Josephs, Keith A.

ABSTRACT Background and Purpose Diffusion tensor imaging (DTI) is commonly used to assess the integrity of gray and white matter (WM) structures in progressive supranuclear palsy (PSP). Beyond DTI, nontraditional diffusion techniques such as diffusion kurtosis imaging (DKI) have been shown to characterize brain tissue further. In this work, we aim to determine the utility of DKI in the differential diagnosis of PSP—Richardson syndrome (PSP‐RS) and PSP with predominant parkinsonism (PSP‐P) from Parkinson's disease (PD) and controls. Methods A multishell diffusion‐weighted sequence was acquired at 3 Tesla on a Siemens system in 22 patients with PSP‐RS, 23 with PSP‐P, 19 with PD, and 19 controls. Fractional anisotropy, mean diffusivity, kurtosis fractional anisotropy (KFA), and mean kurtosis (Kmean) were calculated for nine deep gray matter regions and six different WM tracts. Results DKI identified differences (not found by DTI) between control and PSP groups in the globus pallidum externus, subthalamic region, and putamen, with Kmean in the putamen able to differentiate PSP‐RS and PD. DKI WM measurements in the body of the corpus callosum and dentatorubrothalamic tract differentiated PSP‐RS from PD, and the corticostriatal tract differentiated PSP‐P from PD. KFA in the body of the corpus callosum identified worse microstructural anomalies in PSP‐RS compared to PSP‐P. DKI metrics correlated with the severity of ocular motor impairment and parkinsonism scores. Conclusions DKI measurements could differentiate PSP‐RS, PSP‐P, and PD and, hence, may be a promising imaging tool for studying structural neuropathological changes in PSP.

ObjectivesThe four‐repeat (4R) tauopathies are a group of neurodegenerative diseases, including progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), and globular glial tauopathy (GGT). This study aimed to characterize spatiotemporal atrophy progression using structural magnetic resonance imaging (MRI) and to examine its relationship with clinical course and neuropathology in a cohort of autopsy‐confirmed 4R tauopathies.MethodsThe study included 85 autopsied patients (54 with PSP, 28 with CBD, and 3 with GGT) who underwent multiple 3T MRI scans, as well as neuropsychological, neurological, and speech/language examinations, and standardized postmortem neuropathological evaluations. An unsupervised machine‐learning algorithm, Subtype and Stage Inference (SuStaIn), was applied to the cross‐sectional brain volumes to estimate spatiotemporal atrophy patterns and data‐driven subtypes and stages in each patient. The relationships among estimated subtypes, pathological diagnoses, and longitudinal changes in clinical testing were examined.ResultsThe SuStaIn algorithm identified 2 distinct subtypes: (1) the subcortical subtype, in which atrophy progresses from the midbrain to the cortex, and (2) the cortical subtype, in which atrophy progresses from the frontal cortex to the subcortical regions. The subcortical subtype was more associated with typical PSP, whereas the cortical subtype was more associated with atypical PSP with a cortical distribution of pathology and CBD (p < 0.001). The cortical subtype had a faster rate of change on the PSP Rating Scale than the subcortical subtype (p < 0.05).InterpretationSuStaIn analysis revealed 2 MRI‐driven subtypes with distinct spatiotemporal atrophy patterns, clinical courses, and neuropathology. Our findings contribute to a comprehensive and improved understanding of disease progression and its relationship to tau pathology in 4R tauopathies. ANN NEUROL 2025;98:492–507

Abstract Normal pressure hydrocephalus is typically defined by the triad of gait disturbance, cognitive impairment, and urinary incontinence, and is characterized on MRI by disproportionately enlarged subarachnoid-space. Gait disturbance is also a commonly reported symptom in Parkinsonian disorders, especially progressive supranuclear palsy, although the frequency, clinical significance and mechanisms of hydrocephalus in these disorders are unclear. We aimed to assess the prevalence of hydrocephalic MRI parameters in a large cohort of Parkinsonian disorders and evaluate associations with clinical features and abnormalities on MRI and PET. Two hundred and thirty-eight participants with a Parkinsonian disorder, including 181 progressive supranuclear palsy, 36 corticobasal syndrome and 21 Parkinson’s disease, were enrolled from Mayo Clinic by the Neurodegenerative Research Group between September 2009 to October 2023. Automated detection of disproportionately enlarged subarachnoid-space hydrocephalus (D) was applied and using Evans’ index (E) cut-off point &gt;0.3, participants were classified based on both measures as imaging-suggestive of hydrocephalus (D+E+), enlarged subarachnoid-space only (D+E−), large Evans’ index only (D−E+) and no imaging evidence of hydrocephalus (D−E−). Demographic, clinical and imaging features, including magnetic resonance parkinsonism index, cortical and subcortical volumes, white matter hyperintensities, diffusion tractography metrics, and metabolism on PET, were compared across groups. Among the 238 participants, 24 had borderline subarachnoid space scores and were excluded. The remaining 214 participants were classified as: D+E+ (n = 20, 9%); D+E− (n = 8, 4%); D−E+ (n = 71, 33%) and D−E− (n = 115, 54%). Among the progressive supranuclear palsy participants, 11% were D+E+, 4% D+E−, 34% D−E+ and 51% D−E−. Most cases (n = 18) in the imaging-suggestive of hydrocephalus D+E+ group had progressive supranuclear palsy. The D+E+ participants were older, had more disorientation, more downgaze palsy, greater midbrain and cortical atrophy, lower striatal metabolism, greater degeneration of long-range white matter tracts, larger cistern areas and more periventricular and deep white matter hyperintensities compared to the D−E− participants without imaging evidence of hydrocephalus. The D+E− participants had the highest metabolism in the paracentral lobule and superior parietal gyrus. The D−E+ participants showed worse disease severity and greater midbrain and cortical atrophy compared to the D−E− participants. These findings demonstrate that disproportionately enlarged subarachnoid-space hydrocephalus occurs in ∼15% of progressive supranuclear palsy participants, and is associated with worse clinical and imaging outcomes, as well as white matter hyperintensities. We hypothesize that disproportionately enlarged subarachnoid-space may be a mechanistic byproduct of degeneration and subsequent cerebrospinal fluid flow re-distribution in progressive supranuclear palsy.

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.

Pick’s disease (PiD) is a rare neurodegenerative disorder defined by dementia, frontotemporal lobe atrophy, and 3-repeat tau inclusions. To elucidate PiD pathobiology, we performed the first bulk transcriptomics study on PiD using short- and long-read sequencing on the parietal cortex of 28 PiD and 15 control samples. We identified several significantly differentially expressed genes, with CCL2 displaying the strongest association with 3-repeat tau pathology and increased burden in PiD compared to those in 4-repeat tau progressive supranuclear palsy (PSP) cases. Investigation of co-expressed genes and pathways suggested the involvement of mRNA processing, mitochondrial function, and immune processes in disease pathobiology. Long-read RNA sequencing on a subset of samples (eight PiD and four control) proposed novel, potentially disease-associated transcripts for AZGP1 , CD44 , HSD11B2 , and WIF1 , predicted to result in truncated proteins. In conclusion, we observed transcriptomic changes in the parietal cortex of patients with PiD that may inform into clinically relevant biomarkers and therapeutic strategies.

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.