Current and Future Biomarkers in Multiple Sclerosis

Modeling and simulation for prediction of multiple sclerosis progression

In light of extensive work that has created a wide range of techniques for predicting the course of multiple sclerosis (MS) disease, this paper attempts to provide an overview of these approaches and put forth an alternative way to predict the disease progression. For this purpose, the existing methods for estimating and predicting the course of the disease have been categorized into clinical, radiological, biological, and computational or artificial intelligence-based markers. Weighing the weaknesses and strengths of these prognostic groups is a profound method that is yet in need and works directly at the level of diseased connectivity. Therefore, we propose using the computational models in combination with established connectomes as a predictive tool for MS disease trajectories. The fundamental conduction-based Hodgkin-Huxley model emerged as promising from examining these studies. The advantage of the Hodgkin-Huxley model is that certain properties of connectomes, such as neuronal connection weights, spatial distances, and adjustments of signal transmission rates, can be taken into account. It is precisely these properties that are particularly altered in MS and that have strong implications for processing, transmission, and interactions of neuronal signaling patterns. The Hodgkin-Huxley (HH) equations as a point-neuron model are used for signal propagation inside a small network. The objective is to change the conduction parameter of the neuron model, replicate the changes in myelin properties in MS and observe the dynamics of the signal propagation across the network. The model is initially validated for different lengths, conduction values, and connection weights through three nodal connections. Later, these individual factors are incorporated into a small network and simulated to mimic the condition of MS. The signal propagation pattern is observed after inducing changes in conduction parameters at certain nodes in the network and compared against a control model pattern obtained before the changes are applied to the network. The signal propagation pattern varies as expected by adapting to the input conditions. Similarly, when the model is applied to a connectome, the pattern changes could give an insight into disease progression. This approach has opened up a new path to explore the progression of the disease in MS. The work is in its preliminary state, but with a future vision to apply this method in a connectome, providing a better clinical tool.

Multiple Sclerosis: From the Application of Oligoclonal Bands to Novel Potential Biomarkers

Multiple sclerosis is a chronic immune-mediated disorder of the central nervous system with a high heterogeneity among patients. In the clinical setting, one of the main challenges is a proper and early diagnosis for the prediction of disease activity. Current diagnosis is based on the integration of clinical, imaging, and laboratory results, with the latter based on the presence of intrathecal IgG oligoclonal bands in the cerebrospinal fluid whose detection via isoelectric focusing followed by immunoblotting represents the gold standard. Intrathecal synthesis can also be evidenced by the measurement of kappa free light chains in the cerebrospinal fluid, which has reached similar diagnostic accuracy compared to that of oligoclonal bands in the identification of patients with multiple sclerosis; moreover, recent studies have also highlighted its value for early disease activity prediction. This strategy has significant advantages as compared to using oligoclonal band detection, even though some issues remain open. Here, we discuss the current methods applied for cerebrospinal fluid analysis to achieve the most accurate diagnosis and for follow-up and prognosis evaluation. In addition, we describe new promising biomarkers, currently under investigation, that could contribute both to a better diagnosis of multiple sclerosis and to its monitoring of the therapeutic treatment response.

Current use of fluid biomarkers as outcome measures in Multiple Sclerosis (MS): a review of ongoing pharmacological clinical trials

The present study aims to describe the state of the art of fluid biomarkers use in ongoing multiple sclerosis (MS) clinical trials.A review of 608 ongoing protocols in the clinicaltrials.gov and EudraCT databases was performed. The trials enrolled patients with a diagnosis of relapsing remitting MS, secondary progressive MS, and/or primary progressive MS according to Revised McDonald criteria or relapsing MS according to Lublin et al. (2014). The presence of fluid biomarkers among the primary and/or secondary study outcomes was assessed.Overall, 5% of ongoing interventional studies on MS adopted fluid biomarkers. They were mostly used as secondary outcomes in phase 3-4 clinical trials to support the potential disease-modifying properties of the intervention. Most studies evaluated neurofilament light chains (NfLs). A small number considered other novel fluid biomarkers of neuroinflammation and neurodegeneration such as glial fibrillary acid protein (GFAP).Considering the numerous ongoing clinical trials in MS, still a small number adopted fluid biomarkers as outcome measures, thus testifying the distance from clinical practice. In most protocols, fluid biomarkers were used to evaluate the effectiveness of approved second-line therapies, but also, new drugs (particularly Bruton kinase inhibitors). NfLs were also adopted to monitor disease progression after natalizumab suspension in stable patients, cladribine efficacy after anti-CD20 discontinuation, and the efficacy of autologous hematopoietic stem cell transplant (AHSCT) compared to medical treatment. Nevertheless, further validation studies are needed for all considered fluid biomarkers to access clinical practice, and cost-effectiveness in the "real word" remains to be clarified.

Role of ferroptosis in neuroimmunity and neurodegeneration in multiple sclerosis revealed by multi-omics data

Previous studies have found that ferroptosis plays an important role in a variety of neurological diseases. However, the precise role of ferroptosis in the multiple sclerosis patients remains uncertain. We defined and validated a computational metric of ferroptosis levels. The ferroptosis scores were computed using the AUCell method, which reflects the enrichment scores of ferroptosis-related genes through gene ranking. The reliability of the ferroptosis score was assessed using various methods, involving cells induced to undergo ferroptosis by six different ferroptosis inducers. Through a comprehensive approach integrating snRNA-seq, spatial transcriptomics, and spatial proteomics data, we explored the role of ferroptosis in multiple sclerosis. Our findings revealed that among seven sampling regions of different white matter lesions, the edges of active lesions exhibited the highest ferroptosis score, which was associated with activation of the phagocyte system. Remyelination lesions exhibit the lowest ferroptosis score. In the cortex, ferroptosis score were elevated in neurons, relevant to a variety of neurodegenerative disease-related pathways. Spatial transcriptomics demonstrated a significant co-localization among ferroptosis score, neurodegeneration and microglia, which was verified by spatial proteomics. Furthermore, we established a diagnostic model of multiple sclerosis based on 24 ferroptosis-related genes in the peripheral blood. Ferroptosis might exhibits a dual role in the context of multiple sclerosis, relevant to both neuroimmunity and neurodegeneration, thereby presenting a promising and novel therapeutic target. Ferroptosis-related genes in the blood that could potentially serve as diagnostic and prognostic markers for multiple sclerosis.

Gas6/TAM system as potential biomarker for multiple sclerosis prognosis

Introduction

The protein growth arrest-specific 6 (Gas6) and its tyrosine kinase receptors Tyro-3, Axl, and Mer (TAM) are ubiquitous proteins involved in regulating inflammation and apoptotic body clearance. Multiple sclerosis (MS) is the most common inflammatory demyelinating disease of the central nervous system leading to progressive and irreversible disability if not diagnosed and treated promptly. Gas6 and TAM receptors have been associated with neuronal remyelination and stimulation of oligodendrocyte survival. However, few data are available regarding clinical correlation in MS patients. We aimed to evaluate soluble levels of these molecules in the cerebrospinal fluid (CSF) and serum at MS diagnosis and correlate them with short-term disease severity.

Methods

In a prospective cohort study, we enrolled 64 patients with a diagnosis of clinical isolated syndrome (CIS), radiological isolated syndrome (RIS) and relapsing-remitting (RR) MS according to the McDonald 2017 Criteria. Before any treatment initiation, we sampled the serum and CSF, and collected clinical data: disease course, presence of gadolinium-enhancing lesions, and expanded disability status score (EDSS). At the last clinical follow-up, we assessed EDSS and calculated MS severity score (MSSS) and age-related MS severity (ARMSS). Gas6 and TAM receptors were determined using an ELISA kit (R&D Systems) and compared to neurofilament (NFLs) levels evaluated with SimplePlex™ fluorescence-based immunoassay.

Results

At diagnosis, serum sAxl was higher in patients receiving none or low-efficacy disease-modifying treatments (DMTs) versus patients with high-efficacy DMTs (p = 0.04). Higher CSF Gas6 and serum sAXL were associated with an EDSS <3 at diagnosis (p = 0.04; p = 0.037). Serum Gas6 correlates to a lower MSSS (r2 = -0.32, p = 0.01). Serum and CSF NFLs were confirmed as disability biomarkers in our cohort according to EDSS (p = 0.005; p = 0.002) and MSSS (r2 = 0.27, p = 0.03; r2 = 0.39, p = 0.001). Results were corroborated using multivariate analysis.

Conclusions

Our data suggest a protective role of Gas6 and its receptors in patients with MS and suitable severity disease biomarkers.

Multimodal exercise training to reduce frailty in people with multiple sclerosis: study protocol for a pilot randomized controlled trial

BACKGROUND

Frailty, a syndrome characterized by decreased reserve and resistance to stressors across multiple physiologic systems, is highly prevalent in people living with multiple sclerosis (pwMS), independent of age or disability level. Frailty in MS is strongly associated with adverse clinical outcomes, such as falls, and may aggravate MS-related symptoms. Consequently, there is a pressing necessity to explore and evaluate strategies to reduce frailty levels in pwMS. The purpose of this pilot randomized controlled trial (RCT) will be to examine the feasibility and preliminary efficacy of a multimodal exercise training program to reduce frailty in pwMS.

METHODS

A total of 24 participants will be randomly assigned to 6 weeks of multimodal exercise or to a waitlist control group with a 1:1 allocation. PwMS aged 40-65 years and living with frailty will be eligible. The multimodal exercise program will consist of cognitive-motor rehabilitation (i.e., virtual reality treadmill training) combined with progressive, evidence-based resistance training. At baseline and post-intervention, participants will complete the Evaluative Frailty Index for Physical Activity (EFIP), measures of fall risk, and quality of life. Frailty-related biomarkers will also be assessed. In addition, the feasibility of the multimodal exercise program will be systematically and multidimensionally evaluated.

DISCUSSION

To date, no RCT has yet been conducted to evaluate whether targeted exercise interventions can minimize frailty in MS. The current study will provide novel data on the feasibility and preliminary efficacy of multimodal exercise training as a strategy for counteracting frailty in pwMS.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT06042244 (registered in September 2023).

Value contribution of blood-based neurofilament light chain as a biomarker in multiple sclerosis using multi-criteria decision analysis

Introduction

Multiple sclerosis (MS) is a chronic autoimmune demyelinating disease that represents a leading cause of non-traumatic disability among young and middle-aged adults. MS is characterized by neurodegeneration caused by axonal injury. Current clinical and radiological markers often lack the sensitivity and specificity required to detect inflammatory activity and neurodegeneration, highlighting the need for better approaches. After neuronal injury, neurofilament light chains (NfL) are released into the cerebrospinal fluid, and eventually into blood. Thus, blood-based NfL could be used as a potential biomarker for inflammatory activity, neurodegeneration, and treatment response in MS. The objective of this study was to determine the value contribution of blood-based NfL as a biomarker in MS in Spain using the Multi-Criteria Decision Analysis (MCDA) methodology.

Materials and methods

A literature review was performed, and the results were synthesized in the evidence matrix following the criteria included in the MCDA framework. The study was conducted by a multidisciplinary group of six experts. Participants were trained in MCDA and scored the evidence matrix. Results were analyzed and discussed in a group meeting through reflective MCDA discussion methodology.

Results

MS was considered a severe condition as it is associated with significant disability. There are unmet needs in MS as a disease, but also in terms of biomarkers since no blood biomarker is available in clinical practice to determine disease activity, prognostic assessment, and response to treatment. The results of the present study suggest that quantification of blood-based NfL may represent a safe option to determine inflammation, neurodegeneration, and response to treatments in clinical practice, as well as to complement data to improve the sensitivity of the diagnosis. Participants considered that blood-based NfL could result in a lower use of expensive tests such as magnetic resonance imaging scans and could provide cost-savings by avoiding ineffective treatments. Lower indirect costs could also be expected due to a lower impact of disability consequences. Overall, blood-based NfL measurement is supported by high-quality evidence.

Conclusion

Based on MCDA methodology and the experience of a multidisciplinary group of six stakeholders, blood-based NfL measurement might represent a high-value-option for the management of MS in Spain.

Biofluid-based Biomarkers in Traumatic Brain Injury: A Narrative Review

Traumatic brain injury (TBI) is a complex condition characterized by a multifaceted pathophysiology. It presents significant diagnostic and prognostic challenges in clinical settings. This narrative review explores the evolving role of biofluid biomarkers as essential tools in the diagnosis, prognosis, and treatment of TBI. In recent times, preclinical and clinical trials utilizing these biofluid biomarkers have been actively pursued internationally. Among the biomarkers for nerve tissue proteins are neuronal biomarkers like neuronal specific enolase and ubiquitin C-terminal hydrolase L1; astroglia injury biomarkers such as S100B and glial fibrillary acidic protein; axonal injury and demyelination biomarkers, including neurofilaments and myelin basic protein; new axonal injury and neurodegeneration biomarkers like total tau and phosphorylated tau; and others such as spectrin breakdown products and microtubule-associated protein 2. The interpretation of these biomarkers can be influenced by various factors, including secretion from organs other than the injury site and systemic conditions. This review highlights the potential of these biomarkers to transform TBI management and emphasizes the need for continued research to validate their efficacy, refine testing platforms, and ultimately improve patient care and outcomes.

Neutrophil to lymphocyte ratio and systemic immune-inflammatory index as markers of response to autologous hematopoietic stem cell transplantation in persons with multiple sclerosis

INTRODUCTION

Biomarkers that help to evaluate the immune system and could be useful in multiple sclerosis (MS) are the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and systemic immune-inflammatory index (SII). The objective of this work is to evaluate the significance of the SII index, PLR, and NLR before and after transplantation in individuals with MS who underwent autologous hematopoietic stem cell transplant (aHSCT) at a single institution.

METHODS

Patients with MS who received an aHSCT between 2017 and 2022 were included in the study. NLR, PLR, and SII index were calculated prior to the transplant and 100 days after, and evaluation of the expanded disability status scale (EDSS) was done before the transplant and 12 months after. The cohort was divided into two groups: aHSCT responders (R) and nonresponders (NR).

RESULTS

Fifty-eight individuals were examined: 37 patients in the responders group R group and 21 in NR group. There was no statistically significant difference in the SII, NLR, and PLR prior to the transplant, however at 100 days post-HSCT, NLR in the R group was 1.8 versus 3.1 in the NR group (p = 0.003), PLR was 194 versus 295, respectively (p = 0.024), meanwhile SII index was 489.5 versus 729.3 (p < 0.001).

CONCLUSION

High NLR and SII index values after the aHSCT were associated with a worsening in the EDSS score. However, since this is the first ever study that compared NLR and SII index with the aHSCT response in persons with MS, further studies must be performed to corroborate this information.

Recent Advances in Biosensors for Diagnosis of Autoimmune Diseases

Over the last decade, autoimmune diseases (ADs) have undergone a significant increase because of genetic and/or environmental factors; therefore, their simple and fast diagnosis is of high importance. The conventional diagnostic techniques for ADs require tedious sample preparation, sophisticated instruments, a dedicated laboratory, and qualified personnel. For these reasons, biosensors could represent a useful alternative to these methods. Biosensors are considered to be promising tools that can be used in clinical analysis for an early diagnosis due to their high sensitivity, simplicity, low cost, possible miniaturization (POCT), and potential ability for real-time analysis. In this review, recently developed biosensors for the detection of autoimmune disease biomarkers are discussed. In the first part, we focus on the main AD biomarkers and the current methods of their detection. Then, we discuss the principles and different types of biosensors. Finally, we overview the characteristics of biosensors based on different bioreceptors reported in the literature.

A Radiomic "Warning Sign" of Progression on Brain MRI in Individuals with MS

BACKGROUND AND PURPOSE

MS is a chronic progressive, idiopathic, demyelinating disorder whose diagnosis is contingent on the interpretation of MR imaging. New MR imaging lesions are an early biomarker of disease progression. We aimed to evaluate a machine learning model based on radiomics features in predicting progression on MR imaging of the brain in individuals with MS.

MATERIALS AND METHODS

This retrospective cohort study with external validation on open-access data obtained full ethics approval. Longitudinal MR imaging data for patients with MS were collected and processed for machine learning. Radiomics features were extracted at the future location of a new lesion in the patients' prior MR imaging ("prelesion"). Additionally, "control" samples were obtained from the normal-appearing white matter for each participant. Machine learning models for binary classification were trained and tested and then evaluated the external data of the model.

RESULTS

The total number of participants was 167. Of the 147 in the training/test set, 102 were women and 45 were men. The average age was 42 (range, 21-74 years). The best-performing radiomics-based model was XGBoost, with accuracy, precision, recall, and F1-score of 0.91, 0.91, 0.91, and 0.91 on the test set, and 0.74, 0.74, 0.74, and 0.70 on the external validation set. The 5 most important radiomics features to the XGBoost model were associated with the overall heterogeneity and low gray-level emphasis of the segmented regions. Probability maps were produced to illustrate potential future clinical applications.

CONCLUSIONS

Our machine learning model based on radiomics features successfully differentiated prelesions from normal-appearing white matter. This outcome suggests that radiomics features from normal-appearing white matter could serve as an imaging biomarker for progression of MS on MR imaging.

Role of microRNAs in Immune Regulation with Translational and Clinical Applications

MicroRNAs (miRNAs) are 19-23 nucleotide long, evolutionarily conserved noncoding RNA molecules that regulate gene expression at the post-transcriptional level. In this review, involvement of miRNAs is summarized in the differentiation and function of immune cells, in anti-infective immune responses, immunodeficiencies and autoimmune diseases. Roles of miRNAs in anticancer immunity and in the transplantation of solid organs and hematopoietic stem cells are also discussed. Major focus is put on the translational clinical applications of miRNAs, including the establishment of noninvasive biomarkers for differential diagnosis and prediction of prognosis. Patient selection and response prediction to biological therapy is one of the most promising fields of application. Replacement or inhibition of miRNAs has enormous therapeutic potential, with constantly expanding possibilities. Although important challenges still await solutions, evaluation of miRNA fingerprints may contribute to an increasingly personalized management of immune dysregulation with a remarkable reduction in toxicity and treatment side effects. More detailed knowledge of the molecular effects of physical exercise and nutrition on the immune system may facilitate self-tailored lifestyle recommendations and advances in prevention.

Recent Advances in Diagnostic, Prognostic, and Disease-Monitoring Biomarkers in Multiple Sclerosis

Multiple sclerosis (MS) is a highly heterogeneous disease. Currently, a combination of clinical features, MRI, and cerebrospinal fluid markers are used in clinical practice for diagnosis and treatment decisions. In recent years, there has been considerable effort to develop novel biomarkers that better reflect the pathologic substrates of the disease to aid in diagnosis and early prognosis, evaluation of ongoing inflammatory activity, detection and monitoring of disease progression, prediction of treatment response, and monitoring of disease-modifying treatment safety. In this review, the authors provide an overview of promising recent developments in diagnostic, prognostic, and disease-monitoring/treatment-response biomarkers in MS.

Serum S100A8/A9 and MMP-9 levels are elevated in systemic lupus erythematosus patients with cognitive impairment

Objective

Cognitive impairment (CI) is one of the most common manifestations of Neuropsychiatric Systemic Lupus Erythematosus (NPSLE). Despite its frequency, we have a limited understanding of the underlying immune mechanisms, resulting in a lack of pathways to target. This study aims to bridge this gap by investigating differences in serum analyte levels in SLE patients based on their cognitive performance, independently from the attribution to SLE, and exploring the potential for various serum analytes to differentiate between SLE patients with and without CI.

Methods

Two hundred ninety individuals aged 18-65 years who met the 2019-EULAR/ACR classification criteria for SLE were included. Cognitive function was measured utilizing the adapted ACR-Neuropsychological Battery (ACR-NB). CI was defined as a z-score of ≤-1.5 in two or more domains. The serum levels of nine analytes were measured using ELISA. The data were randomly partitioned into a training (70%) and a test (30%) sets. Differences in the analyte levels between patients with and without CI were determined; and their ability to discriminate CI from non-CI was evaluated.

Results

Of 290 patients, 40% (n=116) had CI. Serum levels of S100A8/A9 and MMP-9, were significantly higher in patients with CI (p=0.006 and p=0.036, respectively). For most domains of the ACR-NB, patients with CI had higher S100A8/A9 serum levels than those without. Similarly, S100A8/A9 had a negative relationship with multiple CI tests and the highest AUC (0.74, 95%CI: 0.66-0.88) to differentiate between patients with and without CI.

Conclusion

In this large cohort of well-characterized SLE patients, serum S100A8/A9 and MMP-9 were elevated in patients with CI. S100A8/A9 had the greatest discriminatory ability in differentiating between patients with and without CI.

Cortical Thin Patch Fraction Reflects Disease Burden in MS: The Mosaic Approach

BACKGROUND AND PURPOSE

GM pathology plays an essential role in MS disability progression, emphasizing the importance of neuroradiologic biomarkers to capture the heterogeneity of cortical disease burden. This study aimed to assess the validity of a patch-wise, individual interpretation of cortical thickness data to identify GM pathology, the "mosaic approach," which was previously suggested as a biomarker for assessing and localizing atrophy.

MATERIALS AND METHODS

We investigated the mosaic approach in a cohort of 501 patients with MS with respect to 89 internal and 651 external controls. The resulting metric of the mosaic approach is the so-called thin patch fraction, which is an estimate of overall cortical disease burden per patient. We evaluated the mosaic approach with respect to the following: 1) discrimination between patients with MS and controls, 2) classification between different MS phenotypes, and 3) association with established biomarkers reflecting MS disease burden, using general linear modeling.

RESULTS

The thin patch fraction varied significantly between patients with MS and healthy controls and discriminated among MS phenotypes. Furthermore, the thin patch fraction was associated with disease burden, including the Expanded Disability Status Scale, cognitive and fatigue scores, and lesion volume.

CONCLUSIONS

This study demonstrates the validity of the mosaic approach as a neuroradiologic biomarker in MS. The output of the mosaic approach, namely the thin patch fraction, is a candidate biomarker for assessing and localizing cortical GM pathology. The mosaic approach can furthermore enhance the development of a personalized cortical MS biomarker, given that the thin patch fraction provides a feature on which artificial intelligence methods can be trained. Most important, we showed the validity of the mosaic approach when referencing data with respect to external control MR imaging repositories.

Neurofilament Light Chain in Adult and Pediatric Multiple Sclerosis: A Promising Biomarker to Better Characterize Disease Activity and Personalize MS Treatment

Many biological markers have been explored in multiple sclerosis (MS) to better quantify disease burden and better evaluate response to treatments, beyond clinical and MRI data. Among these, neurofilament light chain (Nf-L), although non-specific for this disease and found to be increased in other neurological conditions, has been shown to be the most promising biomarker for assessing axonal damage in MS, with a definite role in predicting the development of MS in patients at the first neurological episode suggestive of MS, and also in a preclinical phase. There is strong evidence that Nf-L levels are increased more in relapsing versus stable MS patients, and that they predict future disease evolution (relapses, progression, MRI measures of activity/progression) in MS patients, providing information on response to therapy, helping to anticipate clinical decisions in patients with an apparently stable evolution, and identifying patient non-responders to disease-modifying treatments. Moreover, Nf-L can contribute to the better understanding of the mechanisms of demyelination and axonal damage in adult and pediatric MS. A fundamental requirement for its clinical use is the accurate standardization of normal values, corrected for confounding factors, in particular age, sex, body mass index, and presence of comorbidities. In this review, a guide is provided to update clinicians on the use of Nf-L in clinical activity.

The Comparison of the Selected Parameters of Brain Injury and Interleukins in the CSF in Patients Diagnosed De Novo with RRMS Compared to the Control Group

BACKGROUND

Multiple sclerosis (MS) is a chronic autoimmune disorder affecting the central nervous system (CNS). Due to the different phenotypes of the disease and non-specific symptoms of MS, there is a great need for a validated panel of biomarkers to facilitate the diagnosis, predict disease progression, and evaluate treatment outcomes.

METHODS

We determined the levels of the parameters of brain injury (NF-H, GPAF, S100B, and UCHL1) and the selected cytokines in the cerebrospinal fluid (CSF) in 101 patients diagnosed de novo with RRMS and 75 healthy controls. All determinations were made using the Bio-Plex method.

RESULTS

We found higher levels of NF-H and GFAP in the relapsing-remitting multiple sclerosis (RRMS) group compared to the controls. The concentrations of both molecules were significantly increased in patients with Gd+ lesions on brain MRI. The level of S100B did not differ significantly between the groups. UCHL1 concentrations were higher in the control group. We found some correlations between the selected cytokines, the levels of the parameters of brain injury, and the time from the first symptoms to the diagnosis of MS.

CONCLUSIONS

The role of the above molecules in MS is promising. However, further research is warranted to define their precise functions.

Protein Biomarkers Shared by Multiple Neurodegenerative Diseases Are Calmodulin-Binding Proteins Offering Novel and Potentially Universal Therapeutic Targets

Seven major neurodegenerative diseases and their variants share many overlapping biomarkers that are calmodulin-binding proteins: Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), frontotemporal lobar dementia (FTD), Huntington's disease (HD), Lewy body disease (LBD), multiple sclerosis (MS), and Parkinson's disease (PD). Calcium dysregulation is an early and persistent event in each of these diseases, with calmodulin serving as an initial and primary target of increased cytosolic calcium. Considering the central role of calcium dysregulation and its downstream impact on calcium signaling, calmodulin has gained interest as a major regulator of neurodegenerative events. Here, we show that calmodulin serves a critical role in neurodegenerative diseases via binding to and regulating an abundance of biomarkers, many of which are involved in multiple neurodegenerative diseases. Of special interest are the shared functions of calmodulin in the generation of protein biomarker aggregates in AD, HD, LBD, and PD, where calmodulin not only binds to amyloid beta, pTau, alpha-synuclein, and mutant huntingtin but also, via its regulation of transglutaminase 2, converts them into toxic protein aggregates. It is suggested that several calmodulin binding proteins could immediately serve as primary drug targets, while combinations of calmodulin binding proteins could provide simultaneous insight into the onset and progression of multiple neurodegenerative diseases.

Disease activity in primary progressive multiple sclerosis: a systematic review and meta-analysis

Background

Disease activity in multiple sclerosis (MS) is defined as presence of relapses, gadolinium enhancing lesions and/or new or enlarging lesions on MRI. It is associated with efficacy of immunomodulating therapies (IMTs) in primary progressive MS (PPMS). However, a thorough review on disease activity in PPMS is lacking. In relapsing remitting MS, the prevalence of activity decreases in more contemporary cohorts. For PPMS, this is unknown.

Aim

To review disease activity in PPMS cohorts and identify its predictors.

Methods

A systematic search in EMBASE, MEDLINE, Web of science Core Collection, COCHRANE CENTRAL register of trials, and GOOGLE SCHOLAR was performed. Keywords included PPMS, inflammation, and synonyms. We included original studies with predefined available data, extracted cohort characteristics and disease activity outcomes and performed meta-regression analyses.

Results

We included 34 articles describing 7,109 people with PPMS (pwPPMS). The weighted estimated proportion of pwPPMS with overall disease activity was 26.8% (95% CI 20.6-34.0%). A lower age at inclusion predicted higher disease activity (OR 0.91, p = 0.031). Radiological activity (31.9%) was more frequent than relapses (9.2%), and was predicted by longer follow-up duration (OR 1.27, p = 0.033). Year of publication was not correlated with disease activity.

Conclusion

Inflammatory disease activity is common in PPMS and has remained stable over the last decades. Age and follow-up duration predict disease activity, advocating prolonged monitoring of young pwPPMS to evaluate potential IMT benefits.

The fluctuations of expression profiles of critical genes in the miRNA maturation process and pro-and anti-inflammatory cytokines in the pathogenesis and progression of multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a central nervous system disease known for immune-mediated demyelination, inflammatory, and neurodegeneration symptoms. Discovering molecular biomarkers to classify RRMS and SPMS patients, monitor the disease activity, and response to particular treatments is one area that has received notable attraction. MicroRNA (miRNA), a single-stranded non-coding RNA molecule, is a significant regulator of gene expression recruited in pathogenic mechanisms in diverse diseases, especially cancer and MS. Also, the relapsing-remitting features of MS exhibit that both inflammatory and anti-inflammatory cytokines are effective in the progression of the disease over time.

METHODS AND RESULTS

It was assessed the expression patterns of the genes (Drosha, Pasha (DGCR8), and Dicer ) encoding the critical enzymes in the processing steps of miRNA maturation and major pro-inflammatory and anti-inflammatory cytokines (IFN-α, IFN-β, and IL-6) in blood cells of 40 MS patients (two groups of 10 men and women in both clinical courses of RR and SPMS patients) in comparison with 20 healthy control group (10 males and 10 females). The highest transcription activity of Drosha was observed for RRMS patients (4.2 and 3.6-fold, respectively), and the expression ratio was down regulated in male and female patients with SPMS (3.9- and 3.1-fold, respectively). Considering the studied cytokines, the increase in expression ratio of IL-6 in SPMS patients and the decrease in transcript abundance of INF-α, and INF-β cytokines are consistent with the progression of the disease.

CONCLUSIONS

Our findings showed that the high and low transcriptional levels of the considered genes seem to be effective in the pathogenesis and progression of MS.

The role of miRNAs in multiple sclerosis pathogenesis, diagnosis, and therapeutic resistance

In recent years, microRNAs (miRNAs) have gained increased attention from researchers around the globe. Although it is twenty nucleotides long, it can modulate several gene targets simultaneously. Their mal expression is a signature of various pathologies, and they provide the foundation to elucidate the molecular mechanisms of each pathology. Among the debilitating central nervous system (CNS) disorders with a growing prevalence globally is the multiple sclerosis (MS). Moreover, the diagnosis of MS is challenging due to the lack of disease-specific biomarkers, and the diagnosis mainly depends on ruling out other disabilities. MS could adversely affect patients' lives through its progression, and only symptomatic treatments are available as therapeutic options, but an exact cure is yet unavailable. Consequently, this review hopes to further the study of the biological features of miRNAs in MS and explore their potential as a therapeutic target.

Improving the efficiency of free kappa light chains as diagnostic biomarker of Multiple Sclerosis by using a novel algorithm

BACKGROUND

Intrathecal immunoglobulin synthesis (ITS) plays a crucial role in the diagnosis of multiple sclerosis (MS). Traditionally, the gold standard method for detecting ITS has been through the analysis of oligoclonal bands (OCB). However, the paradigm has shifted with the introduction of the free kappa light chains (FKLC) method. In fact, a recent consensus recommends evaluating FKLC index (FKLCi) as the primary approach and reserving oligoclonal bands with borderline results. The objective of our study is to investigate the diagnostic efficiency of combining FKLC with other methods to predict ITS while minimizing the reliance on OCB.

METHODS

A total of 192 patients were included in the study, consisting of 145 individuals diagnosed with multiple sclerosis (pwMS) and 46 with other neurological diseases (controls). Among the MS cases, 100 patients were assigned to the Training Cohort (TC), while an external Validation Cohort (VC) comprised of 45 MS patients was established. Diagnostic efficiency was assessed for FKLCi, OCB, Link index, and the Reiber formula for IgG and FKLC. Optimal cutoff values for Link index and FKLCi were also determined. The last procedure was developed for diverse algorithms using the parameters mentioned above, which included the optimal cutoffs previously obtained. The calculations were conducted independently for both the TC and the VC, as well as for a composite cohort formed by combining data from all patients (OC) RESULTS: One algorithm, named KRO, was developed based on the determination of FKLCi and Reiber Formula as the primary diagnostic parameters. For cases where the FKLCi result was mildly increased, OCB was utilized as a supplementary test. The KRO algorithm demonstrated superior diagnostic accuracy in the OC (89%), resulting in a reduction of OCB consumption by 91%.

DISCUSSION

The KRO algorithm demonstrated superior sensitivity and accuracy although lower specificity and NPV compared to the use of FKLCi and OCB alone. The present research aligns with the new consensus recommendations regarding the diagnostic approach. Our findings indicate that employing a combined marker approach via KRO could prove to be a proficient screening tool for multiple sclerosis. This approach also holds the potential to address inherent limitations associated with each individual marker. However, to further validate and solidify the efficacy of our algorithm, additional studies involving larger cohorts are warranted.

Association between serum multi-protein biomarker profile and real-world disability in multiple sclerosis

Few studies examined blood biomarkers informative of patient-reported outcome (PRO) of disability in people with multiple sclerosis (MS). We examined the associations between serum multi-protein biomarker profiles and patient-reported MS disability. In this cross-sectional study (2017-2020), adults with diagnosis of MS (or precursors) from two independent clinic-based cohorts were divided into a training and test set. For predictors, we examined seven clinical factors (age at sample collection, sex, race/ethnicity, disease subtype, disease duration, disease-modifying therapy [DMT], and time interval between sample collection and closest PRO assessment) and 19 serum protein biomarkers potentially associated with MS disease activity endpoints identified from prior studies. We trained machine learning (ML) models (Least Absolute Shrinkage and Selection Operator regression [LASSO], Random Forest, Extreme Gradient Boosting, Support Vector Machines, stacking ensemble learning, and stacking classification) for predicting Patient Determined Disease Steps (PDDS) score as the primary endpoint and reported model performance using the held-out test set. The study included 431 participants (mean age 49 years, 81% women, 94% non-Hispanic White). For binary PDDS score, combined feature input of routine clinical factors and the 19 proteins consistently outperformed base models (comprising clinical features alone or clinical features plus one single protein at a time) in predicting severe (PDDS ≥ 4) versus mild/moderate (PDDS < 4) disability across multiple machine learning approaches, with LASSO achieving the best area under the curve (AUCPDDS = 0.91) and other metrics. For ordinal PDDS score, LASSO model comprising combined clinical factors and 19 proteins as feature input (R2PDDS = 0.31) again outperformed base models. The two best-performing LASSO models (i.e., binary and ordinal PDDS score) shared six clinical features (age, sex, race/ethnicity, disease subtype, disease duration, DMT efficacy) and nine proteins (cluster of differentiation 6, CUB-domain-containing protein 1, contactin-2, interleukin-12 subunit-beta, neurofilament light chain [NfL], protogenin, serpin family A member 9, tumor necrosis factor superfamily member 13B, versican). By comparison, LASSO models with clinical features plus one single protein at a time as feature input did not select either NfL or glial fibrillary acidic protein (GFAP) as a final feature. Forcing either NfL or GFAP as a single protein feature into models did not improve performance beyond clinical features alone. Stacking classification model using five functional pathways to represent multiple proteins as meta-features implicated those involved in neuroaxonal integrity as significant contributors to predictive performance. Thus, serum multi-protein biomarker profiles improve the prediction of real-world MS disability status beyond clinical profile alone or clinical profile plus single protein biomarker, reaching clinically actionable performance.

Data Mining of Microarray Datasets in Translational Neuroscience

Data mining involves the computational analysis of a plethora of publicly available datasets to generate new hypotheses that can be further validated by experiments for the improved understanding of the pathogenesis of neurodegenerative diseases. Although the number of sequencing datasets is on the rise, microarray analysis conducted on diverse biological samples represent a large collection of datasets with multiple web-based programs that enable efficient and convenient data analysis. In this review, we first discuss the selection of biological samples associated with neurological disorders, and the possibility of a combination of datasets, from various types of samples, to conduct an integrated analysis in order to achieve a holistic understanding of the alterations in the examined biological system. We then summarize key approaches and studies that have made use of the data mining of microarray datasets to obtain insights into translational neuroscience applications, including biomarker discovery, therapeutic development, and the elucidation of the pathogenic mechanisms of neurodegenerative diseases. We further discuss the gap to be bridged between microarray and sequencing studies to improve the utilization and combination of different types of datasets, together with experimental validation, for more comprehensive analyses. We conclude by providing future perspectives on integrating multi-omics, to advance precision phenotyping and personalized medicine for neurodegenerative diseases.

Gut Microbial Metabolome and Dysbiosis in Neurodegenerative Diseases: Psychobiotics and Fecal Microbiota Transplantation as a Therapeutic Approach-A Comprehensive Narrative Review

The comprehensive narrative review conducted in this study delves into the mechanisms of communication and action at the molecular level in the human organism. The review addresses the complex mechanism involved in the microbiota-gut-brain axis as well as the implications of alterations in the microbial composition of patients with neurodegenerative diseases. The pathophysiology of neurodegenerative diseases with neuronal loss or death is analyzed, as well as the mechanisms of action of the main metabolites involved in the bidirectional communication through the microbiota-gut-brain axis. In addition, interventions targeting gut microbiota restructuring through fecal microbiota transplantation and the use of psychobiotics-pre- and pro-biotics-are evaluated as an opportunity to reduce the symptomatology associated with neurodegeneration in these pathologies. This review provides valuable information and facilitates a better understanding of the neurobiological mechanisms to be addressed in the treatment of neurodegenerative diseases.

The association between disability progression, relapses, and treatment in early relapse onset MS: an observational, multi-centre, longitudinal cohort study

The indirect contribution of multiple sclerosis (MS) relapses to disability worsening outcomes, and vice-versa, remains unclear. Disease modifying therapies (DMTs) are potential modulators of this association. Understanding how these endo-phenotypes interact may provide insights into disease pathogenesis and treatment practice in relapse-onset MS (ROMS). Utilising a unique, prospectively collected clinical data from a longitudinal cohort of 279 first demyelinating event cases followed for up to 15 years post-onset, we examined indirect associations between relapses and treatment and the risk of disability worsening, and vice-versa. Indirect association parameters were estimated using joint models for longitudinal and survival data. Early relapses within 2.5 years of MS onset predicted early disability worsening outcomes (HR = 3.45, C.I 2.29-3.61) per relapse, but did not contribute to long-term disability worsening thereinafter (HR = 0.21, C.I 0.15-0.28). Conversely, disability worsening outcomes significantly contributed to relapse risk each year (HR = 2.96, C.I 2.91-3.02), and persisted over time (HR = 3.34, C.I 2.90-3.86), regardless of DMT treatments. The duration of DMTs significantly reduced the hazards of relapses (1st-line DMTs: HR = 0.68, C.I 0.58-0.79; 3rd-line DMTs: HR = 0.37, C.I 0.32-0.44) and disability worsening events (1st-line DMTs: HR = 0.74, C.I 0.69-0.79; 3rd-line DMTs: HR = 0.90, C.I 0.85-0.95), respectively. Results from time-dynamic survival probabilities further revealed individuals having higher risk of future relapses and disability worsening outcomes, respectively. The study provided evidence that in ROMS, relapses accrued within 2.5 years of MS onset are strong indicators of disability worsening outcomes, but late relapses accrued 2.5 years post onset are not overt risk factors for further disability worsening. In contrast, disability worsening outcomes are strong positive predictors of current and subsequent relapse risk. Long-term DMT use and older age strongly influence the individual outcomes and their associations.

Personality Traits and Fatigue in Multiple Sclerosis: A Narrative Review

(1) Background: Multiple sclerosis (MS) is a chronic neurodegenerative autoimmune disease. Fatigue is a prevalent and debilitating symptom that significantly impacts the quality of life of these patients. A relationship between personality traits and fatigue in MS has been hypothesized but not clearly defined. (2) Methods: A literature search was carried out from databases up to April 2023 for studies correlating personality traits and fatigue in patients suffering from MS. (3) Results: A total of ten articles was included; most of the studies depict a neuroticism-fatigue correlation; however, they were not consistent in terms of the fatigue, personality, and covariate assessments. (4) Conclusions: The clinical and methodological heterogeneity of the included studies prevented us from drawing any firm conclusion on the link between personality traits and fatigue in MS. Several models of personality and different fatigue assessments have been found. Despite this, a common pathway shows that the neuroticism trait or similar personality patterns has a role in fatigue diagnosis. This may be a useful target to improve the quality of life and enhance the modification of the disease treatment results. Further homogeneous and longitudinal studies are needed.

A Comparison of Two Analytical Approaches for the Quantification of Neurofilament Light Chain, a Biomarker of Axonal Damage in Multiple Sclerosis

Neurofilament light chain (NfL), is a neuron-specific cytoskeletal protein detected in extracellular fluid following axonal damage. Extensive research has focused on NfL quantification in CSF, establishing it as a prognostic biomarker of disability progression in Multiple Sclerosis (MS). Our study used a new commercially available Enzyme-Linked Immunosorbent Assay (ELISA) kit and Single Molecular Array (Simoa) advanced technology to assess serum NfL levels in MS patients and Healthy Controls (HC). Verifying the most accurate, cost-effective methodology will benefit its application in clinical settings. Blood samples were collected from 54 MS patients and 30 HC. Protocols accompanying the kits were followed. The ELISA thershold was set as 3 S.D. above the mean of the HC. For Simoa, the Z-score calculation created by Jens Kuhle's group was applied (with permission). Samples exceeding the threshold or z-score ≥1.5 indicated subclinical disease activity. To our knowledge, this is the first study to find strong-positive correlation between ELISA and Simoa for the quantification of NfL in serum (r = 0.919). Despite the strong correlation, Simoa has better analytical sensitivity and can detect small changes in samples making it valuable in clinical settings. Further research is required to evaluate whether serum NfL quantification using ELISA could be utilized to predict disability progression.

Genetic Basis of Inflammatory Demyelinating Diseases of the Central Nervous System: Multiple Sclerosis and Neuromyelitis Optica Spectrum

Demyelinating diseases alter myelin or the coating surrounding most nerve fibers in the central and peripheral nervous systems. The grouping of human central nervous system demyelinating disorders today includes multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) as distinct disease categories. Each disease is caused by a complex combination of genetic and environmental variables, many involving an autoimmune response. Even though these conditions are fundamentally similar, research into genetic factors, their unique clinical manifestations, and lesion pathology has helped with differential diagnosis and disease pathogenesis knowledge. This review aims to synthesize the genetic approaches that explain the differential susceptibility between these diseases, explore the overlapping clinical features, and pathological findings, discuss existing and emerging hypotheses on the etiology of demyelination, and assess recent pathogenicity studies and their implications for human demyelination. This review presents critical information from previous studies on the disease, which asks several questions to understand the gaps in research in this field.

Plasma neurofilament light chain in children with relapsing MS receiving teriflunomide or placebo: A post hoc analysis of the randomized TERIKIDS trial

BACKGROUND

The phase 3 TERIKIDS study demonstrated efficacy and manageable safety for teriflunomide versus placebo in children with relapsing multiple sclerosis (RMS).

OBJECTIVE

Evaluate plasma neurofilament light chain (pNfL) concentrations in TERIKIDS.

METHODS

Patients received placebo or teriflunomide (14 mg adult equivalent) for up to 96 weeks in the double-blind (DB) period. In the open-label extension (OLE), all patients received teriflunomide until up to 192 weeks after randomization. pNfL was measured using single-molecule array assay (Simoa^® NF-light^™).

RESULTS

Baseline mean age was 14.5 years; 69.4% were female. Baseline geometric least square mean pNfL levels were similar for teriflunomide (n = 78) and placebo (n = 33) patients (19.83 vs 18.30 pg/mL). Over the combined DB and OLE periods, pNfL values were lower for teriflunomide versus placebo (analysis of variance p < 0.01; Week 192: 10.61 vs 17.32 pg/mL). Observed between-group pNfL differences were attenuated upon adjustment for gadolinium (Gd)-enhancing or new/enlarged T2 lesion counts at DB Week 24. Higher baseline pNfL levels were associated with shorter time since first MS symptom onset, higher baseline Gd-enhancing lesion counts and T2 lesion volume, and increased hazard of high magnetic resonance imaging activity or clinical relapse during the DB period.

CONCLUSION

Teriflunomide treatment was associated with significantly reduced pNfL levels in children with RMS.

CLINICALTRIALS.GOV IDENTIFIER

NCT02201108.

Ceramide is implicated in humoral peripheral and intrathecal autoimmune response in MS patients

BACKGROUND

The disturbed metabolism of ceramide (Cer) is supposed to evoke the autoimmune response, contributing to MS pathology.

OBJECTIVES

To determine levels of anti-Cer immunoglobulins G (IgGs) in the CSF and serum of subjects with various phenotypes of MS, and to investigate relationships between levels of anti-Cer antibodies and MS-related variables.

METHODS

IgGs isolated from serum and the CSF of 68 MS patients and appropriate controls were examined for their reactivity to Cer subspecies. Their levels were compared between the studied groups and compartments, and analyzed with regard to clinical variables.

RESULTS

Increased levels of anti-C16:0-, C18:0-, C18:1-, C24:0- and C24:1-Cer IgGs were detected in the CSF and serum of MS patients in comparison with controls. For IgGs against particular Cer subspecies, correlations were found between their CSF and serum level, as well as with the Link index. Serum and the CSF anti-Cer IgGs differed between patients with clinically isolated syndrome (CIS) and relapsing-remitting MS from those with progressive MS. No correlations were found between anti-Cer IgGs and other MS-related clinical variables.

CONCLUSION

Patients with MS have shown altered panels of anti-Cer IgGs in the CSF and serum, which might suggest a relevant, though limited role of Cer as a target for autoimmune humoral response. Utility of antibodies against Cer subspecies as potential markers for MS activity and progression deserves further investigations.

Differential proteomic profile of lumbar and ventricular cerebrospinal fluid

BACKGROUND

Pathological cerebral conditions may manifest in altered composition of the cerebrospinal fluid (CSF). Although diagnostic CSF analysis seeks to establish pathological disturbances in the brain proper, CSF is generally sampled from the lumbar compartment for reasons of technical ease and ethical considerations. We here aimed to compare the molecular composition of CSF obtained from the ventricular versus the lumbar CSF compartments to establish a relevance for employing lumbar CSF as a proxy for the CSF bathing the brain tissue.

METHODS

CSF was collected from 46 patients with idiopathic normal pressure hydrocephalus (iNPH) patients during their diagnostic workup (lumbar samples) and in connection with their subsequent CSF diversion shunt surgery (ventricular samples). The mass-spectrometry-based proteomic profile was determined in these samples and in addition, selected biomarkers were quantified with ELISA (S100B, neurofilament light (NfL), amyloid-β (Aβ₄₀, Aβ₄₂), and total tau (T-tau) and phosphorylated tau (P-tau) forms). The latter analysis was extended to include paired porcine samples obtained from the lumbar compartment and the cerebromedullary cistern closely related to the ventricles.

RESULTS

In total 1231 proteins were detected in the human CSF. Of these, 216 distributed equally in the two CSF compartments, whereas 22 were preferentially (or solely) present in the ventricular CSF and four in the lumbar CSF. The selected biomarkers of neurodegeneration and Alzheimer's disease displayed differential distribution, some with higher (S100B, T-tau, and P-tau) and some with lower (NfL, Aβ₄₀, Aβ₄₂) levels in the ventricular compartment. In the porcine samples, all biomarkers were most abundant in the lumbar CSF.

CONCLUSIONS

The overall proteomic profile differs between the ventricular and the lumbar CSF compartments, and so does the distribution of clinically employed biomarkers. However, for a range of CSF proteins and biomarkers, one can reliably employ lumbar CSF as a proxy for ventricular CSF if or a lumbar/cranial index for the particular molecule has been established. It is therefore important to verify the compartmental preference of the proteins or biomarkers of interest prior to extrapolating from lumbar CSF to that of the ventricular fluid bordering the brain.

MicroRNAs expression in peripheral blood mononuclear cells of patients with multiple sclerosis propose

BACKGROUND

MicroRNAs (miRs) are involved in the autoimmune and neurological diseases, including multiple sclerosis (MS), through modulating post-transcriptional gene regulation. Accumulating evidence indicates that miR-10, miR-24a, miR-124, and miR-21 play an imperative role in MS pathogenesis. Therefore, the current research aimed to analyze the expression of the selected miRNAs for MS in Iranian population.

METHODS AND RESULTS

Blood sample of 75 relapsing-remitting MS (RRMS) patients and 75 healthy individuals suffering no neurodegenerative illness was collected. Subsequently, the isolation of peripheral blood mononuclear cells (PBMCs) was performed by employing Ficoll-Hypaque density gradient method. Afterward, total RNA was extracted and subjected to qRT-PCR analysis. The obtained results evidenced that the relative expression of miR-10 (P = 0.0002), miR-21 (P = 0.0014), and miR-124 (P = 0.0091) significantly decreased in RRMS patients compared to healthy participants. On the contrary, no notable change was observed between the studies groups regarding miR-24a expression levels (P = 0.107). ROC curve analysis estimated an area under the curve (AUC) value equal to 0.75 with P = 0.0006 for miR-10, while it was decreased for miR-21 (AUC = 0.67 and P = 0.0054) and miR-124 (AUC = 0.66 and P = 0.012).

CONCLUSION

The change in miR-10, miR-124, and miR-21 expression patterns was implied to participate in MS development. Further large scale observational studies are recommended.

[Traumatic brain injury before the multiple sclerosis onset: a relationship with the progression of neurological disorders and pathobiochemical markers of the cerebrospinal fluid]

OBJECTIVE

To evaluate the association of traumatic brain injury (TBI) before the multiple sclerosis (MS) onset with the rate of progression of neurological disorders and cerebrospinal fluid markers of blood-brain barrier permeability, inflammation, demyelination, and gliosis.

MATERIAL AND METHODS

Patients with relapsing-remitting MS in the Altai region of Russia with/without TBI before the MS onset (n=44; 19 men, 25 women in each group) participated in a prospective, controlled, randomized study. Disability rate was assessed retrospectively. Pleocytosis, levels of protein, albumin, C-reactive protein, TNF-alpha, myelin basic protein, S100 protein were measured in the cerebrospinal fluid in subgroups of patients (n=14 in each group) in MS remission and exacerbation.

RESULTS

Concussion and mild brain contusion were documented in the group of patients with TBI before the MS onset in 35 (79.5%) and 9 (20.5%) patients, respectively. Traumatic brain injury was over the age of 15 in 72.5% of patients. The rate of MS progression was higher in the group with TBI compared to the group without TBI (0.76±1.28 and 0.40±0.43 EDSS points per year, respectively; p=0.014). TBI before the MS onset increases the risk of disability by more than 0.25 EDSS points per year (OR 2.74; 95 CI 1.10-6.85; p=0.029). Intergroup differences in cerebrospinal fluid parameters were not found either during MS exacerbation or remission.

CONCLUSION

Concussion or mild brain contusion before the MS onset may be factors influencing the progression of neurological deficit in MS. It seems relevant to study the mechanisms of adverse effects of TBI on the MS progression.

Development of an ultrasensitive microfluidic assay for the analysis of Glial fibrillary acidic protein (GFAP) in blood

Introduction: A rapid and reliable detection of glial fibrillary acidic protein (GFAP) in biological samples could assist in the diagnostic evaluation of neurodegenerative disorders. Sensitive assays applicable in the routine setting are needed to validate the existing GFAP tests. This study aimed to develop a highly sensitive and clinically applicable microfluidic immunoassay for the measurement of GFAP in blood. Methods: A microfluidic GFAP assay was developed and validated regarding its performance. Subsequently, serum and cerebrospinal fluid (CSF) of Alzheimer's disease (AD), Multiple Sclerosis (MS) and control patients were analyzed with the established assay, and levels were compared to the commercial GFAP Simoa discovery kit. Results: The developed GFAP assay showed a good performance with a recovery of 85% of spiked GFAP in serum and assay variations below 15%. The established assay was highly sensitive with a calculated lower limit of quantification and detection of 7.21 pg/mL and 2.37 pg/mL, respectively. GFAP levels were significantly increased in AD compared to control patients with advanced age (p = 0.002). However, GFAP levels revealed no significant increase in MS compared to control patients in the same age range (p = 0.140). Furthermore, serum GFAP levels evaluated with the novel microfluidic assay strongly correlated with Simoa concentrations (r = 0.88 (95% CI: 0.81-0.93), p < 0.0001). Conclusion: We successfully developed a sensitive and easy-to-use microfluidic assay to measure GFAP in blood. Furthermore, we could confirm previous findings of elevated GFAP levels in AD by applying the assay in a cohort of clinically characterized patients.

Ensemble machine learning identifies genetic loci associated with future worsening of disability in people with multiple sclerosis

Limited studies have been conducted to identify and validate multiple sclerosis (MS) genetic loci associated with disability progression. We aimed to identify MS genetic loci associated with worsening of disability over time, and to develop and validate ensemble genetic learning model(s) to identify people with MS (PwMS) at risk of future worsening. We examined associations of 208 previously established MS genetic loci with the risk of worsening of disability; we learned ensemble genetic decision rules and validated the predictions in an external dataset. We found 7 genetic loci (rs7731626: HR 0.92, P = 2.4 × 10^-5; rs12211604: HR 1.16, P = 3.2 × 10^-7; rs55858457: HR 0.93, P = 3.7 × 10^-7; rs10271373: HR 0.90, P = 1.1 × 10^-7; rs11256593: HR 1.13, P = 5.1 × 10^-57; rs12588969: HR = 1.10, P = 2.1 × 10^-10; rs1465697: HR 1.09, P = 1.7 × 10^-128) associated with risk worsening of disability; most of which were located near or tagged to 13 genomic regions enriched in peptide hormones and steroids biosynthesis pathways by positional and eQTL mapping. The derived ensembles produced a set of genetic decision rules that can be translated to provide additional prognostic values to existing clinical predictions, with the additional benefit of incorporating relevant genetic information into clinical decision making for PwMS. The present study extends our knowledge of MS progression genetics and provides the basis of future studies regarding the functional significance of the identified loci.