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Bhidayasiri R, Aiba I, Nomoto M. The centenarian blueprint: lessons in defying Parkinson's disease. J Neural Transm (Vienna) 2024:10.1007/s00702-024-02875-y. [PMID: 39729254 DOI: 10.1007/s00702-024-02875-y] [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: 11/22/2024] [Accepted: 12/10/2024] [Indexed: 12/28/2024]
Abstract
Recent advancements in neurology have shifted focus from mere diagnosis to comprehensive management of movement disorders, particularly Parkinson's Disease (PD), which is rapidly increasing in prevalence due to global ageing trends. While age is a key risk factor for PD, centenarians often exhibit a remarkably low prevalence of the disease, presenting an intriguing paradox. This viewpoint explores potential reasons for this low prevalence, drawing on studies from regions with high centenarian populations, known as Blue Zones. The authors highlight the importance of genetic, lifestyle, and environmental factors in promoting healthy ageing and examines how these may contribute to the resilience against PD found in centenarians. By understanding the protective mechanisms in centenarians, particularly the concept of hormesis and factors like diet, exercise, and social connections, we may inform prevention strategies for PD. The study proposes the "EAT, MOVE, SLEEP, PROTECT, and REPEAT" approach as a framework for lifestyle interventions to counteract PD risk factors. Ultimately, centenarians offer valuable insights into delaying neurodegeneration, providing a model for potential preventive trials for PD.
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Affiliation(s)
- Roongroj Bhidayasiri
- Chulalongkorn Centre of Excellence for Parkinson's Disease & Related Disorders, Department of Medicine, Faculty of Medicine, Chulalongkorn University and King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, 10330, Thailand.
- The Academy of Science, The Royal Society of Thailand, Bangkok, 10300, Thailand.
- Chulalongkorn Centre of Excellence for Parkinson's Disease & Related Disorders, Chulalongkorn University Hospital, 1873 Rama 4 Road, Bangkok, 10330, Thailand.
| | - Ikuko Aiba
- Department of Neurology, National Hospital Organization, Higashinagoya National Hospital, Aichi, 465-8620, Japan
| | - Masahiro Nomoto
- Department of Neurology, Clinical Research Centre, Saiseikai Imabari Hospital, Ehime, 799- 1592, Japan
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Kiesmann M, Martin RE, Sauleau E, Bulubas I, Fleury MC, Perisse J, Kaltenbach G, Schmitt E. Diagnosis of vascular parkinsonism: A new tool for gait hypokinesia occurring in older persons. Parkinsonism Relat Disord 2023; 109:105360. [PMID: 36921515 DOI: 10.1016/j.parkreldis.2023.105360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 02/27/2023] [Accepted: 03/05/2023] [Indexed: 03/09/2023]
Abstract
INTRODUCTION Reliable diagnosis of vascular parkinsonism (VaP) in the presence of a gait hypokinesia is an issue that is encountered in geriatrics. The EVAMAR-AGEX study was focusing on the phenomenon of recurrent falls in older persons (OP) with this parkinsonian gait. The present study is focusing on the diagnosis of VaP-related parkinsonian gait by developing a diagnostic guidance model adapted to OP. METHODS Data from baseline and the 2-year follow-up visit were used to carry out univariate analysis and calculation of odds ratios, allowing to identify relevant variables to include in the diagnostic guidance model. To evaluate the model, confusion matrices were created, evaluating true positive, false negative, false positive and true negative incidences, sensitivity and specificity, and negative and positive predictive values. RESULTS 79 patients included 58% male; average age 81.24 years. VaP diagnosis according to Zijlmans criteria occurred in 28%; neurodegenerative parkinsonian syndromes in 72%. A 4-criteria model was established to facilitate diagnostic: lack of prior hallucinations, lack of movement disorders tremor excluded, no cognitive fluctuations, and ≥75 years of age at diagnosis. In combination of 4/4 criteria, all of them were required to disclose a specificity of 91% in the diagnosis of VaP. In combination of 3/4, in case of negative test, a negative predictive value for VaP diagnosis of 0.97 was obtained. CONCLUSION The challenge of our tool is both to be able to rule out what is probably not a VaP and to argue what makes a VaP diagnosis probable in OP.
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Affiliation(s)
- Michèle Kiesmann
- Geriatric Department, University Hospitals of Strasbourg, Strasbourg, France
| | | | - Erik Sauleau
- Biostatistical Laboratory, iCube - CNRS UMR 7357, Department of Public Health, Methods in Clinical Research, University of Strasbourg, Strasbourg, France
| | - Irina Bulubas
- Geriatric Department, University Hospitals of Strasbourg, Strasbourg, France
| | - Marie Céline Fleury
- Neurology Department, University Hospitals of Strasbourg, Strasbourg, France
| | - Jérémie Perisse
- Geriatric Department, University Hospitals of Strasbourg, Strasbourg, France
| | - Georges Kaltenbach
- Geriatric Department, University Hospitals of Strasbourg, Strasbourg, France
| | - Elise Schmitt
- Geriatric Department, University Hospitals of Strasbourg, Strasbourg, France; EA-3072, University of Strasbourg, Strasbourg, France.
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Pavelka L, Rauschenberger A, Landoulsi Z, Pachchek S, May P, Glaab E, Krüger R, Acharya G, Aguayo G, Alexandre M, Ali M, Allen D, Ammerlann W, Balling R, Bassis M, Beaumont K, Becker R, Bellora C, Berchem G, Berg D, Bisdorff A, Brockmann K, Calmes J, Castillo L, Contesotto G, Diederich N, Dondelinger R, Esteves D, Fagherazzi G, Ferrand JY, Gantenbein M, Gasser T, Gawron P, Ghosh S, Glaab E, Gomes C, De Lope EG, Goncharenko N, Graas J, Graziano M, Groues V, Grünewald A, Gu W, Hammot G, Hanff AM, Hansen L, Hansen M, Heneka M, Henry E, Herbrink S, Herenne E, Herzinger S, Heymann M, Hu M, Hundt A, Jacoby N, Lebioda JJ, Jaroz Y, Klopfenstein Q, Krüger R, Lambert P, Landoulsi Z, Lentz R, Liepelt I, Liszka R, Longhino L, Lorentz V, Lupu PC, Mackay C, Maetzler W, Marcus K, Marques G, Marques T, May P, Mcintyre D, Mediouni C, Meisch F, Menster M, Minelli M, Mittelbronn M, Mollenhauer B, Mommaerts K, Moreno C, Moudio S, Mühlschlegel F, Nati R, Nehrbass U, Nickels S, Nicolai B, Nicolay JP, Oertel W, Ostaszewski M, Pachchek S, Pauly C, Pauly L, Pavelka L, Perquin M, Lima RR, Rauschenberger A, Rawal R, Bobbili DR, Rosales E, Rosety I, Rump K, Sandt E, Satagopam V, Schlesser M, Schmitt M, Schmitz S, Schneider R, Schwamborn J, Sharify A, Soboleva E, Sokolowska K, Terwindt O, Thien H, Thiry E, Loo RTJ, Trefois C, Trouet J, Tsurkalenko O, Vaillant M, Valenti M, Boas LV, Vyas M, Wade-Martins R, Wilmes P. Age at onset as stratifier in idiopathic Parkinson’s disease – effect of ageing and polygenic risk score on clinical phenotypes. NPJ Parkinsons Dis 2022; 8:102. [PMID: 35945230 PMCID: PMC9363416 DOI: 10.1038/s41531-022-00342-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 05/30/2022] [Indexed: 12/23/2022] Open
Abstract
Several phenotypic differences observed in Parkinson’s disease (PD) patients have been linked to age at onset (AAO). We endeavoured to find out whether these differences are due to the ageing process itself by using a combined dataset of idiopathic PD (n = 430) and healthy controls (HC; n = 556) excluding carriers of known PD-linked genetic mutations in both groups. We found several significant effects of AAO on motor and non-motor symptoms in PD, but when comparing the effects of age on these symptoms with HC (using age at assessment, AAA), only positive associations of AAA with burden of motor symptoms and cognitive impairment were significantly different between PD vs HC. Furthermore, we explored a potential effect of polygenic risk score (PRS) on clinical phenotype and identified a significant inverse correlation of AAO and PRS in PD. No significant association between PRS and severity of clinical symptoms was found. We conclude that the observed non-motor phenotypic differences in PD based on AAO are largely driven by the ageing process itself and not by a specific profile of neurodegeneration linked to AAO in the idiopathic PD patients.
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立花 久. [Diagnosis and treatment of old-onset Parkinson's disease]. Nihon Ronen Igakkai Zasshi 2021; 58:341-352. [PMID: 34483156 DOI: 10.3143/geriatrics.58.341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Campese N, Fanciulli A, Stefanova N, Haybaeck J, Kiechl S, Wenning GK. Neuropathology of multiple system atrophy: Kurt Jellinger`s legacy. J Neural Transm (Vienna) 2021; 128:1481-1494. [PMID: 34319460 PMCID: PMC8528766 DOI: 10.1007/s00702-021-02383-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 07/07/2021] [Indexed: 01/07/2023]
Abstract
Multiple System Atrophy (MSA) is a rare, fatal neurodegenerative disorder. Its etiology and exact pathogenesis still remain poorly understood and currently no disease-modifying therapy is available to halt or slow down this detrimental neurodegenerative process. Hallmarks of the disease are α-synuclein rich glial cytoplasmic inclusions (GCIs). Neuropathologically, various degrees of striatonigral degeneration (SND) and olivopontocerebellar atrophy (OPCA) can be observed. Since the original descriptions of this multifaceted disorder, several steps forward have been made to clarify its neuropathological hallmarks and key pathophysiological mechanisms. The Austrian neuropathologist Kurt Jellinger substantially contributed to the understanding of the underlying neuropathology of this disease, to its standardized assessment and to a broad systematical clinic-pathological correlation. On the occasion of his 90th birthday, we reviewed the current state of the art in the field of MSA neuropathology, highlighting Prof. Jellinger’s substantial contribution.
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Affiliation(s)
- Nicole Campese
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Via Roma 67, 56126, Pisa, Italy.,Department of Neurology, Medical University of Innsbruck, Anichstrasse 35, 6020, Innsbruck, Austria
| | - Alessandra Fanciulli
- Department of Neurology, Medical University of Innsbruck, Anichstrasse 35, 6020, Innsbruck, Austria
| | - Nadia Stefanova
- Department of Neurology, Medical University of Innsbruck, Anichstrasse 35, 6020, Innsbruck, Austria
| | - Johannes Haybaeck
- Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Müllerstrasse 44, 6020, Innsbruck, Austria.,Diagnostic & Research Center for Molecular BioMedicine, Institute of Pathology, Medical University Graz, Neue Stiftingtalstrasse 6, 8010, Graz, Austria
| | - Stefan Kiechl
- Department of Neurology, Medical University of Innsbruck, Anichstrasse 35, 6020, Innsbruck, Austria
| | - Gregor K Wenning
- Department of Neurology, Medical University of Innsbruck, Anichstrasse 35, 6020, Innsbruck, Austria.
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Baldacci F, Mazzucchi S, Della Vecchia A, Giampietri L, Giannini N, Koronyo-Hamaoui M, Ceravolo R, Siciliano G, Bonuccelli U, Elahi FM, Vergallo A, Lista S, Giorgi FS. The path to biomarker-based diagnostic criteria for the spectrum of neurodegenerative diseases. Expert Rev Mol Diagn 2020; 20:421-441. [PMID: 32066283 PMCID: PMC7445079 DOI: 10.1080/14737159.2020.1731306] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 02/14/2020] [Indexed: 12/21/2022]
Abstract
Introduction: The postmortem examination still represents the reference standard for detecting the pathological nature of chronic neurodegenerative diseases (NDD). This approach displays intrinsic conceptual limitations since NDD represent a dynamic spectrum of partially overlapping phenotypes, shared pathomechanistic alterations that often give rise to mixed pathologies.Areas covered: We scrutinized the international clinical diagnostic criteria of NDD and the literature to provide a roadmap toward a biomarker-based classification of the NDD spectrum. A few pathophysiological biomarkers have been established for NDD. These are time-consuming, invasive, and not suitable for preclinical detection. Candidate screening biomarkers are gaining momentum. Blood neurofilament light-chain represents a robust first-line tool to detect neurodegeneration tout court and serum progranulin helps detect genetic frontotemporal dementia. Ultrasensitive assays and retinal scans may identify Aβ pathology early, in blood and the eye, respectively. Ultrasound also represents a minimally invasive option to investigate the substantia nigra. Protein misfolding amplification assays may accurately detect α-synuclein in biofluids.Expert opinion: Data-driven strategies using quantitative rather than categorical variables may be more reliable for quantification of contributions from pathophysiological mechanisms and their spatial-temporal evolution. A systems biology approach is suitable to untangle the dynamics triggering loss of proteostasis, driving neurodegeneration and clinical evolution.
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Affiliation(s)
- Filippo Baldacci
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l’hôpital, Paris, France
| | - Sonia Mazzucchi
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | | | - Linda Giampietri
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Nicola Giannini
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Maya Koronyo-Hamaoui
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Roberto Ceravolo
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Gabriele Siciliano
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Ubaldo Bonuccelli
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Fanny M. Elahi
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Andrea Vergallo
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l’hôpital, Paris, France
- Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, Paris, France
- Department of Neurology, Institute of Memory and Alzheimer’s Disease (IM2A), Pitié-Salpêtrière Hospital, Paris, France
| | - Simone Lista
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l’hôpital, Paris, France
- Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, Paris, France
- Department of Neurology, Institute of Memory and Alzheimer’s Disease (IM2A), Pitié-Salpêtrière Hospital, Paris, France
| | - Filippo Sean Giorgi
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
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Verny M, Duyckaerts C. Cognitive deficit, and neuropathological correlates, in the oldest-old. Rev Neurol (Paris) 2020; 176:670-676. [PMID: 32178879 DOI: 10.1016/j.neurol.2020.01.355] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 01/06/2020] [Accepted: 01/07/2020] [Indexed: 12/14/2022]
Abstract
Several disorders are usually involved in the cognitive deficit of the oldest old. Alzheimer disease is the commonest. It is usually characterized by progressive memory impairment - neocortical symptoms occurring much later in the course of the disease. Alzheimer disease should not be considered any more as the single cause of a cognitive deficit in a very old patient. Vascular alterations, possibly causing microinfarcts, are commonly associated, especially in cerebral amyloid angiopathy. A slowly progressive memory deficit with negative CSF biomarkers of Alzheimer's disease may be due to hippocampal sclerosis that may be the consequence of multiple causes: in most of the cases, it is associated with neuronal TDP-43 inclusions. Recently, a distribution of these inclusions to a territory more extensive than the hippocampus has been reported and attributed to a new entity, called Limbic-predominant Age-related TDP-43 Encephalopathy (LATE) with or without hippocampal sclerosis. The presence of cortical Lewy bodies may cause an intellectual deficit or contribute to it. The prevalence of dementia with cortical Lewy bodies in the oldest old is discussed. Tau inclusions in cortical glia have also been shown to participate to the intellectual deficit. Association of neurodegenerative and vascular changes is the most frequent situation in the very old patients. Systemic diseases such as diabetes or heart failure, prescription drugs (when misused), or toxic such as alcohol may also contribute to the cognitive impairment and be amenable to treatment.
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Affiliation(s)
- M Verny
- Centre de gériatrie, pavillon Marguerite-Bottard, hôpital de la Pitié-Salpêtrière, AP-HP, Sorbonne Université, 47-83, boulevard de l'Hôpital, 75651 Paris cedex, France; Team Neuronal Cell Biology & Pathology, Sorbonne University and UMR8256 (CNRS), Paris, France.
| | - C Duyckaerts
- Département de Neuropathologie Escourolle, AP-HP Sorbonne Université, Paris, France; ICM, équipe Alzheimer-Prions, Paris, France
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Qian E, Huang Y. Subtyping of Parkinson's Disease - Where Are We Up To? Aging Dis 2019; 10:1130-1139. [PMID: 31595207 PMCID: PMC6764738 DOI: 10.14336/ad.2019.0112] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2018] [Accepted: 01/12/2019] [Indexed: 01/22/2023] Open
Abstract
Heterogenous clinical presentations of Parkinson's disease have aroused several attempts in its subtyping for the purpose of strategic implementation of treatment in order to maximise therapeutic effects. Apart from a priori classifications based purely on motor features, cluster analysis studies have achieved little success in receiving widespread adoption. A priori classifications demonstrate that their chosen factors, whether it be age or certain motor symptoms, do have an influence on subtypes. However, the cluster analysis approach is able to integrate these factors and other clinical features to produce subtypes. Differences in inclusion criteria from datasets, in variable selection and in methodology between cluster analysis studies have made it difficult to compare the subtypes. This has impeded such subtypes from clinical applications. This review analysed existing subtypes of Parkinson's disease, and suggested that future research should aim to discover subtypes that are robustly replicable across multiple datasets rather than focussing on one dataset at a time. Hopefully, through clinical applicable subtyping of Parkinson's disease would lead to translation of these subtypes into research and clinical use.
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Affiliation(s)
- Elizabeth Qian
- School of Medical Science, Faculty of Medicine, UNSW Sydney, 2032, Australia.
| | - Yue Huang
- School of Medical Science, Faculty of Medicine, UNSW Sydney, 2032, Australia.
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
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