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Höglinger GU, Adler CH, Berg D, Klein C, Outeiro TF, Poewe W, Postuma R, Stoessl AJ, Lang AE. A biological classification of Parkinson's disease: the SynNeurGe research diagnostic criteria. Lancet Neurol 2024; 23:191-204. [PMID: 38267191 DOI: 10.1016/s1474-4422(23)00404-0] [Citation(s) in RCA: 67] [Impact Index Per Article: 67.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 09/08/2023] [Accepted: 10/06/2023] [Indexed: 01/26/2024]
Abstract
With the hope that disease-modifying treatments could target the molecular basis of Parkinson's disease, even before the onset of symptoms, we propose a biologically based classification. Our classification acknowledges the complexity and heterogeneity of the disease by use of a three-component system (SynNeurGe): presence or absence of pathological α-synuclein (S) in tissues or CSF; evidence of underlying neurodegeneration (N) defined by neuroimaging procedures; and documentation of pathogenic gene variants (G) that cause or strongly predispose to Parkinson's disease. These three components are linked to a clinical component (C), defined either by a single high-specificity clinical feature or by multiple lower-specificity clinical features. The use of a biological classification will enable advances in both basic and clinical research, and move the field closer to the precision medicine required to develop disease-modifying therapies. We emphasise the initial application of these criteria exclusively for research. We acknowledge its ethical implications, its limitations, and the need for prospective validation in future studies.
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Affiliation(s)
- Günter U Höglinger
- Department of Neurology, University Hospital, Ludwig-Maximilians-University (LMU) and German Center for Neurodegenerative Diseases, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Charles H Adler
- Department of Neurology, Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Daniela Berg
- Christian Albrechts University and University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Christine Klein
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Campus Lübeck, Lüebeck, Germany
| | - Tiago F Outeiro
- Department of Experimental Neurodegeneration, Center for Biostructural Imaging of Neurodegeneration, University Medical Center Göttingen, Göttingen, Germany; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Werner Poewe
- Medical University Innsbruck, Innsbruck, Austria
| | - Ronald Postuma
- Department of Neurology, McGill University, Montreal Neurological Institute, Montreal, QC, Canada
| | - A Jon Stoessl
- Pacific Parkinson's Research Centre and Parkinson's Foundation Centre of Excellence, University of British Columbia, BC, Canada
| | - Anthony E Lang
- University Health Network's Krembil Brain Institute, Edmond J Safra Program in Parkinson's Disease and the Rossy PSP Centre, Toronto Western Hospital, Toronto, ON, Canada.
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Pitton Rissardo J, Caprara ALF. Neuroimaging Techniques in Differentiating Parkinson's Disease from Drug-Induced Parkinsonism: A Comprehensive Review. Clin Pract 2023; 13:1427-1448. [PMID: 37987429 PMCID: PMC10660852 DOI: 10.3390/clinpract13060128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 10/19/2023] [Accepted: 11/13/2023] [Indexed: 11/22/2023] Open
Abstract
Neuroimaging can provide significant benefits in evaluating patients with movement disorders associated with drugs. This literature review describes neuroimaging techniques performed to distinguish Parkinson's disease from drug-induced parkinsonism. The dopaminergic radiotracers already reported to assess patients with drug-induced parkinsonism are [123I]-FP-CIT, [123I]-β-CIT, [99mTc]-TRODAT-1, [18F]-DOPA, [18F]-AV-133, and [18F]-FP-CIT. The most studied one and the one with the highest number of publications is [123I]-FP-CIT. Fludeoxyglucose (18F) revealed a specific pattern that could predict individuals susceptible to developing drug-induced parkinsonism. Another scintigraphy method is [123I]-MIBG cardiac imaging, in which a relationship between abnormal cardiac imaging and normal dopamine transporter imaging was associated with a progression to degenerative disease in individuals with drug-induced parkinsonism. Structural brain magnetic resonance imaging can be used to assess the striatal region. A transcranial ultrasound is a non-invasive method with significant benefits regarding costs and availability. Optic coherence tomography only showed abnormalities in the late phase of Parkinson's disease, so no benefit in distinguishing early-phase Parkinson's disease and drug-induced parkinsonism was found. Most methods demonstrated a high specificity in differentiating degenerative from non-degenerative conditions, but the sensitivity widely varied in the studies. An algorithm was designed based on clinical manifestations, neuroimaging, and drug dose adjustment to assist in the management of patients with drug-induced parkinsonism.
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Stoyanov D. Advances in the Diagnosis and Management of Psychosis. Diagnostics (Basel) 2023; 13:diagnostics13091517. [PMID: 37174908 PMCID: PMC10177207 DOI: 10.3390/diagnostics13091517] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 04/18/2023] [Accepted: 04/20/2023] [Indexed: 05/15/2023] Open
Abstract
Psychosis research in the contemporary sense of scientific inquiry may be traced as far as the formulation of the "unitary psychosis" concept, or Einheitpsychose, which is usually attributed to Wilhelm Griesinger, Ernst von Zeller, and Heinrich Neumann [...].
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Affiliation(s)
- Drozdstoy Stoyanov
- Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 4002 Plovdiv, Bulgaria
- Research Institute, Research Group "Translational and Computational Neuroscience", SRIPD, Medical University Plovdiv, 4002 Plovdiv, Bulgaria
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