Alzheimer’s disease-related atrophy in the posterior cingulate cortex, a key node of the default mode network, is present in the early stages of disease progression across clinical phenotypic variants of the disease. In the typical amnestic variant, posterior cingulate cortex neuropathology has been linked with disrupted connectivity of the posterior default mode network, but it remains unclear if this relationship is observed across atypical variants of Alzheimer’s disease. In the present study, we first sought to determine if tau pathology is consistently present in the posterior cingulate cortex and other posterior nodes of the default mode network across the atypical Alzheimer’s disease syndromic spectrum. Second, we examined functional connectivity disruptions within the default mode network and sought to determine if tau pathology is related to functional disconnection within this network. We studied a sample of 25 amyloid-positive atypical Alzheimer’s disease participants examined with high-resolution MRI, tau (¹⁸F-AV-1451) PET, and resting-state functional MRI. In these patients, high levels of tau pathology in the posteromedial cortex and hypoconnectivity between temporal and parietal nodes of the default mode network were observed relative to healthy older controls. Furthermore, higher tau signal and reduced grey matter density in the posterior cingulate cortex and angular gyrus were associated with reduced parietal functional connectivity across individual patients, related to poorer cognitive scores. Our findings converge with what has been reported in amnestic Alzheimer’s disease, and together these observations offer a unifying mechanistic feature that relates posterior cingulate cortex tau deposition to aberrant default mode network connectivity across heterogeneous clinical phenotypes of Alzheimer’s disease.

Heterogeneity within the Alzheimer's disease (AD) syndromic spectrum is typically classified in a domain-specific manner (e.g., language vs. visual cognitive function). The central aim of this study was to investigate whether impairment in visual cognitive tasks thought to be subserved by posterior cortical dysfunction in non-amnestic AD presentations is associated with tau, amyloid, or neurodegeneration in those regions using ¹⁸F-AV-1451 and ¹¹C-PiB positron emission tomography (PET) and magnetic resonance imaging (MRI). Sixteen amyloid-positive patients who met criteria for either Posterior Cortical Atrophy (PCA; n = 10) or logopenic variant Primary Progressive Aphasia (lvPPA; n = 6) were studied. All participants underwent a structured clinical assessment, neuropsychological battery, structural MRI, amyloid PET, and tau PET. The neuropsychological battery included two visual cognitive tests: VOSP Number Location and Benton Facial Recognition. Surface-based whole-cortical general linear models were used to first explore the similarities and differences between these biomarkers in the two patient groups, and then to assess their regional associations with visual cognitive test performance. The results show that these two variants of AD have both dissociable and overlapping areas of tau and atrophy, but amyloid is distributed with a stereotyped localization in both variants. Performance on both visual cognitive tests were associated with tau and atrophy in the right lateral and medial occipital association cortex, superior parietal cortex, and posterior ventral occipitotemporal cortex. No cortical associations were observed with amyloid PET. We further demonstrate that cortical atrophy has a partially mediating effect on the association between tau pathology and visual cognitive task performance. Our findings show that non-amnestic variants of AD have partially dissociable spatial patterns of tau and atrophy that localize as expected based on symptoms, but similar patterns of amyloid. Further, we demonstrate that impairments of visual cognitive dysfunction are strongly associated with tau in visual cortical regions and mediated in part by atrophy.

Posterior cortical atrophy (PCA), usually an atypical clinical syndrome of Alzheimer’s disease, has well-characterized patterns of cortical atrophy and tau deposition that are distinct from typical amnestic presentations of Alzheimer’s disease. However, the mechanisms underlying the cortical spread of tau in PCA remain unclear. Here, in a sample of 17 biomarker-confirmed (A+/T+/N+) individuals with PCA, we sought to identify functional networks with heightened vulnerability to tau pathology by examining the cortical distribution of elevated tau as measured by ¹⁸F-flortaucipir (FTP) PET. We then assessed the relationship between network-specific FTP uptake and visuospatial cognitive task performance. As predicted, we found consistent and prominent localization of tau pathology in the dorsal attention network and visual network of the cerebral cortex. Elevated FTP uptake within the dorsal attention network (particularly the ratio of FTP uptake between the anterior and posterior nodes) was associated with poorer visuospatial attention in PCA; associations were also identified in other functional networks, although to a weaker degree. Furthermore, using functional MRI data collected from each patient at wakeful rest, we found that a greater anterior-to-posterior ratio in FTP uptake was associated with stronger intrinsic functional connectivity between anterior and posterior nodes of the dorsal attention network. Taken together, we conclude that our cross-sectional marker of anterior-to-posterior FTP ratio could indicate tau propagation from posterior to anterior dorsal attention network nodes, and that this anterior progression occurs in relation to intrinsic functional connectivity within this network critical for visuospatial attention. Our findings help to clarify the spatiotemporal pattern of tau propagation in relation to visuospatial cognitive decline and highlight the key role of the dorsal attention network in the disease progression of PCA.

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 positron emission tomography (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 magnetic resonance imaging (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 < .001, Cohen’s d = 0.95. Across clinical phenotypes, baseline tau in the default mode network was the strongest predictor of clinical decline (R² = .30), outperforming a simpler model with baseline clinical impairment and demographic variables (R² = .10), tau in other functional networks (R² = .11-.26), and the magnitude of cortical atrophy (R² = .20) and amyloid burden (R² = .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 one 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.

Alzheimer's disease (AD) is characterized neuropathologically by β-amyloid (Aβ) plaques, hyperphosphorylated tau neurofibrillary tangles, and neurodegeneration, which lead to a phenotypically heterogeneous cognitive-behavioral dementia syndrome. Our understanding of how these neuropathological and neurodegeneration biomarkers relate to each other is still evolving. A relatively new approach to measuring structural brain change, gray matter to white matter signal intensity ratio (GWR), quantifies the signal contrast between these tissue compartments, and has emerged as a promising marker of AD-related neurodegeneration. We sought to validate GWR as a novel MRI biomarker of neurodegeneration in 29 biomarker positive individuals across the atypical syndromic spectrum of AD. Bivariate correlation analyses revealed that GWR was associated with cortical thickness, tau PET, and amyloid PET, with GWR showing a larger magnitude of abnormality than cortical thickness. We also found that combining GWR, cortical thickness, and amyloid PET better explained observed tau PET signal than using these modalities alone, suggesting that the three imaging biomarkers contribute independently and synergistically to explaining the variance in the distribution of tau pathology. We conclude that GWR is a uniquely sensitive in vivo marker of neurodegenerative change that reflects pathological mechanisms which may occur prior to cortical atrophy. By using all of these imaging biomarkers of AD together, we may be better able to capture, and possibly predict, AD neuropathologic changes in vivo. We hope that such an approach will ultimately contribute to better endpoints to evaluate the efficacy of therapeutic interventions as we move toward an era of disease-modifying treatments for this devastating disease.

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% of sample), Amnestic Predominant (11%), Language Predominant (11%), Visuospatial Predominant (15%), Mixed Amnestic/Dysexecutive Predominant (11%), and Multidomain (30%). These phenotypes did not differ by age, sex, or years of education. The APOE ɛ4 genotype was enriched in the Amnestic Predominant group, who were also rated as least impaired. Cortical thickness analysis validated these clinical phenotypes with dissociations in atrophy patterns observed between the Dysexecutive and Amnestic Predominant groups. In contrast to the heterogeneity observed from our neuropsychological 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% met criteria for Posterior Cortical Atrophy, and 5% met criteria for Primary Progressive Aphasia. A neuropsychological data-driven method to phenotype EOAD individuals uncovered a more detailed understanding of the presenting heterogeneity in this atypical AD sample compared to clinical judgment alone. Clinicians and patients may over-report memory dysfunction at the expense of non-memory symptoms. These findings have important implications for diagnostic accuracy and treatment considerations.