Proteomic Analysis Of Cerebrospinal Fluid Research Articles

Proteomic analysis of cerebrospinal fluid and plasma during neonatal late-onset sepsis investigations: a way to define neuro-flogosis and maturation of blood-brain barrier in newborn infants

Proteomic analysis of cerebrospinal fluid and plasma during neonatal late-onset sepsis investigations: a way to define neuro-flogosis and maturation of blood-brain barrier in newborn infants

Integrative Metabolome and Proteome Analysis of Cerebrospinal Fluid in Parkinson's Disease.

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra. Recent studies have highlighted the significant role of cerebrospinal fluid (CSF) in reflecting pathophysiological PD brain conditions by analyzing the components of CSF. Based on the published literature, we created a single network with altered metabolites in the CSF of patients with PD. We analyzed biological functions related to the transmembrane of mitochondria, respiration of mitochondria, neurodegeneration, and PD using a bioinformatics tool. As the proteome reflects phenotypes, we collected proteome data based on published papers, and the biological function of the single network showed similarities with that of the metabolomic network. Then, we analyzed the single network of integrated metabolome and proteome. In silico predictions based on the single network with integrated metabolomics and proteomics showed that neurodegeneration and PD were predicted to be activated. In contrast, mitochondrial transmembrane activity and respiration were predicted to be suppressed in the CSF of patients with PD. This review underscores the importance of integrated omics analyses in deciphering PD's complex biochemical networks underlying neurodegeneration.

Deep Proteome Analysis of Cerebrospinal Fluid from Pediatric Patients with Central Nervous System Cancer.

The cerebrospinal fluid (CSF) is a key matrix for discovery of biomarkers relevant for prognosis and the development of therapeutic targets in pediatric central nervous system malignancies. However, the wide range of protein concentrations and age-related differences in children makes such discoveries challenging. In addition, pediatric CSF samples are often sparse and first prioritized for clinical purposes. The present work focused on optimizing each step of the proteome analysis workflow to extract the most detailed proteome information possible from the limited CSF resources available for research purposes. The strategy included applying sequential ultracentrifugation to enrich for extracellular vesicles (EV) in addition to analysis of a small volume of raw CSF, which allowed quantification of 1351 proteins (+55% relative to raw CSF) from 400 μL CSF. When including a spectral library, a total of 2103 proteins (+240%) could be quantified. The workflow was optimized for CSF input volume, tryptic digestion method, gradient length, mass spectrometry data acquisition method and database search strategy to quantify as many proteins a possible. The fully optimized workflow included protein aggregation capture (PAC) digestion, paired with data-independent acquisition (DIA, 21 min gradient) and allowed 2989 unique proteins to be quantified from only 400 μL CSF, which is a 340% increase in proteins compared to analysis of a tryptic digest of raw CSF.

Proteomics and digital subtraction angiography approaches reveal CDH18 as a potential target for therapy of moyamoya disease

Moyamoya disease, characterized by basal cerebral artery obstruction, was studied for differential protein expression to elucidate its pathogenesis. Proteomic analysis of cerebrospinal fluid from 10 patients, categorized by postoperative angiography into good and poor prognosis groups, revealed 46 differentially expressed proteins. Notably, cadherin 18 (CDH18) was the most significantly upregulated in the good prognosis group. In addition, the expression of cadherin 18 (CDH18) and phenotypic transformation-related proteins were measured by qRT-PCR and western blot. The effects of CDH18 in vascular smooth muscle cells were detected by CCK-8, EdU, transwell and wound healing assays. The overexpression of CDH18 in vascular smooth muscle cells (VSMCs) was found to inhibit proliferation, migration, and phenotypic transformation. These findings suggest CDH18 as a potential therapeutic target in moyamoya disease.

Molecular signatures of normal pressure hydrocephalus: a large-scale proteomic analysis of cerebrospinal fluid

Given the persistent challenge of differentiating idiopathic Normal Pressure Hydrocephalus (iNPH) from similar clinical entities, we conducted an in-depth proteomic study of cerebrospinal fluid (CSF) in 28 shunt-responsive iNPH patients, 38 Mild Cognitive Impairment (MCI) due to Alzheimer’s disease, and 49 healthy controls. Utilizing the Olink Explore 3072 panel, we identified distinct proteomic profiles in iNPH that highlight significant downregulation of synaptic markers and cell-cell adhesion proteins. Alongside vimentin and inflammatory markers upregulation, these results suggest ependymal layer and transependymal flow dysfunction. Moreover, downregulation of multiple proteins associated with congenital hydrocephalus (e.g., L1CAM, PCDH9, ISLR2, ADAMTSL2, and B4GAT1) points to a possible shared molecular foundation between congenital hydrocephalus and iNPH. Through orthogonal partial least squares discriminant analysis (OPLS-DA), a panel comprising 13 proteins has been identified as potential diagnostic biomarkers of iNPH, pending external validation. These findings offer novel insights into the pathophysiology of iNPH, with implications for improved diagnosis.

Cerebrospinal Fluid Proteomics Identifies Potential Biomarkers for Early-Onset Alzheimer’s Disease

Background: Early-onset Alzheimer’s disease (EOAD) exhibits a notable degree of heterogeneity as compared to late-onset Alzheimer’s disease (LOAD). The proteins and pathways contributing to the pathophysiology of EOAD still need to be completed and elucidated. Objective: Using correlation network analysis and machine learning to analyze cerebrospinal fluid (CSF) proteomics data to identify potential biomarkers and pathways associated with EOAD. Methods: We employed mass spectrometry to conduct CSF proteomic analysis using the data-independent acquisition method in a Chinese cohort of 139 CSF samples, including 40 individuals with normal cognition (CN), 61 patients with EOAD, and 38 patients with LOAD. Correlation network analysis of differentially expressed proteins was performed to identify EOAD-associated pathways. Machine learning assisted in identifying crucial proteins differentiating EOAD. We validated the results in an Western cohort and examined the proteins expression by enzyme-linked immunosorbent assay (ELISA) in additional 9 EOAD, 9 LOAD, and 9 CN samples from our cohort. Results: We quantified 2,168 CSF proteins. Following adjustment for age and sex, EOAD exhibited a significantly greater number of differentially expressed proteins than LOAD compared to CN. Additionally, our data indicates that EOAD may exhibit more pronounced synaptic dysfunction than LOAD. Three potential biomarkers for EOAD were identified: SH3BGRL3, LRP8, and LY6 H, of which SH3BGRL3 also accurately classified EOAD in the Western cohort. LY6 H reduction was confirmed via ELISA, which was consistent with our proteomic results Conclusions: This study provides a comprehensive profile of the CSF proteome in EOAD and identifies three potential EOAD biomarker proteins.

A proteogenomic view of Parkinson’s disease causality and heterogeneity

The pathogenesis and clinical heterogeneity of Parkinson’s disease (PD) have been evaluated from molecular, pathophysiological, and clinical perspectives. High-throughput proteomic analysis of cerebrospinal fluid (CSF) opened new opportunities for scrutinizing this heterogeneity. To date, this is the most comprehensive CSF-based proteomics profiling study in PD with 569 patients (350 idiopathic patients, 65 GBA + mutation carriers and 154 LRRK2 + mutation carriers), 534 controls, and 4135 proteins analyzed. Combining CSF aptamer-based proteomics with genetics we determined protein quantitative trait loci (pQTLs). Analyses of pQTLs together with summary statistics from the largest PD genome wide association study (GWAS) identified 68 potential causal proteins by Mendelian randomization. The top causal protein, GPNMB, was previously reported to be upregulated in the substantia nigra of PD patients. We also compared the CSF proteomes of patients and controls. Proteome differences between GBA + patients and unaffected GBA + controls suggest degeneration of dopaminergic neurons, altered dopamine metabolism and increased brain inflammation. In the LRRK2 + subcohort we found dysregulated lysosomal degradation, altered alpha-synuclein processing, and neurotransmission. Proteome differences between idiopathic patients and controls suggest increased neuroinflammation, mitochondrial dysfunction/oxidative stress, altered iron metabolism and potential neuroprotection mediated by vasoactive substances. Finally, we used proteomic data to stratify idiopathic patients into “endotypes”. The identified endotypes show differences in cognitive and motor disease progression based on previously reported protein-based risk scores.Our findings not only contribute to the identification of new therapeutic targets but also to shape personalized medicine in CNS neurodegeneration.

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. SignificanceCerebral 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.

Quantitative proteomic analysis of cerebrospinal fluid from patients with idiopathic facial nerve palsy.

Idiopathic facial palsy (IFP) accounts for over 60% of peripheral facial palsy (FP) cases. The cause of IFP remains to be determined. Possible etiologies are nerve swelling due to inflammation and/or viral infection. In this study, we applied an integrative mass spectrometry approach to identify possibly altered protein patterns in the cerebrospinal fluid (CSF) of IFP patients. We obtained CSF samples from 34 patients with FP. In four patients, varicella-zoster virus was the cause (VZV-FP). Among the 30 patients diagnosed with IFP, 17 had normal CSF parameters, five had slightly elevated CSF cell counts and normal or elevated CSF protein, and eight had normal CSF cell counts but elevated CSF protein. Five patients with primary headache served as controls. All samples were tested for viral pathogens by PCR and subjected to liquid chromatography tandem mass spectrometry and bioinformatics analysis and multiplex cytokine/chemokine arrays. All CSF samples, except those from VZV-FP patients, were negative for all tested pathogens. The protein composition of CSF samples from IFP patients with normal CSF was comparable to controls. IFP patients with elevated CSF protein showed dysregulated proteins involved in inflammatory pathways, findings which were similar to those in VZV-FP patients. Multiplex analysis revealed similarly elevated cytokine levels in the CSF of IFP patients with elevated CSF protein and VZV-FP. Our study revealed a subgroup of IFP patients with elevated CSF protein that showed upregulated inflammatory pathways, suggesting an inflammatory/infectious cause. However, no evidence for an inflammatory cause was found in IFP patients with normal CSF.

Characterization of the minimal residual disease state reveals distinct evolutionary trajectories of human glioblastoma.

Recurrence of solid tumors renders patients vulnerable to advanced, treatment-refractory disease state with mutational and oncogenic landscape distinctive from initial diagnosis. Improving outcomes for recurrent cancers requires a better understanding of cell populations that expand from the post-therapy, minimal residual disease (MRD) state. We profile barcoded tumor stem cell populations through therapy at tumor initiation, MRD, and recurrence in our therapy-adapted, patient-derived xenograft models of glioblastoma (GBM). Tumors show distinct patterns of recurrence in which clonal populations exhibit either a pre-existing fitness advantage or an equipotency fitness acquired through therapy. Characterization of the MRD state by single-cell and bulk RNA sequencing reveals a tumor-intrinsic immunomodulatory signature with prognostic significance at the transcriptomic level and in proteomic analysis of cerebrospinal fluid (CSF) collected from patients with GBM. Our results provide insight into the innate and therapy-driven dynamics of human GBM and the prognostic value of interrogating the MRD state in solid cancers.

Natural Killer Cells Disrupt Nerve Fibers by Granzyme H in Atheriosclerotic Cerebral Small Vessel Disease.

Natural killer (NK) cells are enriched in the central nervous system in aging-related atheriosclerotic cerebral small vessel disease (aCSVD), but their roles and underlying mechanism remain to be elucidated. To identify potential cytotoxic molecules released by NK cells in aCSVD lesions, proteomic analysis of cerebrospinal fluid (CSF), plasma, and peripheral NK cells from patients with aCSVD were performed. We found that integrin β2 (ITGB2), cathepsin D (CTSD), and granzyme H (GZMH) were highly expressed in NK cells. ITGB2 interacted with intercellular adhesion molecule 1 in vascular endothelial cells. As assessed by immunofluorescence and scanning electron microscopy of the blood-brain barrier model, transwell membranes covered with primary human brain microvascular endothelial cells and astrocytes, we demonstrated that the CTSD-mediated degradation of collagen in the blood-brain barrier depended on the cytotoxicity of NK cells in aCSVD. With the immunostaining in vitro and in vivo, GZMH disruption of demyelinated nerve fibers was reversed by cotreatment with the inhibitor 3,4-DCIC during white matter hyperintensity (WMH) in aCSVD. Our results indicate that NK cells contribute to CTSD-induced damage to the blood-brain barrier and GZMH-induced disruption of nerve fibers during WMH in aCSVD.

Optimized sample preparation and data analysis for TMT proteomic analysis of cerebrospinal fluid applied to the identification of Alzheimer’s disease biomarkers

BackgroundCerebrospinal fluid (CSF) is an important biofluid for biomarkers of neurodegenerative diseases such as Alzheimer’s disease (AD). By employing tandem mass tag (TMT) proteomics, thousands of proteins can be quantified simultaneously in large cohorts, making it a powerful tool for biomarker discovery. However, TMT proteomics in CSF is associated with analytical challenges regarding sample preparation and data processing. In this study we address those challenges ranging from data normalization over sample preparation to sample analysis.MethodUsing liquid chromatography coupled to mass-spectrometry (LC–MS), we analyzed TMT multiplex samples consisting of either identical or individual CSF samples, evaluated quantification accuracy and tested the performance of different data normalization approaches. We examined MS2 and MS3 acquisition strategies regarding accuracy of quantification and performed a comparative evaluation of filter-assisted sample preparation (FASP) and an in-solution protocol. Finally, four normalization approaches (median, quantile, Total Peptide Amount, TAMPOR) were applied to the previously published European Medical Information Framework Alzheimer’s Disease Multimodal Biomarker Discovery (EMIF-AD MBD) dataset.ResultsThe correlation of measured TMT reporter ratios with spiked-in standard peptide amounts was significantly lower for TMT multiplexes composed of individual CSF samples compared with those composed of aliquots of a single CSF pool, demonstrating that the heterogeneous CSF sample composition influences TMT quantitation. Comparison of TMT reporter normalization methods showed that the correlation could be improved by applying median- and quantile-based normalization. The slope was improved by acquiring data in MS3 mode, albeit at the expense of a 29% decrease in the number of identified proteins. FASP and in-solution sample preparation of CSF samples showed a 73% overlap in identified proteins. Finally, using optimized data normalization, we present a list of 64 biomarker candidates (clinical AD vs. controls, p < 0.01) identified in the EMIF-AD cohort.ConclusionWe have evaluated several analytical aspects of TMT proteomics in CSF. The results of our study provide practical guidelines to improve the accuracy of quantification and aid in the design of sample preparation and analytical protocol. The AD biomarker list extracted from the EMIF-AD cohort can provide a valuable basis for future biomarker studies and help elucidate pathogenic mechanisms in AD.

Quantitative proteomic analysis of cerebrospinal fluid reveals CD163, A2M and full-length APP as potential diagnostic biomarkers of paediatric bacterial meningitis.

BackgroundBacterial meningitis (BM) is a life-threatening infectious disease of the central nervous system in infants and children. To date, no diagnostic methods for the early and precise diagnosis of paediatric BM have been developed.MethodsA label-free cerebrospinal fluid (CSF) quantitative proteomic analysis of 8 patients with confirmed or suspected BM, 9 patients with confirmed or suspected viral meningitis (VM) and 6 non-CNS-infected hospital patients was performed via high-resolution LC–MS/MS.ResultsOur CSF proteomic analysis allowed the identification of critical differences between the BM and non-BM groups. Compared to the proteomes of the non-BM groups, the proteome of the paediatric BM group was characterized by upregulation of complement and coagulation cascades, regulation of IGF transport, uptake by IGF-binding proteins and acute inflammatory response, downregulation of developmental growth, and metabolism of carbohydrates. Moreover, the levels of CD163, A2M and full-length APP in CSF showed excellent diagnostic performance for paediatric BM, with AUC values of 0.911 (95% CI: 0.839–0.984), 0.908 (95% CI: 0.816–1.000) and 0.944 (95% CI: 0.86, 1.000), respectively. Among them, A2M and full-length APP are reported here for the first time as potential diagnostic biomarkers of BM. The findings imply that peptidase regulator activity plays an important role in BM and provide potential novel targets for precision medicine in paediatric BM.ConclusionsCD163, A2M and full-length APP are validated as potential diagnostic biomarkers of paediatric BM.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12953-022-00191-5.

TMOD-15. CHARACTERIZATION OF THE MINIMAL RESIDUAL DISEASE STATE REVEALS DISTINCT EVOLUTIONARY TRAJECTORIES OF HUMAN GLIOBLASTOMA

Abstract Recurrence of solid tumors renders patients vulnerable to a distinctly advanced, highly treatment-refractory disease state that has an increased mutational burden and novel oncogenic drivers not detected at initial diagnosis. Improving outcomes for recurrent cancers requires a better understanding of cancer cell populations that expand from the post-therapy, minimal residual disease (MRD) state. We profiled barcoded tumor cell populations through therapy at tumor initiation/engraftment, MRD and recurrence in our therapy-adapted, patient-derived xenograft models of glioblastoma (GBM). Tumors showed distinct patterns of recurrence in which clonal populations exhibited either a priori, pre-existing fitness, or equipotent fitness acquired through therapy. Characterization of the MRD state by single-cell and bulk RNA sequencing revealed a tumor-intrinsic immunomodulatory signature with strong prognostic significance at the transcriptomic level and in proteomic analysis of cerebrospinal fluid (CSF) collected from GBM patients at all stages of disease. Our results provide insight into the innate and therapy-driven dynamics of human glioblastoma, and the prognostic value of the interrogating of the MRD state in solid cancers.

Exploration of the mechanism by which icariin modulates hippocampal neurogenesis in a rat model of depression

Icariin (ICA) has a significant capacity to protect against depression and hippocampal injury, but it cannot effectively cross the blood-brain barrier and accumulate in the brain. Therefore, the mechanism by which ICA protects against hippocampal injury in depression remains unclear. In this study, we performed proteomics analysis of cerebrospinal fluid to investigate the mechanism by which ICA prevents dysfunctional hippocampal neurogenesis in depression. A rat model of depression was established through exposure to chronic unpredictable mild stress for 6 weeks, after which 120 mg/kg ICA was administered subcutaneously every day. The results showed that ICA alleviated depressive symptoms, learning and memory dysfunction, dysfunctional neurogenesis, and neuronal loss in the dentate gyrus of rats with depression. Neural stem cells from rat embryonic hippocampi were cultured in media containing 20% cerebrospinal fluid from each group of rats and then treated with 100 μM corticosterone. The addition of cerebrospinal fluid from rats treated with ICA largely prevented the corticosterone-mediated inhibition of neuronal proliferation and differentiation. Fifty-two differentially expressed proteins regulated by chronic unpredictable mild stress and ICA were identified through proteomics analysis of cerebrospinal fluid. These proteins were mainly involved in the ribosome, PI3K-Akt signaling, and interleukin-17 signaling pathways. Parallel reaction monitoring mass spectrometry showed that Rps4x, Rps12, Rps14, Rps19, Hsp90b1, and Hsp90aa1 were up-regulated by chronic unpredictable mild stress and down-regulated by ICA. In contrast, HtrA1 was down-regulated by chronic unpredictable mild stress and up-regulated by ICA. These findings suggest that ICA can prevent depression and dysfunctional hippocampal neurogenesis through regulating the expression of certain proteins found in the cerebrospinal fluid. The study was approved by the Experimental Animal Ethics Committee of Guangzhou University of Chinese Medicine of China in March 2017.

Pilot proteomic analysis of cerebrospinal fluid in Alzheimer's disease.

Proteomic analysis of cerebrospinal fluid (CSF) holds great promise in understanding the progression of neurodegenerative diseases, including Alzheimer's disease (AD). As one of the primary reservoirs of neuronal biomolecules, CSF provides a window into the biochemical and cellular aspects of the neurological environment. CSF can be drawn from living participants allowing the potential alignment of clinical changes with these biochemical markers. Using cutting-edge mass spectrometry technologies, we perform a streamlined proteomic analysis of CSF. We quantify greater than 700 proteins across 10 pairs of age- and sex-matched participants in approximately one hour of analysis time each. Using the paired participant study structure, we identify a small group of biologically relevant proteins that show substantial changes in abundance between cognitive normal and AD participants, which were then analyzed at the peptide level using parallel reaction monitoring experiments. Our findings suggest the utility of fractionating a single sample and using matching to increase proteomic depth in cerebrospinal fluid, as well as the potential power of an expanded study.

Diagnostic biomarkers from proteomic characterization of cerebrospinal fluid in patients with brain malignancies.

Recent technological advances in molecular diagnostics through liquid biopsies hold the promise to repetitively monitor tumor evolution and treatment response of brain malignancies without the need of invasive surgical tissue accrual. Here, we implemented a mass spectrometry-based protein analysis pipeline which identified hundreds of proteins in 251 cerebrospinal fluid (CSF) samples from patients with four types of brain malignancies (glioblastoma, lymphoma, brain metastasis, and leptomeningeal disease [LMD]) and from healthy individuals with a focus on glioblastoma in a retrospective and confirmatory prospective observational study. CSF proteome deregulation via disruption of the blood brain barrier appeared to be largely conserved across brain tumor entities. CSF analysis of glioblastoma patients identified two proteomic clusters that correlated with tumor size and patient survival. By integrating CSF data with proteomic analyses of matching glioblastoma tumor tissue and primary glioblastoma cells, we identified potential CSF biomarkers for glioblastoma, in particular chitinase-3-like protein 1 (CHI3L1) and glial fibrillary acidic protein (GFAP). Key findings were validated in a prospective cohort consisting of 35 glioma patients. Finally, in LMD patients who frequently undergo repeated CSF work-up, we explored our proteomic pipeline as a mean to profile consecutive CSF samples. Therefore, proteomic analysis of CSF in brain malignancies has the potential to reveal biomarkers for diagnosis and therapy monitoring.

Proteomic Analysis of Cerebrospinal Fluid Following Remote Ischemic Preconditioning to Identify Therapeutic Targets for Perioperative Neurocognitive Disorders

Proteomic Analysis of Cerebrospinal Fluid Following Remote Ischemic Preconditioning to Identify Therapeutic Targets for Perioperative Neurocognitive Disorders

Quantitative proteomic analysis of cerebrospinal fluid of women newly diagnosed with multiple sclerosis

Purpose The lack of reliable diagnostic and/or prognostic biomarkers for multiple sclerosis (MS) is the major obstacle to timely and accurate patient diagnosis in MS patients. To identify new proteins associated with MS we performed a detailed proteomic analysis of cerebrospinal fluid (CSF) of patients newly diagnosed with relapsing-remitting MS (RRMS) and healthy controls. Material Reflecting significantly higher prevalence of MS in women we included only women patients and controls in the study. To eliminate a potential effect of therapy on the CSF composition, only the therapy-naïve patients were included. Methods Pooled CSF samples were processed in a technical duplicate, and labeled with stable-isotope coded TMT tags. To maximize the proteome coverage, peptide fractionation using 2D-LC preceded mass analysis using Orbitrap Fusion Tribrid Mass Spectrometer. Differential concentration of selected identified proteins between patients and controls was verified using specific antibodies. Results Of the identified 900 CSF proteins, we found 69 proteins to be differentially abundant between patients and controls. In addition to several proteins identified as differentially abundant in MS patients previously, we observed several linked to MS for the first time, namely eosinophil-derived neurotoxin and Nogo receptor. Conclusions Our data confirm differential abundance of several previously proposed protein markers, and provide indirect support for involvement of copper–iron disbalance in MS. Most importantly, we identified two new differentially abundant CSF proteins that seem to be directly connected with myelin loss and axonal damage via TLR2 signaling and Nogo-receptor pathway in women newly diagnosed with RRMS.

Proteomic Analysis of Cerebrospinal Fluid in Children with Acute Enterovirus-Associated Meningoencephalitis Identifies Dysregulated Host Processes and Potential Biomarkers.

Enteroviruses (EVs) are major causes of viral meningoencephalitis in children. To better understand the pathogenesis and identify potential biomarkers, cerebrospinal fluid proteome in children (n = 52) suffering from EV meningoencephalitis was compared to that in EV-negative control subjects (n = 53) using the BoxCar acquisition technique. Among 1697 proteins identified, 1193 with robust assay readouts were used for quantitative analyses. Differential expression analyses identified 154 upregulated and 227 downregulated proteins in the EV-positive group. Functional analyses showed that the upregulated proteins are mainly related to activities of lymphocytes and cytokines, inflammation, and responses to stress and viral invasion, while the downregulated proteins are mainly related to neuronal integrity and activity as well as neurogenesis. According to receiver operating characteristic analysis results, Rho-GDP-dissociation inhibitor 2 exhibited the highest sensitivity (96.2%) and specificity (100%) for discriminating EV-positive from EV-negative patients. The chemokine CXCL10 was most upregulated (>300-fold) with also high sensitivity (92.3%) and specificity (94.3%) for indicating EV positivity. Thus, this study uncovered perturbations of multiple host processes due to EV meningoencephalitis, especially the general trend of enhanced immune responses but impaired neuronal functions. The identified dysregulated proteins may also prompt biomarker development.