Whitwell, Jennifer L.

ObjectiveTo determine whether a machine learning model of voxel level [18f]fluorodeoxyglucose positron emission tomography (PET) data could predict progressive supranuclear palsy (PSP) pathology, as well as outperform currently available biomarkers.MethodsOne hundred and thirty‐seven autopsied patients with PSP (n = 42) and other neurodegenerative diseases (n = 95) who underwent antemortem [18f]fluorodeoxyglucose PET and 3.0 Tesla magnetic resonance imaging (MRI) scans were analyzed. A linear support vector machine was applied to differentiate pathological groups with sensitivity analyses performed to assess the influence of voxel size and region removal. A radial basis function was also prepared to create a secondary model using the most important voxels. The models were optimized on the main dataset (n = 104), and their performance was compared with the magnetic resonance parkinsonism index measured on MRI in the independent test dataset (n = 33).ResultsThe model had the highest accuracy (0.91) and F‐score (0.86) when voxel size was 6mm. In this optimized model, important voxels for differentiating the groups were observed in the thalamus, midbrain, and cerebellar dentate. The secondary models found the combination of thalamus and dentate to have the highest accuracy (0.89) and F‐score (0.81). The optimized secondary model showed the highest accuracy (0.91) and F‐scores (0.86) in the test dataset and outperformed the magnetic resonance parkinsonism index (0.81 and 0.70, respectively).InterpretationThe results suggest that glucose hypometabolism in the thalamus and cerebellar dentate have the highest potential for predicting PSP pathology. Our optimized machine learning model outperformed the best currently available biomarker to predict PSP pathology. ANN NEUROL 2025;98:410–420

Abstract Background Classic progressive supranuclear palsy RS syndrome (PSP‐RS) is characterized by early postural instability/falls and vertical supranuclear gaze palsy, although other signs/symptoms can occur, for example, axial rigidity, bradykinesia, and cognitive dysfunction. The Movement Disorders Society‐PSP (MDS‐PSP) criteria consider probable PSP‐RS a homogenous syndrome, but this has not been tested. Objectives We aim to investigate relationships between signs/symptoms of PSP‐RS beyond its core features and determine whether PSP‐RS is a homogeneous syndrome. Methods 118 participants who met MDS‐PSP criteria for probable PSP‐RS were analyzed. All participants received an independent clinical diagnosis based on clinical judgment. We first performed a Network Analysis using qgraph with Spearman's correlation to quantify relationships between 16 signs/symptoms followed by a k‐means clustering analysis using the same signs/symptoms to identify possible heterogeneity of the PSP‐RS designation. Results Five network clusters were identified, reflecting: (1) tremor, (2) sensitivity to bright light, (3) oculomotor function, (4) cognition, and (5) akinetic‐rigidity‐praxis. Worse akinetic‐rigidity was associated with better oculomotor function, but worse cognition. Cluster analysis revealed two clusters. Cluster I ( n = 89) had more severe clinical features than Cluster II ( n = 29). Cluster II had a higher frequency of participants (37.9%) clinically judged as not PSP‐RS: these participants were less likely to have PSP pathology on autopsy ( P = 0.03). Conclusions Some signs/symptoms of PSP‐RS strongly associate and are more likely to co‐occur. PSP‐RS, as defined by the MDS‐PSP criteria includes a subset of participants not clinically judged as PSP‐RS who are less likely to have PSP pathology.

ABSTRACTIndividuals with primary progressive apraxia of speech (PPAOS) often develop parkinsonism and dysphagia. To evaluate the clinical correlates and impact of dysphagia in this population, we compared enrollment visit data between individuals with (n = 12) versus individuals without (n = 44) dysphagia symptoms. The group with dysphagia had more motor speech symptoms and parkinsonism. Longitudinal analysis revealed that almost everyone developed dysphagia before dying; the average time to death after developing dysphagia was 5.43 years and complications of dysphagia resulted in mortality for 35% of the individuals for whom data were available. These results emphasize the need for dysphagia management and provide useful prognostic estimates.

Background Studies suggest that plasma Alzheimer's disease (AD) biomarkers may aid in the overall diagnosis of AD, but their utility among patients with atypical clinical presentations of AD are unknown. Objective The main objective of this study was to determine the relationship between amyloid-β (Aβ) and tau plasma biomarkers and PET measures of both Aβ and tau in atypical AD. The secondary objective was to determine if plasma biomarkers could differentiate patients with different atypical AD phenotypes and whether they were related to measures of disease severity. Methods We assessed whether plasma p-tau 181 and Aβ 42/40 were associated with Aβ and tau PET uptake, clinical phenotype and severity in 77 patients with PET biomarker-confirmed atypical AD. Results Plasma Aβ 42/40 ratio showed positive associations with tau PET uptake, with higher (more normal) Aβ 42/40 ratio associated with higher tau uptake; the ratio was not associated with Aβ PET. No associations were noted with plasma p-tau 181. Plasma Aβ 42/40 ratio and p-tau 181 concentrations were not associated with AD phenotype or cognitive severity. Conclusion Plasma Aβ 42/40 ratio and p-tau 181 concentrations are not associated with amyloid or tau PET or with clinical severity among individuals presenting with atypical AD.