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

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.

Identification of brain-enriched proteins in CSF as biomarkers of relapsing remitting multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a clinically and biologically heterogenous disease with currently unpredictable progression and relapse. After the development and success of neurofilament as a cerebrospinal fluid (CSF) biomarker, there is reinvigorated interest in identifying other markers of or contributors to disease. The objective of this study is to probe the predictive potential of a panel of brain-enriched proteins on MS disease progression and subtype.

METHODS

This study includes 40 individuals with MS and 14 headache controls. The MS cohort consists of 20 relapsing remitting (RR) and 20 primary progressive (PP) patients. The CSF of all individuals was analyzed for 63 brain enriched proteins using a method of liquid-chromatography tandem mass spectrometry. Wilcoxon rank sum test, Kruskal-Wallis one-way ANOVA, logistic regression, and Pearson correlation were used to refine the list of candidates by comparing relative protein concentrations as well as relation to known imaging and molecular biomarkers.

RESULTS

We report 30 proteins with some relevance to disease, clinical subtype, or severity. Strikingly, we observed widespread protein depletion in the disease CSF as compared to control. We identified numerous markers of relapsing disease, including KLK6 (kallikrein 6, OR = 0.367, p < 0.05), which may be driven by active disease as defined by MRI enhancing lesions. Other oligodendrocyte-enriched proteins also appeared at reduced levels in relapsing disease, namely CNDP1 (carnosine dipeptidase 1), LINGO1 (leucine rich repeat and Immunoglobin-like domain-containing protein 1), MAG (myelin associated glycoprotein), and MOG (myelin oligodendrocyte glycoprotein). Finally, we identified three proteins-CNDP1, APLP1 (amyloid beta precursor like protein 1), and OLFM1 (olfactomedin 1)-that were statistically different in relapsing vs. progressive disease raising the potential for use as an early biomarker to discriminate clinical subtype.

CONCLUSIONS

We illustrate the utility of targeted mass spectrometry in generating potential targets for future biomarker studies and highlight reductions in brain-enriched proteins as markers of the relapsing remitting disease stage.

Cerebrospinal fluid camk2a levels at baseline predict long-term progression in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) remains a highly unpredictable disease. Many hope that fluid biomarkers may contribute to better stratification of disease, aiding the personalisation of treatment decisions, ultimately improving patient outcomes.

OBJECTIVE

The objective of this study was to evaluate the predictive value of CSF brain-specific proteins from early in the disease course of MS on long term clinical outcomes.

METHODS

In this study, 34 MS patients had their CSF collected and stored within 5 years of disease onset and were then followed clinically for at least 15 years. CSF concentrations of 64 brain-specific proteins were analyzed in the 34 patient CSF, as well as 19 age and sex-matched controls, using a targeted liquid-chromatography tandem mass spectrometry approach.

RESULTS

We identified six CSF brain-specific proteins that significantly differentiated MS from controls (p < 0.05) and nine proteins that could predict disease course over the next decade. CAMK2A emerged as a biomarker candidate that could discriminate between MS and controls and could predict long-term disease progression.

CONCLUSION

Targeted approaches to identify and quantify biomarkers associated with MS in the CSF may inform on long term MS outcomes. CAMK2A may be one of several candidates, warranting further exploration.

A beginner's guide into curated analyses of open access datasets for biomarker discovery in neurodegeneration

The discovery of surrogate biomarkers reflecting neuronal dysfunction in neurodegenerative diseases (NDDs) remains an active area of research. To boost these efforts, we demonstrate the utility of publicly available datasets for probing the pathogenic relevance of candidate markers in NDDs. As a starting point, we introduce the readers to several open access resources, which contain gene expression profiles and proteomics datasets from patient studies in common NDDs, including proteomics analyses of cerebrospinal fluid (CSF). Then, we illustrate the method for curated gene expression analyses across select brain regions from four cohorts of Parkinson disease patients (and from one study in common NDDs), probing glutathione biogenesis, calcium signaling and autophagy. These data are complemented by findings of select markers in CSF-based studies in NDDs. Additionally, we enclose several annotated microarray studies, and summarize reports on CSF proteomics across the NDDs, which the readers can utilize for translational purposes. We anticipate that this "beginner's guide" will benefit the research community in NDDs, and would serve as a useful educational tool.

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.

Review of Metabolomics-Based Biomarker Research for Parkinson's Disease

Parkinson's disease (PD), as the second most common neurodegenerative disease, is seriously affecting the life quality of the elderly. However, there is still a lack of efficient medical methods to diagnosis PD before apparent symptoms occur. In recent years, clinical biomarkers including genetic, imaging, and tissue markers have exhibited remarkable benefits in assisting PD diagnoses. Due to the advantages of high-throughput detection of metabolites and almost non-invasive sample collection, metabolomics research of PD is widely used for diagnostic biomarker discovery. However, there are also a few shortages for those identified biomarkers, such as the scarcity of verifications regarding the sensitivity and specificity. Thus, reviewing the research progress of PD biomarkers based on metabolomics techniques is of great significance for developing PD diagnosis. To comprehensively clarify the progress of current metabolic biomarker studies in PD, we reviewed 20 research articles regarding the discovery and validation of biomarkers for PD diagnosis from three mainstream academic databases (NIH PubMed, ISI Web of Science, and Elsevier ScienceDirect). By analyzing those materials, we summarized the metabolic biomarkers identified by those metabolomics studies and discussed the potential approaches used for biomarker verifications. In conclusion, this review provides a comprehensive and updated overview of PD metabolomics research in the past two decades and particularly discusses the validation of disease biomarkers. We hope those discussions might provide inspiration for PD biomarker discovery and verification in the future.

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.

Cerebrospinal fluid proteome shows disrupted neuronal development in multiple sclerosis

Despite intensive research, the aetiology of multiple sclerosis (MS) remains unknown. Cerebrospinal fluid proteomics has the potential to reveal mechanisms of MS pathogenesis, but analyses must account for disease heterogeneity. We previously reported explorative multivariate analysis by hierarchical clustering of proteomics data of MS patients and controls, which resulted in two groups of individuals. Grouping reflected increased levels of intrathecal inflammatory response proteins and decreased levels of proteins involved in neural development in one group relative to the other group. MS patients and controls were present in both groups. Here we reanalysed these data and we also reanalysed data from an independent cohort of patients diagnosed with clinically isolated syndrome (CIS), who have symptoms of MS without evidence of dissemination in space and/or time. Some, but not all, CIS patients had intrathecal inflammation. The analyses reported here identified a common protein signature of MS/CIS that was not linked to elevated intrathecal inflammation. The signature included low levels of complement proteins, semaphorin-7A, reelin, neural cell adhesion molecules, inter-alpha-trypsin inhibitor heavy chain H2, transforming growth factor beta 1, follistatin-related protein 1, malate dehydrogenase 1 cytoplasmic, plasma retinol-binding protein, biotinidase, and transferrin, all known to play roles in neural development. Low levels of these proteins suggest that MS/CIS patients suffer from abnormally low oxidative capacity that results in disrupted neural development from an early stage of the disease.

Proteomic Approaches to Decipher Mechanisms Underlying Pathogenesis in Multiple Sclerosis Patients

Multiple sclerosis (MS) is a chronic inflammatory demyelinating and neurodegenerative disease of the central nervous system (CNS). The cause of MS is unknown, with no effective therapies available to halt the progressive neurological disability. Development of new and improvement of existing therapeutic strategies therefore require a better understanding of MS pathogenesis, especially during the progressive phase of the disease. This can be achieved through development of biomarkers that can help to identify disease pathophysiology and monitor disease progression. Proteomics is a powerful and promising tool to accelerate biomarker detection and contribute to novel therapeutics. In this review, an overview of how proteomic technology using CNS tissues and biofluids from MS patients has provided important clues to the pathogenesis of MS is provided. Current publications, pitfalls, as well as directions of future research involving proteomic approaches to understand the pathogenesis of MS are discussed.