Identification and Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Relapsing-Remitting Multiple Sclerosis

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.

Identification of novel hub genes for Alzheimer's disease associated with the hippocampus using WGCNA and differential gene analysis

Background

Alzheimer's disease (AD) is a common, refractory, progressive neurodegenerative disorder in which cognitive and memory deficits are highly correlated with abnormalities in hippocampal brain regions. There is still a lack of hippocampus-related markers for AD diagnosis and prevention.

Methods

Differently expressed genes were identified in the gene expression profile GSE293789 in the hippocampal brain region. Enrichment analyses GO, KEGG, and GSEA were used to identify biological pathways involved in the DEGs and AD-related group. WGCNA was used to identify the gene modules that are highly associated with AD in the samples. The intersecting genes of the genes in DEGs and modules were extracted and the top ten ranked hub genes were identified. Finally GES48350 was used as a validation cohort to predict the diagnostic efficacy of hub genes.

Results

From GSE293789, 225 DEGs were identified, which were mainly associated with calcium response, glutamatergic synapses, and calcium-dependent phospholipid-binding response. WGCNA analysis yielded dark green and bright yellow modular genes as the most relevant to AD. From these two modules, 176 genes were extracted, which were taken to be intersected with DEGs, yielding 51 intersecting genes. Then 10 hub genes were identified in them: HSPA1B, HSPB1, HSPA1A, DNAJB1, HSPB8, ANXA2, ANXA1, SOX9, YAP1, and AHNAK. Validation of these genes was found to have excellent diagnostic performance.

Conclusion

Ten AD-related hub genes in the hippocampus were identified, contributing to further understanding of AD development in the hippocampus and development of targets for therapeutic prevention.

Integrated gene co-expression network analysis and experimental validation revealed potential targets of human urine extract CDA-II in treating chronic myeloid leukemia

BACKGROUND

Cell differentiation agent II (CDA-II) exhibits potent anti-proliferative and apoptosis-inducing properties against a variety of cancer cells. However, its mechanism of action in chronic myeloid leukemia (CML) remains unclear.

METHODS

Cell counting Kit 8 (CCK-8) and flow cytometry were used to investigate the effects of CDA-II on the biological characteristics of K562 cells. Gene (mRNA and lncRNA) expression profiles were analyzed by bioinformatics to screen differentially expressed genes and to perform enrichment analysis. The Pearson correlation coefficients of lncRNAs and mRNAs were calculated using gene expression values, and a lncRNA/mRNA co-expression network was constructed. The MCODE and cytoHubba plugins were used to analyze the co-expression network.

RESULTS

The Results, derived from CCK-8 and flow cytometry, indicated that CDA-II exerts dual effects on K562 cells: it inhibits their proliferation and induces apoptosis. From bioinformatics analysis, we identified 316 mRNAs and 32 lncRNAs. These mRNAs were predominantly related to the meiotic cell cycle, DNA methylation, transporter complex and peptidase regulator activity, complement and coagulation cascades, protein digestion and absorption, and cell adhesion molecule signaling pathways. The co-expression network comprised of 163 lncRNA/mRNA interaction pairs. Notably, our analysis results implicated clustered histone gene families and five lncRNAs in the biological effects of CDA-II on K562 cells.

CONCLUSION

This study highlights the hub gene and lncRNA/mRNA co-expression network as crucial elements in the context of CDA-II treatment of CML. This insight not only enriches our understanding of CDA-II's mechanism of action but also might provide valuable clues for subsequent experimental studies of CDA-II, and potentially contribute to the discovery of new therapeutic targets for CML.

Magnetic resonance imaging and deoxyribonucleic acid methylation-based radiogenomic models for survival risk stratification of glioblastoma

Glioblastoma multiforme (GBM) is one of the deadliest tumours. This study aimed to construct radiogenomic prognostic models of glioblastoma overall survival (OS) based on magnetic resonance imaging (MRI) Gd-T1WI images and deoxyribonucleic acid (DNA) methylation-seq and to understand the related biological pathways. The ResNet3D-18 model was used to extract radiomic features, and Lasso-Cox regression analysis was utilized to establish the prognostic models. A nomogram was constructed by combining the radiogenomic features and clinicopathological variables. The DeLong test was performed to compare the area under the curve (AUC) of the models. We screened differentially expressed genes (DEGs) with original ribonucleic acid (RNA)-seq in risk stratification and used Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) annotations for functional enrichment analysis. For the 1-year OS models, the AUCs of the radiogenomic set, methylation set and deep learning set in the training cohort were 0.864, 0.804 and 0.787, and those in the validation cohort were 0.835, 0.768 and 0.651, respectively. The AUCs of the 0.5-, 1- and 2-year nomograms in the training cohort were 0.943, 0.861 and 0.871, and those in the validation cohort were 0.864, 0.885 and 0.805, respectively. A total of 245 DEGs were screened; functional enrichment analysis showed that these DEGs were associated with cell immunity. The survival risk-stratifying radiogenomic models for glioblastoma OS had high predictability and were associated with biological pathways related to cell immunity.

Gene expression in multiple sclerosis during pregnancy based on integrated bioinformatics analysis

BACKGROUND

The modulation of the activity disease in patients with Multiple Sclerosis (MS) that occurs during pregnancy is a helpful model which could provide insight into central disease mechanisms and facilitate treatment. Therefore, the aim of the study was to identify differentially expressed genes in-silico to perform biological function pathway enrichment analysis and protein-protein interaction from pregnant women with MS.

METHODS

Transcriptome data were obtained from the Gene Expression Omnibus (GEO) database. We selected the microarray dataset GSE17449. The gene expression dataset contains the data of mononuclear cells from four different groups sought, including seven healthy women (H), four healthy pregnant women (HP), eight women with multiple sclerosis (WMS), and nine women nine months pregnant with multiple sclerosis (PMS). The GSEA software was employed for enrichment analysis, and the REACTOME database was used for biological pathways. The protein-protein interaction (PPI) network was plotted with STRING. The databases used to identify the connection of DEGs with different signaling pathways were KEGG and WIKIPATHWAYS.

RESULTS

We identified 42 differentially expressed genes in pregnant women with MS. The significant pathways included IL-10 signaling pathway, ErbB2 activates, the hemoglobin complex (HBD, HBB, HBA1, AHSP, and HBA2), IL-17 signaling pathway (LCN2 and MMP9), antigen processing and presentation, and Th17 cell differentiation (HLA-DQA1), Rap1 signaling pathway (ID1), NOD-Like receptor signaling pathway (CAMP and DEFA4), PD-L1 Signaling, Interferon gamma signaling (MMP9 and ARG1), Neutrophil degranulation (CAMP, DEFA4, ELANE, CEACAM8, S100P, CHI3L1, AZU1, OLFM4, CRISP3, LTF, ARG1, PGLYRP1, and TCN1). In the WIKIPATHWAYS set, significance was found Vitamin B12 metabolism (TCN1, HBB, and HBA2), and IL-18 signaling pathway (S100P).

CONCLUSION

This study can be used to understand several essential target genes and pathways identified in the present study, which may serve as feasible targets for MS therapies.

Response to Fingolimod in Multiple Sclerosis Patients Is Associated with a Differential Transcriptomic Regulation

Fingolimod is an immunomodulatory sphingosine-1-phosphate (S1P) analogue approved for the treatment of relapsing-remitting multiple sclerosis (RRMS). The identification of biomarkers of clinical responses to fingolimod is a major necessity in MS to identify optimal responders and avoid the risk of disease progression in non-responders. With this aim, we used RNA sequencing to study the transcriptomic changes induced by fingolimod in peripheral blood mononuclear cells of MS-treated patients and their association with clinical response. Samples were obtained from 10 RRMS patients (five responders and five non-responders) at baseline and at 12 months of fingolimod therapy. Fingolimod exerted a vast impact at the transcriptional level, identifying 7155 differentially expressed genes (DEGs) compared to baseline that affected the regulation of numerous signaling pathways. These DEGs were predominantly immune related, including genes associated with S1P metabolism, cytokines, lymphocyte trafficking, master transcription factors of lymphocyte functions and the NF-kB pathway. Responder and non-responder patients exhibited a differential transcriptomic regulation during treatment, with responders presenting a higher number of DEGs (6405) compared to non-responders (2653). The S1P, NF-kB and TCR signaling pathways were differentially modulated in responder and non-responder patients. These transcriptomic differences offer the potential of being exploited as biomarkers of a clinical response to fingolimod.

Identification and Preliminary Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Hashimoto's Thyroiditis by Comprehensive Analysis

Hashimoto's thyroiditis (HT) is an autoimmune disruption manifested by immune cell infiltration in thyroid tissue and the production of antibodies against thyroid-specific antigens, such as the thyroid peroxidase antibody (TPOAb) and thyroglobulin antibody (TGAb). TPOAb and TGAb are commonly used in clinical tests; however, handy indicators of the diagnosis and progression of HT are still scarce. Extracellular proteins are glycosylated and are likely to enter body fluids and become readily available and detectable biomarkers. Our research aimed to discover extracellular biomarkers and potential treatment targets associated with HT through integrated bioinformatics analysis and clinical sample validations. A total of 19 extracellular protein-differentially expressed genes (EP-DEGs) were screened by the GSE138198 dataset from the Gene Expression Omnibus (GEO) database and protein annotation databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the function and pathway of EP-DEGs. STRING, Cytoscape, MCODE, and Cytohubba were used to construct a protein-protein interaction (PPI) network and screen key EP-DEGs. Six key EP-DEGs (CCL5, GZMK, CXCL9, CXCL10, CXCL11, and CXCL13) were further validated in the GSE29315 dataset and the diagnostic curves were evaluated, which all showed high diagnostic accuracy (AUC > 0.95) for HT. Immune profiling revealed the correlation of the six key EP-DEGs and the pivotal immune cells in HT, such as CD8+ T cells, dendritic cells, and Th2 cells. Further, we also confirmed the key EP-DEGs in clinical thyroid samples. Our study may provide bioinformatics and clinical evidence for revealing the pathogenesis of HT and improving the potential diagnosis biomarkers and therapeutic strategies for HT.

BIRC5 Inhibition Is Associated with Pyroptotic Cell Death via Caspase3-GSDME Pathway in Lung Adenocarcinoma Cells

Lung adenocarcinoma (LUAD) is a prevalent type of thoracic cancer with a poor prognosis and high mortality rate. However, the exact pathogenesis of this cancer is still not fully understood. One potential factor that can contribute to the development of lung adenocarcinoma is DNA methylation, which can cause changes in chromosome structure and potentially lead to the formation of tumors. The baculoviral IAP repeat containing the 5 (BIRC5) gene encodes the Survivin protein, which is a multifunctional gene involved in cell proliferation, migration, and invasion of tumor cells. This gene is elevated in various solid tumors, but its specific role and mechanism in lung adenocarcinoma are not well-known. To identify the potential biomarkers associated with lung adenocarcinoma, we screened the methylation-regulated differentially expressed genes (MeDEGs) of LUAD via bioinformatics analysis. Gene ontology (GO) process and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were applied to investigate the biological function and pathway of MeDEGs. A protein-protein interaction (PPI) network was employed to explore the key module and screen hub genes. We screened out eight hub genes whose products are aberrantly expressed, and whose DNA methylation modification level is significantly changed in lung adenocarcinoma. BIRC5 is a bona fide marker which was remarkably up-regulated in tumor tissues. Flow cytometry analysis, lactate dehydrogenase release (LDH) assay and Micro-PET imaging were performed in A549 cells and a mouse xenograft tumor to explore the function of BIRC5 in cell death of lung adenocarcinoma. We found that BIRC5 was up-regulated and related to a high mortality rate in lung adenocarcinoma patients. Mechanically, the knockdown of BIRC5 inhibited the proliferation of A549 cells and induced pyroptosis via caspase3/GSDME signaling. Our findings have unraveled that BIRC5 holds promise as a novel biomarker and therapeutic target for lung adenocarcinoma. Additionally, we have discovered a novel pathway in which BIRC5 inhibition can induce pyroptosis through the caspase3-GSDME pathway in lung adenocarcinoma cells.

Brain cell type specific proteomics approach to discover pathological mechanisms in the childhood CNS disorder mucolipidosis type IV

Mucolipidosis IV (MLIV) is an ultra-rare, recessively inherited lysosomal disorder resulting from inactivating mutations in MCOLN1, the gene encoding the lysosomal cation channel TRPML1. The disease primarily affects the central nervous system (CNS) and manifests in the first year with cognitive and motor developmental delay, followed by a gradual decline in neurological function across the second decade of life, blindness, and premature death in third or fourth decades. Brain pathology manifestations in MLIV are consistent with hypomyelinating leukodystrophy with brain iron accumulation. Presently, there are no approved or investigational therapies for MLIV, and pathogenic mechanisms remain largely unknown. The MLIV mouse model, Mcoln1-/- mice, recapitulates all major manifestations of the human disease. Here, to better understand the pathological mechanisms in the MLIV brain, we performed cell type specific LC-MS/MS proteomics analysis in the MLIV mouse model and reconstituted molecular signatures of the disease in either freshly isolated populations of neurons, astrocytes, oligodendrocytes, and neural stem cells, or whole tissue cortical homogenates from young adult symptomatic Mcoln1-/- mice. Our analysis confirmed on the molecular level major histopathological hallmarks of MLIV universally present in Mcoln1-/- tissue and brain cells, such as hypomyelination, lysosomal dysregulation, and impaired metabolism of lipids and polysaccharides. Importantly, pathway analysis in brain cells revealed mitochondria-related alterations in all Mcoln1-/- brain cells, except oligodendrocytes, that was not possible to resolve in whole tissue. We also report unique proteome signatures and dysregulated pathways for each brain cell population used in this study. These data shed new light on cell-intrinsic mechanisms of MLIV and provide new insights for biomarker discovery and validation to advance translational studies for this disease.

Three-Dimensional Cell Cultures: The Bridge between In Vitro and In Vivo Models

Although historically, the traditional bidimensional in vitro cell system has been widely used in research, providing much fundamental information regarding cellular functions and signaling pathways as well as nuclear activities, the simplicity of this system does not fully reflect the heterogeneity and complexity of the in vivo systems. From this arises the need to use animals for experimental research and in vivo testing. Nevertheless, animal use in experimentation presents various aspects of complexity, such as ethical issues, which led Russell and Burch in 1959 to formulate the 3R (Replacement, Reduction, and Refinement) principle, underlying the urgent need to introduce non-animal-based methods in research. Considering this, three-dimensional (3D) models emerged in the scientific community as a bridge between in vitro and in vivo models, allowing for the achievement of cell differentiation and complexity while avoiding the use of animals in experimental research. The purpose of this review is to provide a general overview of the most common methods to establish 3D cell culture and to discuss their promising applications. Three-dimensional cell cultures have been employed as models to study both organ physiology and diseases; moreover, they represent a valuable tool for studying many aspects of cancer. Finally, the possibility of using 3D models for drug screening and regenerative medicine paves the way for the development of new therapeutic opportunities for many diseases.

Prediction of hub genes and key pathways associated with the radiation response of human hematopoietic stem/progenitor cells using integrated bioinformatics methods

Hematopoietic stem cells (HSCs) are indispensable for the maintenance of the entire blood program through cytokine response. However, HSCs have high radiosensitivity, which is often a problem during radiation therapy and nuclear accidents. Although our previous study has reported that the combination cytokine treatment (interleukin-3, stem cell factor, and thrombopoietin) improves the survival of human hematopoietic stem/progenitor cells (HSPCs) after radiation, the mechanism by which cytokines contribute to the survival of HSPCs is largely unclear. To address this issue, the present study characterized the effect of cytokines on the radiation-induced gene expression profile of human CD34⁺ HSPCs and explored the hub genes that play key pathways associated with the radiation response using a cDNA microarray, a protein-protein interaction-MCODE module analysis and Cytohubba plugin tool in Cytoscape. This study identified 2,733 differentially expressed genes (DEGs) and five hub genes (TOP2A, EZH2, HSPA8, GART, HDAC1) in response to radiation in only the presence of cytokines. Furthermore, functional enrichment analysis found that hub genes and top DEGs based on fold change were enriched in the chromosome organization and organelle organization. The present findings may help predict the radiation response and improve our understanding of this response of human HSPCs.

Unearths IFNB1 immune infiltrates in SOP-related ossification of ligamentum flavum pathogenesis

Background

Ossification of ligamentum flavum (OLF) is a hidden, indolent disease condition with variable unexplained etiology and pathology. Growing evidences show a correlation between senile osteoporosis (SOP) and OLF, but the fundamental relationship between SOP and OLF remains unclear. Therefore, the purpose of this work is to investigate unique SOP-related genes and their potential functions in OLF.

Methods

Gene Expression Omnibus (GEO) database was utilized to gather the mRNA expression data (GSE106253) and then analyzed by R software. A variety of methods, including ssGSEA, machine learning (LASSO and SVM-RFE), GO and KEGG enrichment, PPI network, transcription factor enrichment analysis (TFEA), GSEA and xCells were employed to verified the critical genes and signaling pathways. Furthermore, ligamentum flavum cells were cultured and used in vitro to identify the expression of the core genes.

Results

The preliminary identification of 236 SODEGs revealed their involvement in BP pathways associated with ossification, inflammation, and immune response, including the TNF signaling pathway, PI3K/AKT signaling pathway and osteoclast differentiation. Four down-regulated genes (SERPINE1, SOCS3, AKT1, CCL2) and one up-regulated gene (IFNB1) were among the five hub SODEGs that were validated. Additionally, they were performed by ssGSEA and xCell to show the relationship of immune cells infiltrating in OLF. The most fundamental gene, IFNB1, which was only found in the classical ossification- and inflammation-related pathways, suggested that it may affect OLF via regulating the inflammatory response. In vitro experiment, we found that IFNB1 expression was dramatically higher in cells cocultured with osteogenic induction than in controls.

Conclusion

As far as we are concerned, this is the first observation using transcriptome data mining to reveal distinct SOP-related gene profiles between OLF and normal controls. Five hub SODEGs were ultimately found using bioinformatics algorithms and experimental verification. These genes may mediate intricate inflammatory/immune responses or signaling pathways in the pathogenesis of OLF, according to the thorough functional annotations. Since IFNB1 was discovered to be a key gene and was connected to numerous immune infiltrates in OLF, it is possible that IFNB1 expression has a substantial impact on the pathogenesis of OLF. Our research will give rise to new possibilities for potential therapeutics that target SOP reverent genes and immune-associated pathways in OLF.

Biomarkers in autoimmune diseases of the central nervous system

The autoimmune diseases of the central nervous system (CNS) represent individual heterogeneity with different disease entities. Although clinical and imaging features make it possible to characterize larger patient cohorts, they may not provide sufficient evidence to detect disease activity and response to disease modifying drugs. Biomarkers are becoming a powerful tool due to their objectivity and easy access. Biomarkers may indicate various aspects of biological processes in healthy and/or pathological states, or as a response to drug therapy. According to the clinical features described, biomarkers are usually classified into predictive, diagnostic, monitoring and safety biomarkers. Some nerve injury markers, humoral markers, cytokines and immune cells in serum or cerebrospinal fluid have potential roles in disease severity and prognosis in autoimmune diseases occurring in the CNS, which provides a promising approach for clinicians to early intervention and prevention of future disability. Therefore, this review mainly summarizes the potential biomarkers indicated in autoimmune disorders of the CNS.

New Insights into Risk Genes and Their Candidates in Multiple Sclerosis

Oligodendrocytes are central nervous system glial cells that wrap neuronal axons with their differentiated myelin membranes as biological insulators. There has recently been an emerging concept that multiple sclerosis could be triggered and promoted by various risk genes that appear likely to contribute to the degeneration of oligodendrocytes. Despite the known involvement of vitamin D, immunity, and inflammatory cytokines in disease progression, the common causes and key genetic mechanisms remain unknown. Herein, we focus on recently identified risk factors and risk genes in the background of multiple sclerosis and discuss their relationships.

Significance of Identifying Key Genes Involved in HBV-Related Hepatocellular Carcinoma for Primary Care Surveillance of Patients with Cirrhosis

Cirrhosis is frequently the final stage of disease preceding the development of hepatocellular carcinoma (HCC) and is one of the risk factors for HCC. Preventive surveillance for early HCC in patients with cirrhosis is advantageous for achieving early HCC prevention and diagnosis, thereby enhancing patient prognosis and reducing mortality. However, there is no highly sensitive diagnostic marker for the clinical surveillance of HCC in patients with cirrhosis, which significantly restricts its use in primary care for HCC. To increase the accuracy of illness diagnosis, the study of the effective and sensitive genetic biomarkers involved in HCC incidence is crucial. In this study, a set of 120 significantly differentially expressed genes (DEGs) was identified in the GSE121248 dataset. A protein-protein interaction (PPI) network was constructed among the DEGs, and Cytoscape was used to extract hub genes from the network. In TCGA database, the expression levels, correlation analysis, and predictive performance of hub genes were validated. In total, 15 hub genes showed increased expression, and their positive correlation ranged from 0.80 to 0.90, suggesting they may be involved in the same signaling pathway governing HBV-related HCC. The GSE10143, GSE25097, GSE54236, and GSE17548 datasets were used to investigate the expression pattern of these hub genes in the progression from cirrhosis to HCC. Using Cox regression analysis, a prediction model was then developed. The ROC curves, DCA, and calibration analysis demonstrated the superior disease prediction accuracy of this model. In addition, using proteomic analysis, we investigated whether these key hub genes interact with the HBV-encoded oncogene X protein (HBx), the oncogenic protein in HCC. We constructed stable HBx-expressing LO2-HBx and Huh-7-HBx cell lines. Co-immunoprecipitation coupled with mass spectrometry (Co-IP/MS) results demonstrated that CDK1, RRM2, ANLN, and HMMR interacted specifically with HBx in both cell models. Importantly, we investigated 15 potential key genes (CCNB1, CDK1, BUB1B, ECT2, RACGAP1, ANLN, PBK, TOP2A, ASPM, RRM2, NEK2, PRC1, SPP1, HMMR, and DTL) participating in the transformation process of HBV infection to HCC, of which 4 hub genes (CDK1, RRM2, ANLN, and HMMR) probably serve as potential oncogenic HBx downstream target molecules. All these findings of our study provided valuable research direction for the diagnostic gene detection of HBV-related HCC in primary care surveillance for HCC in patients with cirrhosis.

An Update on Diagnostic Laboratory Biomarkers for Multiple Sclerosis

PURPOSE

For many patients, the multiple sclerosis (MS) diagnostic process can be lengthy, costly, and fraught with error. Recent research aims to address the unmet need for an accurate and simple diagnostic process through discovery of novel diagnostic biomarkers. This review summarizes recent studies on MS diagnostic fluid biomarkers, with a focus on blood biomarkers, and includes discussion of technical limitations and practical applicability.

RECENT FINDINGS

This line of research is in its early days. Accurate and easily obtainable biomarkers for MS have not yet been identified and validated, but several approaches to uncover them are underway. Continue efforts to define laboratory diagnostic biomarkers are likely to play an increasingly important role in defining MS at the earliest stages, leading to better long-term clinical outcomes.

Involvement of TLR2-TLR4, NLRP3, and IL-17 in pain induced by a novel Sprague-Dawley rat model of experimental autoimmune encephalomyelitis

Up to 92% of patients suffering from multiple sclerosis (MS) experience pain, most without adequate treatment, and many report pain long before motor symptoms associated with MS diagnosis. In the most commonly studied rodent model of MS, experimental autoimmune encephalomyelitis (EAE), motor impairments/disabilities caused by EAE can interfere with pain testing. In this study, we characterize a novel low-dose myelin-oligodendrocyte-glycoprotein (MOG)-induced Sprague-Dawley (SD) model of EAE-related pain in male rats, optimized to minimize motor impairments/disabilities. Adult male SD rats were treated with increasing doses of intradermal myelin-oligodendrocyte-glycoprotein (MOG1-125) (0, 4, 8, and 16 μg) in incomplete Freund's adjuvant (IFA) vehicle to induce mild EAE. Von Frey testing and motor assessments were conducted prior to EAE induction and then weekly thereafter to assess EAE-induced pain and motor impairment. Results from these studies demonstrated that doses of 8 and 16 μg MOG1-125 were sufficient to produce stable mechanical allodynia for up to 1 month in the absence of hindpaw motor impairments/disabilities. In the follow-up studies, these doses of MOG1-125, were administered to create allodynia in the absence of confounded motor impairments. Then, 2 weeks later, rats began daily subcutaneous injections of the Toll-like receptor 2 and 4 (TLR2-TLR4) antagonist (+)-naltrexone [(+)-NTX] or saline for an additional 13 days. We found that (+)-NTX also reverses EAE-induced mechanical allodynia in the MOG-induced SD rat model of EAE, supporting parallels between models, but now allowing a protracted timecourse to be examined completely free of motor confounds. Exploring further mechanisms, we demonstrated that both spinal NOD-like receptor protein 3 (NLRP3) and interleukin-17 (IL-17) are necessary for EAE-induced pain, as intrathecal injections of NLRP3 antagonist MCC950 and IL-17 neutralizing antibody both acutely reversed EAE-induced pain. Finally, we show that spinal glial immunoreactivity induced by EAE is reversed by (+)-NTX, and that spinal demyelination correlates with the severity of motor impairments/disabilities. These findings characterize an optimized MOG-induced SD rat model of EAE for the study of pain with minimal motor impairments/disabilities. Finally, these studies support the role of TLR2-TLR4 antagonists as a potential treatment for MS-related pain and other pain and inflammatory-related disorders.