Tracking the course of prodromal Parkinson’s disease
Notice bibliographique
Résumé
This scientific commentary refers to ‘Trajectories of prediagnostic functioning in Parkinson disease’, by Darweesh et al. (doi:10.1093/brain/aww291). Timeline of Parkinson’s disease progression. The diagnosis of Parkinson’s disease (PD), based on clinical criteria, is preceded by a prodromal phase of years or even decades. Previous studies have focused mainly on non-motor symptoms, with the precise timing of each symptom differing across the studies and presumably dependent on anatomical localization of Lewy body pathology within the nervous system (both dopaminergic and non-dopaminergic neurons), the severity of neuronal dysfunction and loss in affected regions, and the threshold of these factors required to produce symptoms. The study from Darweesh et al. indicates that early motor impairments can also be identified years before diagnosis. Progressive disability is driven by the accumulation of motor and non-motor symptoms during the course of the disease (particularly late complications such as motor fluctuations, falls, visual hallucinations and dementia). Ageing and dual pathology are likely to play a role in disease expression. RBD = rapid eye movement sleep behaviour disorder. This study was embedded in the prospective Rotterdam Study, a population-based cohort study in which 78% of residents aged 55 or older from the Ommoord district in Rotterdam were enrolled. After excluding cases of parkinsonism and dementia at baseline, 6456 individuals were followed-up between 1990 and 2013. They underwent five study visits in which daily functioning, motor features, and non-motor features (such as cognition, mood and autonomic function) were assessed. There was an impressive rate of follow-up at each visit of 89–95%. Screening for possible parkinsonism relied on several overlapping strategies: in-person evaluation during study visits (including testing for parkinsonian signs by research nurses using standardized protocols), use of anti-parkinsonian medications (based on pharmacy records), and alerts from continuous monitoring of health records. In the event of screening positive in any of these modalities, participants were examined by a research physician specialized in neurological disorders to establish whether they did in fact have parkinsonism, after which the final diagnosis was decided by a consensus panel. In all, 109 cases of incident Parkinson’s disease were diagnosed during the 23-year follow-up period. The study compared the differences in prediagnostic trajectories between Parkinson’s disease cases and selected matched controls (ratio of 1:10). From 7 years before diagnosis, those with Parkinson’s disease reported difficulties with complex tasks requiring a combination of motor and non-motor skills (earliest differences were seen with travelling). Problems with basic activities of daily living became more common ∼5 years before diagnosis (earliest differences were seen with eating) and increased thereafter. This deterioration in daily functioning was paralleled by the emergence of motor impairments, initially in the upper limbs (finger tapping, reduced arm swing) and then more generally (tremor, poverty of movement, imbalance, rigidity, postural abnormalities, falls). A more rapid decline in cognitive scores was observed as early as 7 years before diagnosis in Parkinson’s disease cases compared to controls, with tasks affecting executive function and processing speed primarily affected. Anxiety symptoms, depressive symptoms and use of laxatives only became significantly different in the last few years before diagnosis. This study builds on work from Schrag and colleagues (2014) who, using a large primary care database in the UK, found that tremor and constipation pre-dated the diagnosis of Parkinson’s disease by up to 10 years. A variety of other motor and non-motor features were also found to be more common at 5 and 2 years prior to diagnosis. Similarly, other studies have characterized the evolution of prodromal clinical markers in cohorts known to be at higher risk of Parkinson’s disease, such as those with rapid eye movement sleep behaviour disorder (Postuma et al., 2012) and glucocerebrosidase mutations (Beavan et al., 2015). As the authors acknowledge, this study does not capture the full burden of prodromal symptoms in Parkinson’s disease as many important domains such as sleep and olfactory disturbance were not included. Having said that, some of the results are in line with previous prospective studies. In common with the Rochester Epidemiology Project (Shiba et al., 2000), Darweesh et al. observed anxiety and depression preceding Parkinson’s disease but, in contrast to the earlier project, they found that these complaints developed in close proximity to the time of diagnosis. This raises the possibility that the changes might have been partly caused or exacerbated by unappreciated loss of motor or cognitive functioning (i.e. reactive or secondary) rather than having a distinct neuroanatomical basis in α-synuclein-related degeneration. As in the Honolulu-Asia Aging Study (Ross et al., 2012), constipation (based on laxative use as a proxy measure) was found to be more common in Parkinson’s disease cases. Comprehensive evaluation of other autonomic parameters was not performed. As for all clinical studies of Parkinson’s disease, the potential for misdiagnosis must be considered. Even when specialists in movement disorders use defined criteria, the accuracy of a clinical diagnosis of Parkinson’s disease remains ∼85% when compared to neuropathological findings as the gold standard, and is substantially lower in those with disease duration <5 years (53%) or those who have not received any/adequate dopaminergic replacement (26%) (Adler et al., 2014). It is noteworthy that the age-specific incidence rates of Parkinson’s disease in this study were higher than most other population-based cohorts. One possible explanation for this is that some individuals had an incorrect diagnosis, and with this in mind it is disappointing that the study did not specify the number of individuals diagnosed with atypical parkinsonian syndromes such as progressive supranuclear palsy, multiple system atrophy and corticobasal syndrome; nor did it report the number of patients in whom the original diagnosis of Parkinson's disease was revised. Furthermore, given the high average age at diagnosis (78 years), the possibility of vascular brain disease or other pathologies (e.g. Alzheimer’s disease) contributing to mild parkinsonian signs may also have been more of an issue (Louis et al., 2006). Despite these caveats, this is an important study and the results are extremely valuable. How might they change our approach to the identification and management of Parkinson’s disease? First, the study informs us that motor symptoms in Parkinson’s disease may impact on daily activity far earlier than previously thought. This should be borne in mind when assessing patients because it may signal the need for earlier symptomatic treatment rather than the ‘wait and watch’ approach that many neurologists still espouse. Second, the finding of cognitive deficits early in the prediagnostic course could argue—depending on the anatomical basis of these complaints—against the Braak hypothesis of caudal-rostral spread of pathology. Further work is needed to clarify the clinical-pathological correlations of early premotor/prodromal features, whether the spread of α-synuclein pathology through the nervous system is responsible for all Parkinson’s disease symptoms, or whether dual pathologies (especially in the elderly population studied) contribute in any way to the prodromal course. Finally, the study adds to the belief that large-scale population screening has the potential to identify individuals at-risk (or in the early stages) of Parkinson’s disease. In 2015, the Movement Disorders Society published research criteria for the diagnosis of prodromal Parkinson’s disease (Berg et al., 2015). Subsequent efforts to retrospectively apply these criteria in elderly populations have shown that they are capable of identifying individuals who go on to develop disease (Mahlknecht et al., 2016). Enriching these cohorts using additional risk factors known to be associated with synucleinopathies is likely to further facilitate the identification of high-risk individuals. Several studies such as the Parkinson’s Associated Risk Study (PARS), the Tübingen Evaluation of Risk Factors for Early Detection of Neurodegeneration (TREND) study, and PREDICT-PD are now exploring this possibility. Once definitive diagnostic biomarkers are available (e.g. imaging or measurement of α-synuclein from biospecimens or peripheral tissue biopsies), these individuals could undergo more definitive diagnostic characterization and then be enrolled in clinical trials at what is now considered a ‘prodromal stage’ of their disease. By targeting the right patients at the right time, we should be optimistic that effective neuroprotective therapies will be found in the years ahead. Glossary Braak hypothesis: First proposed by Professor Heiko Braak and colleagues, this staging classification is based on the principle that α-synuclein pathology begins in the enteric nervous system, medulla and olfactory bulb and ascends to more rostral structures including the substantia nigra and cerebral cortex. Nested case-control study: Variation of a case-control study in which only a subset of controls from the cohort are compared to the incident cases. Prodromal Parkinson’s disease: The stage of disease where early signs or symptoms of neurodegeneration related to Parkinson’s disease are present, but clinical diagnosis based on fully evolved motor parkinsonism is not yet possible. Rotterdam study: A prospective, population-based cohort study set up to investigate the occurrence and risk factors for various diseases (cardiovascular, neurological, ophthalmological, endocrine) in the elderly. DPB is supported by an Edmond J Safra Fellowship in Movement Disorders from the Michael J Fox Foundation.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».