Assessment of variation in α-synuclein seed amplification assay results in the PPMI cohort: Association with hyposmia

This poster describes α-synuclein seed amplification assay results in the PPMI cohort including in subgroups based on genetic variant status and olfactory deficit

Predicting Progression in Parkinson's Disease Using Baseline and 1-Year Change Measures.

BackgroundImproved prediction of Parkinson's disease (PD) progression is needed to support clinical decision-making and to accelerate research trials.ObjectivesTo examine whether baseline measures and their 1-year change predict longer-term progression in early PD.MethodsParkinson's Progression Markers Initiative study data were used. Participants had disease duration ≤2 years, abnormal dopamine transporter (DAT) imaging, and were untreated with PD medications. Baseline and 1-year change in clinical, cerebrospinal fluid (CSF), and imaging measures were evaluated as candidate predictors of longer-term (up to 5 years) change in Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) score and DAT specific binding ratios (SBR) using linear mixed-effects models.ResultsAmong 413 PD participants, median follow-up was 5 years. Change in MDS-UPDRS from year-2 to last follow-up was associated with disease duration (β= 0.351; 95% CI = 0.146, 0.555), male gender (β= 3.090; 95% CI = 0.310, 5.869), and baseline (β= -0.199; 95% CI = -0.315, -0.082) and 1-year change (β= 0.540; 95% CI = 0.423, 0.658) in MDS-UPDRS; predictors in the model accounted for 17.6% of the variance in outcome. Predictors of percent change in mean SBR from year-2 to last follow-up included baseline rapid eye movement sleep behavior disorder score (β= -0.6229; 95% CI = -1.2910, 0.0452), baseline (β= 7.232; 95% CI = 2.268, 12.195) and 1-year change (β= 45.918; 95% CI = 35.994,55.843) in mean striatum SBR, and 1-year change in autonomic symptom score (β= -0.325;95% CI = -0.695, 0.045); predictors in the model accounted for 44.1% of the variance.ConclusionsBaseline clinical, CSF, and imaging measures in early PD predicted change in MDS-UPDRS and dopamine-transporter binding, but the predictive value of the models was low. Adding the short-term change of possible predictors improved the predictive value, especially for modeling change in dopamine-transporter binding

Characteristics of patients misdiagnosed with Alzheimer’s disease and their medication use: an analysis of the NACC-UDS database

BACKGROUND: This study compared individuals whose clinical diagnosis of Alzheimer’s disease (AD) matched or did not match neuropathologic results at autopsy on clinical and functional outcomes (cognitive impairment, functional status and neuropsychiatric symptoms). The study also assessed the extent of potentially inappropriate medication use (using potentially unnecessary medications or potentially inappropriate prescribing) among misdiagnosed patients. METHODS: Longitudinal data from the National Alzheimer’s Coordinating Center Uniform Data Set (NACC-UDS, 2005–2010) and corresponding NACC neuropathological data were utilized to compare 88 misdiagnosed and 438 accurately diagnosed patients. RESULTS: Following adjustment of sociodemographic characteristics, the misdiagnosed were found to have less severe cognitive and functional impairment. However, after statistical adjustment for sociodemographics, dementia severity level, time since onset of cognitive decline and probable AD diagnosis at baseline, the groups significantly differed on only one outcome: the misdiagnosed were less likely to be depressed/dysphoric. Among the misdiagnosed, 18.18% were treated with potentially inappropriate medication. An additional analysis noted this rate could be as high as 67.10%. CONCLUSIONS: Findings highlight the importance of making an accurate AD diagnosis to help reduce unnecessary treatment and increase appropriate therapy. Additional research is needed to demonstrate the link between potentially inappropriate treatment and adverse health outcomes in misdiagnosed AD patients

Digital mobility sub-study in the Parkinson's Progressive Marker Initiative (PPMI) study

This poster details the gait sub-study project in PPMI. The sub-study aims to test the feasibility and validity of digital mobility data for enrichment of the prodromal screening and to assess the sensitivity of these measures to early phase progression in prodromal and recently diagnosed patients with Parkinson’s disease. The poster details the protocol and the initial preliminary results of the first 21 participants. The post5er was presented in the Movement Disorders Society Conference held in Copenhagen, Denmark in Sept 2023

The Parkinson's progression markers initiative (PPMI) - establishing a PD biomarker cohort.

ObjectiveThe Parkinson's Progression Markers Initiative (PPMI) is an observational, international study designed to establish biomarker-defined cohorts and identify clinical, imaging, genetic, and biospecimen Parkinson's disease (PD) progression markers to accelerate disease-modifying therapeutic trials.MethodsA total of 423 untreated PD, 196 Healthy Control (HC) and 64 SWEDD (scans without evidence of dopaminergic deficit) subjects were enrolled at 24 sites. To enroll PD subjects as early as possible following diagnosis, subjects were eligible with only asymmetric bradykinesia or tremor plus a dopamine transporter (DAT) binding deficit on SPECT imaging. Acquisition of data was standardized as detailed at www.ppmi-info.org.ResultsApproximately 9% of enrolled subjects had a single PD sign at baseline. DAT imaging excluded 16% of potential PD subjects with SWEDD. The total MDS-UPDRS for PD was 32.4 compared to 4.6 for HC and 28.2 for SWEDD. On average, PD subjects demonstrated 45% and 68% reduction in mean striatal and contralateral putamen Specific Binding Ratios (SBR), respectively. Cerebrospinal fluid (CSF) was acquired from >97% of all subjects. CSF (PD/HC/SWEDD pg/mL) α-synuclein (1845/2204/2141) was reduced in PD vs HC or SWEDD (P < 0.03). Similarly, t-tau (45/53) and p-tau (16/18) were reduced in PD versus HC (P < 0.01).InterpretationPPMI has detailed the biomarker signature for an early PD cohort defined by clinical features and imaging biomarkers. This strategy provides the framework to establish biomarker cohorts and to define longitudinal progression biomarkers to support future PD treatment trials

Mapping the EQ-5D index by UPDRS and PDQ-8 in patients with Parkinson’s disease

Background: Clinical studies employ the Unified Parkinson’s Disease Rating Scale (UPDRS) to measure the severity of Parkinson’s disease. Evaluations often fail to consider the health-related quality of life (HrQoL) or apply disease-specific instruments. Health-economic studies normally use estimates of utilities to calculate quality-adjusted life years. We aimed to develop an estimation algorithm for EuroQol- 5 dimensions (EQ-5D)-based utilities from the clinical UPDRS or disease-specific HrQoL data in the absence of original utilities estimates. Methods: Linear and fractional polynomial regression analyses were performed with data from a study of Parkinson’s disease patients (n=138) to predict the EQ-5D index values from UPDRS and Parkinson’s disease questionnaire eight dimensions (PDQ-8) data. German and European weights were used to calculate the EQ-5D index. The models were compared by R2, the root mean square error (RMS), the Bayesian information criterion, and Pregibon’s link test. Three independent data sets validated the models. Results: The regression analyses resulted in a single best prediction model (R2: 0.713 and 0.684, RMS: 0.139 and 13.78 for indices with German and European weights, respectively) consisting of UPDRS subscores II, III, IVa-c as predictors. When the PDQ-8 items were utilised as independent variables, the model resulted in an R2 of 0.60 and 0.67. The independent data confirmed the prediction models. Conclusion: The best results were obtained from a model consisting of UPDRS subscores II, III, IVa-c. Although a good model fit was observed, primary EQ-5D data are always preferable. Further validation of the prediction algorithm within large, independent studies is necessary prior to its generalised use

Lewy Body Dementia Association\u27s Research Centers of Excellence Program: Inaugural Meeting Proceedings.

The first Lewy Body Dementia Association (LBDA) Research Centers of Excellence (RCOE) Investigator\u27s meeting was held on December 14, 2017, in New Orleans. The program was established to increase patient access to clinical experts on Lewy body dementia (LBD), which includes dementia with Lewy bodies (DLB) and Parkinson\u27s disease dementia (PDD), and to create a clinical trials-ready network. Four working groups (WG) were created to pursue the LBDA RCOE aims: (1) increase access to high-quality clinical care, (2) increase access to support for people living with LBD and their caregivers, (3) increase knowledge of LBD among medical and allied (or other) professionals, and (4) create infrastructure for a clinical trials-ready network as well as resources to advance the study of new therapeutics

Lewy Body Dementia Association\u27s Research Centers of Excellence Program: Inaugural Meeting Proceedings

The first Lewy Body Dementia Association (LBDA) Research Centers of Excellence (RCOE) Investigator\u27s meeting was held on December 14, 2017, in New Orleans. The program was established to increase patient access to clinical experts on Lewy body dementia (LBD), which includes dementia with Lewy bodies (DLB) and Parkinson\u27s disease dementia (PDD), and to create a clinical trials-ready network. Four working groups (WG) were created to pursue the LBDA RCOE aims: (1) increase access to high-quality clinical care, (2) increase access to support for people living with LBD and their caregivers, (3) increase knowledge of LBD among medical and allied (or other) professionals, and (4) create infrastructure for a clinical trials-ready network as well as resources to advance the study of new therapeutics