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      The Personalized Parkinson Project: examining disease progression through broad biomarkers in early Parkinson’s disease

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          Abstract

          Background

          Our understanding of the etiology, pathophysiology, phenotypic diversity, and progression of Parkinson’s disease has stagnated. Consequently, patients do not receive the best care, leading to unnecessary disability, and to mounting costs for society. The Personalized Parkinson Project (PPP) proposes an unbiased approach to biomarker development with multiple biomarkers measured longitudinally. Our main aims are: (a) to perform a set of hypothesis-driven analyses on the comprehensive dataset, correlating established and novel biomarkers to the rate of disease progression and to treatment response; and (b) to create a widely accessible dataset for discovery of novel biomarkers and new targets for therapeutic interventions in Parkinson’s disease.

          Methods/design

          This is a prospective, longitudinal, single-center cohort study. The cohort will comprise 650 persons with Parkinson’s disease. The inclusion criteria are purposely broad: age ≥ 18 years; and disease duration ≤5 years. Participants are followed for 2 years, with three annual assessments at the study center. Outcomes include a clinical assessment (including motor and neuro-psychological tests), collection of biospecimens (stool, whole blood, and cerebrospinal fluid), magnetic resonance imaging (both structural and functional), and ECG recordings (both 12-lead and Holter). Additionally, collection of physiological and environmental data in daily life over 2 years will be enabled through the Verily Study Watch. All data are stored with polymorphic encryptions and pseudonyms, to guarantee the participants’ privacy on the one hand, and to enable data sharing on the other. The data and biospecimens will become available for scientists to address Parkinson’s disease-related research questions.

          Discussion

          The PPP has several distinguishing elements: all assessments are done in a single center; inclusion of “real life” subjects; deep and repeated multi-dimensional phenotyping; and continuous monitoring with a wearable device for 2 years. Also, the PPP is powered by privacy and security by design, allowing for data sharing with scientists worldwide respecting participants’ privacy. The data are expected to open the way for important new insights, including identification of biomarkers to predict differences in prognosis and treatment response between patients. Our long-term aim is to improve existing treatments, develop new therapeutic approaches, and offer Parkinson’s disease patients a more personalized disease management approach.

          Trial registration

          Clinical Trials NCT03364894. Registered December 6, 2017 (retrospectively registered).

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          Most cited references25

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          Validity of the MoCA and MMSE in the detection of MCI and dementia in Parkinson disease.

          Due to the high prevalence of mild cognitive impairment (MCI) and dementia in Parkinson disease (PD), routine cognitive screening is important for the optimal management of patients with PD. The Montreal Cognitive Assessment (MoCA) is more sensitive than the commonly used Mini-Mental State Examination (MMSE) in detecting MCI and dementia in patients without PD, but its validity in PD has not been established. A representative sample of 132 patients with PD at 2 movement disorders centers was administered the MoCA, MMSE, and a neuropsychological battery with operationalized criteria for deficits. MCI and PD dementia (PDD) criteria were applied by an investigator blinded to the MoCA and MMSE results. The discriminant validity of the MoCA and MMSE as screening and diagnostic instruments was ascertained. Approximately one third of the sample met diagnostic criteria for a cognitive disorder (12.9% PDD and 17.4% MCI). Mean (SD) MoCA and MMSE scores were 25.0 (3.8) and 28.1 (2.0). The overall discriminant validity for detection of any cognitive disorder was similar for the MoCA and the MMSE (receiver operating characteristic area under the curve [95% confidence interval]): MoCA (0.79 [0.72, 0.87]) and MMSE (0.76 [0.67, 0.85]), but as a screening instrument the MoCA (optimal cutoff point = 26/27, 64% correctly diagnosed, lack of ceiling effect) was superior to the MMSE (optimal cutoff point = 29/30, 54% correctly diagnosed, presence of ceiling effect). The Montreal Cognitive Assessment, but not the Mini-Mental State Examination, has adequate psychometric properties as a screening instrument for the detection of mild cognitive impairment or dementia in Parkinson disease. However, a positive screen using either instrument requires additional assessment due to suboptimal specificity at the recommended screening cutoff point.
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            Reliability, validity, and clinical correlates of apathy in Parkinson's disease.

            The authors examined a consecutive series of 50 patients for the presence of apathy, depression, anxiety, and neuropsychological deficits using a neuropsychological battery that included a recently designed apathy scale. This scale was found to be reliable and valid in the diagnosis of apathy in patients with PD. Of patients in the study, 12% showed apathy as their primary psychiatric problem, and 30% were both apathetic and depressed. Patients with apathy (with or without depression), showed significantly more deficits in both tasks of verbal memory and time-dependent tasks. Results suggest that apathy is a frequent finding in PD, is significantly associated with specific cognitive impairments, and may have a different mechanism than depression.
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              • Abstract: found
              • Article: not found

              Characterizing mild cognitive impairment in incident Parkinson disease: the ICICLE-PD study.

              To describe the frequency of mild cognitive impairment (MCI) in Parkinson disease (PD) in a cohort of newly diagnosed incident PD cases and the associations with a panel of biomarkers. Between June 2009 and December 2011, 219 subjects with PD and 99 age-matched controls participated in clinical and neuropsychological assessments as part of a longitudinal observational study. Consenting individuals underwent structural MRI, lumbar puncture, and genotyping for common variants of COMT, MAPT, SNCA, BuChE, EGF, and APOE. PD-MCI was defined with reference to the new Movement Disorder Society criteria. The frequency of PD-MCI was 42.5% using level 2 criteria at 1.5 SDs below normative values. Memory impairment was the most common domain affected, with 15.1% impaired at 1.5 SDs. Depression scores were significantly higher in those with PD-MCI than the cognitively normal PD group. A significant correlation was found between visual Pattern Recognition Memory and cerebrospinal β-amyloid 1-42 levels (β standardized coefficient = 0.350; p = 0.008) after controlling for age and education in a linear regression model, with lower β-amyloid 1-42 and 1-40 levels observed in those with PD-MCI. Voxel-based morphometry did not reveal any areas of significant gray matter loss in participants with PD-MCI compared with controls, and no specific genotype was associated with PD-MCI at the 1.5-SD threshold. In a large cohort of newly diagnosed PD participants, PD-MCI is common and significantly correlates with lower cerebrospinal β-amyloid 1-42 and 1-40 levels. Future longitudinal studies should enable us to determine those measures predictive of cognitive decline.
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                Author and article information

                Contributors
                bas.bloem@radboudumc.nl
                wjmarks@verily.com
                ana.silvadelima@radboudumc.nl
                mark.kuijf@mumc.nl
                t.van.laar@umcg.nl
                bart@cs.ru.nl
                marcel.verbeek@radboudumc.nl
                rick.helmich@radboudumc.nl
                bart.vandewarrenburg@radboudumc.nl
                luc.evers@radboudumc.nl
                Joanna.intHout@radboudumc.nl
                tessa.vandezande@radboudumc.nl
                tmsnyder@verily.com
                ritukapur@google.com
                marjan.meinders@radboudumc.nl
                Journal
                BMC Neurol
                BMC Neurol
                BMC Neurology
                BioMed Central (London )
                1471-2377
                17 July 2019
                17 July 2019
                2019
                : 19
                : 160
                Affiliations
                [1 ]ISNI 0000 0004 0444 9382, GRID grid.10417.33, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, , Radboud University Medical Center, ; Nijmegen, The Netherlands
                [2 ]Verily Life Sciences, South San Francisco, CA USA
                [3 ]ISNI 0000 0000 9738 4872, GRID grid.452295.d, CAPES Foundation, Ministry of Education of Brazil, ; Brasília/DF, Brazil
                [4 ]ISNI 0000 0004 0480 1382, GRID grid.412966.e, Department of Neurology, , Maastricht University Medical Center, ; Maastricht, The Netherlands
                [5 ]ISNI 0000 0000 9558 4598, GRID grid.4494.d, Department of Neurology, , Universtity Medical Center Groningen, ; Groningen, The Netherlands
                [6 ]ISNI 0000000122931605, GRID grid.5590.9, Faculty of Science, , University of Nijmegen, ; Nijmegen, The Netherlands
                [7 ]ISNI 0000 0004 0444 9382, GRID grid.10417.33, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Center for Medical Neuroscience, , Radboud University Medical Center, ; Nijmegen, The Netherlands
                [8 ]ISNI 0000 0004 0444 9382, GRID grid.10417.33, Department of Laboratory Medicine, Donders Institute for Brain, Cognition and Behaviour, Donders Center for Medical Neuroscience, , Radboud University Medical Center, ; Nijmegen, The Netherlands
                [9 ]ISNI 0000000122931605, GRID grid.5590.9, Institute for Computing and Information Sciences, , Radboud University, ; Nijmegen, The Netherlands
                [10 ]ISNI 0000 0004 0444 9382, GRID grid.10417.33, Department for Health Evidence, Radboud Institute for Health Sciences, , Radboud University Medical Center, ; Nijmegen, The Netherlands
                [11 ]ISNI 0000 0004 0444 9382, GRID grid.10417.33, Department of Neurology, , Radboud University Medical Center, ; Nijmegen, The Netherlands
                [12 ]Neurology Platform, Verily Life Sciences, South San Francisco, CA USA
                [13 ]ISNI 0000 0004 0444 9382, GRID grid.10417.33, Scientific Center for Quality of Healthcare, Radboud Institute for Health Sciences, , Radboud University Medical Center, ; Nijmegen, the Netherlands
                Article
                1394
                10.1186/s12883-019-1394-3
                6636112
                31315608
                f5833b0e-c485-4af3-9520-5df0a81679db
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 3 April 2018
                : 4 July 2019
                Funding
                Funded by: Verily Life Scineces LLC
                Funded by: FundRef http://dx.doi.org/10.13039/501100006209, Radboud Universitair Medisch Centrum;
                Funded by: FundRef http://dx.doi.org/10.13039/501100001832, Radboud Universiteit;
                Funded by: Top Sector Life Sciences and Health
                Funded by: Provincie Gelderland
                Funded by: Gemeente Nijmegen
                Categories
                Study Protocol
                Custom metadata
                © The Author(s) 2019

                Neurology
                cohort studies,parkinson’s disease,biomarkers,disease progression,wearable device
                Neurology
                cohort studies, parkinson’s disease, biomarkers, disease progression, wearable device

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