Whitwell, Jennifer L.

Abstract Background Atypical clinical presentations of Alzheimer's disease (AD) are associated with heterogeneous patterns of cortical tau‐PET uptake. The medial‐temporal (MTL) meta‐ROI is typically used to determine tau‐PET abnormality in AD, but this approach may not detect focal uptake in atypical patients. Our goal was to develop regional tau‐PET cut‐points and determine whether the number of positive regions better captures positive tau‐PET signal in atypical AD. Method 127 amyloid‐positive atypical AD (visual=68, language=39, motor=15, others=5) and 62 amyloid‐negative cognitively unimpaired (CU) individuals were recruited by the Neurodegenerative Research Group, Mayo Clinic, and underwent, amyloid‐PET and 18 F‐AV‐1451(tau)‐PET. Images were parcellated using the modified Harvard‐Oxford atlas and we focused on 67 AD‐specific regions. Rather than using the average SUVR across voxels within a region to quantify uptake, we used the 95 th percentile of SUVR values across voxels within a region to capture focal cases. We then used receiver operating characteristic (ROC) methods and a Youden threshold to define regional abnormality. The number of abnormal regions was calculated for each participant and used to discriminate between CU and atypical AD at the individual level. Result Across 64 regions, our approach showed excellent (AUROC>0.90) differentiation between atypical AD and CU. The temporal‐fusiform, parahippocampal gyrus and inferior temporal gyrus showed the best differentiation (Figure 1). All 67 regions showed excellent specificity (>85%), with 63 regions showing excellent sensitivity (≥80%). The lateral occipital cortex, temporal‐fusiform and parahippocampal gyrus showed the best specificity and sensitivity (Figure 2). The distribution of the number of tau‐elevated regions is shown in Figure 3. 74% of CU had no positive regions, while 43% of the atypical AD patients had all 67 regions affected. An optimal threshold of 7 tau‐elevated regions classified all CU below, and 123 (97%) atypical AD above threshold. Using a standard approach based on the average SUVR in the MTL meta‐ROI, only 116 (91%) atypical AD patients were tau‐PET positive. Conclusion Tau uptake in temporal regions showed the greatest group‐level differentiation. However, examining regional tau‐positivity may offer better sensitivity in atypical AD patients compared to the temporal meta‐ROI, likely due to the presence of focal non‐temporal patterns of uptake.

Abstract Background The link between regional tau load and clinical manifestation of Alzheimer's disease (AD) highlights the importance of characterizing spatial tau distribution. In typical (memory‐predominant) AD, the spatial progression of tau pathology mirrors the functional connections from temporal lobe epicenters. However, atypical (non‐amnestic‐predominant) AD variants with heterogeneous tau patterns provide a key opportunity to assess the universality of connectivity as a scaffold for tau progression. Method We included tau‐PET data from 320 subjects with atypical AD, characterized by highly heterogeneous tau patterns ( 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) from 14 sites, with a subset of patients ( n = 78) having longitudinal tau‐PET data. As an independent sample, we further 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 modeling 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 1) brain regions with stronger functional connectivity showed greater covariance in cross‐sectional and longitudinal tau‐PET and post‐mortem tau pathology, and 2) functional connectivity of tau‐PET epicenters and tau‐PET accumulation epicenters was associated with cross‐sectional and longitudinal tau patterns. Result Tau‐PET epicenters—defined as the 5% brain regions with the highest tau load—aligned with clinical variants, e.g. a posterior pattern in PCA‐AD (“visual AD”) and left‐hemispheric temporal predominance in lvPPA‐AD (“language AD”) (Figure 1). More strongly functionally connected regions showed correlated concurrent tau‐PET levels, which was confirmed with post‐mortem data (Figure 2). Moreover, the connectivity profile of tau‐PET epicenters and accumulation epicenters corresponded to tau‐PET progression patterns (Figure 3). Conclusion Our data are consistent with the hypothesis that tau propagation occurs along functional connections originating from local epicenters, across all AD clinical variants. Since tau proteinopathy is a key driver of neurodegeneration and cognitive decline, this finding may advance personalized medicine and participant‐specific endpoints in clinical trials.

Abstract Background Primary progressive apraxia of speech (PPAOS) is a frontotemporal lobar degeneration spectrum disorder characterized by progressive speech motor planning/programming decline. Patients often develop neurological symptoms, frequently evolving into progressive supranuclear palsy (PSP)/corticobasal syndrome (CBS) overlap syndromes. Requests for information about disease progression and causes of death are common amongst our clinical and research encounters; however, empiric evidence to guide these discussions is lacking. Understanding causes of death may enhance counseling and support targeted interventions to delay fatal outcomes. This study aimed to describe causes of death in PPAOS. Methods Data from 29 deceased PPAOS patients (16 males) seen in research studies (July 2010–May 2023) were reviewed. Causes of death were established from medical charts and family reports. Fifteen had prosodic and 12 had phonetic‐predominant PPAOS; two had no clear predominance. Median age at onset was 67.08 years, disease duration 9.78 years, and age at death 76.25 years. 28 patients were white and one was Asian Indian. Results Overall, fifteen (52%) patients died from overall deterioration (cachexia/dehydration), nine (31%) from aspiration pneumonia, and the remainder from falls (10%), asphyxiation (3%), or medical aid in dying (3%). There was no clear association with AOS subtype and cause of death. Conclusions Most deaths in PPAOS resulted from systemic failure or dysphagia‐related complications. Half of the patients died without a clear precipitating event, described by family members as “shutting down,” similar to other prior studies that have shown central nervous system deterioration associated with dementia as cause of death. Aspiration pneumonia caused 34% of deaths, highlighting the need for early swallowing management, including assessments, dietary adjustments, and caregiver education. Falls underscore the importance of addressing balance and motor impairments through proactive prevention strategies. Other factors, such as access to healthcare and medical and psychiatric comorbidities were not analyzed but may influence outcomes. Future research should validate these findings in larger, diverse cohorts and compare outcomes to motor‐onset presentations of PSP and CBS. A comprehensive, multidisciplinary approach addressing motor speech impairments, dysphagia, and fall risks is essential to improve care and potentially extend survival for patients with PPAOS.

Abstract Background Frontotemporal dementia (FTD) with right anterior temporal lobe (RATL) predominant atrophy is an emerging area of interest. Recent findings by the International Working Group (IWG) have identified this subtype as having a distinct clinical profile within the FTD spectrum (Ulugut et al., 2024, A&D). However, its genetic and pathological underpinnings remain unexplored in large, multicultural cohorts. Methods Retrospective analyses encompassing clinical, genetic, pathological, and neuroimaging data from 23 IWG sites across 13 countries in Asia, Middle East, Europe, North and South America were conducted. The study included 444 patients with FTD exhibiting predominant RATL atrophy. Results Genetic screening was performed on 51% ( n = 225) of the cohort for at least the major frontotemporal lobar degeneration (FTLD) mutations including microtubule‐associated protein tau ( MAPT ), progranulin ( GRN ), and chromosome 9 open reading frame 72 ( C9orf72 ), or dementia panels encompassing extended sets of genes. Of these, 81% were sporadic, showing negative results for the screened genes and a modified Goldman Score of ≥ 3, indicating a negative family history for dementia. The MAPT mutation was the most common genetic variant, identified in 7% of the screened cases (Figure 1). Pathological confirmation was available for 63 patients. Among the sporadic cases, transactive response DNA‐binding protein 43 type C (TDP‐C) pathology was most prevalent (60%, n = 32), while tau‐MAPT pathology was most common in the genetic cases (38%, n = 16). Fifteen cases did not fit neatly into genetic or sporadic categories, displaying heterogeneous pathologies (Figure 2). At the initial visit, compared to genetic cases, patients with TDP‐C pathology were older, and more frequently exhibited semantic deficits, with less frequent attention difficulties and executive dysfunction. No differences were observed in sex distribution, symptom duration or disease severity between genetic and sporadic TDP‐C cases. However, left handedness was more common in TDP‐C cases (14%) compared to genetic cases (5%). Conclusion While FTD with RATL atrophy primarily appears sporadic, a significant proportion of cases exhibit genetic variants. These sporadic and genetic subtypes display distinct neuropathological features and clinical manifestations. Given the implications for therapeutic strategies, precise clinical and molecular subtyping is critical for enhancing patient management and ensuring appropriate enrollment in clinical trials.

Abstract Background Quantitative susceptibility mapping (QSM) can detect iron deposition or myelin loss in the brain by estimating magnetic susceptibility properties. Iron is an important component in neurofibrillary tangles and is known to co‐localize in regions with tangle burden in Alzheimer's disease (AD). Abnormal magnetic susceptibility measured on QSM has been observed in atypical AD, although it is unclear if susceptibility is regionally related to AV‐1451‐PET uptake in atypical AD. Method Forty atypical AD patients (visual variant=24, language variant=7, others=9) were recruited by the Neurodegenerative Research group from the Department of Neurology, Mayo Clinic, Rochester, MN. They underwent a 3T MRI scan with a five‐echo gradient echo sequence for calculation of QSM ( n = 80), Aβ (Pittsburgh Compound‐B) and a 18 F‐ AV‐1451 PET scan ( n = 73). All patients showed evidence of Aβ positivity on PET. To assess the relationship between QSM and AV‐1451‐PET, two approaches were used i) Voxel‐based regression analysis using VoxelStats for the whole brain, and ii) region‐of‐interest (ROI)‐based Spearman's correlation analyses using cortical and subcortical ROIs. All models were adjusted for age and sex as covariates and were corrected for multiple comparisons, specifically the VoxelStats regression maps were corrected using random field theory and the ROI‐based correlation plots were corrected using false discovery rate. Result At the voxel‐level, positive correlations between AV‐1451‐PET and QSM were only observed in the left caudate (Figure 1). At the ROI‐level, no significant associations were found, although uncorrected data showed a positive association in the occipital lobe (red circle) and a negative association between substantia nigra susceptibility and occipital AV‐1451 uptake (blue circle) (Figure 2). Since these findings did not survive corrections, they should be interpreted cautiously. Conclusion Our data provides little evidence that regional AV‐1451 PET uptake is related to susceptibility changes in patients with atypical AD, suggesting that iron deposition may not be associated with regional tau accumulation in AD.

Abstract Background In addition to visuospatial and visuoperceptual deficits, most PCA patients also report deficits in visual attention, episodic memory, and working memory. The dorsal attention network is known to play a critical role in modulating these clinical functions. However, little is known about the relationship of the dorsal attention network with other core networks and relationships to volume loss and memory functions in PCA. Method Fifty‐seven PCA patients were recruited by the Neurodegenerative Research group, Mayo Clinic, and compared to 60 cognitively unimpaired (CU) individuals from the Mayo Clinic Study of Aging. The CONN functional connectivity toolbox was used to calculate within‐ and between‐network connectivity. Functional connectivity within the key regions (i.e., inter‐hemisphere connectivity) of the dorsal attention network, namely frontal eye field (FEF) and intraparietal sulcus (IPS), and the entire network was generated. Functional connectivity between the dorsal attention network and the frontoparietal, visual, and default mode networks (DMN) were also generated using CONN's network parcellation atlas. Multivariate linear regression models were fit i) to compare within‐ and between‐network connectivity between both groups and ii) to assess relationships between within‐network connectivity and both gray matter volumes and clinical test scores. Result PCA showed reduced within‐network connectivity in the dorsal attention network, specifically within the IPS and the entire network compared to CU. An increase in between‐network connectivity between the frontoparietal network and both FEF and the entire dorsal attention network was noted in PCA compared to CU (Figure 1). Lower dorsal attention within‐network connectivity was associated with a trend for lower volumes in the entire network (Figure 2) and significantly lower scores on the auditory verbal learning test‐recognition percent correct (AVLT‐RCP) and Wechsler Memory Scale (WMS) III‐digit span backward in PCA (Figure 3). Conclusion These findings suggest that within‐ and between‐network connectivity of the dorsal attention network, both within key regions and the entire network, was disrupted in PCA patients. However, this network did not show disrupted connectivity with the core PCA networks. Within‐network connectivity disruptions in the dorsal attention network are associated with aspects of memory function, and to some extent, with volume loss.

Abstract Neuroimaging can assess different pathophysiological features of the brain in Alzheimer's disease (AD), including structure, function and protein deposition, and can be used to help identify patients for clinical treatment trials and monitor and assess potential treatment effects on disease progression. While large scale longitudinal studies are underway to validate potential neuroimaging biomarkers in amnestic AD, less efforts have focused on atypical clinical presentations, such as language, visual, dysexecutive, behavioral and motor presentations of AD. These patients would be ideal candidates for treatment trials given that they are relatively young, and the disease is less influenced by age‐associated co‐pathologies, providing a purer disease model of AD. Rates of brain atrophy provide excellent surrogate disease markers in amnestic AD and they will also likely have utility in atypical AD, although cortical, rather than medial temporal, measurements perform better. Optimum sample size estimates required to detect a 20% treatment effect in both the language and visual variants of AD were obtained with rates of inferior temporal atrophy in our sample (113 and 100 patients required per arm, respectively). However, heterogeneity in rates and patterns of atrophy are observed across phenotypes, and with age and disease stage, and these factors would need to be considered in clinical trials. Utilizing direct markers of tau deposition from PET would be optimal. Tau uptake increases over time in relatively consistent patterns across atypical AD phenotypes, although rates vary across patients and with age and baseline levels, with tau uptake plateauing at high levels potentially limiting utility as an outcome measure in patients with advanced disease. Metrics of connectivity also worsen over time in atypical AD patients, with evidence that declines in default mode network connectivity may be common across phenotypes and have some utility, although once again changes are highly variable and influenced by age and tau burden. In summary, we are gaining a better understanding of factors that influence rates of change in atypical AD that need to be considered in treatment trials, although more work is needed to identify optimum biomarkers to track disease progression across the AD clinical spectrum.

Abstract Background Neuropathologic evaluation is essential for diagnosing and treating dementia, but definitive diagnoses is only available after post‐mortem brain autopsy. Positron emission tomography (PET) offers a potential in vivo proxy for predicting neuropathology. This study proposes a semi‐supervised learning (SSL) model using a single FDG‐PET image to predict underlying neuropathology. Method The SSL model leverages a self‐organized graph structure based on a patient similarity network (PSN) created from 1,495 FDG‐PET images across the aging and neurodegenerative spectrum. Each patient is represented by a node, with edges indicating image similarity derived from principal component analysis features and cosine similarity weights. The PSN structure connects 20 nearest neighbors. Neuropathologic labels were available for 204 autopsied patients. The Poisson Learning Method was employed to propagate labels from these annotated nodes to unlabeled nodes, guided by the PSN structure. FDG‐PET images were collected from clinical and research participants at the Mayo Clinic and processed using an MRI‐free pipeline. Neuropathologic labels were assigned based on widely accepted diagnostic criteria. Leave‐one‐out cross‐validation (LOOCV) was used to assess model performance. Results The confusion matrix demonstrated high accuracy in predicting Alzheimer's disease, frontotemporal lobar degeneration with tau inclusions, and Lewy body disease pathology. A Sankey diagram and label distribution analysis revealed strong correlations between clinical and predicted neuropathologic labels. Conclusion This study highlights the potential of a graph‐based SSL pipeline to predict neuropathological changes using FDG‐PET imaging data, despite limited pathology labels. The findings underscore the value of SSL in bridging the gap between abundant neuroimaging data and scarce neuropathologic labels, contributing to improved dementia diagnosis and understanding.

Abstract Capgras syndrome is a delusional misidentification syndrome characterized by the recurrent belief that someone, usually a family member, has been replaced by an impostor. Although described over a century ago, its aetiology, clinical features and neuroimaging characteristics remain poorly understood due to its rarity. This study aimed to clarify these aspects through the analysis of a large cohort and to explore its clinical implications and underlying mechanisms. We conducted a retrospective cohort study by reviewing medical records of patients diagnosed with Capgras syndrome at the Mayo Clinic (Rochester, MN) over a 28-year period (January 1995 to December 2022). Clinical, neuropathological and neuroimaging data were analysed. A total of 204 patients were included (median age at onset: 73 years; 44% female). Twelve patients underwent neuropathological examination, all of whom exhibited α-synuclein pathology, including one patient with a clinical diagnosis of Alzheimer’s disease (AD). Regarding clinical diagnoses, neurodegenerative diseases were the most common (69%, n = 140), with dementia with Lewy bodies (DLB) being predominant (58%, n = 118), followed by mixed aetiologies (‘two-hits’) (18%, n = 36) and AD (10%, n = 21). Psychotic disorders accounted for 9% (n = 18) of cases. No case was attributed to a single stroke, although 9% (n = 19) involved coexisting cerebrovascular disease in the context of AD or DLB. In DLB, the timing of Capgras syndrome onset varied: it occurred later than cognitive decline and core clinical features (e.g. visual hallucinations, fluctuating cognition, parkinsonism) in both DLB and mild cognitive impairment-onset prodromal DLB, but earlier in psychiatric-onset prodromal DLB. In both DLB and AD, Capgras syndrome typically targeted a single spouse, whereas in psychotic disorders, it often involved multiple, non-spousal targets. Depression or anxiety was present in 55% (n = 112). Capgras syndrome worsened in the evening or at night (87%, n = 45/52), suggesting a link to negative affective states. Among 82 patients with DLB and AD treated with cholinesterase inhibitors, 15% (n = 12) showed symptomatic improvement. Neuroimaging with MRI and 18F-fluorodeoxyglucose-PET revealed widespread bilateral cortical involvement and prominent right frontal dysfunction in DLB and AD. Capgras syndrome is associated with DLB and could serve as a potential early diagnostic clue. Recognizing its phenomenological features—the number and type of targeted individuals—can help differentiate between neurodegenerative and psychiatric aetiologies. In neurodegenerative diseases, Capgras syndrome may reflect a multifactorial, dynamic process, driven by widespread bilateral cortical dysfunction (particularly involving the right frontal lobe) and psychological factors. Thus, a combined approach involving pharmacological and non-pharmacological interventions may offer effective management strategies.