Data for a comprehensive map and functional annotation of the human cerebrospinal fluid proteome

To get a better understanding of the ongoing in situ environmental changes preceding the brain tumorigenesis, we assessed cerebrospinal fluid (CSF) proteome profile changes in a glioma rat model in which brain tumor invariably develop after a single in utero exposure to the neurocarcinogen ethylnitrosourea (ENU). Computationally, the CSF proteome profile dynamics during the tumorigenesis can be modeled as non-smooth or even abrupt state changes. Such brain tumor environment transition analysis, correlating the CSF composition changes with the development of early cellular hyperplasia, can reveal the pathogenesis process at network level during a time before the image detection of the tumors. In this controlled rat model study, matched ENU and salineexposed rats' CSF proteomics changes were quantified at approximately 30, 60, 90, 120, 150 days of age (P30, P60, P90, P120, P150). We applied our transition-based network entropy (TNE) method to compute the CSF proteome changes in the ENU rat model and test the hypothesis of the critical transition state prior to impending hyperplasia. Our analysis identified a dynamic driver network (DDN) of CSF proteins related with the emerging tumorigenesis progressing from the non-hyperplasia state. The DDN associated leading network CSF proteins can allow the early detection of such dynamics before the catastrophic shift to the clear clinical landmarks in gliomas. An improved understanding of the critical transition state (P60) during the brain tumor progression can provide the scientific groundwork to device novel therapeutics preventing tumor formation.

In this study, the human cerebrospinal fluid (CSF) proteome was mapped using three different strategies prior to Orbitrap LC-MS/MS analysis: SDS-PAGE and mixed mode reversed phase-anion exchange for mapping the global CSF proteome, and hydrazide-based glycopeptide capture for mapping glycopeptides. A maximal protein set of 3081 proteins (28,811 peptide sequences) was identified, of which 520 were identified as glycoproteins from the glycopeptide enrichment strategy, including 1121 glycopeptides and their glycosylation sites. To our knowledge, this is the largest number of identified proteins and glycopeptides reported for CSF, including 417 glycosylation sites not previously reported. From parallel plasma samples, we identified 1050 proteins (9739 peptide sequences). An overlap of 877 proteins was found between the two body fluids, whereas 2204 proteins were identified only in CSF and 173 only in plasma. All mapping results are freely available via the new CSF Proteome Resource (http://probe.uib.no/csf-pr), which can be used to navigate the CSF proteome and help guide the selection of signature peptides in targeted quantitative proteomics.

The human CSF pain proteome

The purpose of this mini-review is to examine if publicly available cerebrospinal fluid (CSF) proteomics data sets can be exploited to provide insight into the etiology of hydrocephalus, into the character of the injury inflicted on the parenchyma by ventriculomegaly, and into the response of the brain to this condition. While this undertaking was instigated by reanalysis of recent comparative proteomics of CSF collected from the brain of healthy and Mpdz knockout (KO) mice (Yang et al. 2019), it is an opportunity to survey previously published CSF proteomics data sets to determine if they can be pooled together to that end. The overabundance of extracellular matrix (ECM) proteins, complement factors, and apolipoproteins in the CSF of Mpdz KO mice was taken to indicate that the hydrocephalic brain underwent ischemia, inflammation, and demyelination. The overabundance of five cytokine-binding proteins could be linked uniquely to insulin-like growth factor (IGF) secretion and signaling. The overabundance of two serpins, angiotensinogen and pigment epithelium-derived factor (PEDF) was considered as a biomarker of anti-angiogenic negative-feedback mechanisms to reduce CSF production. These findings raise the intriguing propositions that CSF proteomics can identify biomarkers of case-specific injuries, and that IGF signaling and angiogenesis pathways can serve as therapeutic targets. It appears, however, that the currently available proteomics data is not amenable to comparison of CSF from normal and hydrocephalic patients and cannot be used test the premise of those propositions.

INTRODUCTIONBrain steady‐state gamma oscillations evoked using a non‐invasive medical device (Spectris) have shown potential clinical benefits in patients with mild–moderate Alzheimer's disease (AD), including reduced functional and cognitive decline, reduced brain volume and myelin loss, and increased brain functional connectivity. We analyzed changes in cerebrospinal fluid (CSF) proteins after Spectris treatment in mild cognitive impairment (MCI) and their relationship to established biological pathways implicated in AD.METHODSUnbiased proteomic analysis of CSF samples from participants with amyloid‐positive MCI (n = 10) was conducted from the FLICKER (NCT03543878) clinical trial. Participants used the Cognito Therapeutics medical device (Spectris), confirmed to evoke steady‐state gamma oscillations. Participants were instructed to use the device daily for 1 hour each day during the trial. CSF was collected prior to the start of stimulation and after 4 and 8 weeks of treatment. The proteome was analyzed using tandem mass tag mass spectrometry.RESULTSDifferential expression analysis of proteins at baseline and after 8 weeks of treatment (N = 5) revealed that 110 out of 2951 proteins met the significance threshold (analysis of variance, P < 0.05, no false discovery rate). Sixty proteins were upregulated, and 50 proteins were downregulated after treatment. Changes in protein expression were mapped to the consensus human AD protein network, representing co‐expressed and functionally linked modules linked to cell type and biochemical pathways. Treatment altered CSF proteins linked to AD‐related brain proteome modules, including those involved in myelination (proteolipid protein 1, ecotropic viral integration site 2A), synaptic and neuroimmune functions, and regulation of cellular lipid transportation. Biological pathway analysis revealed that most impacted pathways were associated with lipoproteins, cholesterol, phospholipids processing, and phosphatidylcholine biosynthesis.DISCUSSIONThe CSF proteomic changes observed in this study suggest pleiotropic effects on multiple pathways involved in AD, including myelination, synaptic and neuroimmune function, and lipid transport. These findings are also consistent with observations of white matter and myelin preservation after Spectris treatment of AD.HighlightsWe analyzed changes in cerebrospinal fluid (CSF) proteins in response to sensory‐evoked gamma oscillations in individuals with mild cognitive impairment.Sensory evoked steady‐state gamma oscillations were evoked by Spectris medical device.Changes in CSF proteins were observed after 8 weeks of daily 1 hour treatment.Affected proteins were related to myelination, synaptic and neuroimmune functions, and regulation of cellular lipid transportation.Proteomic changes support clinical outcomes and myelin preservation of Spectris treatment.

Quantitative proteomic analysis of age-related changes in human cerebrospinal fluid

Cerebrospinal fluid (CSF) is the only body fluid in direct contact with the brain and thus is a potential source of biomarkers. Furthermore, CSF serves as a medium of endocrine signaling and contains a multitude of regulatory peptides. A combined study of the peptidome and proteome of CSF or any other body fluid has not been reported previously. We report confident identification in CSF of 563 peptide products derived from 91 precursor proteins as well as a high confidence CSF proteome of 798 proteins. For the CSF peptidome, we use high accuracy mass spectrometry (MS) for MS and MS/MS modes, allowing unambiguous identification of neuropeptides. Combination of the peptidome and proteome data suggests that enzymatic processing of membrane proteins causes release of their extracellular parts into CSF. The CSF proteome has only partial overlap with the plasma proteome, thus it is produced locally rather than deriving from plasma. Our work offers insights into CSF composition and origin.

BackgroundThe exact mechanism underlying amyloid‐related imaging abnormalities (ARIA) is unknown. Several factors explain ARIA risk, including the presence of microbleeds, APOE4 carriership, and very low Aβ42 levels. The cerebrospinal fluid (CSF) proteome reflects ongoing mechanisms and, thereby, provides an accessible fluid to refine risk of ARIA development. In this explorative study, we aimed to determine how the CSF proteome relates to the ARIA risk profile and identify potential biomarkers for ARIA risk.MethodWe included AD dementia patients who were Aβ42/tTau ratio positive (n=156; median age: 67 IQR:60‐72, 38% F, median MMSE‐score: 19.8 IQR:17‐24). We dichotomized all risk factors: microbleeds were divided in 0 (M‐, n=123) or &gt;0 (M+, n=33), APOE4 status was divided in carriers (APOE4+, n=96) and non‐carriers (APOE4‐, n=60), CSF Aβ42 levels were separated based on the median (Low and High). We also defined a high and low risk profile: patients with M+APOE4+AL (n=13) and M‐APOE4‐AH (n=23). CSF proteomics were performed using antibody‐based proteomics (Olink), and we selected 288 proteins previously shown to be related to AD (del Campo et al., 2022). With linear regression analysis (with age and sex corrections), we compared protein levels per risk group.ResultWe identified 20 proteins that were differentially expressed in M+ versus M‐, 7 proteins in APOE4+ versus APOE4‐, 3 proteins in Aβ42L versus Aβ42H, and 49 proteins in M+APOE4+AL to M‐APOE4‐AH. The top proteins include EGFR, CRTAC1, AXL, CNTN1, and TIMP4. Overall, almost all proteins were downregulated in the ARIA risk group and most proteins were not overlapping between risk groups.ConclusionThese results show that there are differences based on the ARIA risk profile. The differentiating proteins could provide extra information on the ongoing biological processes that increase ARIA risk and in the future aid to refine ARIA risk. Potentially, these results could aid in the development of a new biomarker for ARIA risk. Future analysis focus on further understanding the proteins involved and validating the findings.

Sex and age are major risk factors for chronic diseases. Recent studies examining age-related molecular changes in plasma provided insights into age-related disease biology. Cerebrospinal fluid (CSF) proteomics can provide additional insights into brain aging and neurodegeneration. By comprehensively examining 7,006 aptamers targeting 6,139 proteins in CSF obtained from 660 healthy individuals aged from 43 to 91 years old, we subsequently identified significant sex and aging effects on 5,097 aptamers in CSF. Many of these effects on CSF proteins had different magnitude or even opposite direction as those on plasma proteins, indicating distinctive CSF-specific signatures. Network analysis of these CSF proteins revealed not only modules associated with healthy aging but also modules showing sex differences. Through subsequent analyses, several modules were highlighted for their proteins implicated in specific diseases. Module 2 and 6 were enriched for many aging diseases including those in the circulatory systems, immune mechanisms, and neurodegeneration. Together, our findings fill a gap of current aging research and provide mechanistic understanding of proteomic changes in CSF during a healthy lifespan and insights for brain aging and diseases.

BACKGROUND The prognostic significance of cerebrospinal fluid (CSF) glucose and protein levels among patients with leptomeningeal disease (LMD) is unknown. This single-institution retrospective study aims to investigate the association of CSF glucose and protein levels with overall survival (OS) among metastatic breast cancer (MBC) patients with LMD. METHODOLOGY MBC patients diagnosed with LMD between Jan 1st, 2010, and Jan 1st, 2023, were included. Patients without known CSF glucose or protein levels at the time of LMD diagnosis were excluded. OS was evaluated using the Kaplan-Meier method and compared using the log-rank test. For multivariate analysis, a step-wise model selection was performed after the inclusion of sub-type of interest, and variables meeting entry (p&amp;lt;0.10) and staying criteria (p&amp;lt;0.05). Median glucose and protein levels were compared using the Wilcoxon rank-sum test. RESULTS 28 patients met inclusion criteria. Positive CSF cytology samples (CSF+) had significantly lower glucose levels vs CSF cytology negative samples (CSF-) [median (IQR) 40 (18-58) vs. 64 (53-92) mg/dl, p=0.006]. Prior study from this data set had shown that the CSF- group was associated with better OS vs the CSF+ group. Hence, four groups were created based on the CSF (+/-) and glucose (Low vs High/Normal). Median OS (months), 95% confidence Interval (CI) for CSF+/Glucose_Low, CSF+/Glucose_Normal/High, CSF-/Glucose_Low and CSF-/Glucose_High/Normal were 3.4(0.23-NE), 16.5(2.9-NE), 3.1(1.28-NE), 51.5(4.9-NE), p=0.03. Glucose_Low overall was associated with shorter OS in multivariate analysis [hazard ratio (HR), 95%CI 4.64 (1.71, 13.2)]. Median CSF protein was not different between CSF+/– groups. Median OS (months), 95%CI for Protein_High and Protein_Low /Normal groups were 28.5 (2.9, 51.5) vs. 6.5 (0.85, 8.0), p=0.36. In multivariate analysis, CSF protein level was not associated with OS. CONCLUSION The association between low CSF glucose level and worse survival among patients with MBC LMD was observed.

We have developed a new procedure, including three affinity chromatography steps, micro-reversed phase high pressure liquid chromatography (mR-HPLC) and Western blotting/mass spectrometric analysis to study central nervous system (CNS) specific proteins in human cerebro spinal fluid (CSF) in order to find biochemical markers for neuronal and synaptic function and pathology in degenerative brain disorders. After the three affinity chromatography steps, intended to remove interfering serum proteins from CSF, mR-HPLC revealed four major peaks, which by both Western blotting and mass spectrometric analyses were found to correspond to beta 2-microglobulin, cystatin C, transthyretin (TTR) and asialotransferrin. When comparing these peaks in CSF from Alzheimer's disease (AD) patients and age-matched healthy controls, a reduction of the brain-specific TTR was found. Therefore we quantified TTR in CSF and serum samples from 8 patients with early onset AD (EAD), 18 patients with late onset AD (LAD), 8 patients with vascular dementia (VAD) and 18 healthy individuals using a nephelometric method. CSF-TTR was divided into barrier-dependent and barrier-independent TTR. The barrier-independent i.e. brain-specific TTR was significantly reduced in the EAD group compared to the controls. Transthyretin has been found to be present in the senile plaques in AD, and to specifically bind to beta/A4 protein, the major component of the amyloid deposits in AD. Therefore, the reduction of the transthyretin-isoform in CSF in AD may reflect an absorption of transthyretin to the amyloid deposits in the senile plaques.

Cerebrospinal fluid (CSF) is a body fluid of choice for biomarker studies of brain disorders but remains relatively under-studied compared with other biological fluids such as plasma, partly due to the more invasive means of its sample collection. The present study establishes an in-depth CSF proteome through the analysis of a unique CSF sample from a pool of donors. After immunoaffinity depletion, the CSF sample was fractionated using off-gel electrophoresis and analyzed with liquid chromatography tandem mass spectrometry (MS) using the latest generation of hybrid Orbitrap mass spectrometers. The shotgun proteomic analysis allowed the identification of 20 689 peptides mapping on 3379 proteins. To the best of our knowledge, the obtained data set constitutes the largest CSF proteome published so far. Among the CSF proteins identified, 34% correspond to genes whose transcripts are highly expressed in brain according to the Human Protein Atlas. The principal Alzheimer's disease biomarkers (e.g., tau protein, amyloid-β, apolipoprotein E, and neurogranin) were detected. Importantly, our data set significantly contributes to the Chromosome-centric Human Proteome Project (C-HPP), and 12 proteins considered as missing are proposed for validation in accordance with the HPP guidelines. Of these 12 proteins, 8 proteins are based on 2 to 6 uniquely mapping peptides from this CSF analysis, and 4 match a new peptide with a "stranded" single peptide in PeptideAtlas from previous CSF studies. The MS proteomic data are available to the ProteomeXchange Consortium ( http://www.proteomexchange.org/ ) with the data set identifier PXD009646.

Summary An enzyme-linked immunosorbent assay (ELISA) was calibrated and used for quantitation of the folate binding protein in human cerebrospinal fluid. The precision of the assay in terms of the coefficient of variation was 6.3% intra-assay (10 replicate single determinations) and 4.8% inter-assay (8 duplicate determinations). The concentration of folate binding protein in cerebrospinal fluid specimens from 20 patients with no complaints or diseases of neurological type was 0.14-0.38, 0.24 nmol FBP/I (range and median value). The gelfiltration profiles of radioligand bound and immunoreactive folate binding protein were identical, both consisting of one major peak (M, '" 25000) and one minor peak (M, '" 1 00000).

Medulloblastoma (MB) is the most common pediatric malignant central nervous system tumor. Overall survival in MB depends on treatment tuning. There is aneed for biomarkers of residual disease and recurrence. We analyzed the proteome of waste cerebrospinal fluid (CSF) from extraventricular drainage (EVD) from six children bearing various subtypes of MB and six controls needing EVD insertion for unrelated causes. Samples included total CSF, microvesicles, exosomes, and proteins captured by combinatorial peptide ligand library (CPLL). Liquid chromatography-coupled tandem mass spectrometry proteomics identified 3560 proteins in CSF from control and MB patients, 2412 (67.7%) of which were overlapping, and 346 (9.7%) and 805 (22.6%) were exclusive. Multidimensional scaling analysis discriminated samples. The weighted gene co-expression network analysis (WGCNA) identified those modules functionally associated with the samples. A ranked core of 192 proteins allowed distinguishing between control and MB samples. Machine learning highlighted long-chain fatty acid transport protein 4 (SLC27A4) and laminin B-type (LMNB1) as proteins that maximized the discrimination between control and MB samples. Machine learning WGCNA and support vector machine learning were able to distinguish between MB versus non-tumor/hemorrhagic controls. The two potential protein biomarkers for the discrimination between control and MB may guide therapy and predict recurrences, improving the MB patients’ quality of life.

Mining ventricular cerebrospinal fluid from patients with traumatic brain injury using hexapeptide ligand libraries to search for trauma biomarkers