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      The Luxembourg Parkinson’s Study: A Comprehensive Approach for Stratification and Early Diagnosis

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          Abstract

          While genetic advances have successfully defined part of the complexity in Parkinson’s disease (PD), the clinical characterization of phenotypes remains challenging. Therapeutic trials and cohort studies typically include patients with earlier disease stages and exclude comorbidities, thus ignoring a substantial part of the real-world PD population. To account for these limitations, we implemented the Luxembourg PD study as a comprehensive clinical, molecular and device-based approach including patients with typical PD and atypical parkinsonism, irrespective of their disease stage, age, comorbidities, or linguistic background. To provide a large, longitudinally followed, and deeply phenotyped set of patients and controls for clinical and fundamental research on PD, we implemented an open-source digital platform that can be harmonized with international PD cohort studies. Our interests also reflect Luxembourg-specific areas of PD research, including vision, gait, and cognition. This effort is flanked by comprehensive biosampling efforts assuring high quality and sustained availability of body liquids and tissue biopsies. We provide evidence for the feasibility of such a cohort program with deep phenotyping and high quality biosampling on parkinsonism in an environment with structural specificities and alert the international research community to our willingness to collaborate with other centers. The combination of advanced clinical phenotyping approaches including device-based assessment will create a comprehensive assessment of the disease and its variants, its interaction with comorbidities and its progression. We envision the Luxembourg Parkinson’s study as an important research platform for defining early diagnosis and progression markers that translate into stratified treatment approaches.

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          Most cited references48

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          Accuracy of clinical diagnosis of idiopathic Parkinson's disease: a clinico-pathological study of 100 cases.

          Few detailed clinico-pathological correlations of Parkinson's disease have been published. The pathological findings in 100 patients diagnosed prospectively by a group of consultant neurologists as having idiopathic Parkinson's disease are reported. Seventy six had nigral Lewy bodies, and in all of these Lewy bodies were also found in the cerebral cortex. In 24 cases without Lewy bodies, diagnoses included progressive supranuclear palsy, multiple system atrophy, Alzheimer's disease, Alzheimer-type pathology, and basal ganglia vascular disease. The retrospective application of recommended diagnostic criteria improved the diagnostic accuracy to 82%. These observations call into question current concepts of Parkinson's disease as a single distinct morbid entity.
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            Clinical diagnosis of progressive supranuclear palsy: The movement disorder society criteria.

            PSP is a neuropathologically defined disease entity. Clinical diagnostic criteria, published in 1996 by the National Institute of Neurological Disorders and Stroke/Society for PSP, have excellent specificity, but their sensitivity is limited for variant PSP syndromes with presentations other than Richardson's syndrome.
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              Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2).

              Informatics for Integrating Biology and the Bedside (i2b2) is one of seven projects sponsored by the NIH Roadmap National Centers for Biomedical Computing (http://www.ncbcs.org). Its mission is to provide clinical investigators with the tools necessary to integrate medical record and clinical research data in the genomics age, a software suite to construct and integrate the modern clinical research chart. i2b2 software may be used by an enterprise's research community to find sets of interesting patients from electronic patient medical record data, while preserving patient privacy through a query tool interface. Project-specific mini-databases ("data marts") can be created from these sets to make highly detailed data available on these specific patients to the investigators on the i2b2 platform, as reviewed and restricted by the Institutional Review Board. The current version of this software has been released into the public domain and is available at the URL: http://www.i2b2.org/software.
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                Author and article information

                Contributors
                Journal
                Front Aging Neurosci
                Front Aging Neurosci
                Front. Aging Neurosci.
                Frontiers in Aging Neuroscience
                Frontiers Media S.A.
                1663-4365
                29 October 2018
                2018
                : 10
                : 326
                Affiliations
                [1] 1Clinical and Experimental Neuroscience, Luxembourg Centre for Systems Biomedicine, University of Luxembourg , Esch-Belval, Luxembourg
                [2] 2Neurology, Centre Hospitalier de Luxembourg , Luxembourg, Luxembourg
                [3] 3Competence Centre in Methodology and Statistics, Luxembourg Institute of Health , Strassen, Luxembourg
                [4] 4Bioinformatics Core, Luxembourg Centre for Systems Biomedicine, University of Luxembourg , Esch-sur Alzette, Luxembourg
                [5] 5Integrated BioBank of Luxembourg , Dudelange, Luxembourg
                [6] 6Developmental and Cellular Biology, Luxembourg Centre for Systems Biomedicine, University of Luxembourg , Esch-sur Alzette, Luxembourg
                [7] 7Clinical and Epidemiological Investigation Center, Luxembourg Institute of Health , Strassen, Luxembourg
                [8] 8Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg , Erlangen, Germany
                [9] 9Department of Neurodegeneration, Hertie-Institute for Clinical Brain Research and German Center for Neurodegenerative Diseases , Tübingen, Germany
                [10] 10Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford , Oxford, United Kingdom
                Author notes

                Edited by: Daniel Ortuño-Sahagún, Universidad de Guadalajara, Mexico

                Reviewed by: Richard Camicioli, University of Alberta, Canada; Elizabeth B. Torres, Rutgers University, The State University of New Jersey, United States

                *Correspondence: Géraldine Hipp, geraldine.hipp@ 123456uni.lu Rejko Krüger, rejko.krueger@ 123456uni.lu
                Article
                10.3389/fnagi.2018.00326
                6216083
                30420802
                788c1f00-3edf-47c4-95c9-ef96c1be6d14
                Copyright © 2018 Hipp, Vaillant, Diederich, Roomp, Satagopam, Banda, Sandt, Mommaerts, Schmitz, Longhino, Schweicher, Hanff, Nicolai, Kolber, Reiter, Pavelka, Binck, Pauly, Geffers, Betsou, Gantenbein, Klucken, Gasser, Hu, Balling and Krüger.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 15 June 2018
                : 26 September 2018
                Page count
                Figures: 3, Tables: 11, Equations: 0, References: 78, Pages: 14, Words: 0
                Funding
                Funded by: Fonds National de la Recherche Luxembourg 10.13039/501100001866
                Categories
                Neuroscience
                Methods

                Neurosciences
                parkinsonism,cohort,longitudinal,stratification,deep phenotyping
                Neurosciences
                parkinsonism, cohort, longitudinal, stratification, deep phenotyping

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