CSF Proteomics Identifies Specific and Shared Pathways for Multiple Sclerosis Clinical Subtypes

Quantitative proteomics and multi-omics analysis identifies potential biomarkers and the underlying pathological molecular networks in Chinese patients with multiple sclerosis

Multiple sclerosis (MS) is an autoimmune disorder caused by chronic inflammatory reactions in the central nervous system. Currently, little is known about the changes of plasma proteomic profiles in Chinese patients with MS (CpwMS) and its relationship with the altered profiles of multi-omics such as metabolomics and gut microbiome, as well as potential molecular networks that underlie the etiology of MS. To uncover the characteristics of proteomics landscape and potential multi-omics interaction networks in CpwMS, Plasma samples were collected from 22 CpwMS and 22 healthy controls (HCs) and analyzed using a Tandem Mass Tag (TMT)-based quantitative proteomics approach. Our results showed that the plasma proteomics pattern was significantly different in CpwMS compared to HCs. A total of 90 differentially expressed proteins (DEPs), such as LAMP1 and FCG2A, were identified in CpwMS plasma comparing to HCs. Furthermore, we also observed extensive and significant correlations between the altered proteomic profiles and the changes of metabolome, gut microbiome, as well as altered immunoinflammatory responses in MS-affected patients. For instance, the level of LAMP1 and ERN1 were significantly and positively correlated with the concentrations of metabolite L-glutamic acid and pro-inflammatory factor IL-17 (Padj < 0.05). However, they were negatively correlated with the amounts of other metabolites such as L-tyrosine and sphingosine 1-phosphate, as well as the concentrations of IL-8 and MIP-1α. This study outlined the underlying multi-omics integrated mechanisms that might regulate peripheral immunoinflammatory responses and MS progression. These findings are potentially helpful for developing new assisting diagnostic biomarker and therapeutic strategies for MS.

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

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

Prospective outcome analysis of multiple sclerosis cases reveals candidate prognostic cerebrospinal fluid markers

BACKGROUND

Predicting the long-term disability outcomes of multiple sclerosis (MS) cases is challenging.

OBJECTIVE

We prospectively analysed our previous MS cohort with initial cerebrospinal fluid (CSF) proteomics data to reveal disability markers after 8.2±2.2 years of follow-up.

METHODS

Patients with regular follow-up visits were assigned into two groups: those with an age-related MS severity (ARMSS) score ≥5 (unfavourable course group, N = 27) and ARMSS score <5 (favourable course group, N = 67). A machine learning-based algorithm was applied to reveal candidate poor prognosis-associated initial CSF proteins, which were measured in an independent MS cohort (verification group, N = 40) by ELISA. Additionally, the correlation of initial clinical and radiological parameters with long-term disability was analysed.

RESULTS

CSF alpha-2-macroglobulin (P = 0.0015), apo-A1 (P = 0.0016), and haptoglobin (P = 0.0003) protein levels, as well as cerebral lesion load (>9 lesions) on magnetic resonance imaging, gait disturbance (P = 0.04), and bladder/bowel symptoms (P = 0.01) were significantly higher in the unfavourable course group than in the favourable course group. Optic nerve involvement evident on initial magnetic resonance imaging (P = 0.002) and optic neuritis (P = 0.01) were more frequent in the favourable course group.

CONCLUSION

The herein identified initial CSF protein levels, in addition to the clinical and radiological parameters at disease onset, have predictive value for long-term disability in MS cases.

Proteomics in Multiple Sclerosis: The Perspective of the Clinician

Multiple sclerosis (MS) is the inflammatory demyelinating and neurodegenerative disease of the central nervous system (CNS) that affects approximately 2.8 million people worldwide. In the last decade, a new era was heralded in by a new phenotypic classification, a new diagnostic protocol and the first ever therapeutic guideline, making personalized medicine the aim of MS management. However, despite this great evolution, there are still many aspects of the disease that are unknown and need to be further researched. A hallmark of these research are molecular biomarkers that could help in the diagnosis, differential diagnosis, therapy and prognosis of the disease. Proteomics, a rapidly evolving discipline of molecular biology may fulfill this dire need for the discovery of molecular biomarkers. In this review, we aimed to give a comprehensive summary on the utility of proteomics in the field of MS research. We reviewed the published results of the method in case of the pathogenesis of the disease and for biomarkers of diagnosis, differential diagnosis, conversion of disease courses, disease activity, progression and immunological therapy. We found proteomics to be a highly effective emerging tool that has been providing important findings in the research of MS.

Investigation of neuro-inflammatory parameters in a cuprizone induced mouse model of multiple sclerosis

Cuprizone, copper chelator, treatment of mouse is a toxic model of multiple sclerosis (MS) in which oligodendrocyte death, demyelination and remyelination can be observed. Understanding T and B cell subset as well as their cytokines involved in MS pathogenesis still requires further scrutiny to better understand immune component of MS. The study presented here, aimed to evaluate relevant cytokines, lymphocytes, and gene expressions profiles during demyelination and remyelination in the cuprizone mouse model of MS. Eighty male C57BL/6J mice fed with 0.2% cuprizone for eight weeks. Cuprizone has been removed from the diet in the following eight weeks. Cuprizone treated and control mice sacrificed biweekly, and corpus callosum of the brain was investigated by staining. Lymphocyte cells of mice analyzed by flow cytometry with CD3e, CD11b, CD19, CD80, CD86, CD4, CD25 and FOXP3 antibodies. IFN-gamma, IL-1alpha, IL-2, IL-5, IL-6, IL-10, IL-17, TNF-alpha cytokines were analyzed in plasma samples. Neuregulin 1 (Nrg1), ciliary neurotrophic factor (Cntf) and C-X-C chemokine receptor type 4 (Cxcr4) gene expressions in corpus callosum sections of the mice brain were quantified. Histochemistry analysis showed that demyelination began at the fourth week of cuprizone administration and total demyelination occurred at the twelfth week in chronic model. Remyelination occurred at the fourth week of following withdrawal of cuprizone from diet. The level of mature and activated T cells, regulatory T cells, T helper cells and mature B cells increased during demyelination and decreased when cuprizone removed from diet. Further, both type 1 and type 2 cytokines together with the proinflammatory cytokines increased. The level of oligodendrocyte maturation and survival genes showed differential gene expression in parallel to that of demyelination and remyelination. In conclusion, for the first-time, involvement of both cellular immune response and antibody response as well as oligodendrocyte maturation and survival factors having role in demyelination and remyelination of cuprizone mouse model of MS have been shown.

Investigation of multiple sclerosis-related pathways through the integration of genomic and proteomic data

Background

Multiple sclerosis (MS) has a complex pathophysiology, variable clinical presentation, and unpredictable prognosis; understanding the underlying mechanisms requires combinatorial approaches that warrant the integration of diverse molecular omics data.

Methods

Here, we combined genomic and proteomic data of the same individuals among a Turkish MS patient group to search for biologically important networks. We previously identified differentially-expressed proteins by cerebrospinal fluid proteome analysis of 179 MS patients and 42 non-MS controls. Among this study group, 11 unrelated MS patients and 60 independent, healthy controls were subjected to whole-genome SNP genotyping, and genome-wide associations were assessed. Pathway enrichment analyses of MS-associated SNPs and differentially-expressed proteins were conducted using the functional enrichment tool, PANOGA.

Results

Nine shared pathways were detected between the genomic and proteomic datasets after merging and clustering the enriched pathways. Complement and coagulation cascade was the most significantly associated pathway (hsa04610, P = 6.96 × 10-30). Other pathways involved in neurological or immunological mechanisms included adherens junctions (hsa04520, P = 6.64 × 10-25), pathogenic Escherichia coli infection (hsa05130, P = 9.03 × 10-14), prion diseases (hsa05020, P = 5.13 × 10-13).

Conclusion

We conclude that integrating multiple datasets of the same patients helps reducing false negative and positive results of genome-wide SNP associations and highlights the most prominent cellular players among the complex pathophysiological mechanisms.

Multiple Sclerosis Biomarker Discoveries by Proteomics and Metabolomics Approaches

Multiple sclerosis (MS) is an autoimmune inflammatory disorder of the central nervous system (CNS) resulting in demyelination and axonal loss in the brain and spinal cord. The precise pathogenesis and etiology of this complex disease are still a mystery. Despite many studies that have been aimed to identify biomarkers, no protein marker has yet been approved for MS. There is urgently needed for biomarkers, which could clarify pathology, monitor disease progression, response to treatment, and prognosis in MS. Proteomics and metabolomics analysis are powerful tools to identify putative and novel candidate biomarkers. Different human compartments analysis using proteomics, metabolomics, and bioinformatics approaches has generated new information for further clarification of MS pathology, elucidating the mechanisms of the disease, finding new targets, and monitoring treatment response. Overall, omics approaches can develop different therapeutic and diagnostic aspects of complex disorders such as multiple sclerosis, from biomarker discovery to personalized medicine.

The Impact of Multiple Sclerosis Disease Status and Subtype on Hematological Profile

Multiple sclerosis (MS) is an immune-mediated, demyelinating disease of the central nervous system. In this study, an MS cohort and healthy controls were stratified into Caucasian and African American groups. Patient hematological profiles-composed of complete blood count (CBC) and complete metabolic panel (CMP) test values-were analyzed to identify differences between MS cases and controls and between patients with different MS subtypes. Additionally, random forest models were used to determine the aggregate utility of common hematological tests in determining MS disease status and subtype. The most significant and relevant results were increased bilirubin and creatinine in MS cases. The random forest models achieved some success in differentiating between MS cases and controls (AUC values: 0.725 and 0.710, respectively) but were not successful in differentiating between subtypes. However, larger samples that adjust for possible confounding variables, such as treatment status, may reveal the value of these tests in differentiating between MS subtypes.

Characterization of the inflammatory-metabolic phenotype of heart failure with a preserved ejection fraction: a hypothesis to explain influence of sex on the evolution and potential treatment of the disease

Accumulating evidence points to the existence of an inflammatory-metabolic phenotype of heart failure with a preserved ejection fraction (HFpEF), which is characterized by biomarkers of inflammation, an expanded epicardial adipose tissue mass, microvascular endothelial dysfunction, normal-to-mildly increased left ventricular volumes and systolic blood pressures, and possibly, altered activity of adipocyte-associated inflammatory mediators. A broad range of adipogenic metabolic and systemic inflammatory disorders - e.g. obesity, diabetes and metabolic syndrome as well as rheumatoid arthritis and psoriasis - can cause this phenotype, independent of the presence of large vessel coronary artery disease. Interestingly, when compared with men, women are both at greater risk of and may suffer greater cardiac consequences from these systemic inflammatory and metabolic disorders. Women show disproportionate increases in left ventricular filling pressures following increases in central blood volume and have greater arterial stiffness than men. Additionally, they are particularly predisposed to epicardial and intramyocardial fat expansion and imbalances in adipocyte-associated proinflammatory mediators. The hormonal interrelationships seen in inflammatory-metabolic phenotype may explain why mineralocorticoid receptor antagonists and neprilysin inhibitors may be more effective in women than in men with HFpEF. Recognition of the inflammatory-metabolic phenotype may improve an understanding of the pathogenesis of HFpEF and enhance the ability to design clinical trials of interventions in this heterogeneous syndrome.

Identification of candidate biomarkers in converting and non-converting clinically isolated syndrome by proteomics analysis of cerebrospinal fluid

Multiple sclerosis (MS) often starts in the form of clinically isolated syndrome (CIS) and only some of the CIS patients progress to relapsing-remitting MS (RRMS). Biomarkers to predict conversion from CIS to MS are thus greatly needed for making correct treatment decisions. To identify a predictive cerebrospinal fluid (CSF) protein, we analyzed the first-attack CSF samples of CIS patients who converted (CIS-MS) (n = 23) and did not convert (CIS-CIS) (n = 19) to RRMS in a follow-up period of 5 years using proteomics analysis by liquid chromatography tandem-mass spectrometry (LC-MS/MS) and verified by ELISA. Label-free differential proteomics analysis of CSF ensured that 637 proteins were identified and 132 of these proteins were found to be statistically significant. Further investigation with the ingenuity pathway analysis (IPA) software led to identification of three pathway networks mostly comprised proteins involved in inflammatory response, cellular growth and tissue proliferation. CSF levels of four of the most differentially expressed proteins belonging to the cellular proliferation network function, chitinase-3-like protein 1 (CHI3L1), tumor necrosis factor receptor superfamily member 21 (TNFRSF21), homeobox protein Hox-B3 (HOXB3) and iduronate 2-sulfatase (IDS), were measured by ELISA. CSF levels of HOXB3 were significantly increased in CIS-MS patients. Our results indicate that cell and tissue proliferation functions are dysregulated in MS as early as the first clinical episode. HOXB3 has emerged as a potential novel biomarker which might be used for prediction of CIS-MS conversion.

A systems medicine approach reveals disordered immune system and lipid metabolism in multiple sclerosis patients

Identification of autoimmune processes and introduction of new autoantigens involved in the pathogenesis of multiple sclerosis (MS) can be helpful in the design of new drugs to prevent unresponsiveness and side effects in patients. To find significant changes, we evaluated the autoantibody repertoires in newly diagnosed relapsing-remitting MS patients (NDP) and those receiving disease-modifying therapy (RP). Through a random peptide phage library, a panel of NDP- and RP-specific peptides was identified, producing two protein data sets visualized using Gephi, based on protein--protein interactions in the STRING database. The top modules of NDP and RP networks were assessed using Enrichr. Based on the findings, a set of proteins, including ATP binding cassette subfamily C member 1 (ABCC1), neurogenic locus notch homologue protein 1 (NOTCH1), hepatocyte growth factor receptor (MET), RAF proto-oncogene serine/threonine-protein kinase (RAF1) and proto-oncogene vav (VAV1) was found in NDP and was involved in over-represented terms correlated with cell-mediated immunity and cancer. In contrast, transcription factor RelB (RELB), histone acetyltransferase p300 (EP300), acetyl-CoA carboxylase 2 (ACACB), adiponectin (ADIPOQ) and phosphoenolpyruvate carboxykinase 2 mitochondrial (PCK2) had major contributions to viral infections and lipid metabolism as significant events in RP. According to these findings, further research is required to demonstrate the pathogenic roles of such proteins and autoantibodies targeting them in MS and to develop therapeutic agents which can ameliorate disease severity.

Decreased Neuro-Axonal Proteins in CSF at First Attack of Suspected Multiple Sclerosis

The pathology of multiple sclerosis is located in the central nervous system, therefore cerebrospinal fluid (CSF) is an attractive biofluid for biomarker research for proteins related to the early stages of this disease. In this study, the CSF proteome of patients with a clinically isolated syndrome of demyelination (CIS, a first attack of multiple sclerosis) is compared to the CSF proteome of control patients to identify differentially abundant proteins. CSF samples of 47 CIS patients and 45 control subjects are enzymatically digested and subsequently measured by LC-MS/MS (LTQ-Orbitrap). Following mass spectrometry differential abundances of the identified proteins between groups are investigated. A total of 3159 peptides are identified, relating to 485 proteins. One protein is significantly more abundant in CSF of CIS patients than in controls: Ig kappa chain C region. In contrast, 35 proteins are significantly lower in CIS patients than controls, most of them with functions in nervous system development and function, such as amyloid-like protein 1 (validated by ELISA in an independent sample set (p < 0.01)), contactin 1, contactin 2 and neuronal cell adhesion molecule. A remarkably lower abundance of neuro-axonal proteins is observed in patients with a first demyelinating event compared to controls.

Anemoside A3 ameliorates experimental autoimmune encephalomyelitis by modulating T helper 17 cell response

Anemoside A₃ (AA3) is a natural triterpenoid glycoside isolated from the root of Pulsatilla chinensis (Bunge) Regel. We previously showed that AA3 exhibits cognitive-enhancing and neuroprotective properties. In the present study, we demonstrated that AA3 modulates inflammatory responses by regulating prostaglandin E receptor 4 signaling. Because prostaglandin E receptor 4 is involved in the pathophysiology of experimental autoimmune encephalomyelitis (EAE), an animal model of human multiple sclerosis (MS), we assessed the beneficial effect of AA3 in EAE mice. AA3 treatment significantly reduced clinical severity and inflammatory infiltrates in the spinal cord of EAE mice. In vitro studies revealed that AA3 inhibited the T cell response toward the encephalitogenic epitope of myelin oligodendrocyte glycoprotein (MOG). AA3 significantly downregulated the expressions of certain Th1 and Th17 cytokines in activated T cells re-stimulated by MOG. Moreover, AA3 inhibited the activation of STAT4 and STAT3, which are the transcription factors pivotal for Th1 and Th17 lineage differentiation, respectively, in activated T cells. Pharmacological analysis further suggested that AA3 reduced Th17 cell differentiation and expansion. In conclusion, AA3 exerts an immunomodulatory effect in EAE, demonstrating its potential as a therapeutic agent for MS in humans.

In-Depth Cerebrospinal Fluid Quantitative Proteome and Deglycoproteome Analysis: Presenting a Comprehensive Picture of Pathways and Processes Affected by Multiple Sclerosis

In the current study, we conducted a quantitative in-depth proteome and deglycoproteome analysis of cerebrospinal fluid (CSF) from relapsing-remitting multiple sclerosis (RRMS) and neurological controls using mass spectrometry and pathway analysis. More than 2000 proteins and 1700 deglycopeptides were quantified, with 484 proteins and 180 deglycopeptides significantly changed between pools of RRMS and pools of controls. Approximately 300 of the significantly changed proteins were assigned to various biological processes including inflammation, extracellular matrix organization, cell adhesion, immune response, and neuron development. Ninety-six significantly changed deglycopeptides mapped to proteins that were not found changed in the global protein study. In addition, four mapped to the proteins oligo-myelin glycoprotein and noelin, which were found oppositely changed in the global study. Both are ligands to the nogo receptor, and the glycosylation of these proteins appears to be affected by RRMS. Our study gives the most extensive overview of the RRMS affected processes observed from the CSF proteome to date, and the list of differential proteins will have great value for selection of biomarker candidates for further verification.