Discovery of Novel Biomarkers for Diagnosing and Predicting the Progression of Multiple Sclerosis Using TMT-Based Quantitative Proteomics

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 potential biomarkers for neuromyelitis optica by quantitative proteomics

OBJECTIVE

Neuromyelitis optica (NMO) was a serious autoimmune inflammatory condition affecting the central nervous system. Currently, there was a lack of diagnostic biomarkers for AQP4-IgG-negative NMO patients.

METHODS

A comparative proteomic analysis was conducted on the CSF of 10 patients with NMO and 10 patients with non-inflammatory neurological disorders (NND) using tandem mass tagging technology. Differentially expressed proteins (DEPs) were analyzed using bioinformatic methods. The candidate proteins were then validated through ELISAs in a subsequent cohort of 160 samples, consisting of paired CSF and plasma samples from 50 NMO patients, CSF samples from 30 NND patients, and plasma samples from 30 healthy individuals.

RESULTS

We identified 389 proteins via proteomics, screening 79 DEPs. NCAM1, SST and AHSG were selected as candidate molecules for further validation. Compared to NND patients, there were decreased levels of AHSG in CSF and increased levels of NCAM1 and SST in NMO patients. The ELISA results revealed significantly higher levels of AHSG, SST and NCAM1 in the CSF of the NMO group compared to the NND group. Similarly, the serum levels of these three proteins were also higher in the NMO group compared to the healthy control group. It was found that serum NCAM1 levels significantly decreased in patients with non-relapsed NMO compared to patients with relapsed NMO and CSF NCAM1 level increased in patients with bilateral NMO compared to patients with unilateral NMO. Furthermore, CSF SST levels increased in AQP4 antibody-positive NMO patients compared to AQP4 antibody-negative patients.

INTERPRETATION

CSF NCAM1, serum NCAM1 and serum SST may serve as potential biomarkers for NMO patients and aid in the diagnosis of AQP4 antibody-negative NMO patients.

Downregulation of the CD151 protects the cardiac function by the crosstalk between the endothelial cells and cardiomyocytes via exosomes

BACKGROUND

Heart failure (HF) is the last stage in the progression of various cardiovascular diseases. Although it is documented that CD151 contributes to regulate the myocardial infarction, the function of CD151 on HF and involved mechanisms are still unclear.

METHOD AND RESULTS

In the present study, we found that the recombinant adeno-associated virus (rAAV)-mediated endothelial cell-specific knockdown of CD151-transfected mice improved transverse aortic constriction (TAC)-induced cardiac function, attenuated myocardial hypertrophy and fibrosis, and increased coronary perfusion, whereas overexpression of the CD151 protein aggravated cardiac dysfunction and showed the opposite effects. In vitro, the cardiomyocytes hypertrophy induced by PE were significantly improved, while the proliferation and migration of cardiac fibroblasts (CFs) were significantly reduced, when co-cultured with the CD151-silenced endothelial cells (ECs). To further explore the mechanisms, the exosomes from the CD151-silenced ECs were taken by cardiomyocyte (CMs) and CFs, verified the intercellular communication. And the protective effects of CD151-silenced ECs were inhibited when exosome inhibitor (GW4869) was added. Additionally, a quantitative proteomics method was used to identify potential proteins in CD151-silenced EC exosomes. We found that the suppression of CD151 could regulate the PPAR signaling pathway via exosomes.

CONCLUSION

Our observations suggest that the downregulation of CD151 is an important positive regulator of cardiac function of heart failure, which can regulate exosome-stored proteins to play a role in the cellular interaction on the CMs and CFs. Modulating the exosome levels of ECs by reducing CD151 expression may offer novel therapeutic strategies and targets for HF treatment.

TMT quantitative proteomics reveals key proteins relevant to microRNA-1-mediated regulation in osteoarthritis

Osteoarthritis (OA) is the second-commonest arthritis, but pathogenic and regulatory mechanisms underlying OA remain incompletely understood. Here, we aimed to identify the mechanisms associated with microRNA-1 (miR-1) treatment of OA in rodent OA models using a proteomic approach. First, N = 18 Sprague Dawley (SD) rats underwent sham surgery (n = 6) or ACL transection (n = 12), followed at an interval of one week by randomization of the ACL transection group to intra-articular administration of either 50 µL placebo (control group) or miR-1 agomir, a mimic of endogenous miR-1 (experimental group). After allowing for eight weeks of remodeling, articular cartilage tissue was harvested and immunohistochemically stained for the presence of MMP-13. Second, N = 30 Col2a1-cre-ERT2 /GFPf1/fl -RFP-miR-1 transgenic mice were randomized to intra-articular administration of either placebo (control group, N = 15) or tamoxifen, an inducer of miR-1 expression (experimental group, N = 15), before undergoing surgical disruption of the medial meniscus (DMM) after an interval of five days. After allowing for eight weeks of remodeling, articular cartilage tissue was harvested and underwent differential proteomic analysis. Specifically, tandem mass tagging (TMT) quantitative proteomic analysis was employed to identify inter-group differentially-expressed proteins (DEP), and selected DEPs were validated using real-time quantitative polymerase chain reaction (RT-qPCR) technology. Immunohistochemically-detected MMP-13 expression was significantly lower in the experimental rat group, and proteomic analyses of mouse tissue homogenate demonstrated that of 3526 identified proteins, 345 were differentially expressed (relative up- and down-regulation) in the experimental group. Proteins Fn1, P4ha1, P4ha2, Acan, F2, Col3a1, Fga, Rps29, Rpl34, and Fgg were the *top ten most-connected proteins, implying that miR-1 may regulate an expression network involving these proteins. Of these ten proteins, three were selected for further validation by RT-qPCR: the transcript of Fn1, known to be associated with OA, exhibited relative upregulation in the experimental group, whereas the transcripts of P4ha1 and Acan exhibited relative downregulation. These proteins may thus represent key miR-1 targets during OA-regulatory mechanisms, and may provide additional insights regarding therapeutic mechanisms of miR-1 in context of OA.

TMT and PRM Based Quantitative Proteomics to Explore the Protective Role and Mechanism of Iristectorin B in Stroke

Stroke is a serious disease caused by the rupture or blockage of the cerebrovascular system. Its pathogenesis is complex and involves multiple mechanisms. Iristectorin B is a natural isoflavone that has certain anti stroke effects. In this study, an in vitro stroke injury model of glyoxylate deprivation was established using PC12 cells, which was used to evaluate the anti-stroke activity of Iristectorin B in ejecta stem. The results showed that Iristectorin B, a natural isoflavone derived from Dried Shoot, significantly reduced the damage to PC12 cells caused by oxygen glucose deprivation/reoxygenation, decreased apoptosis, enhanced cell survival and reduced Ca2+, LDH and ROS levels. The results showed that Iristectorin B had a significant protective effect on Na2S2O4-injured PC12 cells, and the mechanism may be related to the protective effect of neurons in the brain. After protein extraction and various analyses were performed, a series of cutting-edge technologies were organically combined to study the quantitative proteome of each group. Differential proteins were then analyzed. According to the protein screening principle, ferroptosis-related proteins were most closely associated with stroke. The differential proteins associated with ferroptosis screened were SLC3A2, TFR1 and HMOX1, with HMOX1 being the most significantly elevated and reduced via dosing. Iristectorin B may act as a protective agent against stroke by regulating ferroptosis, and SLC3A2, TFR1 and HMOX1 may serve as potential diagnostic biomarkers for stroke, providing additional evidence to support the importance of ferroptosis in stroke.

TNF-α/STAT1/CXCL10 mutual inflammatory axis that contributes to the pathogenesis of experimental models of multiple sclerosis: A promising signaling pathway for targeted therapies

BACKGROUND

Identifying mutual neuroinflammatory axis in different experimental models of multiple sclerosis (MS) is essential to evaluate the de- and re-myelination processes and improve therapeutic interventions' reproducibility.

METHODS

The expression profile data set of EAE (GSE47900) and cuprizone (GSE100663) models were downloaded from the Gene Expression Omnibus database. The R package and GEO2R software processed these raw chip data. Gene Ontology (GO) functional analysis, KEGG pathway analysis, and protein-protein interaction network analysis were performed to investigate interactions between common differentially expressed genes (DEGs) in all models. Finally, the ELISA method assessed the protein level of highlighted mutual cytokines in serum.

RESULTS

Our data introduced 59 upregulated [CXCL10, CCL12, and GBP6 as most important] and 17 downregulated [Serpinb1a, Prr18, and Ugt8a as most important] mutual genes. The signal transducer and activator of transcription 1 (STAT1) and CXCL10 were the most crucial hub proteins among mutual upregulated genes. These mutual genes were found to be mainly involved in the TNF-α, TLRs, and complement cascade signaling, and animal models shared 26 mutual genes with MS individuals. Finally, significant upregulation of serum level of TNF-α/IL-1β/CXCL10 cytokines was confirmed in all models in a relatively similar pattern.

CONCLUSION

For the first time, our study revealed the common neuroinflammatory pathway in animal models of MS and introduced candidate hub genes for better evaluating the preclinical efficacy of pharmacological interventions and designing prospective targeted therapies.

Diagnostic Potential of Two Novel Biomarkers for Neuromyelitis Optica Spectrum Disorder and Multiple Sclerosis

BACKGROUND

Currently, no tests can definitively diagnose and distinguish neuromyelitis optica spectrum disorder (NMOSD) from multiple sclerosis (MS).

METHODS

Initially, cerebrospinal fluid (CSF) proteomics were employed to uncover the novel biomarkers that differentiate NMOSD from MS into cohorts of 10 MS and 10 NMOSD patients. Subsequently, screening biomarkers were validated using an enzyme-linked immunosorbent assay method and CSF and serum samples from 20 MS patients, 20 NMOSD patients, 20 non-inflammatory neurological controls, and 20 healthy controls.

RESULTS

In study cohort, insulin-like growth factor-binding protein 7 (IGFBP7) and lysosome-associated membrane glycoprotein 2 (LAMP2) were screened. In validation cohort, serum and CSF IGFBP7 not only exhibited higher levels in MS and NMOSD patients than controls, but also had greatest area under the curve (AUC, above or equal to 0.8) in MS and NMOSD diagnoses. Serum IGFBP7 (0.945) and CSF IGFBP7 (0.890) also had the greatest AUCs for predicting MS progression, while serum LAMP2 had a moderate curve (0.720).

CONCLUSIONS

IGFBP7 was superior in diagnosing MS and NMOSD, and IGFBP7 and serum LAMP2 performed exceptionally well in predicting the MS progression. These results offered reasons for further investigations into the functions of IGFBP7 and LAMP2 in MS and NMOSD.

TMT proteomics analysis of cerebrospinal fluid from patients with cerebral venous sinus thrombosis

CVST is a type of venous stroke that mainly affects young adults with no reliable diagnostic markers and effective treatment strategies for secondary pathologies. However, the underlying pathological molecular mechanisms remain unclear. Here, we systematically analyzed the molecule profiling of the cerebrospinal fluid (CSF) in CVST patients via tandem mass tag (TMT)-based proteomics for the first time, aiming to reveal the pathogenesis and provide evidence for the diagnosis and treatment of CVST. Five CVST patients and five control patients were selected, and CSF samples were analyzed by TMT proteomics. Differentially expressed proteins (DEPs) were acquired and bioinformatics analysis was performed. Besides, parallel reaction monitoring (PRM) was utilized to validate the DEPs. 468 differentially expressed proteins were screened, 185 of which were up-regulated and 283 were down-regulated (fold change >1.2, P < 0.05). Bioinformatics analysis displayed that these proteins were significantly enriched in multiple pathways related to a variety of pathophysiological processes. PRM verification showed that apolipoprotein E, MMP-2, neuroserpin, clusterin, and several other molecules were down-regulated. These identified proteins reveal unique pathophysiological characteristics secondary to CVST. Further characterization of these proteins in future research could enable their application as potential therapeutic targets and biomarkers in CVST therapy. SIGNIFICANCE: Cerebral venous sinus thrombosis (CVST) is an underrated and potentially fatal cause of stroke with a reported mortality of 5-10% worldwide. Currently, in addition to anticoagulant and thrombolytic therapy, effective treatments targeting the injured brain parenchyma after CVST remain limited. Besides, accurate diagnostic markers are still sorely lacking. In the present study, we will detect the alterations of the CSF protein spectrum of CVST patients by TMT technique, screen differentially expressed proteins, analyze the functions of these signals through bioinformatics methods, and finally validate the key molecules through parallel reaction monitoring (PRM) technique. Collectively, the study aimed to offer a reference for the discovery of specific protein/pathway alterations in the CSF of CVST patients and further reveal the underlying pathogenesis, thereby providing evidence for the diagnosis and treatment of CVST.

The Brain's Microvascular Response to High Glycemia and to the Inhibition of Soluble Epoxide Hydrolase Is Sexually Dimorphic

Biological sex and a high glycemic diet (HGD) contribute to dementia, yet little is known about the operative molecular mechanisms. Our goal was to understand the differences between males and females in the multi-genomic response of the hippocampal microvasculature to the HGD, and whether there was vasculoprotection via the inhibition of soluble epoxide hydrolase (sEHI). Adult wild type mice fed high or low glycemic diets for 12 weeks, with or without an sEHI inhibitor (t-AUCB), had hippocampal microvessels isolated by laser-capture microdissection. Differential gene expression was determined by microarray and integrated multi-omic bioinformatic analyses. The HGD induced opposite effects in males and females: the HGD-upregulated genes were involved in neurodegeneration or neuroinflammation in males, whereas in females they downregulated the same pathways, favoring neuroprotection. In males, the HGD was associated with a greater number of clinical diseases than in females, the sEHI downregulated genes involved in neurodegenerative diseases to a greater extent with the HGD and compared to females. In females, the sEHI downregulated genes involved in endothelial cell functions to a greater extent with the LGD and compared to males. Our work has potentially important implications for sex-specific therapeutic targets for vascular dementia and cardiovascular diseases in males and females.

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.

A practical guide to interpreting and generating bottom-up proteomics data visualizations

Mass-spectrometry based bottom-up proteomics is the main method to analyze proteomes comprehensively and the rapid evolution of instrumentation and data analysis has made the technology widely available. Data visualization is an integral part of the analysis process and it is crucial for the communication of results. This is a major challenge due to the immense complexity of MS data. In this review, we provide an overview of commonly used visualizations, starting with raw data of traditional and novel MS technologies, then basic peptide and protein level analyses, and finally visualization of highly complex datasets and networks. We specifically provide guidance on how to critically interpret and discuss the multitude of different proteomics data visualizations. Furthermore, we highlight Python-based libraries and other open science tools that can be applied for independent and transparent generation of customized visualizations. To further encourage programmatic data visualization, we provide the Python code used to generate all data Figures in this review on GitHub (https://github.com/MannLabs/ProteomicsVisualization). This article is protected by copyright. All rights reserved.

Molecular biomarkers in multiple sclerosis

Multiple sclerosis (MS) is a highly heterogenous disease regarding radiological, pathological, and clinical characteristics and therapeutic response, including both the efficacy and safety profile of treatments. Accordingly, there is a high demand for biomarkers that sensitively and specifically apprehend the distinctive aspects of the MS heterogeneity, and that can aid in better understanding of the disease diagnosis, prognosis, prediction of the treatment response, and, finally, in the development of new treatments. Currently, clinical characteristics (e.g., relapse rate and disease progression) and magnetic resonance imaging play the most important role in the clinical classification of MS and assessment of its course. Molecular biomarkers (e.g., immunoglobulin G (IgG) oligoclonal bands, IgG index, anti-aquaporin-4 antibodies, neutralizing antibodies against interferon-beta and natalizumab, anti-varicella zoster virus and anti-John Cunningham (JC) virus antibodies) complement these markers excellently. This review provides an overview of exploratory, validated and clinically useful molecular biomarkers in MS which are used for prediction, diagnosis, disease activity and treatment response.