Distinct Immunological Features of Inflammatory Demyelinating Diseases of the Central Nervous System

Soluble biomarkers for Neuromyelitis Optica Spectrum Disorders: a mini review

The Neuromyelitis Optica Spectrum Disorders (NMOSD) constitute a spectrum of rare autoimmune diseases of the central nervous system characterized by episodes of transverse myelitis, optic neuritis, and other demyelinating attacks. Previously thought to be a subtype of multiple sclerosis, NMOSD is now known to be a distinct disease with unique pathophysiology, clinical course, and treatment options. Although there have been significant recent advances in the diagnosis and treatment of NMOSD, the field still lacks clinically validated biomarkers that can be used to stratify disease severity, monitor disease activity, and inform treatment decisions. Here we review many emerging NMOSD biomarkers including markers of cellular damage, neutrophil-to-lymphocyte ratio, complement, and cytokines, with a focus on how each biomarker can potentially be used for initial diagnosis, relapse surveillance, disability prediction, and treatment monitoring.

Delimiting MOGAD as a disease entity using translational imaging

The first formal consensus diagnostic criteria for myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) were recently proposed. Yet, the distinction of MOGAD-defining characteristics from characteristics of its important differential diagnoses such as multiple sclerosis (MS) and aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorder (NMOSD) is still obstructed. In preclinical research, MOG antibody-based animal models were used for decades to derive knowledge about MS. In clinical research, people with MOGAD have been combined into cohorts with other diagnoses. Thus, it remains unclear to which extent the generated knowledge is specifically applicable to MOGAD. Translational research can contribute to identifying MOGAD characteristic features by establishing imaging methods and outcome parameters on proven pathophysiological grounds. This article reviews suitable animal models for translational MOGAD research and the current state and prospect of translational imaging in MOGAD.

Novel index, neutrophil percentage (%) is a useful marker for disease activity in MOG antibody-associated disease

BACKGROUND

Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is a CNS autoimmune disease affecting the brain, spinal cord, and optic nerve. The neutrophil-to-lymphocyte ratio (NLR) is related to autoimmune disease activity. However, the clinical implication of index ratios such as the NLR is unclear in patients with MOGAD.

OBJECTIVES

We investigated the relationship between index ratios such as the NLR and disease activity and disability to discover the index that best correlates with an attack in MOGAD.

METHODS

Using a CNS demyelinating disease cohort, we reviewed 39 patients with MOGAD (age 37.4 ± 12.0 years; F:M = 20:19) who had 390 blood samples available for cell count analysis. We calculated the NLR, eosinophil-to-lymphocyte-ratio (ELR), platelet-to-lymphocyte-ratio (PLR), monocyte-to-lymphocyte ratio (MLR), basophil-to-lymphocyte ratio (BLR), and neutrophil percentage (N%) [neutrophil count (/mm³) / WBC (/mm³) x 100 (%)]. We investigated the associations between each index ratio and disease activity and disability using the receiver operating characteristic (ROC) curve, machine learning program (kNN algorithm), and generalized estimating equations (GEE) analysis.

RESULTS

In patients with MOGAD, the NLR, PLR, and N% were higher and ELR was lower during an attack than in remission (all p<0.001). The areas under the ROC curve for the NLR, ELR, PLR, and N% were 0.68, 0.69, 0.61, and 0.68, respectively, with the highest sensitivity of 76.0% in the ELR and the highest specificity of 76.3% in the N%. The classification accuracy scores of the kNN machine learning algorithm were 71% for the NLR, 62% for the ELR, 63% for the PLR, and 72% for the N%. In the GEE analysis of attack samples, both the NLR and treatment-naive had positive associations with the Expanded Disability Status Scale (EDSS) score (β=0.137, p = 0.008 and β=1.142, p = 0.003, respectively), and the PLR was negatively associated with the EDSS score (β=-0.004, p = 0.022).

DISCUSSION

Our study suggests that the novel index, neutrophil% is the simplest and the most useful marker to differentiate between attack and remission and shows comparable reliability with NLR in MOGAD. Moreover, the NLR and PLR could be used as supportive biomarkers for disease disability during an attack in patients with MOGAD.

Neutrophil to lymphocyte ratio may be a useful marker in distinguishing MOGAD and MS and platelet to lymphocyte ratio associated with MOGAD activity

BACKGROUND AND OBJECTIVE

Clinical overlap is observed between multiple sclerosis (MS) and myelin oligodendrocyte glycoprotein immunoglobulin-G (MOG-IgG) associated disease (MOGAD) and the difficulty in distinguishing between the two diseases. Here, we measured and compared the readily available neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and monocyte to lymphocyte ratio (MLR) to determine whether these three biomarkers can help to distinguish MOGAD and MS at disease onset. The impact of these three biomarkers on MOGAD and MS relapse also needs to be explored.

METHODS

In this retrospective analysis, we obtained clinical and paraclinical data from the first attacks of MOGAD (N = 31) and MS (N = 50). Electronic medical records were used to collect demographic data (gender, age at onset), clinical symptoms, EDSS at onset, and medical treatments. The primary outcome was relapse within one year of onset. Four hematological parameters were recorded, including neutrophil count, platelet count, lymphocyte count, and monocyte count. NLR, PLR, and MLR were calculated and compared between MOGAD, MS, and HC. Receiver operator curve (ROC) analysis was performed to assess the ability of NLR, PLR, and MLR to distinguish between MOGAD and MS, MOGAD and HC, respectively. A logistic regression analysis was performed to determine the impact of NLR/PLR/MLR on MOGAD/MS relapse within one year of onset.

RESULTS

Compared to HC, NLR is significantly higher in MOGAD and MS (p<0.001, p = 0.04, respectively). The PLR and MLR are elevated in MOGAD compared to HC (p<0.001, p<0.001, respectively), and MLR in MS are also statistically higher than in HC (p = 0.023). It is worth noting that NLR and PLR were much higher in MOGAD compared to MS (p<0.001, p = 0.001, respectively), but a significant difference regarding MLR has not been found between MOGAD and MS. Based on ROC curve analyses, we found that using NLR, PLR, and MLR to discriminate between MOGAD and MS yielded a ROC-plot area under the curve (AUC) value of 0.794, 0.727, and 0.681, respectively. Meanwhile, the AUC of NLR, PLR, and MLR to discriminate between MOGAD and HC were 0.926, 0.772, and 0.786. Furthermore, the logistics analysis revealed a significant positive association between PLR and MOGAD relapse.

CONCLUSION

NLR helps differentiate MOGAD and MS in disease onset, and higher PLR was related to MOGAD relapse.

Predictive role of blood-based indicators in neuromyelitis optica spectrum disorders

Introduction

This study aimed to assess the predictive role of blood markers in neuromyelitis optica spectrum disorders (NMOSD).

Methods

Data from patients with NMOSD, multiple sclerosis (MS), and healthy individuals were retrospectively collected in a 1:1:1 ratio. The expanded disability status scale (EDSS) score was used to assess the severity of the NMOSD upon admission. Receiver operating characteristic (ROC) curve analysis was used to distinguish NMOSD patients from healthy individuals, and active NMOSD from remitting NMOSD patients. Binary logistic regression analysis was used to evaluate risk factors that could be used to predict disease recurrence. Finally, Wilcoxon signed-rank test or matched-sample t-test was used to analyze the differences between the indicators in the remission and active phases in the same NMOSD patient.

Results

Among the 54 NMOSD patients, neutrophil count, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) (platelet × NLR) were significantly higher than those of MS patients and healthy individuals and positively correlated with the EDSS score of NMOSD patients at admission. PLR can be used to simultaneously distinguish between NMOSD patients in the active and remission phase. Eleven (20.4%) of the 54 patients had recurrence within 12 months. We found that monocyte-to-lymphocyte ratio (MLR) (AUC = 0.76, cut-off value = 0.34) could effectively predict NMOSD recurrence. Binary logistic regression analysis showed that a higher MLR at first admission was the only risk factor for recurrence (p = 0.027; OR = 1.173; 95% CI = 1.018-1.351). In patients in the relapsing phase, no significant changes in monocyte and lymphocyte count was observed from the first admission, whereas patients in remission had significantly higher levels than when they were first admitted.

Conclusion

High PLR is a characteristic marker of active NMOSD, while high MLR is a risk factor for disease recurrence. These inexpensive indicators should be widely used in the diagnosis, prognosis, and judgment of treatment efficacy in NMOSD.

Demyelinating diseases of the central nervous system registry for patients with traditional Chinese medicine: Rationale and design of a prospective, multicenter, observational study

Background: Traditional Chinese medicine (TCM), a main form of complementary and alternative medicine provides a potential possibility for demyelinating disease of the central nervous system (DDC) management and has been applied in considerable amounts of patients with this disorder. Nevertheless, powerful real-world evidences regarding the epidemiological and clinical characteristics, safety, and outcomes of TCM in DDC are lacking. The primary objective of the Demyelinating Diseases of the Central Nervous System Registry for Patients with Traditional Chinese Medicine (DATE-TCM) is to create an organized multicenter data collection structure to define integrative characteristics of DDC patients treated with TCM in an endeavor to fill these knowledge gaps to better inform clinical care and health policy.

Method: This study provides a prospective and voluntary registry by using a web-based system. Baseline data will be recorded and subsequently regular follow-up visits will be implemented every 3–6 months for a total of 5 years. The primary outcome is Annualized Aggregate Relapse Rate at 5-year follow-up.

Results: DATE-TCM is currently designed to capture the multidimensional (epidemiologic, demographic, clinical, etc.) features of DDC patients receiving TCM treatment, the type and long-term safety and efficacy of TCM intervenes in the DDC populations, as well as the interaction of TCM treatments and disease modifying therapies in the management of DDC, aiming to include 2000 eligible adult DDC patients with TCM intervenes from 35 participating centers, covering 77.4% of provincial administrative regions of mainland China.

Conclusion: DATE-TCM is the first, largest, most geographically extensive, and standard registry-based observational study that systematically document the real-world data regarding the TCM application in the DDC populations, which will be extraordinarily important for clarifying the comprehensive characteristics and outcomes of TCM in DDC, further shed light on standardizing and optimizing the TCM measures for DDC management and establishing evidence-based clinical practice guidelines for TCM application in DDC.

Altered non-coding RNA profiles and potential disease marker identification in peripheral blood mononuclear cells of patients with NMOSD

Neuromyelitis optica spectrum disorder (NMOSD) is an inflammatory demyelination disorder, and dysregulation of RNAs contributes to its pathogenesis. We aimed to reveal the expression profiles of RNAs, including messenger RNA (mRNA), circular RNA (circRNA) and long non-coding RNA (lncRNA), in the peripheral blood mononuclear cells (PBMCs) of patients with NMOSD. Seven NMOSD patients and seven healthy controls (HCs) were enrolled in the competitive endogenous RNA (ceRNA) microarray analysis. Bioinformatics analysis was then performed on the microarray data. Selected RNAs were validated by RT-qPCR. Differentially expressed (DE) RNA profiles of patients and HCs were related to NK cell mediated cytotoxicity, the IL-17 signaling pathway, and the B cell receptor signaling pathway. Moreover, DE non-coding RNAs (DE ncRNAs) including DE circRNAs and DE lncRNAs, may participate in the transforming growth factor beta (TGF-β) signaling pathway, leukocyte migration and neutrophil chemotaxis. Immune cell infiltration analysis showed that the abundance of M1 macrophages and plasma cells significantly increased, while that of M2 macrophages significantly decreased in the NMOSD group. Finally, through RT-qPCR validation, lnc-HELZ-7:1 (95% confidential interval of area under curve [95%CI of AUC] = 0.6633-1.0000), ring finger protein-LIM domain interacting (RLIM; 95%CI of AUC = 0.6980-1.0000), and hsa_circ_0026993 (95%CI of AUC = 0.7550-1.0000) could discriminate NMOSD from HCs by receiver operating characteristic curve analysis. To our knowledge, this is the first study to preliminarily investigate the RNA profiles, especially circRNA profiles in PBMCs of NMOSD patients from North China. We identified lnc-HELZ-7:1, RLIM, and hsa_circ_0026993 as the potential disease markers for NMOSD.

Abnormal expression of long non-coding RNA rhabdomyosarcoma 2-associated transcript (RMST) participates in the pathological mechanism of atherosclerosis by regulating miR-224-3p

Study shows that long non-coding RNA (lncRNA) plays a regulatory role in cardiovascular diseases, and the mechanism of rhabdomyosarcoma 2-associated transcript (RMST) in atherosclerosis (AS) is still unclear. This study aimed to evaluate the expression of RMST and its possible role in the occurrence of AS. RMST and miR-224-3p level in serum and human umbilical vein endothelial cells (HUVECs) were determined by real-time quantitative PCR (RT-qPCR). In vitro atherosclerotic cell model was achieved by treating HUVECs with ox-LDL. Receiver operating characteristic (ROC) curve assessed the diagnostic value of RMST in AS, and Pearson correlation coefficient estimated the correlation of RMST with carotid intima-media thickness (CIMT) and carotid-femoral pulse wave velocity (cfPWV). Cell counting kit-8 (CCK-8) assay and Enzyme-linked immunosorbent assay (ELISA) were performed to evaluate the effect of RMST on cell viability and inflammatory response. The luciferase analysis was used to validate the relationship between RMST and miR-224-3p. The results showed that in serum and HUVECs, RMST levels were increased, while miR-224-3p level was decreased. ROC curve suggested that RMST had clinical diagnostic value for AS. Besides, CIMT and cfPWV were positively correlated with RMST levels, respectively. In HUVECs, RMST-knockdown notably improved the cell viability and inhibited the production of inflammatory factors. Moreover, miR-224-3p was the target of RMST. In conclusion, RMST has the potential to be a diagnostic marker for AS. RMST-knockdown contributes to the enhancement of cell viability and the inhibition of inflammatory response, which may provide new insights into the conquest of AS.