ObjectiveTo investigate the diagnostic value of serum neurofilament light chain (NFL) in patients with clear signs of parkinsonism but whose specific diagnosis was yet uncertain.MethodsSerum samples were collected from patients with clear signs of parkinsonism but with uncertain diagnosis at the inclusion. Clinical diagnoses of Parkinson disease (PD) and atypical parkinsonism disorders (APDs) were established after 3 years of follow-up and updated again after a maximum of 12 years in case longer follow-up data were available. Serum NFL was quantified by single molecule array in patients with PD (n = 55) and APD (n = 29, multiple system atrophy = 22, progressive supranuclear palsy = 7) and 53 nonneurologic controls.ResultsSerum NFL levels were elevated and differentiated the APD group (mean 23.8 ± 10.3 ng/L) from PD (mean 10.4 ± 4.9 ng/L) and controls (mean 11.5 ± 6.5 ng/L, p < 0.0001) with accuracy levels up to 91% (sensitivity = 86% and specificity = 85%). Serum NFL strongly correlated with CSF NFL levels (r = 0.72, p < 0.0001) in all groups and with age in PD (r = 0.78, p < 0.0001) and controls (r = 0.66, p < 0.0001). In our cohort, the probability of having APD was 76% (positive predictive value) and of having PD 92% (negative predictive value).ConclusionSerum NFL levels are markedly elevated in APD compared to PD and discriminate APDs from PD with high accuracy. Serum NFL may be a useful clinical biomarker to identify APD, even at stages when clinical symptoms are not yet conclusive.Classification of evidenceThis study provides Class II evidence that serum NFL levels accurately discriminate APDs from PD.

A reliable biomarker is needed for accurate and early differentiation between Parkinson disease and the various forms of atypical parkinsonism. We used a novel real‐time quaking‐induced conversion (RT‐QuIC) assay to detect α‐synuclein (α‐syn) aggregates in cerebrospinal fluid (CSF) of 118 patients with parkinsonism of uncertain clinical etiology and 52 controls. Diagnostic accuracy to distinguish α‐synucleinopathies from non–α‐synucleinopathies and controls was 84% (sensitivity = 75%, specificity = 94%, area under the curve = 0.84, 95% confidence interval = 0.78–0.91, p < 0.0001, positive predictive value = 93%). CSF α‐syn RT‐QuIC could be a useful diagnostic tool to help clinicians differentiate α‐synucleinopathies from other forms of parkinsonism when the clinical picture is uncertain. Ann Neurol 2019;85:777–781

Parkinson’s disease (PD) and multiple system atrophy (MSA) are both part of the spectrum of neurodegenerative movement disorders and α-synucleinopathies with overlap of symptoms especially at early stages of the disease but with distinct disease progression and responses to dopaminergic treatment. Therefore, having biomarkers that specifically classify patients, which could discriminate PD from MSA, would be very useful. MicroRNAs (miRNAs) regulate protein translation and are observed in biological fluids, including cerebrospinal fluid (CSF), and may therefore have potential as biomarkers of disease. The aim of our study was to determine if miRNAs in CSF could be used as biomarkers for either PD or MSA. Using quantitative PCR (qPCR), we evaluated expression levels of 10 miRNAs in CSF patient samples from PD ( n = 28), MSA ( n = 17), and non-neurological controls ( n = 28). We identified two miRNAs (miR-24 and miR-205) that distinguished PD from controls and four miRNAs that differentiated MSA from controls (miR-19a, miR-19b, miR-24, and miR-34c). Combinations of miRNAs accurately discriminated either PD (area under the curve (AUC) = 0.96) or MSA (AUC = 0.86) from controls. In MSA, we also observed that miR-24 and miR-148b correlated with cerebellar ataxia symptoms, suggesting that these miRNAs are involved in cerebellar degeneration in MSA. Our findings support the potential of miRNA panels as biomarkers for movement disorders and may provide more insights into the pathological mechanisms related to these disorders.

BACKGROUND AND PURPOSE:The differentiation between Parkinson disease and atypical parkinsonian syndromes can be challenging in clinical practice, especially in early disease stages. Brain MR imaging can help to increase certainty about the diagnosis. Our goal was to evaluate the added value of SWI in relation to conventional 3T brain MR imaging for the diagnostic work-up of early-stage parkinsonism.

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IntroductionThe aim of this study is to evaluate whether the diagnostic accuracy of 3 T brain MRI is improved by region of interest (ROI) measures of diffusion tensor imaging (DTI), to differentiate between neurodegenerative atypical parkinsonism (AP) and Parkinson’s disease (PD) in early stage parkinsonism.MethodsWe performed a prospective observational cohort study of 60 patients presenting with early stage parkinsonism and initial uncertain diagnosis. At baseline, patients underwent a 3 T brain MRI including DTI. After clinical follow-up (mean 28.3 months), diagnoses could be made in 49 patients (30 PD and 19 AP). Conventional brain MRI was evaluated for regions of atrophy and signal intensity changes. Tract-based spatial statistics and ROI analyses of DTI were performed to analyze group differences in mean diffusivity (MD) and fractional anisotropy (FA), and diagnostic thresholds were determined. Diagnostic accuracy of conventional brain MRI and DTI was assessed with the receiver operating characteristic (ROC).ResultsSignificantly higher MD of the centrum semiovale, body corpus callosum, putamen, external capsule, midbrain, superior cerebellum, and superior cerebellar peduncles was found in AP. Significantly increased MD of the putamen was found in multiple system atrophy–parkinsonian form (MSA-P) and increased MD in the midbrain and superior cerebellar peduncles in progressive supranuclear palsy (PSP). The diagnostic accuracy of brain MRI to identify AP as a group was not improved by ROI measures of MD, though the diagnostic accuracy to identify MSA-P was slightly increased (AUC 0.82 to 0.85).ConclusionThe diagnostic accuracy of brain MRI to identify AP as a group was not improved by the current analysis approach to DTI, though DTI measures could be of added value to identify AP subgroups.

Background: Parkinson's disease (PD) and atypical parkinsonisms (APD) have overlapping symptoms challenging an early diagnosis. Diagnostic accuracy is important because PD and APD have different prognosis and response to treatment. We aimed to identify diagnostic inflammatory biomarkers of PD and APD in cerebrospinal fluid (CSF) using the multiplex proximity extension assay (PEA) technology and to study possible correlations of biomarkers with disease progression. Methods: CSF from a longitudinal cohort study consisting of PD and APD patients (PD, n = 44; multiple system atrophy (MSA), n = 14; vascular parkinsonism (VaP), n = 9; and PD with VaP, n = 7) and controls (n = 25) were analyzed. Results: Concentrations of CCL28 were elevated in PD compared to controls (p = 0.0001). Five other biomarkers differentiated both MSA and PD from controls (p < 0.05) and 10 biomarkers differentiated MSA from controls, of which two proteins, i.e. beta nerve growth factor (β-NGF) and Delta and Notch like epidermal growth factor-related receptor (DNER), were also present at lower levels in MSA compared to PD (both p = 0.032). Two biomarkers (MCP-1 and MMP-10) positively correlated with PD progression (rho > 0.650; p < 0.01). Conclusions: PEA technique identified potential new CSF biomarkers to help to predict the prognosis of PD. Also, we identified new candidate biomarkers to distinguish MSA from PD.

SummaryBackgroundPrevious case-control studies have suggested that the absence of a swallow-tail appearance in the substantia nigra on high-resolution SWI, representing nigrosome-1, has high accuracy to identify Parkinson’s disease (PD). The first goal of our study was to evaluate nigrosome-1 ex vivo using optimized high-resolution susceptibility sensitive MRI. Our second goal was to evaluate its diagnostic value in vivo using a clinical 3T SWI sequence to differentiate between PD and atypical parkinsonism (AP) in a cohort of patients with early-stage parkinsonism.Material/MethodsCase-control pilot study to evaluate nigrosome-1 ex vivo (2 PD, 2 controls), using high-resolution susceptibility sensitive sequences at 11.7 T MRI. Next, evaluation of nigrosome-1 in vivo using a clinical 3 T SWI sequence in a prospective cohort of 60 patients with early-stage parkinsonism (39 PD, 21 AP). Moreover, 12 control subjects were scanned.The bilateral substantia nigra was evaluated by two neuroradiologists for the presence, absence or indecisive presence of nigrosome-1. The discriminative power was evaluated by Receiver-Operating Characteristic.ResultsWe identified nigrosome-1 in ex vivo control subjects. Nigrosome-1 was not identified in the ex vivo PD cases. In our prospective clinical cohort study, the AUC for the swallow-tail sign to discriminate between PD and AP was 0.56 (0.41–0.71) for reader 1 and 0.68 (0.55–0.82) for reader 2.ConclusionsThe diagnostic accuracy of the swallow-tail sign was marginal to discriminate between PD and AP using our clinical 3 T SWI sequence.