October Infographic: Grossmann, Dajana - MERCS dynamics and calcium homeostasis are differentially disrupted in PINK1- or PRKN-PD neurons

Objective: This study aims to define normative values for the Instrumented Timed Up and Go test using wearable inertial sensors in people affected by Parkinson’s disease and parkinsonism. Background: Parkinson’s disease and atypical parkinsonism (such as Progressive Supranuclear Palsy, Multiple System Atrophy) are neurodegenerative disorders characterized by motor and non-motor symptoms [1]. In addition to […]

In their recent publication, Kühnel et al1 described the progression of multiple system atrophy (MSA) in the European MSA study group (EMSA-SG) cohort via an innovative disease progression model (DPM). DPMs are valuable longitudinal methods to describe MSA natural history while accounting for data uncertainty (delayed diagnosis, uncertain timing, heterogeneous staging).2 The mean trajectories of clinical progression are described along the homogeneous disease continuum (Fig. 1C) rather than the observed time since diagnosis (Fig. 1A) thanks to a temporal recalibration of progression according to an individual latent disease time, anchored to MSA disease stage at inclusion. The population characteristics and the length of individual follow-up are critical in natural history studies and DPMs. Kühnel's study relied on 121 patients with rather advanced stage, outdated diagnosis criteria, and short follow-up of 2 years.1, 3 We replicated Kühnel's analysis on repeated Unified MSA Rating Scale sum scores I (activities of daily living) and II (motor examination) from the French MSA cohort4 (663 patients) with maximum follow-up of 11 years, consensus diagnosis criteria,5 and early stages at entry (see Supplementary Material Data S1 for details). MSA progression spanned a larger period than in the original paper (Fig. 1C) with mean time gaps at inclusion estimated at 3.6 and 9.1 years for moderately-dependent and helpless patients at inclusion, respectively (Fig. 1B right panels); and significant inter-patient differences (SD = 2.14 years). When restricting the sample to 2.5-year follow-up, these differences were smaller, especially among the most aggressively affected patients at entry, with estimates of 2.5 and 6.6 years (Fig. 1B left panels) and smaller inter-patient differences (SD = 0.79 years). This suggests that studies restricted to short-term follow-up overestimate the progression rate and underestimate inter-patient differences. When applying DPMs, differences across stages should be carefully interpreted. They do not quantify the expected amount of time spent in each stage by a patient, but the time gap between patients entering the study at different stages. Estimating the duration spent in each disability stage requires specific modeling of disability over time. Non-informative death: death is assumed to be predictable by the observed course of the markers when death caused by MSA may induce a more informative dropout to be jointly modeled.6 In conclusion, DPM constitutes a promising tool for disease study, but it needs to be interpreted with caution and calls for less stringent assumptions. The replication on the French MSA cohort highlights the importance of describing MSA progression based on long-term follow-up data and large cohorts to prevent too pessimistic projections and underestimation of sample sizes. We would like to thank the French National Research Agency (Project DyMES-ANR-18-C36-0004-01) and the Nouvelle-Aquitaine region (Project AAPR2021A-2020-11937310) for their financial support that made this work possible. Several authors of this publication are members of the European Reference Network for Rare Neurological Diseases—Project ID no: 739510. T.S.: 1A, 1B, 1C, 2A, 2B, 3A M.F.: 2C, 3B A.P.L.: 2C, 3B M.L.: 2C, 3B C.H.: 2C, 3B P.P.: 2C, 3B W.G.M.: 2C, 3B O.R.: 2C, 3B A.F.S.: 1A, 1B, 2A, 2C, 3A C.P.L.: 1A, 1B, 2A, 2C, 3A Research data are not shared. Data S1. Supporting Information. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Heterozygous GAA expansions in the FGF14 gene have been related to autosomal dominant cerebellar ataxia (SCA27B-MIM:620174). Whether they represent a common cause of sporadic late-onset cerebellar ataxia (SLOCA) remains to be established. To estimate the prevalence, characterize the phenotypic spectrum, identify discriminative features, and model longitudinal progression of SCA27B in a prospective cohort of SLOCA patients. FGF14 expansions screening combined with longitudinal deep-phenotyping in a prospective cohort of 118 SLOCA patients (onset >40 years of age, no family history of cerebellar ataxia) without a definite diagnosis. Prevalence of SCA27B was 12.7% (15/118). Higher age of onset, higher Spinocerebellar Degeneration Functional Score, presence of vertigo, diplopia, nystagmus, orthostatic hypotension absence, and sensorimotor neuropathy were significantly associated with SCA27B. Ataxia progression was ≈0.4 points per year on the Scale for Assessment and Rating of Ataxia. FGF14 expansion is a major cause of SLOCA. Our natural history data will inform future FGF14 clinical trials. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The outcome of clinical trials in neurodegeneration can be highly uncertain due to the presence of a strong placebo effect. To develop a longitudinal model that can enhance the success of future Parkinson's disease trials by quantifying trial-to-trial variations in placebo and active treatment response. A longitudinal model-based meta-analysis was conducted on the total score of Unified Parkinson's Disease Rating Scale (UPDRS) Parts 1, 2, and 3. The analysis included aggregate data from 66 arms (observational [4], placebo [28], or investigational-drug-treated [34]) from 4 observational studies and 17 interventional trials. Inter-study variabilities in key parameters were estimated. Residual variability was weighted by the size of study arms. The baseline total UPDRS was estimated to average at 24.5 points. Disease score was estimated to worsen by 3.90 points/year for the duration of the treatments; whilst notably,arms with a lower baseline progressed faster. The model captured the transient nature of the placebo response and sustained symptomatic drug effect. Both placebo and drug effects peaked within 2 months; although, 1 year was needed to observe the full treatment difference. Across these studies, the progression rate varied by 59.4%, the half-life for offset of placebo response varied by 79.4%, and the amplitude for drug effect varied by 105.3%. The longitudinal model-based meta-analysis describes UPDRS progression rate, captures the dynamics of the placebo response, quantifies the effect size of the available therapies, and sets the expectation of uncertainty for future trials. The findings provide informative priors to enhance the rigor and success of future trials of promising agents, including potential disease modifiers. © 2023 GSK. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Data sharing not applicable-no new data generated, or the article describes entirely theoretical research.

Parkinson's disease (PD) patients present with a heterogeneous clinical phenotype, including motor, cognitive, sleep, and affective disruptions. However, this heterogeneity is often either ignored or assessed using only clinical assessments. We aimed to identify different PD sub-phenotypes in a longitudinal follow-up analysis and their electrophysiological profile based on resting-state electroencephalography (RS-EEG) and to assess their clinical significance over the course of the disease. Using electrophysiological features obtained from RS-EEG recordings and data-driven methods (similarity network fusion and source-space spectral analysis), we have performed a clustering analysis to identify disease sub-phenotypes and we examined whether their different patterns of disruption are predictive of disease outcome. We showed that PD patients (n = 44) can be sub-grouped into three phenotypes with distinct electrophysiological profiles. These clusters are characterized by different levels of disruptions in the somatomotor network (Δ and β band), the frontotemporal network (α2 band) and the default mode network (α1 band), which consistently correlate with clinical profiles and disease courses. These clusters are classified into either moderate (only-motor) or mild-to-severe (diffuse) disease. We showed that EEG features can predict cognitive evolution of PD patients from baseline, when the cognitive clinical scores were overlapped. The identification of novel PD subtypes based on electrical brain activity signatures may provide a more accurate prognosis in individual patients in clinical practice and help to stratify subgroups in clinical trials. Innovative profiling in PD can also support new therapeutic strategies that are brain-based and designed to modulate brain activity disruption. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.