Depletion of highly abundant proteins from human cerebrospinal fluid: a cautionary note

Surrogate Cerebrospinal Fluid Biomarkers for Assessing the Efficacy of Gene Therapy in Hurler Syndrome

Mucopolysaccharidosis type I (MPS I) is caused by a deficiency of the lysosomal hydroxylase alpha-l-iduronidase (IDUA). The resulting accumulation of dermatan and heparan sulfate induces intellectual disabilities and pre-mature death, and only a few treatment options are available. In a previous study, we demonstrated the feasibility, safety, and efficacy of gene therapy by injecting recombinant adeno-associated viral vector serotype (AAV)2/5-IDUA into the brain of a canine model of MPS I. We report on a quantitative proteomic analysis of control dogs and untreated dogs with MPS I cerebrospinal fluid (CSF) that had been collected throughout the study in the MPS I dogs. Mass spectrometry (MS) analysis identified numerous proteins present at altered levels in MPS I CSF samples. Quantitative immunoblotting, performed on CSF from healthy controls, untreated MPS I dogs, and MPS I dogs early treated and late treated by gene therapy, confirmed the MS data for a subset of proteins with higher abundance (neuronal pentraxin 1, chitinase 3-like 1, monocyte differentiation antigen CD14, and insulin-like growth factor-binding protein 2). Scoring of the results shows that the expression levels of these proteins are close to those of the control group for dogs that underwent gene therapy early in life but not for older treated animals. Our results disclose four novel predictive biomarker candidates that might be valuable in monitoring the course of the neurological disease in MPS patients at diagnosis, during clinical follow-up, and after treatment.

Isobaric Labeling Strategy Utilizing 4-Plex N,N-Dimethyl Leucine (DiLeu) Tags Reveals Proteomic Changes Induced by Chemotherapy in Cerebrospinal Fluid of Children with B-Cell Acute Lymphoblastic Leukemia

The use of mass spectrometry for protein identification and quantification in cerebrospinal fluid (CSF) is at the forefront of research efforts to identify and explore biomarkers for the early diagnosis and prognosis of neurologic disorders. Here we implemented a 4-plex N,N-dimethyl leucine (DiLeu) isobaric labeling strategy in a longitudinal study aiming to investigate protein dynamics in children with B-cell acute lymphoblastic leukemia (B-cell ALL) undergoing chemotherapy. The temporal profile of CSF proteome during chemotherapy treatment at weeks 5, 10-14, and 24-28 highlighted many differentially expressed proteins, such as neural cell adhesion molecule, neuronal growth regulator 1, and secretogranin-3, all of which play important roles in neurodegenerative diseases. A total of 63 proteins were significantly altered across all of the time points investigated. The most over-represented biological processes from gene ontology analysis included platelet degranulation, complement activation, cell adhesion, fibrinolysis, neuron projection, regeneration, and regulation of neuron death. We expect that results from this and future studies will provide a means to monitor neurotoxicity and develop strategies to prevent central nervous system injury in response to chemotherapy in children.

Novel CSF biomarkers in genetic frontotemporal dementia identified by proteomics

Objective

To identify novel CSF biomarkers in GRN‐associated frontotemporal dementia (FTD) by proteomics using mass spectrometry (MS).

Methods

Unbiased MS was applied to CSF samples from 19 presymptomatic and 9 symptomatic GRN mutation carriers and 24 noncarriers. Protein abundances were compared between these groups. Proteins were then selected for validation if identified by ≥4 peptides and if fold change was ≤0.5 or ≥2.0. Validation and absolute quantification by parallel reaction monitoring (PRM), a high‐resolution targeted MS method, was performed on an international cohort (n = 210) of presymptomatic and symptomatic GRN, C9orf72 and MAPT mutation carriers.

Results

Unbiased MS revealed 20 differentially abundant proteins between symptomatic mutation carriers and noncarriers and nine between symptomatic and presymptomatic carriers. Seven of these proteins fulfilled our criteria for validation. PRM analyses revealed that symptomatic GRN mutation carriers had significantly lower levels of neuronal pentraxin receptor (NPTXR), receptor‐type tyrosine‐protein phosphatase N2 (PTPRN2), neurosecretory protein VGF, chromogranin‐A (CHGA), and V‐set and transmembrane domain‐containing protein 2B (VSTM2B) than presymptomatic carriers and noncarriers. Symptomatic C9orf72 mutation carriers had lower levels of NPTXR, PTPRN2, CHGA, and VSTM2B than noncarriers, while symptomatic MAPT mutation carriers had lower levels of NPTXR and CHGA than noncarriers.

Interpretation

We identified and validated five novel CSF biomarkers in GRN‐associated FTD. Our results show that synaptic, secretory vesicle, and inflammatory proteins are dysregulated in the symptomatic stage and may provide new insights into the pathophysiology of genetic FTD. Further validation is needed to investigate their clinical applicability as diagnostic or monitoring biomarkers.

Affinity depletion versus relative protein enrichment: a side-by-side comparison of two major strategies for increasing human cerebrospinal fluid proteome coverage

Cerebrospinal fluid (CSF) is in direct contact with the central nervous system. This makes human CSF an attractive source of potential biomarkers for neurologic diseases. Similarly to blood plasma, proteomic analysis of CSF is complicated by a high dynamic range of individual protein concentrations and by the presence of several highly abundant proteins. To deal with the abundant human CSF proteins, methods developed for blood plasma/serum are routinely used. Multiple affinity removal systems and protein enrichment of less abundant proteins using a combinatorial peptide ligand library are among the most frequent approaches. However, their relative impact on CSF proteome coverage has never been evaluated side-by-side in a single study. Therefore, we explored the effect of CSF depletion using MARS 14 cartridge and ProteoMiner ligand library on the number of CSF proteins identified in subsequent LC–MS/MS analysis. LC–MS/MS analysis of crude (non-treated) CSF provided roughly 500 identified proteins. Depletion of CSF by MARS 14 cartridge increased the number of identifications to nearly 800, while treatment of CSF using ProteoMiner enabled identification of 600 proteins. To explore the potential losses of CSF proteins during the depletion process, we also analyzed the “waste” fractions generated by both methods, i.e., proteins retained by the MARS 14 cartridge, and the molecules present in the flow-through fraction from ProteoMiner. More than 250 proteins were bound to MARS 14 cartridge, 100 of those were not identified in the corresponding depleted CSF. Similarly, analysis of the waste fraction in ProteoMiner workflow provided almost 70 unique proteins not found in the CSF depleted by the ligand library. Both depletion strategies significantly increased the number of identified CSF proteins compared to crude CSF. However, MARS 14 depletion provided a markedly higher number of identified proteins (773) compared to ProteoMiner (611). Further, we showed that CSF proteins are lost due to co-depletion (MARS 14) or exclusion (ProteoMiner) during the depletion process. This suggests that the routinely discarded “waste” fractions contain proteins of potential interest and should be included in CSF biomarker studies.

Quantitative Evaluation of Different Protein Fractions of Cerebrospinal Fluid Using 18O Labeling

Molecular analysis of cerebrospinal fluid (CSF) provides comprehensive information on physiological and pathological processes related to the brain. In particular, proteomic studies give insights into the pathogenesis of many brain diseases which still pose diagnostic and therapeutic challenges. The identification of reliable biomarkers is an important step to meet these challenges. Mass spectrometry is an essential proteomic tool, not only for highly sensitive identification of proteins and posttranslational modifications, but also for their reliable quantification. Here, ¹⁸O labeling of tryptic peptides was employed to qualitative and quantitative analyses of protein fractions obtained by depletion of highly abundant proteins from cerebrospinal fluid. It was found that the execution of the investigated depletion protocols may cause the loss of potential protein biomarkers of neurological diseases.

Biomarkers for diseases with TDP-43 pathology

The discovery that aggregated transactive response DNA-binding protein 43 kDa (TDP-43) is the major component of pathological ubiquitinated inclusions in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) caused seminal progress in the unveiling of the genetic bases and molecular characteristics of these now so-called TDP-43 proteinopathies. Substantial increase in the knowledge of clinic-pathological coherencies, especially for FTLD variants, could be made in the last decade, but also revealed a considerable complexity of TDP-43 pathology and often a poor correlation of clinical and molecular disease characteristics. To date, an underlying TDP-43 pathology can be predicted only for patients with mutations in the genes C9orf72 and GRN, but is dependent on neuropathological verification in patients without family history, which represent the majority of cases. As etiology-specific therapies for neurodegenerative proteinopathies are emerging, methods to forecast TDP-43 pathology at patients' lifetime are highly required. Here, we review the current status of research pursued to identify specific indicators to predict or exclude TDP-43 pathology in the ALS-FTLD spectrum disorders and findings on candidates for prognosis and monitoring of disease progression in TDP-43 proteinopathies with a focus on TDP-43 with its pathological forms, neurochemical and imaging biomarkers.

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.

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.

Proteomic studies in the discovery of cerebrospinal fluid biomarkers for amyotrophic lateral sclerosis

INTRODUCTION

Amyotrophic lateral sclerosis (ALS) is a progressive degenerative motor neuron disease, which usually leads to death within a few years. The diagnosis is mainly based on clinical symptoms and there is a need for ALS-specific biomarkers to make an early and precise diagnosis, for development of disease-modifying drugs and to gain new insights into pathophysiology. Areas covered: In the present review, we summarize studies using mass spectrometric (MS) approaches to identify protein alterations in the cerebrospinal fluid (CSF) of ALS patients. In total, we identified 11 studies fulfilling our criteria by searching in the PubMed database using the keywords 'ALS' and 'CSF' combined with 'proteome', 'proteomic', 'mass spectrometry' or 'protein biomarker'. Ten proteins were differently regulated in ALS CSF compared to controls in at least 2 studies. We will discuss the relevance of the identified proteins regarding the frequency of identification, extent of alteration and brain-specificity. Expert commentary: Most of the identified CSF biomarker candidates are irreproducible or mainly blood-derived. We assign the missing success of CSF proteomic studies in biomarker discovery to a lack of sensitivity, unsuitable normalization, low quality assurance and variations originating from sample preparation. These issues must be improved in future proteomic studies in CSF.

Analysis of the Cerebrospinal Fluid Proteome in Alzheimer's Disease

Alzheimer’s disease is a neurodegenerative disorder accounting for more than 50% of cases of dementia. Diagnosis of Alzheimer’s disease relies on cognitive tests and analysis of amyloid beta, protein tau, and hyperphosphorylated tau in cerebrospinal fluid. Although these markers provide relatively high sensitivity and specificity for early disease detection, they are not suitable for monitor of disease progression. In the present study, we used label-free shotgun mass spectrometry to analyse the cerebrospinal fluid proteome of Alzheimer’s disease patients and non-demented controls to identify potential biomarkers for Alzheimer’s disease. We processed the data using five programs (DecyderMS, Maxquant, OpenMS, PEAKS, and Sieve) and compared their results by means of reproducibility and peptide identification, including three different normalization methods. After depletion of high abundant proteins we found that Alzheimer’s disease patients had lower fraction of low-abundance proteins in cerebrospinal fluid compared to healthy controls (p<0.05). Consequently, global normalization was found to be less accurate compared to using spiked-in chicken ovalbumin for normalization. In addition, we determined that Sieve and OpenMS resulted in the highest reproducibility and PEAKS was the programs with the highest identification performance. Finally, we successfully verified significantly lower levels (p<0.05) of eight proteins (A2GL, APOM, C1QB, C1QC, C1S, FBLN3, PTPRZ, and SEZ6) in Alzheimer’s disease compared to controls using an antibody-based detection method. These proteins are involved in different biological roles spanning from cell adhesion and migration, to regulation of the synapse and the immune system.