Development of protein biomarkers in cerebrospinal fluid for secondary progressive multiple sclerosis using selected reaction monitoring mass spectrometry (SRM-MS)

Proteomics and Its Current Application in Biomedical Area: Concise Review

Biomedical researchers tirelessly seek cutting-edge technologies to advance disease diagnosis, drug discovery, and therapeutic interventions, all aimed at enhancing human and animal well-being. Within this realm, proteomics stands out as a pivotal technology, focusing on extensive studies of protein composition, structure, function, and interactions. Proteomics, with its subdivisions of expression, structural, and functional proteomics, plays a crucial role in unraveling the complexities of biological systems. Various sophisticated techniques are employed in proteomics, including polyacrylamide gel electrophoresis, mass spectrometry analysis, NMR spectroscopy, protein microarray, X-ray crystallography, and Edman sequencing. These methods collectively contribute to the comprehensive understanding of proteins and their roles in health and disease. In the biomedical field, proteomics finds widespread application in cancer research and diagnosis, stem cell studies, and the diagnosis and research of both infectious and noninfectious diseases. In addition, it plays a pivotal role in drug discovery and the emerging frontier of personalized medicine. The versatility of proteomics allows researchers to delve into the intricacies of molecular mechanisms, paving the way for innovative therapeutic approaches. As infectious and noninfectious diseases continue to emerge and the field of biomedical research expands, the significance of proteomics becomes increasingly evident. Keeping abreast of the latest developments in proteomics applications becomes paramount for the development of therapeutics, translational research, and study of diverse diseases. This review aims to provide a comprehensive overview of proteomics, offering a concise outline of its current applications in the biomedical domain. By doing so, it seeks to contribute to the understanding and advancement of proteomics, emphasizing its pivotal role in shaping the future of biomedical research and therapeutic interventions.

Metabolomic profiles in relapsing-remitting and progressive multiple sclerosis compared to healthy controls: a five-year follow-up study

INTRODUCTION AND OBJECTIVES

Multiple sclerosis (MS) is a disease of the central nervous system associated with immune dysfunction, demyelination, and neurodegeneration. The disease has heterogeneous clinical phenotypes such as relapsing-remitting MS (RRMS) and progressive multiple sclerosis (PMS), each with unique pathogenesis. Metabolomics research has shown promise in understanding the etiologies of MS disease. However, there is a paucity of clinical studies with follow-up metabolomics analyses. This 5-year follow-up (5YFU) cohort study aimed to investigate the metabolomics alterations over time between different courses of MS patients and healthy controls and provide insights into metabolic and physiological mechanisms of MS disease progression.

METHODS

A cohort containing 108 MS patients (37 PMS and 71 RRMS) and 42 controls were followed up for a median of 5 years. Liquid chromatography-mass spectrometry (LC-MS) was applied for untargeted metabolomics profiling of serum samples of the cohort at both baseline and 5YFU. Univariate analyses with mixed-effect ANCOVA models, clustering, and pathway enrichment analyses were performed to identify patterns of metabolites and pathway changes across the time effects and patient groups.

RESULTS AND CONCLUSIONS

Out of 592 identified metabolites, the PMS group exhibited the most changes, with 219 (37%) metabolites changed over time and 132 (22%) changed within the RRMS group (Bonferroni adjusted P < 0.05). Compared to the baseline, there were more significant metabolite differences detected between PMS and RRMS classes at 5YFU. Pathway enrichment analysis detected seven pathways perturbed significantly during 5YFU in MS groups compared to controls. PMS showed more pathway changes compared to the RRMS group.

Histological and Top-Down Proteomic Analyses of the Visual Pathway in the Cuprizone Demyelination Model

A change in visual perception is a frequent early symptom of multiple sclerosis (MS), the pathoaetiology of which remains unclear. Following a slow demyelination process caused by 12 weeks of low-dose (0.1%) cuprizone (CPZ) consumption, histology and proteomics were used to investigate components of the visual pathway in young adult mice. Histological investigation did not identify demyelination or gliosis in the optic tracts, pretectal nuclei, superior colliculi, lateral geniculate nuclei or visual cortices. However, top-down proteomic assessment of the optic nerve/tract revealed a significant change in the abundance of 34 spots in high-resolution two-dimensional (2D) gels. Subsequent liquid chromatography-tandem mass spectrometry (LC-TMS) analysis identified alterations in 75 proteoforms. Literature mining revealed the relevance of these proteoforms in terms of proteins previously implicated in animal models, eye diseases and human MS. Importantly, 24 proteoforms were not previously described in any animal models of MS, eye diseases or MS itself. Bioinformatic analysis indicated involvement of these proteoforms in cytoskeleton organization, metabolic dysregulation, protein aggregation and axonal support. Collectively, these results indicate that continuous CPZ-feeding, which evokes a slow demyelination, results in proteomic changes that precede any clear histological changes in the visual pathway and that these proteoforms may be potential early markers of degenerative demyelinating conditions.

Posttranslational modifications of proteins are key features in the identification of CSF biomarkers of multiple sclerosis

Background

Multiple sclerosis is an inflammatory and degenerative disease of the central nervous system (CNS) characterized by demyelination and concomitant axonal loss. The lack of a single specific test, and the similarity to other inflammatory diseases of the central nervous system, makes it difficult to have a clear diagnosis of multiple sclerosis. Therefore, laboratory tests that allows a clear and definite diagnosis, as well as to predict the different clinical courses of the disease are of utmost importance. Herein, we compared the cerebrospinal fluid (CSF) proteome of patients with multiple sclerosis (in the relapse–remitting phase of the disease) and other diseases of the CNS (inflammatory and non-inflammatory) aiming at identifying reliable biomarkers of multiple sclerosis.

Methods

CSF samples from the discovery group were resolved by 2D-gel electrophoresis followed by identification of the protein spots by mass spectrometry. The results were analyzed using univariate (Student’s t test) and multivariate (Hierarchical Cluster Analysis, Principal Component Analysis, Linear Discriminant Analysis) statistical and numerical techniques, to identify a set of protein spots that were differentially expressed in CSF samples from patients with multiple sclerosis when compared with other two groups. Validation of the results was performed in samples from a different set of patients using quantitative (e.g., ELISA) and semi-quantitative (e.g., Western Blot) experimental approaches.

Results

Analysis of the 2D-gels showed 13 protein spots that were differentially expressed in the three groups of patients: Alpha-1-antichymotrypsin, Prostaglandin-H2-isomerase, Retinol binding protein 4, Transthyretin (TTR), Apolipoprotein E, Gelsolin, Angiotensinogen, Agrin, Serum albumin, Myosin-15, Apolipoprotein B-100 and EF-hand calcium-binding domain—containing protein. ELISA experiments allowed validating part of the results obtained in the proteomics analysis and showed that some of the alterations in the CSF proteome are also mirrored in serum samples from multiple sclerosis patients. CSF of multiple sclerosis patients was characterized by TTR oligomerization, thus highlighting the importance of analyzing posttranslational modifications of the proteome in the identification of novel biomarkers of the disease.

Conclusions

The model built based on the results obtained upon analysis of the 2D-gels and in the validation phase attained an accuracy of about 80% in distinguishing multiple sclerosis patients and the other two groups.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02404-2.

Proteomics of Multiple Sclerosis: Inherent Issues in Defining the Pathoetiology and Identifying (Early) Biomarkers

Multiple Sclerosis (MS) is a demyelinating disease of the human central nervous system having an unconfirmed pathoetiology. Although animal models are used to mimic the pathology and clinical symptoms, no single model successfully replicates the full complexity of MS from its initial clinical identification through disease progression. Most importantly, a lack of preclinical biomarkers is hampering the earliest possible diagnosis and treatment. Notably, the development of rationally targeted therapeutics enabling pre-emptive treatment to halt the disease is also delayed without such biomarkers. Using literature mining and bioinformatic analyses, this review assessed the available proteomic studies of MS patients and animal models to discern (1) whether the models effectively mimic MS; and (2) whether reasonable biomarker candidates have been identified. The implication and necessity of assessing proteoforms and the critical importance of this to identifying rational biomarkers are discussed. Moreover, the challenges of using different proteomic analytical approaches and biological samples are also addressed.

Mass Cytometry of CSF Identifies an MS-Associated B-cell Population

Objective

To identify an MS-specific immune cell population by deep immune phenotyping and relate it to soluble signaling molecules in CSF.

Methods

We analyzed surface expression of 22 markers in paired blood/CSF samples from 39 patients using mass cytometry (cytometry by time of flight). We also measured the concentrations of 296 signaling molecules in CSF using proximity extension assay. Results were analyzed using highly automated unsupervised algorithmic informatics.

Results

Mass cytometry objectively identified a B-cell population characterized by the expression of CD49d, CD69, CD27, CXCR3, and human leukocyte antigen (HLA)-DR as clearly associated with MS. Concentrations of the B cell–related factors, notably FCRL2, were increased in MS CSF, especially in early stages of the disease. The B-cell trophic factor B cell activating factor (BAFF) was decreased in MS. Proteins involved in neural plasticity were also reduced in MS.

Conclusion

When analyzed without a priori assumptions, both the soluble and the cellular compartments of the CSF in MS were characterized by markers related to B cells, and the strongest candidate for an MS-specific cell type has a B-cell phenotype.

Protein variability in cerebrospinal fluid and its possible implications for neurological protein biomarker research

Cerebrospinal fluid is investigated in biomarker studies for various neurological disorders of the central nervous system due to its proximity to the brain. Currently, only a limited number of biomarkers have been validated in independent studies. The high variability in the protein composition and protein abundance of cerebrospinal fluid between as well as within individuals might be an important reason for this phenomenon. To evaluate this possibility, we investigated the inter- and intraindividual variability in the cerebrospinal fluid proteome globally, with a specific focus on disease biomarkers described in the literature. Cerebrospinal fluid from a longitudinal study group including 12 healthy control subjects was analyzed by label-free quantification (LFQ) via LC-MS/MS. Data were quantified via MaxQuant. Then, the intra- and interindividual variability and the reference change value were calculated for every protein. We identified and quantified 791 proteins, and 216 of these proteins were abundant in all samples and were selected for further analysis. For these proteins, we found an interindividual coefficient of variation of up to 101.5% and an intraindividual coefficient of variation of up to 29.3%. Remarkably, these values were comparably high for both proteins that were published as disease biomarkers and other proteins. Our results support the hypothesis that natural variability greatly impacts cerebrospinal fluid protein biomarkers because high variability can lead to unreliable results. Thus, we suggest controlling the variability of each protein to distinguish between good and bad biomarker candidates, e.g., by utilizing reference change values to improve the process of evaluating potential biomarkers in future studies.

Relapsing-Remitting Multiple Sclerosis diagnosis from cerebrospinal fluids via Fourier transform infrared spectroscopy coupled with multivariate analysis

Multiple sclerosis (MS) is a chronic, progressive, inflammatory and degenerative disease of central nervous system. Here, we aimed to develop a method for differential diagnosis of Relapsing-Remitting MS (RRMS) and clinically isolated syndrome (CIS) patients, as well as to identify CIS patients who will progress to RRMS, from cerebrospinal fluid (CSF) by infrared (IR) spectroscopy and multivariate analysis. Spectral analyses demonstrated significant differences in the molecular contents, especially in the lipids and Z conformation of DNA of CSF from CIS, CIS to RRMS transformed (TCIS) and RRMS groups. These changes enables the discrimination of diseased groups and controls (individuals with no neurological disease) from each other using hierarchical cluster and principal component analysis. Some CIS samples were consistently clustered in RRMS class, which may indicate that these CIS patients potentially will transform to RRMS over time. Z-DNA band at 795 cm⁻¹ that is existent only in diseased groups and significant increase in carbonyl amount, decrease in amideI/amide II and lipid/protein ratios observed only for RRMS groups can be used as diagnostic biomarkers. The results of the present study shed light on the early diagnosis of RRMS by IR spectroscopy complemented with multivariate analysis tools.

Protease-activated receptor-1 activation by granzyme B causes neurotoxicity that is augmented by interleukin-1β

Background

The cause of neurodegeneration in progressive forms of multiple sclerosis is unknown. We investigated the impact of specific neuroinflammatory markers on human neurons to identify potential therapeutic targets for neuroprotection against chronic inflammation.

Methods

Surface immunocytochemistry directly visualized protease-activated receptor-1 (PAR1) and interleukin-1 (IL-1) receptors on neurons in human postmortem cortex in patients with and without neuroinflammatory lesions. Viability of cultured neurons was determined after exposure to cerebrospinal fluid from patients with progressive multiple sclerosis or purified granzyme B and IL-1β. Inhibitors of PAR1 activation and of PAR1-associated second messenger signaling were used to elucidate a mechanism of neurotoxicity.

Results

Immunohistochemistry of human post-mortem brain tissue demonstrated cells expressing higher amounts of PAR1 near and within subcortical lesions in patients with multiple sclerosis compared to control tissue. Human cerebrospinal fluid samples containing granzyme B and IL-1β were toxic to human neuronal cultures. Granzyme B was neurotoxic through activation of PAR1 and subsequently the phospholipase Cβ-IP3 second messenger system. Inhibition of PAR1 or IP3 prevented granzyme B toxicity. IL-1β enhanced granzyme B-mediated neurotoxicity by increasing PAR1 expression.

Conclusions

Neurons within the inflamed central nervous system are imperiled because they express more PAR1 and are exposed to a neurotoxic combination of both granzyme B and IL-1β. The effects of these inflammatory mediators may be a contributing factor in the progressive brain atrophy associated with neuroinflammatory diseases. Knowledge of how exposure to IL-1β and granzyme B act synergistically to cause neuronal death yields potential novel neuroprotective treatments for neuroinflammatory diseases.

Composite Marker of Cognitive Dysfunction and Brain Atrophy is Highly Accurate in Discriminating Between Relapsing-Remitting and Secondary Progressive Multiple Sclerosis

Background

With the advent of numerous new-generation disease-modifying drugs for multiple sclerosis (MS), the discrimination between relapsing-remitting MS (RRMS) and secondary progressive MS (SPMS) has become a problem of high importance. The aim of our study was to find a simple way to accurately discriminate between RRMS and SPMS that is applicable in clinical practice as a composite marker, using the linear measures of magnetic resonance imaging (MRI) and the results of cognitive tests.

Material/Methods

We included 88 MS patients in the study: 43 participants had RRMS and 45 had SPMS. A battery consisting of 11 tests was used to evaluate cognitive function. We used 11 linear MRI measures and 7 indexes to assess brain atrophy.

Results

Four cognitive tests and 3 linear MRI measures were able to distinguish RRMS from SPMS with the AUC >0.8 based on ROC analysis. Multiple logistic regression models were constructed to identify the best set of cognitive and MRI markers. The model, using the Rey Auditory Verbal Learning Test (RAVLT), Digit Symbol Substitution Test (DSST), and Huckman Index, showed the highest predictive ability: AUC=0.921 (p<0.001). We constructed a simple remission-progression index from the same 3 variables, which discriminated well between RRMS and SPMS: AUC=0.920 (p<0.001), maximal Youden Index=0.702, cut-off=1.68, sensitivity=79.1%, and specificity=91.1%.

Conclusions

The composite remission-progression index, using the RAVLT test, DSST test, and MRI Huckman Index, is highly accurate in discriminating between RRMS and SPMS.

Label-free analysis of human cerebrospinal fluid addressing various normalization strategies and revealing protein groups affected by multiple sclerosis

The aims of the study were to: (i) identify differentially regulated proteins in cerebrospinal fluid (CSF) between multiple sclerosis (MS) patients and non-MS controls; (ii) examine the effect of matching the CSF samples on either total protein amount or volume, and compare four protein normalization strategies for CSF protein quantification. CSF from MS patients (n = 37) and controls (n = 64), consisting of other noninflammatory neurological diseases (n = 50) and non neurological spinal anesthetic subjects (n = 14), were analyzed using label-free proteomics, quantifying almost 800 proteins. In total, 122 proteins were significantly regulated (p < 0.05), where 77 proteins had p-value <0.01 or AUC value >0.75. Hierarchical clustering indicated that there were two main groups of MS patients, those with increased levels of inflammatory response proteins and decreased levels of proteins involved in neuronal tissue development (n = 30), and those with normal protein levels for both of these protein groups (n = 7). The main subgroup of controls clustering with the MS patients showing increased inflammation and decreased neuronal tissue development were patients suffering from chronic fatigue. Our data indicate that the preferable way to quantify proteins in CSF is to first match the samples on total protein amount and then normalize the data based on the median intensities, preferably from the CNS-enriched proteins.

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

The rapidly growing number of biomedical studies supported by mass spectrometry based quantitative proteomics data has made it increasingly difficult to obtain an overview of the current status of the research field. A better way of organizing the biomedical proteomics information from these studies and making it available to the research community is therefore called for. In the presented work, we have investigated scientific publications describing the analysis of the cerebrospinal fluid proteome in relation to multiple sclerosis, Parkinson's disease and Alzheimer's disease. Based on a detailed set of filtering criteria we extracted 85 data sets containing quantitative information for close to 2000 proteins. This information was made available in CSF-PR 2.0 (http://probe.uib.no/csf-pr-2.0), which includes novel approaches for filtering, visualizing and comparing quantitative proteomics information in an interactive and user-friendly environment. CSF-PR 2.0 will be an invaluable resource for anyone interested in quantitative proteomics on cerebrospinal fluid.

In-Depth Cerebrospinal Fluid Quantitative Proteome and Deglycoproteome Analysis: Presenting a Comprehensive Picture of Pathways and Processes Affected by Multiple Sclerosis

In the current study, we conducted a quantitative in-depth proteome and deglycoproteome analysis of cerebrospinal fluid (CSF) from relapsing-remitting multiple sclerosis (RRMS) and neurological controls using mass spectrometry and pathway analysis. More than 2000 proteins and 1700 deglycopeptides were quantified, with 484 proteins and 180 deglycopeptides significantly changed between pools of RRMS and pools of controls. Approximately 300 of the significantly changed proteins were assigned to various biological processes including inflammation, extracellular matrix organization, cell adhesion, immune response, and neuron development. Ninety-six significantly changed deglycopeptides mapped to proteins that were not found changed in the global protein study. In addition, four mapped to the proteins oligo-myelin glycoprotein and noelin, which were found oppositely changed in the global study. Both are ligands to the nogo receptor, and the glycosylation of these proteins appears to be affected by RRMS. Our study gives the most extensive overview of the RRMS affected processes observed from the CSF proteome to date, and the list of differential proteins will have great value for selection of biomarker candidates for further verification.

An update on the evidence base for peginterferon β1a in the treatment of relapsing-remitting multiple sclerosis

Peginterferon β1a is a modified form of interferon β1a with a polyethylene glycol (PEG) group attached to the α-amino group of the N terminus of the interferon molecule. This modification alters the pharmacokinetic and pharmacodynamic properties of interferon β1a, enabling reduced frequency of dosing and may also result in reduced immunogenicity of the interferon β1a molecule. The efficacy of peginterferon β1a 125 µg administered subcutaneously every 2 or 4 weeks was demonstrated at the end of the placebo-controlled period in the phase III ADVANCE study; both dosing regimens met their primary endpoint of reducing annualized relapse rate (ARR) compared with placebo. Peginterferon β1a administered every 2 weeks resulted in a more robust treatment effect on ARR, sustained disability progression and magnetic resonance imaging endpoints (new or enlarging T2 lesions and gadolinium-enhanced lesions) than peginterferon β1a every 4 weeks. Further reductions in the ARR with additional positive impact on magnetic resonance imaging outcomes were noted in year 2 of the ADVANCE study with the every 2-week dosing regimen. An adverse-effect profile similar to other interferon β formulations coupled with the advantage of a significant reduction in the number of injections, could lead to improved long-term adherence to peginterferon β1a. We review the evidence base for the role of peginterferon β1a in the treatment of relapsing-remitting multiple sclerosis.

Advances in targeted proteomics and applications to biomedical research

Targeted proteomics technique has emerged as a powerful protein quantification tool in systems biology, biomedical research, and increasing for clinical applications. The most widely used targeted proteomics approach, selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), can be used for quantification of cellular signaling networks and preclinical verification of candidate protein biomarkers. As an extension to our previous review on advances in SRM sensitivity (Shi et al., Proteomics, 12, 1074-1092, 2012) herein we review recent advances in the method and technology for further enhancing SRM sensitivity (from 2012 to present), and highlighting its broad biomedical applications in human bodily fluids, tissue and cell lines. Furthermore, we also review two recently introduced targeted proteomics approaches, parallel reaction monitoring (PRM) and data-independent acquisition (DIA) with targeted data extraction on fast scanning high-resolution accurate-mass (HR/AM) instruments. Such HR/AM targeted quantification with monitoring all target product ions addresses SRM limitations effectively in specificity and multiplexing; whereas when compared to SRM, PRM and DIA are still in the infancy with a limited number of applications. Thus, for HR/AM targeted quantification we focus our discussion on method development, data processing and analysis, and its advantages and limitations in targeted proteomics. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale quantification of hundreds of target proteins are discussed.

Developing Biomarkers for MS

Existing clinical outcomes of disease activity, including relapse rates, are inherently insensitive to the underlying pathological process in MS. Moreover, it is extremely difficult to measure clinical disability in patients, which is often a retrospective assessment, and definitely not within the time frame of a clinical trial. Biomarkers , conversely are more specific for a pathologic process and if used correctly can prove invaluable in the diagnosis, stratification and monitoring of disease activity, including any subclinical activity which is not visible to the naked eye. In this chapter, we discuss the development of neurofilaments as surrogate outcomes of disability in MS. The validation and qualification are vital steps in biomarker development and to gaining acceptance in scientific community, and the pitfalls leading up to this are also discussed.

Pre-symptomatic diagnosis and treatment of filovirus diseases

Filoviruses are virulent human pathogens which cause severe illness with high case fatality rates and for which there are no available FDA-approved vaccines or therapeutics. Diagnostic tools including antibody- and molecular-based assays, mass spectrometry, and next-generation sequencing are continually under development. Assays using the polymerase chain reaction (PCR) have become the mainstay for the detection of filoviruses in outbreak settings. In many cases, real-time reverse transcriptase-PCR allows for the detection of filoviruses to be carried out with minimal manipulation and equipment and can provide results in less than 2 h. In cases of novel, highly diverse filoviruses, random-primed pyrosequencing approaches have proved useful. Ideally, diagnostic tests would allow for diagnosis of filovirus infection as early as possible after infection, either before symptoms begin, in the event of a known exposure or epidemiologic outbreak, or post-symptomatically. If tests could provide an early definitive diagnosis, then this information may be used to inform the choice of possible therapeutics. Several exciting new candidate therapeutics have been described recently; molecules that have therapeutic activity when administered to animal models of infection several days post-exposure, once signs of disease have begun. The latest data for candidate nucleoside analogs, small interfering RNA (siRNA) molecules, phosphorodiamidate (PMO) molecules, as well as antibody and blood-product therapeutics and therapeutic vaccines are discussed. For filovirus researchers and government agencies interested in making treatments available for a nation's defense as well as its general public, having the right diagnostic tools to identify filovirus infections, as well as a panel of available therapeutics for treatment when needed, is a high priority. Additional research in both areas is required for ultimate success, but significant progress is being made to reach these goals.

Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure Cancer-Relevant Proteins in Plasma

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens to hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility, and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here, we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and seven control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data, we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to subnanogram/ml sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and interlaboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy-isotope-labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an interlaboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality control measures, enables sensitive, specific, reproducible, and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

Targeted multiplexed selected reaction monitoring analysis evaluates protein expression changes of molecular risk factors for major psychiatric disorders

BACKGROUND

Extensive research efforts have generated genomic, transcriptomic, proteomic, and functional data hoping to elucidate psychiatric pathophysiology. Selected reaction monitoring, a recently developed targeted proteomic mass spectrometric approach, has made it possible to evaluate previous findings and hypotheses with high sensitivity, reproducibility, and quantitative accuracy.

METHODS

Here, we have developed a labelled multiplexed selected reaction monitoring assay, comprising 56 proteins previously implicated in the aetiology of major psychiatric disorders, including cell type markers or targets and effectors of known psychopharmacological interventions. We analyzed postmortem anterior prefrontal cortex (Brodmann area 10) tissue of patients diagnosed with schizophrenia (n=22), bipolar disorder (n=23), and major depressive disorder with (n=11) and without (n=11) psychotic features compared with healthy controls (n=22).

RESULTS

Results agreed with several previous studies, with the finding of alterations of Wnt-signalling and glutamate receptor abundance predominately in bipolar disorder and abnormalities in energy metabolism across the neuropsychiatric disease spectrum. Calcium signalling was predominantly affected in schizophrenia and affective psychosis. Interestingly, we were able to show a decrease of all 4 tested oligodendrocyte specific proteins (MOG, MBP, MYPR, CNPase) in bipolar disorder and to a lesser extent in schizophrenia and affective psychosis. Finally, we provide new evidence linking ankyrin 3 specifically to affective psychosis and the 22q11.2 deletion syndrome-associated protein septin 5 to schizophrenia.

CONCLUSIONS

Our study highlights the potential of selected reaction monitoring to evaluate the protein abundance levels of candidate markers of neuropsychiatric spectrum disorders, providing a high throughput multiplex platform for validation of putative disease markers and drug targets.

Cerebrospinal fluid proteomics in multiple sclerosis

Multiple sclerosis (MS) is an immune mediated chronic inflammatory disease of the central nervous system usually initiated during young adulthood, affecting approximately 2.5 million people worldwide. There is currently no cure for MS, but disease modifying treatment has become increasingly more effective, especially when started in the first phase of the disease. The disease course and prognosis are often unpredictable and it can be challenging to determine an early diagnosis. The detection of novel biomarkers to understand more of the disease mechanism, facilitate early diagnosis, predict disease progression, and find treatment targets would be very attractive. Over the last decade there has been an increasing effort toward finding such biomarker candidates. One promising strategy has been to use state-of-the-art quantitative proteomics approaches to compare the cerebrospinal fluid (CSF) proteome between MS and control patients or between different subgroups of MS. In this review we summarize and discuss the status of CSF proteomics in MS, including the latest findings with a focus on the last five years. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

A type 2 biomarker separates relapsing-remitting from secondary progressive multiple sclerosis

OBJECTIVE

We tested whether it is possible to differentiate relapsing-remitting (RR) from secondary progressive (SP) disease stages in patients with multiple sclerosis (MS) using a combination of nuclear magnetic resonance (NMR) metabolomics and partial least squares discriminant analysis (PLS-DA) of biofluids, which makes no assumptions on the underlying mechanisms of disease.

METHODS

Serum samples were obtained from patients with primary progressive MS (PPMS), SPMS, and RRMS; patients with other neurodegenerative conditions; and age-matched controls. Samples were analyzed by NMR and PLS-DA models were derived to separate disease groups.

RESULTS

The PLS-DA models for serum samples from patients with MS enabled reliable differentiation between RRMS and SPMS. This approach also identified significant differences between the metabolite profiles of each of the MS groups (PP, SP, and RR) and the healthy controls, as well as predicting disease group membership with high specificity and sensitivity.

CONCLUSIONS

NMR metabolomics analysis of serum is a sensitive and robust method for differentiating between different stages of MS, yielding diagnostic markers without a priori knowledge of disease pathogenesis. Critically, this study identified and validated a type II biomarker for the RR to SP transition in patients with MS. This approach may be of considerable benefit in categorizing patients for treatment and as an outcome measure in future clinical trials.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that serum metabolite profiles accurately distinguish patients with different subtypes and stages of MS.

Application of quantitative proteomics technologies to the biomarker discovery pipeline for multiple sclerosis

Multiple sclerosis is an inflammatory-mediated demyelinating disorder most prevalent in young Caucasian adults. The various clinical manifestations of the disease present several challenges in the clinic in terms of diagnosis, monitoring disease progression and response to treatment. Advances in MS-based proteomic technologies have revolutionized the field of biomarker research and paved the way for the identification and validation of disease-specific markers. This review focuses on the novel candidates discovered by the application of quantitative proteomics to relevant disease-affected tissues in both the human context and within the animal model of the disease known as experimental autoimmune encephalomyelitis. The role of targeted MS approaches for biomarker validation studies, such as multiple reaction monitoring will also be discussed.

Identification of novel biomarkers of brain damage in patients with hemorrhagic stroke by integrating bioinformatics and mass spectrometry-based proteomics

Hemorrhagic stroke (HS) is a significant cause of mortality that requires rapid diagnosis and prompt medical attention. A time-efficient diagnostic test to assist in the early classification of patients with stroke would be of great value. The aims here were to (a) select "brain-specific" proteins using a bioinformatics approach, (b) develop selected reaction monitoring (SRM) assays for candidate proteins, and (c) quantify these proteins in cerebrospinal fluid (CSF). "The Human Protein Atlas" and the "Peptide Atlas" were used to select proteins specifically and abundantly expressed in brain tissue, excluding high-abundance plasma proteins. Protein extracts from brain tissue were used for SRM assay development of proteins of interest. The levels of 68 "brain-specific" proteins were measured by SRM in 36 age-matched patients, including individuals with HS (n = 15), ischemic stroke (n = 11), and controls (n = 10). Additionally, S100B was measured using an electrochemoluminometric immunoassay. CSF levels of S100B and eight of the "brain-specific" proteins (NSE, GFAP, α-Inx, MBP, MT3, NFM, β-Syn, and γ-Syn) were increased in a subset of samples from HS patients, especially in those individuals with intraventricular hemorrhage and poor outcome. Seven of these proteins (S100B, NSE, GFAP, α-Inx, MBP, NFM, and β-Syn) showed significant differences between patients with and without brain hemorrhage. Novel biomarkers of brain injury (α-Inx, NFM, and β-Syn) were identified in the CSF of patients with HS. Investigating the role of these proteins in blood with more sensitive methods is warranted.

Biomarker report from the phase II lamotrigine trial in secondary progressive MS - neurofilament as a surrogate of disease progression

Objective

Lamotrigine trial in SPMS was a randomised control trial to assess whether partial blockade of sodium channels has a neuroprotective effect. The current study was an additional study to investigate the value of neurofilament (NfH) and other biomarkers in predicting prognosis and/or response to treatment.

Methods

SPMS patients who attended the NHNN or the Royal Free Hospital, UK, eligible for inclusion were invited to participate in the biomarker study. Primary outcome was whether lamotrigine would significantly reduce detectable serum NfH at 0-12, 12–24 and 0–24 months compared to placebo. Other serum/plasma and CSF biomarkers were also explored.

Results

Treatment effect by comparing absolute changes in NfH between the lamotrigine and placebo group showed no difference, however based on serum lamotrigine adherence there was significant decline in NfH (NfH 12–24 months p = 0.043, Nfh 0–24 months p = 0.023). Serum NfH correlated with disability: walking times, 9-HPT (non-dominant hand), PASAT, z-score, MSIS-29 (psychological) and EDSS and MRI cerebral atrophy and MTR. Other biomarkers explored in this study were not found to be significantly associated, aside from that of plasma osteopontin.

Conclusions

The relations between NfH and clinical scores of disability and MRI measures of atrophy and disease burden support NfH being a potential surrogate endpoint complementing MRI in neuroprotective trials and sample sizes for such trials are presented here. We did not observe a reduction in NfH levels between the Lamotrigine and placebo arms, however, the reduction in serum NfH levels based on lamotrigine adherence points to a possible neuroprotective effect of lamotrigine on axonal degeneration.

The emergence of top-down proteomics in clinical research

Proteomic technology has advanced steadily since the development of 'soft-ionization' techniques for mass-spectrometry-based molecular identification more than two decades ago. Now, the large-scale analysis of proteins (proteomics) is a mainstay of biological research and clinical translation, with researchers seeking molecular diagnostics, as well as protein-based markers for personalized medicine. Proteomic strategies using the protease trypsin (known as bottom-up proteomics) were the first to be developed and optimized and form the dominant approach at present. However, researchers are now beginning to understand the limitations of bottom-up techniques, namely the inability to characterize and quantify intact protein molecules from a complex mixture of digested peptides. To overcome these limitations, several laboratories are taking a whole-protein-based approach, in which intact protein molecules are the analytical targets for characterization and quantification. We discuss these top-down techniques and how they have been applied to clinical research and are likely to be applied in the near future. Given the recent improvements in mass-spectrometry-based proteomics and stronger cooperation between researchers, clinicians and statisticians, both peptide-based (bottom-up) strategies and whole-protein-based (top-down) strategies are set to complement each other and help researchers and clinicians better understand and detect complex disease phenotypes.