Citations

Abstract INTRODUCTION Primary age‐related tauopathy (PART) is defined by neurofibrillary tangles (NFTs) with absent‐minimal amyloid beta (Aβ) plaques. Currently, definitive diagnosis of PART occurs with autopsy. This study investigated whether [ 18 F]fluorodeoxyglucose positron emission tomography (FDG‐PET) could detect PART‐related metabolic changes and assessed the impact of common co‐pathologies. METHODS We performed a retrospective cross‐sectional study of 88 individuals (mean age 85.6) with autopsy‐confirmed PART (Braak I to IV; Thal phases 0 to 2) who underwent ante mortem FDG‐PET. Visual ratings and standardized uptake value ratios (SUVRs) were analyzed in medial and lateral temporal lobes, inferior temporal pole, precuneus, and posterior cingulate regions. RESULTS Medial temporal hypometabolism was observed in PART, in the presence of co‐pathologies. Argyrophilic grain disease and TAR DNA‐binding protein 43 were associated with greater hypometabolism ( p < 0.01). Lewy body disease affected parietal regions. DISCUSSION FDG‐PET reveals that PART‐related hypometabolism occurs when co‐pathologies are present, but PART alone appears to have minimal effect on medial temporal lobe hypometabolism. Highlights FDG‐PET hypometabolism worsens with Braak NFT stage. FDG‐PET detects mild lateral temporal lobe hypometabolism in PART alone. PART alone has a minimal effect on medial temporal lobe hypometabolism. Medial temporal hypometabolism is worse in PART with TDP‐43 and especially AGD. The presence of LBD contributes to parietal hypometabolism on FGD‐PET in PART.

Abstract Objective: We investigated differences in cognition between variants of progressive supranuclear palsy (PSP) including PSP-Richardson (PSP-RS) and subcortical and cortical variants using updated diagnostic criteria and comprehensive neuropsychological assessment. Method: We recruited 140 participants with PSP (age = 71.3 ± 6.9 years; education = 15.0 ± 2.8 years; 49.3% female) who completed neurological and neuropsychological assessment. Participants received diagnoses of PSP clinical variants at their evaluation (or retrospectively if evaluated before 2017) according to the Movement Disorder Society PSP criteria. We grouped variants as PSP-RS (62 participants), PSP-Cortical (25 with PSP-speech/language and 9 with PSP-corticobasal syndrome), and PSP-Subcortical (27 with PSP-parkinsonism, 11 with PSP-progressive gait freezing, and 6 with PSP-postural instability). Analysis of covariance adjusted for age assessed for differences in neuropsychological performance between variants across cognitive domains. Results: PSP-Cortical participants performed worst on measures of visual attention/working memory (Spatial Span Forward/Backward/Total), executive function (Frontal Assessment Battery), and language (Letter Fluency). PSP-RS participants performed worst on verbal memory (Camden Words). There were no significant group differences for the MoCA or indices of visuospatial function. There were no sex or education differences between PSP groups; however, there were differences in age at visit and disease duration. Conclusions: In a large sample of participants with PSP, there were differences in cognition across PSP-RS, PSP-Subcortical, and PSP-Cortical variants, with PSP-Cortical and, to a lesser extent, PSP-RS, performing worse on tests of attention and executive function. These findings suggest cognitive distinctions among PSP clinical variants and highlight the value of neuropsychological assessment in differential diagnosis of PSP subtypes for more accurate and timely clinical classification.

Abstract The link between regional tau load and clinical manifestation of Alzheimer’s disease (AD) highlights the importance of characterizing spatial tau distribution across disease variants. In typical (memory-predominant) AD, the spatial progression of tau pathology mirrors the functional connections from temporal lobe epicentres. However, given the limited spatial heterogeneity of tau in typical AD, atypical (non-amnestic-predominant) AD variants with distinct tau patterns provide a key opportunity to investigate the universality of connectivity as a scaffold for tau progression. In this large-scale, multicentre study across 14 international sites, we included cross-sectional tau-PET data from 320 individuals with atypical AD (n = 139 posterior cortical atrophy/PCA-AD; n = 103 logopenic variant primary progressive aphasia/lvPPA-AD; n = 35 behavioural variant AD/bvAD; n = 43 corticobasal syndrome/CBS-AD), with a subset of individuals (n = 78) having longitudinal tau-PET data. Additionally, as an independent sample, we included regional post-mortem tau stainings from 93 atypical AD patients from two sites (n = 19 PCA-AD, n = 32 lvPPA-AD, n = 23 bvAD, n = 19 CBS-AD). Gaussian mixture modelling was used to harmonize different tau-PET tracers by transforming tau-PET standardized uptake value ratios to tau positivity probabilities (a uniform scale ranging from 0% to 100%). Using linear regression, we assessed whether brain regions with stronger resting-state functional MRI-based functional connectivity, derived from healthy elderly controls in the Alzheimer’s Disease Neuroimaging Initiative (ADNI), showed greater covariance in cross-sectional and longitudinal tau-PET and post-mortem tau pathology. Furthermore, we examined whether functional connectivity of tau-PET epicentres (i.e. the top 5% of regions with the highest baseline tau load) and tau-PET accumulation epicentres (i.e. the top 5% of regions with the highest tau accumulation rates) was associated with cross-sectional and longitudinal tau patterns. Our findings show that tau-PET epicentres aligned with clinical variants, e.g. a visual network predominant pattern in PCA-AD (‘visual AD’) and left-hemispheric temporal predominance, particularly within the language network, in lvPPA-AD (‘language AD’). Moreover, more strongly functionally connected regions showed correlated concurrent tau-PET levels (confirmed with post-mortem data) and tau-PET accumulation rates. The functional connectivity profile of tau-PET epicentres and accumulation epicentres corresponded to tau-PET progression patterns, with higher tau-PET levels and accumulation rates in functionally close regions, and lower tau-PET levels and accumulation rates in functionally distant regions. Our data are consistent with the hypothesis that tau propagation occurs along functional connections originating from local epicentres, across all AD clinical variants. Since tau proteinopathy is a major driver of neurodegeneration and cognitive decline, this finding may advance personalized medicine and participant-specific end points in clinical trials.

Transactive response DNA-binding protein of 43 kDa (TDP-43) and tau proteins play critical roles in neurodegenerative diseases, particularly frontotemporal lobar degeneration (FTLD) and Alzheimer’s disease (AD). The co-occurrence of TDP-43 and tau pathologies raises questions about their role in disease progression. This review explores the simultaneous presence of tau and TDP-43 co-pathologies, emphasizing their molecular interactions and the resultant neuropathological implications. Additionally, we provide representative examples of their clinical presentations, neuroimaging, and neuropathological findings associated with FTLD-TDP and FTLD-tau, emphasizing the need for a comprehensive understanding of these intertwined pathologies. We analyze various clinical scenarios, including argyrophilic grain disease (AGD), primary age-related tauopathy (PART), and limbic predominant age-related TDP-43 encephalopathy (LATE), to elucidate the complex relationship between these proteinopathies. From the literature, the co-occurrence of tau and TDP-43 is linked to more severe and poorer clinical outcomes compared to isolated pathologies. This review underscores the necessity of considering co-pathologies in the context of FTLD, as they may act as accelerators of cognitive decline. This highlights the importance of integrated approaches in diagnosing and treating neurodegenerative conditions characterized by tau and TDP-43 misfolding. Understanding the interplay between these molecular markers is vital for advancing therapeutic strategies for such disorders.

Background: Progressive apraxia of speech (PAOS) is a neurodegenerative disorder most commonly arising from a 4-repeat tauopathy that affects the programming or planning of speech, although many patients develop a Parkinson-plus syndrome. The role of neuroinflammation as a disease mechanism is unknown. We investigated the spatial pattern of neuroinflammation in PAOS using PET and evaluated whether it is associated with disease severity, presence of Parkinson-plus features, and tau PET uptake. Patients and Methods: Twenty-five PAOS patients (13 with Parkinson-plus features) and 30 controls underwent inflammatory 11C-ER176 and tau 18F-flortaucipir PET scans as well as detailed clinical assessments. Multiple linear regression analyses compared the inflammatory standardized uptake value ratio (SUVR) between PAOS and controls and assessed the relationship with clinical test scores. Pearson correlation analysis examined the relationship between inflammatory and tau SUVRs. Results: PAOS had greater neuroinflammatory SUVR than controls in the precentral, supplementary motor area, frontal gyri, putamen, pallidum, subthalamic nucleus, and red nucleus (adjusted P < 0.05). Greater neuroinflammation was associated with worse parkinsonism, and patients who had developed Parkinson-plus features showed a broader pattern of neuroinflammation, extending to prefrontal, temporal and parietal cortices. Neuroinflammation correlated with tau uptake in most (96%) PAOS patients (r > 0.3, P < 0.05). The higher correlation was associated with worse parkinsonism (r = 0.61, P < 0.05) and disease severity (r = 0.54, P < 0.05). Conclusions: 11C-ER176 PET analysis demonstrates neuroinflammation in frontal and subcortical regions in PAOS which is particularly severe and widespread with the development of Parkinson-plus clinical features. The colocalization of neuroinflammation and tau may support a relationship between these disease mechanisms.

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