Discovery, validation and optimization of cerebrospinal fluid biomarkers for use in Parkinson's disease

Diagnostic metabolomic profiling of Parkinson's disease biospecimens

BACKGROUND

Reliable and sensitive biomarkers are needed for enhancing and predicting Parkinson's disease (PD) diagnosis.

OBJECTIVE

To investigate comprehensive metabolomic profiling of biochemicals in CSF and serum for determining diagnostic biomarkers of PD.

METHODS

Fifty subjects, symptomatic with PD for ≥5 years, were matched to 50 healthy controls (HCs). We used ultrahigh-performance liquid chromatography linked to tandem mass spectrometry (UHPLC-MS/MS) for measuring relative concentrations of ≤1.5 kDalton biochemicals. A reference library created from authentic standards facilitated chemical identifications. Analytes underwent univariate analysis for PD association, with false discovery rate-adjusted p-value (≤0.05) determinations. Multivariate analysis (for identifying a panel of biochemicals discriminating PD from HCs) used several biostatistical methods, including logistic LASSO regression.

RESULTS

Comparing PD and HCs, strong differentiation was achieved from CSF but not serum specimens. With univariate analysis, 21 CSF compounds exhibited significant differential concentrations. Logistic LASSO regression led to selection of 23 biochemicals (11 shared with those determined by the univariate analysis). The selected compounds, as a group, distinguished PD from HCs, with Area-Under-the-Receiver-Operating-Characteristic (ROC) curve of 0.897. With optimal cutoff, logistic LASSO achieved 100% sensitivity and 96% specificity (and positive and negative predictive values of 96% and 100%). Ten-fold cross-validation gave 84% sensitivity and 82% specificity (and 82% positive and 84% negative predictive values). From the logistic LASSO-chosen regression model, 2 polyamine metabolites (N-acetylcadaverine and N-acetylputrescine) were chosen and had the highest fold-changes in comparing PD to HCs. Another chosen biochemical, acisoga (N-(3-acetamidopropyl)pyrrolidine-2-one), also is a polyamine metabolism derivative.

CONCLUSIONS

UHPLC-MS/MS assays provided a metabolomic signature highly predictive of PD. These findings provide further evidence for involvement of polyamine pathways in the neurodegeneration of PD.

Monogenetic Forms of Parkinson’s Disease – Bridging the Gap Between Genetics and Biomarkers

The therapy of neurodegenerative diseases such as Parkinson’s disease (PD) is still limited to the treatment of symptoms and primarily aimed at compensating for dopaminergic hypofunction. Numerous disease-modifying therapies currently in the pipeline attempt to modify the underlying pathomechanisms. In recent decades, the results of molecular genetics and biomarker research have raised hopes of earlier diagnosis and new neuroprotective therapeutic approaches. As the disease-causing processes in monogenetic forms of PD are better understood than in sporadic PD, these disease subsets are likely to benefit first from disease-modifying therapies. Recent studies have suggested that disease-relevant changes found in genetically linked forms of PD (i.e., PARK-LRRK2, PARK-GBA) can also be reproduced in patients in whom no genetic cause can be found, i.e., those with sporadic PD. It can, therefore, be assumed that as soon as the first causal therapy for genetic forms of PD is approved, more patients with PD will undergo genetic testing and counseling. Regarding future neuroprotective trials in neurodegenerative diseases and objective parameters such as biomarkers with high sensitivity and specificity for the diagnosis and course of the disease are needed. These biomarkers will also serve to monitor treatment success in clinical trials. Promising examples in PD, such as alpha-synuclein species, lysosomal enzymes, markers of amyloid and tau pathology, and neurofilament light chain, are under investigation in blood and CSF. This paper provides an overview of the opportunities and current limitations of monogenetic diagnostic and biomarker research in PD and aims to build a bridge between current knowledge and association with PD genetics and biomarkers.

Neurofilament Levels Are Reflecting the Loss of Presynaptic Dopamine Receptors in Movement Disorders

Aims: Neurofilament light chain (NfL) and phosphorylated neurofilament heavy chain (pNfH) are biomarkers for neuroaxonal damage. We assessed whether NfL and other biomarker levels in the CSF are correlated to the loss of presynaptic dopamine transporters in neurons as detected with dopamine transporter SPECT (DaTscan). Methods: We retrospectively identified 47 patients (17 Alzheimer's dementia, 10 idiopathic Parkinson's disease, 7 Lewy body dementia, 13 progressive supranuclear palsy or corticobasal degeneration) who received a DaTscan and a lumbar puncture. DaTscan imaging was performed according to current guidelines, and z-scores indicating the decrease in uptake were software based calculated for the nucleus caudatus and putamen. The CSF biomarkers progranulin, total-tau, alpha-synuclein, NfL, and pNfH were correlated with the z-scores. Results: DaTscan results in AD patients did not correlate with any biomarker. Subsuming every movement disorder with nigrostriatal neurodegeneration resulted in a strong correlation between putamen/nucleus caudatus and NfL (nucleus caudatus right p < 0.01, putamen right p < 0.05, left p < 0.05) and between pNfH and putamen (right p < 0.05; left p < 0.042). Subdividing in disease cohorts did not reveal significant correlations. Progranulin, alpha-synuclein, and total-tau did not correlate with DaTscan results. Conclusion: We show a strong correlation of NfL and pNfH with pathological changes in presynaptic dopamine transporter density in the putamen concomitant to nigrostriatal degeneration. This correlation might explain the reported correlation of impaired motor functions in PD and NfL as seen before, despite the pathological heterogeneity of these diseases.

CSF Diagnostics: A Potentially Valuable Tool in Neurodegenerative and Inflammatory Disorders Involving Motor Neurons: A Review

Cerebrospinal fluid (CSF) diagnostics has emerged as a valid tool for a variety of neurological diseases. However, CSF diagnostics has been playing a subordinate role in the diagnosis of many neurological conditions. Thus, in the multitude of neuromuscular diseases in which motor neurons are affected, a CSF sample is rarely taken routinely. However, CSF diagnostics has the potential to specify the diagnosis and monitor the treatment of neuromuscular disorders. In this review, we therefore focused on a variety of neuromuscular diseases, among them amyotrophic lateral sclerosis (ALS), peripheral neuropathies, and spinal muscular atrophy (SMA), for which CSF diagnostics has emerged as a promising option for determining the disease itself and its progression. We focus on potentially valuable biomarkers among different disorders, such as neurofilaments, cytokines, other proteins, and lipids to determine their suitability, differentiating between different neurological disorders and their potential to determine early disease onset, disease progression, and treatment outcome. We further recommend novel approaches, e.g., the use of mass spectrometry as a promising alternative techniques to standard ELISA assays, potentially enhancing biomarker significance in clinical applications.

CSF and Blood Biomarkers in Neuroinflammatory and Neurodegenerative Diseases: Implications for Treatment

Neuroinflammatory and neurodegenerative diseases are characterized by the interplay of a number of molecular pathways that can be assessed through biofluids, especially cerebrospinal fluid and blood. Accordingly, the definition and classification of these disorders will move from clinical and pathological to biological criteria. The consequences of this biomarker-based diagnostic and prognostic approach are highly relevant to the field of drug development. Indeed, in view of the availability of disease-modifying drugs, fluid biomarkers offer a unique opportunity for improving the quality and applicability of results from clinical trials. Herein, we discuss the benefits of using fluid biomarkers for patient stratification, target engagement, and outcome assessment, as well as the most recent developments in neuroinflammatory and neurodegenerative diseases.

Molecular profiling in Parkinsonian syndromes: CSF biomarkers

An accurate and early diagnosis of degenerative parkinsonian syndromes is a major need for their correct and timely therapeutic management. The current diagnostic criteria are mostly based on clinical features and molecular imaging. However, diagnostic doubts often persist especially in the early stages of diseases when signs are slight, ambiguous and overlapping among different syndromes. Molecular imaging may not be altered in the early stages of diseases, also failing to discriminate among different syndromes. Cerebrospinal fluid (CSF) represents an ideal source of biomarkers reflecting different pathways of neuropathological changes taking place in the brain and preceding the clinical onset. The aim of this review is to provide un update on CSF biomarkers in parkinsonian disorders, discussing in detail their association with neuropathological correlates. Their potential contribution in differential diagnosis and prognostic assessment of different parkinsonian syndromes is also discussed. Before entering the clinical use both for diagnostic and prognostic purposes, these CSF biomarkers need to be thoroughly assessed in terms of pre-analytical and analytical variability, as well as to clinical validation in independent cohorts.

The Challenge of Disease-Modifying Therapies in Parkinson's Disease: Role of CSF Biomarkers

The development of disease modifying strategies in Parkinson's disease (PD) largely depends on the ability to identify suitable populations after accurate diagnostic work-up. Therefore, patient molecular profiling and disease subtyping are mandatory. Thus far, in clinical trials, PD has been considered to be a "single entity". Conversely, in front of the common feature of nigro-striatal degeneration, PD is pathogenically heterogeneous with a series of several biological and molecular pathways that differently contribute to clinical development and progression. Currently available diagnostic criteria for PD mainly rely on clinical features and imaging biomarkers, thus missing to identify the contribution of pathophysiological pathways, also failing to catch abnormalities occurring in the early stages of disease. Cerebrospinal fluid (CSF) is a promising source of biomarkers, with the high potential for reflecting early changes occurring in PD brain. In this review, we provide an overview on CSF biomarkers in PD, discussing their association with different molecular pathways involved either in pathophysiology or progression in detail. Their potential application in the field of disease modifying treatments is also discussed.

CSF or serum neurofilament light added to α-Synuclein panel discriminates Parkinson's from controls

BACKGROUND

Neurofilament light chain is a marker of axonal damage and is of interest as a biofluid biomarker for PD. The objective of this study was to investigate whether CSF or serum neurofilament contributes to a combination of CSF biomarkers in defining the optimal biomarker panel for discriminating PD patients from healthy controls. In addition, we aimed to assess whether CSF and/or serum neurofilament levels are associated with clinical measures of disease severity.

METHODS

We measured neurofilament light chain levels in CSF and/or serum of 139 PD patients and 52 age-matched healthy controls. We used stepwise logistic regression analyses to test whether neurofilament contributes to a biomarker CSF panel including total, oligomeric, and phosphorylated α-synuclein and Alzheimer's disease biomarkers. Measures of disease severity included disease duration, UPDRS-III, Hoehn & Yahr stage, and MMSE.

RESULTS

After correcting for age, CSF neurofilament levels were 42% higher in PD patients compared with controls (P < 0.01), whereas serum neurofilament levels were 37% higher (P = 0.08). Combining CSF neurofilament, phosphorylated-/total α-synuclein, and oligomeric-/total α-synuclein yielded the best-fitting model for discriminating PD patients from controls (area under the curve 0.92). The discriminatory potential of serum neurofilament in the CSF biomarker panel was similar (area under the curve 0.90). Higher serum neurofilament was associated with a lower MMSE score. There were no other associations between CSF and/or serum neurofilament levels and clinical disease severity.

CONCLUSIONS

CSF neurofilament contributes to a panel of CSF α-synuclein species in differentiating PD patients from healthy controls. Serum neurofilament may have added value to a biofluid biomarker panel for differentiating PD patients from controls. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

DJ-1 in Parkinson's Disease: Clinical Insights and Therapeutic Perspectives

Mutations in the protein DJ-1 cause autosomal recessive forms of Parkinson’s disease (PD) and oxidized DJ-1 is found in the brains of idiopathic PD individuals. While several functions have been ascribed to DJ-1 (most notably protection from oxidative stress), its contribution to PD pathogenesis is not yet clear. Here we provide an overview of the clinical research to date on DJ-1 and the current state of knowledge regarding DJ-1 characterization in the human brain. The relevance of DJ-1 as a PD biomarker is also discussed, as are studies exploring DJ-1 as a possible therapeutic target for PD and neurodegeneration.

Dissecting the Interactions between Human Serum Albumin and α-Synuclein: New Insights on the Factors Influencing α-Synuclein Aggregation in Biological Fluids

α-Synuclein (α-syn) is found to be naturally present in biofluids such as cerebrospinal fluid (CSF) and serum. Human serum albumin (HSA) is the most abundant protein found in these biofluids, which, beyond transporting hormones and drugs, also exerts a chaperone-like activity binding other proteins in blood and inhibiting their aggregation. Contrasting results are reported in the literature about the effects of albumin on α-syn aggregation. We characterized the binding region of HSA on α-syn by high-field solution NMR spectroscopy and the effect of HSA on α-syn aggregation by thioflavin-T (ThT) fluorescence under both low-ionic-strength and physiological conditions at the albumin concentration in serum and CSF. We found that HSA, at the concentration found in human serum, slows the aggregation of α-syn significantly. α-Syn interacts with HSA in an ionic strength- and pH-dependent manner. The binding is driven by hydrophobic interactions at the N-terminus under physiological experimental conditions and by electrostatic interactions at the C-terminus at low ionic strength. This work provides novel information about the proteostasis of α-syn in biofluids and supports the hypothesis of a chaperone-like behavior of HSA.

Parkinson's and Lewy body dementia CSF biomarkers

The clinical diagnosis of Parkinson's disease (PD) and Dementia with Lewy bodies (DLB) is challenging due to highly variable clinical presentation and clinical and pathological overlap with other neurodegenerative diseases. Since cerebrospinal fluid (CSF) mirrors the pathological changes taking place in the brain, it represents a promising source of biomarkers. With respect to classical AD biomarkers, low CSF Aβ₄₂ levels have shown a robust prognostic value in terms of development of cognitive impairment in PD and DLB. In the differential diagnosis between AD and DLB, a potential role of t-tau, p-tau and Aβ₄₂/Aβ₃₈ ratio has been demonstrated. Regarding CSF α-synuclein (α-syn) species, lower levels of total α-synuclein (t-α-syn) and higher concentration of oligomeric-α-synuclein (o-α-syn) and phosphorylated α-synuclein (p-α-syn) have been observed in PD. Furthermore, the detection of "pro-aggregating" α-synuclein has enabled the discrimination of patients affected by synucleinopathies with high sensitivity and specificity. New promising biomarkers are emerging: GCase activity (reduced in PD and DLB patients vs. controls), CSF/serum albumin ratio (increased in PD and DLB), fatty-acid-binding protein (increased in AD and DLB vs. PD), visinin-like protein-1 (increased in AD vs. DLB) and monoamines (useful in differential diagnosis among PD and DLB). These encouraging results need to be confirmed by future studies.

Advances in the Research of Risk Factors and Prodromal Biomarkers of Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disease in the world. With the advent of an aging population and improving life expectancy worldwide, the number of PD patients is expected to increase, which may lead to an urgent need for effective preventive and diagnostic strategies for PD. Although there is increasing research regarding the pathogenesis of PD, there is limited knowledge regarding the prevention of PD. Moreover, the diagnosis of PD depends on clinical criteria, which require the occurrence of bradykinesia and at least one symptom of rest tremor or rigidity. However, converging evidence from clinical, genetic, neuropathological, and imaging studies suggests the initiation of PD-specific pathology prior to the initial presentation of these classical motor clinical features by years or decades. This latent stage of neurodegeneration in PD is a particularly important stage for effective neuroprotective therapies, which might retard the progression or prevent the onset of PD. Therefore, the exploration of risk factors and premotor biomarkers is not only crucial to the early diagnosis of PD but is also helpful in the development of effective neuroprotection and health care strategies for appropriate populations at risk for PD. In this review, we searched and summarized ∼249 researches and 31 reviews focusing on the risk factors and prodromal biomarkers of PD and published in MEDLINE.

Decreased Cerebrospinal Fluid Aβ42 in Patients with Idiopathic Parkinson's Disease and White Matter Lesions

BACKGROUND

Cerebral small vessel disease (SVD), often manifesting as white matter lesions (WMLs), and Parkinson's disease (PD) are common disorders whose prevalence increases with age. Vascular risk factors contribute to SVD, but their role in PD is less clear.

OBJECTIVES

The study objective was to investigate the frequency and grade of WMLs in PD, and their association with clinical and biochemical parameters.

METHODS

In total, 100 consecutive patients with available magnetic resonance imaging were included. Vascular risk factors including smoking, hypertension, diabetes type 2, atrial fibrillation, heart insufficiency and hypercholesterolemia were assessed. In 50 patients that had underwent lumbar puncture, cerebrospinal fluid (csf) levels of beta-amyloid1-42, tau and phospho-tau were measured.

RESULTS

WMLs were present in 86 of 100 patients. Increasing WML severity was independently associated with increased age and lower csf beta-amyloid1-42.

CONCLUSIONS

In our study, WMLs were very common in patients with PD, and were associated with low levels of csf beta-amyloid1-42. Longitudinal studies would increase understanding of the interplay between WMLs and amyloid pathology in PD.

Increased DJ-1 and α-Synuclein in Plasma Neural-Derived Exosomes as Potential Markers for Parkinson's Disease

The diagnosis of PD might be in difficulty, especially in the early stages. Therefore, the identification of novel biomarkers is imperative for the diagnosis and monitoring disease progression in PD. DJ-1 and α-synuclein, are two proteins that are critically involved in the pathogenesis of PD, and they have been examined as disease biomarkers in studies. However, no study exists regarding DJ-1 in plasma neural-derived exosomes. In the present study, the levels of DJ-1 and α-synuclein in plasma neural-derived exosomes were studied together in order to investigate novel biomarkers for PD. DJ-1 and α-synuclein in plasma and plasma neural-derived exosomes of the patients with PD and controls were quantified by ELISAs. The data revealed that the levels of DJ-1 and α-synuclein in plasma neural-derived exosomes and the ratio of plasma neural-derived exosomal DJ-1 to total DJ-1 were significantly higher in patients with PD, compared with controls, while levels of the two proteins in plasma exhibited no difference between the patients with PD and controls. However, no relationship was identified between biomarkers and disease progression. In addition, significant positive correlations between DJ-1 and α-synuclein in plasma neural-derived exosomes were found in the patients with PD and in healthy individuals. We hypothesize that DJ-1 in plasma neural-derived exosomes may be used as a potential biomarker as α-synuclein in PD and they might participate in the mechanism of PD together.

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

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

Robust Ensemble Classification Methodology for I123-Ioflupane SPECT Images and Multiple Heterogeneous Biomarkers in the Diagnosis of Parkinson's Disease

In last years, several approaches to develop an effective Computer-Aided-Diagnosis (CAD) system for Parkinson's Disease (PD) have been proposed. Most of these methods have focused almost exclusively on brain images through the use of Machine-Learning algorithms suitable to characterize structural or functional patterns. Those patterns provide enough information about the status and/or the progression at intermediate and advanced stages of Parkinson's Disease. Nevertheless this information could be insufficient at early stages of the pathology. The Parkinson's Progression Markers Initiative (PPMI) database includes neurological images along with multiple biomedical tests. This information opens up the possibility of comparing different biomarker classification results. As data come from heterogeneous sources, it is expected that we could include some of these biomarkers in order to obtain new information about the pathology. Based on that idea, this work presents an Ensemble Classification model with Performance Weighting. This proposal has been tested comparing Healthy Control subjects (HC) vs. patients with PD (considering both PD and SWEDD labeled subjects as the same class). This model combines several Support-Vector-Machine (SVM) with linear kernel classifiers for different biomedical group of tests—including CerebroSpinal Fluid (CSF), RNA, and Serum tests—and pre-processed neuroimages features (Voxels-As-Features and a list of defined Morphological Features) from PPMI database subjects. The proposed methodology makes use of all data sources and selects the most discriminant features (mainly from neuroimages). Using this performance-weighted ensemble classification model, classification results up to 96% were obtained.

Are We Ready for Detecting α-Synuclein Prone to Aggregation in Patients? The Case of "Protein-Misfolding Cyclic Amplification" and "Real-Time Quaking-Induced Conversion" as Diagnostic Tools

The accumulation and deposition of α-synuclein aggregates in brain tissue is the main event in the pathogenesis of different neurodegenerative disorders grouped under the term of synucleinopathies. They include Parkinson's disease, dementia with Lewy bodies and multiple system atrophy. To date, the diagnosis of any of these disorders mainly relies on the recognition of clinical symptoms, when the neurodegeneration is already in an advanced phase. In the last years, several efforts have been carried out to develop new diagnostic tools for early diagnosis of synucleinopathies, with special interest to Parkinson's disease. The Protein-Misfolding Cyclic Amplification (PMCA) and the Real-Time Quaking-Induced Conversion (RT-QuIC) are ultrasensitive protein amplification assays for the detection of misfolded protein aggregates. Starting from the successful application in the diagnosis of human prion diseases, these techniques were recently tested for the detection of misfolded α-synuclein in brain homogenates and cerebrospinal fluid samples of patients affected by synucleinopathies. So far, only a few studies on a limited number of samples have been performed to test PMCA and RT-QuIC diagnostic reliability. Neverthless, these assays have shown very high sensitivity and specificity in detecting synucleinopathies even at the pre-clinical stage. Despite the application of PMCA and RT-QuIC for α-synuclein detection in biological fluids is very recent, these techniques seem to have the potential for identifying subjects that will be likely to develop synucleinopathies.