Low clinical diagnostic accuracy of early vs advanced Parkinson disease: clinicopathologic study

Development and Validation of the Automated Imaging Differentiation in Parkinsonism (AID-P): A Multi-Site Machine Learning Study

Background

There is a critical need to develop valid, non-invasive biomarkers for Parkinsonian syndromes. The current 17-site, international study assesses whether non-invasive diffusion MRI (dMRI) can distinguish between Parkinsonian syndromes.

Methods

We used dMRI from 1002 subjects, along with the Movement Disorders Society Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III), to develop and validate disease-specific machine learning comparisons using 60 template regions and tracts of interest in Montreal Neurological Institute (MNI) space between Parkinson's disease (PD) and Atypical Parkinsonism (multiple system atrophy - MSA, progressive supranuclear palsy - PSP), as well as between MSA and PSP. For each comparison, models were developed on a training/validation cohort and evaluated in a test cohort by quantifying the area under the curve (AUC) of receiving operating characteristic (ROC) curves.

Findings

In the test cohort for both disease-specific comparisons, AUCs were high in the dMRI + MDS-UPDRS (PD vs. Atypical Parkinsonism: 0·962; MSA vs. PSP: 0·897) and dMRI Only (PD vs. Atypical Parkinsonism: 0·955; MSA vs. PSP: 0·926) models, whereas the MDS-UPDRS III Only models had significantly lower AUCs (PD vs. Atypical Parkinsonism: 0·775; MSA vs. PSP: 0·582).

Interpretations

This study provides an objective, validated, and generalizable imaging approach to distinguish different forms of Parkinsonian syndromes using multi-site dMRI cohorts. The dMRI method does not involve radioactive tracers, is completely automated, and can be collected in less than 12 minutes across 3T scanners worldwide. The use of this test could thus positively impact the clinical care of patients with Parkinson's disease and Parkinsonism as well as reduce the number of misdiagnosed cases in clinical trials.

[A partition bagging ensemble learning algorithm for Parkinson's speech data mining]

Methods for achieving diagnosis of Parkinson's disease (PD) based on speech data mining have been proven effective in recent years. However, due to factors such as the degree of disease of the data collection subjects and the collection equipment and environment, there are different categories of sample aliasing in the sample space of the acquired data set. Samples in the aliased area are difficult to be identified effectively, which seriously affects the classification accuracy of the algorithm. In order to solve this problem, a partition bagging ensemble learning is proposed in this article, which measures the aliasing degree of the sample by designing the the ratio of sample centroid distance metrics and divides the training set into multiple subsets. And then the method of transfer training of misclassified samples is used to adjust the results of subset partitioning. Finally, the optimized weights of each sub-classifier are used to integrate the test results. The experimental results show that the classification accuracy of the proposed method is significantly improved on two public datasets and the increasement of mean accuracy is up to 25.44%. This method not only effectively improves the classification accuracy of PD speech dataset, but also increases the sample utilization rate, providing a new idea for the diagnosis of PD.

Efficient RT-QuIC seeding activity for α-synuclein in olfactory mucosa samples of patients with Parkinson's disease and multiple system atrophy

Background

Parkinson’s disease (PD) is a neurodegenerative disorder whose diagnosis is often challenging because symptoms may overlap with neurodegenerative parkinsonisms. PD is characterized by intraneuronal accumulation of abnormal α-synuclein in brainstem while neurodegenerative parkinsonisms might be associated with accumulation of either α-synuclein, as in the case of Multiple System Atrophy (MSA) or tau, as in the case of Corticobasal Degeneration (CBD) and Progressive Supranuclear Palsy (PSP), in other disease-specific brain regions. Definite diagnosis of all these diseases can be formulated only neuropathologically by detection and localization of α-synuclein or tau aggregates in the brain. Compelling evidence suggests that trace-amount of these proteins can appear in peripheral tissues, including receptor neurons of the olfactory mucosa (OM).

Methods

We have set and standardized the experimental conditions to extend the ultrasensitive Real Time Quaking Induced Conversion (RT-QuIC) assay for OM analysis. In particular, by using human recombinant α-synuclein as substrate of reaction, we have assessed the ability of OM collected from patients with clinical diagnoses of PD and MSA to induce α-synuclein aggregation, and compared their seeding ability to that of OM samples collected from patients with clinical diagnoses of CBD and PSP.

Results

Our results showed that a significant percentage of MSA and PD samples induced α-synuclein aggregation with high efficiency, but also few samples of patients with the clinical diagnosis of CBD and PSP caused the same effect. Notably, the final RT-QuIC aggregates obtained from MSA and PD samples owned peculiar biochemical and morphological features potentially enabling their discrimination.

Conclusions

Our study provide the proof-of-concept that olfactory mucosa samples collected from patients with PD and MSA possess important seeding activities for α-synuclein. Additional studies are required for (i) estimating sensitivity and specificity of the technique and for (ii) evaluating its application for the diagnosis of PD and neurodegenerative parkinsonisms. RT-QuIC analyses of OM and cerebrospinal fluid (CSF) can be combined with the aim of increasing the overall diagnostic accuracy of these diseases, especially in the early stages.

Electronic supplementary material

The online version of this article (10.1186/s40035-019-0164-x) contains supplementary material, which is available to authorized users.

"Pseudo-syndromes" associated with Parkinson disease, dementia, apathy, anxiety, and depression

PURPOSE OF REVIEW

Physicians treating patients with Parkinson disease must evaluate not only motor symptoms but also acquire expertise in assessing the complex behavioral features that often accompany the disease, such as dementia, apathy, anxiety, and depression.

RECENT FINDINGS

There is a risk of diagnostic confusion and error because many of the behavioral and motor symptoms accentuate, overlap, or mimic each other.

SUMMARY

Awareness of potential diagnostic pitfalls and "pseudo-syndromes" should lead to more accurate clinical assessment and better care for our patients.

Altered Neurometabolic Profile in Early Parkinson's Disease: A Study With Short Echo-Time Whole Brain MR Spectroscopic Imaging

Objective: To estimate alterations in neurometabolic profile of patients with early stage Parkinson's disease (PD) by using a short echo-time whole brain magnetic resonance spectroscopic imaging (wbMRSI) as possible biomarker for early diagnosis and monitoring of PD.

Methods: 20 PD patients in early stage (H&Y ≤ 2) without evidence of severe other diseases and 20 age and sex matched healthy controls underwent wbMRSI. In each subject brain regional concentrations of metabolites N-acetyl-aspartate (NAA), choline (Cho), total creatine (tCr), glutamine (Gln), glutamate (Glu), and myo-inositol (mIns) were obtained in atlas-defined lobar structures including subcortical basal ganglia structures (the left and right frontal lobes, temporal lobes, parietal lobes, occipital lobes, and the cerebellum) and compared between patients and matched healthy controls. Clinical characteristics of the PD patients were correlated with spectroscopic findings.

Results: In comparison to controls the PD patients revealed altered lobar metabolite levels in all brain lobes contralateral to dominantly affected body side, i.e., decreases of temporal NAA, Cho, and tCr, parietal NAA and tCr, and frontal as well as occipital NAA. The frontal NAA correlated negatively with the MDS-UPDRS II (R = 22120.585, p = 0.008), MDS-UPDRS IV (R = −0.458, p = 0.048) and total MDS-UPDRS scores (R = −0.679, p = 0.001).

Conclusion: In early PD stages metabolic alterations are evident in all contralateral brain lobes demonstrating that the neurodegenerative process affects not only local areas by dopaminergic denervation, but also the functional network within different brain regions. The wbMRSI-detectable brain metabolic alterations reveal the potential to serve as biomarkers for early PD.

Artificial intelligence for assisting diagnostics and assessment of Parkinson's disease-A review

Artificial intelligence, specifically machine learning, has found numerous applications in computer-aided diagnostics, monitoring and management of neurodegenerative movement disorders of parkinsonian type. These tasks are not trivial due to high inter-subject variability and similarity of clinical presentations of different neurodegenerative disorders in the early stages. This paper aims to give a comprehensive, high-level overview of applications of artificial intelligence through machine learning algorithms in kinematic analysis of movement disorders, specifically Parkinson's disease (PD). We surveyed papers published between January 2007 and January 2019, within online databases, including PubMed and Science Direct, with a focus on the most recently published studies. The search encompassed papers dealing with the implementation of machine learning algorithms for diagnosis and assessment of PD using data describing motion of upper and lower extremities. This systematic review presents an overview of 48 relevant studies published in the abovementioned period, which investigate the use of artificial intelligence for diagnostics, therapy assessment and progress prediction in PD based on body kinematics. Different machine learning algorithms showed promising results, particularly for early PD diagnostics. The investigated publications demonstrated the potentials of collecting data from affordable and globally available devices. However, to fully exploit artificial intelligence technologies in the future, more widespread collaboration is advised among medical institutions, clinicians and researchers, to facilitate aligning of data collection protocols, sharing and merging of data sets.

Parkinsonism in essential tremor cases: A clinicopathological study

BACKGROUND

Essential tremor and Parkinson's syndrome are two common movement disorders that may co-occur in some individuals. There is no diagnostic neuropathology for essential tremor, but in PD and other Parkinson's syndrome variants, the neuropathology is well known. The spectrum of Parkinson's syndrome variants associated with essential tremor, their clinical features, and course have not been determined in autopsy-confirmed cases.

OBJECTIVES

To identify: diagnostic features of essential tremor/Parkinson's syndrome, different Parkinson's syndrome variants, and long-term clinical profile in such cases.

METHODS

Patients that had an essential tremor diagnosis and a subsequent clinical or pathological diagnosis of Parkinson's syndrome seen in our clinic during 50 years were included. The diagnosis of parkinsonism was made when bradykinesia, rigidity, and resting tremor were all clinically evident.

RESULTS

Twenty-one cases were included. All the common variants of parkinsonism co-occurred with essential tremor. The most common was PD (67%) followed by PSP. The pathological findings were not predicted clinically in 2 cases that had essential tremor/PD and in all 5 essential tremor/PSP cases.

CONCLUSION

In most essential tremor/Parkinson's syndrome patients, the main motor features of parkinsonism-bradykinesia, rigidity, and resting tremor-were identifiable. All known degenerative Parkinson's syndrome variants co-occurred in essential tremor patients. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

An NMR-based lipidomic approach to identify Parkinson's disease-stage specific lipoprotein-lipid signatures in plasma

Disturbances in lipid composition and lipoproteins metabolism can play a crucial role in the pathogenesis of Parkinson's disease (PD) and other neurodegenerative diseases. The lipidomic strategy proposed here involves lipoprotein profiling using NMR spectroscopy and multivariate data pre-processing and analysis tools on 94 plasma samples (belonging to 38 early-stage PD patients, 10 PD-related dementia patients, 23 persons with Alzheimer's dementia, and 23 healthy control subjects) to firstly differentiate PD patients (irrespective of the stage of the disease) from persons with Alzheimer's disease (AD) as well as from controls, and then to discriminate among PD patients according to disease severity. The whole data set was subdivided into 86 training and 8 external test samples for validation purposes. A two-step classification scheme, based on linear discriminant analysis with variable selection accomplished by a stepwise orthogonalisation procedure, was proposed to optimise classification performance. Careful pre-processing of NMR signals was crucial to ensure data set quality. A total of 30 chemical shift buckets enabled differentiation between PD patients (regardless of disease severity), AD and control subjects, providing classification, cross-validation and external prediction rates of 100% in all cases. Only 15 variables were required to further discriminate between early-stage PD and PD-related dementia, again with 100% correct classifications, and internal/external predictions. The simplicity and effectiveness of the classification methodology proposed support the use of NMR spectroscopy, in combination with chemometrics, as a viable alternative diagnostic tool to conventional PD clinical diagnosis.

Network imaging biomarkers: insights and clinical applications in Parkinson's disease

Parkinson's disease presents several practical challenges: it can be difficult to distinguish from atypical parkinsonian syndromes, clinical ratings can be insensitive as markers of disease progression, and its non-motor manifestations are not readily assessed in animal models. These challenges, along with others, are beginning to be addressed by innovative imaging methods to characterise Parkinson's disease-specific functional networks across the whole brain and measure their expression in each patient. These signatures can help improve differential diagnosis, guide selection of patients for clinical trials, and quantify treatment responses and placebo effects in individual patients. The primary Parkinson's disease-related metabolic pattern has been replicated in multiple patient populations and used as an outcome measure in clinical trials. It can also be used as a predictor of near-term phenoconversion in prodromal syndromes, such as rapid eye movement sleep behaviour disorder. Functional network imaging holds great promise for future clinical use in the management of neurodegenerative disorders.

An update on advances in magnetic resonance imaging of multiple system atrophy

In this review, we describe how different neuroimaging tools have been used to identify novel MSA biomarkers, highlighting their advantages and limitations. First, we describe the main structural MRI changes frequently associated with MSA including the 'hot cross-bun' and 'putaminal rim' signs as well as putaminal, pontine, and middle cerebellar peduncle (MCP) atrophy. We discuss the sensitivity and specificity of different supra- and infratentorial changes in differentiating MSA from other disorders, highlighting those that can improve diagnostic accuracy, including the MCP width and MCP/superior cerebellar peduncle (SCP) ratio on T1-weighted imaging, raised putaminal diffusivity on diffusion-weighted imaging, and increased T2* signal in the putamen, striatum, and substantia nigra on susceptibility-weighted imaging. Second, we focus on recent advances in structural and functional MRI techniques including diffusion tensor imaging (DTI), resting-state functional MRI (fMRI), and arterial spin labelling (ASL) imaging. Finally, we discuss new approaches for MSA research such as multimodal neuroimaging strategies and how such markers may be applied in clinical trials to provide crucial data for accurately selecting patients and to act as secondary outcome measures.

Alpha-Synuclein in Skin Nerve Fibers as a Biomarker for Alpha-Synucleinopathies

The common pathological features of synucleinopathies are abnormal aggregates of the synaptic protein alpha-synuclein (αSN) in the cytoplasm of neurons or glia. These abnormal aggregates appear several years before the onset of clinical manifestations, and so the early detection of αSN in body fluids or peripheral tissues (e.g., cerebrospinal fluid, colonic mucosa, salivary glands, and skin) is considered a potential tool for identifying synucleinopathies. Performing a skin biopsy is a practical option because it is a relatively noninvasive, safe, and reliable method to measure αSN deposition in the peripheral nervous system. Moreover, there is growing research interest in the use of cutaneous synuclein deposition as a biomarker for synucleinopathies. The aim of this study was to interpret the current data on cutaneous αSN deposition and present the current perspectives and future prospects.

Progressive parkinsonism in older adults is related to the burden of mixed brain pathologies

OBJECTIVE

To examine whether indices of Parkinson disease (PD) pathology and other brain pathologies are associated with the progression of parkinsonism in older adults.

METHODS

We used data from decedents who had undergone annual clinical testing prior to death and structured brain autopsy. Parkinsonism was based on assessment with a modified Unified Parkinson's Disease Rating Scale and a clinical diagnosis of PD was based on medical history. We used a series of mixed-effects models controlling for age and sex to investigate the association of PD pathology (nigral neuronal loss and Lewy bodies) and indices of 8 other brain pathologies with the progression of parkinsonism prior to death.

RESULTS

During an average of 8.5 years' follow-up, more than half (771/1,430, 53.9%) developed parkinsonism proximate to death. On average, parkinsonism was progressive (estimate 0.130, SE 0.005, p < 0.001) in all older adults, but more rapid in adults with a clinical diagnosis of PD (n = 52; 3.6%) (estimate 0.066, SE 0.021, p < 0.001). Progression of parkinsonism was more rapid in adults with PD pathology (estimate 0.087, SE 0.013, p < 0.001). Alzheimer disease and several cerebrovascular pathologies were all independently associated with more rapid progression (all p values <0.05). The association between a higher person-specific weighted pathology score and more rapidly progressive parkinsonism did not differ between individuals with and without a clinical diagnosis of PD (estimate 0.003, SE 0.047, p = 0.957).

CONCLUSION

The rate of progressive parkinsonism in older adults with and without a clinical diagnosis of PD is related to the burden of mixed brain pathologies.

Identifying Parkinson's disease and parkinsonism cases using routinely collected healthcare data: A systematic review

Background

Population-based, prospective studies can provide important insights into Parkinson’s disease (PD) and other parkinsonian disorders. Participant follow-up in such studies is often achieved through linkage to routinely collected healthcare datasets. We systematically reviewed the published literature on the accuracy of these datasets for this purpose.

Methods

We searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely collected data to a reference standard. We extracted study characteristics and two accuracy measures: positive predictive value (PPV) and/or sensitivity.

Results

We identified 18 articles, resulting in 27 measures of PPV and 14 of sensitivity. For PD, PPV ranged from 56–90% in hospital datasets, 53–87% in prescription datasets, 81–90% in primary care datasets and was 67% in mortality datasets. Combining diagnostic and medication codes increased PPV. For parkinsonism, PPV ranged from 36–88% in hospital datasets, 40–74% in prescription datasets, and was 94% in mortality datasets. Sensitivity ranged from 15–73% in single datasets for PD and 43–63% in single datasets for parkinsonism.

Conclusions

In many settings, routinely collected datasets generate good PPVs and reasonable sensitivities for identifying PD and parkinsonism cases. However, given the wide range of identified accuracy estimates, we recommend cohorts conduct their own context-specific validation studies if existing evidence is lacking. Further research is warranted to investigate primary care and medication datasets, and to develop algorithms that balance a high PPV with acceptable sensitivity.

The Qualification of an Enrichment Biomarker for Clinical Trials Targeting Early Stages of Parkinson's Disease

As therapeutic trials target early stages of Parkinson's disease (PD), appropriate patient selection based purely on clinical criteria poses significant challenges. Members of the Critical Path for Parkinson's Consortium formally submitted documentation to the European Medicines Agency (EMA) supporting the use of Dopamine Transporter (DAT) neuroimaging in early PD. Regulatory documents included a comprehensive literature review, a proposed analysis plan of both observational and clinical trial data, and an assessment of biomarker reproducibility and reliability. The research plan included longitudinal analysis of the Parkinson Research Examination of CEP-1347 Trial (PRECEPT) and the Parkinson's Progression Markers Initiative (PPMI) study to estimate the degree of enrichment achieved and impact on future trials in subjects with early motor PD. The presence of reduced striatal DAT binding based on visual reads of single photon emission tomography (SPECT) scans in early motor PD subjects was an independent predictor of faster decline in UPDRS Parts II and III as compared to subjects with scans without evidence of dopaminergic deficit (SWEDD) over 24 months. The EMA issued in 2018 a full Qualification Opinion for the use of DAT as an enrichment biomarker in PD trials targeting subjects with early motor symptoms. Exclusion of SWEDD subjects in future clinical trials targeting early motor PD subjects aims to enrich clinical trial populations with idiopathic PD patients, improve statistical power, and exclude subjects who are unlikely to progress clinically from being exposed to novel test therapeutics.

Magnetic resonance T1w/T2w ratio: A parsimonious marker for Parkinson disease

OBJECTIVE

Newer magnetic resonance imaging (MRI) techniques have shown promise in capturing early Parkinson disease (PD)-related changes in the substantia nigra pars compacta (SNc), the key pathological loci. Their translational value, however, is hindered by technical complexity and inconsistent results.

METHODS

A novel yet simple MRI contrast, the T1w/T2w ratio, was used to study 76 PD patients and 70 controls. The T1w/T2w ratio maps were analyzed using both voxel-based and region-of-interest approaches in normalized space. The sensitivity and specificity of the SNc T1w/T2w ratio in discriminating between PD and controls also were assessed. In addition, its diagnostic performance was tested in a subgroup of PD patients with disease duration ≤2 years (PDE). A second independent cohort of 73 PD patients and 49 controls was used for validation.

RESULTS

Compared to controls, PD patients showed a higher T1w/T2w ratio in both the right (cluster size = 164mm3 , p < 0.0001) and left (cluster size = 213mm3 , p < 0.0001) midbrain that was located ventrolateral to the red nucleus and corresponded to the SNc. The region-of-interest approach confirmed the group difference in the SNc T1w/T2w ratio between PD and controls (p < 0.0001). The SNc T1w/T2w ratio had high sensitivity (0.908) and specificity (0.80) to separate PD and controls (area under the curve [AUC] = 0.926), even for PDE patients (AUC = 0.901, sensitivity = 0.857, specificity = 0.857). These results were validated in the second cohort.

INTERPRETATION

The T1w/T2w ratio can detect PD-related changes in the SNc and may be used as a novel, parsimonious in vivo biomarker for the disease, particularly for early stage patients, with high translational value for clinical practice and research. ANN NEUROL 2019;85:96-104.

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.

Skin nerve α-synuclein deposits in Parkinson's disease and other synucleinopathies: a review

PURPOSE

The in vivo diagnosis of synucleinopathies is an important research aim since clinical diagnostic criteria show low accuracy. The skin innervation, especially the autonomic subdivision, is a useful region to search for abnormal α-syn aggregates in synucleinopathies since the peripheral sympathetic nerves can be the earliest-affected neural region and autonomic symptoms may precede the classical symptoms of these disorders.

METHODS

The major advantages of skin biopsy as an in vivo diagnostic tool for synucleinopathies are that it is an inexpensive and easy-to-perform technique requiring only limited facilities, and that it is repeatable in long-term studies as it causes only minor discomfort to the patient.

RESULTS

This review analyzes current progress in this area of research that may facilitate the standardization of this method, potentially eliminating differences among laboratories in the implementation of the method.

CONCLUSIONS

The most suitable and commonly used technique for identifying in vivo α-syn aggregates in skin nerves is indirect immunofluorescence, although several aspects of this approach need to be standardized, particularly when synucleinopathies without autonomic failure present a patchy distribution of abnormal α-syn aggregates in skin nerves. By contrast, synucleinopathies with autonomic failure may present widespread diffusion of abnormal aggregates in autonomic skin nerves.

Sensor Array for Detection of Early Stage Parkinson's Disease before Medication

Early diagnosis of Parkinson's disease (PD) is important because it affects the choice of therapy and is subject to a relatively high degree of error. In addition, early detection of PD can potentially enable the start of neuroprotective therapy before extensive loss of dopaminergic neurons of the substantia nigra occurs. However, until now, studies for early detection of PD using volatile biomarkers sampled only treated and medicated patients. Therefore, there is a great need to evaluate untreated patients for establishing a real world screening and diagnostic technology. Here we describe for the first time a clinical trial to distinguish between de novo PD and control subjects using an electronic system for detection of volatile molecules in exhaled breath (sensor array). We further determine for the first time the association to other common tests for PD diagnostics as smell, ultrasound, and nonmotor symptoms. The test group consisted of 29 PD patients after initial diagnosis by an experienced neurologist, compared with 19 control subjects of similar age. The sensitivity, specificity, and accuracy values of the sensor array to detect PD from controls were 79%, 84%, and 81% respectively, in comparison with midbrain ultrasonography (93%, 90%, 92%) and smell detection (62%, 89%, 73%). The results confirm previous data showing the potential of sensor arrays to detect PD.

Evaluation of cerebrospinal fluid proteins as potential biomarkers for early stage Parkinson's disease diagnosis

Cerebrospinal fluid (CSF) has often been used as the source of choice for biomarker discovery with the goal to support the diagnosis of neurodegenerative diseases. For this study, we selected 15 CSF protein markers which were identified in previously published clinical investigations and proposed as potential biomarkers for PD diagnosis. We aimed at investigating and confirming their suitability for early stage diagnosis of the disease. The current study was performed in a two-fold confirmatory approach. Firstly, the CSF protein markers were analysed in confirmatory cohort I comprising 80 controls and 80 early clinical PD patients. Through univariate analysis we found significant changes of six potential biomarkers (α-syn, DJ-1, Aβ42, S100β, p-Tau and t-Tau). In order to increase robustness of the observations for potential patient differentiation, we developed-based on a machine learning approach-an algorithm which enabled identifying a panel of markers which would improve clinical diagnosis. Based on that model, a panel comprised of α-syn, S100β and UCHL1 were suggested as promising candidates. Secondly, we aimed at replicating our observations in an independent cohort (confirmatory cohort II) comprising 30 controls and 30 PD patients. The univariate analysis demonstrated Aβ42 as the only reproducible potential biomarker. Taking into account both technical and clinical aspects, these observations suggest that the large majority of the investigated CSF proteins currently proposed as potential biomarkers lack robustness and reproducibility in supporting diagnosis in the early clinical stages of PD.

Early predictors of mortality in parkinsonism and Parkinson disease: A population-based study

Objective

To examine mortality and associated risk factors, including possible effects of mild cognitive impairment, imaging, and CSF abnormalities, in a community-based population with incident parkinsonism and Parkinson disease.

Methods

One hundred eighty-two patients with new-onset, idiopathic parkinsonism were diagnosed from January 2004 through April 2009, in a catchment area of 142,000 inhabitants in Sweden. Patients were comprehensively investigated according to a multimodal research protocol and followed prospectively for up to 13.5 years. A total of 109 patients died. Mortality rates in the general Swedish population were used to calculate standardized mortality ratio and expected survival, and Cox proportional hazard models were used to investigate independent predictors of mortality.

Results

The standardized mortality ratio for all patients was 1.84 (95% confidence interval 1.50–2.22, p < 0.001). Patients with atypical parkinsonism (multiple system atrophy or progressive supranuclear palsy) had the highest mortality. In early Parkinson disease, a mild cognitive impairment diagnosis, freezing of gait, hyposmia, reduced dopamine transporter activity in the caudate, and elevated leukocytes in the CSF were significantly associated with shorter survival.

Conclusion

Although patients presenting with idiopathic parkinsonism have reduced survival, the survival is highly dependent on the type and characteristics of the parkinsonian disorder. Patients with Parkinson disease presenting with normal cognitive function seem to have a largely normal life expectancy. The finding of a subtle CSF leukocytosis in patients with Parkinson disease with short survival may have clinical implications.

Are Clinical Certainty Ratings Helpful in the Diagnosis of Parkinson's Disease?

Background

Clinical diagnostic criteria for PD rely on rest tremor, bradykinesia, and rigidity. These features are non-specific and neuropathological confirmation remains the gold standard for diagnosis. This study presents data on clinical certainty ratings in autopsy-proven PD.

Methods

Subjects were assessed annually by a movement disorders specialist and assigned to a clinical certainty group for PD based on multiple clinical features before autopsy. The three groups considered for analysis are as follows: Group I 0-49% certainty, Group II 50-89% certainty, and Group III 90-100% certainty. All subjects were autopsied and had a standardized neuropathological assessment.

Results

275 subjects were assigned a PD certainty at their last visit before death. Group I had 80 subjects, Group II 56 subjects, and Group III 139 subjects. The clinical features recorded in Group I, II, and III, were as follows: rest tremor, bradykinesia, rigidity, postural instability, asymmetric onset, persistent asymmetry, current response to dopaminergic treatment, motor fluctuations, and dyskinesia. Rigidity, postural instability, asymmetric onset, current response to dopaminergic treatment, motor fluctuation, and dyskinesia were more likely to be present in the group which was rated with higher certainty. The final diagnosis of PD was confirmed by neuropathological assessment in 85% of the patients in Group III as compared to 30% in Group II and 5% in Group I.

Conclusions

High certainty (90-100%) had strong positive predictive value (85%) for autopsy-proven PD as compared to either lower certainty groups (0-49% and 50-89%) which had lower predictive value (5% and 30% respectively).

Is transcranial sonography useful for diagnosing Parkinson's disease in clinical practice?

OBJECTIVE

Transcranial sonography (TCS) is an emerging ancillary examination for diagnosing Parkinson's disease (PD).

OBJECTIVE

To evaluate TCS features in patients with PD and its mimics, and establish their accuracy in predicting the final clinical diagnosis after follow-up.

METHODS

We retrospectively studied 85 patients with an initial clinical suspicion of PD, atypical parkinsonism or essential tremor, all of whom underwent TCS. Two specialists reviewed the follow-up clinical visit records and determined the final clinical diagnosis. The accuracy analysis of the TCS was determined using Bayesian statistical methods.

RESULTS

The finding of substantia nigra hyperechogenicity (> 20 mm2) showed high sensitivity (93.4%) and specificity (86.6%). The positive likelihood ratio showed 6.93-fold greater odds for diagnosing PD than an alternative condition when this finding was present.

CONCLUSIONS

This study revealed the practical usefulness of TCS in differentiating PD from its prevalent mimics when the clinical diagnosis was initially unclear.

Phosphorylated α-synuclein deposits in sural nerve deriving from Schwann cells: A biomarker for Parkinson's disease

INTRODUCTION

Paresthesia is common in Parkinson's disease (PD) patients. We assumed that peripheral nerve might be implicated. This study aimed to investigate whether phosphorylated α-synuclein (pSNCA) pathology occurred in sural nerve fibers and to explore the underlying pathogenesis of paresthesia of lower limbs associated with PD.

METHODS

Clinical assessments and sural nerve biopsy were performed to evaluate clinical characteristics and the deposition of total α-synuclein (tSNCA) and pSNCA in biopsy pieces using immunochemistry methods on 16 PD patients and 15 controls. In addition, immunofluorescence staining was performed using certain antibodies to characterize the component of sural nerve and to localize the expression of pSNCA.

RESULTS

Deposition of pSNCA was found in 16/16 PD patients with a high positive percentage of 100% but in 0/15 controls, however, all biopsy pieces showed positive response to tSNCA immunohistological staining in nerve fibers. pSNCA was expressed mainly in Schwann cells but scarcely in axons, demonstrating a novel pattern of pSNCA expression in peripheral nervous system.

CONCLUSION

Our findings suggest that peripheral somatic sensory nerve is also involved in SNCA pathology in PD. The search for pSNCA in sural nerve might serve as a novel biomarker for early diagnosis of PD and pSNCA in sural nerve may derive from Schwann cells rather than propagate retrograde along the primary sensory neurons from the central nervous system.

Identifying mild-moderate Parkinson's disease using whole-brain functional connectivity

OBJECTIVE

Our study aims to extract significant disorder-associated patterns from whole brain functional connectivity to distinguish mild-moderate Parkinson's disease (PD) patients from controls.

METHODS

Resting-state fMRI data were measured from thirty-six PD individuals and thirty-five healthy controls. Multivariate pattern analysis was applied to investigate whole-brain functional connectivity patterns in individuals with 'mild-moderate' PD. Additionally, the relationship between the asymmetry of functional connectivity and the side of the initial symptoms was also analyzed.

RESULTS

In a leave-one-out cross-validation, we got the generalization rate of 80.28% for distinguishing PD patients from controls. The most discriminative functional connectivity was found in cortical networks that included the default mode, sensorimotor and attention networks. Compared to patients with the left side initially affected, an increased abnormal functional connectivity was found in patients in whom the right side was initially affected.

CONCLUSIONS

Our results indicated that discriminative functional connectivity is likely associated with disturbances of cortical networks involved in sensorimotor control and attention. The spatiotemporal patterns of motor asymmetry may be related to the lateralized dysfunction on the early stages of PD.

SIGNIFICANCE

This study identifies discriminative functional connectivity that is associated with disturbances of cortical networks. Our results demonstrated new evidence regarding the functional brain changes related to the unilateral motor symptoms of early PD.

Immunohistochemical Method and Histopathology Judging for the Systemic Synuclein Sampling Study (S4)

Immunohistochemical (IHC) α-synuclein (Asyn) pathology in peripheral biopsies may be a biomarker of Parkinson disease (PD). The multi-center Systemic Synuclein Sampling Study (S4) is evaluating IHC Asyn pathology within skin, colon and submandibular gland biopsies from 60 PD and 20 control subjects. Asyn pathology is being evaluated by a blinded panel of specially trained neuropathologists. Preliminary work assessed 2 candidate immunoperoxidase methods using a set of PD and control autopsy-derived sections from formalin-fixed, paraffin-embedded blocks of the 3 tissues. Both methods had 100% specificity; one, utilizing the 5C12 monoclonal antibody, was more sensitive in skin (67% vs 33%), and was chosen for further use in S4. Four trainee neuropathologists were trained to perform S4 histopathology readings; in subsequent testing, their scoring was compared to that of the trainer neuropathologist on both glass slides and digital images. Specificity and sensitivity were both close to 100% with all readers in all tissue types on both glass slides and digital images except for skin, where sensitivity averaged 75% with digital images and 83.5% with glass slides. Semiquantitative (0-3) density score agreement between trainees and trainer averaged 67% for glass slides and 62% for digital images.

Susceptibility MRI captures nigral pathology in patients with parkinsonian syndromes

BACKGROUND

Parkinsonisms are neurodegenerative disorders characterized pathologically by α-synuclein-positive (e.g., PD, diffuse Lewy body disease, and MSA) and/or tau-positive (e.g., PSP, cortical basal degeneration) pathology. Using R2* and quantitative susceptibility mapping, susceptibility changes have been reported in the midbrain of living parkinsonian patients, although the exact underlying pathology of these alterations is unknown.

OBJECTIVE

The current study investigated the pathological correlates of these susceptibility MRI measures.

METHODS

In vivo MRIs (T1- and T2-weighted, and T2*) and pathology were obtained from 14 subjects enrolled in an NINDS PD Biomarker Program (PDBP). We assessed R2* and quantitative susceptibility mapping values in the SN, semiquantitative α-synuclein, tau, and iron values, as well as neuronal and glial counts. Data were analyzed using age-adjusted Spearman correlations.

RESULTS

R2* was associated significantly with nigral α-synuclein (r = 0.746; P = 0.003). Quantitative susceptibility mapping correlated significantly with Perls' (r = 0.758; P = 0.003), but not with other pathological measurements. Neither measurement correlated with tau or glial cell counts (r ≤ 0.11; P ≥ 0.129).

CONCLUSIONS

Susceptibility MRI measurements capture nigral pathologies associated with parkinsonian syndromes. Whereas quantitative susceptibility mapping is more sensitive to iron, R2* may reflect pathological aspects of the disorders beyond iron such as α-synuclein. They may be invaluable tools in diagnosing differential parkinsonian syndromes, and tracking in living patients the dynamic changes associated with the pathological progression of these disorders. © 2018 International Parkinson and Movement Disorder Society.

What a neurologist should know about PET and SPECT functional imaging for parkinsonism: A practical perspective

The diagnosis of a parkinsonian syndrome based on clinical criteria remains sometimes difficult, especially at disease onset. Brain or heart molecular imaging techniques (SPECT or PET) can provide a major help to improve and speed up diagnosis, influencing treatment strategies. Presynaptic dopaminergic imaging using either [¹⁸F]-Dopa PET or ¹²³I -2β-Carbomethoxy-3β-(4-Iodophenyl)- N-(3-Fluoropropyl) Nortropane ([¹²³I]-Ioflupane)SPECT demonstrates or rules out the presence of a dopaminergic degenerative process. This allows to distinguish Parkinson's disease, Parkinson "plus" syndromes and dementia with Lewy bodies (reduced radiotracers binding) from essential tremor, psychogenic, post-neuroleptic or vascular parkinsonisms, dopa-responsive dystonia and Alzheimer's disease (normal radiotracers binding). For differential diagnosis between Parkinson's disease and Parkinson "plus" syndromes, brain molecular imaging with [¹⁸F]-Fluorodeoxyglucose ([¹⁸F]-FDG) PET or ^99mTc-HMPAO SPECT can provide useful information, whereas [¹⁸F]-Dopa PET or [¹²³I]-Ioflupane does not separate these entities. Finally, sympathetic cardiac [¹²³I]-Metaiodobenzylguanidine ([¹²³I]-MIBG) scintigraphy or SPECT can help distinguishing Parkinson's disease and dementia with Lew bodies (decreased binding) from multiple system atrophy and progressive supranuclear palsy (normal binding). New radiotracers notably those targeting the pathological process itself such as Tau aggregates are under development and may provide interesting informations to delineate the different Parkinson "plus" syndromes.

Finding useful biomarkers for Parkinson's disease

The recent advent of an "ecosystem" of shared biofluid sample biorepositories and data sets will focus biomarker efforts in Parkinson's disease, boosting the therapeutic development pipeline and enabling translation with real-world impact.

Brain tissue pulsatility is related to clinical features of Parkinson's disease

Introduction

This study investigated whether brain tissue pulsatility is associated with features of disease severity in Parkinson's disease (PD).

Methods

Data were extracted from the Parkinson's Progression Markers Initiative among 81 adults with PD (confirmed with DATSCAN™). Brain tissue pulsatility was computed using resting state blood oxygenation level dependent (BOLD) MRI in white matter (WM), referred to as BOLD_TP. Motor impairment was assessed using the Movement Disorders Society unified Parkinson's disease rating scale. Factor analysis generated composite scores for cognition and vascular risk burden. A linear regression model examined the association of BOLD_TP with age, sex, motor impairment, cognition, vascular risk burden and PD duration. In addition, we investigated whether BOLD_TP relates to WM hyperintensity (WMH) volume, WM fractional anisotropy (WM-FA) and striatal binding ratio (SBR) of dopamine transporter.

Results

Motor impairment (t = 2.3, p = .02), vascular burden (t = 2.4, p = .02) and male sex (t = 3.0, p = .003) were independently associated with BOLD_TP (r² = 0.40, p < .001). BOLD_TP was correlated with WMH volume (r = 0.22, p = .05) but not WM-FA nor SBR (p > .1). In addition, BOLD_TP (t = 2.76, p = .008) and SBR (t = -2.04, p = .04) were independently related to motor impairment (r² = 0.18, p = .006).

Conclusion

Our findings show that brain tissue pulsatility from BOLD images in WM is related to neurological and vascular features in PD. BOLD_TP may be useful in PD to study small vessel alterations that appear distinct from WM structural changes.

Phosphorylated α-synuclein in the retina is a biomarker of Parkinson's disease pathology severity

BACKGROUND

PD patients often have visual alterations, for example, loss of visual acuity, contrast sensitivity or motion perception, and diminished electroretinogram responses. PD pathology is mainly characterized by the accumulation of pathological α-synuclein deposits in the brain, but little is known about how synucleinopathy affects the retina.

OBJECTIVE

To study the correlation between α-synuclein deposits in the retina and brain of autopsied subjects with PD and incidental Lewy body disease.

METHODS

We evaluated the presence of phosphorylated α-synuclein in the retina of autopsied subjects with PD (9 subjects), incidental Lewy body disease (4 subjects), and controls (6 subjects) by immunohistochemistry and compared the retinal synucleinopathy with brain disease severity indicators.

RESULTS

Whereas controls did not show any phosphorylated α-synuclein immunoreactivity in their retina, all PD subjects and 3 of 4 incidental Lewy body disease subjects had phosphorylated α-synuclein deposits in ganglion cell perikarya, dendrites, and axons, some of them resembling brain Lewy bodies and Lewy neurites. The Lewy-type synucleinopathy density in the retina significantly correlated with Lewy-type synucleinopathy density in the brain, with the Unified Parkinson's disease pathology stage and with the motor UPDRS.

CONCLUSION

These data suggest that phosphorylated α-synuclein accumulates in the retina in parallel with that in the brain, including in early stages preceding development of clinical signs of parkinsonism or dementia. Therefore, the retina may provide an in vivo indicator of brain pathology severity, and its detection could help in the diagnosis and monitoring of disease progression. © 2018 International Parkinson and Movement Disorder Society.

Characterisation of tau in the human and rodent enteric nervous system under physiological conditions and in tauopathy

Tau is normally a highly soluble phosphoprotein found predominantly in neurons. Six different isoforms of tau are expressed in the adult human CNS. Under pathological conditions, phosphorylated tau aggregates are a defining feature of neurodegenerative disorders called tauopathies. Recent findings have suggested a potential role of the gut-brain axis in CNS homeostasis, and therefore we set out to examine the isoform profile and phosphorylation state of tau in the enteric nervous system (ENS) under physiological conditions and in tauopathies. Surgical specimens of human colon from controls, Parkinson's disease (PD) and progressive supranuclear palsy (PSP) patients were analyzed by Western Blot and immunohistochemistry using a panel of anti-tau antibodies. We found that adult human ENS primarily expresses two tau isoforms, localized in the cell bodies and neuronal processes. We did not observe any difference in the enteric tau isoform profile and phosphorylation state between PSP, PD and control subjects. The htau mouse model of tauopathy also expressed two main isoforms of human tau in the ENS, and there were no apparent differences in ENS tau localization or phosphorylation between wild-type and htau mice. Tau in both human and mouse ENS was found to be phosphorylated but poorly susceptible to dephosphorylation with lambda phosphatase. To investigate ENS tau phosphorylation further, primary cultures from rat enteric neurons, which express four isoforms of tau, were pharmacologically manipulated to show that ENS tau phosphorylation state can be regulated, at least in vitro. Our study is the first to characterize tau in the rodent and human ENS. As a whole, our findings provide a basis to unravel the functions of tau in the ENS and to further investigate the possibility of pathological changes in enteric neuropathies and tauopathies.

The role of substantia nigra sonography in the differentiation of Parkinson's disease and multiple system atrophy

Background

The differential diagnosis of Parkinson's disease (PD) and multiple system atrophy (MSA) remains a challenge, especially in the early stage. Here, we assessed the value of transcranial sonography (TCS) to discriminate non-tremor dominant (non-TD) PD from MSA with predominant parkinsonism (MSA-P).

Methods

Eighty-six MSA-P patients and 147 age and gender-matched non-TD PD patients who had appropriate temporal acoustic bone windows were included in this study. All the patients were followed up for at least 2 years to confirm the initial diagnosis. Patients with at least one substantia nigra (SN) echogenic size ≥18 mm² were classified as hyperechogenic, those with at least one SN echogenic size ≥25 mm² was defined as markedly hyperechogenic.

Results

The frequency of SN hyperechogenicity in non-TD PD patients was significantly higher than that in MSA-P patients (74.1% vs. 38.4%, p <  0.001). SN hyperechogenicity discriminated non-TD PD from MSA-P with sensitivity of 74.1%, specificity of 61.6%, and positive predictive value of 76.8%. If marked SN hyperechogenicity was used as the cutoff value (≥ 25 mm²), the sensitivity decreased to 46.3%, but the specificity and positive predictive value increased to 80.2 and 80.0%. Additionally, in those patients with SN hyperechogenicity, positive correlation between SN hyperechogenicity area and disease duration was found in non-TD PD rather than in MSA-P patients. In this context, among early-stage patients with disease duration ≤3 years, the sensitivity, specificity and positive predictive value of SN hyperechogenicity further declined to 69.8%, 52.2%, and 66.7%, respectively.

Conclusions

TCS could help discriminate non-TD PD from MSA-P in a certain extent, but the limitation was also obvious with relatively low specificity, especially in the early stage.

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

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

Spinal Lewy body pathology in older adults without an antemortem diagnosis of Parkinson's disease

To test the hypothesis that Lewy body pathology (LBs) is present in the spinal cord of older community-dwelling adults without a clinical diagnosis of Parkinson's disease (PD). We studied 162 prospective autopsies from older adults with PD (N = 6) and without PD (N = 156). We documented the presence of LBs in cerebrum and brainstem structures from each of the six regions used for Braak PD staging and four spinal cord levels (C5/6, T7, L4/5 and S4/5). Parkinsonism proximate to death was based on a previously validated measure present if two or more of the four signs of parkinsonism were present based on a modified version of the Unified Parkinson's Disease Rating Scale (UPDRS). Fifty-three of 156 individuals without PD (34%) had LBs in a least one site within the CNS. About half of cases with LBs in the cerebrum or brainstem, (25/53, 47%) also had spinal LBs. Almost 90% (22/25, 88%) of cases with spinal LBs had LBs in the cerebrum (Braak stages 4-6) and about 10% (3/25, 12%) had only brainstem LBs (Braak stages 1-3). Four of six cases with PD showed LBs in cerebrum, brainstem and spinal cord. Individuals with LBs in the spinal cord were more likely to have clinical parkinsonism proximate to death compared to individuals with LBs in brainstem and cerebrum alone (52% vs. 32%; Chi-Square x2  = 5.368, d.f. = 1, P = 0.0.021) and more severe nigral neuronal loss (48% vs. 11%; Chi-Square x2  = 9.049, d.f. = 1, P = 0.003). These findings were unchanged when we included cases with a history of PD. Older community-dwelling adults without a clinical diagnosis of PD have evidence of LBs throughout the CNS including the spinal cord which is associated with parkinsonism and more severe nigral neuronal loss.

An Intelligent Neural Stem Cell Delivery System for Neurodegenerative Diseases Treatment

Transplanted stem cells constitute a new therapeutic strategy for the treatment of neurological disorders. Emerging evidence indicates that a negative microenvironment, particularly one characterized by the acute inflammation/immune response caused by physical injuries or transplanted stem cells, severely impacts the survival of transplanted stem cells. In this study, to avoid the influence of the increased inflammation following physical injuries, an intelligent, double-layer, alginate hydrogel system is designed. This system fosters the matrix metalloproeinases (MMP) secreted by transplanted stem cell reactions with MMP peptide grafted on the inner layer and destroys the structure of the inner hydrogel layer during the inflammatory storm. Meanwhile, the optimum concentration of the arginine-glycine-aspartate (RGD) peptide is also immobilized to the inner hydrogels to obtain more stem cells before arriving to the outer hydrogel layer. It is found that blocking Cripto-1, which promotes embryonic stem cell differentiation to dopamine neurons, also accelerates this process in neural stem cells. More interesting is the fact that neural stem cell differentiation can be conducted in astrocyte-differentiation medium without other treatments. In addition, the system can be adjusted according to the different parameters of transplanted stem cells and can expand on the clinical application of stem cells in the treatment of this neurological disorder.

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.

Rapid eye movement sleep behavior disorder and the link to alpha-synucleinopathies

Rapid eye movement (REM) sleep behavior disorder (RBD) involves REM sleep without atonia in conjunction with a recurrent nocturnal dream enactment behavior, with vocalizations such as shouting and screaming, and motor behaviors such as punching and kicking. Secondary RBD is well described in association with neurological disorders including Parkinson's disease (PD), multiple system atrophy (MSA), and other conditions involving brainstem structures such as tumors. However, RBD alone is now considered to be a potential harbinger of later development of neurodegenerative disorders, in particular PD, MSA, dementia with Lewy bodies (DLB), and pure autonomic failure. These conditions are linked by their underpinning pathology of alpha-synuclein protein aggregation. In RBD, it is therefore important to recognize the potential risk for later development of an alpha-synucleinopathy, and to investigate for other potential causes such as medications. Other signs and symptoms have been described in RBD, such as orthostatic hypotension, or depression. While it is important to recognize these features to improve patient management, they may ultimately provide clinical clues that will lead to risk stratification for phenoconversion. A critical need is to improve our ability to counsel patients, particularly with regard to prognosis. The ability to identify who, of those with RBD, is at high risk for later neurodegenerative disorders will be paramount, and would in addition advance our understanding of the prodromal stages of the alpha-synucleinopathies. Moreover, recognition of at-risk individuals for neurodegenerative disorders may ultimately provide a platform for the testing of possible neuroprotective agents for these neurodegenerative disorders.

miRNA-based signatures in cerebrospinal fluid as potential diagnostic tools for early stage Parkinson's disease

Parkinson’s Disease is the second most common neurodegenerative disorder, affecting 1–2% of the elderly population. Its diagnosis is still based on the identification of motor symptoms when a considerable number of dopaminergic neurons are already lost. The development of translatable biomarkers for accurate diagnosis at the earliest stages of PD is of extreme interest. Several microRNAs have been associated with PD pathophysiology. Consequently, microRNAs are emerging as potential biomarkers, especially due to their presence in Cerebrospinal Fluid and peripheral circulation. This study employed small RNA sequencing, protein binding ligand assays and machine learning in a cross-sectional cohort comprising 40 early stage PD patients and 40 well-matched controls. We identified a panel comprising 5 microRNAs (Let-7f-5p, miR-27a-3p, miR-125a-5p, miR-151a-3p and miR-423-5p), with 90% sensitivity, 80% specificity and 82% area under the curve (AUC) for the differentiation of the cohorts. Moreover, we combined miRNA profiles with hallmark-proteins of PD and identified a panel (miR-10b-5p, miR-22-3p, miR-151a-3p and α-synuclein) reaching 97% sensitivity, 90% specificity and 96% AUC. We performed a gene ontology analysis for the genes targeted by the microRNAs present in each panel and showed the likely association of the models with pathways involved in PD pathogenesis.

Brain Atrophy and Reorganization of Structural Network in Parkinson's Disease With Hemiparkinsonism

Hemiparkinsonism duration in patients with Parkinson's disease (PD) is a key time window to study early pathology of PD. We aimed to comprehensively explore the alterations of deformation and structural network in PD patients with hemiparkinsonism, which could potentially disclose the early biomarker for PD. Thirty-one PD patients with hemiparkinsonism and 37 age- and gender- matched normal controls were included in the present study. First of all, we normalized the left hemisphere of structural images as the contralateral side to the affected limbs. Deformation-based morphometry (DBM) was conducted to evaluate the brain atrophy and/or enlargement. structural networks were constructed by thresholding gray matter volume correlation matrices of 116 regions and analyzed using graph theoretical approaches (e.g., small-worldness, global, and nodal measures). Significantly decreased deformation values were observed in the temporoparietal regions like bilateral middle temporal gyri, ipsilateral precuneus and contralateral Rolandic operculum extending to supramarginal and postcentral gyri. Lower deformation values in contralateral middle temporal gyrus were negatively correlated with higher motor impairment which was dominated by akinesia/rigidity. Moreover, nodal reorganization of structural network mainly located in frontal, temporal, subcortex and cerebellum was bilaterally explored in PD patients with hemiparkinsonism. Increased nodal properties could be commonly observed in frontal lobes. Disruption of subcortex including basal ganglia and amygdala was detected by nodal local efficiency and nodal clustering coefficient. Twelve hubs, mainly from paralimbic-limbic and heteromodal networks, were disrupted and, alternatively, 14 hubs, most of which were located in frontal lobes, were additionally detected in PD patients with hemiparkinsonism. In conclusion, during hemiparkinsonism period, mild brain atrophy in the temporoparietal regions and widespread reorganization of structural network, e.g., enhanced frontal function and disruption of basal ganglia nodes, occurred in both hemispheres. With our data, we can also argue that MTG contralateral to the affected limbs (expressing clinically verified brain atrophy) might be a potential living biomarker to monitor disease progression. Therefore, the combination of DBM and structural network analyses can provide a comprehensive and sensitive evaluation for potential pathogenesis of early PD patients with hemiparkinsonism.

Diagnostic Criteria for Parkinson's Disease: From James Parkinson to the Concept of Prodromal Disease

The diagnosis of Parkinson’s disease (PD) is based on clinical features and differently to the common opinion that detecting this condition is easy, seminal clinicopathological studies have shown that up one-fourth of patients diagnosed as PD during life has an alternative diagnosis at postmortem. The misdiagnosis is even higher when only the initial diagnosis is considered, since the diagnostic accuracy improves by time, during follow-up visits. Given that the confirmation of the diagnosis of PD can be only obtained through neuropathology, to improve and facilitate the diagnostic–therapeutic workup in PD, a number of criteria and guidelines have been introduced in the last three decades. In the present paper, we will critically re-appraise the main diagnostic criteria proposed for PD, with particular attention to the recently published criteria by the International Parkinson and Movement Disorder Society (MDS) task force, underlying their novelty and focusing on the diagnostic issues still open. We also emphasize that the MDS-PD criteria encompass the two main previous sets of diagnostic criteria (United Kingdom PD Society Brain Bank and Gelb’s criteria), introducing at the same time new aspects as the use of non-motor symptoms as additional diagnostic features, and the adoption of the concept of prodromal PD, crucial to enroll in clinical trials PD patients in the very early phase of the disease. To better understand the real diffusion of the new MDS-PD diagnostic criteria among neurologists, we have also collected selective opinions of sixteen movement disorder experts from various world regions on their practical approach for the clinical diagnosis of PD. Results from this brief survey showed that, although innovative and complete, the revised diagnostic criteria produced by MDS task force are still scarcely employed among clinicians. We believe that both national and international scientific societies should operate in the future for a broader diffusion of these criteria with specific initiatives, including dedicated events and teaching courses.