CSF-PR 2.0: An Interactive Literature Guide to Quantitative Cerebrospinal Fluid Mass Spectrometry Data from Neurodegenerative Disorders

Cerebrospinal Fluid Proteome Map Reveals Molecular Signatures of Reversible Cerebral Vasoconstriction Syndrome

Reversible cerebral vasoconstriction syndrome (RCVS) is a complex neurovascular disorder characterized by repetitive thunderclap headaches and reversible cerebral vasoconstriction. The pathophysiological mechanism of this mysterious syndrome remains underexplored and there is no clinically available molecular biomarker. To provide insight into the pathogenesis of RCVS, this study reported the first landscape of dysregulated proteome of cerebrospinal fluid (CSF) in patients with RCVS (n  =  21) compared to the age- and sex-matched controls (n  =  20) using data-independent acquisition mass spectrometry. Protein-protein interaction and functional enrichment analysis were employed to construct functional protein networks using the RCVS proteome. An RCVS-CSF proteome library resource of 1054 proteins was established, which illuminated large groups of upregulated proteins enriched in the brain and blood-brain barrier (BBB). Personalized RCVS-CSF proteomic profiles from 17 RCVS patients and 20 controls reveal proteomic changes involving the complement system, adhesion molecules, and extracellular matrix, which may contribute to the disruption of BBB and dysregulation of neurovascular units. Moreover, an additional validation cohort validated a panel of biomarker candidates and a two-protein signature predicted by machine learning model to discriminate RCVS patients from controls with an area under the curve of 0.997. This study reveals the first RCVS proteome and a potential pathogenetic mechanism of BBB and neurovascular unit dysfunction. It also nominates potential biomarker candidates that are mechanistically plausible for RCVS, which may offer potential diagnostic and therapeutic opportunities beyond the clinical manifestations.

Central nervous system-derived extracellular vesicles: the next generation of neural circulating biomarkers?

The central nervous system (CNS) is integrated by glial and neuronal cells, and both release extracellular vesicles (EVs) that participate in CNS homeostasis. EVs could be one of the best candidates to operate as nanosized biological platforms for analysing multidimensional bioactive cargos, which are protected during systemic circulation of EVs. Having a window into the molecular level processes that are happening in the CNS could open a new avenue in CNS research. This raises a particular point of interest: can CNS-derived EVs in blood serve as circulating biomarkers that reflect the pathological status of neurological diseases? L1 cell adhesion molecule (L1CAM) is a widely reported biomarker to identify CNS-derived EVs in peripheral blood. However, it has been demonstrated that L1CAM is also expressed outside the CNS. Given that principal data related to neurodegenerative diseases, such as multiple sclerosis, amyotrophic lateral sclerosis, Parkinson's disease and Alzheimer's disease were obtained using L1CAM-positive EVs, efforts to overcome present challenges related to its specificity are required. In this sense, other surface biomarkers for CNS-derived EVs, such as glutamate aspartate transporter (GLAST) and myelin oligodendrocyte glycoprotein (MOG), among others, have started to be used. Establishing a panel of EV biomarkers to analyse CNS-derived EVs in blood could increase the specificity and sensitivity necessary for these types of studies. This review covers the main evidence related to CNS-derived EVs in cerebrospinal fluid and blood samples of patients with neurological diseases, focusing on the reported biomarkers and the technical possibilities for their isolation. EVs are emerging as a mirror of brain physiopathology, reflecting both localized and systemic changes. Therefore, when the technical hindrances for EV research and clinical applications are overcome, novel disease-specific panels of EV biomarkers would be discovered to facilitate transformation from traditional medicine to personalized medicine.

Natalizumab promotes anti-inflammatory and repair effects in multiple sclerosis

BACKGROUND

Multiple sclerosis is an inflammatory and degenerative disease of the central nervous system leading to demyelination and axonal loss. Relapsing-remitting multiple sclerosis (RRMS) is commonly treated by anti-inflammatory drugs, where one of the most effective drugs to date is the monoclonal antibody natalizumab.

METHODS

The cerebrospinal fluid (CSF) proteome was analyzed in 56 patients with RRMS before and after natalizumab treatment, using label-free mass spectrometry and a subset of the changed proteins were verified by parallel reaction monitoring in a new cohort of 20 patients, confirming the majority of observed changes.

RESULTS

A total of 287 differentially abundant proteins were detected including (i) the decrease of proteins with roles in immunity, such as immunoglobulin heavy constant mu, chitinase-3-like protein 1 and chitotriosidase, (ii) an increase of proteins involved in metabolism, such as lactate dehydrogenase A and B and malate-dehydrogenase cytoplasmic, and (iii) an increase of proteins associated with the central nervous system, including lactadherin and amyloid precursor protein. Comparison with the CSF-PR database provided evidence that natalizumab counters protein changes commonly observed in RRMS. Furthermore, vitamin-D binding protein and apolipoprotein 1 and 2 were unchanged during treatment with natalizumab, implying that these may be involved in disease activity unaffected by natalizumab.

CONCLUSIONS

Our study revealed that some of the previously suggested biomarkers for MS were affected by the natalizumab treatment while others were not. Proteins not previously suggested as biomarkers were also found affected by the treatment. In sum, the results provide new information on how the natalizumab treatment impacts the CSF proteome of MS patients, and points towards processes affected by the treatment. These findings ought to be explored further to disclose potential novel disease mechanisms and predict treatment responses.

Comparative analysis of hippocampal extracellular space uncovers widely altered peptidome upon epileptic seizure in urethane-anaesthetized rats

BACKGROUND

The brain extracellular fluid (ECF), composed of secreted neurotransmitters, metabolites, peptides, and proteins, may reflect brain processes. Analysis of brain ECF may provide new potential markers for synaptic activity or brain damage and reveal additional information on pathological alterations. Epileptic seizure induction is an acute and harsh intervention in brain functions, and it can activate extra- and intracellular proteases, which implies an altered brain secretome. Thus, we applied a 4-aminopyridine (4-AP) epilepsy model to study the hippocampal ECF peptidome alterations upon treatment in rats.

METHODS

We performed in vivo microdialysis in the hippocampus for 3-3 h of control and 4-AP treatment phase in parallel with electrophysiology measurement. Then, we analyzed the microdialysate peptidome of control and treated samples from the same subject by liquid chromatography-coupled tandem mass spectrometry. We analyzed electrophysiological and peptidomic alterations upon epileptic seizure induction by two-tailed, paired t-test.

RESULTS

We detected 2540 peptides in microdialysate samples by mass spectrometry analysis; and 866 peptides-derived from 229 proteins-were found in more than half of the samples. In addition, the abundance of 322 peptides significantly altered upon epileptic seizure induction. Several proteins of significantly altered peptides are neuropeptides (Chgb) or have synapse- or brain-related functions such as the regulation of synaptic vesicle cycle (Atp6v1a, Napa), astrocyte morphology (Vim), and glutamate homeostasis (Slc3a2).

CONCLUSIONS

We have detected several consequences of epileptic seizures at the peptidomic level, as altered peptide abundances of proteins that regulate epilepsy-related cellular processes. Thus, our results indicate that analyzing brain ECF by in vivo microdialysis and omics techniques is useful for monitoring brain processes, and it can be an alternative method in the discovery and analysis of CNS disease markers besides peripheral fluid analysis.

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.

Utilizing databases for astrocyte secretome research

INTRODUCTION

Astrocytes are the most abundant cell type in the central nervous system (CNS). They play a pivotal role in supporting neuronal function and maintaining homeostasis by releasing a variety of bioactive proteins, collectively known as the astrocyte secretome. Investigating secretome provides insights into the molecular mechanisms underlying astrocyte function and dysfunction, as well as novel strategies to prevent and treat diseases affecting the CNS.

AREAS COVERED

Proteomics databases are a valuable resource for studying the role of astrocytes in healthy and diseased brain function, as they provide information about gene expression, protein expression, and cellular function. In this review, we discuss existing databases that are useful for astrocyte secretome research.

EXPERT OPINION

Astrocyte secretomics is a field that is rapidly progressing, yet the availability of dedicated databases is currently limited. To meet the increasing demand for comprehensive omics data in glia research, developing databases specifically focused on astrocyte secretome is crucial. Such databases would allow researchers to investigate the intricate molecular landscape of astrocytes and comprehend their involvement in diverse physiological and pathological processes. Expanding resources through the development of databases dedicated to the astrocyte secretome may facilitate further advancements in this field.

Multi-Omics Interdisciplinary Research Integration to Accelerate Dementia Biomarker Development (MIRIADE)

Proteomics studies have shown differential expression of numerous proteins in dementias but have rarely led to novel biomarker tests for clinical use. The Marie Curie MIRIADE project is designed to experimentally evaluate development strategies to accelerate the validation and ultimate implementation of novel biomarkers in clinical practice, using proteomics-based biomarker development for main dementias as experimental case studies. We address several knowledge gaps that have been identified in the field. First, there is the technology-translation gap of different technologies for the discovery (e.g., mass spectrometry) and the large-scale validation (e.g., immunoassays) of biomarkers. In addition, there is a limited understanding of conformational states of biomarker proteins in different matrices, which affect the selection of reagents for assay development. In this review, we aim to understand the decisions taken in the initial steps of biomarker development, which is done via an interim narrative update of the work of each ESR subproject. The results describe the decision process to shortlist biomarkers from a proteomics to develop immunoassays or mass spectrometry assays for Alzheimer's disease, Lewy body dementia, and frontotemporal dementia. In addition, we explain the approach to prepare the market implementation of novel biomarkers and assays. Moreover, we describe the development of computational protein state and interaction prediction models to support biomarker development, such as the prediction of epitopes. Lastly, we reflect upon activities involved in the biomarker development process to deduce a best-practice roadmap for biomarker development.

Signatures of glial activity can be detected in the CSF proteome

SignificanceSingle-cell transcriptomics has revealed specific glial activation states associated with the pathogenesis of neurodegenerative diseases, such as Alzheimer's and Parkinson's disease (AD and PD). What is still needed are clinically relevant biomarkers for deciphering such glial states in AD and PD patients. To this end, we applied proteome analysis in cerebrospinal fluid (CSF) of mouse models of AD and PD pathology. This allowed us to identify a panel of glial CSF proteins that largely match the transcriptomic changes. The identified proteins can also be quantified in human CSF and show changes in AD patients, supporting their relevance as biomarker candidates to stage glial activation in patients with neurodegenerative diseases.

Proteomics of Human Biological Fluids for Biomarker Discoveries: Technical Advances and Recent Applications

INTRODUCTION

Biological fluids are routine samples for diagnostic testing and monitoring. Blood samples are typically measured because of their moderate collection invasiveness and high information content on health and disease. Several body fluids, such as cerebrospinal fluid (CSF), are also studied and suited to specific pathologies. Over the last two decades proteomics has quested to identify protein biomarkers but with limited success. Recent technologies and refined pipelines have accelerated the profiling of human biological fluids.

AREAS COVERED

We review proteomic technologies for the identification of biomarkers. Those are based on antibodies/aptamers arrays or mass spectrometry (MS), but new ones are emerging. Advances in scalability and throughput have allowed to better design studies and cope with the limited sample size that had until now prevailed due to technological constraints. With these enablers, plasma/serum, CSF, saliva, tears, urine, and milk proteomes have been further profiled; we provide a non-exhaustive picture of some recent highlights (mainly covering literature from last five years in the Scopus database) using MS-based proteomics.

EXPERT OPINION

While proteomics has been in the shadow of genomics for years, proteomic tools and methodologies have reached a certain maturity. They are better suited to discover innovative and robust biofluid biomarkers.

Phosphatidylethanolamine Binding Protein 1 (PEBP1) in Alzheimer's Disease: ELISA Development and Clinical Validation

BACKGROUND

Phosphatidylethanolamine binding protein 1 (PEBP1) is a multifunctional protein, mainly known for its specific binding of phosphatidylethanolamine and the ability to suppress the Raf1-MAPK pathway. Its potential role as an Alzheimer's disease (AD) biomarker has been proposed in several studies. However, evaluation of its discriminative value in clinical cohorts is missing.

OBJECTIVE

We aimed to develop a new immunoassay for the measurement of PEBP1 in cerebrospinal fluid (CSF) and assess the possible role of this protein as AD biomarker.

METHODS

We developed a sandwich enzyme-linked immunosorbent assay (ELISA) for detection of PEBP1 in CSF and performed a technical and a clinical validation on two well-characterized cohorts. The first cohort included 14 mild cognitive impairment due to AD (MCI-AD) and 11 other neurological diseases (OND) patients. The second, larger cohort, included 25 MCI-AD, 29 AD dementia (AD-dem), and 21 OND patients.

RESULTS

PEBP1 is highly sensitive to pre-analytical conditions, especially to prolonged storage at room temperature or 4°C. Analysis of the first cohort showed a trend of an increase of PEBP1 level in MCI-AD patients versus OND subjects. Analysis of the second cohort did not show significant differences among diagnostic groups. Weak, positive correlation was found between CSF PEBP1 and t-tau, p-tau, and Aβ40 in the AD-dem group.

CONCLUSION

A novel ELISA for the detection of PEBP1 in CSF was developed. Further research is needed to assess the potential of PEBP1 in AD diagnostics. The observed dependence of the PEBP1 signal on operating procedures encourages its potential application as CSF quality control.

Advancing mechanistic understanding and biomarker development in amyotrophic lateral sclerosis

INTRODUCTION

Proteomic analysis has contributed significantly to the study of the neurodegenerative disease amyotrophic lateral sclerosis (ALS). It has helped to define the pathological change common to nearly all cases, namely intracellular aggregates of phosphorylated TDP-43, shifting the focus of pathogenesis in ALS toward RNA biology. Proteomics has also uniquely underpinned the delineation of disease mechanisms in model systems and has been central to recent advances in human ALS biomarker development.

AREAS COVERED

The contribution of proteomics to understanding the cellular pathological changes, disease mechanisms, and biomarker development in ALS are covered.

EXPERT OPINION

Proteomics has delivered unique insights into the pathogenesis of ALS and advanced the goal of objective measurements of disease activity to improve therapeutic trials. Further developments in sensitivity and quantification are expected, with application to the presymptomatic phase of human disease offering the hope of prevention strategies.

Deciphering the Interregional and Interhemisphere Proteome of the Human Brain in the Context of the Human Proteome Project

This study, which performs an extensive mass spectrometry-based analysis of 19 brain regions from both left and right hemispheres, presents the first draft of the human brain interhemispheric proteome. This high-resolution proteomics data provides comprehensive coverage of 3300 experimentally measured (nonhypothetical) proteins across multiple regions, allowing the characterization of protein-centric interhemispheric differences and synapse biology, and portrays the regional mapping of specific regions for brain disorder biomarkers. In the context of the Human Proteome Project (HPP), the interhemispheric proteome data reveal specific markers like chimerin 2 (CHN2) in the cerebellar vermis, olfactory marker protein (OMP) in the olfactory bulb, and ankyrin repeat domain 63 (ANKRD63) in basal ganglia, in line with regional brain transcriptomes mapped in the Human Protein Atlas (HPA). In addition, an in silico analysis pipeline was used to predict the structure and function of the uncharacterized uPE1 protein ANKRD63, and parallel reaction monitoring (PRM) was applied to validate its region-specific expression. Finally, we have built the Interhemispheric Brain Proteome Map (IBPM) Portal (www.brainprot.org) to stimulate the scientific community's interest in the brain molecular landscape and accelerate and support research in neuroproteomics. Data are available via ProteomeXchange with identifier PXD019936.

Proteomic Approaches to Study Cysteine Oxidation: Applications in Neurodegenerative Diseases

Oxidative stress appears to be a key feature of many neurodegenerative diseases either as a cause or consequence of disease. A range of molecules are subject to oxidation, but in particular, proteins are an important target and measure of oxidative stress. Proteins are subject to a range of oxidative modifications at reactive cysteine residues, and depending on the level of oxidative stress, these modifications may be reversible or irreversible. A range of experimental approaches has been developed to characterize cysteine oxidation of proteins. In particular, mass spectrometry-based proteomic methods have emerged as a powerful means to identify and quantify cysteine oxidation sites on a proteome scale; however, their application to study neurodegenerative diseases is limited to date. Here we provide a guide to these approaches and highlight the under-exploited utility of these methods to measure oxidative stress in neurodegenerative diseases for biomarker discovery, target engagement and to understand disease mechanisms.

Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

Background

Verification of cerebrospinal fluid (CSF) biomarkers for multiple sclerosis and other neurological diseases is a major challenge due to a large number of candidates, limited sample material availability, disease and biological heterogeneity, and the lack of standardized assays. Furthermore, verification studies are often based on a low number of proteins from a single discovery experiment in medium-sized cohorts, where antibodies and surrogate peptides may differ, thus only providing an indication of proteins affected by the disease and not revealing the bigger picture or concluding on the validity of the markers. We here present a standard approach for locating promising biomarker candidates based on existing knowledge, resulting in high-quality assays covering the main biological processes affected by multiple sclerosis for comparable measurements over time.

Methods

Biomarker candidates were located in CSF-PR (proteomics.uib.no/csf-pr), and further filtered based on estimated concentration in CSF and biological function. Peptide surrogates for internal standards were selected according to relevant criteria, parallel reaction monitoring (PRM) assays created, and extensive assay quality testing performed, i.e. intra- and inter-day variation, trypsin digestion status over time, and whether the peptides were able to separate multiple sclerosis patients and controls.

Results

Assays were developed for 25 proteins, represented by 72 peptides selected according to relevant guidelines and available literature and tested for assay peptide suitability. Stability testing revealed 64 peptides with low intra- and inter-day variations, with 44 also being stably digested after 16 h of trypsin digestion, and 37 furthermore showing a significant difference between multiple sclerosis and controls, thereby confirming literature findings. Calibration curves and the linear area of measurement have, so far, been determined for 17 of these peptides.

Conclusions

We present 37 high-quality PRM assays across 21 CSF-proteins found to be affected by multiple sclerosis, along with a recommended workflow for future development of new assays. The assays can directly be used by others, thus enabling better comparison between studies. Finally, the assays can robustly and stably monitor biological processes in multiple sclerosis patients over time, thus potentially aiding in diagnosis and prognosis, and ultimately in treatment decisions.

The Implementation of Mass Spectrometry-Based Proteomics Workflows in Clinical Routines of Acute Myeloid Leukemia: Applicability and Perspectives

With the current reproducibility of proteome preparation workflows along with the speed and sensitivity of the mass spectrometers, the transition of the mass spectrometry (MS)-based proteomics technology from biomarker discovery to clinical implementation is under appraisal in the biomedicine community. Therefore, this technology might be implemented soon to detect well-known biomarkers in cancers and other diseases. Acute myeloid leukemia (AML) is an aggressive heterogeneous malignancy that requires intensive treatment to cure the patient. Leukemia relapse is still a major challenge even for patients who have favorable genetic abnormalities. MS-based proteomics could be of great help to both describe the proteome changes of individual patients and identify biomarkers that might encourage specific treatments or clinical strategies. Herein, we will review the advances and availability of the MS-based proteomics strategies that could already be used in clinical proteomics. However, the heterogeneity of complex diseases as AML requires consensus to recognize AML biomarkers and to establish MS-based workflows that allow their unbiased identification and quantification. Although our literature review appears promising towards the utilization of MS-based proteomics in clinical AML in a near future, major efforts are required to validate AML biomarkers and agree on clinically approved workflows.

Proteome profiling in cerebrospinal fluid reveals novel biomarkers of Alzheimer's disease

Neurodegenerative diseases are a growing burden, and there is an urgent need for better biomarkers for diagnosis, prognosis, and treatment efficacy. Structural and functional brain alterations are reflected in the protein composition of cerebrospinal fluid (CSF). Alzheimer's disease (AD) patients have higher CSF levels of tau, but we lack knowledge of systems-wide changes of CSF protein levels that accompany AD. Here, we present a highly reproducible mass spectrometry (MS)-based proteomics workflow for the in-depth analysis of CSF from minimal sample amounts. From three independent studies (197 individuals), we characterize differences in proteins by AD status (> 1,000 proteins, CV < 20%). Proteins with previous links to neurodegeneration such as tau, SOD1, and PARK7 differed most strongly by AD status, providing strong positive controls for our approach. CSF proteome changes in Alzheimer's disease prove to be widespread and often correlated with tau concentrations. Our unbiased screen also reveals a consistent glycolytic signature across our cohorts and a recent study. Machine learning suggests clinical utility of this proteomic signature.

Determination of a Tumor-Promoting Microenvironment in Recurrent Medulloblastoma: A Multi-Omics Study of Cerebrospinal Fluid

Molecular classification of medulloblastoma (MB) is well-established and reflects the cell origin and biological properties of tumor cells. However, limited data is available regarding the MB tumor microenvironment. Here, we present a mass spectrometry-based multi-omics pilot study of cerebrospinal fluid (CSF) from recurrent MB patients. A group of age-matched patients without a neoplastic disease was used as control cohort. Proteome profiling identified characteristic tumor markers, including FSTL5, ART3, and FMOD, and revealed a strong prevalence of anti-inflammatory and tumor-promoting proteins characteristic for alternatively polarized myeloid cells in MB samples. The up-regulation of ADAMTS1, GAP43 and GPR37 indicated hypoxic conditions in the CSF of MB patients. This notion was independently supported by metabolomics, demonstrating the up-regulation of tryptophan, methionine, serine and lysine, which have all been described to be induced upon hypoxia in CSF. While cyclooxygenase products were hardly detectable, the epoxygenase product and beta-oxidation promoting lipid hormone 12,13-DiHOME was found to be strongly up-regulated. Taken together, the data suggest a vicious cycle driven by autophagy, the formation of 12,13-DiHOME and increased beta-oxidation, thus promoting a metabolic shift supporting the formation of drug resistance and stem cell properties of MB cells. In conclusion, the different omics-techniques clearly synergized and mutually supported a novel model for a specific pathomechanism.

Bioinformatics to Tackle the Biological Meaning of Human Cerebrospinal Fluid Proteome

Cerebrospinal fluid (CSF) is a source of valuable information concerning brain disorders. The technical advances of high-throughput omics platforms to analyze body fluids can generate a huge amount of data, whose translation to biological meaning is a challenge. Several bioinformatic tools have emerged to help handling this data into systems biology comprehensively. Herein, we describe a step-by-step tutorial for CSF proteome data analysis in the set of neurodegenerative diseases using (1) ClueGO+CluePedia tool to perform cluster-based analysis envisioning the characterization of the biological processes dysregulated in neurodegenerative diseases including Alzheimer's and Parkinson's diseases; (2) Cytoscape to map disease-specific proteins; (3) SecretomeP to inquire the secretion pathway of CSF proteins; and (4) STRING to identify biological processes modulated by secreted CSF proteins based on protein-protein interaction analysis. This step-by-step guide might help researchers to better characterize disease pathogenesis and to identify putative disease biomarkers.

Essential Features and Use Cases of the Cerebrospinal Fluid Proteome Resource (CSF-PR)

Every year, a large number of published studies present biomarkers for various neurological disorders. Many of these studies are based on mass spectrometry proteomics data and describe comparison of the abundance of proteins in cerebrospinal fluid between two or more disease groups. As the number of such studies is growing, it is no longer straightforward to obtain an overview of which specific proteins are increased or decreased between the numerous relevant diseases and their many subcategories, or to see the larger picture or trends between related diseases. To alleviate this situation, we therefore mined the literature for mass spectrometry-based proteomics studies including quantitative protein data from cerebrospinal fluid of patients with multiple sclerosis, Alzheimer's disease, and Parkinson's disease and organized the extracted data in the Cerebrospinal Fluid Proteome Resource (CSF-PR). CSF-PR is freely available online at http://probe.uib.no/csf-pr , is highly interactive, and allows for easy navigation, visualization, and export of the published scientific data. This chapter will guide the user through some of the most important features of the tool and show examples of the suggested use cases.

Development of parallel reaction monitoring assays for cerebrospinal fluid proteins associated with Alzheimer's disease

Detailed knowledge of protein changes in cerebrospinal fluid (CSF) across healthy and diseased individuals would provide a better understanding of the onset and progression of neurodegenerative disorders. In this study, we selected 20 brain-enriched proteins previously identified in CSF by antibody suspension bead arrays (SBA) to be potentially biomarkers for Alzheimer's disease (AD) and verified these using an orthogonal approach. We examined the same set of 94 CSF samples from patients affected by AD (including preclinical and prodromal), mild cognitive impairment (MCI), non-AD dementia and healthy individuals, which had previously been analyzed by SBA. Twenty-eight parallel reaction monitoring (PRM) assays were developed and 13 of them could be validated for protein quantification. Antibody profiles were verified by PRM. For seven proteins, the antibody profiles were highly correlated with the PRM results (r > 0.7) and GAP43, VCAM1 and PSAP were identified as potential markers of preclinical AD. In conclusion, we demonstrate the usefulness of targeted mass spectrometry as a tool for the orthogonal verification of antibody profiling data, suggesting that these complementary methods can be successfully applied for comprehensive exploration of CSF protein levels in neurodegenerative disorders.

Deployment of Label-Free Quantitative Olfactory Proteomics to Detect Cerebrospinal Fluid Biomarker Candidates in Synucleinopathies

Nowadays, diagnosis of neurodegenerative disorders is mainly based on neuroimaging and clinical symptoms, although postmortem neuropathological confirmation remains the gold standard diagnostic technique. Therefore, cerebrospinal fluid (CSF) proteome is considered a valuable molecular repository for diagnosing and targeting the neurodegenerative process. It is well known that olfactory dysfunction is among the earliest features of synucleinopathies such as Parkinson's disease (PD). Consequently, we consider that the application of tissue proteomics in primary olfactory structures is an ideal approach to explore early pathophysiological changes, detecting olfactory proteins that might be tested in CSF as potential biomarkers. Data mining of mass spectrometry-generated datasets has revealed that 30% of the olfactory bulb (OB) proteome is also localized in CSF. In this chapter, we describe a method that utilizes label-free quantitative proteomics and computational analysis to characterize human OB proteomes and potential cerebrospinal fluid (CSF) biomarkers associated with neurodegenerative syndromes. For that, we applied peptide fractionation methods, followed by tandem mass spectrometry (nanoLC-MS/MS), in silico analysis, and semi-quantitative orthogonal techniques in OB derived from PD subjects. After obtaining the differential OB proteome across Lewy-type alpha-synucleinopathy (LTS) stages and further validating the method, this workflow was applied to probe changes in NEGR1 (neuronal growth regulator 1) and GNPDA2 (glucosamine-6-phosphate deaminase 2) protein levels in CSF derived from parkinsonian subjects with respect to controls, observing an inverse correlation between both proteins and α-synuclein, the principal component analysis of Lewy pathology.

Characterization of Cerebrospinal Fluid via Data-Independent Acquisition Mass Spectrometry

Cerebrospinal fluid (CSF) is in direct contact with the brain and serves as a valuable specimen to examine diseases of the central nervous system through analyzing its components. These include the analysis of metabolites, cells as well as proteins. For identifying new suitable diagnostic protein biomarkers bottom-up data-dependent acquisition (DDA) mass spectrometry-based approaches are most popular. Drawbacks of this method are stochastic and irreproducible precursor ion selection. Recently, data-independent acquisition (DIA) emerged as an alternative method. It overcomes several limitations of DDA, since it combines the benefits of DDA and targeted methods like selected reaction monitoring (SRM). We established a DIA method for in-depth proteome analysis of CSF. For this, four spectral libraries were generated with samples from native CSF ( n = 5), CSF fractionation (15 in total) and substantia nigra fractionation (54 in total) and applied to three CSF DIA replicates. The DDA and DIA methods for CSF were conducted with the same nanoLC parameters using a 180 min gradient. Compared to a conventional DDA method, our DIA approach increased the number of identified protein groups from 648 identifications in DDA to 1574 in DIA using a comprehensive spectral library generated with DDA measurements from five native CSF and 54 substantia nigra fractions. We also could show that a sample specific spectral library generated from native CSF only increased the identification reproducibility from three DIA replicates to 90% (77% with a DDA method). Moreover, by utilizing a substantia nigra specific spectral library for CSF DIA, over 60 brain-originated proteins could be identified compared to only 11 with DDA. In conclusion, the here presented optimized DIA method substantially outperforms DDA and could develop into a powerful tool for biomarker discovery in CSF. Data are available via ProteomeXchange with the identifiers PXD010698, PXD010708, PXD010690, PXD010705, and PXD009624.

Phosphotyrosine profiling of human cerebrospinal fluid

Background

Cerebrospinal fluid (CSF) is an important source of potential biomarkers that affect the brain. Biomarkers for neurodegenerative disorders are needed to assist in diagnosis, monitoring disease progression and evaluating efficacy of therapies. Recent studies have demonstrated the involvement of tyrosine kinases in neuronal cell death. Thus, neurodegeneration in the brain is related to altered tyrosine phosphorylation of proteins in the brain and identification of abnormally phosphorylated tyrosine peptides in CSF has the potential to ascertain candidate biomarkers for neurodegenerative disorders.

Methods

In this study, we used an antibody-based tyrosine phosphopeptide enrichment method coupled with high resolution Orbitrap Fusion Tribrid Lumos Fourier transform mass spectrometer to catalog tyrosine phosphorylated peptides from cerebrospinal fluid. The subset of identified tyrosine phosphorylated peptides was also validated using parallel reaction monitoring (PRM)-based targeted approach.

Results

To date, there are no published studies on global profiling of phosphotyrosine modifications of CSF proteins. We carried out phosphotyrosine profiling of CSF using an anti-phosphotyrosine antibody-based enrichment and analysis using high resolution Orbitrap Fusion Lumos mass spectrometer. We identified 111 phosphotyrosine peptides mapping to 66 proteins, which included 24 proteins which have not been identified in CSF previously. We then validated a set of 5 tyrosine phosphorylated peptides in an independent set of CSF samples from cognitively normal subjects, using a PRM-based targeted approach.

Conclusions

The findings from this deep phosphotyrosine profiling of CSF samples have the potential to identify novel disease-related phosphotyrosine-containing peptides in CSF.

Electronic supplementary material

The online version of this article (10.1186/s12014-018-9205-1) contains supplementary material, which is available to authorized users.

Deep Dive on the Proteome of Human Cerebrospinal Fluid: A Valuable Data Resource for Biomarker Discovery and Missing Protein Identification

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.

Proteomic Approaches for the Discovery of Biofluid Biomarkers of Neurodegenerative Dementias

Neurodegenerative dementias are highly complex disorders driven by vicious cycles of intersecting pathophysiologies. While most can be definitively diagnosed by the presence of disease-specific pathology in the brain at postmortem examination, clinical disease presentations often involve substantially overlapping cognitive, behavioral, and functional impairment profiles that hamper accurate diagnosis of the specific disease. As global demographics shift towards an aging population in developed countries, clinicians need more sensitive and specific diagnostic tools to appropriately diagnose, monitor, and treat neurodegenerative conditions. This review is intended as an overview of how modern proteomic techniques (liquid chromatography mass spectrometry (LC-MS/MS) and advanced capture-based technologies) may contribute to the discovery and establishment of better biofluid biomarkers for neurodegenerative disease, and the limitations of these techniques. The review highlights some of the more interesting technical innovations and common themes in the field but is not intended to be an exhaustive systematic review of studies to date. Finally, we discuss clear reporting principles that should be integrated into all studies going forward to ensure data is presented in sufficient detail to allow meaningful comparisons across studies.

Orthologous proteins of experimental de- and remyelination are differentially regulated in the CSF proteome of multiple sclerosis subtypes

OBJECTIVE

Here, we applied a multi-omics approach (i) to examine molecular pathways related to de- and remyelination in multiple sclerosis (MS) lesions; and (ii) to translate these findings to the CSF proteome in order to identify molecules that are differentially expressed among MS subtypes.

METHODS

To relate differentially expressed genes in MS lesions to de- and remyelination, we compared transcriptome of MS lesions to transcriptome of cuprizone (CPZ)-induced de- and remyelination. Protein products of the overlapping orthologous genes were measured within the CSF by quantitative proteomics, parallel reaction monitoring (PRM). Differentially regulated proteins were correlated with molecular markers of inflammation by using MesoScale multiplex immunoassay. Expression kinetics of differentially regulated orthologous genes and proteins were examined in the CPZ model.

RESULTS

In the demyelinated and remyelinated corpus callosum, we detected 1239 differentially expressed genes; 91 orthologues were also differentially expressed in MS lesions. Pathway analysis of these orthologues suggested that the TYROBP (DAP12)-TREM2 pathway, TNF-receptor 1, CYBA and the proteasome subunit PSMB9 were related to de- and remyelination. We designed 129 peptides representing 51 orthologous proteins, measured them by PRM in 97 individual CSF, and compared their levels between relapsing (n = 40) and progressive MS (n = 57). Four proteins were differentially regulated among relapsing and progressive MS: tyrosine protein kinase receptor UFO (UFO), TIMP-1, apolipoprotein C-II (APOC2), and beta-2-microglobulin (B2M). The orthologous genes/proteins in the mouse brain peaked during acute remyelination. UFO, TIMP-1 and B2M levels correlated inversely with inflammation in the CSF (IL-6, MCP-1/CCL2, TARC/CCL17). APOC2 showed positive correlation with IL-2, IL-16 and eotaxin-3/CCL26.

CONCLUSIONS

Pathology-based multi-omics identified four CSF markers that were differentially expressed in MS subtypes. Upregulated TIMP-1, UFO and B2M orthologues in relapsing MS were associated with reduced inflammation and reflected reparatory processes, in contrast to the upregulated orthologue APOC2 in progressive MS that reflected changes in lipid metabolism associated with increased inflammation.

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.

Proteomic studies of cerebrospinal fluid biomarkers of Alzheimer's disease: an update

INTRODUCTION

Alzheimer's disease (AD) is a neurodegenerative disease affecting the brain. Today there are three cerebrospinal fluid (CSF) biomarkers, amyloid-β consisting of 42 amino acids (Aβ42), total-tau (t-tau) and phosphorylated-tau (p-tau), which combined have sensitivity and specificity figures around 80%. However, pathological studies have shown that comorbidity is a common feature in AD and that the three currently used CSF biomarkers do not optimally reflect the activity of the disease process. Thus, additional markers are needed. Areas covered: In the present review, we screened PubMed for articles published the last five years (2012-2017) for proteomic studies in CSF with the criteria that AD had to be included as one of the diagnostic groups. Based on inclusion criteria, 28 papers were included reporting in total 224 biomarker-data that were altered in AD compared to control. Both mass spectrometry and multi-panel immunoassays were considered as proteomic studies. Expert commentary: A large number of pilot studies have been reported but so far there is a lack of replicated findings and to date no CSF biomarker discovered in proteomic studies has reached the clinic to aid in the diagnostic work-up of patients with cognitive impairment.