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. 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. 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). 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.

In this study, we investigated longitudinal tau spreading in 23 amyloid-positive individuals with early-stage posterior cortical atrophy (PCA), a clinical syndrome typically characterized by progressive visual cognitive deficits emerging largely from underlying Alzheimer's disease-related tau deposition in posterior cortical areas. Each PCA participant underwent structural MRI and 18F-Flortaucipir PET at baseline and follow-up (mean interval between baseline and follow-up PET = 1.17 ± 0.29 years). Using directional regression analysis (i.e., a regression-based model testing temporal directionality in tau spread), we quantified how tau epicenters (top 10% regions by baseline tau) predicted longitudinal tau accumulation. Seed-based analysis revealed evidence supporting the role of posterior cortical epicenters in the visual and dorsal attention networks (DAN), showing directional spreading of tau to anterior DAN nodes and the default mode network (DMN), with the largest effects in anterior DAN regions. Complementary graph theory analysis identified the visual network and posterior DMN as hubs of tau spread. These findings collectively suggest that longitudinal tau spread in PCA follows hierarchical progression from primary epicenters within the visual network and DAN to secondary epicenters, including the posterior DMN, possibly mediated by dynamic connectivity reorganization as primary epicenters become saturated with tau pathology.

Patients with atypical variants of Alzheimer's disease (AD) often present at a younger age with predominantly non-amnestic impairments and a more aggressive disease course. Historically, individuals with atypical presentations have not been included in large-scale clinical trials, which typically focus on late-onset, sporadic amnestic-predominant AD. Consequently, treatment options and research efforts specific to atypical AD remain limited. The emergence of amyloid-targeting therapies that slow disease progression underscores these challenges, as evidence supporting their efficacy in early-onset amnestic and non-amnestic AD variants is scarce. This perspective article argues that atypical AD represents an excellent disease model for clinical trials and proposes strategies to address critical gaps in clinical trial design for this population. Key considerations include optimizing participant selection approaches, establishing syndrome-specific or surrogate biological and clinical endpoints, and fostering advocacy to enhance early and accurate diagnosis, equitable representation, and outcomes for these populations.

The diagnostic criteria for atypical syndromes of Alzheimer's disease (AD) specify that episodic memory is relatively preserved at initial stages and may develop as the disease progresses. Memory deficits have been reported in posterior cortical atrophy (PCA), and logopenic variant primary progressive aphasia (lvPPA), despite these groups being referred to as “non-amnestic”. The shared and dissociable patterns of memory impairment across atypical syndromes have not yet been clearly delineated. We tested 16 early-onset (EOAD), 9 lvPPA, 21 PCA, and 29 cognitively normal (CN) participants with a novel object-location memory test (OLMT) designed to foster deep learning and interrogate associative memory between objects and locations without lexical retrieval demands. Analysis of variance (ANOVA) and post-hoc t -tests were conducted to characterize between group performance. General linear models interrogated the association of atrophy in the default mode network with different stages of memory. All atypical AD variants demonstrated impaired encoding over three learning trials compared to CNs, with a positive learning curve. EOAD demonstrated greater storage loss compared to the other groups at 3-minute delayed recognition (vs. PCA: t  = 3.2, p  = 0.002; vs. lvPPA: t  = 3.1, p  = 0.005) but comparable levels of impairment at 30-minute delayed recognition (EOAD: z=-4.4 ± 6.1; PCA: z=-2.2 ± 3.6; lvPPA: z=-1.2 ± 2.1). While the lvPPA group was able to effectively associate locations with objects and retain this association over time, other variants struggled with both encoding (EOAD: z=-4.4 ± 6.1; PCA: z=-2.2 ± 3.6) and retention (EOAD: z=-4.4 ± 6.1; PCA: z=-2.2 ± 3.6) of spatial locations over time. Medial temporal lobe atrophy was uniquely associated with object-location associative binding and storage over time, but not object encoding alone. All atypical AD syndromes demonstrated poor encoding and storage loss, adding to the characterization of memory impairment in atypical “non-amnestic” AD. EOAD participants demonstrated faster storage loss compared to the other variants, potentially reflecting multidomain impairment. While PCA and lvPPA performed comparably on object memory, these groups were differentiated by location memory binding. Understanding the varied presentation of memory deficits in atypical syndromes can help inform accurate diagnosis and cognitive skills training to cope with neurodegenerative decline.

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.

There 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. We 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% [ 18 F]AV1451/[ 18 F]flortaucipir/Tauvid, 27% [ 18 F]MK6240, 19% [ 18 F]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. Tau 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). This 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.

The clinical presentations of early-onset Alzheimer’s disease (EOAD) and late-onset Alzheimer’s disease are distinct, with EOAD having a more aggressive disease course with greater heterogeneity. Recent publications from the Longitudinal Early-Onset Alzheimer’s Disease Study (LEADS) described EOAD as predominantly amnestic, though this phenotypic description was based solely on clinical judgment. To better understand the phenotypic range of EOAD presentation, we applied a neuropsychological data-driven method to subtype the LEADS cohort. Neuropsychological test performance from 169 amyloid-positive EOAD participants were analyzed. Education-corrected normative comparisons were made using a sample of 98 cognitively normal participants. Comparing the relative levels of impairment between each cognitive domain, we applied a cut-off of 1 SD below all other domain scores to indicate a phenotype of “predominant” impairment in a given cognitive domain. Individuals were otherwise considered to have multidomain impairment. Whole-cortex general linear modeling of cortical atrophy was applied as an MRI-based validation of these distinct clinical phenotypes. We identified 6 phenotypic subtypes of EOAD: Dysexecutive Predominant (22

Background: Posterior Cortical Atrophy (PCA) is a clinical syndrome marked by progressive visuospatial impairment, usually due to underlying Alzheimer’s disease. While reading and spelling deficits are recognized clinical features of this syndrome, the contributions of visuoperceptual versus linguistic deficits to these impairments are still unclear. Methods: To that end, we examined reading and spelling performance in 23 individuals from the Massachusetts General Hospital PCA cohort. Participants completed tests of reading from the Western Aphasia Battery and spelling to dictation from the Boston Diagnostic Aphasia Examination. A mixed-methods analysis included quantitative scoring and qualitative observations of visual behaviors, error patterns, and compensatory strategies. Results: Participants commonly demonstrated visual scanning errors, difficulty following multi-line text, and spelling errors reflecting both visual–perceptual and orthographic–linguistic breakdowns. Conclusions: Because reading and spelling in PCA are variably impaired cognitive skills driven by visual deficits and lexical vulnerability, assessments and interventions must account for deficits in both cognitive processes. Our findings highlight the vulnerability of reading and spelling in PCA and underscore the need for multimodal assessment strategies that account for the interplay of visual, phonological, and lexical processes. These insights can inform diagnosis and guide the development of accessible interventions tailored to optimize compensatory strategies to support functional language abilities.

The computational analysis of language has demonstrated significant diagnostic value in typical older-onset Alzheimer's disease (AD). Here, we investigate whether digital language markers can distinguish between variants of atypical AD, including logopenic variant Primary Progressive Aphasia (lvPPA) and Posterior Cortical Atrophy (PCA). Both lvPPA and PCA patients exhibit deficits in spontaneous speech, such as difficulty accessing low-frequency words. However, these deficits likely arise from distinct mechanisms: lvPPA patients have an intrinsic deficit in lexicosemantic retrieval, while deficits in PCA may be secondary to visual processing abnormalities. We hypothesize that distinct digital language markers can differentiate between these variants and provide insight into these cognitive mechanisms. We analyzed the spoken language of 29 healthy controls, 52 lvPPA participants, and 32 PCA participants during two tasks: 1) a picture description task requiring a high visual demand and 2) a job description task with minimal visual demand. Computational methods quantified word frequency and the total number of visual content words retrieved from the picture. Tau PET imaging was used to investigate the anatomical correlates of digital language markers in the picture description task. Both lvPPA and PCA participants demonstrated difficulty accessing low-frequency words during the picture description task. In the job description task, lvPPA participants continued to struggle to access low-frequency words while PCA participants were comparable to healthy controls. Furthermore, although both AD variants retrieved fewer visual content words from the picture compared to healthy controls, PCA participants produced significantly fewer words, underscoring their challenges in processing visual information. We found that word frequency positively correlated with tau deposition in distinct regions in lvPPA and PCA during the picture description task. Furthermore, the total number of visual content words was found to anti-correlate with tau deposition in occipital visual processing areas in PCA but not in lvPPA. While both lvPPA and PCA patients struggle with low-frequency word retrieval, this deficit in lvPPA stems from intrinsic lexicosemantic impairments, whereas in PCA, it is secondary to difficulties in visual processing. These results highlight the significant utility of digital language markers in differentiating between AD variants and understanding underlying language mechanisms.

Posterior Cortical Atrophy (PCA) is a syndrome characterized by a progressive decline in higher-order visuospatial processing, leading to symptoms such as space perception deficit, simultanagnosia, and object perception impairment. While PCA is primarily known for its impact on visuospatial abilities, recent studies have documented language abnormalities in PCA patients. This study aims to delineate the nature and origin of language impairments in PCA, hypothesizing that language deficits reflect the visuospatial processing impairments of the disease. We compared the language samples of 25 patients with PCA with age-matched cognitively normal (CN) individuals across two distinct tasks: a visually-dependent picture description and a visually-independent job description task. We extracted word frequency, word utterance latency, and spatial relational words for this comparison. We then conducted an in-depth analysis of the language used in the picture description task to identify specific linguistic indicators that reflect the visuospatial processing deficits of PCA. Patients with PCA showed significant language deficits in the visually-dependent task, characterized by higher word frequency, prolonged utterance latency, and fewer spatial relational words, but not in the visually-independent task. An in-depth analysis of the picture description task further showed that PCA patients struggled to identify certain visual elements as well as the overall theme of the picture. A predictive model based on these language features distinguished PCA patients from CN individuals with high classification accuracy. The findings indicate that language is a sensitive behavioral construct to detect visuospatial processing abnormalities of PCA. These insights offer theoretical and clinical avenues for understanding and managing PCA, underscoring language as a crucial marker for the visuospatial deficits of this atypical variant of Alzheimer’s disease.

Identifying individuals with early-stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would enable better-informed medical, support and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. Across heterogeneous clinical phenotypes, patients with atypical AD consistently exhibit abnormal tau accumulation in the posterior nodes of the default mode network of the cerebral cortex. This evidence suggests that tau burden in this functional network could be a common imaging biomarker for prognostication across the syndromic spectrum of AD. Here, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes: Posterior Cortical Atrophy (n = 16); logopenic variant Primary Progressive Aphasia (n = 15); and amnestic syndrome with multi-domain impairment and young age of onset < 65 years (n = 17). All patients underwent MRI, tau PET and amyloid PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Atypical early AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, P < 0.001, Cohen's d = 0.95. Across clinical phenotypes, baseline tau in the default mode network was the strongest predictor of clinical decline (R2 = 0.30), outperforming a simpler model with baseline clinical impairment and demographic variables (R2 = 0.10), tau in other functional networks (R2 = 0.11-0.26) and the magnitude of cortical atrophy (R2 = 0.20) and amyloid burden (R2 = 0.09) in the default mode network. Overall, these findings point to the contribution of default mode network tau to predicting the magnitude of clinical decline in atypical early AD patients 1 year later. This simple measure could aid the development of a personalized prognostic, monitoring and treatment plan, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course.

The presence of Subjective Cognitive Decline (SCD) in cognitively unimpaired (CU) individuals represents a significant risk factor for progression from preclinical to the symptomatic stage of Alzheimer's disease (AD). Studies on SCD to date have focused on memory concerns as a risk factor for developing amnestic AD dementia. However, AD pathology underlies a heterogeneous phenotypic spectrum, including a visual variant of AD—Posterior Cortical Atrophy (PCA)—thought to comprise 5‐15% of AD dementia cases. We do not yet have a method for identifying individuals at the preclinical stage of AD who go on to develop PCA. Self‐report responses on the Everyday Cognition Scale (ECOG) from 253 CU participants (mean age = 72.1 ± 8.9) in the Harvard Aging Brain Study were analyzed. We explored associations between total participant responses on the visuospatial subscale, objective cognitive tests, and amyloid PET positivity. An exploratory whole‐cortex tau PET general linear model was conducted to examine the association between subjective visuospatial decline and emerging tau burden in the neocortex. Four percent of participants ( N = 9) endorsed “at least occasional problems” or more averaged across the 7‐item ECOG visuospatial subscale. These individuals did not differ from the rest of the sample on age, sex, education, or MMSE. ECOG visuospatial scores across the whole CU group were unrelated to MMSE or objective visuospatial cognition. ECOG visuospatial scores were higher in PiB+ individuals compared to PiB‐ individuals ( t = 3.4, p = 0.001). Subjective visuospatial concerns were associated with right‐hemisphere predominant tau in temporoparietal and prefrontal cortices, largely overlapping with regions associated with subjective memory concerns and with tau epicenters reported in preclinical AD. A subset of CU individuals endorsed subjective visuospatial decline, a cognitive domain that does not typically decline in healthy aging. The positive relationships observed between subjective visuospatial decline and biomarkers of amyloid and tau suggest that the ECOG can be a useful tool in capturing subtle visuospatial decline in addition to early memory concerns in preclinical AD. Developing methodology to predict the development of atypical AD variants has significant implications for optimizing early diagnosis and treatment of this disease.

Early-onset Alzheimer’s disease (EOAD) manifests prior to the age of 65. Clinical presentation of EOAD is distinct from that of late-onset Alzheimer’s disease, and is characterized as having a more aggressive disease course with greater heterogeneity. Recent publications from the Longitudinal Early-Onset Alzheimer’s Disease Study (LEADS) described their sample as predominantly amnestic, though this phenotypic description was based solely on clinical judgment. To better understand the range of EOAD presentation, we applied a neuropsychological data-driven method to phenotypic subtyping within the LEADS cohort. Data from 169 amyloid-positive EOAD participants with composite data in all cognitive domains (Episodic Memory, Executive Functioning, Speed/Attention, Language, and Visuospatial) were analyzed. Our approach consisted of comparing the relative levels of baseline impairment in each cognitive domain. Education-corrected normative comparisons were made using a sample of 98 aged-matched cognitively normal participants. A cut-off of 1 SD below all other composite domain scores was applied to indicate a phenotype of “predominant” impairment in a given cognitive domain. Individuals were otherwise considered to have a phenotype best characterized by multidomain impairment. We identified 6 phenotypic subtypes of EOAD (Table 1): Dysexecutive-predominant (22% of sample), Amnestic-predominant (11%), Language-predominant (11%), Visuospatial-predominant (15%), Mixed Amnestic/Dysexecutive-predominant (11%), and Multidomain (30%). These subtypes did not differ on age, age-at-symptom-onset, sex, or overall clinical severity ( p >0.05). Groups differed on global cognitive functioning (MMSE) such that the Amnestic-predominant group performed better than other domain-predominant subtypes of EOAD ( p >0.05). In contrast to the heterogeneity observed from our data-driven approach, diagnostic classifications for this same sample based solely on clinical judgment indicated that 82% of individuals were amnestic-predominant, 9% were non-amnestic, 4% were visuospatial-predominant, and 5% were language-predominant. Applying a neuropsychological data-driven method of phenotyping EOAD individuals uncovered a more detailed understanding of the diversity of presenting heterogeneity in this atypical AD group compared to clinical judgment alone. These results suggest that clinicians and patients may over-prioritize memory dysfunction during subjective reporting at the expense of non-memory symptoms, which has important implications for diagnostic accuracy and treatment considerations. We plan to investigate the patterns of cortical atrophy and network dysfunction subserving this heterogeneity.

BACKGROUND:The computational analysis of language has demonstrated significant diagnostic value in typical older-onset Alzheimer's disease (AD). Here, we investigate whether digital language markers can distinguish between variants of atypical AD, including logopenic variant Primary Progressive Aphasia (lvPPA) and Posterior Cortical Atrophy (PCA). Both lvPPA and PCA patients exhibit deficits in spontaneous speech, such as difficulty accessing low-frequency words. However, these deficits likely arise from distinct mechanisms: lvPPA patients have an intrinsic deficit in lexicosemantic retrieval, while deficits in PCA may be secondary to visual processing abnormalities. We hypothesize that distinct digital language markers can differentiate between these variants and provide insight into these cognitive mechanisms. METHODS:We analyzed the spoken language of 29 healthy controls, 52 lvPPA participants, and 32 PCA participants during two tasks: 1) a picture description task requiring a high visual demand and 2) a job description task with minimal visual demand. Computational methods quantified word frequency and the total number of visual content words retrieved from the picture. Tau PET imaging was used to investigate the anatomical correlates of digital language markers in the picture description task. RESULTS:Both lvPPA and PCA participants demonstrated difficulty accessing low-frequency words during the picture description task. In the job description task, lvPPA participants continued to struggle to access low-frequency words while PCA participants were comparable to healthy controls. Furthermore, although both AD variants retrieved fewer visual content words from the picture compared to healthy controls, PCA participants produced significantly fewer words, underscoring their challenges in processing visual information. We found that word frequency positively correlated with tau deposition in distinct regions in lvPPA and PCA during the picture description task. Furthermore, the total number of visual content words was found to anti-correlate with tau deposition in occipital visual processing areas in PCA but not in lvPPA. CONCLUSION:While both lvPPA and PCA patients struggle with low-frequency word retrieval, this deficit in lvPPA stems from intrinsic lexicosemantic impairments, whereas in PCA, it is secondary to difficulties in visual processing. These results highlight the significant utility of digital language markers in differentiating between AD variants and understanding underlying language mechanisms.

Abstract Identifying individuals with early-stage Alzheimer’s disease (AD) at greater risk of steeper clinical decline would enable better-informed medical, support and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. Across heterogeneous clinical phenotypes, patients with atypical AD consistently exhibit abnormal tau accumulation in the posterior nodes of the default mode network of the cerebral cortex. This evidence suggests that tau burden in this functional network could be a common imaging biomarker for prognostication across the syndromic spectrum of AD. Here, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes: Posterior Cortical Atrophy (n = 16); logopenic variant Primary Progressive Aphasia (n = 15); and amnestic syndrome with multi-domain impairment and young age of onset < 65 years (n = 17). All patients underwent MRI, tau PET and amyloid PET scans at baseline. Each patient’s longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Atypical early AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, P < 0.001, Cohen’s d = 0.95. Across clinical phenotypes, baseline tau in the default mode network was the strongest predictor of clinical decline (R2 = 0.30), outperforming a simpler model with baseline clinical impairment and demographic variables (R2 = 0.10), tau in other functional networks (R2 = 0.11–0.26) and the magnitude of cortical atrophy (R2 = 0.20) and amyloid burden (R2 = 0.09) in the default mode network. Overall, these findings point to the contribution of default mode network tau to predicting the magnitude of clinical decline in atypical early AD patients 1 year later. This simple measure could aid the development of a personalized prognostic, monitoring and treatment plan, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient’s tau burden while still early in the disease course.

Introduction:Posterior Cortical Atrophy (PCA) is a syndrome characterized by a progressive decline in higher-order visuospatial processing, leading to symptoms such as space perception deficit, simultanagnosia, and object perception impairment. While PCA is primarily known for its impact on visuospatial abilities, recent studies have documented language abnormalities in PCA patients. This study aims to delineate the nature and origin of language impairments in PCA, hypothesizing that language deficits reflect the visuospatial processing impairments of the disease.Methods:We compared the language samples of 25 patients with PCA with age-matched cognitively normal (CN) individuals across two distinct tasks: a visually-dependent picture description and a visually-independent job description task. We extracted word frequency, word utterance latency, and spatial relational words for this comparison. We then conducted an in-depth analysis of the language used in the picture description task to identify specific linguistic indicators that reflect the visuospatial processing deficits of PCA.Results:Patients with PCA showed significant language deficits in the visually-dependent task, characterized by higher word frequency, prolonged utterance latency, and fewer spatial relational words, but not in the visually-independent task. An in-depth analysis of the picture description task further showed that PCA patients struggled to identify certain visual elements as well as the overall theme of the picture. A predictive model based on these language features distinguished PCA patients from CN individuals with high classification accuracy.Discussion:The findings indicate that language is a sensitive behavioral construct to detect visuospatial processing abnormalities of PCA. These insights offer theoretical and clinical avenues for understanding and managing PCA, underscoring language as a crucial marker for the visuospatial deficits of this atypical variant of Alzheimer's disease.

IntroductionVisual naming ability reflects semantic memory retrieval and is a hallmark deficit of Alzheimer’s disease (AD). Naming impairment is most prominently observed in the late-onset amnestic and logopenic variant Primary Progressive Aphasia (lvPPA) syndromes. However, little is known about how other patients across the atypical AD syndromic spectrum perform on tests of auditory naming, particularly those with primary visuospatial deficits (Posterior Cortical Atrophy; PCA) and early onset (EOAD) syndromes. Auditory naming tests may be of particular relevance to more accurately measuring anomia in PCA syndrome and in others with visual perceptual deficits.MethodsForty-six patients with biomarker-confirmed AD (16 PCA, 12 lvPPA, 18 multi-domain EOAD), at the stage of mild cognitive impairment or mild dementia, were administered the Auditory Naming Test (ANT). Performance differences between groups were evaluated using one-way ANOVA and post-hoc t-tests. Correlation analyses were used to examine ANT performance in relation to measures of working memory and word retrieval to elucidate cognitive mechanisms underlying word retrieval deficits. Whole-cortex general linear models were generated to determine the relationship between ANT performance and cortical atrophy.ResultsBased on published cutoffs, out of a total possible score of 50 on the ANT, 56% of PCA patients (mean score = 45.3), 83% of EOAD patients (mean = 39.2), and 83% of lvPPA patients (mean = 29.8) were impaired. Total uncued ANT performance differed across groups, with lvPPA performing most poorly, followed by EOAD, and then PCA. ANT performance was still impaired in lvPPA and EOAD after cuing, while performance in PCA patients improved to the normal range with phonemic cues. ANT performance was also directly correlated with measures of verbal fluency and working memory, and was associated with cortical atrophy in a circumscribed semantic language network.DiscussionAuditory confrontation naming is impaired across the syndromic spectrum of AD including in PCA and EOAD, and is likely related to auditory-verbal working memory and verbal fluency which represent the nexus of language and executive functions. The left-lateralized semantic language network was implicated in ANT performance. Auditory naming, in the absence of a visual perceptual demand, may be particularly sensitive to measuring naming deficits in PCA.

Posterior Cortical Atrophy (PCA) is a clinical syndrome characterized by progressive visuospatial and visuoperceptual impairment. As the neurodegenerative disease progresses, patients lose independent functioning due to the worsening of initial symptoms and development of symptoms in other cognitive domains. The timeline of clinical progression is variable across patients, and the field currently lacks robust methods for prognostication. Here, evaluated the utility of MRI-based cortical atrophy as a predictor of longitudinal clinical decline in a sample of PCA patients. PCA patients were recruited through the Massachusetts General Hospital Frontotemporal Disorders Unit PCA Program. All patients had cortical thickness estimates from baseline MRI scans, which were used to predict longitudinal change in clinical impairment assessed by the CDR Sum-of-Boxes (CDR-SB) score. Multivariable linear regression was used to estimate the magnitude of cortical atrophy in PCA patients relative to a group of amyloid-negative cognitively unimpaired participants. Linear mixed-effects models were used to test hypotheses about the utility of baseline cortical atrophy for predicting longitudinal clinical decline. Data acquired from 34 PCA patients (mean age = 65.41 ± 7.90, 71

Purpose of review The study aims to provide a summary of recent developments for diagnosing and managing posterior cortical atrophy (PCA). We present current efforts to improve PCA characterisation and recommendations regarding use of clinical, neuropsychological and biomarker methods in PCA diagnosis and management and highlight current knowledge gaps. Recent findings Recent multi-centre consensus recommendations provide PCA criteria with implications for different management strategies (e.g. targeting clinical features and/or disease). Studies emphasise the preponderance of primary or co-existing Alzheimer’s disease (AD) pathology underpinning PCA. Evidence of approaches to manage PCA symptoms is largely derived from small studies. Summary PCA diagnosis is frequently delayed, and people are likely to receive misdiagnoses of ocular or psychological conditions. Current treatment of PCA is symptomatic — pharmacological and non-pharmacological — and the use of most treatment options is based on small studies or expert opinion. Recommendations for non-pharmacological approaches include interdisciplinary management tailored to the PCA clinical profile — visual-spatial — rather than memory-led, predominantly young onset — and psychosocial implications. Whilst emerging disease-modifying treatments have not been tested in PCA, an accurate and timely diagnosis of PCA and determining underlying pathology is of increasing importance in the advent of disease-modifying therapies for AD and other albeit rare causes of PCA.

Identifying individuals with symptomatic Alzheimer’s disease (AD) at greater risk of steeper cognitive decline would allow professionals and loved-ones to make better-informed medical, support, and life-planning decisions. In typical AD, the magnitude of cerebral tau accumulation in vivo predicts clinical deterioration. Despite its promise, the utility of tau PET in predicting cognitive decline in individuals with atypical clinical presentations of AD remains unclear. We examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline across atypical AD syndromes. Fifty-seven A/T/N-positive patients (mean age = 64.13 ± 7.72; 24M/33F) with atypical syndromes of AD (19 Posterior Cortical Atrophy, 16 logopenic variant of Primary Progressive Aphasia, 16 dysexecutive AD, five early-onset AD with single-domain impairment, and one Corticobasal Syndrome) and 24 amyloid-negative control participants were included in this study. All participants underwent 18F-Flortaucipir (FTP) PET, amyloid PET, and structural MRI scans at baseline. The rate of clinical decline was quantified as the annualized change in Clinical Dementia Rating Sum-of-Boxes scores (CDR-SB) at baseline and follow-up visits (mean time interval = 1.24 ± 0.34 years). General linear model analyses were performed to examine the pattern of baseline cortical tau deposition in atypical AD patients and its relationship with the rate of clinical decline. Compared with amyloid-negative controls, atypical AD patients showed prominent FTP uptake in posterior cortical regions at baseline, including bilateral posterior cingulate cortex/precuneus and lateral temporo-parietal cortices, which canonically constitute the posterior default mode network (DMN). A brain-behavior regression analysis revealed widespread regions within the DMN where the magnitude of baseline FTP uptake predicted the rate of change in CDR-SB, with anterior DMN regions (medial prefrontal and anterior temporal cortices) most strongly predicting clinical decline. Greater baseline tau accumulation in the anterior DMN, possibly suggesting more extensive tau spread in this network, predicts faster clinical decline in atypical AD. This may serve as an imaging biomarker to guide prognostication for patients with atypical AD and their families and to inform the design of clinical trials, including potentially recruiting multiple clinical phenotypes of AD into a single trial.