have facilitated the in vivo detection of various components of MS pathogenesis, and, in recent years, MRI biomarkers have been utilized to assess the response of patients with relapsing-remitting MS to the available treatments. Similarly, MRI indicators of neurodegeneration demonstrate potential as primary and secondary endpoints in clinical trials targeting progressive phenotypes. This review aims to provide an overview of the latest advancements in brain and spinal cord neuroimaging in MS.

Artificial Intelligence for Multiple Sclerosis Management Using Retinal Images: Pearl, Peaks, and Pitfalls

Multiple sclerosis (MS) is a complex autoimmune disease characterized by inflammatory processes, demyelination, neurodegeneration, and axonal damage within the central nervous system (CNS). Retinal imaging, particularly Optical coherence tomography (OCT), has emerged as a crucial tool for investigating MS-related retinal injury. The integration of artificial intelligence(AI) has shown promise in enhancing OCT analysis for MS. Researchers are actively utilizing AI algorithms to accurately detect and classify MS-related abnormalities, leading to improved efficiency in diagnosis, monitoring, and personalized treatment planning. The prognostic value of AI in predicting MS disease progression has garnered substantial attention. Machine learning (ML) and deep learning (DL) algorithms can analyze longitudinal OCT data to forecast the course of the disease, providing critical information for personalized treatment planning and improved patient outcomes. Early detection of high-risk patients allows for targeted interventions to mitigate disability progression effectively. As such, AI-driven approaches yielded remarkable abilities in classifying distinct MS subtypes based on retinal features, aiding in disease characterization and guiding tailored therapeutic strategies. Additionally, these algorithms have enhanced the accuracy and efficiency of OCT image segmentation, streamlined diagnostic processes, and reduced human error. This study reviews the current research studies on the integration of AI,including ML and DL algorithms, with OCT in the context of MS. It examines the advancements, challenges, potential prospects, and ethical concerns of AI-powered techniques in enhancing MS diagnosis, monitoring disease progression, revolutionizing patient care, the development of patient screening tools, and supported clinical decision-making based on OCT images.

Transcranial magnetic stimulation enhances the specificity of multiple sclerosis diagnostic criteria: a critical narrative review

Background

Multiple sclerosis (MS) is an immune-mediated neurodegenerative disease that involves attacks of inflammatory demyelination and axonal damage, with variable but continuous disability accumulation. Transcranial magnetic stimulation (TMS) is a noninvasive method to characterize conduction loss and axonal damage in the corticospinal tract. TMS as a technique provides indices of corticospinal tract function that may serve as putative MS biomarkers. To date, no reviews have directly addressed the diagnostic performance of TMS in MS. The authors aimed to conduct a critical narrative review on the diagnostic performance of TMS in MS.

Methods

The authors searched the Embase, PubMed, Scopus, and Web of Science databases for studies that reported the sensitivity and/or specificity of any reported TMS technique compared to established clinical MS diagnostic criteria. Studies were summarized and critically appraised for their quality and validity.

Results

Seventeen of 1,073 records were included for data extraction and critical appraisal. Markers of demyelination and axonal damage-most notably, central motor conduction time (CMCT)-were specific, but not sensitive, for MS. Thirteen (76%), two (12%), and two (12%) studies exhibited high, unclear, and low risk of bias, respectively. No study demonstrated validity for TMS techniques as diagnostic biomarkers in MS.

Conclusions

CMCT has the potential to: (1) enhance the specificity of clinical MS diagnostic criteria by "ruling in" true-positives, or (2) revise a diagnosis from relapsing to progressive forms of MS. However, there is presently insufficient high-quality evidence to recommend any TMS technique in the diagnostic algorithm for MS.

Potential Metabolite Biomarkers of Multiple Sclerosis from Multiple Biofluids

Multiple sclerosis (MS) is a chronic and progressive neurological disorder without a cure, but early intervention can slow disease progression and improve the quality of life for MS patients. Obtaining an accurate diagnosis for MS is an arduous and error-prone task that requires a combination of a detailed medical history, a comprehensive neurological exam, clinical tests such as magnetic resonance imaging, and the exclusion of other possible diseases. A simple and definitive biofluid test for MS does not exist, but is highly desirable. To address this need, we employed NMR-based metabolomics to identify potentially unique metabolite biomarkers of MS from a cohort of age and sex-matched samples of cerebrospinal fluid (CSF), serum, and urine from 206 progressive MS (PMS) patients, 46 relapsing-remitting MS (RRMS) patients, and 99 healthy volunteers without a MS diagnosis. We identified 32 metabolites in CSF that varied between the control and PMS patients. Utilizing patient-matched serum samples, we were able to further identify 31 serum metabolites that may serve as biomarkers for PMS patients. Lastly, we identified 14 urine metabolites associated with PMS. All potential biomarkers are associated with metabolic processes linked to the pathology of MS, such as demyelination and neuronal damage. Four metabolites with identical profiles across all three biofluids were discovered, which demonstrate their potential value as cross-biofluid markers of PMS. We further present a case for using metabolic profiles from PMS patients to delineate biomarkers of RRMS. Specifically, three metabolites exhibited a variation from healthy volunteers without MS through RRMS and PMS patients. The consistency of metabolite changes across multiple biofluids, combined with the reliability of a receiver operating characteristic classification, may provide a rapid diagnostic test for MS.

Exploring Spinal Cord Changes in Multiple Sclerosis Patients Using MRI

Multiple sclerosis (MS) is an autoimmune disease affecting the central nervous system (CNS). The diagnosis of MS is based on clinical signs and symptoms as well as findings in magnetic resonance imaging (MRI) sequences by demonstrating the spatial and temporal dispersion of white matter lesions, which are thought to be typical of MS in distribution, shape, extent, and signal abnormalities. Spinal cord MRI can identify asymptomatic lesions and rule out malignancies or spinal stenosis in patients for whom brain imaging is not helpful in making an MS diagnosis. This study examines the MRI features of Saudi Arabian patients clinically proven to have MS with typical lesions exclusively evident in the spinal cord. This retrospective cross-sectional study was carried out in 151 patients who are confirmed cases of MS based on clinical findings and MRI results. Patients' MRI data were reviewed from the picture archiving and communication system (PACS). The study revealed that MS incidence was higher in females than males and that the number of people diagnosed with MS increased in middle age. Cervical cord plaques and cervical cord curve straightening were the most frequent changes (67% and 56%, respectively), indicating that MRI can complement and even replace clinical data in MS diagnosis, leading to earlier, more precise diagnoses and speedier starts to treatment.

Psoriasis and risk of central neurological disorders in European populations: A mendelian randomization analysis

Background

People with psoriasis are at a higher risk for having central neurological problems, according to previous studies; however, it is unclear if there is a genetic link between the risk of developing psoriasis and developing central neurological disorders. In this study, the possible link between genetically predisposed psoriasis and the risk of common central nervous system disorders was comprehensively investigated.

Methods

There was no overlap in the participant populations between the psoriasis and central neurological disorders genome-wide association studies, which provide the genetic resources. Inverse variance weighting, often used as Mendelian randomization (MR) analysis, is the main method. To guarantee the accuracy of our findings, a number of sensitivity studies were carried out.

Results

MR analysis revealed that although psoriasis was reported to increase the risk of Parkinson's disease (OR = 4.42, 95%CI[-3.81～6.79], P = 0.58) and epilepsy (OR = 4.71, 95%CI[-2.20～5.30], P = 0.42) in this study, they did not reach statistical significance. At the same time, this study did not observe that psoriasis would increase the risk of multiple sclerosis (OR = 0.01, 95%CI [-12.61～3.83], P = 0.30) and migraine (OR = 0.99, 95%CI [0.94～1.05], P = 0.78), they also did not reach statistical significance. Under all sensitivity assessments, the results remained stable.

Conclusions

Psoriasis does not appear to raise the risk of migraine, Parkinson's disease, multiple sclerosis, or epilepsy, according to our study.

Neuropsychiatric Systemic Lupus Erythematosus: Molecules Involved in Its Imunopathogenesis, Clinical Features, and Treatment

Systemic lupus erythematosus (SLE) is an idiopathic chronic autoimmune disease that can affect any organ in the body, including the neurological system. Multiple factors, such as environmental (infections), genetic (many HLA alleles including DR2 and DR3, and genes including C4), and immunological influences on self-antigens, such as nuclear antigens, lead to the formation of multiple autoantibodies that cause deleterious damage to bodily tissues and organs. The production of autoantibodies, such as anti-dsDNA, anti-SS(A), anti-SS(B), anti-Smith, and anti-neuronal DNA are characteristic features of this disease. This autoimmune disease results from a failure of the mechanisms responsible for maintaining self-tolerance in T cells, B cells, or both. Immune complexes, circulating antibodies, cytokines, and autoreactive T lymphocytes are responsible for tissue injury in this autoimmune disease. The diagnosis of SLE is a rheumatological challenge despite the availability of clinical criteria. NPSLE was previously referred to as lupus cerebritis or lupus sclerosis. However, these terms are no longer recommended because there is no definitive pathological cause for the neuropsychiatric manifestations of SLE. Currently, the treatment options are primarily based on symptomatic presentations. These include the use of antipsychotics, antidepressants, and anxiolytic medications for the treatment of psychiatric and mood disorders. Antiepileptic drugs to treat seizures, and immunosuppressants (e.g., corticosteroids, azathioprine, and mycophenolate mofetil), are directed against inflammatory responses along with non-pharmacological interventions.

Investigating the feasibility of differentiating MS active lesions from inactive ones using texture analysis and machine learning methods in DWI images

BACKGROUND

Magnetic resonance imaging (MRI) is commonly used in conjunction with a gadolinium-based contrast agent (GBCA) to distinguish active multiple sclerosis (MS) lesions. However, recent studies have raised concerns regarding the long-term effects of the accumulation of GBCA in the body. Thus, the purpose of this study is to investigate the possibility of using texture analysis in diffusion-weighted imaging (DWI) and machine learning algorithms to discriminate active from inactive MS lesions without the use of GBCA.

METHODS

To achieve this purpose, we introduce an image processing pipeline. In the proposed pipeline, following registration and alignment of slices, MS lesions from DWI images are segmented and quantized. Next, different texture analysis methods are employed to extract texture features from the lesions. Then, a two-stage feature reduction method is applied, in which the first stage involves a statistical t-test and the second stage relies on principal component analysis (PCA), sequential forward selection (SFS), sequential backward selection (SBS), and ReliefF algorithms. Finally, we use five classifiers logistic regression (LR), support vector machine (SVM), decision tree (DT), K nearest neighbor (KNN), and linear discriminant analysis (LDA) in a 5-fold cross-validation procedure to determine active and inactive MS lesions.

RESULTS

In this study, we collected and prepared 255 active/inactive MS lesions from MRI scans of 34 patients diagnosed with MS, with a mean age of 35.56±10.89. Among 89 texture features extracted, 63 features showed statistically significant differences between the means of active and inactive lesions (P<0.05). The SVM classifier with the PCA feature reduction algorithm demonstrated the best performance with an average accuracy of 0.960 (±0.024), specificity and precision of 1.0, sensitivity of 0.913 (±0.053), and AUC of 0.957 (±0.027).

CONCLUSION

Our study indicates that DWI changes detected using texture analysis-based machine learning models can precisely differentiate active from inactive MS lesions. This finding provides valuable clinical information for the early diagnosis and effective monitoring of MS disease.

Differences in Brain Atrophy Pattern between People with Multiple Sclerosis and Systemic Diseases with Central Nervous System Involvement Based on Two-Dimensional Linear Measures

Conventional brain magnetic resonance imaging (MRI) in systemic diseases with central nervous system involvement (SDCNS) may imitate MRI findings of multiple sclerosis (MS). In order to better describe the MRI characteristics of these conditions, in our study we assessed brain volume parameters in MS (n = 58) and SDCNS (n = 41) patients using two-dimensional linear measurements (2DLMs): bicaudate ratio (BCR), corpus callosum index (CCI) and width of third ventricle (W3V). In SDCNS patients, all 2DLMs were affected by age (CCI p = 0.005, BCR p < 0.001, W3V p < 0.001, respectively), whereas in MS patients only BCR and W3V were (p = 0.001 and p = 0.015, respectively). Contrary to SDCNS, in the MS cohort BCR and W3V were associated with T1 lesion volume (T1LV) (p = 0.020, p = 0.009, respectively) and T2 lesion volume (T2LV) (p = 0.015, p = 0.009, respectively). CCI was associated with T1LV in the MS cohort only (p = 0.015). Moreover, BCR was significantly higher in the SDCNS group (p = 0.01) and CCI was significantly lower in MS patients (p = 0.01). The best predictive model to distinguish MS and SDCNS encompassed gender, BCR and T2LV as the explanatory variables (sensitivity 0.91; specificity 0.68; AUC 0.86). Implementation of 2DLMs in the brain MRI analysis of MS and SDCNS patients allowed for the identification of diverse patterns of local brain atrophy in these clinical conditions.

Multiple Sclerosis: New Insights into Molecular Pathogenesis and Novel Platforms for Disease Treatment

BACKGROUND

Multiple sclerosis (MS), a chronic inflammatory disorder, affects the central nervous system via myelin degradation. The cause of MS is not fully known, but during recent years, our knowledge has deepened significantly regarding the different aspects of MS, including etiology, molecular pathophysiology, diagnosis and therapeutic options. Myelin basic protein (MBP) is the main myelin protein that accounts for maintaining the stability of the myelin sheath. Recent evidence has revealed that MBP citrullination or deamination, which is catalyzed by Ca2+ dependent peptidyl arginine deiminase (PAD) enzyme leads to the reduction of positive charge, and subsequently proteolytic cleavage of MBP. The overexpression of PAD2 in the brains of MS patients plays an essential role in new epitope formation and progression of the autoimmune disorder. Some drugs have recently entered phase III clinical trials with promising efficacy and will probably obtain approval in the near future. As different therapeutic platforms develop, finding an optimal treatment for each individual patient will be more challenging.

AIMS

This review provides a comprehensive insight into MS with a focus on its pathogenesis and recent advances in diagnostic methods and its present and upcoming treatment modalities.

CONCLUSION

MS therapy alters quickly as research findings and therapeutic options surrounding MS expand. McDonald's guidelines have created different criteria for MS diagnosis. In recent years, ever-growing interest in the development of PAD inhibitors has led to the generation of many reversible and irreversible PAD inhibitors against the disease with satisfactory therapeutic outcomes.

A Novel Sensory Wave (P25) in Myelin Oligodendrocyte Glycoprotein-induced Experimental Autoimmune Encephalomyelitis Murine Model

Myelin oligodendrocyte glycoprotein (MOG)-induced experimental autoimmune encephalomyelitis (EAE) is a murine model for multiple sclerosis. This model is characterized by chronic and progressive demyelination, leading to impairment of motor function and paralysis. While the outcomes of the disease, including impaired motor function and immunological changes, are well-characterized, little is known about the impact of EAE on the electrophysiology of the motor and sensory systems. In this study, we assessed evoked potentials as a quantitative marker for in vivo monitoring of nervous system damage. Motor-evoked potentials (MEPs) and sensory-evoked potentials (SEPs) were first standardized in naïve C57BL mice and studied thoroughly in EAE mice. The duration of MEPs and the number of connotative potentials increased significantly alongside an increase in temporal SEP amplitudes. Moreover, a new SEP wave was identified in naïve animals, which significantly increased in MOG-induced EAE animals with no or mild symptoms (clinical score 0-2, 0-5 scale). This wave occurred ∼25 milliseconds poststimulation, thus named p25. P25 was correlated with increased vocalization and was also reduced in amplitude following treatment with morphine. As the EAE score progressed (clinical score 3-4, 0-5 scale), the amplitude of MEPs and SEPs decreased drastically. Our results demonstrate that desynchronized neural motor activity, along with hypersensitivity in the early stages of EAE, leads to a complete loss of motor and sensory functions in the late stages of the disease. The findings also suggest an increase in p25 amplitude before motor deficits appear, indicating SEP as a predictive marker for disease progression. PERSPECTIVE: This article assesses p25, a new sensory electrophysiology wave that correlates with pain-related behavior in MOG-induced EAE mice and appears prior to the clinical symptoms. Motor electrophysiology correlates with traditional motor behavior scoring and histology.

Cerebrospinal fluid oligoclonal bands in Chinese patients with multiple sclerosis: the prevalence and its association with clinical features

Background

Cerebrospinal fluid oligoclonal band (CSF-OCB) is an established biomarker in diagnosing multiple sclerosis (MS), however, there are no nationwide data on CSF-OCB prevalence and its diagnostic performance in Chinese MS patients, especially in the virtue of common standard operation procedure (SOP).

Methods

With a consensus SOP and the same isoelectric focusing system, we conducted a nationwide multi-center study on OCB status in consecutively, and recruited 483 MS patients and 880 non-MS patients, including neuro-inflammatory diseases (NID, n = 595) and non-inflammatory neurological diseases (NIND, n=285). Using a standardized case report form (CRF) to collect the clinical, radiological, immunological, and CSF data, we explored the association of CSF-OCB positivity with patient characters and the diagnostic performance of CSF-OCB in Chinese MS patients. Prospective source data collection, and retrospective data acquisition and statistical data analysis were used.

Findings

369 (76.4%) MS patients were OCB-positive, while 109 NID patients (18.3%) and 6 NIND patients (2.1%) were OCB-positive, respectively. Time from symptom onset to diagnosis was significantly shorter in OCB-positive than that in OCB-negative MS patients (13.2 vs 23.7 months, P=0.020). The prevalence of CSF-OCB in Chinese MS patients was significantly higher in high-latitude regions (41°-50°N)(P=0.016), and at high altitudes (>1000m)(P=0.025). The diagnostic performance of CSF-OCB differentiating MS from non-MS patients yielded a sensitivity of 76%, a specificity of 87%.

Interpretation

The nationwide prevalence of CSF-OCB was 76.4% in Chinese MS patients, and demonstrated a good diagnostic performance in differentiating MS from other CNS diseases. The CSF-OCB prevalence showed a correlation with high latitude and altitude in Chinese MS patients.

Multiple sclerosis: Implications for the primary care NP

ABSTRACT

Multiple sclerosis is a demyelinating disease of the central nervous system. It contributes to a variety of symptoms affecting different areas of the body. The primary care NP must be familiar with the disease, therapies, and social impact to provide proper care to affected patients.

Multiple Sclerosis-A Demyelinating Disorder and Its Dental Considerations-A Literature Review with Own Case Report

Multiple sclerosis (MS) is a chronic, autoimmune condition that primarily affects the myelin sheath covering the neurons of the central nervous system, including those of the brain and spinal cord. Although the etiology is not completely understood, various factors, such as genetic infections and environmental background, play a role in the pathogenesis. Repeated active episodes of MS characterized with marked inflammation results in the scarring of particular nerve segments, and eventually results in functional impairment over a period of time. Based on the clinical course of the disease, four clinical types of MS have been identified, with the relapsing-remitting type being the commonest. MS is known to occur more commonly in females in the age group of 20-40 years. Dysarthria, fatigue, muscle spasm, and numbness are the common presenting symptoms of MS. Diagnosis is generally achieved with MRI brain scans, showing demyelination plaques and lumbar puncture. Treatment of MS's acute phase includes high doses of corticosteroids; whereas preventive treatment of MS includes the prescription of immunosuppressive therapy, including biologics. A large group of MS patients present with oral manifestations, including dysphagia, dysarthria, temporomandibular joint (TMJ) disturbances, facial palsy, and chronic periodontal diseases. Other typical oral manifestations seen in MS patients include trigeminal neuralgia, paresthesia, or orofacial pain. Dental treatment and following drug prescription needs to be tailored to each patient, as there is a possibility of drug interactions. This paper presents a comprehensive, updated review of MS, with emphasis on oral manifestations and dental considerations. Additionally, it presents a case of a 40-year-old female diagnosed with MS that was presented to a dental hospital. The report discusses the oral manifestations and dental management.

Factors associated with the misdiagnosis of neuromyelitis optica spectrum disorder

BACKGROUND

Neuromyelitis optica spectrum disorder (NMOSD) is a rare autoimmune condition that is associated with severe disability. Approximately 40% of individuals are misdiagnosed with multiple sclerosis (MS) or other diseases. We aimed to define factors that influence the misdiagnosis of people with NMOSD and provide strategies for reducing error rates.

METHODS

A retrospective study was performed involving all people with a confirmed diagnosis of NMOSD within a single academic institution. Comprehensive clinical timelines were constructed for each individual that included presenting symptoms, provider type and timing of evaluations, aquaporin 4-IgG (AQP4) results, and MRI scans. Two-sample comparisons of continuous and categorial variables were performed for people accurately diagnosed with NMOSD and those originally misdiagnosed with another medical condition. A subanalysis of only AQP4-IgG positive people was also performed.

RESULTS

The study cohort included 199 people fulfilling International Panel criteria for NMOSD with 71 people (62 female; mean age at first symptom presentation (standard deviation (SD)) = 32.8 years (y) (SD 16.1)) being initially misdiagnosed and 128 people (106 female; 41.14y (SD 15.41)) who were accurately diagnosed. Of the 199 people with NMOSD, 166 had a positive serostatus. Identified factors associated with misdiagnosis, regardless of AQP4-IgG serostatus, were the presence of protracted nausea/vomiting/hiccups without any accompanying neurological symptoms, 23 (32.4%) versus 16 (12.5%) (p = 0.001), a longer median (range) time to see a neuroimmunology specialist 4.2y (0.14-31.8) versus 0.5y (0.0-21.2) (p<0.0001), and a delay in acquiring an MRI study, 4.7y (0.0-27.3) versus 0.3y (0.0-20.2) (p<0.0001). A greater proportion of people misdiagnosed were identified with a negative live-cell based AQP4-IgG serum test result, 13/13 (100%) versus 22/114 (19.3%) (p<0.0001). Additionally, the mean (SD) time between a first negative and successive live-cell based AQP4-IgG positive test result was greater for people misdiagnosed with another condition, 3.9y (SD 5.0) versus 1.5y (SD 2.1) (p = 0.01). Although not significant between groups, a rash was also reported in 63/199 people with NMOSD, with 31/63 having an anti-nuclear antibody titer ≥ 1:160.

CONCLUSION

Defined factors can help guide both generalists and specialists in the pursuit of strategies aimed at efficiently diagnosing those with NMOSD such that effective care can be delivered.

Cerebrospinal Fluid Biomarkers in Differential Diagnosis of Multiple Sclerosis and Systemic Inflammatory Diseases with Central Nervous System Involvement

BACKGROUND

Diagnosis of multiple sclerosis (MS) is established on criteria according to clinical and radiological manifestation. Cerebrospinal fluid (CSF) analysis is an important part of differential diagnosis of MS and other inflammatory processes in the central nervous system (CNS).

METHODS

In total, 242 CSF samples were collected from patients undergoing differential MS diagnosis because of the presence of T2-hyperintensive lesions on brain MRI. The non-MS patients were subdivided into systemic inflammatory diseases with CNS involvement (SID) or cerebrovascular diseases (CVD) or other non-inflammatory diseases (NID). All samples were analyzed for the presence of oligoclonal bands and ELISA was performed for detection of: INF gamma, IL-6, neurofilaments light chain (NF-L), GFAP, CHI3L1, CXCL13, and osteopontin.

RESULTS

The level of IL-6 (p = 0.024), osteopontin (p = 0.0002), and NF-L (p = 0.002) was significantly different among groups. IL-6 (p = 0.0350) and NF-L (p = 0.0015) level was significantly higher in SID compared to NID patients. A significantly higher level of osteopontin (p = 0.00026) and NF-L (p = 0.002) in MS compared to NID population was noted. ROC analysis found weak diagnostic power for osteopontin and NFL-L.

CONCLUSIONS

The classical and non-standard markers of inflammatory process and neurodegeneration do not allow for sufficient differentiation between MS and non-MS inflammatory CNS disorders. Weak diagnostic power observed for the osteopontin and NF-L needs to be further investigated.

Bacillus amyloliquifaciens-Supplemented Camel Milk Suppresses Neuroinflammation of Autoimmune Encephalomyelitis in a Mouse Model by Regulating Inflammatory Markers

Multiple sclerosis (MS), a distinct autoimmune neuroinflammatory disorder, affects millions of people worldwide, including Saudi Arabia. Changes in the gut microbiome are linked to the development of neuroinflammation via mechanisms that are not fully understood. Prebiotics and probiotics in camel milk that has been fermented have a variety of health benefits. In this study, Bacillus amyloliquefaciens-supplemented camel milk (BASY) was used to assess its preventive effect on MS symptoms in a myelin oligodendrocyte glycoprotein (MOG)-immunized C57BL6J mice model. To this end, MOG-induced experimental autoimmune encephalomyelitis (EAE) was established and the level of disease index, pathological scores, and anti-inflammatory markers of BASY-treated mice using macroscopic and microscopic examinations, qPCR and immunoblot were investigated. The results demonstrate that BASY significantly reduced the EAE disease index, increased total microbial load (2.5 fold), and improved the levels of the short-chain fatty acids propionic, butyric and caproic acids in the diseased mice group. Additionally, myeloperoxidase (MPO) proinflammatory cytokines (IL-1β, IL-6, IL-17, TNF-α) and anti-inflammatory cytokines (TGF-β) were regulated by BASY treatment. Significant suppression of MPO and VCAM levels were noticed in the BASY-treated group (from 168 to 111 µM and from 34 to 27 pg/mL, respectively), in comparison to the EAE group. BASY treatment significantly reduced the expression of inflammatory cytokines, inflammatory progression related transcripts, and inflammatory progression protein markers. In conclusion, BASY significantly reduced the symptoms of EAE mice and may be used to develop a probiotic-based diet to promote host gut health. The cumulative findings of this study confirm the significant neuroprotection of BASY in the MOG-induced mice model. They could also suggest a novel approach to the treatment of MS-associated disorders.

Treadmill aerobic training improve beam-walking test, up-regulate expression of main proteins of myelin and myelination in the hippocampus of cuprizone-fed mice

Multiple sclerosis (MS) is a potentially disabling disease of the brain and spinal cord (central nervous system). The aim of this study was to investigate the effect of 6 weeks of aerobic training on the main proteins of myelin including myelin basic protein (MBP), myelin oligodendrocyte (MOG), myelin associated glycoprotein (MAG), and myelin proteolipid protein (PLP) at hippocampus of C57BL/6 mouse model of cuprizone-induced MS. Twenty-eight female C57BL/6 mice (23 ± 3 g) were randomly divided into four groups (n = 7 per group): control, exercise (Exe), cuprizone (CPZ), and cuprizone with exercise (CPZ + Exe). Exercise groups performed treadmill aerobic exercise training 5 days a week, 15-22 m/min, and 15-60 min, during 6 weeks. Cuprizone were fed to mice at CPZ and CPZ + Exe groups for 6 weeks. Animals were sacrificed after 6 weeks. Biochemical and molecular biology analyses were performed. Mice at CPZ group had decreased myelination of nerve cells in the hippocampus. In addition, the use of CPZ in the hippocampus caused a decrease in the MBP, MOG gene expression, as well as a decrease in the MAG and PLP gene and protein expression compared to the healthy control group. However, performing aerobic exercise with CPZ consumption increased MBP gene expression and increased MAG and PLP protein expression, as well as increased myelination of nerve cells in the hippocampus compared to the CPZ group (p < 0.05). It seems that regular aerobic exercise in the MS model controls the destruction of myelin in the nerve cells of hippocampus by upregulating MBP, MAG and PLP, which can have positive effects on cognitive and motor performance.

Applications of Extracellular Vesicles in Nervous System Disorders: An Overview of Recent Advances

Diseases affecting the brain and spinal cord fall under the umbrella term "central nervous system disease". Most medications used to treat or prevent chronic diseases of the central nervous system cannot cross the blood-brain barrier (BBB) and hence cannot reach their intended target. Exosomes facilitate cellular material movement and signal transmission. Exosomes can pass the blood-brain barrier because of their tiny size, high delivery efficiency, minimal immunogenicity, and good biocompatibility. They enter brain endothelial cells via normal endocytosis and reverse endocytosis. Exosome bioengineering may be a method to produce consistent and repeatable isolation for clinical usage. Because of their tiny size, stable composition, non-immunogenicity, non-toxicity, and capacity to carry a wide range of substances, exosomes are indispensable transporters for targeted drug administration. Bioengineering has the potential to improve these aspects of exosomes significantly. Future research into exosome vectors must focus on redesigning the membrane to produce vesicles with targeting abilities to increase exosome targeting. To better understand exosomes and their potential as therapeutic vectors for central nervous system diseases, this article explores their basic biological properties, engineering modifications, and promising applications.

Temporal trends of epilepsy in multiple sclerosis

OBJECTIVES

Epilepsy is associated with advanced multiple sclerosis (MS). We aimed to investigate whether the incidence of epilepsy in MS has been affected by the introduction of disease-modifying treatments (DMT) for MS.

MATERIALS AND METHODS

This retrospective study included 14,557 patients from the Swedish MS register with MS onset between 1991 and 2018. Incident diagnoses of epilepsy or any seizure were identified through cross-linkage with the National Patient Register. Next, yearly prevalence of epilepsy as well as 5- and 10 years incidence of epilepsy or any seizure for consecutive years of MS onset were estimated, the latter with Kaplan-Meier analysis. Cox regression was used to adjust the association between the year of MS onset and incidence of epilepsy for baseline variables.

RESULTS

Prevalence of epilepsy in the MS cohort increased from 0.34% in 1991 to 2.54% in 2018 (yearly odds: 1.26 [1.22, 1.29]). The 5 years incidence rate of epilepsy, ranging from 0.4% (95% CI 0.008-0.79%) to 1.3% (95% CI 0.71-1.89%), and the 10 years incidence rate of epilepsy, ranging from 1.1% (95% CI 0.31-1.88%) to 2.6% (95% CI 1.22-3.97%) showed no significant trends (p = .147 and p = .418, respectively). Similarly, no significant trends were found for the incidences of any seizure. The incidence trends of epilepsy remained not significant after adjusting for sex, MS onset type (relapsing or progressive onset), or age at MS onset.

CONCLUSIONS

Our findings do not support the hypothesis that the introduction of novel DMT for MS has reduced the incidence of epilepsy among MS patients.

Multiple Sclerosis Diagnosis Using Machine Learning and Deep Learning: Challenges and Opportunities

Multiple Sclerosis (MS) is a disease that impacts the central nervous system (CNS), which can lead to brain, spinal cord, and optic nerve problems. A total of 2.8 million are estimated to suffer from MS. Globally, a new case of MS is reported every five minutes. In this review, we discuss the proposed approaches to diagnosing MS using machine learning (ML) published between 2011 and 2022. Numerous models have been developed using different types of data, including magnetic resonance imaging (MRI) and clinical data. We identified the methods that achieved the best results in diagnosing MS. The most implemented approaches are SVM, RF, and CNN. Moreover, we discussed the challenges and opportunities in MS diagnosis to improve AI systems to enable researchers and practitioners to enhance their approaches and improve the automated diagnosis of MS. The challenges faced by automated MS diagnosis include difficulty distinguishing the disease from other diseases showing similar symptoms, protecting the confidentiality of the patients' data, achieving reliable ML models that are also easily understood by non-experts, and the difficulty of collecting a large reliable dataset. Moreover, we discussed several opportunities in the field such as the implementation of secure platforms, employing better AI solutions, developing better disease prognosis systems, combining more than one data type for better MS prediction and using OCT data for diagnosis, utilizing larger, multi-center datasets to improve the reliability of the developed models, and commercialization.

Adult-Onset Genetic Central Nervous System Disorders Masquerading as Acquired Neuroinflammatory Disorders: A Review

Importance

Adult-onset genetic disorders may present with clinical and magnetic resonance imaging (MRI) features suggestive of acquired inflammatory diseases. An ever-growing number of potentially treatable adult-onset genetic neuroinflammatory disorders have been described in the past few years that need to be rapidly identified.

Observations

Adult-onset acquired neuroinflammatory disorders encompass a large group of central nervous system (CNS) diseases with varying presentation, MRI characteristics, and course, among which the most common is multiple sclerosis. Despite recent progress, including the discovery of specific autoantibodies, a significant number of adult-onset neuroinflammatory disorders with progressive or relapsing course still remain without a definite diagnosis. In addition, some patients with genetic disorders such as leukodystrophies, hemophagocytic lymphohistiocytosis, or genetic vasculopathies can mimic acquired neuroinflammatory disorders. These genetic disorders, initially described in pediatric populations, are increasingly detected in adulthood thanks to recent progress in molecular genetics and the larger availability of high-throughput sequencing technologies.

Conclusions and Relevance

Genetic adult-onset neuroinflammatory diseases are at the border between primary CNS inflammatory diseases and systemic disorders with multiorgan involvement and predominantly neurologic manifestations. Neurologists must be aware of the main clues and red flags so they can confirm a diagnosis early, when some of these genetic disorders can be successfully treated.

NMOSD-Diagnostic Dilemmas Leading towards Final Diagnosis

(1) Background: The emergence of white matter lesions in the central nervous system (CNS) can lead to diagnostic dilemmas. They are a common radiological symptom and their patterns may overlap CNS or systemic diseases and provoke underdiagnosis or misdiagnosis. The aim of the study was to assess factors influencing the underdiagnosis of neuromyelitis optica spectrum disorder (NMOSD) as well as to estimate NMOSD epidemiology in Lubelskie voivodeship, Poland. (2) Methods: This retrospective study included 1112 patients, who were made a tentative or an established diagnosis of acute or subacute onset of neurological deficits. The evaluation was based on medical history, neurological examination, laboratory and radiographic results and fulfilment of diagnosis criteria. (3) Results: Up to 1.62 percent of patients diagnosed with white matter lesions and up to 2.2% of the patients previously diagnosed with MS may suffer from NMOSD. The duration of delayed diagnosis is longer for males, despite the earlier age of onset. Seropositive cases for antibodies against aquaporin-4 have worse prognosis for degree of disability. (4) Conclusions: Underdiagnosis or misdiagnosis in NMOSD still remains a problem in clinical practice and has important implications for patients. The incorrect diagnosis is caused by atypical presentation or NMOSD-mimics; however, covariates such as gender, onset and diagnosis age may also have an influence.

Immunopathology of the Optic Nerve in Multiple Sclerosis

Optic neuritis, a primary clinical manifestation commonly observed in multiple sclerosis (MS) is a major factor leading to permanent loss of vision. Despite decreased vision (optic neuritis), diplopia, and nystagmus, the immunopathology of the optic nerve in MS is unclear. Here, we have characterised the optic nerve pathology in a large cohort of MS cases (n=154), focusing on the immune responses in a sub-cohort of MS (n=30) and control (n=6) cases. Immunohistochemistry was used to characterise the myeloid (HLA-DR, CD68, Iba1, TMEM119, P2RY12) and adaptive immune cells (CD4, CD8, CD138) in the parenchyma, perivascular spaces, and meninges in optic nerve tissues from MS and control cases. Of the 154 MS cases, 122 (79%) reported visual problems of which 99 (81%) optic nerves showed evidence of damage. Of the 31 cases with no visual disturbances, 19 (61%) showed evidence of pathology. A pattern of myeloid cell activity and demyelination in the optic nerve was similar to white matter lesions in the brain and spinal cord. In the optic nerves, adaptive immune cells were more abundant in the meninges close to active and chronic active lesions, and significantly higher compared to the parenchyma. Similar to brain tissues in this Dutch cohort, B-cell follicles in the meninges were absent. Our study reveals that optic nerve pathology is a frequent event in MS and may occur in the absence of clinical symptoms.

Role of exosomes in the pathogenesis, diagnosis, and treatment of central nervous system diseases

Central nervous system (CNS) diseases, such as multiple sclerosis, Alzheimer's disease (AD), and Parkinson’s disease (PD), affect millions of people around the world. Great efforts were put in disease related research, but few breakthroughs have been made in the diagnostic and therapeutic approaches. Exosomes are cell-derived extracellular vesicles containing diverse biologically active molecules secreted by their cell of origin. These contents, including nucleic acids, proteins, lipids, amino acids, and metabolites, can be transferred between different cells, tissues, or organs, regulating various intercellular cross-organ communications and normal and pathogenic processes. Considering that cellular environment and cell state strongly impact the content and uptake efficiency of exosomes, their detection in biological fluids and content composition analysis potentially offer a multicomponent diagnostic readout of several human diseases. Recently, studies have found that aberrant secretion and content of exosomes are closely related to the pathogenesis of CNS diseases. Besides, loading natural cargoes, exosomes can deliver drugs cross the blood brain barrier, making them emerging candidates of biomarkers and therapeutics for CNS diseases. In this review, we summarize and discuss the advanced research progress of exosomes in the pathological processes of several CNS diseases in regarding with neuroinflammation, CNS repair, and pathological protein aggregation. Moreover, we propose the therapeutic strategies of applying exosomes to the diagnosis, early detection, and treatment of CNS diseases.

Isolated sixth nerve palsy: a rare first presentation in multiple sclerosis

True isolated sixth nerve palsy as the initial presentation of multiple sclerosis (MS) is rare. MS is a chronic inflammatory, immune-mediated disease of the central nervous system. This is the most common cause of neurological disability in young adults. Common symptoms include acute episodes of muscle weakness, altered sensation, balance and gait disturbances, visual loss and bladder dysfunction.Diagnosis of MS is supported with the incidence of symptomatic clinical episodes with subsequent cross-sectional imaging to confirm radiological lesions that are disseminated in space and time.In the following report, we discuss the case of a woman in her 30s who presented to ophthalmology with a sixth nerve palsy in the absence of ocular or systemic disease. This is the first presentation of MS, a rare clinical event.

Magnetic Resonance Imaging of Autoimmune Demyelinating Diseases as a Diagnostic Challenge for Radiologists: Report of Two Cases and Literature Review

The magnetic resonance characteristics of autoimmune demyelinating diseases are complex and represent a challenge for the radiologist. In this study we presented two different cases of detected autoimmune demyelinating diseases: one case of acute disseminated encephalomyelitis and one case of neuromyelitis optica, respectively. Expected and unexpected findings of magnetic resonance imaging examination for autoimmune demyelinating diseases were reported in order to provide a valuable approach for diagnosis. In particular, we highlight, review and discuss the presence of several uncommon imaging findings which could lead to a misinterpretation. The integration of magnetic resonance imaging findings with clinical and laboratory data is necessary to provide a valuable diagnosis.

Kappa Free Light Chains, Soluble Interleukin-2 Receptor, and Interleukin-6 Help Explore Patients Presenting With Brain White Matter Hyperintensities

Introduction

Many patients are referred to multiple sclerosis (MS) tertiary centers to manage brain white matter hyperintensities (WMH). Multiple diagnoses can match in such situations, and we lack proper tools to diagnose complex cases.

Objective

This study aimed to prospectively analyze and correlate with the final diagnosis, cerebrospinal fluid (CSF) interleukin (IL)-1β, soluble IL-2 receptor (CD25), IL-6, IL-10, and kappa free light chains (KFLC) concentrations in patients presenting with brain WMH.

Methods

All patients over 18 years addressed to our MS tertiary center for the diagnostic workup of brain WMH were included from June 1, 2020, to June 1, 2021. Patients were separated into three groups-MS and related disorder (MSARD), other inflammatory neurological disorder (OIND), and non-inflammatory neurological disorder (NIND) groups-according to clinical presentation, MRI characteristics, and biological workup.

Results

A total of 176 patients (129 women, mean age 45.8 ± 14.7 years) were included. The diagnosis was MSARD (n = 88), OIND (n = 35), and NIND (n = 53). Median CSF KFLC index and KFLC intrathecal fraction (IF) were higher in MSARD than in the OIND and NIND groups; p < 0.001 for all comparisons. CSF CD25 and IL-6 concentrations were higher in the OIND group than in both the MSARD and NIND groups; p < 0.001 for all comparisons. KFLC index could rule in MSARD when compared to NIND (sensitivity, 0.76; specificity, 0.91) or OIND (sensitivity, 0.73; specificity, 0.76). These results were similar to those with oligoclonal bands (sensitivity, 0.59; specificity, 0.98 compared to NIND; sensitivity, 0.59; specificity, 0.88 compared to OIND). In contrast, elevated CSF CD25 and IL-6 could rule out MSARD when compared to OIND (sensitivity, 0.58 and 0.88; specificity, 0.95 and 0.74, respectively).

Discussion

Our results show that, as OCBs, KFLC biomarkers are helpful tools to rule in MSARD, whereas elevated CSF CD25 and IL-6 rule out MSARD. Interestingly, CSF IL-6 concentration could help identify neuromyelitis optica spectrum disorder, myelin oligodendrocyte glycoprotein antibody-associated disease, and central nervous system (CNS) vasculitis. These results need to be confirmed within more extensive and multicentric studies. Still, they sustain that KFLC, CSF CD25, and CSF IL-6 could be reliable biomarkers in brain WMH diagnostic workup for differentiating MSARD from other brain inflammatory MS mimickers.

Multiple Sclerosis: Systemic Challenges to Cost-Effective Care

BACKGROUND

Multiple sclerosis (MS) is a progressive autoimmune disorder of the central nervous system characterized by symptoms including reduced mobility, pain, fatigue, and spasticity. MS affects nearly 1 million people in the United States, with significant negative impact on a patient's quality of life, and an average lifetime cost of care in excess of $4 million. The cost-effective management of patients with MS faces several challenges.

OBJECTIVE

To review the challenges to the cost-effective management of patients with MS, and to offer healthcare stakeholders a roadmap to address them.

DISCUSSION

The cost-effective management of patients with MS, which is driven largely by how quickly a patient receives effective medication therapy, is challenged by a paucity of between-office-visit clinical data, variability of provider expertise with magnetic resonance imaging (MRI), MRI machine quality, lack of standards for MRI machines and reports, misaligned financial incentives, the limited number of available Current Procedural Terminology (CPT) codes for brain MRI, the complexity of disease-modifying therapy (DMT) selection, poor patient adherence to treatment plans, poor communication among providers, and a lack of objective measures of disease progression.

CONCLUSION

Insurers, neurologists, researchers, and patient advocacy groups must address the needs of patients with MS holistically. These efforts should include establishing standards for MRI machines and reports, matching patients with MS specialists, aligning financial incentives, including creating a new CPT code for complex brain MRI, streamlining prior authorization processes of DMTs, using technology to gather patient data and improve coordination of care, and developing better measurement tools of disease activity.

The Application of Consensus Weighted Gene Co-expression Network Analysis to Comparative Transcriptome Meta-Datasets of Multiple Sclerosis in Gray and White Matter

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system characterized by demyelination, which leads to the formation of white matter lesions (WMLs) and gray matter lesions (GMLs). Recently, a large amount of transcriptomics or proteomics research works explored MS, but few studies focused on the differences and similarities between GMLs and WMLs in transcriptomics. Furthermore, there are astonishing pathological differences between WMLs and GMLs, for example, there are differences in the type and abundance of infiltrating immune cells between WMLs and GMLs. Here, we used consensus weighted gene co-expression network analysis (WGCNA), single-sample gene set enrichment analysis (ssGSEA), and machine learning methods to identify the transcriptomic differences and similarities of the MS between GMLs and WMLs, and to find the co-expression modules with significant differences or similarities between them. Through weighted co-expression network analysis and ssGSEA analysis, CD56 bright natural killer cell was identified as the key immune infiltration factor in MS, whether in GM or WM. We also found that the co-expression networks between the two groups are quite similar (density = 0.79), and 28 differentially expressed genes (DEGs) are distributed in the midnightblue module, which is most related to CD56 bright natural killer cell in GM. Simultaneously, we also found that there are huge disparities between the modules, such as divergences between darkred module and lightyellow module, and these divergences may be relevant to the functions of the genes in the modules.

Posttranslational modifications of proteins are key features in the identification of CSF biomarkers of multiple sclerosis

Background

Multiple sclerosis is an inflammatory and degenerative disease of the central nervous system (CNS) characterized by demyelination and concomitant axonal loss. The lack of a single specific test, and the similarity to other inflammatory diseases of the central nervous system, makes it difficult to have a clear diagnosis of multiple sclerosis. Therefore, laboratory tests that allows a clear and definite diagnosis, as well as to predict the different clinical courses of the disease are of utmost importance. Herein, we compared the cerebrospinal fluid (CSF) proteome of patients with multiple sclerosis (in the relapse–remitting phase of the disease) and other diseases of the CNS (inflammatory and non-inflammatory) aiming at identifying reliable biomarkers of multiple sclerosis.

Methods

CSF samples from the discovery group were resolved by 2D-gel electrophoresis followed by identification of the protein spots by mass spectrometry. The results were analyzed using univariate (Student’s t test) and multivariate (Hierarchical Cluster Analysis, Principal Component Analysis, Linear Discriminant Analysis) statistical and numerical techniques, to identify a set of protein spots that were differentially expressed in CSF samples from patients with multiple sclerosis when compared with other two groups. Validation of the results was performed in samples from a different set of patients using quantitative (e.g., ELISA) and semi-quantitative (e.g., Western Blot) experimental approaches.

Results

Analysis of the 2D-gels showed 13 protein spots that were differentially expressed in the three groups of patients: Alpha-1-antichymotrypsin, Prostaglandin-H2-isomerase, Retinol binding protein 4, Transthyretin (TTR), Apolipoprotein E, Gelsolin, Angiotensinogen, Agrin, Serum albumin, Myosin-15, Apolipoprotein B-100 and EF-hand calcium-binding domain—containing protein. ELISA experiments allowed validating part of the results obtained in the proteomics analysis and showed that some of the alterations in the CSF proteome are also mirrored in serum samples from multiple sclerosis patients. CSF of multiple sclerosis patients was characterized by TTR oligomerization, thus highlighting the importance of analyzing posttranslational modifications of the proteome in the identification of novel biomarkers of the disease.

Conclusions

The model built based on the results obtained upon analysis of the 2D-gels and in the validation phase attained an accuracy of about 80% in distinguishing multiple sclerosis patients and the other two groups.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02404-2.

Potential Contribution of IL-27 and IL-23 Gene Polymorphisms to Multiple Sclerosis Susceptibility: An Association Analysis at Genotype and Haplotype Level

(1) Background: interleukin 23 (IL-23) and interleukin 27 (IL-27) modulate the activity of T helper 17 cells (Th17) with critical roles in autoimmune diseases and multiple sclerosis (MS). The genes responsible for cytokine generation are highly influenced by the presence of single nucleotide polymorphisms (SNP) in main regions such as regulatory sequences or in promoter regions, contributing to disease susceptibility and evolution. The present study analyzed the associations of IL-23 and IL-27 SNPs with susceptibility to multiple sclerosis. (2) Methods: We performed a case-control study including 252 subjects: 157 patients diagnosed with MS and 95 controls. We used polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) to determine the genotypes for IL-27 T4730C (rs 181206), IL-27 A964G (rs 153109), and IL-23 receptor gene (IL-23R) G1142A (rs 11209026). (3) Results: The IL27-T4730C gene polymorphism was significantly associated with an increased odds of MS under the dominant genetic model (TC + CC variant genotypes, adjusted odds ratio OR = 4.06, 95% CI: 2.14–7.83, p-value = 0.000007, Q-value = 0.000063). Individuals carrying the IL-27 A924G variant (AG + GG) genotype presented higher odds of MS compared to non-carriers under the dominant model (adjusted OR = 1.93, 95% CI: 1.05–3.51, p-value = 0.0324, Q-value = 0.05832) and the allelic genetic model (unadjusted p-value = 0.015, OR = 1.58, 95% CI: 1.09–2.28), while IL-23-R381Q SNP conferred a decreased odds of MS under a codominant model of inheritance (adjusted OR = 0.26, 95% CI: 0.08–0.92, p-value = 0.0276, Q-value = 0.058) and an allelic model (unadjusted p-value = 0.008, OR = 0.23, 95% CI: 0.07–0.75). In an additive model with adjustment for age group (≤40 years vs. >40 years), sex and smoking, patients carrying the G-C (A964G, T4730C) haplotype had a 3.18 increased risk (95% CI: 1.74–5.81, p < 0.001) to develop multiple sclerosis. (4) Conclusions: The results of the current study showed a significant relationship of IL-27-A964G and IL-27-T4730C polymorphisms with increased risk of MS, and also the protective role of the IL-23-R381Q polymorphism. Moreover, the haplotype-based analysis proposed the mutant G-C (A924G, T4730C) as a significant risk haplotype for the development of MS.

C1q inhibits differentiation of oligodendrocyte progenitor cells via Wnt/β-catenin signaling activation in a cuprizone-induced mouse model of multiple sclerosis

Multiple sclerosis (MS) is a chronic central nervous system demyelinating disease of autoimmune originate. Complement C1q, a complex glycoprotein, mediates a variety of immunoregulatory functions considered important in the prevention of autoimmunity. Although we found that the increased serum C1q level was highly associated with the Fazekas scores and T2 lesion volume of MS patients, the effect and mechanism of C1q on demyelination remains unclear. Cluster analysis and protein array results showed that serum Wnt receptors Frizzled-6 and LRP-6 levels in MS patients were both increased, we proposed that C1q may be involved in demyelination via Wnt signaling. The increased C1q protein levels in the serum and brain tissue were confirmed in a cuprizone (CPZ)-induced demyelination mice model. Moreover, CPZ treatment induced significant increase of LRP-6 and Frizzled-6 protein in mice corpus callosum. LRP-6 extra-cellular domain (LRP-6-ECD) level in the serum and cerebrospinal fluid (CSF) of CPZ mice also significantly increased. Knockdown of the subunit C1s of C1 not only substantially attenuated demyelination, promoted M2 microglia polarization and improved neurological function, but inhibited β-catenin expression and its nuclear translocation in oligodendrocyte progenitor cells (OPCs). In vitro, C1s silence reversed the increased level of LRP-6-ECD in the medium and β-catenin expression in OPCs induced by C1q treatment. Meanwhile, inhibition of C1s also markedly lowered the number of EDU positive OPCs, but enhanced the number of CNPase positive oligodendrocyte and the protein of MBP. The present study indicated that C1q was involved in demyelination in response to CPZ in mice by preventing OPC from differentiating into mature oligodendrocyte via Wnt/β-catenin signaling activation.

Optical Coherence Tomography in the Differential Diagnosis of Patients with Multiple Sclerosis and Patients with MRI Nonspecific White Matter Lesions

In the differential diagnosis of nonspecific white matter lesions (NSWMLs) detected on magnetic resonance imaging (MRI), multiple sclerosis (MS) should be taken into consideration. Optical coherence tomography (OCT) is a promising tool applied in the differential diagnostic process of MS. We tested whether OCT may be useful in distinguishing between MS and NSWMLs patients. In patients with MS (n = 41) and NSWMLs (n = 19), the following OCT parameters were measured: thickness of the peripapillary Retinal Nerve Fibre Layer (pRNFL) in superior, inferior, nasal, and temporal segments; thickness of the ganglion cell-inner plexiform layer (GCIPL); thickness of macular RNFL (mRNFL); and macular volume (MV). In MS patients, GCIPL was significantly lower than in NSWMLs patients (p = 0.024). Additionally, in MS patients, mRNFL was significantly lower than in NSWMLs patients (p = 0.030). The average segmental pRNFL and MV did not differ between MS and NSWMLs patients (p > 0.05). GCIPL and macular RNFL thinning significantly influenced the risk of MS (18.6% [95% CI 2.7%, 25.3%]; 27.4% [95% CI 4.5%, 62.3%]), and reduced GCIPL thickness appeared to be the best predictor of MS. We conclude that OCT may be helpful in the differential diagnosis of MS and NSWMLs patients in real-world settings.

Burden and cost of comorbidities in patients with neuromyelitis optica spectrum disorder

BACKGROUND

Neuromyelitis optica spectrum disorder (NMOSD) is associated with various comorbidities, including non-autoimmune and autoimmune conditions. The burden and cost of illness for NMOSD are unclear, particularly in the context of comorbidities.

METHODS

Claims data from IBM MarketScan Commercial and Medicare Supplemental Databases between 2014 and 2018 were analyzed. Patients with NMOSD were specified as having inpatient or outpatient claims for NMOSD diagnosis or specific NMOSD symptoms claims and no subsequent claims for multiple sclerosis (MS) or use of MS disease-modifying therapy (DMT). Continuous enrollment ≥ 6 months before and ≥ 1 year after the first claim (index date) was required for study inclusion. Total costs stratified by comorbidities within 12 months post-index date were calculated per patient and compared 1:5 with matched non-NMOSD controls.

RESULTS

A total of 162 patients with NMOSD and 810 non-NMOSD controls were evaluated. A significantly higher proportion of NMOSD patients had comorbidities than non-NMOSD controls (66.7% vs 41.5%; P < 0.001). Concomitant autoimmune disease occurred in 19.1% vs 4.9% (P < 0.001) of patients with NMOSD vs non-NMOSD controls. NMOSD patients incurred significantly higher total median (interquartile range) healthcare costs per patient ($68,386.48 [$23,373.54-$160,862.70]) than matched non-NMOSD controls with autoimmune disease ($17,215.13 [$6715.48-$31,441.93]; P < 0.001) or patients with NMOSD without autoimmune comorbidity ($23,905.42 [$8632.82-$67,251.54]; P = 0.022). Similarly, patients with NMOSD and non-autoimmune comorbidities incurred higher median healthcare costs than matched controls.

CONCLUSIONS

Patients with NMOSD experience significant disease burden and cost that are amplified by comorbidities. Effective therapies are needed, particularly for patients with concomitant autoimmune disease.

Do Multiple Brain Lesions Always Connote Worse Outcomes? Appraisal Evidence from a Tertiary Care Center in Koshi/Purbanchal Province of Nepal

Advances in medicine comprising diverse diagnostic and management modalities call for a bundle approach to improve patient care. This study aimed to present diagnostic patterns in patients with multiple intracranial lesions together with connoted survival implications. We retrospectively reviewed medical files of 85 patients with tumor and non-tumor intracranial lesions. Metastatic brain lesions were identified in 23.5% of patients. Neurological pathogenesis underlay 29.4%, infectious 21.2%, and vascular 14.1% of lesions, with the remaining portion comprising less frequent disorders. A favorable prognosis was predicted in 52/85 (61.2%) of the study population despite a variety of pathologies, which speaks for substantial improvements in outcomes of once hardly manageable or mortal brain disorders, comprising both common and rare conditions. The improvements are to the credit of advances in medical radio-imaging enhancing the diagnostic power which enables a precise stratification of brain pathologies. We emphasize the use of an algorithmic evaluation of patients presenting with multiple brain lesions for differential diagnosis and survival prognostication. There seems to be an ongoing transition from imperfect probabilistic prediction models to precision medicine, which determines advantages in disease management and outcome.