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ABSTRACT Alzheimer's disease (AD) is the leading cause of dementia in the elderly, marked by abnormal protein buildup (beta‐amyloid and tau) resulting in neuronal loss, especially in the medial temporal lobe and other limbic regions. The presence of transactive response DNA binding protein 43 (TDP‐43) immunoreactive inclusions in medial temporal lobe regions has also been associated with neuroimaging changes in limbic regions. It has been proposed that hypometabolism in limbic regions on [ 18 F] fluorodeoxyglucose positron emission tomography (FDG‐PET) in a patient with a slowly evolving amnestic syndrome may be a signature of the presence of TDP‐43. In this context, we observed an 86‐year‐old Caucasian female with dementia characterized by a slowly evolving amnestic syndrome, along with focal medial temporal atrophy evident on MRI and hypometabolism in limbic regions on FDG‐PET. The patient subsequently died and underwent an autopsy. We performed detailed neuroimaging and digital neuropathological analyses of the hippocampal subfields to better understand the relationship between clinico‐imaging findings and histopathology. In addition to TDP‐43, we identified three other pathological processes in the medial temporal lobe: sequestosome‐1/p62, argyrophilic grain disease (AGD), and primary age‐related tauopathy (PART). Hippocampal subfield volumes and rates of atrophy were no different from those of matched healthy controls, except for the atrophy rate in cornu ammonis 1 (CA1). Digital histopathology revealed the relative highest burden of pathology for p62, followed by TDP‐43, AGD, and PART in CA1. Multiple pathological processes appear to have contributed to the hippocampal atrophy and hypometabolism in our patient with a slowly progressive amnestic syndrome.

Background and Objectives: Hearing loss is relatively common in older individuals, and individuals with frontotemporal lobar degeneration (FTLD) are no exception; this can exacerbate communication difficulties stemming from speech-language impairments. The co-occurrence of these symptoms can contribute to increased frustration and isolation for patients and their communication partners. The objective of this study was to evaluate the feasibility of self-administered hearing testing. Ultimately, this could be administered remotely, which would increase access to assessment and inform management for this population. Method: Seventeen patients with underlying FTLD, clinically presenting with progressive apraxia of speech with and without agrammatic aphasia, independently completed the Home Hearing Test supervised while in office. Results: Three patients self-reported hearing loss, but results for 100% recommended formal evaluation. Eleven patients demonstrated good test accuracy. Six patients had “poor” or not computable accuracy; among them, five had evidence of cognitive impairment and/or behavioral changes, and one had known severe hearing loss, although differences between those with good and poor test accuracy were not significant. Patients with poor test accuracy had more difficulty with limb praxis. Conclusions: Most participants independently completed the test, though some had reduced test accuracy that may have been associated with cognitive impairment and/or limb apraxia. This study supports the need for hearing screenings in all patients with progressive apraxia of speech and aphasia and highlights both the feasibility and caution required in implementing self-administered testing protocols. Further work should evaluate the feasibility of in-home hearing screenings in a broader range of FTLD phenotypes and directly compare sensitivity and specificity of hearing loss detection with in-clinic administration. Supplemental Material: https://doi.org/10.23641/asha.28306613

Abstract INTRODUCTION Greater white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) are seen with transactive response DNA‐binding protein 43 (TDP‐43) pathology in frontotemporal lobar degeneration (FTLD‐TDP). WMH associations with TDP‐43 pathology in Alzheimer's disease (AD‐TDP) remain unclear. METHODS A total of 157 participants from Mayo Clinic Rochester with autopsy‐confirmed AD, known TDP‐43 status, and antemortem fluid‐attenuated inversion recovery (FLAIR) MRI were included. Vascular risk factors were assessed. A semi‐automated WMH segmentation‐quantification process produced total and regional WMH volumes. Penalized linear regression models adjusting for age at MRI analyzed TDP‐43 associations (status and typing) with WMHs. RESULTS TDP‐43‐positive status was not associated with WMH burden overall because opposite effects were seen based on AD‐TDP typing. Despite similar antemortem vascular risk factors and postmortem vascular pathologies, AD‐TDP type‐ α showed greater total and regional WMH burden (particularly in subcortical frontotemporal and basal ganglia regions) than TDP‐43 negatives and AD‐TDP type‐ β . DISCUSSION AD‐TDP types may have different WMH pathomechanisms, with type‐ α having associations more like FTLD‐TDP than AD. Highlights In transactive response DNA‐binding protein 43 (TDP‐43) pathology in Alzheimer's disease (AD‐TDP), TDP‐43 status alone is not associated with total or regional WMH burden AD‐TDP type‐ α shows greater total, frontotemporal subcortical, and basal ganglia white matter hyperintensities (WMHs) AD‐TDP type‐ β shows less total and subcortical occipital WMHs AD‐TDP type‐ α effect on WMH burden closely mimics the effects of frontotemporal lobar degeneration with TDP‐43 (FTLD‐TDP) rather than AD Different relationships of AD‐TDP types with WMHs suggest different pathomechanisms

Abstract Background Perry syndrome (PS) is a rare and fatal hereditary autosomal dominant neurodegenerative disorder caused by mutations in dynactin ( DCTN1 ). PS brains accumulate inclusions positive for ubiquitin, transactive‐response DNA‐binding protein of 43 kDa (TDP‐43), and to a lesser extent dynactin. Objectives Little is known regarding the contributions of TDP‐43, an RNA binding protein that represses cryptic exon inclusion, in PS. Therefore, we sought to identify the degree of TDP‐43 dysfunction in two regions of PS brains. Methods We evaluated the levels of insoluble pTDP‐43 and TDP‐43‐regulated cryptic RNAs and protein in the caudate nucleus and substantia nigra of 7 PS cases, 12 cases of frontotemporal lobar degeneration (FTLD) with TDP‐43 pathology, and 11 cognitively healthy controls without TDP‐43 pathology. Results Insoluble pTDP‐43 protein levels were detected in PS brains to a similar extent in the caudate nucleus and substantia nigra but lower than those in FTLD brains. The caudate nucleus of PS showed accumulation of eight TDP‐43‐regulated cryptic RNAs ( ACTL6B , CAMK2B , STMN2 , UNC13A , KCNQ2 , ATG4B , GPSM2 , and HDGFL2 ) and cryptic protein (HDGFL2) characteristic of FTLD. Conversely, only one cryptic target, UNC13A , reached significance in the substantia nigra despite similar pTDP‐43 levels. Conclusion We detected TDP‐43 cryptic RNAs and protein in PS caudate nucleus. Given the importance of cryptic exon biology in the development of biomarkers, and the identification of novel targets for therapeutic intervention, it is imperative we understand the consequences of TDP‐43 dysfunction across different brain regions and determine the targets that are specific and common to TDP‐43 proteinopathies. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

AbstractBackgroundThere is a strong link between tau and progression of Alzheimer’s disease (AD), necessitating an understanding of tau spreading mechanisms. Prior research, predominantly in typical AD, suggested that tau propagates from epicenters (regions with earliest tau) to functionally connected regions. However, given the constrained spatial heterogeneity of tau in typical AD, validating this connectivity‐based tau spreading model in AD variants with distinct tau deposition patterns is crucial.MethodWe included 269 amyloid‐β‐positive (PET/CSF) individuals with clinically diagnosed atypical AD (113 posterior cortical atrophy, PCA‐AD; 83 logopenic variant primary progressive aphasia, lvPPA‐AD; 33 behavioural variant AD, bvAD; 40 corticobasal syndrome, CBS‐AD) and 68 with typical AD from 12 international cohorts, who underwent tau‐PET (54% [18F]AV1451/[18F]flortaucipir/Tauvid, 27% [18F]MK6240, 19% [18F]PI2620). Using Gaussian mixture modeling including amyloid‐β‐negative controls, cross‐sectional tau‐PET standardized uptake value ratios within Schaefer‐200 atlas regions were transformed to tau positivity probabilities. Tau epicenters were defined as the 5% regions with highest tau positivity probabilities. For each variant, the association between functional connectivity‐based distance (using the 30% strongest positive region‐to‐region connections of a group‐average connectivity matrix from ADNI elderly controls) and tau‐PET covariance (group‐average correlation per region pair) was assessed through linear regression, adjusting for age, sex, site, and Euclidean distance. Regions were categorized based on functional proximity to the epicenter (quartiles 1‐4) and tau positivity probabilities were assessed accordingly.ResultTau positivity probabilities matched clinical variants, with a posterior pattern in PCA‐AD, left‐hemispheric dominant pattern in lvPPA‐AD, widespread pattern in bvAD, sensorimotor cortex involvement in CBS‐AD, and temporo‐parietal predominance in typical AD (Figure 1). In line with this, tau epicenters were highly heterogeneous across variants (Figure 1). In all variants, greater tau‐PET covariance was associated with shorter functional connectivity‐based distance (Figure 2). We observed that regions in closer functional proximity to the epicenter exhibited higher tau positivity probabilities than regions functionally further away (p<0.05, Figure 3).ConclusionThis multi‐center study shows that the brain’s functional architecture serves as a universal predictor of tau spreading in AD. Since tau is a key driver of neurodegeneration and cognitive decline in AD, this finding holds potential for personalized medicine and defining participant‐specific endpoints in clinical trials.

AbstractBackgroundThe TAR DNA‐binding protein of 43 kDa (TDP‐43) is linked to hippocampal volume loss and faster rates of hippocampal atrophy in Alzheimer's disease and primary age‐related tauopathy (PART). Hence, TDP‐43 is becoming an important player in age‐related neurodegeneration. To advance our understanding of TDP‐43 effect on hippocampus, we conducted an imaging‐pathological study to determine which specific hippocampal subfields are affected by TDP‐43 in cases of PART.MethodOne‐hundred fifteen autopsied cases from Mayo Clinic Alzheimer Disease Center, Study of Aging and Neurodegenerative Research Group were analyzed. All had completed antemortem brain MRIs, underwent neuropathological examination per NIA and Alzheimer’s Association (NIA‐AA) criteria and had additional assessment for TDP‐43 deposition. Only cases meeting criteria for PART (Thal phases 0‐2 and Braak NFT stages I‐IV) were included. Hippocampal subfield segmentation was performed using FreeSurfer‐7. Brain volumes were normalized to total intracranial volume (TIV) when comparing TDP‐43 groups. Statistical analyses including logistic regression analyses were utilized to explore associations between TDP‐43 status and hippocampal subfield volumes.ResultForty‐nine of the 115 cases (43%) with PART were female. Thirty‐seven (32%) cases were TDP‐positive. Mean age at last MRI was 84 years. There were no differences in pathological characteristics between both groups except for presence of hippocampal sclerosis which was more frequent in the TDP(+) group (P <0.001). Whole hippocampal volume was significantly smaller in the TDP(+) group (176 ±31 vs. 188 ±27, p=0.049). After stratification of hippocampus into head, body, and tail, TDP‐positive cases had smaller volumes of hippocampal body (p=0.031) and tail (p=0.021) but did not reach significance for hippocampal head (p=0.129). When regions were subdivided into hippocampal subfields, TDP(+) cases showed smaller volumes of molecular layer of the hippocampal body (p=0.046), CA1 body (p=0.031), subiculum body (p=0.023), and presubiculum body (p=0.046) compared to TDP(‐) cases. Logistic regression analysis adjusting for TIV confirmed these associations.ConclusionThis study underscores the association between TDP‐43 and the hippocampus and provides further evidence that TDP‐43 targets multiple regions and subfields of the hippocampus in patients with PART. Intriguingly, regions targeted are those where TDP‐43 deposition is microscopically observed, suggesting a direct “hit” by TDP‐43 deposition.

AbstractBackgroundProgressive supranuclear palsy (PSP) can present with different clinical variants which show distinct, but partially overlapping, patterns of neurodegeneration and tau deposition in a PSP network of regions, including cerebellar dentate, superior cerebellar peduncle, midbrain, thalamus, basal ganglia, and frontal lobe. We sought to determine whether disruptions in functional connectivity within this PSP network measured using resting‐state functional MRI (rs‐fMRI) differed between PSP‐Richardson’s syndrome and the cortical and subcortical variants of PSP.MethodStructural MRI and rs‐fMRI scans were collected for 40 PSP‐RS, 24 PSP‐cortical (12 speech and language; 10 corticobasal syndrome; 2 frontal) and 36 PSP‐subcortical (18 parkinsonism; 11 progressive gait freezing; 6 postural instability; 1 oculomotor) participants who met the Movement Disorder Society PSP clinical criteria (Table 1). Ninety‐six participants underwent flortaucipir‐PET scans. MRIs were processed using CONN Toolbox. Functional connectivity between seeds placed throughout the PSP network was compared between each PSP group and 83 healthy controls, and between the PSP groups, covarying for age and sex.ResultsConnectivity was reduced throughout the network in PSP‐RS compared to controls (Figure 1A), involving cerebellar dentate, midbrain nuclei, subthalamic nuclei, basal ganglia, thalamus, and frontal regions. Frontal regions showed reduced connectivity to other regions in the network in PSP‐cortical, including substantia nigra and superior cerebellar peduncle. Disruptions in connectivity in PSP‐subcortical were less pronounced, with the strongest disruption between the pallidum and putamen. When PSP groups were compared to each other (Figure 1B), PSP‐RS had lower connectivity from the thalamus and cerebellar dentate to the cortex compared to PSP‐subcortical and from the thalamus to substantia nigra than PSP‐cortical. PSP‐subcortical had lower connectivity from the subthalamic nucleus to caudate than PSP‐RS and from the subthalamic nucleus to substantia nigra than PSP‐cortical and higher connectivity from the thalamus to the prefrontal cortex than both the other variants. Voxel‐based analyses replicated these patterns. There was moderate evidence that tau uptake in the PSP network regions influenced connectivity between these regions in PSP.ConclusionsPatterns of disrupted functional connectivity revealed both variant‐specific and shared disease pathways among PSP variants, providing insight into the disease heterogeneity beyond patterns of atrophy.

AbstractBackgroundCorticobasal syndrome (CBS) is a progressive neurodegenerative syndrome that can result from several underlying neuropathologies, including Alzheimer’s disease (AD). Little is known about the utility of blood plasma measures to predict PET biomarker confirmed AD in CBS.MethodEighteen CBS patients (8 PET Aβ+; 10 PET Aβ‐) and 8 cognitively unimpaired Aβ‐ individuals (CU) were recruited by the Neurodegenerative Research group from the Department of Neurology, Mayo Clinic, Rochester, MN, underwent Aβ (Pittsburgh Compound‐B) and tau (18F‐flortaucipir) PET and provided a blood sample. Blood plasma analysis was performed to assess p‐tau 181, total tau, Aβ 42/40, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) using the Quanterix Simoa platform. Plasma concentrations were compared between Aβ‐, and Aβ+ CBS and controls using Kruskal‐Wallis corrected for multiple comparisons using Dunn’s test, with effect size measured with area under the receiver operating characteristic curve (AUROC) analysis. Spearman correlations were calculated to assess relationships between plasma concentrations and Aβ and tau PET uptake.ResultThe CBS Aβ+ group showed reduced Aβ42/40 ratio, with elevated p‐tau 181, GFAP and NfL plasma concentrations compared to CU, while the CBS Aβ‐ group only showed elevated NfL concentration compared to CU (Figure 1). Both p‐tau 181 (AUROC=0.95) and GFAP (AUROC=0.91) plasma concentrations were able to differentiate CBS Aβ‐ from CBS Aβ+. Plasma p‐tau 181 and GFAP concentrations showed a positive correlation to both Aβ and tau PET uptake, and the Aβ42/40 ratio showed a negative correlation to Aβ PET uptake (Figure 2). No correlations were observed between NfL and Aβ and tau PET.ConclusionThis study supports the use of plasma p‐tau 181 and GFAP to detect AD in CBS, while NfL shows potential as a nonspecific disease biomarker of CBS regardless of underlying pathology. Plasma concentrations of these biomarkers may potentially be incorporated into clinical trials targeting CBS patients with underlying AD pathology.

AbstractBackgroundBlood plasma metrics provide excellent biomarkers of the presence of Alzheimer’s disease (AD) pathology in population cohorts. However, it is less clear whether plasma metrics correlate with PET measures of AD pathology in cohorts of patients with advanced AD disease, particularly in those with atypical clinical presentations of AD.MethodSeventy‐seven patients (visual variant=43, language variant=32, motor variant=1 and dysexecutive variant=1) with PET biomarker‐confirmed atypical AD were recruited by the Neurodegenerative Research group at Mayo Clinic, Rochester, MN, underwent Aβ (Pittsburgh Compound‐B) and tau (18F‐flortaucipir) PET and provided a blood sample. Blood plasma analysis was performed to assess p‐tau 181 and Aβ42/40 ratio concentrations using the Quanterix Simoa platform. Multivariate linear regression models assessed the relationship between plasma concentrations and both global Aβ, atypical AD summary and regional tau PET measures. For each PET measure, two separate models were fit to assess the influence of each plasma biomarker separately, while the third model included all plasma measures to assess the combined influence of all biomarkers on PET uptake. To investigate differences in plasma concentrations between atypical AD phenotypes, we performed Mann‐Whitney’s test across the visual and language variants of AD.ResultPlasma Aβ42/40 ratio showed positive associations with tau PET uptake, specifically within precuneus, parietal and temporal regions and was not associated with Aβ PET. There was no relationship between plasma p‐tau 181 and Aβ or tau PET uptake. However, the model that included both plasma biomarkers showed that with the addition of p‐tau 181, all significant associations between Aβ42/40 ratio and regional tau uptake were weakened to trends. The Aβ42/40 ratio continued to show no relationship with global Aβ‐PET uptake and plasma p‐tau 181 showed no relationship to PET measures (Figure 1). Lastly, no significant difference in plasma Aβ42/40 and p‐tau 181 levels was noted between the visual and language variants of AD (Figure 2).ConclusionThe lack of associations between plasma concentrations and PET measures of Aβ and tau in this relatively advanced AD cohort may suggest that plasma concentrations have greater utility as diagnostic biomarkers of early AD as compared to advanced AD.