Biomarkers In Multiple Sclerosis Research Articles

Brain volume loss and physical and cognitive impairment in naive multiple sclerosis patients treated with fingolimod: prospective cohort study in Buenos Aires, Argentina.

The percentage of brain volume loss (PBVL) has been classically considered as a biomarker in multiple sclerosis (MS). The objective of the present study was to analyze if the PBVL during the 1st year after the onset of the disease predicts physical and cognitive impairment (CI). Prospective study that included naïve patients without cognitive impairment who initiated MS treatment with fingolimod. Patients were followed for 3 years and relapses, expanded disability status scale (EDSS) progression (defined as worsening of 1 point on the EDSS), the annual PBVL (evaluated by structural image evaluation using normalization of atrophy [SIENA]), and the presence of CI were evaluated. Cognitive impairment was defined in patients who scored at least 2 standard deviations (SDs) below controls on at least 2 domains. The PBVL after 1 year of treatment with fingolimod was used as an independent variable, while CI and EDSS progression at the 3rd year of follow-up as dependent variables. A total of 71 patients were included, with a mean age of 35.4 ± 3 years old. At the 3rd year, 14% of the patients were classified as CI and 6.2% had EDSS progression. In the CI group, the PBVL during the 1st year was - 0.52 (±0.07) versus -0.42 (±0.04) in the no CI group (p < 0.01; odds ratio [OR] = 2.24; 95% confidence interval [CI]: 1.72-2.44). In the group that showed EDSS progression, the PBVL during the 1st year was - 0.59 (±0.05) versus - 0.42 (±0.03) (p < 0.01; OR = 2.33; 95%CI: 1.60-2.55). A higher PBVL during the 1st year in naïve MS patients was independently associated with a significant risk of CI and EDSS progression.

STAT3 and NTRK2 Genes Predicted by the Bioinformatics Approach May Play Important Roles in the Pathogenesis of Multiple Sclerosis and Obsessive-Compulsive Disorder.

Background: There are no data available on the levels of genetic networks between obsessive–compulsive disorder (OCD) and multiple sclerosis (MS). To this point, we aimed to investigate common mechanisms and pathways using bioinformatics approaches to find novel genes that may be involved in the pathogenesis of OCD in MS. Methods: To obtain gene–gene interactions for MS and OCD, the STRING database was used. Cytoscape was then used to reconstruct and visualize graphs. Then, ToppGene and Enrichr were used to identify the main pathological processes and pathways involved in MS-OCD novel genes. Additionally, to predict transcription factors and microRNAs (miRNAs), the Enrichr database and miRDB database were used, respectively. Results: Our bioinformatics analysis showed that the signal transducer and the activator of transcription 3 (STAT3) and neurotrophic receptor tyrosine kinase 2 (NTRK2) genes had connections with 32 shared genes between MS and OCD. Furthermore, STAT3 and NTRK2 had the greatest enrichment parameters (i.e., molecular function, cellular components, and signaling pathways) among ten hub genes. Conclusions: To summarize, data from our bioinformatics analysis showed that there was a significant overlap in the genetic components of MS and OCD. The findings from this study make two contributions to future studies. First, predicted mechanisms related to STAT3 and NTRK2 in the context of MS and OCD can be investigated for pharmacological interventions. Second, predicted miRNAs related to STAT3 and NTRK2 can be tested as biomarkers in MS with OCD comorbidity. However, our study involved bioinformatics research; therefore, considerable experimental work (e.g., postmortem studies, case–control studies, and cohort studies) will need to be conducted to determine the etiology of OCD in MS from a mechanistic view.

Serum neurofilament light chain concentration predicts disease worsening in multiple sclerosis

Background: Serum neurofilament light (sNfL) chain is a promising biomarker reflecting neuro-axonal injury in multiple sclerosis (MS). However, the ability of sNfL to predict outcomes in real-world MS cohorts requires further validation. Objective: The aim of the study is to investigate the associations of sNfL concentration, magnetic resonance imaging (MRI) and retinal optical coherence tomography (OCT) markers with disease worsening in a longitudinal European multicentre MS cohort. Methods: MS patients (n = 309) were prospectively enrolled at four centres and re-examined after 2 years (n = 226). NfL concentration was measured by single molecule array assay in serum. The patients’ phenotypes were thoroughly characterized with clinical examination, retinal OCT and MRI brain scans. The primary outcome was disease worsening at median 2-year follow-up. Results: Patients with high sNfL concentrations (⩾8 pg/mL) at baseline had increased risk of disease worsening at median 2-year follow-up (odds ratio (95% confidence interval) = 2.8 (1.5–5.3), p = 0.001). We found no significant associations of MRI or OCT measures at baseline with risk of disease worsening. Conclusion: Serum NfL concentration was the only factor associated with disease worsening, indicating that sNfL is a useful biomarker in MS that might be relevant in a clinical setting.

Fluid phase biomarkers in multiple sclerosis.

Multiple sclerosis (MS) is highly heterogenic disorder with respect to clinical course, diagnosis, and treatment response. There is an urgent need to search for simply and reliable fluid body biomarker which would assist the diagnosis and prediction of clinical and treatment prognosis. 'Traditional' MS biomarkers, with exception of cerebrospinal fluid oligoclonal bands, still are having limited clinical value. Therefore, there is growing interest in novel molecules and ingredients. The most robust results have been generated with regard to cerebrospinal fluid and serum levels of neurofilament light chains (NfL). However, there are still some limitations related to specificity of NfL which delays its use in everyday practice. We present a new approach to search for biomarkers involving extracellular RNA, particularly microRNA (miRNA), and small extracellular vesicles. MiRNA represents an important molecular mechanism influencing gene expression, including those involved in MS pathogenesis and extracellular vesicles transfer multiple cargo, including myelin molecules from parental cells of central nervous system to the long-distance targets. MiRNAs which control gene expression in cells involved in autoimmune processes in MS as well as extracellular vesicles transferring myelin content might generate a new promising categories of biomarkers of MS.

Monitoring autoimmune diseases by bioelectrochemical detection of autoantibodies. Application to the determination of anti-myelin basic protein autoantibodies in serum of multiple sclerosis patients.

This work reports an amperometric bioplatform for the determination of anti-myelin basic protein autoantibodies (anti-MBP), a relevant biomarker for multiple sclerosis (MS) autoimmune disease. The developed configuration involves the use of carboxylated magnetic microparticles (cMBs) where the protein for specific capture of the target autoantibodies was covalently attached. The immobilized anti-MBP were further conjugated with a secondary antibody labelled with horseradish peroxidase (HRP-anti-hIgG) and amperometric transduction was performed by adding hydrogen peroxide and using hydroquinone (HQ) as redox mediator. The cathodic current resulting from the reduction of the corresponding quinone was directly proportional to the logarithmic concentration of the target autoantibodies. The analytical performance of the developed method for the determination of anti-MBP is competitive in terms of sensitivity and range of linearity with that claimed for the only biosensor reported so far in the literature, as well as with commercially available ELISA kits showing a remarkably shorter assay time. The bioplatform was applied to the analysis of serum samples of healthy individuals and patients diagnosed with MS providing results in agreement with the ELISA methodology.

Exploring Retinal Blood Vessel Diameters as Biomarkers in Multiple Sclerosis.

We aimed to determine whether retinal vessel diameters and retinal oxygen saturation in newly diagnosed patients with multiple sclerosis (pwMS) are different from those of a healthy population. Retinal blood vessel diameters were measured using imaging with a spectrophotometric non-invasive retinal oximeter. Twenty-three newly diagnosed untreated relapsing-remitting MS (RRMS) patients (mean age: 32.2 ± 7.5 years, age range = 18–50 years, 56.5% female) were measured and compared to 23 age- and sex-matched healthy controls (HCs) (mean age: 34.8 ± 8.1 years). Patients with Optic Neuritis were excluded. Retinal venular diameter (143.8 µm versus 157.8 µm: mean; p = 0.0013) and retinal arteriolar diameter (112.6 µm versus 120.6 µm: mean; p = 0.0089) were smaller in pwMS when compared with HCs, respectively. There was no significant difference in the oxygen saturation in retinal venules and arterioles in pwMS (mean: 60.0% and 93.7%; p = 0.5980) compared to HCs (mean: 59.3% and 91.5%; p = 0.8934), respectively. There was a significant difference in the median low contrast visual acuity (2.5% contrast) between the pwMS and the HC groups (p = 0.0143) Retinal arteriolar and venular diameter may have potential as objective biomarkers for MS.

Identifying Multiple Sclerosis Activity

Reverberating throughout neuro-ophthalmology training programs is an informal proverb that the eye is a window into the brain. Almost every neurologic disease may have an ocular manifestation. Multiple sclerosis (MS) is no exception and for retinal imaging has been the prototype application of optical coherence tomography (OCT) in neurologic disease. While publications demonstrating the utility of OCT outcomes as biomarkers in MS have exponentially increased over 20 years,1 the most critical results have emerged in the last few years, showing that OCT measures may have predictive value for disease course and may be sensitive to treatment effects.

Current and Future Biomarkers in Multiple Sclerosis.

Multiple sclerosis (MS) is a debilitating autoimmune disorder. Currently, there is a lack of effective treatment for the progressive form of MS, partly due to insensitive readout for neurodegeneration. The recent development of sensitive assays for neurofilament light chain (NfL) has made it a potential new biomarker in predicting MS disease activity and progression, providing an additional readout in clinical trials. However, NfL is elevated in other neurodegenerative disorders besides MS, and, furthermore, it is also confounded by age, body mass index (BMI), and blood volume. Additionally, there is considerable overlap in the range of serum NfL (sNfL) levels compared to healthy controls. These confounders demonstrate the limitations of using solely NfL as a marker to monitor disease activity in MS patients. Other blood and cerebrospinal fluid (CSF) biomarkers of axonal damage, neuronal damage, glial dysfunction, demyelination, and inflammation have been studied as actionable biomarkers for MS and have provided insight into the pathology underlying the disease process of MS. However, these other biomarkers may be plagued with similar issues as NfL. Using biomarkers of a bioinformatic approach that includes cellular studies, micro-RNAs (miRNAs), extracellular vesicles (EVs), metabolomics, metabolites and the microbiome may prove to be useful in developing a more comprehensive panel that addresses the limitations of using a single biomarker. Therefore, more research with recent technological and statistical approaches is needed to identify novel and useful diagnostic and prognostic biomarker tools in MS.

The analysis of dynamic gene expression patterns in peripheral blood of multiple sclerosis patients indicates possible diagnostic and prognostic biomarkers

IntroductionAmong numerous invasive procedures for the research of biomarkers, blood-based indicators are regarded as marginally non-invasive procedures in the diagnosis and prognosis of demyelinating disorders, including multiple sclerosis (MS). In this study, we looked into the blood-derived gene expression profiles of patients with multiple sclerosis to investigate their clinical traits and linked them with dysregulated gene expressions to establish diagnostic and prognostic indicators. MethodsWe included 51 patients with relapsing-remitting MS (RRMS, n = 31), clinically isolated syndrome (CIS, n = 12), primary progressive MS (PPMS, n = 8) and a control group (n = 51). Using correlational analysis, the transcriptional patterns of chosen gene panels were examined and subsequently related with disease duration and the expanded disease disability score (EDSS). In addition, principal component analysis, univariate regression, and logistic regression analysis were employed to highlight distinct profiles of genes and prognosticate the excellent biomarkers of this illness. ResultsOur findings demonstrated that neurofilament light (NEFL), tumor necrosis factor α (TNF-α), Tau, and clusterin (CLU) were revealed to be increased in recruited patients, whereas the presenilin-1 (PSEN1) and cell-surface glycoprotein-44 (CD44) were downregulated. Principal Component Analysis revealed distinct patterns between the MS and control groups. Correlation analysis indicated co-dependent dysregulated genes and their differential expression with clinical findings. Furthermore, logistic regression demonstrated that Clusterin (AUC=0.940), NEFL (AUC=0.775), TNF-α (AUC=0.817), Tau (AUC=0.749), PSEN1 (AUC=0.6913), and CD44 (AUC=0.832) had diagnostic relevance. Following the univariate linear regression, a significant regression equation was found between EDSS and IGF-1 (R2 adj = 0.10844; p= 0.0060), APP (R2 adj = 0.1107; p= 0.0098), and PSEN1 (R2 adj = 0.1266; p=0.0102). ConclusionThis study exhibits dynamic gene expression patterns that represent the significance of specified genes that are prospective diagnostic and prognostic biomarkers for multiple sclerosis.

Discovering miRNAs Associated With Multiple Sclerosis Based on Network Representation Learning and Deep Learning Methods.

Identifying biomarkers of Multiple Sclerosis is important for the diagnosis and treatment of Multiple Sclerosis. The existing study has shown that miRNA is one of the most important biomarkers for diseases. However, few existing methods are designed for predicting Multiple Sclerosis-related miRNAs. To fill this gap, we proposed a novel computation framework for predicting Multiple Sclerosis-associated miRNAs. The proposed framework uses a network representation model to learn the feature representation of miRNA and uses a deep learning-based model to predict the miRNAs associated with Multiple Sclerosis. The evaluation result shows that the proposed model can predict the miRNAs associated with Multiple Sclerosis precisely. In addition, the proposed model can outperform several existing methods in a large margin.

Role of Chitinase 3-like 1 as a Biomarker in Multiple Sclerosis: A Systematic Review and Meta-analysis.

Background and ObjectivesMultiple sclerosis (MS) is an autoimmune disease confined in the CNS, and its course is frequently subtle and variable. Therefore, predictive biomarkers are needed. In this scenario, we conducted a systematic review and meta-analysis to evaluate the reliability of chitinase 3–like 1 as a biomarker of MS.MethodsResearch through the main scientific databases (PubMed, Scopus, Web of Science, and Cochrane Library) published from January 2010 to December 2020 was performed using the following keywords: “chitinase 3-like 1 and multiple sclerosis” and “YKL40 and multiple sclerosis.” Articles were selected according to the 2020 updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines by 2 authors independently, and data were extracted; 20 of the 90 studies screened were included in the meta-analysis. The main efficacy measure was represented by the standardized mean difference of CSF and blood CHI3L1 levels; Review Manager version 5.4 and R software applications were used for analysis.ResultsHigher levels of CHI3L1 were found in CSF of 673 patients with MS compared with 336 healthy controls (size-weighted mean difference [SMD] 50.88; 95% CI = 44.98–56.79; p < 0.00001) and in 461 patients with MS than 283 patients with clinically isolated syndrome (CIS) (SMD 28.18; 95% CI = 23.59–32.76; p < 0.00001). Mean CSF CHI3L1 levels were significantly higher in 561 converting than 445 nonconverting CIS (SMD 30.6; 95% CI = 28.31–32.93; p < 0.00001). CSF CHI3L1 levels were significantly higher in patients with primary progressive MS (PPMS) than in patients with relapsing-remitting MS (RRMS) (SMD 43.15; 95% CI = 24.41–61.90; p < 0.00001) and in patients with secondary progressive MS (SMD 41.86 with 95% CI = 32.39–51.33; p < 0.00001). CSF CHI3L1 levels in 407 patients with MS during remission phase of disease were significantly higher than those in 395 patients with MS with acute relapse (SMD 10.48; 95% CI = 08.51–12.44; p < 0.00001). The performances of CHI3L1 in blood for differentiating patients with MS from healthy controls were not significant (SMD 0.48; 95% CI = −1.18 to 2.14; p: 0.57).DiscussionCSF levels of CHI3L1 have a strong correlation with the MS pathologic course, in particular with the mechanism of progression of the disease; it helps to distinguish the PPMS from the RRMS. The potential role of CHI3L1 in serum needs to be further studied in the future.

MiR-150-5p and let-7b-5p in Blood Myeloid Extracellular Vesicles Track Cognitive Symptoms in Patients with Multiple Sclerosis.

Cognitive deficits strongly affect the quality of life of patients with multiple sclerosis (MS). However, no cognitive MS biomarkers are currently available. Extracellular vesicles (EVs) contain markers of parental cells and are able to pass from the brain into blood, representing a source of disease biomarkers. The aim of this study was to investigate whether small non-coding microRNAs (miRNAs) targeting synaptic genes and packaged in plasma EVs may reflect cognitive deficits in MS patients. Total EVs were precipitated by Exoquick from the plasma of twenty-six cognitively preserved (CP) and twenty-three cognitively impaired (CI) MS patients belonging to two independent cohorts. Myeloid EVs were extracted by affinity capture from total EVs using Isolectin B4 (IB4). Fourteen miRNAs targeting synaptic genes were selected and measured by RT-PCR in both total and myeloid EVs. Myeloid EVs from CI patients expressed higher levels of miR-150-5p and lower levels of let-7b-5p compared to CP patients. Stratification for progressive MS (PMS) and relapsing-remitting MS (RRMS) and correlation with clinical parameters suggested that these alterations might be attributable to cognitive deficits rather than disease progression. This study identifies miR-150-5p and let-7b-5p packaged in blood myeloid EVs as possible biomarkers for cognitive deficits in MS.

Multiple Sclerosis Biomarker Candidates Revealed by Cell-Type-Specific Interactome Analysis.

Multiple sclerosis (MS) is a demyelinating disorder that affects multiple regions of the central nervous system such as the brain, spinal cord, and optic nerves. Susceptibility to MS, as well as disease progression rates, displays marked patient-to-patient variability. To date, biomarkers that forecast differences in clinical phenotypes and outcomes have been limited. In this context, cell-type-specific interactome analyses offer important prospects and hope for novel diagnostics and therapeutics. We report here an original study using bioinformatic analysis of MS data sets that revealed interaction profiles as well as specific hub proteins in white matter (WM) and gray matter (GM) that appear critical for disease mechanisms. First, cell-type-specific interactome analyses suggested that while interactions within the WM were focused on oligodendrocytes, interactions within the GM were mostly neuron centric. Second, hub proteins such as APP, EGLN3, PTEN, and LRRK2 were identified to be differentially regulated in MS data sets. Lastly, a comparison of the brain and peripheral blood samples identified biomarker candidates such as NRGN, CRTC1, CDC42, and IFITM3 to be differentially expressed in different types of MS. These findings offer a unique cell-type-specific cell-to-cell interaction network in MS and identify potential biomarkers by comparative analysis of the brain and the blood transcriptomics. From a study design and methodology perspective, we suggest that the cell-type-specific interactome analysis is an important systems science frontier that might offer new insights on other neurodegenerative and brain disorders as well.

Synaptic pathology in multiple sclerosis: a role for Nogo-A signaling in astrocytes?

Synaptic pathology in multiple sclerosis: a role for Nogo-A signaling in astrocytes?

An Update on Laboratory-Based Diagnostic Biomarkers for Multiple Sclerosis and Beyond.

Multiple sclerosis (MS) is an immune-mediated central nervous system (CNS) inflammatory demyelinating disease in which analysis of clinical presentation, imaging studies, and laboratory tests aid in diagnosis. This review discusses laboratory tests ordered to rule out and rule in MS, such as the traditional measurement of cerebrospinal fluid (CSF) IgG index and oligoclonal bands. Biomarkers discovered in the past 2 decades, such as aquaporin-4 (AQP4) antibodies and myelin oligodendrocyte glycoprotein (MOG) antibodies, have been incorporated into clinical practice in the diagnosis of disorders referred to as MS mimics. The importance of test selection, assay methodology, optimal sample for testing, and diagnostic utility of these biomarkers is reviewed. Other laboratory testing that can aid in the differentiation between MS and these biomarker-defined CNS demyelinating diseases is described. There is a focus on emerging biomarkers such as the use of kappa immunoglobulin free light chain concentration in CSF and kappa CSF index measurement as an alternative to oligoclonal bands which has a potential for an improvement in laboratory workflows. Finally, the role of biomarkers of disease activity and prognosis are discussed, including neurofilament light chain, glial fibrillary acidic protein, and myelin basic protein. Future perspectives with improved laboratory testing tools and discovery of additional biomarkers are provided. Laboratory testing for demyelinating disorders using CSF and serum are routine practices that can benefit from an update, as novel biomarker-defined entities have reduced the potential for MS misdiagnosis, and CSF/serum biomarkers reinstated in the diagnostic criteria of MS.

Possible roles of sestrin2 in multiple sclerosis and its relationships with clinical outcomes.

Characterized by demyelination, inflammation and axonal damage, multiple sclerosis (MS) is one of the most common disorders of central nervous system led by the immune system. There is an urgent and obvious need for biomarkers for the diagnosis and follow-up of MS. To investigate serum levels of sestrin2 (SESN2), a protein that responds to acute stress, in MS patients. A total of 85 participants, 40 patients diagnosed previously with relapsing-remitting MS and 45 healthy controls, were included. Serum SESN2 parameters were investigated in blood samples drawn from each participant in the patient and control groups. SESN2 levels were significantly lower in MS patients than in controls (z: -3.06; p=0.002). In the ROC analysis of SESN2, the predictive level for MS was 2.36 ng/mL [sensitivity, 72.50%; specificity, 55.56%; p=0.002; area under the curve (AUC)=0.693]. For the cut-off value in both groups, SESN2 was an independent predictor for MS [Exp (B)=3.977, 95% confidence interval (95%CI) 1.507-10.494 and p=0.013]. The decreased expression of SESN2 may play a role in MS pathogenesis, and SESN2 could be used as a biomarker for MS and as immunotherapeutic agent to treat MS.

Update on Multiple Sclerosis Molecular Biomarkers to Monitor Treatment Effects.

Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease of the central nervous system characterized by broad inter- and intraindividual heterogeneity. The relapse rate, disability progression, and lesion load assessed through MRI are used to detect disease activity and response to treatment. Although it is possible to standardize these characteristics in larger patient groups, so far, this has been difficult to achieve in individual patients. Easily detectable molecular biomarkers can be powerful tools, permitting a tailored therapy approach for MS patients. However, only a few molecular biomarkers have been routinely used in clinical practice as the validation process, and their transfer into clinical practice takes a long time. This review describes the characteristics of an ideal MS biomarker, the challenges of establishing new biomarkers, and promising molecular biomarkers from blood or CSF samples used to monitor MS treatment effects in clinical practice.

Emerging Biomarkers of Multiple Sclerosis in the Blood and the CSF: A Focus on Neurofilaments and Therapeutic Considerations

Introduction: Multiple Sclerosis (MS) is the most common immune-mediated chronic neurodegenerative disease of the central nervous system (CNS) affecting young people. This is due to the permanent disability, cognitive impairment, and the enormous detrimental impact MS can exert on a patient’s health-related quality of life. It is of great importance to recognise it in time and commence adequate treatment at an early stage. The currently used disease-modifying therapies (DMT) aim to reduce disease activity and thus halt disability development, which in current clinical practice are monitored by clinical and imaging parameters but not by biomarkers found in blood and/or the cerebrospinal fluid (CSF). Both clinical and radiological measures routinely used to monitor disease activity lack information on the fundamental pathophysiological features and mechanisms of MS. Furthermore, they lag behind the disease process itself. By the time a clinical relapse becomes evident or a new lesion appears on the MRI scan, potentially irreversible damage has already occurred in the CNS. In recent years, several biomarkers that previously have been linked to other neurological and immunological diseases have received increased attention in MS. Additionally, other novel, potential biomarkers with prognostic and diagnostic properties have been detected in the CSF and blood of MS patients. Areas covered: In this review, we summarise the most up-to-date knowledge and research conducted on the already known and most promising new biomarker candidates found in the CSF and blood of MS patients. Discussion: the current diagnostic criteria of MS relies on three pillars: MRI imaging, clinical events, and the presence of oligoclonal bands in the CSF (which was reinstated into the diagnostic criteria by the most recent revision). Even though the most recent McDonald criteria made the diagnosis of MS faster than the prior iteration, it is still not an infallible diagnostic toolset, especially at the very early stage of the clinically isolated syndrome. Together with the gold standard MRI and clinical measures, ancillary blood and CSF biomarkers may not just improve diagnostic accuracy and speed but very well may become agents to monitor therapeutic efficacy and make even more personalised treatment in MS a reality in the near future. The major disadvantage of these biomarkers in the past has been the need to obtain CSF to measure them. However, the recent advances in extremely sensitive immunoassays made their measurement possible from peripheral blood even when present only in minuscule concentrations. This should mark the beginning of a new biomarker research and utilisation era in MS.

High Levels of Cerebrospinal Fluid Kappa Free Light Chains Relate to IgM Intrathecal Synthesis and Might Have Prognostic Implications in Relapsing Multiple Sclerosis.

Cerebrospinal kappa free light chain (KFLC)-index is a marker of intrathecal immunoglobulin synthesis that aids in the diagnosis of multiple sclerosis (MS). However, little evidence exists on its prognostic role. Our aim is to analyze the relationship between KFLC-index and other MS biomarkers and to explore its prognostic role. This is a monocentric observational study in a cohort of 52 people with relapsing MS (pwRMS) performed on prospectively acquired clinical data and with retrospective evaluation of biomarkers. We measured KFLC-index, immunoglobulin intrathecal synthesis, cerebrospinal fluid (CSF) chitinase 3-like 1 (CHI3L1), and neurofilament light protein (NFL) and reviewed MRI to detect leptomeningeal contrast enhancement (LMCE). We compared time to Expanded Disability Status Scale (EDSS) 3 and to initiation of high-efficacy disease-modifying therapies (heDMTs) by multivariate Cox regression analysis. Median KFLC-index correlated with IgG/IgM indexes (p < 0.0001/p < 0.05) and IgG-oligoclonal bands (OCGBs) (p < 0.001). Patients with IgM-oligoclonal bands (OCMBs) had a higher KFLC-index (p = 0.049). KFLC-index was higher in patients with LMCE (p = 0.008) and correlated with CHI3L1 (p = 0.007), but disease activity had no effect on its value. Bivariate and multivariate analyses confirmed KFLC-index > 58 as an independent risk factor for reaching an EDSS of 3 (hazard ratio (HR) = 12.4; 95% CI = 1.1–147; p = 0.047) and for the need of treatment with heDMTs (HR = 3.0; 95% CI = 1.2–7.1; p = 0.0013). To conclude, our data suggest a potential prognostic role of the KFLC-index during the MS course.

Early detection of multiple sclerosis (MS) as a neurodegenerative disease using electrochemical nano-aptasensor

Multiple sclerosis (MS) is a progressive inflammatory disease (neurodegenerative), and its diagnosis is very important. MicroRNAs (miR) are small, non-coding RNAs that are abnormally expressed in many diseases and have been identified as predictive biomarkers for the early detection of diseases. One of the best diagnostic biomarkers of MS is miR-155. In this report, a sensitive, low-cost, non-label electrochemical nano biosensor was used for miR-155 detection. The biosensor comprises a nanocomposite of single-walled carbon nanotubes (SWCNT) and polypyrrole (PPY) on the graphite sheet (GS) substrate which was modified with an aptamer as miR-155 capture probe. All electrochemical measurements were performed in the presence of Fe(CN)63-/4- as a redox probe. The biosensor has a dynamic range of 10 aM to 1 µM with a detection limit of 10 aM. Also, the fabricated biosensor was successfully used in human serum. According to the ease of preparation, almost low cost, good selectivity, repeatability, and reproducibility the proposed biosensor can be a promising candidate for early detection of MS.