Serum Exosome MicroRNAs Predict Multiple Sclerosis Disease Activity after Fingolimod Treatment

Big data and artificial intelligence applied to blood and CSF fluid biomarkers in multiple sclerosis

Artificial intelligence (AI) has meant a turning point in data analysis, allowing predictions of unseen outcomes with precedented levels of accuracy. In multiple sclerosis (MS), a chronic inflammatory-demyelinating condition of the central nervous system with a complex pathogenesis and potentially devastating consequences, AI-based models have shown promising preliminary results, especially when using neuroimaging data as model input or predictor variables. The application of AI-based methodologies to serum/blood and CSF biomarkers has been less explored, according to the literature, despite its great potential. In this review, we aimed to investigate and summarise the recent advances in AI methods applied to body fluid biomarkers in MS, highlighting the key features of the most representative studies, while illustrating their limitations and future directions.

Exosome Content-Mediated Signaling Pathways in Multiple Sclerosis

Exosomes are small extracellular vesicles with a complex lipid-bilayer surface and 30-150 nm diameter. These vesicles play a critical role in intercellular signaling networks during physiopathological processes through data trafficking and cell reprogramming. It has been demonstrated that exosomes are involved in a variety of central nervous system (CNS) disorders such as multiple sclerosis (MS). Exosome mediators' cell-to-cell communication is possibly by delivering their contents such as proteins, RNAs (coding and non-coding), DNAs (mitochondrial and genomic), and transposable elements to the target cells. Exosomal microRNAs (miRNAs) differ in their expression patterns in MS disease, thereby providing novel diagnostic and prognostic biomarkers and therapeutic options for better treatment of MS disease. Furthermore, these microvesicles are non-immunogenic and non-toxic therapeutic tools for transferring miRNAs across the blood-brain barrier (BBB). Collectively, exosomes could be used as novel drug delivery devices for the treatment of MS patients. This review summarized research regarding the exosomes from serum, plasma, PBMC, and other cells in MS patients and experimental models. We also provide a critical view of exosome content-mediated signaling pathways in MS, including TNF-α, TGF-β, NF-κB, and Wnt pathways. The use of exosomes as a therapeutic potential in MS has also been discussed.

Extracellular Vesicles: The Next Generation of Biomarkers and Treatment for Central Nervous System Diseases

It has been widely established that the characterization of extracellular vesicles (EVs), particularly small EVs (sEVs), shed by different cell types into biofluids, helps to identify biomarkers and therapeutic targets in neurological and neurodegenerative diseases. Recent studies are also exploring the efficacy of mesenchymal stem cell-derived extracellular vesicles naturally enriched with therapeutic microRNAs and proteins for treating various diseases. In addition, EVs released by various neural cells play a crucial function in the modulation of signal transmission in the brain in physiological conditions. However, in pathological conditions, such EVs can facilitate the spread of pathological proteins from one brain region to the other. On the other hand, the analysis of EVs in biofluids can identify sensitive biomarkers for diagnosis, prognosis, and disease progression. This review discusses the potential therapeutic use of stem cell-derived EVs in several central nervous system diseases. It lists their differences and similarities and confers various studies exploring EVs as biomarkers. Further advances in EV research in the coming years will likely lead to the routine use of EVs in therapeutic settings.

Extracellular Vesicles in Multiple Sclerosis: Their Significance in the Development and Possible Applications as Therapeutic Agents and Biomarkers

Extracellular vesicles (EVs) are "micro-shuttles" that play a role as mediators of intercellular communication. Cells release EVs into the extracellular environment in both physiological and pathological conditions and are involved in intercellular communication, due to their ability to transfer proteins, lipids, and nucleic acids, and in the modulation of the immune system and neuroinflammation. Because EVs can penetrate the blood-brain barrier and move from the central nervous system to the peripheral circulation, and vice versa, recent studies have shown a substantial role for EVs in several neurological diseases, including multiple sclerosis (MS). MS is a demyelinating disease where the main event is caused by T and B cells triggering an autoimmune reaction against myelin constituents. Recent research has elucidate the potential involvement of extracellular vesicles (EVs) in the pathophysiology of MS, although, to date, their potential role both as agents and therapeutic targets in MS is not fully defined. We present in this review a summary and comprehensive examination of EVs' involvement in the pathophysiology of multiple sclerosis, exploring their potential applications as biomarkers and indicators of therapy response.

Pathway analysis of peripheral blood CD8+ T cell transcriptome shows differential regulation of sphingolipid signaling in multiple sclerosis and glioblastoma

Multiple sclerosis (MS) and glioblastoma (GBM) are CNS diseases in whose development and progression immune privilege is intimately important, but in a relatively opposite manner. Maintenance and strengthening of immune privilege have been shown to be an important mechanism in glioblastoma immune evasion, while the breakdown of immune privilege leads to MS initiation and exacerbation. We hypothesize that molecular signaling pathways can be oppositely regulated in peripheral blood CD8+ T cells of MS and glioblastoma patients at a transcriptional level. We analyzed publicly available data of the peripheral blood CD8+ T cell MS vs. control (MSvsCTRL) and GBM vs. control (GBMvsCTRL) differentially expressed gene (DEG) contrasts with Qiagen's Ingenuity pathway analysis software (IPA). We have identified sphingolipid signaling pathway which was significantly downregulated in the GBMvsCTRL and upregulated in the MSvsCTRL. As the pathway is important for the CD8+ T lymphocytes CNS infiltration, this result is in line with our previously stated hypothesis. Comparing publicly available lists of differentially expressed serum exosomal miRNAs from MSvsCTRL and GBMvsCTRL contrasts, we have identified that hsa-miR-182-5p has the greatest potential effect on sphingolipid signaling regarding the number of regulated DEGs in the GBMvsCTRL contrast, while not being able to find any relevant potential sphingolipid signaling target transcripts in the MSvsCTRL contrast. We conclude that the sphingolipid signaling pathway is a top oppositely regulated pathway in peripheral blood CD8+ T cells from GBM and MS, and might be crucial for the differences in CNS immune privilege maintenance of investigated diseases, but further experimental research is necessary.

Exploring miRNAs' Based Modeling Approach for Predicting PIRA in Multiple Sclerosis: A Comprehensive Analysis

The current hypothesis on the pathophysiology of multiple sclerosis (MS) suggests the involvement of both inflammatory and neurodegenerative mechanisms. Disease Modifying Therapies (DMTs) effectively decrease relapse rates, thus reducing relapse-associated disability in people with MS. In some patients, disability progression, however, is not solely linked to new lesions and clinical relapses but can manifest independently. Progression Independent of Relapse Activity (PIRA) significantly contributes to long-term disability, stressing the urge to unveil biomarkers to forecast disease progression. Twenty-five adult patients with relapsing-remitting multiple sclerosis (RRMS) were enrolled in a cohort study, according to the latest McDonald criteria, and tested before and after high-efficacy Disease Modifying Therapies (DMTs) (6-24 months). Through Agilent microarrays, we analyzed miRNA profiles from peripheral blood mononuclear cells. Multivariate logistic and linear models with interactions were generated. Robustness was assessed by randomization tests in R. A subset of miRNAs, correlated with PIRA, and the Expanded Disability Status Scale (EDSS), was selected. To refine the patient stratification connected to the disease trajectory, we computed a robust logistic classification model derived from baseline miRNA expression to predict PIRA status (AUC = 0.971). We built an optimal multilinear model by selecting four other miRNA predictors to describe EDSS changes compared to baseline. Multivariate modeling offers a promising avenue to uncover potential biomarkers essential for accurate prediction of disability progression in early MS stages. These models can provide valuable insights into developing personalized and effective treatment strategies.

Protein phosphatase 2A modulation and connection with miRNAs and natural products

Protein phosphatase 2A (PP2A), a heterotrimeric holoenzyme (scaffolding, catalytic, and regulatory subunits), regulates dephosphorylation for more than half of serine/threonine phosphosites and exhibits diverse cellular functions. Although several studies on natural products and miRNAs have emphasized their impacts on PP2A regulation, their connections lack systemic organization. Moreover, only part of the PP2A family has been investigated. This review focuses on the PP2A-modulating effects of natural products and miRNAs' interactions with potential PP2A targets in cancer and non-cancer cells. PP2A-modulating natural products and miRNAs were retrieved through a literature search. Utilizing the miRDB database, potential PP2A targets of these PP2A-modulating miRNAs for the whole set (17 members) of the PP2A family were retrieved. Finally, PP2A-modulating natural products and miRNAs were linked via a literature search. This review provides systemic directions for assessing natural products and miRNAs relating to the PP2A-modulating functions in cancer and disease treatments.

Exploiting Sound for Emerging Applications of Extracellular Vesicles

Extracellular vesicles are nano- to microscale, membrane-bound particles released by cells into extracellular space, and act as carriers of biomarkers and therapeutics, holding promising potential in translational medicine. However, the challenges remain in handling and detecting extracellular vesicles for disease diagnosis as well as exploring their therapeutic capability for disease treatment. Here, we review the recent engineering and technology advances by leveraging the power of sound waves to address the challenges in diagnostic and therapeutic applications of extracellular vesicles and biomimetic nanovesicles. We first introduce the fundamental principles of sound waves for understanding different acoustic-assisted extracellular vesicle technologies. We discuss the acoustic-assisted diagnostic methods including the purification, manipulation, biosensing, and bioimaging of extracellular vesicles. Then, we summarize the recent advances in acoustically enhanced therapeutics using extracellular vesicles and biomimetic nanovesicles. Finally, we provide perspectives into current challenges and future clinical applications of the promising extracellular vesicles and biomimetic nanovesicles powered by sound.

Dual Role of Exosome in Neurodegenerative Diseases: A Review Study

INTRODUCTION

Extracellular vesicles (EVs) are one of the crucial means of intercellular communication, which takes many different forms. They are heterogeneous, secreted by a range of cell types, and can be generally classified into microvesicles and exosomes depending on their location and function. Exosomes are small EVs with diameters of about 30-150 nm and diverse cell sources.

METHODS

The MEDLINE/PubMed database was reviewed for papers written in English and publication dates of recent years, using the search string "Exosome" and "Neurodegenerative diseases."

RESULTS

The exosomes have attracted interest as a significant biomarker for a better understanding of disease development, gene silencing delivery, and alternatives to stem cell-based therapy because of their low-invasive therapeutic approach, repeatable distribution in the central nervous system (CNS), and high efficiency. Also, they are nanovesicles that carry various substances, which can have an impact on neural plasticity and cognitive functioning in both healthy and pathological circumstances. Therefore, exosomes are conceived as nanovesicles containing proteins, lipids, and nucleic acids. However, their composition varies considerably depending on the cells from which they are produced.

CONCLUSION

In the present review, we discuss several techniques for the isolation of exosomes from different cell sources. Furthermore, reviewing research on exosomes' possible functions as carriers of bioactive substances implicated in the etiology of neurodegenerative illnesses, we further examine them. We also analyze the preclinical and clinical research that shows exosomes to have therapeutic potential.

Exosome-based regenerative rehabilitation: A novel ice breaker for neurological disorders

Neurological disorders affect a large population, often leading to different levels of disability and resulting in decreased quality of life. Due to the limited recovery obtained from surgical procedures and other medical approaches, a large number of patients with prolonged dysfunction receive neurorehabilitation protocols to improve their neural plasticity and regeneration. However, the poor neural regeneration ability cannot effectively rebuild the tissue integrity and neural functional networks; consequently, the prognoses of neurorehabilitation remain undetermined. To increase the chances of neural regeneration and functional recovery for patients with neurological disorders, regenerative rehabilitation was introduced with combined regenerative medicine and neurorehabilitation protocols to repair neural tissue damage and create an optimized biophysical microenvironment for neural regeneration potential. With the deepening of exosome research, an increasing number of studies have found that the systemic therapeutic effects of neurorehabilitation approaches are mediated by exosomes released by physically stimulated cells, which provides new insight into rehabilitative mechanisms. Meanwhile, exosome therapy also serves as an alternative cell-free therapy of regenerative medicine that is applied in partnership with neurorehabilitation approaches and formulates exosome-based neurological regenerative rehabilitation. In this study, we review the current state of exosome-associated neurorehabilitation. On the one hand, we focus on presenting the varied mediating effects of exosomes in neurorehabilitation protocols of specific neurological pathologies; on the other hand, we discuss the diverse combinations of exosome therapies and neurorehabilitation approaches in the field of neurological regenerative rehabilitation, aiming to increase the awareness of exosome research and applications in the rehabilitation of neurological disorders.

A systematic review of the application of machine-learning algorithms in multiple sclerosis

INTRODUCTION

The applications of artificial intelligence, and in particular automatic learning or "machine learning" (ML), constitute both a challenge and a great opportunity in numerous scientific, technical, and clinical disciplines. Specific applications in the study of multiple sclerosis (MS) have been no exception, and constitute an area of increasing interest in recent years.

OBJECTIVE

We present a systematic review of the application of ML algorithms in MS.

MATERIALS AND METHODS

We used the PubMed search engine, which allows free access to the MEDLINE medical database, to identify studies including the keywords "machine learning" and "multiple sclerosis." We excluded review articles, studies written in languages other than English or Spanish, and studies that were mainly technical and did not specifically apply to MS. The final selection included 76 articles, and 38 were rejected.

CONCLUSIONS

After the review process, we established 4 main applications of ML in MS: 1) classifying MS subtypes; 2) distinguishing patients with MS from healthy controls and individuals with other diseases; 3) predicting progression and response to therapeutic interventions; and 4) other applications. Results found to date have shown that ML algorithms may offer great support for health professionals both in clinical settings and in research into MS.

Abnormal DNA methylation analysis of leucine-rich glioma-inactivated 1 antibody encephalitis reveals novel methylation-driven genes related to prognostic and clinical features

BACKGROUND

Aberrant DNA methylation occurs commonly during pathogenesis of neuroimmunological diseases and is of clinical value in various encephalitis subtypes. However, knowledge of the impact of DNA methylation changes on pathogenesis of leucine-rich glioma-inactivated 1 (LGI1) antibody encephalitis remains limited.

METHODS

A total of 44 cytokines and 10 immune checkpoint moleculars (ICMs) in the serum of patients with LGI1 encephalitis and healthy donors (HDs) were measured to evaluate the association of them with clinical parameters. Genome-wide DNA methylation profiles were performed in peripheral blood mononuclear cell (PBMC) from LGI1 encephalitis patients and HDs using reduced representation bisulfite sequencing (RRBS) and validated for the methylation status by pyrosequencing. MicroRNA profiles were acquired in serum exosome by small RNA sequencing. Targeted cytokines expression was assessed at the presence or absence of miR-2467-5p in PBMCs and the culture media, and the binding of miR-2467-5p and its targeted genes was validated by luciferase assay.

RESULTS

There existed significant difference in 22 cytokines/chemokines and 6 ICMs between LGI1 encephalitis patients and HDs. Decreased PDCD1 with increased ICAM1 could predict unfavorable prognosis in one-year follow-up for LGI1 encephalitis patients. Fifteen of cytokines/chemokines and ICMs presented DNA-methylated changes in the promoter and gene body using RRBS in which five were verified as methylation status by pyrosequencing, and the methylation level of CSF3, CCL2, and ICAM1 was conversely associated with their expression in PBMCs. By combining RRBS data with exosome-derived microRNA sequencing, we found that hypomethylated-driven hsa-miR-2467-5p presented elevated expression in serum exosomes and PBMCs in LGI1 encephalitis. Mechanically, miR-2467-5p significantly induced reduced expression of CSF3 and PDCD1 by binding with their 3`UTR while enhanced CCL15 expression, but not significantly correlated with peripheral blood CD19 + B cell proportion of LGI1 encephalitis patients.

CONCLUSIONS

Our results provided convincing evidence for DNA methylation changes, microRNA profiles in serum exosome for LGI1 encephalitis, and we also identified several novel cytokines related to clinical features in which some represented epigenetic modification of methylated-driven pattern and microRNA modulation. Our study contributed to develop treatment for epigenetic pathogenesis in LGI1 encephalitis.

Advances in Therapeutic Applications of Extracellular Vesicles

Extracellular vesicles (EVs) are nanoscale bilayer phospholipid membrane vesicles released by cells. Contained large molecules such as nucleic acid, protein, and lipid, EVs are an integral part of cell communication. The contents of EVs vary based on the cell source and play an important role in both pathological and physiological conditions. EVs can be used as drugs or targets in disease treatment, and changes in the contents of EVs can indicate the progression of diseases. In recent years, with the continuous exploration of the structure, characteristics, and functions of EVs, the potential of engineered EVs for drug delivery and therapy being constantly explored. This review provides a brief overview of the structure, characteristics and functions of EVs, summarizes the advanced application of EVs and outlook on the prospect of it. It is our hope that this review will increase understanding of the current development of medical applications of EVs and help us overcome future challenges.

miRNA 548a-3p as biomarker of NEDA-3 at 2 years in multiple sclerosis patients treated with fingolimod

BACKGROUND

Multiple sclerosis (MS) is a disabling autoimmune demyelinating disorder affecting young people and causing significant disability. In the last decade, different microRNA (miRNA) expression patterns have been associated to several treatment response therapies such as interferon and glatiramer acetate. Nowadays, there is increasing interest in the potential role of miRNA as treatment response biomarkers to the most recent oral and intravenous treatments. In this study, we aimed to evaluate serum miRNAs as biomarkers of No Evidence of Disease Activity (NEDA-3) at 2 years in patients with relapsing remitting MS (RRMS) treated with fingolimod.

MAIN BODY

A Discovery cohort of 31 RRMS patients treated with fingolimod were identified from the CLIMB study and classified as No Evidence of Disease Activity (NEDA-3) or Evidence of Disease Activity (EDA-3) after 2 years on treatment. Levels of miRNA expression were measured at 6 months using human serum miRNA panels and compared in EDA-3 and NEDA-3 groups using the Wilcoxon rank sum test. A set of differentially expressed miRNA was further validated in an independent cohort of 22 fingolimod-treated patients. We found that 548a-3p serum levels were higher levels in fingolimod-treated patients classified as NEDA-3, compared to the EDA-3 group in both the Discovery (n = 31; p = 0.04) and Validation (n = 22; p = 0.03) cohorts 6 months after treatment initiation; miR-548a-3p provided an AUC of 0.882 discriminating patients with NEDA-3 at 2 years in the Validation cohort.

CONCLUSION

Our results show differences in miR-548a-3p expression at 6 months after fingolimod start in patients with MS with NEDA-3 at 2 years. These results provide class III evidence of the use of miR-548a-3p as biomarker of NEDA-3 in patients with fingolimod.

Increased NLRP3 Inflammasome Activation and Pyroptosis in Patients With Multiple Sclerosis With Fingolimod Treatment Failure

BACKGROUND AND OBJECTIVES

Inflammasomes are involved in the pathogenesis of different neuroimmune and neurodegenerative diseases, including multiple sclerosis (MS). In a previous study by our group, the nucleotide-binding oligomerization domain, leucine-rich repeat receptor and pyrin-domain-containing 3 (NLRP3) inflammasome was reported to be associated with the response to interferon-beta in MS. Based on recent data showing the potential for the oral therapy fingolimod to inhibit NLRP3 inflammasome activation, here we investigated whether fingolimod could also be implicated in the response to this therapy in patients with MS.

METHODS

NLRP3 gene expression levels were measured by real-time PCR in peripheral blood mononuclear cells at baseline and after 3, 6, and 12 months in a cohort of patients with MS treated with fingolimod (N = 23), dimethyl fumarate (N = 21), and teriflunomide (N = 21) and classified into responders and nonresponders to the treatment according to clinical and radiologic criteria. In a subgroup of fingolimod responders and nonresponders, the percentage of monocytes with an oligomer of ASC was determined by flow cytometry, and the levels of interleukin (IL)-1β, IL-18, IL-6, tumor necrosis factor (TNF)α, and galectin-3 were quantified by ELISA.

RESULTS

NLPR3 expression levels were significantly increased in fingolimod nonresponders after 3 (p = 0.03) and 6 months (p = 0.008) of treatment compared with the baseline but remained similar in responders at all time points. These changes were not observed in nonresponders to the other oral therapies tested. The formation of an oligomer of ASC in monocytes after lipopolysaccharide and adenosine 5'-triphosphate stimulation was significantly decreased in responders (p = 0.006) but increased in nonresponders (p = 0.0003) after 6 months of fingolimod treatment compared with the baseline. Proinflammatory cytokine release from stimulated peripheral blood mononuclear cells was comparable between responders and nonresponders, but galectin-3 levels on cell supernatants, as a marker of cell damage, were significantly increased in fingolimod nonresponders (p = 0.02).

DISCUSSION

The differential effect of fingolimod on the formation of an inflammasome-triggered ASC oligomer in monocytes between responders and nonresponders could be used as a response biomarker after 6 months of fingolimod treatment and suggests that fingolimod may exert their beneficial effects by reducing inflammasome signaling in a subset of patients with MS.

Role of stem cell derivatives in inflammatory diseases

Mesenchymal stem cells (MSCs) are pluripotent stem cells of mesodermal origin with the ability of self-renewal and multidirectional differentiation, which have all the common characteristics of stem cells and the ability to differentiate into adipocytes, osteoblasts, neuron-like cells and other cells. Stem cell derivatives are extracellular vesicles(EVs) released from mesenchymal stem cells that are involved in the process of body’s immune response, antigen presentation, cell differentiation, and anti-inflammatory. EVs are further divided into ectosomes and exosomes are widely used in degenerative diseases, cancer, and inflammatory diseases due to their parental cell characteristics. However, most diseases are closely related to inflammation, and exosomes can mitigate the damage caused by inflammation in terms of suppressing the inflammatory response, anti-apoptosis and promoting tissue repair. Stem cell-derived exosomes have become an emerging modality for cell-free therapy because of their high safety and ease of preservation and transportation through intercellular communication. In this review, we highlight the characteristics and functions of MSCs-derived exosomes and discuss the regulatory mechanisms of MSCs-derived exosomes in inflammatory diseases and their potential applications in clinical diagnosis and therapy.

Exosomes as biomarkers and therapeutic delivery for autoimmune diseases: Opportunities and challenges

Exosomes are spherical lipid bilayer vesicles composed of lipids, proteins and nucleic acids that deliver signaling molecules through a vesicular transport system to regulate the function and morphology of target cells, thereby involving in a variety of biological processes, such as cell apoptosis or proliferation, and cytokine production. In the past decades, there are emerging evidence that exosomes play pivotal roles in the pathological mechanisms of several autoimmune diseases (ADs), including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes mellitus (T1DM), Sjogren's syndrome (SS), multiple sclerosis (MS), inflammatory bowel disease (IBD). systemic sclerosis (SSc), etc. Several publications have shown that exosomes are involved in the pathogenesis of ADs mainly through intercellular communication and by influencing the response of immune cells. The level of exosomes and the expression of nucleic acids can reflect the degree of disease progression and are excellent biomarkers for ADs. In addition, exosomes have the potential to be used as drug carriers thanks to their biocompatibility and stability. In this review, we briefly summarized the current researches regarding the biological functions of exosomes in ADs, and provided an insight into the potential of exosomes as biomarkers and therapeutic delivery for these diseases.

Exosome Structures Supported by Machine Learning Can Be Used as a Promising Diagnostic Tool

Principal component analysis (PCA) as a machine-learning technique could serve in disease diagnosis and prognosis by evaluating the dynamic morphological features of exosomes via Cryo-TEM-imaging. This hypothesis was investigated after the crude isolation of similarly featured exosomes derived from the extracellular vehicles (EVs) of immature dendritic cells (IDCs) JAWSII. It is possible to identify functional molecular groups by FTIR, but the unique physical and morphological characteristics of exosomes can only be revealed by specialized imaging techniques such as cryo-TEM. On the other hand, PCA has the ability to examine the morphological features of each of these IDC-derived exosomes by considering software parameters such as various membrane projections and differences in Gaussians, Hessian, hue, and class to assess the 3D orientation, shape, size, and brightness of the isolated IDC-derived exosome structures. In addition, Brownian motions from nanoparticle tracking analysis of EV IDC-derived exosomes were also compared with EV IDC-derived exosome images collected by scanning electron microscopy and confocal microscopy. Sodium-Dodecyl-Sulphate-Polyacrylamide-Gel-Electrophoresis (SDS-PAGE) was performed to separate the protein content of the crude isolates showing that no considerable protein contamination occurred during the crude isolation technique of IDC-derived-exosomes. This is an important finding because no additional purification of these exosomes is required, making PCA analysis both valuable and novel.

The role of machine learning in developing non-magnetic resonance imaging based biomarkers for multiple sclerosis: a systematic review

BACKGROUND

Multiple sclerosis (MS) is a neurological condition whose symptoms, severity, and progression over time vary enormously among individuals. Ideally, each person living with MS should be provided with an accurate prognosis at the time of diagnosis, precision in initial and subsequent treatment decisions, and improved timeliness in detecting the need to reassess treatment regimens. To manage these three components, discovering an accurate, objective measure of overall disease severity is essential. Machine learning (ML) algorithms can contribute to finding such a clinically useful biomarker of MS through their ability to search and analyze datasets about potential biomarkers at scale. Our aim was to conduct a systematic review to determine how, and in what way, ML has been applied to the study of MS biomarkers on data from sources other than magnetic resonance imaging.

METHODS

Systematic searches through eight databases were conducted for literature published in 2014-2020 on MS and specified ML algorithms.

RESULTS

Of the 1, 052 returned papers, 66 met the inclusion criteria. All included papers addressed developing classifiers for MS identification or measuring its progression, typically, using hold-out evaluation on subsets of fewer than 200 participants with MS. These classifiers focused on biomarkers of MS, ranging from those derived from omics and phenotypical data (34.5% clinical, 33.3% biological, 23.0% physiological, and 9.2% drug response). Algorithmic choices were dependent on both the amount of data available for supervised ML (91.5%; 49.2% classification and 42.3% regression) and the requirement to be able to justify the resulting decision-making principles in healthcare settings. Therefore, algorithms based on decision trees and support vector machines were commonly used, and the maximum average performance of 89.9% AUC was found in random forests comparing with other ML algorithms.

CONCLUSIONS

ML is applicable to determining how candidate biomarkers perform in the assessment of disease severity. However, applying ML research to develop decision aids to help clinicians optimize treatment strategies and analyze treatment responses in individual patients calls for creating appropriate data resources and shared experimental protocols. They should target proceeding from segregated classification of signals or natural language to both holistic analyses across data modalities and clinically-meaningful differentiation of disease.

EVAtool: an optimized reads assignment tool for small ncRNA quantification and its application in extracellular vesicle datasets

Extracellular vesicles (EVs) carrying various small non-coding RNAs (sncRNAs) play a vital roles in cell communication and diseases. Correct quantification of multiple sncRNA biotypes simultaneously in EVs is a challenge due to the short reads (<30 bp) could be mapped to multiple sncRNA types. To address this question, we developed an optimized reads assignment algorithm (ORAA) to dynamically map multi-mapping reads to the sncRNA type with a higher proportion. We integrated ORAA with reads processing steps into EVAtool Python-package (http://bioinfo.life.hust.edu.cn/EVAtool) to quantify sncRNAs, especially for sncRNA-seq from EV samples. EVAtool allows users to specify interested sncRNA types in advanced mode or use default seven sncRNAs (microRNA, small nucleolar RNA, PIWI-interacting RNAs, small nuclear RNA, ribosomal RNA, transfer RNA and Y RNA). To prove the utilities of EVAtool, we quantified the sncRNA expression profiles for 200 samples from cognitive decline and multiple sclerosis. We found that more than 20% of short reads on average were mapped to multiple sncRNA biotypes in multiple sclerosis. In cognitive decline, the proportion of Y RNA is significantly higher than other sncRNA types. EVAtool is a flexible and extensible tool that would benefit to mine potential biomarkers and functional molecules in EVs.

microRNA Expression and Its Association With Disability and Brain Atrophy in Multiple Sclerosis Patients Treated With Glatiramer Acetate

Background

MicroRNAs are small non-coding RNA that regulate gene expression at a post-transcriptional level affecting several cellular processes including inflammation, neurodegeneration and remyelination. Different patterns of miRNAs expression have been demonstrated in multiple sclerosis compared to controls, as well as in different courses of the disease. For these reason they have been postulated as promising biomarkers candidates in multiple sclerosis.

Objective

to correlate serum microRNAs profile expression with disability, cognitive functioning and brain volume in patients with remitting-relapsing multiple sclerosis.

Methods

cross-sectional study in relapsing-remitting multiple sclerosis patients treated with glatiramer acetate. Disability was measured with Expanded Disability Status Scale (EDSS) and cognitive function was studied with Symbol Digit Modalities Test (SDMT). Brain volume was analyzed with automatic software NeuroQuant®.

Results

We found an association between miR.146a.5p (rs:0.434, p=0.03) and miR.9.5p (rs:0.516, p=0.028) with EDSS; and miR-146a.5p (rs:-0.476, p=0.016) and miR-126.3p (rs:-0.528, p=0.007) with SDMT. Regarding to the brain volume, miR.9.5p correlated with thalamus (rs:-0.545, p=0.036); miR.200c.3p with pallidum (rs:-0.68, p=0.002) and cerebellum (rs:-0.472, p=0.048); miR-138.5p with amygdala (rs:0.73, p=0.016) and pallidum (rs:0.64, p=0.048); and miR-223.3p with caudate (rs:0.46, p=0.04).

Conclusions

These data support the hypothesis of microRNA as potential biomarkers in this disease. More studies are needed to validate these results and to better understand the role of microRNAs in the pathogenesis, monitoring and therapeutic response of multiple sclerosis.

Machine Learning-Based Models for Detection of Biomarkers of Autoimmune Diseases by Fragmentation and Analysis of miRNA Sequences

Thanks to high-throughput data technology, microRNA analysis studies have evolved in early disease detection. This work introduces two complete models to detect the biomarkers of two autoimmune diseases, multiple sclerosis and rheumatoid arthritis, via miRNA analysis. Based on work the authors published previously, both introduced models involve complete pipelines of text mining methods, integrated with traditional machine learning methods, and LSTM deep learning. This work also studies the fragmentation of miRNA sequences to reduce the needed processing time and computational power. Moreover, this work studies the impact of obtaining two different library preparation kits (NEBNEXT and NEXTFLEX) on the detection accuracy for rheumatoid arthritis. Additional experiments are applied to the proposed models based on three different transcriptomic datasets. The results denote that the transcriptomic fragmentation model reported a biomarker detection accuracy of 96.45% on a sequence fragment size of 0.2, indicating a significant reduction in execution power while retaining biomarker detection accuracy. On the other hand, the LSTM model obtained a promising detection accuracy of 72%, implying savings in feature engineering processing. Additionally, the fragmentation model and the LSTM model reported 22.4% and 87.5% less execution time than work in the literature, respectively, denoting a considerable execution power reduction.

Applications of Phyto-Nanotechnology for the Treatment of Neurodegenerative Disorders

The strategies involved in the development of therapeutics for neurodegenerative disorders are very complex and challenging due to the existence of the blood-brain barrier (BBB), a closely spaced network of blood vessels and endothelial cells that functions to prevent the entry of unwanted substances in the brain. The emergence and advancement of nanotechnology shows favourable prospects to overcome this phenomenon. Engineered nanoparticles conjugated with drug moieties and imaging agents that have dimensions between 1 and 100 nm could potentially be used to ensure enhanced efficacy, cellular uptake, specific transport, and delivery of specific molecules to the brain, owing to their modified physico-chemical features. The conjugates of nanoparticles and medicinal plants, or their components known as nano phytomedicine, have been gaining significance lately in the development of novel neuro-therapeutics owing to their natural abundance, promising targeted delivery to the brain, and lesser potential to show adverse effects. In the present review, the promising application, and recent trends of combined nanotechnology and phytomedicine for the treatment of neurological disorders (ND) as compared to conventional therapies, have been addressed. Nanotechnology-based efforts performed in bioinformatics for early diagnosis as well as futuristic precision medicine in ND have also been discussed in the context of computational approach.

Profiling of Plasma Extracellular Vesicle Transcriptome Reveals That circRNAs Are Prevalent and Differ between Multiple Sclerosis Patients and Healthy Controls

(1) Background: Extracellular vesicles (EVs) are released by most cell types and are implicated in several biological and pathological processes, including multiple sclerosis (MS). Differences in the number and cargo of plasma-derived EVs have been described in MS. In this work, we have characterised the EV RNA cargo of MS patients, with particular attention to circular RNAs (circRNAs), which have attracted increasing attention for their roles in physiology and disease and their biomarker potential. (2) Methods: Plasma-derived EVs were isolated by differential centrifugation (20 patients, 8 controls), and RNA-Sequencing was used to identify differentially expressed linear and circRNAs. (3) Results: We found differences in the RNA type distribution, circRNAs being enriched in EVs vs. leucocytes. We found a number of (corrected p-value < 0.05) circRNA significantly DE between the groups. Nevertheless, highly structured circRNAs are preferentially retained in leukocytes. Differential expression analysis reports significant differences in circRNA and linear RNA expression between MS patients and controls, as well as between different MS types. (4) Conclusions: Plasma derived EV RNA cargo is not a representation of leukocytes’ cytoplasm but a message worth studying. Moreover, our results reveal the interest of circRNAs as part of this message, highlighting the importance of further understanding RNA regulation in MS.

The pathogenic, therapeutic and diagnostic role of exosomal microRNA in the autoimmune diseases

Exosomes are a nano-vesicle surrounded by a bilipid layer that can release from almost all cells and could be detected in tissues and biological liquids. These vesicles contain lipids, proteins, and nucleic acids (including DNA, mRNA, and miRNA) inside and on the exosomes' surface constitute their content. Exosomes can transfer their cargo into the recipient cell, which can modify recipient cells' biological activities. Recently it has been deciphering that the miRNA pattern of exosomes reveals the cellular pathophysiological situation and modifies various biological processes. Increasing data regarding exosomes highlights that the exosomes and their cargo, especially miRNAs, are implicated in the pathophysiology of various disorders, such as autoimmune disease. The current evidence on the deciphering of mechanisms in which exosomal miRNAs contributed to autoimmunity was indicated that exosomal miRNA might hold information that can reprogram the function of many of the immune cells involved in autoimmune diseases' pathogenesis. In the present study, we summarized the pathogenic role of exosomal miRNAs in several autoimmune diseases, including myasthenia gravis (MG), psoriasis, inflammatory bowel disease (IBD), type 1 diabetes (T1D), multiple sclerosis (MS), systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), Sjogren's Syndrome (SS), systemic sclerosis (SSc), vitiligo, and autoimmune thyroid diseases (AITD). Moreover, in this work, we present evidence of the potential role of exosomal miRNAs as therapeutic and diagnostic agents in autoimmune diseases.

Potential Roles of Extracellular Vesicles as Biomarkers and a Novel Treatment Approach in Multiple Sclerosis

Extracellular vesicles (EVs) are a heterogeneous group of bilayer membrane-wrapped molecules that play an important role in cell-to-cell communication, participating in many physiological processes and in the pathogenesis of several diseases, including multiple sclerosis (MS). In recent years, many studies have focused on EVs, with promising results indicating their potential role as biomarkers in MS and helping us better understand the pathogenesis of the disease. Recent evidence suggests that there are novel subpopulations of EVs according to cell origin, with those derived from cells belonging to the nervous and immune systems providing information regarding inflammation, demyelination, axonal damage, astrocyte and microglia reaction, blood–brain barrier permeability, leukocyte transendothelial migration, and ultimately synaptic loss and neuronal death in MS. These biomarkers can also provide insight into disease activity and progression and can differentiate patients’ disease phenotype. This information can enable new pathways for therapeutic target discovery, and consequently the development of novel treatments. Recent evidence also suggests that current disease modifying treatments (DMTs) for MS modify the levels and content of circulating EVs. EVs might also serve as biomarkers to help monitor the response to DMTs, which could improve medical decisions concerning DMT initiation, choice, escalation, and withdrawal. Furthermore, EVs could act not only as biomarkers but also as treatment for brain repair and immunomodulation in MS. EVs are considered excellent delivery vehicles. Studies in progress show that EVs containing myelin antigens could play a pivotal role in inducing antigen-specific tolerance of autoreactive T cells as a novel strategy for the treatment as “EV-based vaccines” for MS. This review explores the breakthrough role of nervous and immune system cell-derived EVs as markers of pathological disease mechanisms and potential biomarkers of treatment response in MS. In addition, this review explores the novel role of EVs as vehicles for antigen delivery as a therapeutic vaccine to restore immune tolerance in MS autoimmunity.

Exosomes as cell-derivative carriers in the diagnosis and treatment of central nervous system diseases

Exosomes are extracellular vesicles with the diameter ranging from 50 to 100 nm and are found in different body fluids such as blood, cerebrospinal fluid (CSF), urine and saliva. Like in case of various diseases, based on the parent cells, the content of exosomes (protein, mRNA, miRNA, DNA, lipids and metabolites) varies and thus can be utilized as potential biomarker for diagnosis and prognosis of the brain diseases. Furthermore, utilizing the natural potential exosomes to cross the blood–brain barrier and by specifically decorating it with the ligand as per the desired brain sites therapeutics can be delivered to brain parenchyma. This review article conveys the importance of exosomes and their use in the treatment and diagnosis of brain/central nervous system diseases.

Central Nervous System Cell-Derived Exosomes in Neurodegenerative Diseases

Exosomes are a type of extracellular vesicles secreted by almost all kinds of mammalian cells that shuttle "cargo" from one cell to another, indicative of its role in cell-to-cell transportation. Interestingly, exosomes are known to undergo alterations or serve as a pathway in multiple diseases, including neurodegenerative diseases. In the central nervous system (CNS), exosomes originating from neurons or glia cells contribute to or inhibit the progression of CNS-related diseases in special ways. In lieu of this, the current study investigated the effect of CNS cell-derived exosomes on different neurodegenerative diseases.

Extracellular vesicles (exosomes and ectosomes) play key roles in the pathology of brain diseases

Last century, neurons and glial cells were mostly believed to play distinct functions, relevant for the brain. Progressively, however, it became clear that neurons, astrocytes and microglia co-operate intensely with each other by release/binding of signaling factors, direct surface binding and generation/release of extracellular vesicles, the exosomes and ectosomes, called together vesicles in this abstract. The present review is focused on these vesicles, fundamental in various brain diseases. Their properties are extraordinary. The specificity of their membrane governs their fusion with distinct target cells, variable depending on the state and specificity of their cells of origin and target. Result of vesicle fusion is the discharge of their cargos into the cytoplasm of target cells. Cargos are composed of critical molecules, from proteins (various nature and function) to nucleotides (especially miRNAs), playing critical roles in immune and neurodegenerative diseases. Among immune diseases is multiple sclerosis, affected by extensive dysregulation of co-trafficking neural and glial vesicles, with distinct miRNAs inducing severe or reducing effects. The vesicle-dependent differences between progressive and relapsing-remitting forms of the disease are relevant for clinical developments. In Alzheimer’s disease the vesicles can affect the brain by changing their generation and inducing co-release of effective proteins, such Aβ and tau, from neurons and astrocytes. Specific miRNAs can delay the long-term development of the disease. Upon their traffic through the blood-brainbarrier, vesicles of various origin reach fluids where they are essential for the identification of biomarkers, important for diagnostic and therapeutic innovations, critical for the future of many brain patients.

Secreted Extracellular Vesicle Molecular Cargo as a Novel Liquid Biopsy Diagnostics of Central Nervous System Diseases

Secreted extracellular vesicles (EVs) are heterogeneous cell-derived membranous granules which carry a large diversity of molecules and participate in intercellular communication by transferring these molecules to target cells by endocytosis. In the last decade, EVs’ role in several pathological conditions, from etiology to disease progression or therapy evasion, has been consolidated, including in central nervous system (CNS)-related disorders. For this review, we performed a systematic search of original works published, reporting the presence of molecular components expressed in the CNS via EVs, which have been purified from plasma, serum or cerebrospinal fluid. Our aim is to provide a list of molecular EV components that have been identified from both nonpathological conditions and the most common CNS-related disorders. We discuss the methods used to isolate and enrich EVs from specific CNS-cells and the relevance of its components in each disease context.

Recent Advances on Extracellular Vesicles in Central Nervous System Diseases

Extracellular vesicles (EVs) are particles released by multiple cells, encapsulated by lipid bilayers and containing a variety of biological materials, including proteins, nucleic acids, lipids and metabolites. With the advancement of separation and characterization methods, EV subtypes and their complex and diverse functions have been recognized. In the central nervous system (CNS), EVs are involved in various physiological and pathological processes, such as regulation of neuronal firing, synaptic plasticity, formation and maintenance of myelin sheath, propagation of neuroinflammation, neuroprotection, and spread and removal of toxic protein aggregates. Activity-dependent alteration of constituents enables EVs to reflect the change of cell and tissue states, and the wide distribution of EVs in biological fluids endows them with potential as diagnostic and prognostic biomarkers for CNS diseases, including neurodegenerative disease, cerebrovascular disease, traumatic brain disease, and brain tumor. Favorable biocompatibility, ability of crossing the blood–brain barrier and protecting contents from degradation, give promising therapeutic effects of EVs, either collected from mesenchymal stem cells culture conditioned media, or designed as drug delivery vehicles loaded with specific agents. In this review, we summarized EVs’ basic biological properties, and mainly focused on their applications in CNS diseases.

A systematic review of the application of machine-learning algorithms in multiple sclerosis

INTRODUCTION

The applications of artificial intelligence, and in particular automatic learning or "machine learning" (ML), constitute both a challenge and a great opportunity in numerous scientific, technical, and clinical disciplines. Specific applications in the study of multiple sclerosis (MS) have been no exception, and constitute an area of increasing interest in recent years.

OBJECTIVE

We present a systematic review of the application of ML algorithms in MS.

MATERIALS AND METHODS

We used the PubMed search engine, which allows free access to the MEDLINE medical database, to identify studies including the keywords "machine learning" and "multiple sclerosis." We excluded review articles, studies written in languages other than English or Spanish, and studies that were mainly technical and did not specifically apply to MS. The final selection included 76 articles, and 38 were rejected.

CONCLUSIONS

After the review process, we established 4 main applications of ML in MS: 1) classifying MS subtypes; 2) distinguishing patients with MS from healthy controls and individuals with other diseases; 3) predicting progression and response to therapeutic interventions; and 4) other applications. Results found to date have shown that ML algorithms may offer great support for health professionals both in clinical settings and in research into MS.

Extracellular Vesicles in Neuroinflammation

Extracellular vesicles (EVs) are a heterogenous group of membrane-bound particles that play a pivotal role in cell–cell communication, not only participating in many physiological processes, but also contributing to the pathogenesis of several diseases. The term EVs defines many and different vesicles based on their biogenesis and release pathway, including exosomes, microvesicles (MVs), and apoptotic bodies. However, their classification, biological function as well as protocols for isolation and detection are still under investigation. Recent evidences suggest the existence of novel subpopulations of EVs, increasing the degree of heterogeneity between EV types and subtypes. EVs have been shown to have roles in the CNS as biomarkers and vehicles of drugs and other therapeutic molecules. They are known to cross the blood brain barrier, allowing CNS EVs to be detectable in peripheral fluids, and their cargo may give information on parental cells and the pathological process they are involved in. In this review, we summarize the knowledge on the function of EVs in the pathogenesis of multiple sclerosis (MS) and discuss recent evidences for their potential applications as diagnostic biomarkers and therapeutic targets.

Precision Medicine in Neurodegenerative Diseases: Some Promising Tips Coming from the microRNAs' World

: Novel insights in the development of a precision medicine approach for treating the neurodegenerative diseases (NDDs) are provided by emerging advances in the field of pharmacoepigenomics. In this context, microRNAs (miRNAs) have been extensively studied because of their implication in several disorders related to the central nervous system, as well as for their potential role as biomarkers of diagnosis, prognosis, and response to treatment. Recent studies in the field of neurodegeneration reported evidence that drug response and efficacy can be modulated by miRNA-mediated mechanisms. In fact, miRNAs seem to regulate the expression of pharmacology target genes, while approved (conventional and non-conventional) therapies can restore altered miRNAs observed in NDDs. The knowledge of miRNA pharmacoepigenomics may offers new clues to develop more effective treatments by providing novel insights into interindividual variability in drug disposition and response. Recently, the therapeutic potential of miRNAs is gaining increasing attention, and miRNA-based drugs (for cancer) have been under observation in clinical trials. However, the effective use of miRNAs as therapeutic target still needs to be investigated. Here, we report a brief review of representative studies in which miRNAs related to therapeutic effects have been investigated in NDDs, providing exciting potential prospects of miRNAs in pharmacoepigenomics and translational medicine.