Identification of candidate cerebrospinal fluid biomarkers in parkinsonism using quantitative proteomics

Cerebrospinal fluid protein biomarkers in Parkinson's disease

Proteomic profiling is an effective way to identify biomarkers for Parkinson's disease (PD). Cerebrospinal fluid (CSF) has direct connectivity with the brain and could be a source of finding biomarkers and their clinical implications. Comparative proteomic profiling has shown that a group of differentially displayed proteins exist. The studies performed using conventional and classical tools also supported the occurrence of these proteins. Many studies have highlighted the potential of CSF proteomic profiling for biomarker identification and their clinical applications. Some of these proteins are useful for disease diagnosis and prediction. Proteomic profiling of CSF also has immense potential to distinguish PD from similar neurodegenerative disorders. A few protein biomarkers help in fundamental knowledge generation and clinical interpretation. However, the specific biomarker of PD is not yet known. The use of proteomic approaches in clinical settings is also rare. A large-scale, multi-centric, multi-population and multi-continental study using multiple proteomic tools is warranted. Such a study can provide valuable, comprehensive and reliable information for a better understanding of PD and the development of specific biomarkers. The current article sheds light on the role of CSF proteomic profiling in identifying biomarkers of PD and their clinical implications. The article also explains the achievements, obstacles and hopes for future directions of this approach.

High-Throughput CSF Proteomics and Machine Learning to Identify Proteomic Signatures for Parkinson Disease Development and Progression

BACKGROUND AND OBJECTIVES

This study aimed to identify CSF proteomic signatures characteristic of Parkinson disease (PD) and evaluate their clinical utility.

METHODS

This observational study used data from the Parkinson's Progression Markers Initiative (PPMI), which enrolled patients with PD, healthy controls (HCs), and non-PD participants carrying GBA1, LRRK2, and/or SNCA pathogenic variants (genetic prodromals) at international sites. Study participants were chosen from PPMI enrollees based on the availability of aptamer-based CSF proteomic data, quantifying 4,071 proteins, and classified as patients with PD without GBA1, LRRK2, and/or SNCA pathogenic variants (nongenetic PD), HCs, patients with PD carrying the aforementioned pathogenic variants (genetic PD), or genetic prodromals. Differentially expressed protein (DEP) analysis and the least absolute shrinkage and selection operator (LASSO) were applied to the data from nongenetic PD and HCs. Signatures characteristics of nongenetic PD were quantified as a PD proteomic score (PD-ProS), validated internally and then externally using data of 1,556 CSF proteins from the LRRK2 Cohort Consortium (LCC). We further tested the PD-ProS in genetic PD and genetic prodromals and examined associations with clinical progression.

RESULTS

Data from 279 patients with nongenetic PD (mean ± SD, age 62.0 ± 9.6 years; male 67.7%) and 141 HCs (age 60.5 ± 11.9 years; male 64.5%) were used for PD-ProS derivation. From 23 DEPs, LASSO determined weights of 14 DEPs for the PD-ProS (area under the curve [AUC] 0.83, 95% CI 0.78-0.87), validated in an independent internal validation cohort of 71 patients with nongenetic PD and 35 HCs (AUC 0.81, 95% CI 0.73-0.90). In the LCC, only 5 of the 14 DEPs were also measured. Notably, these 5 DEPs still distinguished 34 patients with nongenetic PD from 31 HCs with the same weights (AUC 0.75, 95% CI 0.63-0.87). Furthermore, the PD-ProS distinguished 258 patients with genetic PD from 365 genetic prodromals. Finally, regardless of genetic status, the PD-ProS independently predicted both cognitive and motor decline in PD (dementia, adjusted hazard ratio in the highest quintile [aHR-Q5] 2.8 [95% CI 1.6-5.0]; Hoehn and Yahr stage IV, aHR-Q5 2.1 [95% CI 1.1-4.0]).

DISCUSSION

By integrating high-throughput proteomics with machine learning, we identified PD-associated CSF proteomic signatures crucial for PD development and progression.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov (NCT01176565). A link to the trial registry page is clinicaltrials.gov/ct2/show/NCT01141023.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that the CSF proteome contains clinically important information regarding the development and progression of Parkinson disease that can be deciphered by a combination of high-throughput proteomics and machine learning.

Cerebrospinal fluid and blood serum biomarkers in neurodegenerative proteinopathies: A prospective, open, cross-correlation study

Neurodegenerative diseases are a broad heterogeneous group affecting the nervous system. They are characterized, from a pathophysiological perspective, by the selective involvement of a subpopulation of nerve cells with a consequent clinical picture of a disease. Clinical diagnoses of neurodegenerative diseases are quite challenging and often not completely accurate because of their marked heterogeneity and frequently overlapping clinical pictures. Efforts are being made to define sufficiently specific and sensitive markers for individual neurodegenerative diseases or groups of diseases in order to increase the accuracy and speed of clinical diagnosis. Thus said, this present research aimed to identify biomarkers in the cerebrospinal fluid (CSF) and serum (α-synuclein [α-syn], tau protein [t-tau], phosphorylated tau protein [p-tau], β-amyloid [Aβ], clusterin, chromogranin A [chromogrA], cystatin C [cyst C], neurofilament heavy chains [NFH], phosphorylated form of neurofilament heavy chains [pNF-H], and ratio of tau protein/amyloid beta [Ind tau/Aβ]) that could help in the differential diagnosis and differentiation of the defined groups of α-synucleinopathies and four-repeat (4R-) tauopathies characterized by tau protein isoforms with four microtubule-binding domains. In this study, we analyzed a cohort of 229 patients divided into four groups: (1) Parkinson's disease (PD) + dementia with Lewy bodies (DLB) (n = 82), (2) multiple system atrophy (MSA) (n = 25), (3) progressive supranuclear palsy (PSP) + corticobasal syndrome (CBS) (n = 30), and (4) healthy controls (HC) (n = 92). We also focused on analyzing the biomarkers in relation to each other with the intention of determining whether they are useful in distinguishing among individual proteinopathies. Our results indicate that the proposed set of biomarkers, when evaluated in CSF, is likely to be useful for the differential diagnosis of MSA versus 4RT. However, these biomarkers do not seem to provide any useful diagnostic information when assessed in blood serum.

Prediction of Proteins in Cerebrospinal Fluid and Application to Glioma Biomarker Identification

Cerebrospinal fluid (CSF) proteins are very important because they can serve as biomarkers for central nervous system diseases. Although many CSF proteins have been identified with wet experiments, the identification of CSF proteins is still a challenge. In this paper, we propose a novel method to predict proteins in CSF based on protein features. A two-stage feature-selection method is employed to remove irrelevant features and redundant features. The deep neural network and bagging method are used to construct the model for the prediction of CSF proteins. The experiment results on the independent testing dataset demonstrate that our method performs better than other methods in the prediction of CSF proteins. Furthermore, our method is also applied to the identification of glioma biomarkers. A differentially expressed gene analysis is performed on the glioma data. After combining the analysis results with the prediction results of our model, the biomarkers of glioma are identified successfully.

Cerebrospinal Fluid Biomarkers of Synaptic Dysfunction are Altered in Parkinson's Disease and Related Disorders

BACKGROUND

Synaptic dysfunction and degeneration are central contributors to the pathogenesis and progression of parkinsonian disorders. Therefore, identification and validation of biomarkers reflecting pathological synaptic alterations are greatly needed and could be used in prognostic assessment and to monitor treatment effects.

OBJECTIVE

To explore candidate biomarkers of synaptic dysfunction in Parkinson's disease (PD) and related disorders.

METHODS

Mass spectrometry was used to quantify 15 synaptic proteins in two clinical cerebrospinal fluid (CSF) cohorts, including PD (n₁  = 51, n₂  = 101), corticobasal degeneration (CBD) (n₁  = 11, n₂  = 3), progressive supranuclear palsy (PSP) (n₁  = 22, n₂  = 21), multiple system atrophy (MSA) (n₁  = 31, n₂  = 26), and healthy control (HC) (n₁  = 48, n₂  = 30) participants, as well as Alzheimer's disease (AD) (n₂  = 23) patients in the second cohort.

RESULTS

Across both cohorts, lower levels of the neuronal pentraxins (NPTX; 1, 2, and receptor) were found in PD, MSA, and PSP, compared with HC. In MSA and PSP, lower neurogranin, AP2B1, and complexin-2 levels compared with HC were observed. In AD, levels of 14-3-3 zeta/delta, beta- and gamma-synuclein were higher compared with the parkinsonian disorders. Lower pentraxin levels in PD correlated with Mini-Mental State Exam scores and specific cognitive deficits (NPTX2; rho = 0.25-0.32, P < 0.05) and reduced dopaminergic pre-synaptic integrity as measured by DaTSCAN (NPTX2; rho = 0.29, P = 0.023). Additionally, lower levels were associated with the progression of postural imbalance and gait difficulty symptoms (All NPTX; β-estimate = -0.025 to -0.038, P < 0.05) and cognitive decline (NPTX2; β-estimate = 0.32, P = 0.021).

CONCLUSIONS

These novel findings show different alterations of synaptic proteins in parkinsonian disorders compared with AD and HC. The neuronal pentraxins may serve as prognostic CSF biomarkers for both cognitive and motor symptom progression in PD. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Global, in situ analysis of the structural proteome in individuals with Parkinson's disease to identify a new class of biomarker

Parkinson's disease (PD) is a prevalent neurodegenerative disease for which robust biomarkers are needed. Because protein structure reflects function, we tested whether global, in situ analysis of protein structural changes provides insight into PD pathophysiology and could inform a new concept of structural disease biomarkers. Using limited proteolysis-mass spectrometry (LiP-MS), we identified 76 structurally altered proteins in cerebrospinal fluid (CSF) of individuals with PD relative to healthy donors. These proteins were enriched in processes misregulated in PD, and some proteins also showed structural changes in PD brain samples. CSF protein structural information outperformed abundance information in discriminating between healthy participants and those with PD and improved the discriminatory performance of CSF measures of the hallmark PD protein α-synuclein. We also present the first analysis of inter-individual variability of a structural proteome in healthy individuals, identifying biophysical features of variable protein regions. Although independent validation is needed, our data suggest that global analyses of the human structural proteome will guide the development of novel structural biomarkers of disease and enable hypothesis generation about underlying disease processes.

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.

Alterations in Self-Aggregating Neuropeptides in Cerebrospinal Fluid of Patients with Parkinsonian Disorders

Background: Parkinson’s disease (PD), progressive supranuclear palsy (PSP), and multiple system atrophy (MSA) present with similar movement disorder symptoms but distinct protein aggregates upon pathological examination. Objective: Discovery and validation of candidate biomarkers in parkinsonian disorders for differential diagnosis of subgroup molecular etiologies. Methods: Untargeted liquid chromatography (LC)-mass spectrometry (MS) proteomics was used for discovery profiling in cerebral spinal fluid (CSF) followed by LC-MS/MS based multiple reaction monitoring for validation of candidates. We compared clinical variation within the parkinsonian cohort including PD subgroups exhibiting tremor dominance (TD) or postural instability gait disturbance and those with detectable leukocytes in CSF. Results: We have identified candidate peptide biomarkers and validated related proteins with targeted quantitative multiplexed assays. Dopamine-drug naïve patients at first diagnosis exhibit reduced levels of signaling neuropeptides, chaperones, and processing proteases for packaging of self-aggregating peptides into dense core vesicles. Distinct patterns of biomarkers were detected in the parkinsonian disorders but were not robust enough to offer a differential diagnosis. Different biomarker changes were detected in male and female patients with PD. Subgroup specific candidate biomarkers were identified for TD PD and PD patients with leukocytes detected in CSF. Conclusion: PD, MSA, and PSP exhibit overlapping as well as distinct protein biomarkers that suggest specific molecular etiologies. This indicates common sensitivity of certain populations of selectively vulnerable neurons in the brain, and distinct therapeutic targets for PD subgroups. Our report validates a decrease in CSF levels of self-aggregating neuropeptides in parkinsonian disorders and supports the role of native amyloidogenic proteins in etiologies of 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.

Update on CSF Biomarkers in Parkinson's Disease

Progress in developing disease-modifying therapies in Parkinson’s disease (PD) can only be achieved through reliable objective markers that help to identify subjects at risk. This includes an early and accurate diagnosis as well as continuous monitoring of disease progression and therapy response. Although PD diagnosis still relies mainly on clinical features, encouragingly, advances in biomarker discovery have been made. The cerebrospinal fluid (CSF) is a biofluid of particular interest to study biomarkers since it is closest to the brain structures and therefore could serve as an ideal source to reflect ongoing pathologic processes. According to the key pathophysiological mechanisms, the CSF status of α-synuclein species, markers of amyloid and tau pathology, neurofilament light chain, lysosomal enzymes and markers of neuroinflammation provide promising preliminary results as candidate biomarkers. Untargeted approaches in the field of metabolomics provide insights into novel and interconnected biological pathways. Markers based on genetic forms of PD can contribute to identifying subgroups suitable for gene-targeted treatment strategies that might also be transferable to sporadic PD. Further validation analyses in large PD cohort studies will identify the CSF biomarker or biomarker combinations with the best value for clinical and research purposes.

The Neuroinflammatory Acute Phase Response in Parkinsonian-Related Disorders

BACKGROUND

Neuroinflammation is implicated in the pathophysiology of Parkinson's disease (PD) and related conditions, yet prior clinical biomarker data report mixed findings.

OBJECTIVES

The aim was to measure a panel of neuroinflammatory acute phase response (APR) proteins in the cerebrospinal fluid (CSF) of participants with PD and related disorders.

METHODS

Eleven APR proteins were measured in the CSF of 867 participants from the BioFINDER cohort who were healthy (612) or had a diagnosis of PD (155), multiple system atrophy (MSA) (26), progressive supranuclear palsy (PSP) (22), dementia with Lewy bodies (DLB) (23), or Parkinson's disease with dementia (PDD) (29).

RESULTS

CSF APR proteins were mostly unchanged in PD, with only haptoglobin and α1-antitrypsin significantly elevated compared to controls. These proteins were variably increased in the other disorders. Certain protein components yielded unique signatures according to diagnosis: ferritin and transthyretin were selectively elevated in MSA and discriminated these patients from all others. Haptoglobin was selectively increased in PSP, discriminating this disease from MSA when used in combination with ferritin and transthyretin. This panel of proteins did not correlate well with severity of motor impairment in any disease category, but several (particularly ceruloplasmin and ferritin) were associated with memory performance (Mini-Mental State Examination) in patients with DLB and PDD.

CONCLUSIONS

These findings provide new insights into inflammatory changes in PD and related disorders while also introducing biomarkers of potential clinical diagnostic utility. © 2022 International Parkinson and Movement Disorder Society.

Blood and Cerebrospinal Fluid Biomarkers of Inflammation in Parkinson's Disease

Given the clear role of inflammation in the pathogenesis of Parkinson's disease (PD) and its impact on incidence and phenotypical characteristics, this review provides an overview with focus on inflammatory biofluid markers in blood and cerebrospinal fluid (CSF) in PD patient cohorts. In preparation for clinical trials targeting the immune system, we specifically address the following questions: 1) What evidence do we have for pro-inflammatory profiles in blood and in CSF of sporadic and genetic PD patients? 2) Is there a role of anti-inflammatory mediators in blood/CSF? 3) Do inflammatory profiles in blood reflect those in CSF indicative of a cross-talk between periphery and brain? 4) Do blood/CSF inflammatory profiles change over the disease course as assessed in repeatedly taken biosamples? 5) Are blood/CSF inflammatory profiles associated with phenotypical trajectories in PD? 6) Are blood/CSF inflammatory profiles associated with CSF levels of neurodegenerative/PD-specific biomarkers? Knowledge on these questions will inform future strategies for patient stratification and cohort enrichment as well as suitable outcome measures for clinical trials.

Identification of cerebrospinal fluid biomarkers for parkinsonism using a proteomics approach

The aim of our study was to investigate cerebrospinal fluid (CSF) tryptic peptide profiles as potential diagnostic biomarkers for the discrimination of parkinsonian disorders. CSF samples were collected from individuals with parkinsonism, who had an uncertain diagnosis at the time of inclusion and who were followed for up to 12 years in a longitudinal study. We performed shotgun proteomics to identify tryptic peptides in CSF of Parkinson's disease (PD, n = 10), multiple system atrophy patients (MSA, n = 5) and non-neurological controls (n = 10). We validated tryptic peptides with differential levels between PD and MSA using a newly developed selected reaction monitoring (SRM) assay in CSF of PD (n = 46), atypical parkinsonism patients (AP; MSA, n = 17; Progressive supranuclear palsy; n = 8) and non-neurological controls (n = 39). We identified 191 tryptic peptides that differed significantly between PD and MSA, of which 34 met our criteria for SRM development. For 14/34 peptides we confirmed differences between PD and AP. These tryptic peptides discriminated PD from AP with moderate-to-high accuracy. Random forest modelling including tryptic peptides plus either clinical assessments or other CSF parameters (neurofilament light chain, phosphorylated tau protein) and age improved the discrimination of PD vs. AP. Our results show that the discovery of tryptic peptides by untargeted and subsequent validation by targeted proteomics is a suitable strategy to identify potential CSF biomarkers for PD versus AP. Furthermore, the tryptic peptides, and corresponding proteins, that we identified as differential biomarkers may increase our current knowledge about the disease-specific pathophysiological mechanisms of parkinsonism.

Neuronal pentraxins as biomarkers of synaptic activity: from physiological functions to pathological changes in neurodegeneration

The diagnosis of neurodegenerative disorders is often challenging due to the lack of diagnostic tools, comorbidities and shared pathological manifestations. Synaptic dysfunction is an early pathological event in many neurodegenerative disorders, but the underpinning mechanisms are still poorly characterised. Reliable quantification of synaptic damage is crucial to understand the pathophysiology of neurodegeneration, to track disease status and to obtain prognostic information. Neuronal pentraxins (NPTXs) are extracellular scaffolding proteins emerging as potential biomarkers of synaptic dysfunction in neurodegeneration. They are a family of proteins involved in homeostatic synaptic plasticity by recruiting post-synaptic receptors into synapses. Recent research investigates the dynamic changes of NPTXs in the cerebrospinal fluid (CSF) as an expression of synaptic damage, possibly related to cognitive impairment. In this review, we summarise the available data on NPTXs structure and expression patterns as well as on their contribution in synaptic function and plasticity and other less well-characterised roles. Moreover, we propose a mechanism for their involvement in synaptic damage and neurodegeneration and assess their potential as CSF biomarkers for neurodegenerative diseases.

CSF Proteomic Alzheimer's Disease-Predictive Subtypes in Cognitively Intact Amyloid Negative Individuals

We recently discovered three distinct pathophysiological subtypes in Alzheimer’s disease (AD) using cerebrospinal fluid (CSF) proteomics: one with neuronal hyperplasticity, a second with innate immune system activation, and a third subtype with blood–brain barrier dysfunction. It remains unclear whether AD proteomic subtype profiles are a consequence of amyloid aggregation, or might exist upstream from aggregated amyloid. We studied this question in 127 older individuals with intact cognition and normal AD biomarkers in two independent cohorts (EMIF-AD MBD and ADNI). We clustered 705 proteins measured in CSF that were previously related to AD. We identified in these cognitively intact individuals without AD pathology three subtypes: two subtypes were seen in both cohorts (n = 49 with neuronal hyperplasticity and n = 44 with blood–brain barrier dysfunction), and one only in ADNI (n = 12 with innate immune activation). The proteins specific for these subtypes strongly overlapped with AD subtype protein profiles (overlap coefficients 92%–71%). Longitudinal p₁₈₁-tau and amyloid β 1–42 (Aβ42) CSF analysis showed that in the hyperplasticity subtype p₁₈₁-tau increased (β = 2.6 pg/mL per year, p = 0.01) and Aβ42 decreased over time (β = −4.4 pg/mL per year, p = 0.03), in the innate immune activation subtype p₁₈₁-tau increased (β = 3.1 pg/mL per year, p = 0.01) while in the blood–brain barrier dysfunction subtype Aβ42 decreased (β = −3.7 pg/mL per year, p = 0.009). These findings suggest that AD proteomic subtypes might already manifest in cognitively normal individuals and may predispose for AD before amyloid has reached abnormal levels.

Neuropathological and Biomarker Findings in Parkinson's Disease and Alzheimer's Disease: From Protein Aggregates to Synaptic Dysfunction

There is mounting evidence that Parkinson’s disease (PD) and Alzheimer’s disease (AD) share neuropathological hallmarks, while similar types of biomarkers are being applied to both. In this review we aimed to explore similarities and differences between PD and AD at both the neuropathology and the biomarker levels, specifically focusing on protein aggregates and synapse dysfunction. Thus, amyloid-β peptide (Aβ) and tau lesions of the Alzheimer-type are common in PD and α-synuclein Lewy-type aggregates are frequent findings in AD. Modern neuropathological techniques adding to routine immunohistochemistry might take further our knowledge of these diseases beyond protein aggregates and down to their presynaptic and postsynaptic terminals, with potential mechanistic and even future therapeutic implications. Translation of neuropathological discoveries to the clinic remains challenging. Cerebrospinal fluid (CSF) and positron emission tomography (PET) markers of Aβ and tau have been shown to be reliable for AD diagnosis. Conversely, CSF markers of α-synuclein have not been that consistent. In terms of PET markers, there is no PET probe available for α-synuclein yet, while the AD PET markers range from consistent evidence of their specificity (amyloid imaging) to greater uncertainty of their reliability due to off-target binding (tau imaging). CSF synaptic markers are attractive, still needing more evidence, which currently suggests those might be non-specific markers of disease progression. It can be summarized that there is neuropathological evidence that protein aggregates of AD and PD are present both at the soma and the synapse. Thus, a number of CSF and PET biomarkers beyond α-synuclein, tau and Aβ might capture these different faces of protein-related neurodegeneration. It remains to be seen what the longitudinal outcomes and the potential value as surrogate markers of these biomarkers are.

Pathophysiological subtypes of Alzheimer's disease based on cerebrospinal fluid proteomics

Alzheimer's disease is biologically heterogeneous, and detailed understanding of the processes involved in patients is critical for development of treatments. CSF contains hundreds of proteins, with concentrations reflecting ongoing (patho)physiological processes. This provides the opportunity to study many biological processes at the same time in patients. We studied whether Alzheimer's disease biological subtypes can be detected in CSF proteomics using the dual clustering technique non-negative matrix factorization. In two independent cohorts (EMIF-AD MBD and ADNI) we found that 705 (77% of 911 tested) proteins differed between Alzheimer's disease (defined as having abnormal amyloid, n = 425) and controls (defined as having normal CSF amyloid and tau and normal cognition, n = 127). Using these proteins for data-driven clustering, we identified three robust pathophysiological Alzheimer's disease subtypes within each cohort showing (i) hyperplasticity and increased BACE1 levels; (ii) innate immune activation; and (iii) blood-brain barrier dysfunction with low BACE1 levels. In both cohorts, the majority of individuals were labelled as having subtype 1 (80, 36% in EMIF-AD MBD; 117, 59% in ADNI), 71 (32%) in EMIF-AD MBD and 41 (21%) in ADNI were labelled as subtype 2, and 72 (32%) in EMIF-AD MBD and 39 (20%) individuals in ADNI were labelled as subtype 3. Genetic analyses showed that all subtypes had an excess of genetic risk for Alzheimer's disease (all P > 0.01). Additional pathological comparisons that were available for a subset in ADNI suggested that subtypes showed similar severity of Alzheimer's disease pathology, and did not differ in the frequencies of co-pathologies, providing further support that found subtypes truly reflect Alzheimer's disease heterogeneity. Compared to controls, all non-demented Alzheimer's disease individuals had increased risk of showing clinical progression (all P < 0.01). Compared to subtype 1, subtype 2 showed faster clinical progression after correcting for age, sex, level of education and tau levels (hazard ratio = 2.5; 95% confidence interval = 1.2, 5.1; P = 0.01), and subtype 3 at trend level (hazard ratio = 2.1; 95% confidence interval = 1.0, 4.4; P = 0.06). Together, these results demonstrate the value of CSF proteomics in studying the biological heterogeneity in Alzheimer's disease patients, and suggest that subtypes may require tailored therapy.

Unraveling Pathophysiological Mechanisms of Parkinson's Disease: Contribution of CSF Biomarkers

Diagnosis of Parkinson's disease (PD) relies on clinical history and physical examination, but misdiagnosis is common in early stages. Identification of biomarkers for PD may allow for early and more precise diagnosis and provide information about prognosis. Developments in analytical chemistry allow for the detection of a large number of molecules in cerebrospinal fluid (CSF), which are known to be associated with the pathogenesis of PD. Given the pathophysiology of PD, CSF α-synuclein species have the strongest rationale for use, also providing encouraging preliminary results in terms of early diagnosis. In the field of classical Alzheimer's disease (AD) biomarkers, low CSF Aβ₄₂ levels have shown a robust prognostic value in terms of development of cognitive impairment. Other CSF biomarkers including lysosomal enzymes, neurofilament light chain, markers of neuroinflammation and oxidative stress, although promising, have not proved to be reliable for diagnostic and prognostic purposes yet. Overall, the implementation of CSF biomarkers may give a substantial contribution to the optimal use of disease-modifying drugs.

Fluid Biomarkers for Synaptic Dysfunction and Loss

Synapses are the site for brain communication where information is transmitted between neurons and stored for memory formation. Synaptic degeneration is a global and early pathogenic event in neurodegenerative disorders with reduced levels of pre- and postsynaptic proteins being recognized as a core feature of Alzheimer's disease (AD) pathophysiology. Together with AD, other neurodegenerative and neurodevelopmental disorders show altered synaptic homeostasis as an important pathogenic event, and due to that, they are commonly referred to as synaptopathies. The exact mechanisms of synapse dysfunction in the different diseases are not well understood and their study would help understanding the pathogenic role of synaptic degeneration, as well as differences and commonalities among them and highlight candidate synaptic biomarkers for specific disorders. The assessment of synaptic proteins in cerebrospinal fluid (CSF), which can reflect synaptic dysfunction in patients with cognitive disorders, is a keen area of interest. Substantial research efforts are now directed toward the investigation of CSF synaptic pathology to improve the diagnosis of neurodegenerative disorders at an early stage as well as to monitor clinical progression. In this review, we will first summarize the pathological events that lead to synapse loss and then discuss the available data on established (eg, neurogranin, SNAP-25, synaptotagmin-1, GAP-43, and α-syn) and emerging (eg, synaptic vesicle glycoprotein 2A and neuronal pentraxins) CSF biomarkers for synapse dysfunction, while highlighting possible utilities, disease specificity, and technical challenges for their detection.

Synucleinopathies: Where we are and where we need to go

Synucleinopathies are a group of disorders characterized by the accumulation of inclusions rich in the a-synuclein (aSyn) protein. This group of disorders includes Parkinson's disease, dementia with Lewy bodies (DLB), multiple systems atrophy, and pure autonomic failure (PAF). In addition, genetic alterations (point mutations and multiplications) in the gene encoding for aSyn (SNCA) are associated with familial forms of Parkinson's disease, the most common synucleinopathy. The Synuclein Meetings are a series that has been taking place every 2 years for about 12 years. The Synuclein Meetings bring together leading experts in the field of Synuclein and related human conditions with the goal of discussing and advancing the research. In 2019, the Synuclein meeting took place in Ofir, a city in the outskirts of Porto, Portugal. The meeting, entitled "Synuclein Meeting 2019: Where we are and where we need to go", brought together >300 scientists studying both clinical and molecular aspects of synucleinopathies. The meeting covered a many of the open questions in the field, in a format that prompted open discussions between the participants, and underscored the need for additional research that, hopefully, will lead to future therapies for a group of as of yet incurable disorders. Here, we provide a summary of the topics discussed in each session and highlight what we know, what we do not know, and what progress needs to be made in order to enable the field to continue to advance. We are confident this systematic assessment of where we stand will be useful to steer the field and contribute to filling knowledge gaps that may form the foundations for future therapeutic strategies, which is where we need to go.

Neurofilament Light Chain as a Biomarker, and Correlation with Magnetic Resonance Imaging in Diagnosis of CNS-Related Disorders

The search for diagnostic and prognostic biomarkers for neurodegenerative conditions is of high importance, since these disorders may present difficulties in differential diagnosis. Biomarkers with high sensitivity and specificity are required. Neurofilament light chain (NfL) is a unique biomarker related to axonal damage and neural cell death, which is elevated in a number of neurological disorders, and can be detected in cerebrospinal fluid (CSF), as well as blood, serum, or plasma samples. Although the NfL concentration in CSF is higher than that in blood, blood measurement may be easier in practice due to its lesser invasiveness, reproducibility, and convenience. Many studies have investigated NfL in both CSF and serum/plasma as a potential biomarker of neurodegenerative disorders. Neuroimaging biomarkers can also potentially improve detection of CNS-related disorders at an early stage. Magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) are sensitive techniques to visualize neuroaxonal loss. Therefore, investigating the combination of NfL levels with indices extracted from MRI and DTI scans could potentially improve diagnosis of CNS-related disorders. This review summarizes the evidence for NfL being a reliable biomarker in the early detection and disease management in several CNS-related disorders. Moreover, we highlight the correlation between MRI and NfL and ask whether they can be combined.

Corticobasal degeneration and corticobasal syndrome: A review

Corticobasal degeneration (CBD) is a rare neurodegenerative disorder. The most common presentation of CBD is the corticobasal syndrome (CBS), which is a constellation of cortical and extrapyramidal symptoms and signs. Clinical-pathological studies have illustrated that CBD can present with diverse clinical phenotypes, including a non-fluent, agrammatic primary progressive aphasia syndrome, a behavioral, dysexecutive and visuospatial syndrome, as well as a progressive supranuclear palsy-like syndrome. Conversely, multiple pathologies, such as CBD, Alzheimer's disease and progressive supranuclear palsy may underlie a patient with CBS. This clinical-pathological overlap emphasizes the need for biomarkers that will assist in the accurate diagnosis of patients with CBS. This review presents an overview of the pathological, genetic, clinical and therapeutic characteristics of CBD, with an emphasis on the imaging (structural and functional) and biochemical (cerebrospinal fluid) biomarkers of CBD.

Cerebrospinal Fluid Proteomics For Identification Of α2-Macroglobulin As A Potential Biomarker To Monitor Pharmacological Therapeutic Efficacy In Dopamine Dictated Disease States Of Parkinson's Disease And Schizophrenia

AIM

Parkinson's disease and schizophrenia are clinical end points of dopaminergic deficit and excess, respectively, in the mid-brain. In accordance, current pharmacological interventions aim to restore normal dopamine levels, the overshooting of which culminates in adverse effects which results in psychotic symptoms in Parkinson's disease and extra-pyramidal symptoms in schizophrenia. Currently, there are no laboratory assays to assist treatment decisions or help foresee these drug side-effect outcomes. Therefore, the aim was to discover a protein biomarker that had a varying linear expression across the clinical dopaminergic spectrum.

MATERIALS AND METHODS

iTRAQ-based proteomic experiments along with mass spectrometric analysis was used for comparative proteomics using cerebrospinal fluid (CSF). CSF fluid was collected from 36 patients with Parkinson's disease, 15 patients with urological diseases that served as neurological controls, and seven schizophrenic patients with hallucinations. Validation included ELISA and pathway analysis to highlight the varying expression and provide plausible molecular pathways for differentially expressed proteins in the three clinical phenotypes.

RESULTS

Protein profiles were delineated in CSF from Parkinson's disease patients, neurological control and schizophrenia, respectively. Ten of the proteins that were identified had a linear relationship across the dopaminergic spectrum. α-2-Macroglobulin showed to be having high statistical significance on inter-group comparison on validation studies using ELISA.

CONCLUSIONS

Non-gel-based proteomic experiments are an ideal platform to discover potential biomarkers that can be used to monitor pharmaco-therapeutic efficacy in dopamine-dictated clinical scenarios. α-2 Macroglobulin is a potential biomarker to monitor pharmacological therapy in Parkinson's disease and schizophrenia.

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.

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.

Cerebrospinal fluid NFL in the differential diagnosis of parkinsonian disorders: A meta-analysis

Neurofilament light chain (NFL) in cerebrospinal fluid (CSF) is a promising biomarker candidate which may discriminate atypical parkinsonian disorders (APD), mainly including multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD), from Parkinson's disease (PD). We aim to evaluate the diagnostic accuracy of CSF NFL level as a differentiating biomarker between APD and PD. Databases of PubMed, OVID and Web of Science were searched for studies (published until May 31, 2017) that reported on CSF NFL as a diagnostic biomarker between APD and PD. Eight studies were pooled in this meta-analysis, including 341 PD and 396 APD patients and 388 healthy controls. The pooled sensitivity was 82% (95% CI, 68%-91%) and specificity was 85% (95% CI, 79%-89%) in differentiating APD from PD. The pooled positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR) were 5.4 (95% CI, 3.6%-8.1%), 0.21 (95% CI, 0.11%-0.40%), and 25 (95% CI, 9%-69%) respectively; and the area under the curve (AUC) was 0.89 (95% CI, 0.86%-0.91%). Subgroup analysis revealed sensitivity and specificity were significantly influenced by study design. The APD subtypes, disease duration and severity were the main heterogeneity sources in specificity. The results of Deeks' test revealed a low risk of publication bias. The CSF NFL level may be used as a biomarker in discriminating APD from PD with high diagnostic accuracy at an early stage of disease. Large and longitudinal studies are still needed on individuals who are suspected to have APD.

From Genomics to Omics Landscapes of Parkinson's Disease: Revealing the Molecular Mechanisms

Molecular mechanisms of Parkinson's disease (PD) have already been investigated in various different omics landscapes. We reviewed the literature about different omics approaches between November 2005 and November 2017 to depict the main pathological pathways for PD development. In total, 107 articles exploring different layers of omics data associated with PD were retrieved. The studies were grouped into 13 omics layers: genomics-DNA level, transcriptomics, epigenomics, proteomics, ncRNomics, interactomics, metabolomics, glycomics, lipidomics, phenomics, environmental omics, pharmacogenomics, and integromics. We discussed characteristics of studies from different landscapes, such as main findings, number of participants, sample type, methodology, and outcome. We also performed curation and preliminary synthesis of multiple omics data, and identified overlapping results, which could lead toward selection of biomarkers for further validation of PD risk loci. Biomarkers could support the development of targeted prognostic/diagnostic panels as a tool for early diagnosis and prediction of progression rate and prognosis. This review presents an example of a comprehensive approach to revealing the underlying processes and risk factors of a complex disease. It urges scientists to structure the already known data and integrate it into a meaningful context.

Multiple System Atrophy: An Oligodendroglioneural Synucleinopathy1

Multiple system atrophy (MSA) is an orphan, fatal, adult-onset neurodegenerative disorder of uncertain etiology that is clinically characterized by various combinations of parkinsonism, cerebellar, autonomic, and motor dysfunction. MSA is an α-synucleinopathy with specific glioneuronal degeneration involving striatonigral, olivopontocerebellar, and autonomic nervous systems but also other parts of the central and peripheral nervous systems. The major clinical variants correlate with the morphologic phenotypes of striatonigral degeneration (MSA-P) and olivopontocerebellar atrophy (MSA-C). While our knowledge of the molecular pathogenesis of this devastating disease is still incomplete, updated consensus criteria and combined fluid and imaging biomarkers have increased its diagnostic accuracy. The neuropathologic hallmark of this unique proteinopathy is the deposition of aberrant α-synuclein in both glia (mainly oligodendroglia) and neurons forming glial and neuronal cytoplasmic inclusions that cause cell dysfunction and demise. In addition, there is widespread demyelination, the pathogenesis of which is not fully understood. The pathogenesis of MSA is characterized by propagation of misfolded α-synuclein from neurons to oligodendroglia and cell-to-cell spreading in a "prion-like" manner, oxidative stress, proteasomal and mitochondrial dysfunction, dysregulation of myelin lipids, decreased neurotrophic factors, neuroinflammation, and energy failure. The combination of these mechanisms finally results in a system-specific pattern of neurodegeneration and a multisystem involvement that are specific for MSA. Despite several pharmacological approaches in MSA models, addressing these pathogenic mechanisms, no effective neuroprotective nor disease-modifying therapeutic strategies are currently available. Multidisciplinary research to elucidate the genetic and molecular background of the deleterious cycle of noxious processes, to develop reliable biomarkers and targets for effective treatment of this hitherto incurable disorder is urgently needed.