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- Førland, Marthe Gurine, et al.
(author)
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Evolution of cerebrospinal fluid total α-synuclein in Parkinson's disease.
- 2018
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In: Parkinsonism & related disorders. - : Elsevier BV. - 1873-5126 .- 1353-8020. ; 49, s. 4-8
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Journal article (peer-reviewed)abstract
- Cerebrospinal fluid (CSF) total α-synuclein is considered a potential biomarker for Parkinson's disease (PD), but little is known about the evolution of this marker during the course of the disease. Our objective was to investigate whether CSF total α-synuclein concentrations change over time and are associated with motor and cognitive function in PD.CSF total α-synuclein concentrations were quantified in 56 longitudinally followed PD patients, 27 of whom provided CSF repeatedly 2 and/or 4 years later. Another 18 subjects were included as controls. The samples were analyzed using two independent, validated ELISA methods: our recently developed and validated in-house ELISA and a commercial kit from BioLegend.CSF total α-synuclein levels did not distinguish PD patients from controls, displayed no substantial changes during a period of up to 4 years, and did not predict subsequent motor or cognitive decline. These findings were consistent for both analytical methods.Our findings do not support the clinical utility of total α-synuclein as a single diagnostic or prognostic biomarker in PD.
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| 2. |
- Patil, Ketan S., et al.
(author)
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Combinatory microRNA serum signatures as classifiers of Parkinson's disease
- 2019
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In: Parkinsonism & Related Disorders. - : Elsevier. - 1353-8020 .- 1873-5126. ; 64, s. 202-210
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Journal article (peer-reviewed)abstract
- Introduction: As current clinical diagnostic protocols for Parkinson's disease (PD) may be prone to inaccuracies there is a need to identify and validate molecular biomarkers, such as circulating microRNAs, which will complement current practices and increase diagnostic accuracy. This study identifies, verifies and validates combinatory serum microRNA signatures as diagnostic classifiers of PD across different patient cohorts. Methods: 370 PD (drug naive) and control serum samples from the Norwegian ParkWest study were used for identification and verification of differential microRNA levels in PD which were validated in a blind study using 64 NY Parkinsonism in UMea (NYPUM) study serum samples and tested for specificity in 48 Dementia Study of Western Norway (DemWest) study Alzheimer's disease (AD) serum samples using miRNA-microarrays, and quantitative (q) RT-PCR. Proteomic approaches identified potential molecular targets for these microRNAs. Results: Using Affymetrix GeneChip (R) miRNA 4.0 arrays and qRT-PCR we comprehensively analyzed serum microRNA levels and found that the microRNA (PARKmiR)-combinations, hsa-miR-335-5p/hsa-miR-3613-3p (95% CI, 0.87-0.94), hsa-miR-335-5p/hsa-miR-6865-3p (95% CI, 0.87-0.93), and miR-335-5p/miR-3613-3p/miR-6865-3p (95% CI, 0.87-0.94) show a high degree of discriminatory accuracy (AUC 0.9-1.0). The PARKmiR signatures were validated in an independent PD cohort (AUC <= 0.71) and analysis in AD serum samples showed PARKmiR signature specificity to PD. Proteomic analyses showed that the PAFtKmiRs regulate key PD-associated proteins, including alpha-synuclein and Leucine Rich Repeat Kinase 2. Conclusions: Our study has identified and validated unique miRNA serum signatures that represent PD classifiers, which may complement and increase the accuracy of current diagnostic protocols.
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| 3. |
- Ramsay, Neil, et al.
(author)
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Validation of a UPDRS-/MDS-UPDRS-based definition of functional dependency for Parkinson's disease
- 2020
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In: Parkinsonism & Related Disorders. - : Elsevier. - 1353-8020 .- 1873-5126. ; 76, s. 49-53
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Journal article (peer-reviewed)abstract
- INTRODUCTION: Functional dependency in basic activities of daily living (ADLs) is a key outcome in Parkinson's disease (PD). We aimed to define dependency in PD, using the original and MDS versions of the Unified Parkinson's Disease Rating Scale (UPDRS).METHODS: We developed two algorithms to define dependency from items of UPDRS Part 2 and MDS-UPDRS Part 2 relating to basic ADLs (feeding, dressing, hygiene and walking, and getting out of a chair). We validated both algorithms using data from 1110 patients from six community-based PD incidence cohorts, testing concurrent validity, convergent validity, and predictive validity.RESULTS: Our optimal algorithm showed high specificity and moderate to high sensitivity versus Schwab & England <80% (specificity 95% [95% confidence interval (CI) 93-97] and sensitivity 65% [95% CI 55-73] at baseline; 88% [95% CI 85-91] and 85% [95% CI 79-97] respectively at five-years follow-up). Convergent validity was demonstrated by strong associations between dependency defined by the algorithm and cognition (MMSE), quality of life (PDQ39), and impairment (UPDRS part 3) (all p < 0.001). Algorithm-defined dependency status also predicted mortality: HR for mortality in those dependent vs independent at baseline was 1.6 (95%CI 1.2-2.1) and in those dependent vs independent at five-years' follow-up was 2.2 (1.6-3.0).DISCUSSION: We have demonstrated the concurrent validity, convergent validity, and predictive validity of a UPDRS-/MDS-UPDRS-based algorithm to define functional dependency in PD. This can be used for studying dependency in any study where UPDRS or MDS-UPDRS part 2 data have been collected.
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