Protein biomarkers in Parkinson's disease: Focus on cerebrospinal fluid markers and synaptic proteins

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.

Large-scale proximity extension assay reveals CSF midkine and DOPA decarboxylase as supportive diagnostic biomarkers for Parkinson's disease

BACKGROUND

There is a need for biomarkers to support an accurate diagnosis of Parkinson's disease (PD). Cerebrospinal fluid (CSF) has been a successful biofluid for finding neurodegenerative biomarkers, and modern highly sensitive multiplexing methods offer the possibility to perform discovery studies. Using a large-scale multiplex proximity extension assay (PEA) approach, we aimed to discover novel diagnostic protein biomarkers allowing accurate discrimination of PD from both controls and atypical Parkinsonian disorders (APD).

METHODS

CSF from patients with PD, corticobasal syndrome (CBS), progressive supranuclear palsy (PSP), multiple system atrophy and controls, were analysed with Olink PEA panels. Three cohorts were used in this study, comprising 192, 88 and 36 cases, respectively. All samples were run on the Cardiovascular II, Oncology II and Metabolism PEA panels.

RESULTS

Our analysis revealed that 26 and 39 proteins were differentially expressed in the CSF of test and validation PD cohorts, respectively, compared to controls. Among them, 6 proteins were changed in both cohorts. Midkine (MK) was increased in PD with the strongest effect size and results were validated with ELISA. Another most increased protein in PD, DOPA decarboxylase (DDC), which catalyses the decarboxylation of DOPA (L-3,4-dihydroxyphenylalanine) to dopamine, was strongly correlated with dopaminergic treatment. Moreover, Kallikrein 10 was specifically changed in APD compared with both PD and controls, but unchanged between PD and controls. Wnt inhibitory factor 1 was consistently downregulated in CBS and PSP patients in two independent cohorts.

CONCLUSIONS

Using the large-scale PEA approach, we have identified potential novel PD diagnostic biomarkers, most notably MK and DDC, in the CSF of PD patients.

Neurochemical Monitoring of Traumatic Brain Injury by the Combined Analysis of Plasma Beta-Synuclein, NfL, and GFAP in Polytraumatized Patients

Traumatic brain injury (TBI) represents a major determining factor of outcome in severely injured patients. However, reliable brain-damage-monitoring markers are still missing. We therefore assessed brain-specific beta-synuclein as a novel blood biomarker of synaptic damage and measured the benchmarks neurofilament light chain (NfL), as a neuroaxonal injury marker, and glial fibrillary acidic protein (GFAP), as an astroglial injury marker, in patients after polytrauma with and without TBI. Compared to healthy volunteers, plasma NfL, beta-synuclein, and GFAP were significantly increased after polytrauma. The markers demonstrated highly distinct time courses, with beta-synuclein and GFAP peaking early and NfL concentrations gradually elevating during the 10-day observation period. Correlation analyses revealed a distinct influence of the extent of extracranial hemorrhage and the severity of head injury on biomarker concentrations. A combined analysis of beta-synuclein and GFAP effectively discriminated between polytrauma patients with and without TBI, despite the comparable severity of injury. Furthermore, we found a good predictive performance for fatal outcome by employing the initial plasma concentrations of NfL, beta-synuclein, and GFAP. Our findings suggest a high diagnostic value of neuronal injury markers reflecting distinct aspects of neuronal injury for the diagnosis of TBI in the complex setting of polytrauma, especially in clinical surroundings with limited imaging opportunities.

Proteome profiling of cerebrospinal fluid reveals biomarker candidates for Parkinson's disease

Parkinson's disease (PD) is a growing burden worldwide, and there is no reliable biomarker used in clinical routines to date. Cerebrospinal fluid (CSF) is routinely collected in patients with neurological symptoms and should closely reflect alterations in PD patients' brains. Here, we describe a scalable and sensitive mass spectrometry (MS)-based proteomics workflow for CSF proteome profiling. From two independent cohorts with over 200 individuals, our workflow reproducibly quantifies over 1,700 proteins from minimal CSF amounts. Machine learning determines OMD, CD44, VGF, PRL, and MAN2B1 to be altered in PD patients or to significantly correlate with clinical scores. We also uncover signatures of enhanced neuroinflammation in LRRK2 G2019S carriers, as indicated by increased levels of CTSS, PLD4, and HLA proteins. A comparison with our previously acquired urinary proteomes reveals a large overlap in PD-associated changes, including lysosomal proteins, opening up new avenues to improve our understanding of PD pathogenesis.

Proteomics for comprehensive characterization of extracellular vesicles in neurodegenerative disease

Extracellular vesicles (EVs) are small lipid bilayer particles ubiquitously released by almost every cell type. A specific and selective constituents of EVs loaded with variety of proteins, lipids, small noncoding RNAs, and long non-coding RNAs are reflective of cellular events, type, and physiologic/pathophysiologic status of the cell of origin. Moreover, these molecular contents carry information from the cell of origin to recipient cells, modulating intercellular communication. Recent studies demonstrated that EVs not only play a neuroprotective role by mediating the removal of toxic proteins, but also emerge as an important player in various neurodegenerative disease onset and progression through facilitating of misfolded proteins propagation. For this reason, neurodegenerative disease-associated differences in EV proteome relative to normal EVs can be used to fulfil diagnostic, prognostic, and therapeutic purposes. Nonetheless, characterizing EV proteome obtained from biological samples (brain tissue and body fluids, including urea, blood, saliva, and CSF) is a challenging task. Herein, we review the status of EV proteome profiling and the updated discovery of potential biomarkers for the diagnosis of neurodegenerative disease with an emphasis on the integration of high-throughput advanced mass spectrometry (MS) technologies for both qualitative and quantitative analysis of EVs in different clinical tissue/body fluid samples in past five years.

Brain proteome profiling implicates the complement and coagulation cascade in multiple system atrophy brain pathology

BACKGROUND

Multiple system atrophy (MSA) is a rare, progressive, neurodegenerative disorder presenting glia pathology. Still, disease etiology and pathophysiology are unknown, but neuro-inflammation and vascular disruption may be contributing factors to the disease progression. Here, we performed an ex vivo deep proteome profiling of the prefrontal cortex of MSA patients to reveal disease-relevant molecular neuropathological processes. Observations were validated in plasma and cerebrospinal fluid (CSF) of novel cross-sectional patient cohorts.

METHODS

Brains from 45 MSA patients and 30 normal controls (CTRLs) were included. Brain samples were homogenized and trypsinized for peptide formation and analyzed by high-performance liquid chromatography tandem mass spectrometry (LC-MS/MS). Results were supplemented by western blotting, immuno-capture, tissue clearing and 3D imaging, immunohistochemistry and immunofluorescence. Subsequent measurements of glial fibrillary acid protein (GFAP) and neuro-filament light chain (NFL) levels were performed by immunoblotting in plasma of 20 MSA patients and 20 CTRLs. Finally, we performed a proteome profiling of 144 CSF samples from MSA and CTRLs, as well as other parkinsonian disorders. Data were analyzed using relevant parametric and non-parametric two-sample tests or linear regression tests followed by post hoc tests corrected for multiple testing. Additionally, high-throughput bioinformatic analyses were applied.

RESULTS

We quantified more than 4,000 proteins across samples and identified 49 differentially expressed proteins with significantly different abundances in MSA patients compared with CTRLs. Pathway analyses showed enrichment of processes related to fibrinolysis and complement cascade activation. Increased fibrinogen subunit β (FGB) protein levels were further verified, and we identified an enriched recognition of FGB by IgGs as well as intra-parenchymal accumulation around blood vessels. We corroborated blood-brain barrier leakage by a significant increase in GFAP and NFL plasma levels in MSA patients that correlated to disease severity and/or duration. Proteome profiling of CSF samples acquired during the disease course, confirmed increased total fibrinogen levels and immune-related components in the soluble fraction of MSA patients. This was also true for the other atypical parkinsonian disorders, dementia with Lewy bodies and progressive supra-nuclear palsy, but not for Parkinson's disease patients.

CONCLUSION

Our results implicate activation of the fibrinolytic cascade and immune system in the brain as contributing factors in MSA associated with a more severe disease course.

Review of Metabolomics-Based Biomarker Research for Parkinson's Disease

Parkinson's disease (PD), as the second most common neurodegenerative disease, is seriously affecting the life quality of the elderly. However, there is still a lack of efficient medical methods to diagnosis PD before apparent symptoms occur. In recent years, clinical biomarkers including genetic, imaging, and tissue markers have exhibited remarkable benefits in assisting PD diagnoses. Due to the advantages of high-throughput detection of metabolites and almost non-invasive sample collection, metabolomics research of PD is widely used for diagnostic biomarker discovery. However, there are also a few shortages for those identified biomarkers, such as the scarcity of verifications regarding the sensitivity and specificity. Thus, reviewing the research progress of PD biomarkers based on metabolomics techniques is of great significance for developing PD diagnosis. To comprehensively clarify the progress of current metabolic biomarker studies in PD, we reviewed 20 research articles regarding the discovery and validation of biomarkers for PD diagnosis from three mainstream academic databases (NIH PubMed, ISI Web of Science, and Elsevier ScienceDirect). By analyzing those materials, we summarized the metabolic biomarkers identified by those metabolomics studies and discussed the potential approaches used for biomarker verifications. In conclusion, this review provides a comprehensive and updated overview of PD metabolomics research in the past two decades and particularly discusses the validation of disease biomarkers. We hope those discussions might provide inspiration for PD biomarker discovery and verification in the future.

A six-metabolite panel as potential blood-based biomarkers for Parkinson's disease

Characterisation and diagnosis of idiopathic Parkinson's disease (iPD) is a current challenge that hampers both clinical assessment and clinical trial development with the potential inclusion of non-PD cases. Here, we used a targeted mass spectrometry approach to quantify 38 metabolites extracted from the serum of 231 individuals. This cohort is currently one of the largest metabolomic studies including iPD patients, drug-naïve iPD, healthy controls and patients with Alzheimer's disease as a disease-specific control group. We identified six metabolites (3-hydroxykynurenine, aspartate, beta-alanine, homoserine, ornithine (Orn) and tyrosine) that are significantly altered between iPD patients and control participants. A multivariate model to predict iPD from controls had an area under the curve (AUC) of 0.905, with an accuracy of 86.2%. This panel of metabolites may serve as a potential prognostic or diagnostic assay for clinical trial prescreening, or for aiding in diagnosing pathological disease in the clinic.

Multi-omics analysis of brain tissue metabolome and proteome reveals the protective effect of gross saponins of Tribulus terrestris L. fruit against ischemic stroke in rat

ETHNOPHARMACOLOGICAL RELEVANCE

Gross Saponins of Tribulus terrestris L. Fruit (GSTTF) has been reported to have a protective effect against ischemic stroke, but the related mechanism is complex and still not fully investigated.

AIM OF THE STUDY

The combination of metabolomics and proteomics approach was applied to reveal the mechanisms of GSTTF in treating ischemic stroke.

MATERIALS AND METHODS

The metabolite and protein changes in brain tissue were analyzed by the LC-MS-based untargeted metabolomics method and tandem mass tags (TMT)-based quantitative proteomics technology. The multivariate statistical analysis and protein-protein interaction (PPI) analysis were conducted to screen out the biomarkers, and their related pathway was further investigated by the joint pathway analysis.

RESULTS

A total of 110 metabolites and 359 differential proteins, which were mainly associated with complement and coagulation cascades, sphingolipid metabolism, glycerophospholipid metabolism, glutathione metabolism, and platelet activation, etc. were screened out from the rat brain tissue. The PPI network exhibited that the protein F2, Fga, Fgb, Fgg, Plg, and C3, which are greatly involved in the complement and coagulation cascades, have a relatively high connectivity degree, indicating their importance in the process of middle cerebral artery occlusion (MCAO). The GSTTF exerted a protective effect against MCAO via modulating multiple proteins on this pathway. Moreover, F2 played a key role during the protective process and worth to be further investigated due to it has been reported as one of the therapeutic targets of ischemic stroke.

CONCLUSION

The present study could improve the understanding of the potential therapeutic mechanism of GSTTF against ischemic stroke.

Beta-synuclein in cerebrospinal fluid as an early diagnostic marker of Alzheimer's disease

OBJECTIVE

Synaptic loss plays a major role in Alzheimer's disease (AD). However so far no neurochemical marker for synaptic loss has been introduced into clinical routine. By mass spectrometry beta-synuclein was established as a candidate marker. We now aimed to set up a novel ELISA for beta-synuclein for evaluation of its potential as a diagnostic and predictive marker for AD.

METHODS

We analysed in total 393 patients from four specialised centres. The diagnostic groups comprised: AD (n=151), behavioural variant frontotemporal dementia (bvFTD, n=18), Parkinson syndrome (n=46), Creutzfeldt-Jakob disease (CJD, n=23), amyotrophic lateral sclerosis (ALS, n=29), disease control (n=66) and 60 non-neurodegenerative control patients. Results were compared with core AD biomarkers (total tau, phospho-tau and amyloid-β peptide 1-42). Additionally, coexistence of beta-synuclein with vesicular glutamate transporter 1 (VGLUT1) was determined and beta-synuclein levels were quantified in brain homogenates.

RESULTS

Beta-synuclein levels quantified with the newly established ELISA correlated strongly with antibody-free quantitative mass spectrometry data (r=0.92 (95% CI: 0.89 to 0.94), p<0.0001). Cerebrospinal fluid (CSF) beta-synuclein levels were increased in AD-mild cognitive impairment (p<0.0001), AD dementia (p<0.0001) and CJD (p<0.0001), but not in bvFTD, Parkinson syndrome or ALS. Furthermore, beta-synuclein was localised in VGLUT1-positive glutamatergic synapses, and its expression was significantly reduced in brain tissue from patients with AD (p<0.01).

CONCLUSION

We successfully established a sensitive and robust ELISA for the measurement of brain-enriched beta-synuclein, which we could show is localised in glutamatergic synapses. We confirmed previous, mass spectrometry-based observations of increased beta-synuclein levels in CSF of patients with AD and CJD supporting its potential use as a marker of synaptic degeneration.

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.

What Room for Two-Dimensional Gel-Based Proteomics in a Shotgun Proteomics World?

Two-dimensional gel electrophoresis was instrumental in the birth of proteomics in the late 1980s. However, it is now often considered as an outdated technique for proteomics—a thing of the past. Although this opinion may be true for some biological questions, e.g., when analysis depth is of critical importance, for many others, two-dimensional gel electrophoresis-based proteomics still has a lot to offer. This is because of its robustness, its ability to separate proteoforms, and its easy interface with many powerful biochemistry techniques (including western blotting). This paper reviews where and why two-dimensional gel electrophoresis-based proteomics can still be profitably used. It emerges that, rather than being a thing of the past, two-dimensional gel electrophoresis-based proteomics is still highly valuable for many studies. Thus, its use cannot be dismissed on simple fashion arguments and, as usual, in science, the tree is to be judged by the fruit.

A Versatile Workflow for Cerebrospinal Fluid Proteomic Analysis with Mass Spectrometry: A Matter of Choice between Deep Coverage and Sample Throughput

Human cerebrospinal fluid (CSF) is a sample of choice in the study of brain disorders. This biological fluid circulates in the brain and the spinal cord and contains tissue-specific proteins, indicative of health and disease conditions. Despite its potential as a valid source of biological markers, CSF remains largely understudied as compared to blood, in particular due to its more invasive way of sampling.Challenges remain when performing proteomic analysis in clinical research studies. State-of-the-art mass spectrometry (MS) enables deep characterization of the human proteome. But some technical limitations are cardinal to be addressed, such as the capacity to routinely analyze large cohorts of samples. Importantly, a trade-off still needs to be made between the proteome coverage depth and the number of measured samples. In this context, we developed a scalable automated proteomic pipeline for the analysis of CSF. Because of its versatility, this workflow can be adapted to accommodate proteome coverage and/or sample throughput. It allows us to prepare and quantitatively analyze hundreds to thousands of CSF samples; it can also allow identification of more than 3000 proteins in a CSF sample when coupled with isoelectric focusing fractionation.In this chapter, we describe an end-to-end pipeline for the proteomic analysis of CSF. The main steps of the sample preparation comprise spiking of a standard, protein digestion, isobaric labeling, and purification; these are performed in a 96-well plate format enabling automation. Depending on the targeted depth of the CSF proteome, optional analytical steps can be included, such as the removal of abundant proteins and sample pre-fractionation. Liquid chromatography tandem MS as well as data processing and analysis complete the pipeline.

Serum neurofilament light chain levels reflect cortical neurodegeneration in de novo Parkinson's disease

INTRODUCTION

Cognitive impairment and dementia are highly prevalent non-motor complications in Parkinson's disease (PD) with deleterious consequences for patients and caregivers. With no treatment currently available, finding and validating minimally-invasive biomarkers of neurodegeneration in this population represents an urgent need for clinical trials targeting its prevention or delay. Recently, serum neurofilament light chain (NfL) levels have been identified as a promising biomarker of neural loss, but whether they reflect cortical neurodegeneration in early PD stages has not been addressed.

METHODS

From the Parkinson's Progression Markers Initiative (PPMI), we selected 133 de novo PD patients and 56 healthy controls (HC) with available structural neuroimaging and serum NfL data. We then studied whether NfL levels were abnormal in the PD group with respect to HC, and whether they correlated with cognitive indicators and cortical macro (cortical thinning) and microstructural (increased intracortical mean diffusivity) degeneration.

RESULTS

Serum NfL levels were significantly increased in the PD group (p = 0.010), and were also related to worse cognitive performance and a cortical macro and microstructural compromise (p < 0.05 corrected). These associations were observed both cross-sectionally and longitudinally within a one-year follow-up period. Topographically, NfL levels reflected posterior-cortical deterioration rather than frontal damage. Importantly, NfL levels were not associated with striatal SPECT-DAT uptake or β-amyloid burden.

DISCUSSION

Our results show that serum NfL levels reflect cortical neurodegeneration from the very early stages of PD. Moreover, its brain structural correlates and its lack of relationship with dopaminergic depletion or amyloidosis suggests that NfL could track the underlying pathological process leading to PD dementia.

Blood Contamination in CSF and Its Impact on Quantitative Analysis of Alpha-Synuclein

Analysis of cerebrospinal fluid (CSF) is important for diagnosis of neurological diseases. Especially for neurodegenerative diseases, abnormal protein abundance in CSF is an important biomarker. However, the quality of CSF is a key factor for the analytic outcome. Any external contamination has tremendous impact on the analysis and the reliability of the results. In this study, we evaluated the effect of blood contamination in CSF with respect to protein biomarker identification. We compared three distinct measures: Combur10-Test^® strips, a specific hemoglobin ELISA, and bottom-up mass spectrometry (MS)-based proteomics for the determination of the general blood contamination level. In parallel, we studied the impact of blood contamination on the detectability of alpha-synuclein (aSyn), a highly abundant protein in blood/erythrocytes and a potential biomarker for Parkinson’s disease. Comparable results were achieved, with all three approaches enabling detection of blood levels in CSF down to 0.001%. We found higher aSyn levels with increasing blood contamination, highlighting the difficulty of authentic quantification of this protein in CSF. Based on our results, we identified other markers for blood contamination beyond hemoglobin and defined a grading system for blood levels in CSF samples, including a lower limit of tolerable blood contamination for MS-based biomarker studies.

Skeletal muscle transcriptional networks linked to type I myofiber grouping in Parkinson's disease

Parkinson's disease (PD) is a common neurodegenerative disorder impacting cognition, movement, and quality of life in >10 million individuals worldwide. We recently characterized and quantified a skeletal muscle pathology in PD represented by exaggerated type I myofiber grouping presumed to result from denervation-reinnervation processes. Our previous findings indicated that impaired neuromuscular junction integrity may be involved in type I grouping, which is associated with excessive motor unit activation during weight-bearing tasks. In this study, we performed transcriptional profiling to test the hypothesis that type I grouping severity would link to distinct gene expression networks. We generated transcriptome-wide poly(A) RNA-Seq data from skeletal muscle of individuals with PD [n = 12 (9 men, 3 women); 67 ± 2 yr], age- and sex-matched older adults (n = 12; 68 ± 2 yr), and sex-matched young adults (n = 12; 30 ± 1 yr). Differentially expressed genes were evaluated across cohorts. Weighted gene correlation network analysis (WGCNA) was performed to identify gene networks most correlated with indicators of abnormal type I grouping. Among coexpression networks mapping to phenotypes pathologically increased in PD muscle, one network was highly significantly correlated to type I myofiber group size and another to percentage of type I myofibers found in groups. Annotation of coexpressed networks revealed that type I grouping is associated with altered expression of genes involved in neural development, postsynaptic signaling, cell cycle regulation and cell survival, protein and energy metabolism, inflammation/immunity, and posttranscriptional regulation (microRNAs). These transcriptomic findings suggest that skeletal muscle may play an active role in signaling to promote myofiber survival, reinnervation, and remodeling, perhaps to an extreme in PD.NEW & NOTEWORTHY Despite our awareness of the impact of Parkinson's disease (PD) on motor function for over two centuries, limited attention has focused on skeletal muscle. We previously identified type I myofiber grouping, a novel indicator of muscle dysfunction in PD, presumably a result of heightened rates of denervation/reinnervation. Using transcriptional profiling to identify networks associated with this phenotype, we provide insight into potential mechanistic roles of skeletal muscle in signaling to promote its survival in PD.

NfL (Neurofilament Light Chain) Levels as a Predictive Marker for Long-Term Outcome After Ischemic Stroke

Background and Purpose—

Ischemic stroke causes major disability as a consequence of neuronal loss and recurrent ischemic events. Biomarkers predicting tissue damage or stroke recurrence might be useful to guide an individualized stroke therapy. NfL (neurofilament light chain) is a promising biomarker that might be used for this purpose.

Methods—

We used individual data of patients with an acute ischemic stroke and clinical long term follow-up. Serum NfL (sNfL) was quantified within 24 hours after admission and after 1 year and compared with other biomarkers (GDF15 [growth differentiation factor 15], S100, NT-proBNP [N-terminal pro-B-type natriuretic peptide], ANP [atrial natriuretic peptide], and FABP [fatty acid–binding protein]). The primary end point was functional outcome after 90 days and cerebrovascular events and death (combined cardiovascular end point) within 36 months of follow-up.

Results—

Two hundred eleven patients (mean age, 68.7 years; SD, ±12.6; 41.2% women) with median clinical severity on the National Institutes of Health Stroke Scale (NIHSS) score of 3 (interquartile range, 1–5) and long-term follow-up with a median of 41.8 months (interquartile range, 40.0–44.5) were prospectively included. We observed a significant correlation between sNfL and NIHSS at hospital admission (r=0.234; P <0.001). sNfL levels increased with the grade of age-related white matter changes ( P <0.001) and were able to predict unfavorable clinical outcome (modified Rankin Scale score, ≥2) 90 days after stroke (odds ratio [OR], 1.562; 95% CI, 1.003–2.433; P =0.048) together with NIHSS (OR, 1.303; 95% CI, 1.164–1.458; P <0.001) and age-related white matter change rating (severe; OR, 3.326; 95% CI, 1.186–9.326; P =0.022). Similarly, sNfL was valuable for the prediction of the combined cardiovascular end point (OR, 2.002; 95% CI, 1.213–3.302; P =0.007), besides NIHSS (OR, 1.110; 95% CI, 1.000–1.232; P =0.049), diabetes mellitus (OR, 2.942; 95% CI, 1.306–6.630; P =0.005), and age-related white matter change rating (severe; OR, 4.816; 95% CI, 1.206–19.229; P =0.026) after multivariate regression analysis. Kaplan-Meier analysis revealed significantly more combined cardiovascular end points (18 [14.1%] versus 38 [45.8%], log-rank test P <0.001) during long-term follow-up in patients with elevated sNfL levels.

Conclusions—

sNFL is a valuable biomarker for functional independence 90 days after ischemic stroke and predicts cardiovascular long-term outcome.

Clinical Trial Registration—

URL: http://www.isrctn.com . Unique identifier: ISRCTN 46104198.

Chronic nigral neuromodulation aggravates behavioral deficits and synaptic changes in an α-synuclein based rat model for Parkinson's disease

Aggregation of alpha-synuclein (α-SYN) is the pathological hallmark of several diseases named synucleinopathies, including Parkinson's disease (PD), which is the most common neurodegenerative motor disorder. Alpha-SYN has been linked to synaptic function both in physiological and pathological conditions. However, the exact link between neuronal activity, α-SYN toxicity and disease progression in PD is not clear. In this study, we aimed to investigate the effect of chronic neuromodulation in an α-SYN-based rat model for PD using chemogenetics. To do this, we expressed excitatory Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) combined with mutant A53T α-SYN, using two different recombinant adeno-associated viral (rAAV) vectors (serotypes 2/7 and 2/8) in rat substantia nigra (SN) and investigated the effect on motor behavior, synapses and neuropathology. We found that chronic neuromodulation aggravates motor deficits induced by α-SYN, without altering dopaminergic neurodegeneration. In addition, neuronal activation led to changes in post-translational modification and subcellular localization of α-SYN, linking neuronal activity to the pathophysiological role of α-SYN in PD.

Differential proteomic analysis of serum exosomes reveals alterations in progression of Parkinson disease

Exosomes are nanometer-sized vesicles with intercellular communication functions, and their encapsulated proteins may participate in the pathological process of neurodegenerative disorders. The aim of this study was to identify the protein changes of serum exosomes in Parkinson disease (PD) patients with different disease progress types, and to identify potential biomarkers. The exosomes of PD patients with different severity and healthy control group were isolated from serum. The exosome proteins were analyzed by mass spectrometry with label-free quantitative proteomics. A total of 429 proteins were identified, of which 14 were significantly different in mild and severe PD patients. The expression levels of 7 proteins, including pigmented epithelium-derived factor, afamin, apolipoprotein D and J, were significantly increased in PD patients. The expression levels of 7 proteins, including complement C1q and protein Immunoglobulin Lambda Variable 1-33 (IGLV1-33)Cluster -33, were decreased in PD patients. These differentially expressed proteins were analyzed by gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, which confirmed that the interaction between prion diseases and ECM receptors was the most significant pathways of enrichment. The changes of proteins and pathways may be related to the pathophysiological mechanism of PD. Therefore, some of these proteins could be considered as potential biomarkers for early PD diagnosis.

Mediterranean Diet in Preventing Neurodegenerative Diseases

PURPOSE OF REVIEW

We reviewed the most recent literature examining the associations between the Mediterranean-style diet (MD), neurodegenerative diseases, and markers and mechanisms of neurodegeneration.

RECENT FINDINGS

Most, but not all, epidemiologic studies report a protective association between MD adherence, cognitive impairment, and brain health. Data from clinical trials supporting these observational findings are also emerging. Limited evidence suggests that MD adherence may be protective for Parkinson's disease risk. Mechanistically, plant polyphenols may activate similar molecular pathways as caloric restriction diets, which helps explain the neuroprotective properties of the MD. Evidence for cognitive disorders is abundant, but there is a dearth of literature for other neurodegenerative disorders and for markers of neurodegeneration. Further research is needed to elucidate the protective role of MD on neurodegeneration, the most salient components of the MD, and the most sensitive time periods over the lifecourse at which the MD may exert its effects.

Synaptic markers of cognitive decline in neurodegenerative diseases: a proteomic approach

See Attems and Jellinger (doi:10.1093/brain/awx360) for a scientific commentary on this article.Cognitive changes occurring throughout the pathogenesis of neurodegenerative diseases are directly linked to synaptic loss. We used in-depth proteomics to compare 32 post-mortem human brains in the prefrontal cortex of prospectively followed patients with Alzheimer's disease, Parkinson's disease with dementia, dementia with Lewy bodies and older adults without dementia. In total, we identified 10 325 proteins, 851 of which were synaptic proteins. Levels of 25 synaptic proteins were significantly altered in the various dementia groups. Significant loss of SNAP47, GAP43, SYBU (syntabulin), LRFN2, SV2C, SYT2 (synaptotagmin 2), GRIA3 and GRIA4 were further validated on a larger cohort comprised of 92 brain samples using ELISA or western blot. Cognitive impairment before death and rate of cognitive decline significantly correlated with loss of SNAP47, SYBU, LRFN2, SV2C and GRIA3 proteins. Besides differentiating Parkinson's disease dementia, dementia with Lewy bodies, and Alzheimer's disease from controls with high sensitivity and specificity, synaptic proteins also reliably discriminated Parkinson's disease dementia from Alzheimer's disease patients. Our results suggest that these particular synaptic proteins have an important predictive and discriminative molecular fingerprint in neurodegenerative diseases and could be a potential target for early disease intervention.

Biomarkers of Parkinson's disease: 20 years later

Despite intensive effort, biomarker research for the detection of prodromal stage, diagnosis and progression of Parkinson's disease (PD) falls short of expectations. This article reviews the attempts in the last 20 years to find a biomarker, addresses challenges along the biomarker search and suggests the steps that should be taken to overcome these challenges. Although several biomarkers are currently available, none of them is specific enough for diagnosis, prediction of future PD or disease progression. The main reason for the failure finding a strong biomarker seems to be drastic heterogeneity of PD, which exhibits itself in all domains; from the clinic to pathophysiology or genetics. The diversity in patient selection, assessment methods or outcomes in biomarker studies also limit the interpretation and generalizability of the data. In search of a reliable biomarker, consideration of novel approaches encompassing individual demographic, clinical, genetic, epigenetic and environmental differences, employment of strategies enabling marker combinations, designing multicenter studies with compatible assessment methods, integration of data from preclinical domains and utilization of novel technology-based assessments are necessary.

Cerebrospinal fluid biomarker for Parkinson's disease: An overview

In Parkinson's disease (PD), there is a wide field of recent and ongoing search for useful biomarkers for early and differential diagnosis, disease monitoring or subtype characterization. Up to now, no biofluid biomarker has entered the daily clinical routine. Cerebrospinal fluid (CSF) is often used as a source for biomarker development in different neurological disorders because it reflects changes in central-nervous system homeostasis. This review article gives an overview about different biomarker approaches in PD, mainly focusing on CSF analyses. Current state and future perspectives regarding classical protein markers like alpha‑synuclein, but also different "omics" techniques are described. In conclusion, technical advancements in the field already yielded promising results, but further multicenter trials with well-defined cohorts, standardized protocols and integrated data analysis of different modalities are needed before successful translation into routine clinical application.

Proteomic analysis of protein homeostasis and aggregation

Protein homeostasis (proteostasis) refers to the ability of cells to preserve the correct balance between protein synthesis, folding and degradation. Proteostasis is essential for optimal cell growth and survival under stressful conditions. Various extracellular and intracellular stresses including heat shock, oxidative stress, proteasome malfunction, mutations and aging-related modifications can result in disturbed proteostasis manifested by enhanced misfolding and aggregation of proteins. To limit protein misfolding and aggregation cells have evolved various strategies including molecular chaperones, proteasome system and autophagy. Molecular chaperones assist folding of proteins, protect them from denaturation and facilitate renaturation of the misfolded polypeptides, whereas proteasomes and autophagosomes remove the irreversibly damaged proteins. The impairment of proteostasis results in protein aggregation that is a major pathological hallmark of numerous age-related disorders, such as cataract, Alzheimer's, Parkinson's, Huntington's, and prion diseases. To discover protein markers and speed up diagnosis of neurodegenerative diseases accompanied by protein aggregation, proteomic tools have increasingly been used in recent years. Systematic and exhaustive analysis of the changes that occur in the proteomes of affected tissues and biofluids in humans or in model organisms is one of the most promising approaches to reveal mechanisms underlying protein aggregation diseases, improve their diagnosis and develop therapeutic strategies. Significance: In this review we outline the elements responsible for maintaining cellular proteostasis and present the overview of proteomic studies focused on protein-aggregation diseases. These studies provide insights into the mechanisms responsible for age-related disorders and reveal new potential biomarkers for Alzheimer's, Parkinson's, Huntigton's and prion diseases.

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.

Machine Learning Reveals Protein Signatures in CSF and Plasma Fluids of Clinical Value for ALS

We use shotgun proteomics to identify biomarkers of diagnostic and prognostic value in individuals diagnosed with amyotrophic lateral sclerosis. Matched cerebrospinal and plasma fluids were subjected to abundant protein depletion and analyzed by nano-flow liquid chromatography high resolution tandem mass spectrometry. Label free quantitation was used to identify differential proteins between individuals with ALS (n = 33) and healthy controls (n = 30) in both fluids. In CSF, 118 (p-value < 0.05) and 27 proteins (q-value < 0.05) were identified as significantly altered between ALS and controls. In plasma, 20 (p-value < 0.05) and 0 (q-value < 0.05) proteins were identified as significantly altered between ALS and controls. Proteins involved in complement activation, acute phase response and retinoid signaling pathways were significantly enriched in the CSF from ALS patients. Subsequently various machine learning methods were evaluated for disease classification using a repeated Monte Carlo cross-validation approach. A linear discriminant analysis model achieved a median area under the receiver operating characteristic curve of 0.94 with an interquartile range of 0.88–1.0. Three proteins composed a prognostic model (p = 5e-4) that explained 49% of the variation in the ALS-FRS scores. Finally we investigated the specificity of two promising proteins from our discovery data set, chitinase-3 like 1 protein and alpha-1-antichymotrypsin, using targeted proteomics in a separate set of CSF samples derived from individuals diagnosed with ALS (n = 11) and other neurological diseases (n = 15). These results demonstrate the potential of a panel of targeted proteins for objective measurements of clinical value in ALS.

Unveiling the olfactory proteostatic disarrangement in Parkinson's disease by proteome-wide profiling

Olfactory dysfunction is one of the earliest features in Lewy-type alpha-synucleinopathies (LTSs) such as Parkinson's disease (PD). However, the underlying molecular mechanisms associated to smell impairment are poorly understood. Applying mass spectrometry-based quantitative proteomics in postmortem olfactory bulbs across limbic, early-neocortical, and neocortical LTS stages of parkinsonian patients, a proteostasis impairment, was observed, identifying 268 differentially expressed proteins between controls and PD phenotypes. In addition, network-driven proteomics revealed a modulation in ERK1/2, MKK3/6, and PDK1/PKC signaling axes. Moreover, a cross-disease study of selected olfactory molecules in sporadic Alzheimer's disease (AD) cases revealed different protein derangements in the modulation of secretagogin (SCGN), calcyclin-binding protein (CACYBP), and glucosamine 6 phosphate isomerase 2 (GNPDA2) between PD and AD. An inverse correlation between GNPDA2 and α-synuclein protein levels was also reflected in PD cerebrospinal fluid. Interestingly, PD patients exhibited significantly lower serum GNPDA2 levels than controls (n = 82/group). Our study provides important avenues for understanding the olfactory bulb proteostasis imbalance in PD, deciphering mechanistic clues to the equivalent smell deficits observed in AD and PD pathologies.

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.

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

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

Cerebrospinal Fluid Concentrations of Neuronal Proteins Are Reduced in Primary Angiitis of the Central Nervous System

Primary angiitis of the central nervous system (PACNS) is a rare autoimmune vasculitis limited to the CNS often causing substantial disability. Understanding of this disease is impaired by the lack of available biomaterial. Here, we collected cerebrospinal fluid (CSF) from patients with PACNS and matched controls and performed unbiased proteomics profiling using ion mobility mass spectrometry to identify novel disease mechanisms and candidate biomarkers. We identified 14 candidate proteins, including amyloid-beta A4 protein (APP), with reduced abundance in the CSF of PACNS patients and validated APP by Enzyme-linked Immunosorbent Assay (ELISA) in an extended cohort of patients with PACNS. Subsequent functional annotation surprisingly suggested neuronal pathology rather than immune activation in PACNS. Our study is the first to employ mass spectrometry to local immune reactions in PACNS and it identifies candidates such as APP with pathogenic relevance in PACNS to improve patient care in the future.

Cerebrospinal fluid and blood biomarkers for neurodegenerative dementias: An update of the Consensus of the Task Force on Biological Markers in Psychiatry of the World Federation of Societies of Biological Psychiatry

In the 12 years since the publication of the first Consensus Paper of the WFSBP on biomarkers of neurodegenerative dementias, enormous advancement has taken place in the field, and the Task Force takes now the opportunity to extend and update the original paper. New concepts of Alzheimer's disease (AD) and the conceptual interactions between AD and dementia due to AD were developed, resulting in two sets for diagnostic/research criteria. Procedures for pre-analytical sample handling, biobanking, analyses and post-analytical interpretation of the results were intensively studied and optimised. A global quality control project was introduced to evaluate and monitor the inter-centre variability in measurements with the goal of harmonisation of results. Contexts of use and how to approach candidate biomarkers in biological specimens other than cerebrospinal fluid (CSF), e.g. blood, were precisely defined. Important development was achieved in neuroimaging techniques, including studies comparing amyloid-β positron emission tomography results to fluid-based modalities. Similarly, development in research laboratory technologies, such as ultra-sensitive methods, raises our hopes to further improve analytical and diagnostic accuracy of classic and novel candidate biomarkers. Synergistically, advancement in clinical trials of anti-dementia therapies energises and motivates the efforts to find and optimise the most reliable early diagnostic modalities. Finally, the first studies were published addressing the potential of cost-effectiveness of the biomarkers-based diagnosis of neurodegenerative disorders.

Alpha-synuclein is present in dental calculus but not altered in Parkinson's disease patients in comparison to controls

INTRODUCTION

In autopsy cases staged for sporadic Parkinson's disease (PD), the neuropathology is characterized by a preclinical phase that targets the enteric nervous system of the gastrointestinal tract (GIT). Therefore, the ENS might be a source of potential (presymptomatic) PD biomarkers.

METHODS

In this clinically based study, we examined the alpha-synuclein (αSyn) concentration in an easily accessible protein storage medium of the GIT, dental calculus, in 21/50 patients with PD and 28/50 age- and gender-matched controls using ELISA.

RESULTS

αSyn was detectable in dental calculus and the median concentration in the control patients was 8.6 pg/mg calculus (interquartile range 2.6-13.1 pg/mg). αSyn concentrations were significantly influenced by blood contamination and samples with a hemoglobin concentration of > 4000 ng/mL were excluded. There was no significant difference of αSyn concentrations in the dental calculus of PD patients (5.76 pg/mg, interquartile range 2.91-9.74 pg/mg) compared to those in controls (p = 0.40).

CONCLUSION

The total αSyn concentration in dental calculus is not a suitable biomarker for sporadic PD. Disease-related variants such as oligomeric or phosphorylated αSyn in calculus might prove to be more specific.

Regulatory-accepted drug development tools are needed to accelerate innovative CNS disease treatments

Central Nervous System (CNS) diseases represent one of the most challenging therapeutic areas for successful drug approvals. Developing quantitative biomarkers as Drug Development Tools (DDTs) can catalyze the path to innovative treatments, and improve the chances of drug approvals. Drug development and healthcare management requires sensitive, reliable, validated, and regulatory accepted biomarkers and endpoints. This review highlights the regulatory paths and considerations for developing DDTs required to advance biomarker and endpoint use in clinical development (e.g., consensus CDISC [Clinical Data Interchange Standards Consortium] data standards, precompetitive sharing of anonymized patient-level data, and continual alignment with regulators). Summarized is the current landscape of biomarkers in a range of CNS diseases including Alzheimer disease, Parkinson Disease, Amyotrophic Lateral Sclerosis, Autism Spectrum Disorders, Depression, Huntington's disease, Multiple Sclerosis and Traumatic Brain Injury. Advancing DDTs for these devastating diseases that are both validated and qualified will require an integrated, cross-consortium approach to accelerate the delivery of innovative CNS therapeutics.

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.

Comparison of Internal Standard Approaches for SRM Analysis of Alpha-Synuclein in Cerebrospinal Fluid

Absolute protein quantification by selected reaction monitoring (SRM, also MRM) is an alternative to immunoassays, and the gold standard here is the addition of stable-isotope labeled (SIL) proteins (PSAQ). Cerebrospinal fluid (CSF) is the preferred source of biomarkers for neurological diseases, and recent improvements in mass spectrometry enable the quantification of disease-relevant proteins in CSF. We used alpha-synuclein SRM to investigate alternatives to the PSAQ approach in human CSF regarding precision and accuracy, including SIL peptides, winged SIL (WiSIL) peptides, and quantitative protein epitope signature tags (QPrESTs). All approaches yielded precise results in CSF with CV values <15% in several runs for all four measured peptides. PSAQ and QPrEST also showed good accuracy (deviation ≤15%), whereas SIL and WiSIL peptides yielded deviations up to 54% that greatly depended on the measured peptide. Total protein concentration in CSF did not affect precision and accuracy. Thus, our study indicates that all four approaches are suitable for relative quantification of alpha-synuclein in CSF. QPrESTs are a valuable alternative to PSAQ in terms of precision and accuracy, although SIL and WiSIL peptides can yield accurate results as well when peptides are selected consciously.

Decreased serum proNGF concentration in patients with Parkinson's disease

Parkinson's disease (PD), a progressive and age-related neurodegenerative condition, is a common neurodegenerative disorder. However, no validated biomarkers for PD have been identified to date. Accumulating evidence supports the role of proNGF-p75NTR-sortilin signaling in the neurodegeneration and pathogenesis of PD. The aim of our study was to investigate alterations in serum proNGF concentrations in PD patients and related anxiety. Seventy-seven consecutive PD patients and 39 healthy controls were enrolled, and clinical data were collected. Modified Hoehn-Yahr Staging Scale, Unified Parkinson's Disease Rating Scale (UPDRS), and Hamilton Anxiety (HAMA) Scale scores were assessed upon admission. Serum proNGF concentration was compared between that of PD patients and healthy controls. Pearson correlation coefficients were determined to explore the relationship between proNGF concentration and UPDRS, Hoehn-Yahr, and HAMA scores. Received operating characteristic (ROC) curves and proNGF optimal cutoff point were used to distinguish PD and related anxiety. The median concentration of proNGF was significantly lower (p = 0.000) in PD patients (94.91 ng/L, range 85.92-118.06 ng/L) compared with that of healthy controls (106.67 ng/L, range 102.39-122.06 ng/L). The optimal proNGF cutoff point for distinguishing PD patients was 102.29 ng/L, and the sensitivity and specificity values were 87.0 and 100%, respectively. proNGF concentration positively correlated with UPDRS (r = 0.281, p = 0.013), Hoehn-Yahr (r = 0.260, p = 0.023), and HAMA (r = 0.276, p = 0.015) scores. Our results indicate that serum proNGF concentration may represent a biomarker for PD and its role in the pathogenesis of PD thus warrants further investigation.

An iTRAQ-based proteomic analysis reveals dysregulation of neocortical synaptopodin in Lewy body dementias

Lewy body dementias are the second most common cause of neurodegenerative dementia in the elderly after Alzheimer's disease (AD). The two clinical subgroups of Lewy body dementias, namely, dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD), are differentiated by the chronology of cognitive symptoms relative to parkinsonism. At present, there remains a debate on whether DLB and PDD are separate disease entities, or fall within the same spectrum of Lewy body dementias. In this study, we compared the detergent-soluble proteome via an 8-plex isobaric tag for relative and absolute quantitation (iTRAQ) analysis of pooled lysates from the prefrontal cortex (BA9) of DLB (n = 19) and PDD (n = 21) patients matched a priori for amyloid (total Aβ42) burden, semi-quantitative scores for Lewy bodies and neurofibrillary tangles together with age-matched control (n = 21) subjects. A total of 1914 proteins were confidently identified by iTRAQ (false discovery rate = 0%). None of the proteins showed a significant yet opposite regulation in between DLB and PDD when compared to aged controls in the proteomic data set as well as following immunoblot analysis of the pooled and individual lysates involving all 61 subjects. The postsynaptic protein, synaptopodin (SYNPO) was significantly down-regulated in both DLB and PDD subgroups, suggesting a defective synaptic transmission in the demented patients. In conclusion, the largely similar proteome of DLB and PDD matched for amyloid burden suggests that variations in concomitant AD-related pathology, abnormal post-translational modifications or protein-protein interactions, defective intracellular trafficking or misfolding of proteins could play a part in driving the clinically observed differences between these two subgroups of Lewy body dementias. This further indicates that amyloid-targeting therapeutic strategies may show different efficacies in DLB versus PDD.

Recent advances in applying mass spectrometry and systems biology to determine brain dynamics

INTRODUCTION

Neurological disorders encompass various pathologies which disrupt normal brain physiology and function. Poor understanding of their underlying molecular mechanisms and their societal burden argues for the necessity of novel prevention strategies, early diagnostic techniques and alternative treatment options to reduce the scale of their expected increase. Areas covered: This review scrutinizes mass spectrometry based approaches used to investigate brain dynamics in various conditions, including neurodegenerative and neuropsychiatric disorders. Different proteomics workflows for isolation/enrichment of specific cell populations or brain regions, sample processing; mass spectrometry technologies, for differential proteome quantitation, analysis of post-translational modifications and imaging approaches in the brain are critically deliberated. Future directions, including analysis of cellular sub-compartments, targeted MS platforms (selected/parallel reaction monitoring) and use of mass cytometry are also discussed. Expert commentary: Here, we summarize and evaluate current mass spectrometry based approaches for determining brain dynamics in health and diseases states, with a focus on neurological disorders. Furthermore, we provide insight on current trends and new MS technologies with potential to improve this analysis.

An alpha-synuclein MRM assay with diagnostic potential for Parkinson's disease and monitoring disease progression

AIM

The alpha-synuclein (α-syn) level in human cerebrospinal fluid (CSF), as measured by immunoassays, is promising as a Parkinson's disease (PD) biomarker. However, the levels of total α-syn are inconsistent among studies with large cohorts and different measurement platforms. Total α-syn level also does not correlate with disease severity or progression. Here, the authors developed a highly sensitive MRM method to measure absolute CSF α-syn peptide concentrations without prior enrichment or fractionation, aiming to discover new candidate biomarkers.

RESULTS

Six peptides covering 73% of protein sequence were reliably identified, and two were consistently quantified in cross-sectional and longitudinal cohorts. Absolute concentration of α-syn in human CSF was determined to be 2.1 ng/mL. A unique α-syn peptide, TVEGAGSIAAATGFVK (81-96), displayed excellent correlation with previous immunoassay results in two independent PD cohorts (p < 0.001), correlated with disease severity, and its changes significantly tracked the disease progression longitudinally.

CONCLUSIONS

An MRM assay to quantify human CSF α-syn was developed and optimized. Sixty clinical samples from cross-sectional and longitudinal PD cohorts were analyzed with this approach. Although further larger scale validation is needed, the results suggest that α-syn peptide could serve as a promising biomarker in PD diagnosis and progression.

Proteomic Biomarker Identification in Cerebrospinal Fluid for Leptomeningeal Metastases with Neurological Complications

Leptomeningeal metastases (LM) from solid tumours, lymphoma and leukaemia are characterized by multifocal neurological deficits with a high mortality rate. Early diagnosis and initiation of treatment are essential to kerb neurological deterioration. However, this is not always possible as 25% of cerebrospinal fluid samples produce false-negative results at first cytological examination. The identification of biomarkers that allow stratification of individuals according to risk for developing LM would be a major benefit. Proteomic-based approaches are now in increasing use for this purpose, and these are reviewed in this chapter with a focus on cerebrospinal fluid (CSF) analyses. The construction of a CSF proteome disease database would also facilitate analysis of other neurological disorders.

Unmet needs in Parkinson's disease: New horizons in a changing landscape

The success of levodopa and other classes of drugs have meant that most people with Parkinson's disease enjoy a good quality of life for many years. However, despite the availability of several drugs and formulations that can be used as monotherapy and in combination, there are a number of disease features that the current therapies are unable to address. The disease continues to progress despite treatment, patients suffer from a myriad of motor and non-motor symptoms, and a neuroprotective therapy is urgently required. To move forward with medical and surgical management, it is important to consider new insights that recent research offers and in this review we examine how a better understanding of the disease pathology and progression might improve and enrich our daily clinical practice. It is also timely to consider the service provision changes that will increasingly be needed to effectively manage the needs of the aging population.

Alpha-, Beta-, and Gamma-synuclein Quantification in Cerebrospinal Fluid by Multiple Reaction Monitoring Reveals Increased Concentrations in Alzheimer's and Creutzfeldt-Jakob Disease but No Alteration in Synucleinopathies

α-Synuclein (αSyn) is a major constituent of proteinaceous aggregates in neurodegenerative diseases such as Parkinson's disease (PD) and a potential biomarker candidate for diagnosis and treatment effects. However, studies about αSyn in cerebrospinal fluid (CSF) in diseases are inconsistent and mainly based on immunological assays. Quantitative information about β-synuclein (βSyn) and γ-synuclein (γSyn) in CSF is not available.Here, we present an alternative method for the simultaneous quantification of αSyn, βSyn and γSyn in CSF by multiple reaction monitoring (MRM) with a high sequence coverage (70%) of αSyn to validate previous, ELISA-based results and characterize synucleins in CSF in more detail.The MRM has high sensitivity in the low pg/ml range (3-30pg/ml full-length αSyn) using 200 μl CSF. A high portion of CSF αSyn is present in the N-terminally acetylated form and the concentration of unmodified peptides in the nonamyloid component region is about 40% lower than in the N-terminal region. Synuclein concentrations show a high correlation with each other in CSF (r>0.80) and in contrast to αSyn and γSyn, βSyn is not affected by blood contamination. CSF αSyn, βSyn and γSyn concentrations were increased in Alzheimer's and Creutzfeldt-Jakob disease but not altered in PD, PD dementia (PDD), Lewy body dementia and atypical parkinsonian syndromes. The ratio βSyn/αSyn was increased in PDD (1.49 ± 0.38, p < 0.05) compared with PD (1.11 ± 0.26) and controls (1.15 ± 0.28). βSyn shows a high correlation with CSF tau concentrations (r = 0.86, p < 0.0001, n = 125).In conclusion, we could not confirm previous observations of reduced αSyn in PD and our results indicate that CSF synuclein concentrations are rather general markers of synaptic degeneration than specific for synucleinopathies. βsyn is an attractive biomarker candidate that might be used as an alternative to or in combination with tau in AD and CJD diagnosis and in combination with αSyn it is a biomarker candidate for PDD.