How have advances in genetic technology modified movement disorder nosology?

The role of genetics and its technological development have been fundamental in advancing the field of movement disorders, opening the door to precision medicine. Starting from the revolutionary discovery of the locus of the Huntington’s disease gene, we review the milestones of genetic discoveries in movement disorders and their impact on clinical practice and research efforts. Before the 1980s, early techniques did not allow the identification of genetic alteration in complex diseases. Further advances increasingly defined a large number of pathogenic genetic alterations. Moreover, these techniques allowed epigenomic, transcriptomic and microbiome analyses. In the 2020s, these new technologies are poised to displace phenotype-based classifications towards a nosology based on genetic/biological data. Advances in genetic technologies are engineering a reversal of the phenotype-to-genotype order of nosology development, replacing convergent clinicopathological disease models with the genotypic divergence required for future precision medicine applications.Fil: Sturchio, A.. University of Cincinnati; Estados UnidosFil: Marsili, L.. University of Cincinnati; Estados UnidosFil: Mahajan, A.. University of Cincinnati; Estados UnidosFil: Grimberg, M.B.. University of Cincinnati; Estados UnidosFil: Kauffman, Marcelo Andres. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; ArgentinaFil: Espay, A.J.. University of Cincinnati; Estados Unido

Revisiting protein aggregation as pathogenic in sporadic Parkinson and Alzheimer diseases.

The gold standard for a definitive diagnosis of Parkinson disease (PD) is the pathologic finding of aggregated α-synuclein into Lewy bodies and for Alzheimer disease (AD) aggregated amyloid into plaques and hyperphosphorylated tau into tangles. Implicit in this clinicopathologic-based nosology is the assumption that pathologic protein aggregation at autopsy reflects pathogenesis at disease onset. While these aggregates may in exceptional cases be on a causal pathway in humans (e.g., aggregated α-synuclein in SNCA gene multiplication or aggregated β-amyloid in APP mutations), their near universality at postmortem in sporadic PD and AD suggests they may alternatively represent common outcomes from upstream mechanisms or compensatory responses to cellular stress in order to delay cell death. These 3 conceptual frameworks of protein aggregation (pathogenic, epiphenomenon, protective) are difficult to resolve because of the inability to probe brain tissue in real time. Whereas animal models, in which neither PD nor AD occur in natural states, consistently support a pathogenic role of protein aggregation, indirect evidence from human studies does not. We hypothesize that (1) current biomarkers of protein aggregates may be relevant to common pathology but not to subgroup pathogenesis and (2) disease-modifying treatments targeting oligomers or fibrils might be futile or deleterious because these proteins are epiphenomena or protective in the human brain under molecular stress. Future precision medicine efforts for molecular targeting of neurodegenerative diseases may require analyses not anchored on current clinicopathologic criteria but instead on biological signals generated from large deeply phenotyped aging populations or from smaller but well-defined genetic-molecular cohorts

Plasma NfL, clinical subtypes and motor progression in Parkinson's disease.

INTRODUCTION: neurofilament light chain (NfL) levels have been proposed as reliable biomarkers of neurodegeneration in Parkinson's disease (PD) but the relationship between plasma NfL, clinical subtypes of PD and motor progression is still debated. METHODS: plasma NfL concentration was measured in 45 healthy controls and consecutive 92 PD patients who underwent an extensive motor and non-motor assessment at baseline and after 2 years of follow-up. PD malignant phenotype was defined as the combination of at least two out of cognitive impairment, orthostatic hypotension and REM sleep behavior disorder. PD patients were divided according to the age-adjusted cut-offs of plasma NfL levels into high and normal NfL (H-NfL and N-NfL, respectively). A multivariable linear regression model was used to assess the value of plasma NfL as predictor of 2-years progression in PD. RESULTS: NfL was higher in PD patients than in controls (p = 0.037). H-NfL (n = 16) group exhibited more severe motor and non-motor symptoms, higher prevalence of malignant phenotype and worse motor progression (MDS-UPDRS-III 11.3 vs 0.7 points, p = 0.003) compared to N-NfL group (n = 76). In linear regression analyses plasma NfL emerged as the best predictor of 2-year motor progression compared to age, sex, disease duration, baseline motor/non-motor variables. CONCLUSION: increased plasma NfL concentration is associated with malignant PD phenotype and faster motor progression. These findings support the role of NfL assessment as a useful measure for stratifying patients with different baseline slopes of decline in future clinical trials of putative disease-modifying treatments

Outcome measurement in functional neurological disorder: a systematic review and recommendations.

OBJECTIVES: We aimed to identify existing outcome measures for functional neurological disorder (FND), to inform the development of recommendations and to guide future research on FND outcomes. METHODS: A systematic review was conducted to identify existing FND-specific outcome measures and the most common measurement domains and measures in previous treatment studies. Searches of Embase, MEDLINE and PsycINFO were conducted between January 1965 and June 2019. The findings were discussed during two international meetings of the FND-Core Outcome Measures group. RESULTS: Five FND-specific measures were identified-three clinician-rated and two patient-rated-but their measurement properties have not been rigorously evaluated. No single measure was identified for use across the range of FND symptoms in adults. Across randomised controlled trials (k=40) and observational treatment studies (k=40), outcome measures most often assessed core FND symptom change. Other domains measured commonly were additional physical and psychological symptoms, life impact (ie, quality of life, disability and general functioning) and health economics/cost-utility (eg, healthcare resource use and quality-adjusted life years). CONCLUSIONS: There are few well-validated FND-specific outcome measures. Thus, at present, we recommend that existing outcome measures, known to be reliable, valid and responsive in FND or closely related populations, are used to capture key outcome domains. Increased consistency in outcome measurement will facilitate comparison of treatment effects across FND symptom types and treatment modalities. Future work needs to more rigorously validate outcome measures used in this population

Choosing the most suitable classifier For supporting assistive technology adoption In people with Parkinson’s disease: a fuzzy Multi-criteria approach

Parkinson’s disease (PD) is the second most common neurodegenerative disorder which requires a long-term, interdisciplinary disease management. While there remains no cure for Parkinson’s disease, treatments are available to help reduce the main symptoms and maintain quality of life for as long as possible. Owing to the global burden faced by chronic conditions such as PD, Assistive technologies (AT’s) are becoming an increasingly common prescribed form of treatment. Low adoption is hampering the potential of digital technologies within health and social care. It is then necessary to employ classification algorithms have been developed for differentiating adopters and non-adopters of these technologies; thereby, potential negative effects on people with PD and cost overruns can be further minimized. This paper bridges this gap by extending the Multi-criteria decision-making approach adopted in technology adoption modeling for people with dementia. First, the fuzzy Analytic Hierarchy Process (FAHP) is applied to estimate the initial relative weights of criteria and sub-criteria. Then, the Decisionmaking Trial and Evaluation Laboratory (DEMATEL) is used for evaluating the interrelations and feedback among criteria and sub-criteria. The Technique for Order of Preferences by Similarity to Ideal Solution (TOPSIS) is finally implemented to rank three classifiers (Lazy IBk – knearest neighbors, Naïve bayes, and J48 decision tree) according to their ability to model technology adoption. A real case study considering is presented to validate the proposed approach

Functional neurological disorders in Parkinson disease

OBJECTIVE: To ascertain demographic and clinical features of Parkinson disease (PD) associated with functional neurological features. METHODS: A standardised form was used to extract data from electronic records of 53 PD patients with associated functional neurological disorders (PD-FND) across eight movement disorders centres in the USA, Canada and Europe. These subjects were matched for age, gender and disease duration to PD patients without functional features (PD-only). Logistic regression analysis was used to compare both groups after adjusting for clustering effect. RESULTS: Functional symptoms preceded or co-occurred with PD onset in 34% of cases, nearly always in the most affected body side. Compared with PD-only subjects, PD-FND were predominantly female (68%), had longer delay to PD diagnosis, greater prevalence of dyskinesia (42% vs 18%; P=0.023), worse depression and anxiety (P=0.033 and 0.025, respectively), higher levodopa-equivalent daily dose (972±701 vs 741±559 mg; P=0.029) and lower motor severity (P=0.019). These patients also exhibited greater healthcare resource utilisation, higher use of [(123)I]FP-CIT SPECT and were more likely to have had a pre-existing psychiatric disorder (P=0.008) and family history of PD (P=0.036). CONCLUSIONS: A subtype of PD with functional neurological features is familial in one-fourth of cases and associated with more psychiatric than motor disability and greater use of diagnostic and healthcare resources than those without functional features. Functional manifestations may be prodromal to PD in one-third of patients

Biomarker-driven phenotyping in Parkinson's disease: A translational missing link in disease-modifying clinical trials

Past clinical trials of putative neuroprotective therapies have targeted PD as a single pathogenic disease entity. From an Oslerian clinicopathological perspective, the wide complexity of PD converges into Lewy bodies and justifies a reductionist approach to PD: A single-mechanism therapy can affect most of those sharing the classic pathological hallmark. From a systems-biology perspective, PD is a group of disorders that, while related by sharing the feature of nigral dopamine-neuron degeneration, exhibit unique genetic, biological, and molecular abnormalities, which probably respond differentially to a given therapeutic approach, particularly for strategies aimed at neuroprotection. Under this model, only biomarker-defined, homogenous subtypes of PD are likely to respond optimally to therapies proven to affect the biological processes within each subtype. Therefore, we suggest that precision medicine applied to PD requires a reevaluation of the biomarker-discovery effort. This effort is currently centered on correlating biological measures to clinical features of PD and on identifying factors that predict whether various prodromal states will convert into the classical movement disorder. We suggest, instead, that subtyping of PD requires the reverse view, where abnormal biological signals (i.e., biomarkers), rather than clinical definitions, are used to define disease phenotypes. Successful development of disease-modifying strategies will depend on how relevant the specific biological processes addressed by an intervention are to the pathogenetic mechanisms in the subgroup of targeted patients. This precision-medicine approach will likely yield smaller, but well-defined, subsets of PD amenable to successful neuroprotection.Fil: Espay, Alberto J.. University of Cincinnati; Estados UnidosFil: Schwarzschild, Michael A.. Massachusetts General Hospital; Estados UnidosFil: Tanner, Caroline M.. University of California; Estados UnidosFil: Fernandez, Hubert H.. Cleveland Clinic; Estados UnidosFil: Simon, David K.. Harvard Medical School; Estados UnidosFil: Leverenz, James B.. Cleveland Clinic; Estados UnidosFil: Merola, Aristide. University of Cincinnati; Estados UnidosFil: Chen Plotkin, Alice. University of Pennsylvania; Estados UnidosFil: Brundin, Patrik. Van Andel Research Institute. Center for Neurodegenerative Science; Estados UnidosFil: Kauffman, Marcelo Andres. Universidad Austral; Argentina. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; ArgentinaFil: Erro, Roberto. Universita di Verona; Italia. University College London; Reino UnidoFil: Kieburtz, Karl. University of Rochester Medical Center; Estados UnidosFil: Woo, Daniel. University of Cincinnati; Estados UnidosFil: Macklin, Eric A.. Massachusetts General Hospital; Estados UnidosFil: Standaert, David G.. University of Alabama at Birmingahm; Estados UnidosFil: Lang, Anthony E.. University of Toronto; Canad

Long-term dementia prevalence in Parkinson Disease: Glass half-full?

Introduction: Dementia occurs in up to 80% of Parkinson’s disease (PD) patients long-term, but studies reporting such high rates were published years ago and had relatively small sample sizes and other limitations. Objective: To determine long-term, cumulative dementia prevalence rates in PD using data from two large, ongoing, prospective observational studies. Design: Analyses of data from the Parkinson’s Progression Markers Initiative (PPMI) and a longstanding PD research clinical core at the University of Pennsylvania (Penn). Setting: PPMI is a multi-site international study, and Penn is a single site study at a tertiary movement disorders center. Participants: PPMI enrolls de novo, untreated PD participants at baseline, and Penn enrolls a convenience cohort from a large clinical center. Methods: For PPMI a cognitive battery and MDS-UPDRS Part I are administered annually, and the site investigator assigns a cognitive diagnosis annually. At Penn a comprehensive cognitive battery is administered either annually or biennially, and a cognitive diagnosis is made by expert consensus. Main Outcomes: Kaplan-Meier (KM) survival curves were fit for time from PD diagnosis to stable dementia diagnosis for each cohort, using assigned cognitive diagnosis of dementia as the primary endpoint (for both PPMI and Penn), and MoCA score <21 and MDS-UPDRS Part I cognition score ≥3 as secondary endpoints (for PPMI). In addition, cumulative dementia prevalence by PD disease duration was tabulated for each study and endpoint. Results: For the PPMI cohort, 417 PD participants were seen at baseline; estimated cumulative probability of dementia at year 10 disease duration were: 7% (site investigator diagnosis), 9% (MoCA) or 7.4% (MDS-UPDRS Part I cognition). For the Penn cohort, 389 PD participants were followed over time, with 184 participants (47% of cohort) eventually diagnosed with dementia. The KM curve for the Penn cohort had median time to dementia diagnosis =15 years (95% CI: 13-15) disease duration; the estimated cumulative probability of dementia was 27% at year 10, 50% at year 15, and 74% at year 20. Conclusions and Relevance: Results from two large, prospective studies suggest that dementia in Parkinson disease occurs less frequently, or later in the disease course, than often-cited previous research studies have reported

Differential response to pallidal deep brain stimulation among monogenic dystonias: systematic review and meta-analysis

ObjectiveGenetic subtypes of dystonia may respond differentially to deep brain stimulation of the globus pallidus pars interna (GPi DBS). We sought to compare GPi DBS outcomes among the most common monogenic dystonias.MethodsThis systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses and Meta-analysis of Observational Studies in Epidemiology guidelines. We searched PubMed for studies on genetically confirmed monogenic dystonia treated with GPi DBS documenting pre-surgical and post-surgical assessments using the Burke-Fahn-Marsden Dystonia Rating Scale Motor Score (BFMMS) and Burke-Fahn-Marsden Disability Score (BFMDS). We performed (i) meta-analysis for each gene mutation; (ii) weighted ordinary linear regression analyses to compare BFMMS and BFMDS outcomes between DYT-TOR1A and other monogenic dystonias, adjusting for age and disease duration and (iii) weighted linear regression analysis to estimate the effect of age, sex and disease duration on GPi DBS outcomes. Results were summarised with mean change and 95% CI.ResultsDYT-TOR1A (68%, 38.4 points; p<0.001), DYT-THAP1 (37% 14.5 points; p<0.001) and NBIA/DYT-PANK2 (27%, 21.4 points; p<0.001) improved in BFMMS; only DYT-TOR1A improved in BFMDS (69%, 9.7 points; p<0.001). Improvement in DYT-TOR1A was significantly greater than in DYT-THAP1 (BFMMS -31%), NBIA/DYT-PANK2 (BFMMS -35%; BFMDS -53%) and CHOR/DYT-ADCY5 (BFMMS -36%; BFMDS -42%). Worse motor outcomes were associated with longer dystonia duration and older age at dystonia onset in DYT-TOR1A, longer dystonia duration in DYT/PARK-TAF1 and younger age at dystonia onset in DYT-SGCE.ConclusionsGPi DBS outcomes vary across monogenic dystonias. These data serve to inform patient selection and prognostic counselling