Body fluid biomarkers in multiple sclerosis

Glial cell injury and atrophied lesion volume as measures of chronic multiple sclerosis inflammation

BACKGROUND

Atrophied lesion volume (aLV), a proposed biomarker of disability progression in multiple sclerosis (MS) and transition into progressive MS (PMS), depicts chronic periventricular white matter (WM) pathology. Meningeal infiltrates, imaged as leptomeningeal contrast enhancement (LMCE), are linked with greater cortical pathology.

OBJECTIVES

To determine the relationship between serum-derived proteomic data with the development of aLV and LMCE in a heterogeneous group of people with MS (pwMS).

METHODS

Proteomic and MRI data for 202 pwMS (148 clinically isolated syndrome /relapsing-remitting MS and 54 progressive MS (PMS)) were acquired at baseline and at 5.4-year follow-up. The concentrations of 21 proteins related to multiple MS pathophysiology pathways were derived using a custom-developed Proximity Extension Assay on the Olink™ platform. The accrual of aLV was determined as the volume of baseline T2-weighted lesions that were replaced by cerebrospinal fluid over the follow-up. Regression models and age-adjusted analysis of covariance (ANCOVA) were used.

RESULTS

Older age (standardized beta = 0.176, p = 0.022), higher glial fibrillary acidic protein (standardized beta = 0.312, p = 0.001), and lower myelin oligodendrocyte glycoprotein levels (standardized beta = -0.271, p = 0.002) were associated with accrual of aLV over follow-up. This relationship was driven by the pwPMS population. The presence of LMCE at the follow-up visit was not predicted by any baseline proteomic biomarker nor cross-sectionally associated with any protein concentration.

CONCLUSION

Proteomic markers of glial activation are associated with chronic lesional WM pathology (measured as aLV) and may be specific to the progressive MS phenotype. LMCE presence in MS does not appear to relate to proteomic measures.

CHIT1 at diagnosis predicts faster disability progression and reflects early microglial activation in multiple sclerosis

Multiple sclerosis (MS) is characterized by heterogeneity in disease course and prediction of long-term outcome remains a major challenge. Here, we investigate five myeloid markers - CHIT1, CHI3L1, sTREM2, GPNMB and CCL18 - in the cerebrospinal fluid (CSF) at diagnostic lumbar puncture in a longitudinal cohort of 192 MS patients. Through mixed-effects and machine learning models, we show that CHIT1 is a robust predictor for faster disability progression. Integrative analysis of 11 CSF and 26 central nervous system (CNS) parenchyma single-cell/nucleus RNA sequencing samples reveals CHIT1 to be predominantly expressed by microglia located in active MS lesions and enriched for lipid metabolism pathways. Furthermore, we find CHIT1 expression to accompany the transition from a homeostatic towards a more activated, MS-associated cell state in microglia. Neuropathological evaluation in post-mortem tissue from 12 MS patients confirms CHIT1 production by lipid-laden phagocytes in actively demyelinating lesions, already in early disease stages. Altogether, we provide a rationale for CHIT1 as an early biomarker for faster disability progression in MS.

Identification of Novel Genes and Pathways of Ovarian Cancer Using a Comprehensive Bioinformatic Framework

Ovarian cancer (OC) is a significant contributor to gynecological cancer-related deaths worldwide, with a high mortality rate. Despite several advances in understanding the pathogenesis of OC, the molecular mechanisms underlying its development and prognosis remain poorly understood. Therefore, the current research study aimed to identify hub genes involved in the pathogenesis of OC that could serve as selective diagnostic and therapeutic targets. To achieve this, the dataset GEO2R was used to retrieve differentially expressed genes. The study identified a total of five genes (CDKN1A, DKK1, CYP1B1, NTS, and GDF15) that were differentially expressed in OC. Subsequently, a network analysis was performed using the STRING database, followed by the construction of a network using Cytoscape. The network analyzer tool in Cytoscape predicted 276 upregulated and 269 downregulated genes. Furthermore, KEGG analysis was conducted to identify different pathways related to OC. Subsequently, survival analysis was performed to validate gene expression alterations and predict hub genes, using a p-value of 0.05 as a threshold. Four genes (CDKN1A, DKK1, CYP1B1, and NTS) were predicted as significant hub genes, while one gene (GDF15) was predicted as non-significant. The adjusted P values of said predicted genes are 2.85E - 07, 5.49E - 06, 4.28E - 07, 1.43E - 07, and 3.70E - 07 for CDKN1A, DKK1, NTS, GDF15, and CYP1B1 respectively; additionally 6.08, 5.76, 5.74, 5.01, and 4.9 LogFc values of the said genes were predicted in GEO data set. In a boxplot analysis, the expression of these genes was analyzed in normal and tumor cells. The study found that three genes were highly expressed in tumor cells, while two genes (CDKN1A and DKK1) were more elevated in normal cells. According to the boxplot analysis for CDKN1A, 50% of tumor cells ranged between approx 3.8 and 5, while 50% of normal cells ranged between approx 6.9 and 7.9, which is greater than tumor cells. This shows that in normal cells, the CYP1B1 has a high expression level according to the GEPIA boxplot; addtionally the boxplot for DKK1 indicated that 50% of tumor cells ranged between approx 0 and 0.5, which was less than that of normal cells which ranged between approx 0.3 and 0.9. It shows that DKK1 is highly expressed in normal genes. Overall, the current study provides novel insights into the molecular mechanisms underlying OC. The identified hub genes and drug candidate targets could potentially serve as alternative diagnostic and therapeutic options for OC patients. Further research is needed to investigate the clinical significance of these findings and develop effective interventions that can improve the prognosis of patients with OC.

Brain stimulation for patients with multiple sclerosis: an umbrella review of therapeutic efficacy

Multiple sclerosis patients often experience various symptoms that can greatly impact their quality of life. There are various brain stimulation techniques that have been evaluated for their ability to reduce the symptoms of multiple sclerosis. However, there is inconsistency in the specific stimulation methods used and the symptoms targeted in the existing research. This umbrella review conducted in order to evaluate the effectiveness of brain stimulation and identify limitations and gaps for further research. In this umbrella review, we conducted a searched on Web of Knowledge, PubMed, and Scopus database. We specifically looked for reviews, with or without meta-analyses, that have investigated the effects of brain stimulation methods on symptoms of multiple sclerosis. All articles were examined by AMSTAR 2 (A Measure Tool to Assess Systematic Review 2). We identified 155 articles, of which 14 were eligible for inclusion. Of those, five were qualitative studies and nine were meta-analyses. Among the included studies, four examined the use of deep brain stimulation, while ten investigated the therapeutic potential of noninvasive brain stimulation. Considering the heterogeneity of studies, the current evidence suggests that repetitive transcranial magnetic stimulation may be effective in treating pain and improving motor function, while transcranial direct current stimulation may be useful in alleviating fatigue and enhancing certain aspects of cognitive performance. Deep brain stimulation, on the other hand, appears to be effective in reducing tremors. However, further research is warranted to validate these findings and address the existing limitations in the field.

Inflammatory and neurodegenerative serum protein biomarkers increase sensitivity to detect clinical and radiographic disease activity in multiple sclerosis

The multifaceted nature of multiple sclerosis requires quantitative biomarkers that can provide insights related to diverse physiological pathways. To this end, proteomic analysis of deeply-phenotyped serum samples, biological pathway modeling, and network analysis were performed to elucidate inflammatory and neurodegenerative processes, identifying sensitive biomarkers of multiple sclerosis disease activity. Here, we evaluated the concentrations of > 1400 serum proteins in 630 samples from three multiple sclerosis cohorts for association with clinical and radiographic new disease activity. Twenty proteins were associated with increased clinical and radiographic multiple sclerosis disease activity for inclusion in a custom assay panel. Serum neurofilament light chain showed the strongest univariate correlation with gadolinium lesion activity, clinical relapse status, and annualized relapse rate. Multivariate modeling outperformed univariate for all endpoints. A comprehensive biomarker panel including the twenty proteins identified in this study could serve to characterize disease activity for a patient with multiple sclerosis.

Aptamer-based electrochemical nanobiosensor for research and monitoring of multiple sclerosis in mice models

Multiple sclerosis (MS) is a severe progressive autoimmune-inflammatory, demyelinating process in the central nervous system (CNS) with heterogeneous neurological symptoms appearing as a consequence of myelin break down. Myelin basic protein (MBP) makes up to 30 % of the CNS myelin [1] and it is known to be released into the cerebrospinal fluid (CSF) as a bioindicator of MS. Autoimmune encephalomyelitis (EAE) is a mice model of MS widely used for research and development of new treatments [2]. Herein, MBP specific aptamer developed for possible therapeutic purposes in mouse model [3] was applied as a bioreceptor for MBP recognition. A nanobiosensor for MBP detection and monitoring was developed by using graphene oxide (GO) nanoparticles integrated onto the screen-printed carbon electrodes (SPCE) and aptamer immobilized to create a bioactive layer on the sensor surface for MBP binding. The measurements were carried out using electrochemical impedance spectrometry (EIS). Validation studies were carried out in a biological matrix (artificial CSF) containing MBP, and MSA. The aptasensor had LOD in artificial CSF 0.01 ng/mL and showed its usability in the concentration range of 0.01 … 64 ng/mL.

Brain Expression Levels of Commonly Measured Blood Biomarkers of Neurological Damage Differ with Respect to Sex, Race, and Age

It is increasingly evident that blood biomarkers have potential to improve the diagnosis and management of both acute and chronic neurological conditions. The most well-studied candidates, and arguably those with the broadest utility, are proteins that are highly enriched in neural tissues and released into circulation upon cellular damage. It is currently unknown how the brain expression levels of these proteins is influenced by demographic factors such as sex, race, and age. Given that source tissue abundance is likely a key determinant of the levels observed in the blood during neurological pathology, understanding such influences is important in terms of identifying potential clinical scenarios that could produce diagnostic bias. In this study, we leveraged existing mRNA sequencing data originating from 2,642 normal brain specimens harvested from 382 human donors to examine potential demographic variability in the expression levels of genes which code for 28 candidate blood biomarkers of neurological damage. Existing mass spectrometry data originating from 26 additional normal brain specimens harvested from 26 separate human donors was subsequently used to tentatively assess whether observed transcriptional variance was likely to produce corresponding variance in terms of protein abundance. Genes associated with several well-studied or emerging candidate biomarkers including neurofilament light chain (NfL), ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCH-L1), neuron-specific enolase (NSE), and synaptosomal-associated protein 25 (SNAP-25) exhibited significant differences in expression with respect to sex, race, and age. In many instances, these differences in brain expression align well with and provide a mechanistic explanation for previously reported differences in blood levels.

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.

Soluble CD27 is an intrathecal biomarker of T-cell-mediated lesion activity in multiple sclerosis

OBJECTIVE

Soluble CD27 is a promising cerebrospinal fluid inflammatory biomarker in multiple sclerosis. In this study, we investigate relevant immune and neuro-pathological features of soluble CD27 in multiple sclerosis.

METHODS

Protein levels of soluble CD27 were correlated to inflammatory cell subpopulations and inflammatory cytokines and chemokines detected in cerebrospinal fluid of 137 patients with multiple sclerosis and 47 patients with inflammatory and non-inflammatory neurological disease from three independent cohorts. Production of soluble CD27 was investigated in cell cultures of activated T and B cells and CD27-knockout T cells. In a study including matched cerebrospinal fluid and post-mortem brain tissues of patients with multiple sclerosis and control cases, levels of soluble CD27 were correlated with perivascular and meningeal infiltrates and with neuropathological features.

RESULTS

We demonstrate that soluble CD27 favours the differentiation of interferon-γ-producing T cells and is released through a secretory mechanism activated by TCR engagement and regulated by neutral sphingomyelinase. We also show that the levels of soluble CD27 correlate with the representation of inflammatory T cell subsets in the CSF of patients with relapsing-remitting multiple sclerosis and with the magnitude of perivascular and meningeal CD27 + CD4 + and CD8 + T cell infiltrates in post-mortem central nervous system tissue, defining a subgroup of patients with extensive active inflammatory lesions.

INTERPRETATION

Our results demonstrate that soluble CD27 is a biomarker of disease activity, potentially informative for personalized treatment and monitoring of treatment outcomes.

Serum neurofilament light chain correlations in patients with a first clinical demyelinating event in the REFLEX study: a post hoc analysis

Background

In REFLEX, subcutaneous interferon beta-1a (sc IFN β-1a) delayed the onset of multiple sclerosis (MS) in patients with a first clinical demyelinating event (FCDE).

Objectives

This post hoc analysis aimed to determine whether baseline serum neurofilament light (sNfL) chain can predict conversion to MS and whether correlations exist between baseline sNfL and magnetic resonance imaging (MRI) metrics.

Methods

sNfL was measured for 494 patients who received sc IFN β-1a 44 μg once weekly (qw; n = 168), three times weekly (tiw; n = 161), or placebo (n = 165) over 24 months. Median baseline sNfL (26.1 pg/mL) was used to define high/low sNfL subgroups. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox's proportional hazard model to determine factors influencing the risk of conversion to MS. Kaplan-Meier estimates calculated median time-to-conversion to MS (McDonald 2005 criteria) or clinically definite MS (CDMS; Poser criteria). Correlations between sNfL and MRI findings were assessed using Spearman's rank correlation coefficient (r).

Results

Multivariable models indicated that high baseline sNfL was associated with the likelihood of converting to MS and inversely to time-to-conversion (HR = 1.3, 95% CI: 1.03-1.64; p = 0.024). Significant additional factors affecting conversion to McDonald MS were on-study treatment (sc IFN β-1a/placebo; qw: HR = 0.59, 95% CI: 0.46-0.76; tiw: HR = 0.45, 95% CI: 0.34-0.59), classification of FCDE (monofocal/multifocal; HR = 0.69, 95% CI: 0.55-0.85), and most baseline imaging findings (T2 and T1 gadolinium-enhancing [Gd+] lesions; HR = 1.02, 95% CI: 1.01-1.03 and HR = 1.07, 95% CI: 1.03-1.11); all p ⩽ 0.001. Conversion to CDMS showed similar results. At month 24, sNfL was strongly correlated with a mean number of combined unique active (r = 0.71), new T2 (r = 0.72), and new T1 Gd+ (r = 0.60) lesions; weak correlations were observed between sNfL and clinical outcomes for all treatment groups.

Conclusion

Higher baseline sNfL was associated with an increased risk of MS conversion, a risk that was mitigated by treatment with sc IFN β-1a tiw.

Trial registration

ClinicalTrials.gov identifier: NCT00404352. Date registered: 28 November 2006.

The role of oligoclonal band count and IgG index in treatment response and disease activity in multiple sclerosis

BACKGROUND/AIM

Multiple sclerosis (MS) is an inflammatory demyelinating central nervous system (CNS) disease. Among the paraclinical tests, brain and spinal Magnetic Resonance Imaging (MRI) is primarily involved in the diagnosis process, and cerebrospinal fluid (CSF) analysis is fundamental in diagnosing MS and the differential diagnosis. A positive relationship was demonstrated between oligoclonal band (OCB) positivity, CSF band number and immunoglobulin G(IgG) index. The study aimed to evaluate whether the number of OCB can predict disease activity and determine a correlation with the IgG index.

METHODS

Our study included 401 MS patients who had relapsing-remitting multiple sclerosis (RRMS), primary progressive multiple sclerosis (PPMS), secondary progressive multiple sclerosis (SPMS), clinic isolated syndrome (CIS), radiologic isolated syndrome (RIS), Neuromyelitis optica spectrum disorder (NMOSD) and Acute disseminated encephalomyelitis (ADEM) with OCB number groups of 2-4, 4-8, 8-12, and 12 and above.

RESULTS

No significant correlation was observed between IgG index, pre-and post-treatment EDSS (Expanded Disability Status Scale Scores) and disease-modifying therapies (DMT). Drug response was better in the patient group with band number between 2 and 8 and post-treatment EDSS scores were lower (1.62±0.44).

CONCLUSION

The study results suggested that band number may be as valuable as the IgG index and a predictive biomarker for disease activity.

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.

Prognostic value of cerebrospinal fluid biomarkers in multiple sclerosis: The key role of kappa free light chains and a multivariate predictor for disease progression

OBJECTIVE

Multiple sclerosis (MS) is a chronic, inflammatory, demyelinating disease of the central nervous system with varying progression rates among individuals. The ability to predict disease progression is crucial for treatment decisions with disease-modifying therapies (DMTs). A few cerebrospinal fluid (CSF) biomarkers have been investigated in relation to disease progression, but few have been effectively translated into clinical practice. The aim of this study was to evaluate the diagnostic and prognostic value of known CSF markers, to compare their sensitivity and specificity, and to develop a prognostic model using a combination of markers to predict disease progression.

METHODS

This retrospective cohort study included 82 patients with a first episode of inflammatory demyelinating symptoms suggestive of MS between January 2018 and January 2021. Patients underwent diagnostic lumbar puncture and other investigations according to the multiple sclerosis (MS) protocol. They were divided into three groups according to MRI findings, relapse rate and EDSS score. CSF marker concentrations were determined by laser nephelometry and electrochemiluminescence immunoassay.

RESULTS

The results showed that the number of oligoclonal bands could discriminate the progression-free group from the other groups, but had a lower discriminatory power compared to CSF marker concentrations. Among CSF markers, FLC kappa showed the best discriminatory performance. By combining FLC kappa with gender and lesion localization information, a simple predictor of progression-free group membership was proposed. This predictor showed good sensitivity (91 %) and specificity (65 %).

CONCLUSION

In conclusion, CSF FLC kappa concentration, together with gender and lesion localization, may be a valuable predictor of disease progression in MS patients. This study highlights the potential of using CSF biomarkers for prognostic purposes and offers a simple approach to predicting disease progression.

Multiple sclerosis

Multiple sclerosis remains one of the most common causes of neurological disability in the young adult population (aged 18-40 years). Novel pathophysiological findings underline the importance of the interaction between genetics and environment. Improvements in diagnostic criteria, harmonised guidelines for MRI, and globalised treatment recommendations have led to more accurate diagnosis and an earlier start of effective immunomodulatory treatment than previously. Understanding and capturing the long prodromal multiple sclerosis period would further improve diagnostic abilities and thus treatment initiation, eventually improving long-term disease outcomes. The large portfolio of currently available medications paved the way for personalised therapeutic strategies that will balance safety and effectiveness. Incorporation of cognitive interventions, lifestyle recommendations, and management of non-neurological comorbidities could further improve quality of life and outcomes. Future challenges include the development of medications that successfully target the neurodegenerative aspect of the disease and creation of sensitive imaging and fluid biomarkers that can effectively predict and monitor disease changes.

Advances in microfluidic chips targeting toxic aggregation proteins for neurodegenerative diseases

Neurodegenerative diseases (NDs) are characterized by nervous system damage, often influenced by genetic and aging factors. Pathological analysis frequently reveals the presence of aggregated toxic proteins. The intricate and poorly understood origins of these diseases have hindered progress in early diagnosis and drug development. The development of novel in-vitro and in-vivo models could enhance our comprehension of ND mechanisms and facilitate clinical treatment advancements. Microfluidic chips are employed to establish three-dimensional culture conditions, replicating the human ecological niche and creating a microenvironment conducive to neuronal cell survival. The incorporation of mechatronic controls unifies the chip, cells, and culture medium optimizing living conditions for the cells. This study provides a comprehensive overview of microfluidic chip applications in drug and biomarker screening for neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, Huntington's disease, multiple sclerosis, and amyotrophic lateral sclerosis. Our Lab-on-a-Chip system releases toxic proteins to simulate the pathological characteristics of neurodegenerative diseases, encompassing β-amyloid, α-synuclein, huntingtin, TAR DNA-binding protein 43, and Myelin Basic Protein. Investigating molecular and cellular interactions in vitro can enhance our understanding of disease mechanisms while minimizing harmful protein levels and can aid in screening potential therapeutic agents. We anticipate that our research will promote the utilization of microfluidic chips in both fundamental research and clinical applications for neurodegenerative diseases.

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.

Effects of disease-modifying therapies on lipid parameters in patients with multiple sclerosis

BACKGROUND

Cholesterol and lipids are essential components of nerve cells. Myelin synthesis and stabilization is a cholesterol-dependent process. It has been shown in several studies that high plasma cholesterol levels may be associated with clinical deterioration in Multiple Sclerosis (MS). There is scarce information about the effects of disease-modifying treatment (DMTs) on lipid profile. In this study, we aimed to investigate the effect of DMTs on plasma lipid profiles in MS patients.

METHOD

The records of 380 MS patients who were still under follow-up were analyzed in terms of age, sex, disease duration, EDSS scores, serum lipid levels, and used DMTs. The data of patients receiving Interferon (n = 53), Glatiramer acetate (n = 25), Fingolimod (n = 44), Teriflunomide (n = 24), Dimethyl fumarate (n = 7) and Ocrelizumab (n = 14) were compared with the data of control group (n = 53).

RESULTS

A total of 220 patients, 157 women, and 63 men, were included in the study. The average age of the participants in the study was 39.83 ± 10.21 years, mean disease duration was 8.45 ± 6.56 years, and the EDSS score was 2.25 ± 1.97. Although, Lipid parameters were higher in MS patients using Fingolimod the difference cannot reach the statistical significance.

CONCLUSION

No significant relationship was found between the DMTs that MS patients had been using for the last six months and their cholesterol levels.

Haematopoietic Stem Cell Transplantation for the Treatment of Multiple Sclerosis: Recent Advances

PURPOSE OF REVIEW

Autologous haematopoietic stem cell transplantation (AHSCT) is increasingly considered a treatment option for patients with multiple sclerosis (MS), an autoimmune demyelinating and degenerative disease of the central nervous system (CNS). AHSCT persistently suppresses inflammation and improves the disease course in large proportions of patients with relapsing-remitting (RR) MS. Aim of this article is to review the relevant new knowledge published during the last 3 years.

RECENT FINDINGS

Laboratory studies reported confirmatory and new insights into the immunological and biomarker effects of AHSCT. Retrospective clinical studies confirmed excellent outcomes in RRMS, showing possible superior effectiveness over standard therapies and suggesting a possible benefit in early secondary progressive (SP) MS with inflammatory features. New data on risks of infertility and secondary autoimmunity were also reported. Further evidence on the high effectiveness and acceptable safety of AHSCT strengthens its position as a clinical option for aggressive RRMS. Further research is needed to better define its role in treatment-naïve and progressive forms of MS, ideally within randomised clinical trials (RCTs).

Biochemical biomarkers for multiple sclerosis

INTRODUCTION

Multiple sclerosis (MS) is the most frequent demyelinating disease of the central nervous system. Although there is currently no definite cure for MS, new therapies have recently been developed based on a continuous search for new biomarkers.

DEVELOPMENT

MS diagnosis relies on the integration of clinical, imaging and laboratory findings as there is still no singlepathognomonicclinical feature or diagnostic laboratory biomarker. The most commonly laboratory test used is the presence of immunoglobulin G oligoclonal bands (OCB) in cerebrospinal fluid of MS patients. This test is now included in the 2017 McDonald criteria as a biomarker of dissemination in time. Nevertheless, there are other biomarkers currently in use such as kappa free light chain, which has shown higher sensitivity and specificity for MS diagnosis than OCB. In addition, other potential laboratory tests involved in neuronal damage, demyelination and/or inflammation could be used for detecting MS.

CONCLUSIONS

CSF and serum biomarkers have been reviewed for their use in MS diagnosis and prognosis to stablish an accurate and prompt MS diagnosis, crucial to implement an adequate treatment and to optimize clinical outcomes over time.

Inflammatory and neurodegenerative serum protein biomarkers increase sensitivity to detect disease activity in multiple sclerosis

Background/Objectives

Serum proteomic analysis of deeply-phenotyped samples, biological pathway modeling and network analysis were performed to elucidate the inflammatory and neurodegenerative processes of multiple sclerosis (MS) and identify sensitive biomarkers of MS disease activity (DA).

Methods

Over 1100 serum proteins were evaluated in >600 samples from three MS cohorts to identify biomarkers of clinical and radiographic (gadolinium-enhancing lesions) new MS DA. Protein levels were analyzed and associated with presence of gadolinium-enhancing lesions, clinical relapse status (CRS), and annualized relapse rate (ARR) to create a custom assay panel.

Results

Twenty proteins were associated with increased clinical and radiographic MS DA. Serum neurofilament light chain (NfL) showed the strongest univariate correlation with radiographic and clinical DA measures. Multivariate modeling significantly outperformed univariate NfL to predict gadolinium lesion activity, CRS and ARR.

Discussion

These findings provide insight regarding correlations between inflammatory and neurodegenerative biomarkers and clinical and radiographic MS DA.

Funding

Octave Bioscience, Inc (Menlo Park, CA).

Proteomics and relationship with axonal pathology in multiple sclerosis: 5-year diffusion tensor imaging study

Blood-based biomarkers can be economic and easily accessible tools for monitoring and predicting disease activity in multiple sclerosis. The objective of this study was to determine the predictive value of a multivariate proteomic assay for concurrent and future microstructural/axonal brain pathology in a longitudinal study of a heterogeneous group of people with multiple sclerosis. A proteomic analysis was obtained on serum samples from 202 people with multiple sclerosis (148 relapsing-remitting and 54 progressive) at baseline and 5-year follow-up. The concentration of 21 proteins related to multiple pathways of multiple sclerosis pathophysiology was derived using Proximity Extension Assay on the Olink platform. Patients were imaged on the same 3T MRI scanner at both timepoints. Тhe rate of whole brain, white matter and grey matter atrophy over the 5-year follow-up was determined using the multi-timepoint Structural Image Evaluation, using Normalisation, of Atrophy algorithms. Lesion burden measures were also assessed. The severity of microstructural axonal brain pathology was quantified using diffusion tensor imaging. Fractional anisotropy and mean diffusivity of normal-appearing brain tissue, normal-appearing white matter, grey matter, T2 and T1 lesions were calculated. Age, sex and body mass index-adjusted step-wise regression models were used. Glial fibrillary acidic protein was the most common and highest-ranked proteomic biomarker associated with greater concurrent microstructural central nervous system alterations (P < 0.001). The rate of whole brain atrophy was associated with baseline levels of glial fibrillary acidic protein, protogenin precursor, neurofilament light chain and myelin oligodendrocyte (P < 0.009), whereas grey matter atrophy was associated with higher baseline neurofilament light chain, higher osteopontin and lower protogenin precursor levels (P < 0.016). Higher baseline glial fibrillary acidic protein level was a significant predictor of future severity of the microstructural CNS alterations as measured by normal-appearing brain tissue fractional anisotropy and mean diffusivity (standardized β = -0.397/0.327, P < 0.001), normal-appearing white matter fractional anisotropy (standardized β = -0.466, P < 0.0012), grey matter mean diffusivity (standardized β = 0.346, P < 0.011) and T2 lesion mean diffusivity (standardized β = 0.416, P < 0.001) at the 5-year follow-up. Serum levels of myelin-oligodendrocyte glycoprotein, neurofilament light chain, contactin-2 and osteopontin proteins were additionally and independently associated with worse concomitant and future axonal pathology. Higher glial fibrillary acidic protein levels were associated with future disability progression (Exp(B) = 8.65, P = 0.004). Multiple proteomic biomarkers are independently associated with greater severity of axonal brain pathology as measured by diffusion tensor imaging in multiple sclerosis. Baseline serum glial fibrillary acidic protein levels can predict future disability progression.

Nanopore Single-molecule Analysis of Biomarkers: Providing Possible Clues to Disease Diagnosis

Biomarker detection has attracted increasing interest in recent years due to the minimally or non-invasive sampling process. Single entity analysis of biomarkers is expected to provide real-time and accurate biological information for early disease diagnosis and prognosis, which is critical to the effective disease treatment and is also important in personalized medicine. As an innovative single entity analysis method, nanopore sensing is a pioneering single-molecule detection technique that is widely used in analytical bioanalytical fields. In this review, we overview the recent progress of nanopore biomarker detection as new approaches to disease diagnosis. In highlighted studies, nanopore was focusing on detecting biomarkers of different categories of communicable and noncommunicable diseases, such as pandemic Covid-19, AIDS, cancers, neurologic diseases, etc. Various sensitive and selective nanopore detecting strategies for different types of biomarkers are summarized. In addition, the challenges, opportunities, and direction for future development of nanopore-based biomarker sensors are also discussed.

The efficacy and safety of ginger supplementation in patients with multiple sclerosis: A rationale and study protocol for a double-blind randomized controlled trial

Background and Aims

Multiple sclerosis (MS) is a chronic disease characterized by axonal damage, demyelination, inflammation, oxidative stress, and immune cell infiltration. This disease is the first cause of nontraumatic disability in young adults leading to a decline in patients' quality of life. Patients with MS may also suffer from gastrointestinal symptoms due to the disease or prescription drugs. Unfortunately, no treatment for MS has been discovered yet, and prescribed drugs can only help control its clinical course. Interestingly, recent animal studies have shown positive effects of ginger administration in the MS model. Therefore, we aim to determine the effect of ginger supplementation on neurofilament light chain, matrix metalloproteinase-9, interleukin-17, nitric oxide, complete and differential blood counts, disability status, quality of life, gastrointestinal symptoms, and body mass index (BMI) in MS patients.

Methods

This study is a double-blind randomized controlled trial. Fifty-two patients with relapsing-remitting MS will be assigned to intervention and control groups using stratified permuted block randomization. The intervention and control groups will take 1500 mg/day ginger and placebo (as corn) supplements for 12 weeks, respectively. All outcomes will be assessed before and after the trial. Serum concentrations of neurofilament light chain, matrix metalloproteinase-9, and interleukin-17 will be measured by enzyme-linked immunosorbent assay. Nitric oxide serum levels will be detected using colorimetry. Complete and differential blood counts will be assessed by an automated hematology analyzer. Disability status, quality of life, and gastrointestinal symptoms will be evaluated by the Expanded Disability Status Scale, MS Impact Scale, and Visual Analog Scale, respectively. BMI will be calculated by dividing weight in kilograms by height in meters squared. Potential side effects of ginger supplementation will also be closely monitored during the study.

Trial Registration

This protocol was registered at the Iranian Registry of Clinical Trials (www.irct.ir) under the registration number IRCT20180818040827N3.

Serum Levels of CXCL13 Are Associated With Teriflunomide Response in Patients With Multiple Sclerosis

BACKGROUND AND OBJECTIVES

To identify biomarkers associated with treatment response in patients with multiple sclerosis (MS) treated with the oral therapies teriflunomide, dimethyl fumarate (DMF), and fingolimod.

METHODS

Serum levels of IL-6, IL-17, TNF-α, granulocyte-macrophage colony-stimulating factor, IL-10, interferon-gamma (IFN-γ) IL-1β, and chemokine ligand 13 (CXCL13) were measured at baseline and 12 months with single molecule array (Simoa) assays in a cohort of patients with MS treated with teriflunomide (N = 19), DMF (N = 22), and fingolimod (N = 25) and classified into "no evidence of disease activity" (NEDA) and EDA patients after 1 year of treatment.

RESULTS

Serum CXCL13 and TNF-α levels were significantly decreased after treatment with teriflunomide in NEDA compared with EDA patients after 1 year of treatment (p = 0.008 for both cytokines). These findings were validated in an independent cohort of patients with MS treated with teriflunomide (N = 36) and serum CXCL13, and TNF-α levels were again significantly reduced in NEDA patients (p < 0.0001 for CXCL13 and p = 0.003 for TNF-α). CXCL13, but not TNF-α, showed good performance to classify NEDA and EDA patients according to a cut-off value of 9.64 pg/mL based on the change in CXCL13 levels between baseline and 12 months, with a sensitivity of 75% and specificity of 82% in the original cohort, and sensitivity of 65.4% and specificity of 60% in the validation cohort.

DISCUSSION

Altogether, these results point to CXCL13 as a treatment response biomarker to teriflunomide in relapsing-remitting patients with MS, and the change in CXCL13 levels during the first year of treatment can be used in clinical practice to identify optimal responders to teriflunomide.

Dynamics of Inflammatory and Neurodegenerative Biomarkers after Autologous Hematopoietic Stem Cell Transplantation in Multiple Sclerosis

Autologous hematopoietic stem cell transplantation (aHSCT) is a highly efficient treatment of multiple sclerosis (MS), and hence it likely normalizes pathological and/or enhances beneficial processes in MS. The disease pathomechanisms include neuroinflammation, glial cell activation and neuronal damage. We studied biomarkers that in part reflect these, like markers for neuroinflammation (C-X-C motif chemokine ligand (CXCL) 9, CXCL10, CXCL13, and chitinase 3-like 1 (CHI3L1)), glial perturbations (glial fibrillary acidic protein (GFAP) and in part CHI3L1), and neurodegeneration (neurofilament light chain (NfL)) by enzyme-linked immunosorbent assays (ELISA) and single-molecule array assay (SIMOA) in the serum and cerebrospinal fluid (CSF) of 32 MS patients that underwent aHSCT. We sampled before and at 1, 3, 6, 12, 24 and 36 months after aHSCT for serum, as well as before and 24 months after aHSCT for CSF. We found a strong increase of serum CXCL10, NfL and GFAP one month after the transplantation, which normalized one and two years post-aHSCT. CXCL10 was particularly increased in patients that experienced reactivation of cytomegalovirus (CMV) infection, but not those with Epstein-Barr virus (EBV) reactivation. Furthermore, patients with CMV reactivation showed increased Th1 phenotype in effector memory CD4+ T cells. Changes of the other serum markers were more subtle with a trend for an increase in serum CXCL9 early post-aHSCT. In CSF, GFAP levels were increased 24 months after aHSCT, which may indicate sustained astroglia activation 24 months post-aHSCT. Other CSF markers remained largely stable. We conclude that MS-related biomarkers indicate neurotoxicity early after aHSCT that normalizes after one year while astrocyte activation appears increased beyond that, and increased serum CXCL10 likely does not reflect inflammation within the central nervous system (CNS) but rather occurs in the context of CMV reactivation or other infections post-aHSCT.

A Scoping Review on Body Fluid Biomarkers for Prognosis and Disease Activity in Patients with Multiple Sclerosis

Multiple sclerosis (MS) is a complex demyelinating disease of the central nervous system, presenting with different clinical forms, including clinically isolated syndrome (CIS), which is a first clinical episode suggestive of demyelination. Several molecules have been proposed as prognostic biomarkers in MS. We aimed to perform a scoping review of the potential use of prognostic biomarkers in MS clinical practice. We searched MEDLINE up to 25 November 2021 for review articles assessing body fluid biomarkers for prognostic purposes, including any type of biomarkers, cell types and tissues. Original articles were obtained to confirm and detail the data reported by the review authors. We evaluated the reliability of the biomarkers based on the sample size used by various studies. Fifty-two review articles were included. We identified 110 molecules proposed as prognostic biomarkers. Only six studies had an adequate sample size to explore the risk of conversion from CIS to MS. These confirm the role of oligoclonal bands, immunoglobulin free light chain and chitinase CHI3L1 in CSF and of serum vitamin D in the prediction of conversion from CIS to clinically definite MS. Other prognostic markers are not yet explored in adequately powered samples. Serum and CSF levels of neurofilaments represent a promising biomarker.

Integrated Approaches to Identify miRNA Biomarkers Associated with Cognitive Dysfunction in Multiple Sclerosis Using Text Mining, Gene Expression, Pathways, and GWAS

Multiple sclerosis (MS), a chronic autoimmune disorder, affects the central nervous system of many young adults. More than half of MS patients develop cognition problems. Although several genomic and transcriptomic studies are currently reported in MS cognitive impairment, a comprehensive repository dealing with all the experimental data is still underdeveloped. In this study, we combined text mining, gene regulation, pathway analysis, and genome-wide association studies (GWAS) to identify miRNA biomarkers to explore the cognitive dysfunction in MS, and to understand the genomic etiology of the disease. We first identified the dysregulated miRNAs associated with MS and cognitive dysfunction using PubTator (text mining), HMDD (experimental associations), miR2Disease, and PhenomiR database (differentially expressed miRNAs). Our results suggest that miRNAs such as hsa-mir-148b-3p, hsa-mir-7b-5p, and hsa-mir-7a-5p are commonly associated with MS and cognitive dysfunction. Next, we retrieved GWAS signals from GWAS Catalog, and analyzed the enrichment analysis of association signals in genes/miRNAs and their association networks. Then, we identified susceptible genetic loci, rs17119 (chromosome 6; p = 1 × 10−10), rs1843938 (chromosome 7; p = 1 × 10−10), and rs11637611 (chromosome 15; p = 1.00 × 10−15), associated with significant genetic risk. Lastly, we conducted a pathway analysis for the susceptible genetic variants and identified novel risk pathways. The ECM receptor signaling pathway (p = 3.98 × 10−8) and PI3K/Akt signaling pathway (p = 5.98 × 10−5) were found to be associated with differentially expressed miRNA biomarkers.

Biodetection Techniques for Quantification of Chemokines

Chemokines are a class of cytokine whose special properties, together with their involvement and relevant role in various diseases, make them a restricted group of biomarkers suitable for diagnosis and monitoring. Despite their importance, biodetection techniques dedicated to the selective determination of one or more chemokines are very scarce. For some years now, the critical diagnosis of inflammatory diseases by detecting both cytokine and chemokine biomarkers, has had a strong impact on the development of multiple detection platforms. However, it would be desirable to implement methodologies with a higher degree of selectivity for chemokines, in order to provide more precise information. In addition, better development of biosensor technology applied to this specific field would make it possible to address the main challenges of detection methods for several diseases with a high incidence in the population, avoiding high costs and low sensitivity. Taking this into account, this review aims to present the state of the art of chemokine biodetection techniques and emphasize the role of these systems in the prevention, monitoring and treatment of various diseases associated with chemokines as a starting point for future developments that are also analyzed throughout the article.

Development of a Highly Sensitive Neurofilament Light Chain Assay on an Automated Immunoassay Platform

Background

Neurofilament light chain (NfL) is an axonal cytoskeletal protein that is released into the extracellular space following neuronal or axonal injury associated with neurological conditions such as multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and other diseases. NfL is detectable in the cerebrospinal fluid (CSF) and blood. Numerous studies on MS have demonstrated that NfL is correlated with disease activity, predicts disease progression, and is reduced by treatment with MS disease-modifying drugs, making NfL an attractive candidate to supplement existing clinical and imaging measures in MS. However, for NfL to achieve its potential as a clinically useful biomarker for clinical decision-making or drug development, a standardized, practical, and widely accessible assay is needed. Our objective was to develop a novel NfL assay on an automated, globally available immunoassay platform and validate its performance.

Methods

A prototype NfL assay was first developed and evaluated on the ADVIA Centaur® XP immunoassay system from Siemens Healthineers. The lower limit of quantitation (LLoQ), within-lab precision, assay range, cross-reactivity with neurofilament medium and heavy chains, and effect of interfering substances were determined. NfL assay values in serum and CSF were compared with radiological and clinical disease activity measures in patients with MS and ALS, respectively. This assay was further optimized to utilize serum, plasma, and CSF sample types on the Atellica® IM system and transferred to Siemens' CLIA laboratory where it was analytically validated as a laboratory-developed test (LDT).

Results

In this study, an LLoQ of 1.85 pg/mL, within-lab precision <6%, and an assay range of up to 646 pg/mL were demonstrated with the serum prototype assay. Cross-reactivity of <0.7% with the neurofilament medium and heavy chains was observed. Serum and CSF NfL assay values were associated with radiological and clinical disease activity measures in patients with MS and ALS, respectively. The optimized version of the NfL assay demonstrated specimen equivalence with additional plasma tube types and was analytically validated as an LDT.

Conclusion

The analytical performance of the NfL assay fulfilled all acceptance criteria; therefore, we suggest that the assay is acceptable for use in both research and clinical practice settings to determine elevated NfL levels in patients.

Recent Advances in Intelligent Wearable Medical Devices Integrating Biosensing and Drug Delivery

The primary roles of precision medicine are to perform real-time examination, administer on-demand medication, and apply instruments continuously. However, most current therapeutic systems implement these processes separately, leading to treatment interruption and limited recovery in patients. Personalized healthcare and smart medical treatment have greatly promoted research on and development of biosensing and drug-delivery integrated systems, with intelligent wearable medical devices (IWMDs) as typical systems, which have received increasing attention because of their non-invasive and customizable nature. Here, the latest progress in research on IWMDs is reviewed, including their mechanisms of integrating biosensing and on-demand drug delivery. The current challenges and future development directions of IWMDs are also discussed.

Serum neurofilament as a predictor of 10-year grey matter atrophy and clinical disability in multiple sclerosis: a longitudinal study

BACKGROUND

The predictive value of serum neurofilament light chain (sNfL) on long-term prognosis in multiple sclerosis (MS) is still unclear.

OBJECTIVE

Investigate the relation between sNfL levels over a 2-year period in patients with relapsing-remitting MS, and clinical disability and grey matter (GM) atrophy after 10 years.

METHODS

85 patients, originally enrolled in a multicentre, randomised trial of ω-3 fatty acids, participated in a 10-year follow-up visit. sNfL levels were measured by Simoa quarterly until month 12, and then at month 24. The appearance of new gadolinium-enhancing (Gd+) lesions was assessed monthly between baseline and month 9, and then at months 12 and 24. At the 10-year follow-up visit, brain atrophy measures were obtained using FreeSurfer.

RESULTS

Higher mean sNfL levels during early periods of active inflammation (Gd+ lesions present or recently present) predicted lower total (β=-0.399, p=0.040) and deep (β=-0.556, p=0.010) GM volume, lower mean cortical thickness (β=-0.581, p=0.010) and higher T2 lesion count (β=0.498, p=0.018). Of the clinical outcomes, higher inflammatory sNfL levels were associated with higher disability measured by the dominant hand Nine-Hole Peg Test (β=0.593, p=0.004). Mean sNfL levels during periods of remission (no Gd+ lesions present or recently present) did not predict GM atrophy or disability progression.

CONCLUSION

Higher sNfL levels during periods of active inflammation predicted more GM atrophy and specific aspects of clinical disability 10 years later. The findings suggest that subsequent long-term GM atrophy is mainly due to neuroaxonal degradation within new lesions.

Serum-Based Biomarkers in Neurodegeneration and Multiple Sclerosis

Multiple Sclerosis (MS) is a debilitating disease with typical onset between 20 and 40 years of age, so the disability associated with this disease, unfortunately, occurs in the prime of life. At a very early stage of MS, the relapsing-remitting mobility impairment occurs in parallel with a progressive decline in cognition, which is subclinical. This stage of the disease is considered the beginning of progressive MS. Understanding where a patient is along such a subclinical phase could be critical for therapeutic efficacy and enrollment in clinical trials to test drugs targeted at neurodegeneration. Since the disease course is uneven among patients, biomarkers are needed to provide insights into pathogenesis, diagnosis, and prognosis of events that affect neurons during this subclinical phase that shapes neurodegeneration and disability. Thus, subclinical cognitive decline must be better understood. One approach to this problem is to follow known biomarkers of neurodegeneration over time. These biomarkers include Neurofilament, Tau and phosphotau protein, amyloid-peptide-β, Brl2 and Brl2-23, N-Acetylaspartate, and 14-3-3 family proteins. A composite set of these serum-based biomarkers of neurodegeneration might provide a distinct signature in early vs. late subclinical cognitive decline, thus offering additional diagnostic criteria for progressive neurodegeneration and response to treatment. Studies on serum-based biomarkers are described together with selective studies on CSF-based biomarkers and MRI-based biomarkers.

Multiple sclerosis: Immunopathological heterogeneity and its implications

MS is the most common autoimmune demyelinating disease of the CNS. For the past decades, several immunomodulatory disease-modifying treatments with multiple presumed mechanisms of action have been developed, but MS remains an incurable disease. Whereas high efficacy, at least in early disease, corroborates underlying immunopathophysiology, there is profound heterogeneity in clinical presentation as well as immunophenotypes that may also vary over time. In addition, functional plasticity in the immune system as well as in the inflamed CNS further contributes to disease heterogeneity. In this review, we will highlight immune-pathophysiological and associated clinical heterogeneity that may have an implication for more precise immunomodulatory therapeutic strategies in MS.

Lower cerebral arterial blood flow is associated with greater serum neurofilament light chain levels in multiple sclerosis patients

BACKGROUND

Hypoperfusion, vascular pathology, and cardiovascular risk factors are associated with disease severity in multiple sclerosis (MS). We aimed to assess relationships between cerebral arterial blood flow (CABF) and serum neurofilament light chain (sNfL), as neuronal damage biomarker.

METHODS AND MATERIALS

Total CABF was measured in 137 patients (86 clinically isolated syndrome (CIS)/relapsing-remitting (RR) and 51 progressive MS (PMS)) and 48 healthy controls (HCs) using Doppler ultrasound. sNfL was quantitated using single molecule assay (Simoa). 3.0T MRI examination allowed quantification of T2 lesion and whole-brain volume (WBV). Multiple linear regression models determined the sNfL associated with CABF after correction for demographic and MRI-derived variables.

RESULTS

After adjustment for age, sex and BMI, total CABF remained statistically significant and model comparisons showed that CABF explained additional 2.6% of the sNfL variance (β=-0.167, p=0.044). CABF also remained significant in a step-wise regression model (β=0.18, p=0.034) upon the inclusion of T2 lesion burden and WBV effects. Patients in the lowest CABF quartile (CABF≤761mL/min) had significantly higher sNfL (34.6pg/mL versus 23.9pg/mL, adjusted-p=0.042) when compared to the highest quartile (CABF≥1130mL/min).

CONCLUSION

Lower CABF is associated with increased sNfL in MS patients, highlighting the relationship between cerebral hypoperfusion and axonal pathology.

Experimental laboratory biomarkers in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a chronic autoimmune disorder of the central nervous system; the cause of this condition remains unknown. Researchers have analyzed different biomarkers related to MS. Here, experimental laboratory biomarkers for MS are identified and analyzed.

METHODS

The current study examined articles investigating biomarkers for MS. Records were obtained from the PubMed, LILACS, and EBSCO databases using an identical search strategy and terms that included "multiple sclerosis," "MS," and "biomarkers." In the current review, we also focus on lesser known biomarkers that have not yet been established for use in clinical practice.

RESULTS

Previous studies have explored molecular substances that may help diagnose MS and manage its adverse effects. Commonly studied factors include neurofilaments, sCD163, CXCL13, NEO, NF‑L, OPN, B cells, T cells, and integrin-binding proteins.

CONCLUSIONS

Interactions between environmental and genetic factors have been implicated in the development of MS. Previous investigations have identified a wide range of biomarkers that can be used for diagnosis and disease management. These molecules and their associated studies provide vital insight and data to help primary physicians improve clinical and health outcomes for MS patients.

Neurodegeneration and convergent factors contributing to the deterioration of the cytoskeleton in Alzheimer's disease, cerebral ischemia and multiple sclerosis (Review)

The cytoskeleton is the main intracellular structure that determines the morphology of neurons and maintains their integrity. Therefore, disruption of its structure and function may underlie several neurodegenerative diseases. This review summarizes the current literature on the tau protein, microtubule-associated protein 2 (MAP2) and neurofilaments as common denominators in pathological conditions such as Alzheimer's disease (AD), cerebral ischemia, and multiple sclerosis (MS). Insights obtained from experimental models using biochemical and immunocytochemical techniques highlight that changes in these proteins may be potentially used as protein targets in clinical settings, which provides novel opportunities for the detection, monitoring and treatment of patients with these neurodegenerative diseases.

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.

Plasma Protein Levels Analysis in Multiple Sclerosis Sardinian Families Identified C9 and CYP24A1 as Candidate Biomarkers

Here we investigate protein levels in 69 multiple sclerosis (MS) cases and 143 healthy controls (HC) from twenty Sardinian families to search for promising biomarkers in plasma. Using antibody suspension bead array technology, the plasma levels of 56 MS-related proteins were obtained. Differences between MS cases and HC were estimated using Linear Mixed Models or Linear Quantile Mixed Models. The proportion of proteins level variability, explained by a set of 119 MS-risk SNPs as to the literature, was also quantified. Higher plasma C9 and CYP24A1 levels were found in MS cases compared to HC (p < 0.05 after Holm multiple testing correction), with protein level differences estimated as, respectively, 0.53 (95% CI: 0.25, 0.81) and 0.42 (95% CI: 0.19, 0.65) times plasma level standard deviation measured in HC. Furthermore, C9 resulted in both statistically significantly higher relapsing-remitting MS (RRMS) and secondary-progressive MS (SPMS) compared to HC, with SPMS showing the highest differences. Instead, CYP24A1 was statistically significantly higher only in RRMS as compared to HC. Respectively, 26% (95% CI: 10%, 44%) and 16% (95% CI: 9%, 39%) of CYP24A1 and C9 plasma level variability was explained by known MS-risk SNPs. Our results highlight C9 and CYP24A1 as potential biomarkers in plasma for MS and allow us to gain insight into molecular disease mechanisms.

Metabolomics as a promising tool for improving understanding of Multiple Sclerosis: a review of recent advances

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system that usually affects young adults. The development of MS is closely related to the changes in the metabolome. Metabolomics studies have been performed using biofluids or tissue samples from rodent models and human patients to reveal metabolic alterations associated with MS progression. This review aims to provide an overview of the applications of metabolomics that for the investigations of the perturbed metabolic pathways in MS and to reveal the potential of metabolomics in personalizing treatments. In conclusion, informative variations of metabolites can be potential biomarkers in advancing our understanding of MS pathogenesis for MS diagnosis, predicting the progression of the disease, and estimating drug effects. Metabolomics will be a promising technique for improving clinical care in MS.

Molecular biomarkers in multiple sclerosis

Multiple sclerosis (MS) is a highly heterogenous disease regarding radiological, pathological, and clinical characteristics and therapeutic response, including both the efficacy and safety profile of treatments. Accordingly, there is a high demand for biomarkers that sensitively and specifically apprehend the distinctive aspects of the MS heterogeneity, and that can aid in better understanding of the disease diagnosis, prognosis, prediction of the treatment response, and, finally, in the development of new treatments. Currently, clinical characteristics (e.g., relapse rate and disease progression) and magnetic resonance imaging play the most important role in the clinical classification of MS and assessment of its course. Molecular biomarkers (e.g., immunoglobulin G (IgG) oligoclonal bands, IgG index, anti-aquaporin-4 antibodies, neutralizing antibodies against interferon-beta and natalizumab, anti-varicella zoster virus and anti-John Cunningham (JC) virus antibodies) complement these markers excellently. This review provides an overview of exploratory, validated and clinically useful molecular biomarkers in MS which are used for prediction, diagnosis, disease activity and treatment response.

The Serum Level of Midkine in Patients With Multiple Sclerosis and Neuromyelitis Optica

Introduction

Midkine (MK), a heparin-binding growth factor, is involved in neurological diseases by mediating the inflammatory responses through enhancing the leukocyte migration. The present study assesses the serum concentration of this growth factor among newly developed Multiple Sclerosis (MS) and Neuromyelitis Optica (NMO) patients.

Methods

The present research, as a cross-sectional study, was performed at Isfahan University of Medical Sciences, Isfahan City, Iran. All samples were selected from patients who visited Kashani and Alzahra hospitals for two years (2014 to 2016). The MK level was assessed in 80 new MS cases, 80 NMO patients, and 80 healthy subjects. After collecting blood sera samples, MK serum level was measured using the ELISA. The obtained data were analyzed in SPSS.

Results

The Mean±SD MK level was 1038.58±44.73 pg/mL in the MS group, which was significantly higher than the Mean±SD MK level in the NMO (872.62±55.42 pg/mL) and control groups (605.02±9.42 pg/mL).

Conclusion

Overall, these results demonstrated that MK plays a prominent role in inflammatory reactions and neuroautoimmune diseases, especially in MS. So, the MK level may be used for earlier diagnosis and also prevention of disease progression by using a special inhibitor.

Serum GFAP and NfL levels in benign relapsing-remitting multiple sclerosis

OBJECTIVE

We aimed to investigate serum glial fibrillary acidic protein (GFAP) and serum neurofilament light chain (NfL) levels as potential discriminative biomarkers between benign relapsing-remitting multiple sclerosis (BRRMS) and aggressive relapsing-remitting MS (ARRMS).

METHODS

Serum GFAP and NfL levels were analyzed in patients with BRRMS (n = 34), ARRMS (n = 29), and healthy controls (n = 14) by using Single Molecule Array (Simoa). Patients with ARRMS had been treated with highly effective disease-modifying treatments (DMT) (fingolimod or natalizumab).

RESULTS

Serum GFAP levels in both BRRMS (median 210.19 pg/ml, IQR 163.69-287.19) and in ARRMS (median 188.60 pg/ml, IQR39.23-244.93) were significantly higher (p = 0.035 and p = 0.034, respectively) compared to healthy controls (median 117.93 pg/ml, IQR 60.28-183.83). Serum GFAP levels did not differ between BRRMS and ARRMS. There were no statistical differences in NfL levels between BRRMS, ARRMS and healthy controls. GFAP level was significantly higher (p = 0.04) in BRRMS without DMT (median 216.04 pg/ml, IQR 188.60-274.79) than in those BRRMS patients who had used DMT (median 196.26 pg/ml, IQR 133.33-325.54).

CONCLUSIONS

We found elevated levels of serum GFAP in both BRRMS and ARRMS compared to healthy controls, reflecting astrocytic activation. Serum NfL did not differ between BRRMS and ARRMS, probably due to the stable inflammatory phase of the disease and effective DMT use in ARRMS. Single serum NfL and GFAP measurements cannot separate a patient with BRRMS from effectively treated ARRMS after a long history of the disease, thus consecutive samples are needed in the follow-up.

Outcome measures assisting treatment optimization in multiple sclerosis

Objective

To review instruments used to assess disease stability or progression in persons with multiple sclerosis (pwMS) that can guide clinicians in optimizing therapy.

Methods

A non-systematic review of scientific literature was undertaken to explore modalities of monitoring symptoms and the disease evolution of MS.

Results

Multiple outcome measures, or tools, have been developed for use in MS research as well as for the clinical management of pwMS. Beginning with the Expanded Disability Status Scale, introduced in 1983, clinicians and researchers have developed monitoring modalities to assess all aspects of MS and the neurological impairment it causes.

Conclusions

Much progress has been made in recent decades for the management of MS and for the evaluation of disease progression. New technology, such as wearable sensors, will provide new opportunities to better understand changes in function, dexterity, and cognition. Essential work over the decades since EDSS was introduced continues to improve our ability to treat this debilitating disease.

Neurofilament light chain as a biomarker of meningoencephalitis of unknown etiology in dogs

BACKGROUND

Neurofilament light chain (NfL) is a neuron-specific cytoskeletal protein expressed in axons. Damaged axons of the central nervous system release NfLs into the cerebrospinal fluid (CSF) and the blood. In humans with neurologic diseases, NfL is used as a biomarker.

OBJECTIVES

To identify the potential of NfL as a supportive tool for the diagnosis, prognosis, and monitoring of meningoencephalitis of unknown etiology (MUE) in dogs.

ANIMALS

Twenty-six client-owned healthy dogs, 10 normal Beagle dogs, and 38 client-owned MUE dogs.

METHODS

Cohort study. The concentrations of NfL in serum and CSF were measured using single-molecule array technology.

RESULTS

Median NfL concentration was significantly higher in MUE dogs (serum, 125 pg/mL; CSF, 14 700 pg/mL) than in healthy dogs (serum, 11.8 pg/mL, P < .0001; CSF, 1410 pg/mL, P = .0002). The areas under the receiver operating characteristic curves of serum and CSF NfL concentrations were 0.99 and 0.95, respectively. The cut-off values were 41.5 pg/mL (serum) and 4005 pg/mL (CSF) for differentiating between healthy and MUE dogs, with sensitivities of 89.19% and 90%, respectively, and specificities of 96.97% and 100%, respectively. The NfL concentration showed a significant decrease (pretreatment, 122 pg/mL; posttreatment, 36.6 pg/mL; P = .02) in the good treatment-response group and a significant increase (pretreatment, 292.5 pg/mL; posttreatment, 1880 pg/mL, P = .03) in the poor treatment-response group.

CONCLUSIONS AND CLINICAL IMPORTANCE

Neurofilament light chain is a potential biomarker for diagnosing MUE and evaluating response to treatment.

The potential of serum neurofilament as biomarker for multiple sclerosis

Multiple sclerosis is a highly heterogeneous disease, and the detection of neuroaxonal damage as well as its quantification is a critical step for patients. Blood-based serum neurofilament light chain (sNfL) is currently under close investigation as an easily accessible biomarker of prognosis and treatment response in patients with multiple sclerosis. There is abundant evidence that sNfL levels reflect ongoing inflammatory-driven neuroaxonal damage (e.g. relapses or MRI disease activity) and that sNfL levels predict disease activity over the next few years. In contrast, the association of sNfL with long-term clinical outcomes or its ability to reflect slow, diffuse neurodegenerative damage in multiple sclerosis is less clear. However, early results from real-world cohorts and clinical trials using sNfL as a marker of treatment response in multiple sclerosis are encouraging. Importantly, clinical algorithms should now be developed that incorporate the routine use of sNfL to guide individualized clinical decision-making in people with multiple sclerosis, together with additional fluid biomarkers and clinical and MRI measures. Here, we propose specific clinical scenarios where implementing sNfL measures may be of utility, including, among others: initial diagnosis, first treatment choice, surveillance of subclinical disease activity and guidance of therapy selection.

Neurofilament Light Chain Levels Are Associated with Disease Activity Determined by No Evident Disease Activity in Multiple Sclerosis Patients

INTRODUCTION

There is a need for blood biomarkers of disease activity in multiple sclerosis (MS). The aim of the study was to assess the relationship between plasma neurofilament light chain (pNfL) and disease activity as defined by the concept three-domain no evident disease activity (NEDA-3).

METHODS

Levels of pNfL (SIMOA) were examined in 159 MS patients and analyzed in relationship to NEDA-3 status (absence of relapse, disability score worsening, and brain magnetic resonance activity) during the last 12 months. The accuracy of the proposed model was evaluated by calculating the area under the receiver operating characteristics (ROC) curve. From the pNfL cutoff, we evaluated the NEDA-NfL status (no relapse, no Expanded Disability Status Scale [EDSS] worsening, and pNfL below the cutoff value).

RESULTS

Levels of pNfL were significantly higher in MS patients than in healthy controls (p <  0.001). From a total of 159 patients, 80 (50.3%) achieved NEDA-3 status, while 79 (49.7%) patients showed evident disease activity (EDA) status. pNfL were significantly lower in the NEDA-3 group than in the EDA group (pNfL mean 7.06 pg/mL [standard deviation (SD) 2.37] vs. pNfL mean 13.04 pg/mL [SD 7.07]) (p < 0.001). ROC analysis showed that pNfL predicts NEDA-3 status (sensitivity and specificity were 80.5 and 72.7%, respectively, p < 0.001), and NEDA-NfL predicts NEDA-3 status (sensitivity and specificity were 97.1 and 82.9%, respectively, p < 0.001).

CONCLUSION

The results show that pNfL levels are a useful biomarker of disease activity determined by NEDA status in patients with MS and could be an alternative to brain magnetic resonance investigation.

Tissue Transglutaminase Expression Associates With Progression of Multiple Sclerosis

Objective

The clinical course of multiple sclerosis (MS) is variable and largely unpredictable pointing to an urgent need for markers to monitor disease activity and progression. Recent evidence revealed that tissue transglutaminase (TG2) is altered in patient-derived monocytes. We hypothesize that blood cell–derived TG2 messenger RNA (mRNA) can potentially be used as biomarker in patients with MS.

Methods

In peripheral blood mononuclear cells (PBMCs) from 151 healthy controls and 161 patients with MS, TG2 mRNA was measured and correlated with clinical and MRI parameters of disease activity (annualized relapse rate, gadolinium-enhanced lesions, and T2 lesion volume) and disease progression (Expanded Disability Status Scale [EDSS], normalized brain volume, and hypointense T1 lesion volume).

Results

PBMC-derived TG2 mRNA levels were significantly associated with disease progression, i.e., worsening of the EDSS over 2 years of follow-up, normalized brain volume, and normalized gray and white matter volume in the total MS patient group at baseline. Of these, in patients with relapsing-remitting MS, TG2 expression was significantly associated with worsening of the EDSS scores over 2 years of follow-up. In the patients with primary progressive (PP) MS, TG2 mRNA levels were significantly associated with EDSS, normalized brain volume, and normalized gray and white matter volume at baseline. In addition, TG2 mRNA associated with T1 hypointense lesion volume in the patients with PP MS at baseline.

Conclusion

PBMC-derived TG2 mRNA levels hold promise as biomarker for disease progression in patients with MS.

Classification of Evidence

This study provides Class II evidence that in patients with MS, PBMC-derived TG2 mRNA levels are associated with disease progression.