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

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

Co-morbidity and polypharmacy in Parkinson's Disease:insights from a large Scottish primary care database

Background: Parkinson’s disease is complicated by comorbidity and polypharmacy, but the extent and patterns of these are unclear. We describe comorbidity and polypharmacy in patients with and without Parkinson’s disease across 31 other physical, and seven mental health conditions. Methods: We analysed primary health-care data on 510,502 adults aged 55 and over. We generated standardised prevalence rates by age-groups, gender, and neighbourhood deprivation, then calculated age, sex and deprivation adjusted odds ratios (OR) and 95% confidence intervals (95% CI) for those with PD compared to those without, for the prevalence, and number of conditions. Results: Two thousand six hundred forty (0.5%) had Parkinson’s disease, of whom only 7.4% had no other conditions compared with 22.9% of controls (adjusted OR [aOR] 0.43, 95% 0.38–0.49). The Parkinson’s group had more conditions, with the biggest difference found for seven or more conditions (PD 12.1% vs. controls 3.9%; aOR 2.08 95% CI 1.84–2.35). 12 of the 31 physical conditions and five of the seven mental health conditions were significantly more prevalent in the PD group. 44.5% with Parkinson’s disease were on five to nine repeat prescriptions compared to 24.5% of controls (aOR 1.40; 95% CI 1.28 to 1.53) and 19.2% on ten or more compared to 6.2% of controls (aOR 1.90; 95% CI 1.68 to 2.15). Conclusions: Parkinson’s disease is associated with substantial physical and mental co-morbidity. Polypharmacy is also a significant issue due to the complex nature of the disease and associated treatments

Pathway to Regulatory Approval of Digital Health Technologies in Progressive Supranuclear Palsy: A Scoping Review

Background/Objectives: Progressive supranuclear palsy (PSP) is an atypical Parkinsonian disorder characterized by Parkinsonism with gait imbalance, vertical gaze palsy, and frontal cognitive dysfunction. Though digital health technologies (DHTs) are widely used both clinically and in research as outcome measures, there is a lack of consistency applied to these devices and their resulting metrics. This scoping review aims to identify efforts taken to validate wearable DHTs for use in PSP, identify gaps in research, and discuss the steps needed to expand their use and acceptance as primary trial endpoints. Methods: In this scoping review, we conducted a search of the MEDLINE database to examine the use of DHTs as outcome measures in Progressive Supranuclear Palsy. Results: A total of 17 publications were identified and reviewed. Included articles evaluated the use of DHT to measure lower extremity function/gait, balance, upper extremity function, and speech. Conclusions: Our scoping review highlights the importance of standardization of DHT metrics by thorough assessment of their content validity, reliability, construct validity, responsiveness, and discriminant validity. Efforts must be taken to ensure DHTs capture clinically relevant, patient-centered outcome measures that are comparable to conventional rating scales, that consistently discriminate disease progression. Incorporation of DHTs as clinical trial endpoints has the potential to encourage clinical research and to advance patient care

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

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

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

Anticipating Tomorrow: Tailoring Parkinson's Symptomatic Therapy Using Predictors of Outcome

Background: Although research into Parkinson's disease (PD) subtypes and outcome predictions has continued to advance, recommendations for using outcome prediction to guide current treatment decisions remain sparse. Objectives: To provide expert opinion‐based recommendations for individually tailored PD symptomatic treatment based on knowledge of risk prediction and subtypes. Methods: Using a modified Delphi approach, members of the Movement Disorders Society (MDS) Task Force on PD subtypes generated a series of general recommendations around the question: “Using what you know about genetic/biological/clinical subtypes (or any individual‐level predictors of outcome), what advice would you give for selecting symptomatic treatments for an individual patient now, based on what their subtype or individual characteristics predict about their future disease course?” After four iterations and revisions, those recommendations with over 75% endorsement were adopted. Results: A total of 19 recommendations were endorsed by a group of 13 panelists. The recommendations primarily centered around two themes: (1) incorporating future risk of cognitive impairment into current treatment plans; and (2) identifying future symptom clusters that might be forestalled with a single medication. Conclusions: These recommendations provide clinicians with a framework for integrating future outcomes into patient‐specific treatment choices. They are not prescriptive guidelines, but adaptable suggestions, which should be tailored to each individual. They are to be considered as a first step of a process that will continue to evolve as additional stakeholders provide new insights and as new information becomes available. As individualized risk prediction advances, the path to better tailored treatment regimens will become clearer

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