Recent insights into the pathology of multiple sclerosis and neuromyelitis optica

Joint radiomics and spatial distribution model for MRI-based discrimination of multiple sclerosis, neuromyelitis optica spectrum disorder, and myelin-oligodendrocyte-glycoprotein-IgG-associated disorder

OBJECTIVE

To develop a discrimination pipeline concerning both radiomics and spatial distribution features of brain lesions for discrimination of multiple sclerosis (MS), aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorder (NMOSD), and myelin-oligodendrocyte-glycoprotein-IgG-associated disorder (MOGAD).

METHODS

Hyperintensity T2 lesions were delineated in 212 brain MRI scans of MS (n = 63), NMOSD (n = 87), and MOGAD (n = 45) patients. To avoid the effect of fixed training/test dataset sampling when developing machine learning models, patients were allocated into 4 sub-groups for cross-validation. For each scan, 351 radiomics and 27 spatial distribution features were extracted. Three models, i.e., multi-lesion radiomics, spatial distribution, and joint models, were constructed using random forest and logistic regression algorithms for differentiating: MS from the others (MS models) and MOGAD from NMOSD (MOG-NMO models), respectively. Then, the joint models were combined with demographic characteristics (i.e., age and sex) to create MS and MOG-NMO discriminators, respectively, based on which a three-disease discrimination pipeline was generated and compared with radiologists.

RESULTS

For classification of both MS-others and MOG-NMO, the joint models performed better than radiomics or spatial distribution model solely. The MS discriminator achieved AUC = 0.909 ± 0.027 and bias-corrected C-index = 0.909 ± 0.027, and the MOG-NMO discriminator achieved AUC = 0.880 ± 0.064 and bias-corrected C-index = 0.883 ± 0.068. The three-disease discrimination pipeline differentiated MS, NMOSD, and MOGAD patients with 75.0% accuracy, prominently outperforming the three radiologists (47.6%, 56.6%, and 66.0%).

CONCLUSIONS

The proposed pipeline integrating multi-lesion radiomics and spatial distribution features could effectively differentiate MS, NMOSD, and MOGAD.

CLINICAL RELEVANCE STATEMENT

The discrimination pipeline merging both radiomics and spatial distribution features of brain lesions may facilitate the differential diagnoses of multiple sclerosis, neuromyelitis optica spectrum disorder, and myelin-oligodendrocyte-glycoprotein-IgG-associated disorder.

KEY POINTS

• Our study introduces an approach by combining radiomics and spatial distribution models. • The joint model exhibited superior performance in distinguishing multiple sclerosis from aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorder and myelin-oligodendrocyte-glycoprotein-IgG-associated disorder as well as discriminating the latter two diseases. • The three-disease discrimination pipeline showcased remarkable accuracy, surpassing the performance of experienced radiologists, highlighting its potential as a valuable diagnostic tool.

Uncovering novel therapeutic targets in glucose, nucleotides and lipids metabolism during cancer and neurological diseases

BACKGROUND

Cell metabolism functions without a stop in normal and pathological cells. Different metabolic changes occur in the disease. Cell metabolism influences biochemical and metabolic processes, signaling pathways, and gene regulation. Knowledge regarding disease metabolism is limited.

OBJECTIVE

The review examines the cell metabolism of glucose, nucleotides, and lipids during homeostatic and pathological conditions of neurotoxicity, neuroimmunological disease, Parkinson's disease, thymoma in myasthenia gravis, and colorectal cancer.

METHODS

Data collection includes electronic databases, the National Center for Biotechnology Information, and Google Scholar, with several inclusion criteria: cell metabolism, glucose metabolism, nucleotide metabolism, and lipid metabolism in health and disease patients suffering from neurotoxicity, neuroinflammation, Parkinson's disease, thymoma in myasthenia gravis. The initial number of collected and analyzed papers is 250. The final analysis included 150 studies out of 94 selected papers. After the selection process, 62.67% remains useful.

RESULTS AND CONCLUSION

A literature search shows that signaling molecules are involved in metabolic changes in cells. Differences between cancer and neuroimmunological diseases are present in the result section. Our finding enables insight into novel therapeutic targets and the development of scientific approaches for cancer and neurological disease onset, outcome, progression, and treatment, highlighting the importance of metabolic dysregulation. Current understanding, emerging research technologies and potential therapeutic interventions in metabolic programming is disucussed and highlighted.

Personalized estimates of morphometric similarity in multiple sclerosis and neuromyelitis optica spectrum disorders

Brain morphometric alterations involve multiple brain regions on progression of the disease in multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) and exhibit age-related degenerative changes during the pathological aging. Recent advance in brain morphometry as measured using MRI have leveraged Person-Based Similarity Index (PBSI) approach to assess the extent of within-diagnosis similarity or heterogeneity of brain neuroanatomical profiles between individuals of healthy populations and validate in neuropsychiatric disorders. Brain morphometric changes throughout the lifespan would be invaluable for understanding regional variability of age-related structural degeneration and the substrate of inflammatory demyelinating disease. Here, we aimed to quantify the neuroanatomical profiles with PBSI measures of cortical thickness (CT) and subcortical volumes (SV) in 263 MS, 207 NMOSD, and 338 healthy controls (HC) from six separate central datasets (aged 11-80). We explored the between-group comparisons of PBSI measures, as well as the advancing age and sex effects on PBSI measures. Compared to NMOSD, MS showed a lower extent of within-diagnosis similarity. Significant differences in regional contributions to PBSI score were observed in 29 brain regions between MS and NMOSD (P < 0.05/164, Bonferroni corrected), of which bilateral cerebellum in MS and bilateral parahippocampal gyrus in NMOSD represented the highest divergence between the two patient groups, with a high similarity effect within each group. The PBSI scores were generally lower with advancing age, but their associations showed different patterns depending on the age range. For MS, CT profiles were significantly negatively correlated with age until the early 30 s (ρ = -0.265, P = 0.030), while for NMOSD, SV profiles were significantly negatively correlated with age with 51 year-old and older (ρ = -0.365, P = 0.008). The current study suggests that PBSI approach could be used to quantify the variation in brain morphometric changes in CNS inflammatory demyelinating disease, and exhibited a greater neuroanatomical heterogeneity pattern in MS compared with NMOSD. Our results reveal that, as an MR marker, PBSI may be sensitive to distribute the disease-associated grey matter diversity and complexity. Disease-driven production of regionally selective and age stage-dependency changes in the neuroanatomical profile of MS and NMOSD should be considered to facilitate the prediction of clinical outcomes and assessment of treatment responses.

Study on the Anti-demyelination Mechanism of Bu-Shen-Yi-Sui Capsule in the Central Nervous System Based on Network Pharmacology and Experimental Verification

Methods

The potential active ingredients and corresponding potential targets of BSYS Capsule were obtained from the TCMSP, BATMAN-TCM, Swiss Target Prediction platform, and literature research. Disease targets of CNSD were explored through the GeneCards and the DisGeNET databases. The matching targets of BSYS in CNSD were identified from a Venn diagram. The protein-protein interaction (PPI) network was constructed using bioinformatics methods. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to predict the mechanisms of BSYS. Furthermore, the neuroprotective effects of BSYS were evaluated using a cell model of hydrogen peroxide- (H₂O₂-) induced cell death in OLN-93 cells.

Results

A total of 59 potential bioactive components of BSYS Capsule and 227 intersection targets were obtained. Topological analysis showed that AKT had the highest connectivity degrees in the PPI network. Enrichment analysis revealed that the targets of BSYS in the treatment of CNSD were the PI3K-Akt and MAPK signaling pathway, among other pathways. GO analysis results showed that the targets were associated with various biological processes, including apoptosis, reactive oxygen species metabolic process, and response to oxidative stress, among others. The experimental results demonstrated that BSYS drug-containing serum alleviated the H₂O₂-induced increase in LDH, MDA, and ROS levels and reversed the decrease in SOD and mitochondrial membrane potential induced by H₂O₂. BSYS treatment also decreased the number of TUNEL (+) cells, downregulated Bcl-2 expression, and upregulated Bax and c-caspase-3 expression by promoting Akt phosphorylation.

Conclusion

BSYS Capsule alleviated H₂O₂-induced OLN-93 cell injury by increasing Akt phosphorylation to suppress oxidative stress and cell apoptosis. Therefore, BSYS can be potentially used for CNSD treatment. However, the results of this study are only derived from in vitro experiments, lacking the validation of in vivo animal models, which is a limitation of our study. We will further verify the underlying mechanisms of BSYS in animal experiments in the future.

Modeling compartmentalized chronic immune-mediated demyelinating CNS disease in the Biozzi ABH mouse

We explored whether experimental autoimmune encephalomyelitis (EAE) in Biozzi mice recapitulates temporal dynamics of tissue injury, immune-pathogenesis and CNS compartmentalization occurring in progressive multiple sclerosis (MS). Chronic EAE exhibited relapsing and progressing disease, partial closure of BBB, reduced tissue inflammatory activity, and development of meningeal ectopic lymphoid tissue, directly opposing (potentially driving) spinal subpial demyelinated plaques. A T cell predominant disease during relapses transformed into a B cell predominant disease in late chronic EAE, with high serum anti-MOG reactivity. Thus, late chronic Biozzi EAE recapitulates essential features of progressive MS, and is suitable for developing disease modifying and regenerative therapies.

The CSF Levels of Neutrophil-Related Chemokines in Patients with Neuromyelitis Optica

Pathologic findings showed that neutrophils played an important role in the pathogenesis of NMO. This study aims to investigate the CSF levels of neutrophil‐related chemokines in NMO. CXCL1, CXCL5, and CXCL7 were measured in 95 patients with NMO, 15 patients with MS, 18 patients with GFAP astrocytopathy, and 16 controls. The CSF level of CXCL1, CXCL5, and CXCL7 was significantly elevated in the NMO group but not correlated with the patient clinical severity. Besides, the CSF CXCL1, CXCL5, and CXCL7 could act as biomarkers to distinguish NMO from MS with good reliability, especially the CXCL7.

When an octopus has MS: Application of neurophysiology and immunology of octopuses for multiple sclerosis

Multiple sclerosis (MS) is an immune-mediated disease which can cause different symptoms due to the involvement of different regions of the central nervous system (CNS). Although this disease is characterized by the demyelination process, the most important feature of the disease is its degenerative nature. This nature is clinically manifested as progressive symptoms, especially in patients' walking, which can even lead to complete debilitation. Therefore, finding a treatment to prevent the degenerative processes is one of the most important goals in MS studies. To better understand the process and the effect of drugs, scientists use animal models which mostly consisting of mouse, rat, and monkey. In evolutionary terms, octopuses belong to the invertebrates which have many substantial differences with vertebrates. One of these differences is related to the nervous system of these organisms, which is divided into central and peripheral parts. The difference lies in the fact that the main volume of this system expands in the limbs of these organisms instead of their brain. This offers a kind of freedom of action and processing strength in the octopus limbs. Also, the brain of these organisms follows a non-somatotopic model. Although the complex actions of this organism are stimulated by the brain, in contrast to the human brain, this activity is not related to a specific region of the brain; rather the entire brain area of the octopus is activated during a process. Indeed, the brain mapping or the topological perception of a particular action, such as moving the limbs, reflects itself in how that activity is distributed in the octopus brain neurons. Accordingly, various actions are known with varying degrees of activity of neurons in the brain of octopus. Another important feature of octopuses is their ability to regenerate defective tissues including the central and peripheral nervous system. These characteristics raise the question of what features can an octopus show when it is used as an organism to create experimental autoimmune encephalomyelitis (EAE). Can the immune system damage of the octopus brain cause a regeneration process? Will the autonomy of the organs reduce the severity of the symptoms? This article seeks to provide evidence to prove that use of octopuses as laboratory samples for generation of EAE may open up new approaches for researchers to better approach MS.

The features of cerebral permeability and perfusion detected by dynamic contrast-enhanced magnetic resonance imaging with Patlak model in relapsing-remitting multiple sclerosis

Objective

To investigate the features of cerebral permeability and perfusion detected by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with Patlak model in relapsing–remitting multiple sclerosis (RRMS) and their correlations with Expanded Disability Status Scale (EDSS) scores and disease duration.

Patients and methods

Twenty-seven RRMS patients underwent conventional MRI and DCE-MRI with 3.0 T magnetic resonance scanner were enrolled in the study. A Patlak model was used to quantitatively measure MRI biomarkers, including volume transfer constant (K^trans), fractional plasma volume (V_p), cerebral blood flow (CBF), and cerebral blood volume (CBV). The correlations of MRI biomarkers with EDSS scores and disease duration were analyzed.

Results

The MRI biomarkers K^trans, V_p, CBF, and CBV of contrast-enhancing (CE) lesions were significantly higher (P<0.05) than those of non-enhancing (NE) lesions and normal-appearing white matter (NAWM) regions. The skewness and kurtosis of K^trans values in CE lesions were significantly higher (P<0.05) than that of NE lesions. No significant correlation was found among the biomarkers with EDSS scores and disease duration (P>0.05).

Conclusion

Our study demonstrated the abnormalities of permeability and perfusion characteristics in multiple sclerosis (MS) lesions and NAWM regions by DCE-MRI with Patlak model. The K^trans, V_p, CBF, and CBV of CE lesions were significantly higher than that of NE lesions, but these MRI biomarkers did not associate with the severity and duration of the disease. The skewness and kurtosis of K^trans value in CE lesions were significantly higher than that in NE lesions, indicating that these parameters of K^trans histogram can be used to distinguish the pathology of MS lesions.

Quantitative radiomic biomarkers for discrimination between neuromyelitis optica spectrum disorder and multiple sclerosis

BACKGROUND

Precise diagnosis and early appropriate treatment are of importance to reduce neuromyelitis optica spectrum disorder (NMOSD) and multiple sclerosis (MS) morbidity. Distinguishing NMOSD from MS based on clinical manifestations and neuroimaging remains challenging.

PURPOSE

To investigate radiomic signatures as potential imaging biomarkers for distinguishing NMOSD from MS, and to develop and validate a diagnostic radiomic-signature-based nomogram for individualized disease discrimination.

STUDY TYPE

Retrospective, cross-sectional study.

SUBJECTS

Seventy-seven NMOSD patients and 73 MS patients.

FIELD STRENGTH/SEQUENCE

3T/T₂ -weighted imaging.

ASSESSMENT

Eighty-eight patients and 62 patients were respectively enrolled in the primary and validation cohorts. Quantitative radiomic features were automatically extracted from lesioned regions on T₂ -weighted imaging. A least absolute shrinkage and selection operator analysis was used to reduce the dimensionality of features. Finally, we constructed a radiomic nomogram for disease discrimination.

STATISTICAL TESTS

Features were compared using the Mann-Whitney U-test with a nonnormal distribution. We depicted the nomogram on the basis of the results of the logistic regression using the rms package in R. The Hmisc package was used to investigate the performance of the nomogram via Harrell's C-index.

RESULTS

A total of 273 quantitative radiomic features were extracted from lesions. A multivariable analysis selected 11 radiomic features and five clinical features to be included in the model. The radiomic signature (P < 0.001 for both the primary and validation cohorts) showed good potential for building a classification model for disease discrimination. The area under the receiver operating characteristic curve was 0.9880 for the training cohort and 0.9363 for the validation cohort. The nomogram exhibited good discrimination, a concordance index of 0.9363, and good calibration in the primary cohort. The nomogram showed similar discrimination, concordance (0.9940), and calibration in the validation cohort.

DATA CONCLUSION

The diagnostic radiomic-signature-based nomogram has potential utility for individualized disease discrimination of NMOSD from MS in clinical practice.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1113-1121.

Matrine promotes NT3 expression in CNS cells in experimental autoimmune encephalomyelitis

Neurotrophin 3 (NT3) is a potent neurotrophic factor for promoting remyelination and recovery of neuronal function; upregulation of its expression in the central nervous system (CNS) is thus of major therapeutic importance for neurological deficits. Matrine (MAT), a quinolizidine alkaloid derived from the herb Radix Sophorae Flavescent, has been recently reported to effectively ameliorate clinical signs in experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis (MS), by secreting antiinflammatory cytokines. In the present study, our goal was to investigate whether MAT could affect NT3 expression of glial cells in the CNS, the major cell populations in the CNS foci of MS/EAE. We found that MAT markedly upregulated NT3 expression in the CNS not only by microglia/macrophages and astrocytes, but also by oligodendrocyte precursor cells, indicative of both paracrine and autocrine effects on myelinating cells. While MAT treatment reduced the numbers of iNOS⁺ M1, but increased Arg1⁺ M2 microglia/macrophage phenotypes, NT3 expression was upregulated in both phenotypes. These results indicate that MAT therapy for EAE acts, at least in part, by stimulating local production of NT3 by glial cells in the CNS, which protects neural cells from CNS inflammation-induced tissue damage.

Metabolic changes in normal appearing white matter in multiple sclerosis patients using multivoxel magnetic resonance spectroscopy imaging

Demyelination and axonal degeneration caused by multiple sclerosis (MS) exist in the white matter and not only in the lesion area. Magnetic resonance spectroscopy (MRS) could provide a unique insight into metabolic changes in the normal appearing white matter (NAWM). To evaluate the subtle axonal degeneration and delineate the spatial distribution of metabolite abnormalities in the NAWM in patients with MS. A total of 17 clinically definite relapsing-remitting MS (RRMS) patients and 21 healthy controls were enrolled in this study. 2D 1H magnetic resonance spectroscopic imaging (MRSI) performed at 3 Tesla was used to measure metabolite concentrations in the frontal-parietal-occipital NAWM. Ratios of N-acetyl-aspartate (NAA) and choline (Cho) to creatine (Cr) and Cho to NAA were calculated in each voxel. MS patients showed decreased NAA/Cr and increased Cho/NAA ratios in the NAWM compared to healthy controls. In the parietal NAWM, the extent of NAA/Cr decrease was significantly higher than that in the frontal and parietal-occipital NAWM. Decreased NAA in the NAWM would provide useful metabolic information for evaluation of disease progression in MS. The high extent of NAA decrease in the parietal NAWM helps improve the accuracy of the prediction.

Pathology of Ischemic Optic Neuropathy

Ischemic optic neuropathy (ION) describes a state of hypoxic injury of the optic nerve. Clinically, ION is divided into anterior and posterior forms defined by the presence or absence of optic disc swelling, respectively. It is further classified as arteritic when secondary to vasculitis, and nonarteritic when not. The site of vascular occlusion for anterior ION from giant cell arteritis is the short posterior ciliary arteries, but mechanical vascular obstruction does not play a role in most nonarteritic cases. Histologically, ION is characterized by axon and glial necrosis, edema, and a sparse mononuclear response. Like other ischemic injuries, the morphologic alternations in the nerve are time dependent. A variant of ION called cavernous degeneration (of Schnabel) features large cystic spaces filled with mucin. Several conditions can histologically mimic cavernous degeneration of the optic nerve. The scarcity of cases of ION examined histologically has contributed to an incomplete understanding of its pathogenesis.

Rituximab monitoring and redosing in pediatric neuromyelitis optica spectrum disorder

Objective:

To study rituximab in pediatric neuromyelitis optica (NMO)/NMO spectrum disorders (NMOSD) and the relationship between rituximab, B cell repopulation, and relapses in order to improve rituximab monitoring and redosing.

Methods:

Multicenter retrospective study of 16 children with NMO/NMOSD receiving ≥2 rituximab courses. According to CD19 counts, events during rituximab were categorized as “repopulation,” “depletion,” or “depletion failure” relapses (repopulation threshold CD19 ≥10 × 10⁶ cells/L).

Results:

The 16 patients (14 girls; mean age 9.6 years, range 1.8–15.3) had a mean of 6.1 events (range 1–11) during a mean follow-up of 6.1 years (range 1.6–13.6) and received a total of 76 rituximab courses (mean 4.7, range 2–9) in 42.6-year cohort treatment. Before rituximab, 62.5% had received azathioprine, mycophenolate mofetil, or cyclophosphamide. Mean time from rituximab to last documented B cell depletion and first repopulation was 4.5 and 6.8 months, respectively, with large interpatient variability. Earliest repopulations occurred with the lowest doses. Significant reduction between pre- and post-rituximab annualized relapse rate (ARR) was observed (p = 0.003). During rituximab, 6 patients were relapse-free, although 21 relapses occurred in 10 patients, including 13 “repopulation,” 3 “depletion,” and 4 “depletion failure” relapses. Of the 13 “repopulation” relapses, 4 had CD19 10–50 × 10⁶ cells/L, 10 had inadequate monitoring (≤1 CD19 in the 4 months before relapses), and 5 had delayed redosing after repopulation detection.

Conclusion:

Rituximab is effective in relapse prevention, but B cell repopulation creates a risk of relapse. Redosing before B cell repopulation could reduce the relapse risk further.

Classification of evidence:

This study provides Class IV evidence that rituximab significantly reduces ARR in pediatric NMO/NMOSD. This study also demonstrates a relationship between B cell repopulation and relapses.

Classification algorithms with multi-modal data fusion could accurately distinguish neuromyelitis optica from multiple sclerosis

Neuromyelitis optica (NMO) exhibits substantial similarities to multiple sclerosis (MS) in clinical manifestations and imaging results and has long been considered a variant of MS. With the advent of a specific biomarker in NMO, known as anti-aquaporin 4, this assumption has changed; however, the differential diagnosis remains challenging and it is still not clear whether a combination of neuroimaging and clinical data could be used to aid clinical decision-making. Computer-aided diagnosis is a rapidly evolving process that holds great promise to facilitate objective differential diagnoses of disorders that show similar presentations. In this study, we aimed to use a powerful method for multi-modal data fusion, known as a multi-kernel learning and performed automatic diagnosis of subjects. We included 30 patients with NMO, 25 patients with MS and 35 healthy volunteers and performed multi-modal imaging with T1-weighted high resolution scans, diffusion tensor imaging (DTI) and resting-state functional MRI (fMRI). In addition, subjects underwent clinical examinations and cognitive assessments. We included 18 a priori predictors from neuroimaging, clinical and cognitive measures in the initial model. We used 10-fold cross-validation to learn the importance of each modality, train and finally test the model performance. The mean accuracy in differentiating between MS and NMO was 88%, where visible white matter lesion load, normal appearing white matter (DTI) and functional connectivity had the most important contributions to the final classification. In a multi-class classification problem we distinguished between all of 3 groups (MS, NMO and healthy controls) with an average accuracy of 84%. In this classification, visible white matter lesion load, functional connectivity, and cognitive scores were the 3 most important modalities. Our work provides preliminary evidence that computational tools can be used to help make an objective differential diagnosis of NMO and MS.