Toward Precision Phenotyping of Multiple Sclerosis

The molecular subtypes of autoimmune diseases

Autoimmune diseases (ADs) are characterized by their complexity and a wide range of clinical differences. Despite patients presenting with similar symptoms and disease patterns, their reactions to treatments may vary. The current approach of personalized medicine, which relies on molecular data, is seen as an effective method to address the variability in these diseases. This review examined the pathologic classification of ADs, such as multiple sclerosis and lupus nephritis, over time. Acknowledging the limitations inherent in pathologic classification, the focus shifted to molecular classification to achieve a deeper insight into disease heterogeneity. The study outlined the established methods and findings from the molecular classification of ADs, categorizing systemic lupus erythematosus (SLE) into four subtypes, inflammatory bowel disease (IBD) into two, rheumatoid arthritis (RA) into three, and multiple sclerosis (MS) into a single subtype. It was observed that the high inflammation subtype of IBD, the RA inflammation subtype, and the MS "inflammation & EGF" subtype share similarities. These subtypes all display a consistent pattern of inflammation that is primarily driven by the activation of the JAK-STAT pathway, with the effective drugs being those that target this signaling pathway. Additionally, by identifying markers that are uniquely associated with the various subtypes within the same disease, the study was able to describe the differences between subtypes in detail. The findings are expected to contribute to the development of personalized treatment plans for patients and establish a strong basis for tailored approaches to treating autoimmune diseases.

Individual Prognostication of Disease Activity and Disability Worsening in Multiple Sclerosis With Retinal Layer Thickness z Scores

BACKGROUND AND OBJECTIVES

Retinal optical coherence tomography (OCT) provides promising prognostic imaging biomarkers for future disease activity in multiple sclerosis (MS). However, raw OCT-derived measures have multiple dependencies, supporting the need for establishing reference values adjusted for possible confounders. The purpose of this study was to investigate the capacity for age-adjusted z scores of OCT-derived measures to prognosticate future disease activity and disability worsening in people with MS (PwMS).

METHODS

We established age-adjusted OCT reference data using generalized additive models for location, scale, and shape for peripapillary retinal nerve fiber layer (pRNFL) and ganglion cell-inner plexiform layer (GCIP) thicknesses, involving 910 and 423 healthy eyes, respectively. Next, we transformed the retinal layer thickness of PwMS from 3 published studies into age-adjusted z scores (pRNFL-z and GCIP-z) based on the reference data. Finally, we investigated the association of pRNFL-z or GCIP-z as predictors with future confirmed disability worsening (Expanded Disability Status Scale score increase) or disease activity (failing of the no evidence of disease activity [NEDA-3] criteria) as outcomes. Cox proportional hazards models or logistic regression analyses were applied according to the original studies. Optimal cutoffs were identified using the Akaike information criterion as well as location with the log-rank and likelihood-ratio tests.

RESULTS

In the first cohort (n = 863), 172 PwMS (24%) had disability worsening over a median observational period of 2.0 (interquartile range [IQR]:1.0-3.0) years. Low pRNFL-z (≤-2.04) were associated with an increased risk of disability worsening (adjusted hazard ratio (aHR) [95% CI] = 2.08 [1.47-2.95], p = 3.82e-5). In the second cohort (n = 170), logistic regression analyses revealed that lower pRNFL-z showed a higher likelihood for disability accumulation at the two-year follow-up (reciprocal odds ratio [95% CI] = 1.51[1.06-2.15], p = 0.03). In the third cohort (n = 78), 46 PwMS (59%) did not maintain the NEDA-3 status over a median follow-up of 2.0 (IQR: 1.9-2.1) years. PwMS with low GCIP-z (≤-1.03) had a higher risk of showing disease activity (aHR [95% CI] = 2.14 [1.03-4.43], p = 0.04). Compared with raw values with arbitrary cutoffs, applying the z score approach with optimal cutoffs showed better performance in discrimination and calibration (higher Harrell's concordance index and lower integrated Brier score).

DISCUSSION

In conclusion, our work demonstrated reference cohort-based z scores that account for age, a major driver for disease progression in MS, to be a promising approach for creating OCT-derived measures useable across devices and toward individualized prognostication.

Predictive potential of serum and cerebrospinal fluid biomarkers for disease activity in treated multiple sclerosis patients

BACKGROUND

Our objective was to explore various biomarkers for predicting suboptimal responses to disease-modifying treatments (DMTs) in patients with MS (pwMS).

METHODS

We conducted a longitudinal, bicentric study with pwMS stratified based on their DMTs responses. Treatment failure (TF) was defined as the onset of a second relapse, presence of two or more T2 new lesions, or disability progression independent of relapse during the follow-up period. We evaluated intrathecal synthesis (ITS) of IgG and IgM using OCB, linear indices, and Reibergrams. Free kappa light chains ITS was assessed using the linear index (FKLCi). NfL and GFAP in serum and CSF, and CHI3L1 in CSF were quantified. Quantitative variables were dichotomized based on the third quartile. Predictive efficacy was assessed through bivariate and multivariate analyses, adjusting for age, sex, EDSS, acute inflammatory activity (AI) -defined as the onset of a relapse or gadolinium-enhancing lesions within a 90-day window of lumbar puncture-, treatment modality, study center, and time from disease onset to treatment initiation. In case of collinearity, multiple models were generated or confounding variables were excluded if collinearity existed between them and the biomarker. The same methodology was used to investigate the predictive potential of various combinations of two biomarkers, based on whether any of them tested positive or exceeded the third quartile.

RESULTS

A total of 137 pwMS were included. FKLCi showed no differences based on AI, no correlation with EDSS and was significantly higher in pwMS with TF (p = 0.008). FKLCi>130 was associated with TF in bivariate analysis (Log-Rank p = 0.004). Due to collinearity between age and EDSS, two different models were generated with each of them and the rest of the confounding variables, in which FKLCi>130 showed a Hazard Ratio (HR) of 2.69 (CI: 1.35-5.4) and 2.67 (CI: 1.32-5.4), respectively. The combination of either FKLC or sNfL exceeding the third quartile was also significant in bivariate (Log-Rank p = 0.04) and multivariate (HR=3.1 (CI: 1.5-6.5)) analyses. However, when analyzed independently, sNfL did not show significance, and FKLCi mirrored the pattern obtained in the previous model (HR: 3.04; CI: 1.51-6.1). Treatment with highefficacy DMTs emerged as a protective factor in all models.

DISCUSSION

Our analysis and the fact that FKLCi is independent of EDSS and AI suggest that it might be a valuable parameter for discriminating aggressive phenotypes. We propose implementing high-efficacy drugs in pwMS with elevated FKLCi.

Myelin debris phagocytosis in demyelinating disease

Demyelinating diseases are often caused by a variety of triggers, including immune responses, viral infections, malnutrition, hypoxia, or genetic factors, all of which result in the loss of myelin in the nervous system. The accumulation of myelin debris at the lesion site leads to neuroinflammation and inhibits remyelination; therefore, it is crucial to promptly remove the myelin debris. Initially, Fc and complement receptors on cellular surfaces were the primary clearance receptors responsible for removing myelin debris. However, subsequent studies have unveiled the involvement of additional receptors, including Mac-2, TAM receptors, and the low-density lipoprotein receptor-related protein 1, in facilitating the removal process. In addition to microglia and macrophages, which serve as the primary effector cells in the disease phase, a variety of other cell types such as astrocytes, Schwann cells, and vascular endothelial cells have been demonstrated to engage in the phagocytosis of myelin debris. Furthermore, we have concluded that oligodendrocyte precursor cells, as myelination precursor cells, also exhibit this phagocytic capability. Moreover, our research group has innovatively identified the low-density lipoprotein receptor as a potential phagocytic receptor for myelin debris. In this article, we discuss the functional processes of various phagocytes in demyelinating diseases. We also highlight the alterations in signaling pathways triggered by phagocytosis, and provide a comprehensive overview of the various phagocytic receptors involved. Such insights are invaluable for pinpointing potential therapeutic strategies for the treatment of demyelinating diseases by targeting phagocytosis.

An Overview of Multiple Sclerosis In Vitro Models

Multiple sclerosis (MS) still poses a challenge in terms of complex etiology, not fully effective methods of treatment, and lack of healing agents. This neurodegenerative condition considerably affects the comfort of life by causing difficulties with movement and worsening cognition. Neuron, astrocyte, microglia, and oligodendrocyte activity is engaged in multiple pathogenic processes associated with MS. These cells are also utilized in creating in vitro cellular models for investigations focusing on MS. In this article, we present and discuss a summary of different in vitro models useful for MS research and describe their development. We discuss cellular models derived from animals or humans and present in the form of primary cell lines or immortalized cell lines. In addition, we characterize cell cultures developed from induced pluripotent stem cells (iPSCs). Culture conditions (2D and 3D cultures) are also discussed.

Digital Pathology Identifies Associations between Tissue Inflammatory Biomarkers and Multiple Sclerosis Outcomes

BACKGROUND

Multiple sclerosis (MS) is a clinically heterogeneous disease underpinned by inflammatory, demyelinating and neurodegenerative processes, the extent of which varies between individuals and over the course of the disease. Recognising the clinicopathological features that most strongly associate with disease outcomes will inform future efforts at patient phenotyping.

AIMS

We used a digital pathology workflow, involving high-resolution image acquisition of immunostained slides and opensource software for quantification, to investigate the relationship between clinical and neuropathological features in an autopsy cohort of progressive MS.

METHODS

Sequential sections of frontal, cingulate and occipital cortex, thalamus, brain stem (pons) and cerebellum including dentate nucleus (n = 35 progressive MS, females = 28, males = 7; age died = 53.5 years; range 38-98 years) were immunostained for myelin (anti-MOG), neurons (anti-HuC/D) and microglia/macrophages (anti-HLA). The extent of demyelination, neurodegeneration, the presence of active and/or chronic active lesions and quantification of brain and leptomeningeal inflammation was captured by digital pathology.

RESULTS

Digital analysis of tissue sections revealed the variable extent of pathology that characterises progressive MS. Microglia/macrophage activation, if found at a higher level in a single block, was typically elevated across all sampled blocks. Compartmentalised (perivascular/leptomeningeal) inflammation was associated with age-related measures of disease severity and an earlier death.

CONCLUSION

Digital pathology identified prognostically important clinicopathological correlations in MS. This methodology can be used to prioritise the principal pathological processes that need to be captured by future MS biomarkers.

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.

The Role of Diet in Multiple Sclerosis Onset: A Prospective Study Using UK Biobank

Multiple sclerosis (MS) is a debilitating autoimmune condition primarily affecting young adults, and its rise is evident globally. Despite this, its precise etiology remains elusive. Both genetic and environmental factors contribute to MS susceptibility; however, the link between diet and MS lacks substantial evidence due to limited large-scale studies. We exploited the UK Biobank resources to explore the nexus between diet, lifestyle, and MS risk. The dietary and lifestyle habits of MS incident cases, derived from a general food frequency questionnaire (FFQ) completed by all participants at study enrollment, were compared to those of subjects who did not develop MS during the follow-up. Our findings suggest the protective role of moderate oily fish consumption and weekly alcohol intake. Furthermore, by analyzing food intake data obtained through 24 h recall, completed by a subset of participants, we found a protective, though non-significant, trend of an increased adherence to the Mediterranean diet (MD). These findings, derived from the analysis of the UK Biobank and representing an unprecedented approach for this inquiry, warrant further exploration and integration in future research.

Understanding multiple sclerosis as a disease spectrum: above and below the clinical threshold

PURPOSE OF REVIEW

Research in multiple sclerosis (MS) has long been predicated on clinical groupings that do not reflect the underlying biologic heterogeneity apparent within patient populations. This review explicates the various levels of explanation through which the spectrum of disease is described and investigated both above and below the clinical threshold of detection, as framed by the topographical model of MS, to help advance a cogent mechanistic framework.

RECENT FINDINGS

Contemporary evidence has amended the view of MS as consisting of sequential disease phases in favor of a spectrum of disease with an admixture of interdependent and dynamic pathobiological axes driving tissue injury and progression. Recent studies have shown the presence of acute and compartmentalized inflammation and mechanisms of neurodegeneration beginning early and evolving throughout the disease continuum. Still, the gap between the understanding of immunopathologic processes in MS and the tools used to measure relevant molecular, laboratory, radiologic, and clinical metrics needs attention to enable better prognostication of disease and monitoring for changes along specific pathologic axes and variable treatment outcomes.

SUMMARY

Aligning on a consistently-applied mechanistic framework at distinct levels of explanation will enable greater precision across bench and clinical research, and inform discourse on drivers of disability progression and delivery of care for individuals with MS.

Blood-Brain Barrier-Targeting Nanoparticles: Biomaterial Properties and Biomedical Applications in Translational Neuroscience

Overcoming the blood-brain barrier (BBB) remains a significant hurdle in effective drug delivery to the brain. While the BBB serves as a crucial protective barrier, it poses challenges in delivering therapeutic agents to their intended targets within the brain parenchyma. To enhance drug delivery for the treatment of neurological diseases, several delivery technologies to circumvent the BBB have been developed in the last few years. Among them, nanoparticles (NPs) are one of the most versatile and promising tools. Here, we summarize the characteristics of NPs that facilitate BBB penetration, including their size, shape, chemical composition, surface charge, and importantly, their conjugation with various biological or synthetic molecules such as glucose, transferrin, insulin, polyethylene glycol, peptides, and aptamers. Additionally, we discuss the coating of NPs with surfactants. A comprehensive overview of the common in vitro and in vivo models of the BBB for NP penetration studies is also provided. The discussion extends to discussing BBB impairment under pathological conditions and leveraging BBB alterations under pathological conditions to enhance drug delivery. Emphasizing the need for future studies to uncover the inherent therapeutic properties of NPs, the review advocates for their role beyond delivery systems and calls for efforts translating NPs to the clinic as therapeutics. Overall, NPs stand out as a highly promising therapeutic strategy for precise BBB targeting and drug delivery in neurological disorders.

From progression to progress: The future of multiple sclerosis

Significant advances have been made in the diagnosis and treatment of multiple sclerosis in recent years yet challenges remain. The current classification of MS phenotypes according to disease activity and progression, for example, does not adequately reflect the underlying pathophysiological mechanisms that may be acting in an individual with MS at different time points. Thus, there is a need for clinicians to transition to a management approach based on the underlying pathophysiological mechanisms that drive disability in MS. A Canadian expert panel convened in January 2023 to discuss priorities for clinical discovery and scientific exploration that would help advance the field. Five key areas of focus included: identifying a mechanism-based disease classification system; developing biomarkers (imaging, fluid, digital) to identify pathologic processes; implementing a data-driven approach to integrate genetic/environmental risk factors, clinical findings, imaging and biomarker data, and patient-reported outcomes to better characterize the many factors associated with disability progression; utilizing precision-based treatment strategies to target different disease processes; and potentially preventing disease through Epstein-Barr virus (EBV) vaccination, counselling about environmental risk factors (e.g. obesity, exercise, vitamin D/sun exposure, smoking) and other measures. Many of the tools needed to meet these needs are currently available. Further work is required to validate emerging biomarkers and tailor treatment strategies to the needs of individual patients. The hope is that a more complete view of the individual's pathobiology will enable clinicians to usher in an era of truly personalized medicine, in which more informed treatment decisions throughout the disease course achieve better long-term outcomes.

A rapid review of differences in cerebrospinal neurofilament light levels in clinical subtypes of progressive multiple sclerosis

Background

Multiple sclerosis (MS) is divided into three clinical phenotypes: relapsing-remitting MS (RRMS), secondary progressive MS (SPMS), and primary progressive MS (PPMS). It is unknown to what extent SPMS and PPMS pathophysiology share inflammatory or neurodegenerative pathological processes. Cerebrospinal (CSF) neurofilament light (NfL) has been broadly studied in different MS phenotypes and is a candidate biomarker for comparing MS subtypes.

Research question

Are CSF NfL levels different among clinical subtypes of progressive MS?

Methods

A search strategy identifying original research investigating fluid neurodegenerative biomarkers in progressive forms of MS between 2010 and 2022 was applied to Medline. Identified articles underwent title and abstract screen and full text review against pre-specified criteria. Data abstraction was limited to studies that measured NfL levels in the CSF. Reported statistical comparisons of NfL levels between clinical phenotypes were abstracted qualitatively.

Results

18 studies that focused on investigating direct comparisons of CSF NfL from people with MS were included in the final report. We found NfL levels were typically reported to be higher in relapsing and progressive MS compared to healthy controls. Notably, higher NfL levels were not clearly associated with progressive MS subtypes when compared to relapsing MS, and there was no observed difference in NfL levels between PPMS and SPMS in articles that separately assessed these phenotypes.

Conclusion

CSF NfL levels distinguish individuals with MS from healthy controls but do not differentiate MS subtypes. Broad biological phenotyping is needed to overcome limitations of current clinical phenotyping and improve biomarker translatability to decision-making in the clinic.

Blood metabolomic and transcriptomic signatures stratify patient subgroups in multiple sclerosis according to disease severity

There are no blood-based biomarkers distinguishing patients with relapsing-remitting (RRMS) from secondary progressive multiple sclerosis (SPMS) although evidence supports metabolomic changes according to MS disease severity. Here machine learning analysis of serum metabolomic data stratified patients with RRMS from SPMS with high accuracy and a putative score was developed that stratified MS patient subsets. The top differentially expressed metabolites between SPMS versus patients with RRMS included lipids and fatty acids, metabolites enriched in pathways related to cellular respiration, notably, elevated lactate and glutamine (gluconeogenesis-related) and acetoacetate and bOHbutyrate (ketone bodies), and reduced alanine and pyruvate (glycolysis-related). Serum metabolomic changes were recapitulated in the whole blood transcriptome, whereby differentially expressed genes were also enriched in cellular respiration pathways in patients with SPMS. The final gene-metabolite interaction network demonstrated a potential metabolic shift from glycolysis toward increased gluconeogenesis and ketogenesis in SPMS, indicating metabolic stress which may trigger stress response pathways and subsequent neurodegeneration.

Disentangling multiple sclerosis phenotypes through Mendelian disorders: A network approach

BACKGROUND

The increasing knowledge about multiple sclerosis (MS) pathophysiology has reinforced the need for an improved description of disease phenotypes, connected to disease biology. Growing evidence indicates that complex diseases constitute phenotypical and genetic continuums with "simple," monogenic disorders, suggesting shared pathomechanisms.

OBJECTIVES

The objective of this study was to depict a novel MS phenotypical framework leveraging shared physiopathology with Mendelian diseases and to identify phenotype-specific candidate drugs.

METHODS

We performed an enrichment testing of MS-associated variants with Mendelian disorders genes. We defined a "MS-Mendelian network," further analyzed to define enriched phenotypic subnetworks and biological processes. Finally, a network-based drug screening was implemented.

RESULTS

Starting from 617 MS-associated loci, we showed a significant enrichment of monogenic diseases (p < 0.001). We defined an MS-Mendelian molecular network based on 331 genes and 486 related disorders, enriched in four phenotypic classes: neurologic, immunologic, metabolic, and visual. We prioritized a total of 503 drugs, of which 27 molecules active in 3/4 phenotypical subnetworks and 140 in subnetwork pairs.

CONCLUSION

The genetic architecture of MS contains the seeds of pathobiological multiplicities shared with immune, neurologic, metabolic and visual monogenic disorders. This result may inform future classifications of MS endophenotypes and support the development of new therapies in both MS and rare diseases.

Role of fenofibrate in multiple sclerosis

Multiple sclerosis (MS) is the most frequent inflammatory and demyelinating disease of the central nervous system (CNS). The underlying pathophysiology of MS is the destruction of myelin sheath by immune cells. The formation of myelin plaques, inflammation, and injury of neuronal myelin sheath characterizes its neuropathology. MS plaques are multiple focal regions of demyelination disseminated in the brain's white matter, spinal cords, deep grey matter, and cerebral cortex. Fenofibrate is a peroxisome proliferative activated receptor alpha (PPAR-α) that attenuates the inflammatory reactions in MS. Fenofibrate inhibits differentiation of Th17 by inhibiting the expression of pro-inflammatory signaling. According to these findings, this review intended to illuminate the mechanistic immunoinflammatory role of fenofibrate in mitigating MS neuropathology. In conclusion, fenofibrate can attenuate MS neuropathology by modulating different pathways, including oxidative stress, autophagy, mitochondrial dysfunction, inflammatory-signaling pathways, and neuroinflammation.

Neutrophil extracellular traps in central nervous system (CNS) diseases

Excessive induction of inflammatory and immune responses is widely considered as one of vital factors contributing to the pathogenesis and progression of central nervous system (CNS) diseases. Neutrophils are well-studied members of inflammatory and immune cell family, contributing to the innate and adaptive immunity. Neutrophil-released neutrophil extracellular traps (NETs) play an important role in the regulation of various kinds of diseases, including CNS diseases. In this review, current knowledge on the biological features of NETs will be introduced. In addition, the role of NETs in several popular and well-studied CNS diseases including cerebral stroke, Alzheimer's disease, multiple sclerosis, amyotrophic lateral sclerosis (ALS), and neurological cancers will be described and discussed through the reviewing of previous related studies.

Cladribine and ocrelizumab induce differential miRNA profiles in peripheral blood mononucleated cells from relapsing-remitting multiple sclerosis patients

Background and objectives

Multiple sclerosis (MS) is a chronic, progressive neurological disease characterized by early-stage neuroinflammation, neurodegeneration, and demyelination that involves a spectrum of heterogeneous clinical manifestations in terms of disease course and response to therapy. Even though several disease-modifying therapies (DMTs) are available to prevent MS-related brain damage-acting on the peripheral immune system with an indirect effect on MS lesions-individualizing therapy according to disease characteristics and prognostic factors is still an unmet need. Given that deregulated miRNAs have been proposed as diagnostic tools in neurodegenerative/neuroinflammatory diseases such as MS, we aimed to explore miRNA profiles as potential classifiers of the relapsing-remitting MS (RRMS) patients' prospects to gain a more effective DMT choice and achieve a preferential drug response.

Methods

A total of 25 adult patients with RRMS were enrolled in a cohort study, according to the latest McDonald criteria before (pre-cladribine, pre-CLA; pre-ocrelizumab, pre-OCRE, time T0) and after high-efficacy DMTs, time T1, 6 months post-CLA (n = 10, 7 F and 3 M, age 39.0 ± 7.5) or post-OCRE (n = 15, 10 F and 5 M, age 40.5 ± 10.4) treatment. A total of 15 age- and sex-matched healthy control subjects (9 F and 6 M, age 36.3 ± 3.0) were also selected. By using Agilent microarrays, we analyzed miRNA profiles from peripheral blood mononuclear cells (PBMC). miRNA-target networks were obtained by miRTargetLink, and Pearson's correlation served to estimate the association between miRNAs and outcome clinical features.

Results

First, the miRNA profiles of pre-CLA or pre-OCRE RRMS patients compared to healthy controls identified modulated miRNA patterns (40 and seven miRNAs, respectively). A direct comparison of the two pre-treatment groups at T0 and T1 revealed more pro-inflammatory patterns in the pre-CLA miRNA profiles. Moreover, both DMTs emerged as being capable of reverting some dysregulated miRNAs toward a protective phenotype. Both drug-dependent miRNA profiles and specific miRNAs, such as miR-199a-3p, miR-29b-3p, and miR-151a-3p, emerged as potentially involved in these drug-induced mechanisms. This enabled the selection of miRNAs correlated to clinical features and the related miRNA-mRNA network.

Discussion

These data support the hypothesis of specific deregulated miRNAs as putative biomarkers in RRMS patients' stratification and DMT drug response.

Microglia activation in periplaque white matter in multiple sclerosis depends on age and lesion type, but does not correlate with oligodendroglial loss

Multiple sclerosis (MS) is the most frequent inflammatory and demyelinating disease of the CNS. The disease course in MS is highly variable and driven by a combination of relapse-driven disease activity and relapse-independent disease progression. The formation of new focal demyelinating lesions is associated with clinical relapses; however, the pathological mechanisms driving disease progression are less well understood. Current concepts suggest that ongoing focal and diffuse inflammation within the CNS in combination with an age-associated failure of compensatory and repair mechanisms contribute to disease progression. The aim of our study was to characterize the diffuse microglia activation in periplaque white matter (PPWM) of MS patients, to identify factors modulating its extent and to determine its potential correlation with loss or preservation of oligodendrocytes. We analyzed microglial and oligodendroglial numbers in PPWM in a cohort of 96 tissue blocks from 32 MS patients containing 100 lesions as well as a control cohort (n = 37). Microglia activation in PPWM was dependent on patient age, proximity to lesion, lesion type, and to a lesser degree on sex. Oligodendrocyte numbers were decreased in PPWM; however, increased microglia densities did not correlate with lower oligodendroglial cell counts, indicating that diffuse microglia activation is not sufficient to drive oligodendroglial loss in PPWM. In summary, our findings support the notion of the close relationship between focal and diffuse inflammation in MS and that age is an important modulator of MS pathology.

Reshaping neuroimmunology: diagnosis and treatment in the era of precision medicine

Precision medicine has revolutionized the field of neuroimmunology, with innovative approaches that characterize diseases based on their biology, deeper understanding of the factors leading to heterogeneity within the same disease, development of targeted therapies, and strategies to tailor therapies to each patient. This review explores the impact of precision medicine on various neuroimmunological conditions, including multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), optic neuritis, autoimmune encephalitis, and immune-mediated neuropathies. We discuss advances in disease subtyping, recognition of novel entities, promising biomarkers, and the development of more selective monoclonal antibodies and cutting-edge synthetic cell-based immunotherapies in neuroimmunological disorders. In addition, we analyze the challenges related to affordability and equity in the implementation of these emerging technologies, especially in situations with limited resources.

Data Mining of Microarray Datasets in Translational Neuroscience

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

Alterations of Oligodendrocyte and Myelin Energy Metabolism in Multiple Sclerosis

Multiple sclerosis (MS) is a complex autoimmune disease of the central nervous system (CNS), characterized by demyelination and neurodegeneration. Oligodendrocytes play a vital role in maintaining the integrity of myelin, the protective sheath around nerve fibres essential for efficient signal transmission. However, in MS, oligodendrocytes become dysfunctional, leading to myelin damage and axonal degeneration. Emerging evidence suggests that metabolic changes, including mitochondrial dysfunction and alterations in glucose and lipid metabolism, contribute significantly to the pathogenesis of MS. Mitochondrial dysfunction is observed in both immune cells and oligodendrocytes within the CNS of MS patients. Impaired mitochondrial function leads to energy deficits, affecting crucial processes such as impulse transmission and axonal transport, ultimately contributing to neurodegeneration. Moreover, mitochondrial dysfunction is linked to the generation of reactive oxygen species (ROS), exacerbating myelin damage and inflammation. Altered glucose metabolism affects the energy supply required for oligodendrocyte function and myelin synthesis. Dysregulated lipid metabolism results in changes to the composition of myelin, affecting its stability and integrity. Importantly, low levels of polyunsaturated fatty acids in MS are associated with upregulated lipid metabolism and enhanced glucose catabolism. Understanding the intricate relationship between these mechanisms is crucial for developing targeted therapies to preserve myelin and promote neurological recovery in individuals with MS. Addressing these metabolic aspects may offer new insights into potential therapeutic strategies to halt disease progression and improve the quality of life for MS patients.

Lysosomal acidification dysfunction in microglia: an emerging pathogenic mechanism of neuroinflammation and neurodegeneration

Microglia are the resident innate immune cells in the brain with a major role in orchestrating immune responses. They also provide a frontline of host defense in the central nervous system (CNS) through their active phagocytic capability. Being a professional phagocyte, microglia participate in phagocytic and autophagic clearance of cellular waste and debris as well as toxic protein aggregates, which relies on optimal lysosomal acidification and function. Defective microglial lysosomal acidification leads to impaired phagocytic and autophagic functions which result in the perpetuation of neuroinflammation and progression of neurodegeneration. Reacidification of impaired lysosomes in microglia has been shown to reverse neurodegenerative pathology in Alzheimer's disease. In this review, we summarize key factors and mechanisms contributing to lysosomal acidification impairment and the associated phagocytic and autophagic dysfunction in microglia, and how these defects contribute to neuroinflammation and neurodegeneration. We further discuss techniques to monitor lysosomal pH and therapeutic agents that can reacidify impaired lysosomes in microglia under disease conditions. Finally, we propose future directions to investigate the role of microglial lysosomal acidification in lysosome-mitochondria crosstalk and in neuron-glia interaction for more comprehensive understanding of its broader CNS physiological and pathological implications.

Integrative multi-omics and systems bioinformatics in translational neuroscience: A data mining perspective

Bioinformatic analysis of large and complex omics datasets has become increasingly useful in modern day biology by providing a great depth of information, with its application to neuroscience termed neuroinformatics. Data mining of omics datasets has enabled the generation of new hypotheses based on differentially regulated biological molecules associated with disease mechanisms, which can be tested experimentally for improved diagnostic and therapeutic targeting of neurodegenerative diseases. Importantly, integrating multi-omics data using a systems bioinformatics approach will advance the understanding of the layered and interactive network of biological regulation that exchanges systemic knowledge to facilitate the development of a comprehensive human brain profile. In this review, we first summarize data mining studies utilizing datasets from the individual type of omics analysis, including epigenetics/epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, and spatial omics, pertaining to Alzheimer's disease, Parkinson's disease, and multiple sclerosis. We then discuss multi-omics integration approaches, including independent biological integration and unsupervised integration methods, for more intuitive and informative interpretation of the biological data obtained across different omics layers. We further assess studies that integrate multi-omics in data mining which provide convoluted biological insights and offer proof-of-concept proposition towards systems bioinformatics in the reconstruction of brain networks. Finally, we recommend a combination of high dimensional bioinformatics analysis with experimental validation to achieve translational neuroscience applications including biomarker discovery, therapeutic development, and elucidation of disease mechanisms. We conclude by providing future perspectives and opportunities in applying integrative multi-omics and systems bioinformatics to achieve precision phenotyping of neurodegenerative diseases and towards personalized medicine.

Building a monitoring matrix for the management of multiple sclerosis

Multiple sclerosis (MS) has a longitudinal and heterogeneous course, with an increasing number of therapy options and associated risk profiles, leading to a constant increase in the number of parameters to be monitored. Even though important clinical and subclinical data are being generated, treating neurologists may not always be able to use them adequately for MS management. In contrast to the monitoring of other diseases in different medical fields, no target-based approach for a standardized monitoring in MS has been established yet. Therefore, there is an urgent need for a standardized and structured monitoring as part of MS management that is adaptive, individualized, agile, and multimodal-integrative. We discuss the development of an MS monitoring matrix which can help facilitate data collection over time from different dimensions and perspectives to optimize the treatment of people with MS (pwMS). In doing so, we show how different measurement tools can combined to enhance MS treatment. We propose to apply the concept of patient pathways to disease and intervention monitoring, not losing track of their interrelation. We also discuss the use of artificial intelligence (AI) to improve the quality of processes, outcomes, and patient safety, as well as personalized and patient-centered care. Patient pathways allow us to track the patient's journey over time and can always change (e.g., when there is a switch in therapy). They therefore may assist us in the continuous improvement of monitoring in an iterative process. Improving the monitoring process means improving the care of pwMS.

Hopelessness in Patients with Early-Stage Relapsing-Remitting Multiple Sclerosis

Background

Hopelessness is a risk factor for depression and suicide. There is little information on this phenomenon among patients with relapsing-remitting multiple sclerosis (RRMS), one of the most common causes of disability and loss of autonomy in young adults. The aim of this study was to assess state hopelessness and its associated factors in early-stage RRMS.

Methods

A multicenter, non-interventional study was conducted. Adult patients with a diagnosis of RRMS, a disease duration ≤ 3 years, and an Expanded Disability Status Scale (EDSS) score of 0-5.5 were included. The State-Trait Hopelessness Scale (STHS) was used to measure patients´ hopelessness. A battery of patient-reported and clinician-rated measurements was used to assess clinical status. A multivariate logistic regression analysis was conducted to determine the association between patients' characteristics and state hopelessness.

Results

A total of 189 patients were included. Mean age (standard deviation-SD) was 36.1 (9.4) years and 71.4% were female. Median disease duration (interquartile range-IQR) was 1.4 (0.7, 2.1) years. Symptom severity and disability were low with a median EDSS (IQR) score of 1.0 (0, 2.0). A proportion of 65.6% (n=124) of patients reported moderate-to-severe hopelessness. Hopelessness was associated with older age (p=0.035), depressive symptoms (p=<0.001), a threatening illness perception (p=0.001), and psychological and cognitive barriers to workplace performance (p=0.029) in the multivariate analysis after adjustment for confounders.

Conclusion

Hopelessness was a common phenomenon in early-stage RRMS, even in a population with low physical disability. Identifying factors associated with hopelessness may be critical for implementing preventive strategies helping patients to adapt to the new situation and cope with the disease in the long term.

Defective lysosomal acidification: a new prognostic marker and therapeutic target for neurodegenerative diseases

Lysosomal acidification dysfunction has been implicated as a key driving factor in the pathogenesis of neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease. Multiple genetic factors have been linked to lysosomal de-acidification through impairing the vacuolar-type ATPase and ion channels on the organelle membrane. Similar lysosomal abnormalities are also present in sporadic forms of neurodegeneration, although the underlying pathogenic mechanisms are unclear and remain to be investigated. Importantly, recent studies have revealed early occurrence of lysosomal acidification impairment before the onset of neurodegeneration and late-stage pathology. However, there is a lack of methods for organelle pH monitoring in vivo and a dearth of lysosome-acidifying therapeutic agents. Here, we summarize and present evidence for the notion of defective lysosomal acidification as an early indicator of neurodegeneration and urge the critical need for technological advancement in developing tools for lysosomal pH monitoring and detection both in vivo and for clinical applications. We further discuss current preclinical pharmacological agents that modulate lysosomal acidification, including small molecules and nanomedicine, and their potential clinical translation into lysosome-targeting therapies. Both timely detection of lysosomal dysfunction and development of therapeutics that restore lysosomal function represent paradigm shifts in targeting neurodegenerative diseases.

Three-dimensional multi-parameter brain mapping using MR fingerprinting

The purpose of this study was to develop and test a 3D multi-parameter MR fingerprinting (MRF) method for brain imaging applications. The subject cohort included 5 healthy volunteers, repeatability tests done on 2 healthy volunteers and tested on two multiple sclerosis (MS) patients. A 3D-MRF imaging technique capable of quantifying T1, T2 and T1ρ was used. The imaging sequence was tested in standardized phantoms and 3D-MRF brain imaging with multiple shots (1, 2 and 4) in healthy human volunteers and MS patients. Quantitative parametric maps for T1, T2, T1ρ, were generated. Mean gray matter (GM) and white matter (WM) ROIs were compared for each mapping technique, Bland-Altman plots and intra-class correlation coefficient (ICC) were used to assess repeatability and Student T-tests were used to compare results in MS patients. Standardized phantom studies demonstrated excellent agreement with reference T1/T2/T1ρ mapping techniques. This study demonstrates that the 3D-MRF technique is able to simultaneously quantify T1, T2 and T1ρ for tissue property characterization in a clinically feasible scan time. This multi-parametric approach offers increased potential to detect and differentiate brain lesions and to better test imaging biomarker hypotheses for several neurological diseases, including MS.

Phenotyping variants of tumefactive demyelinating lesions according to clinical and radiological features-A case series

Background

Tumefactive demyelinating lesions (TDLs) are defined as lesions >2 cm on MRI of the brain. They are identified in a range of demyelinating diseases including massive demyelination due to Marburg's acute MS, Schilder's Disease, Balo's concentric sclerosis, and Tumefactive MS. Apart from the rare demyelinating variants which are often diagnosed histologically, there are no detailed data to phenotype TDLs.

Methods

We describe the clinical and radiological features of four similar patients with very large TDLs (>4 cm), that are not consistent with the rare demyelinating variants and may represent a distinct phenotype.

Results

All patients presented with hemiplegia and apraxia. The mean age at onset was 37 years with an equal sex distribution. All patients were diagnosed with Tumefactive demyelination based on MRI and CSF analysis, precluding the need for brain biopsy. All responded to potent immunotherapy (including high dose corticosteroids, plasma exchange, rituximab, and/or cyclophosphamide). The mean lag from diagnosis to treatment was 1 day. The median EDSS at presentation was six and recovery to a median EDSS of two occurred over 6 months.

Conclusion

We propose that Tumefactive lesions larger than 4 cm are termed "Giant demyelinating lesions" (GDLs) not only on the basis of size, but a rapid and fulminant demyelinating presentation leading to acute, severe neurological disability that is, nonetheless, responsive to immunotherapy. Further clinical studies are required to ratify this proposed phenotype, establish the immunological profile and best treatment for such patients.

Combining in vivo proton exchange rate (k ex) MRI with quantitative susceptibility mapping to further stratify the gadolinium-negative multiple sclerosis lesions

Background

Conventional gadolinium (Gd)-enhanced MRI is currently used for stratifying the lesion activity of multiple sclerosis (MS) despite limited correlation with disability and disease activity. The stratification of MS lesion activity needs further improvement to better support clinics.

Purpose

To investigate if the novel proton exchange rate (k _ex ) MRI combined with quantitative susceptibility mapping (QSM) may help to further stratify non-enhanced (Gd-negative) MS lesions.

Materials and methods

From December 2017 to December 2020, clinically diagnosed relapsing-remitting MS patients who underwent MRI were consecutively enrolled in this IRB-approved retrospective study. The customized MRI protocol covered conventional T₂-weighted, T₂-fluid-attenuated-inversion-recovery, pre- and post-contrast T₁-weighted imaging, and quantitative sequences, including k _ex MRI based on direct-saturation removed omega plots and QSM. Each MS lesion was evaluated based on its Gd-enhancement as well as its susceptibility and k _ex elevation compared to the normal appearing white matter. The difference and correlation concerning lesion characteristics and imaging contrasts were analyzed using the Mann-Whitney U test or Kruskal-Wallis test, and Spearman rank analysis with p < 0.05 considered significant.

Results

A total of 322 MS lesions from 30 patients were identified with 153 Gd-enhanced and 169 non-enhanced lesions. We found that the k _ex elevation of all lesions significantly correlated with their susceptibility elevation (r = 0.30, p < 0.001). Within the 153 MS lesions with Gd-enhancement, ring-enhanced lesions showed higher k _ex elevation than the nodular-enhanced ones' (p < 0.001). Similarly, lesions with ring-hyperintensity in QSM also had higher k _ex elevation than the lesions with nodular-QSM-hyperintensity (p < 0.001). Of the 169 Gd-negative lesions, three radiological patterns were recognized according to lesion manifestations on the k _ex map and QSM images: Pattern I (k _ex ⁺ and QSM⁺, n = 114, 67.5%), Pattern II (only k _ex ⁺ or QSM⁺, n = 47, 27.8%) and Pattern III (k _ex ^- and QSM^-, n = 8, 4.7%). Compared to Pattern II and III, Pattern I had higher k _ex (p < 0.001) and susceptibility (p < 0.05) elevation. The percentage of Pattern I of each subject was negatively correlated with the disease duration (r = -0.45, p = 0.015).

Conclusion

As a potential imaging biomarker for inflammation due to oxidative stress, in vivo k _ex MRI combined with QSM is promising in extending the clinical classification of MS lesions beyond conventional Gd-enhanced MRI.