Lee, Eddie B

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.

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.

AbstractBackgroundScalable, efficient methods are needed to enroll diverse populations of older adults into AD observational studies and clinical trials. We evaluated preliminary feasibility of a novel, digital, culturally informed approach to recruit and screen participants for the Alzheimer’s Disease Neuroimaging Initiative (ADNI4).MethodsDigital advertising tailored towards Black/African American and Latinx older adults residing near six clinical ADNI sites directed potential participants to a recruitment website (Figure 1). They completed digital surveys of demographics, ADNI exclusion criteria, memory concerns and changes, self‐report cognitive impairment, and the Everyday Cognition Scale (ECog)‐12 item. Participants also completed Novoic Storyteller, a self‐administered speech‐based cognitive test. Digital assessment results were used to prioritize those from minoritized ethnocultural groups, with low educational attainment, and possible Mild Cognitive Impairment (MCI) for remote blood draw at local Quest phlebotomy centers to obtain AD plasma biomarkers. Completion rates and digital assessment performance were compared between minoritized and non‐minoritized groups.ResultsOf 989 participants recruited from digital advertising efforts who provided contact information, 230 (23%) signed consent, and 183 (19%) completed at least one remote assessment (Table 1). 45% were from minoritized ethnocultural groups, 4% had ≤12 years of education, and 53% had evidence of possible MCI from digital assessments. 34 (19%) were referred to the plasma biomarker study, of which 21% completed blood draw. Compared to non‐minoritized participants, minoritized participants were less likely to report a diagnosed cognitive impairment or a family history of AD, less likely to have ECog scores indicative of MCI, and less likely to have a study partner. Minoritized participants had lower ECog and Novoic Storyteller completion rates.ConclusionRecruitment and assessment of a diverse cohort of older adults, including those with possible cognitive impairment, is feasible using culturally informed digital advertising. Improving study engagement and achieving educational diversity are key challenges. This approach is now being scaled up to facilitate recruitment into in‐clinic ADNI4, with the goal of enrolling 500 new participants: >50% from minoritized groups, 40% with MCI, and 80% amyloid positive across diagnostic groups. This approach can be adapted to facilitate recruitment and longitudinal assessment in other AD studies and trials.

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‐ß‐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‐ß‐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 (Fig.1). In line with this, tau epicenters were highly heterogeneous across variants (Fig.1). In all variants, greater tau‐PET covariance was associated with shorter functional connectivity‐based distance (Fig.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, Fig.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.

AbstractBackgroundAlthough the rate of Alzheimer’s disease (AD) in African‐ancestry (AA) Americans is higher than that of persons from European‐ancestry (EA) populations, AA participants have been underrepresented in AD neuropathological studies.MethodUtilizing the AD Research Centers (ADRC) infrastructure, we obtained AA donor pre‐frontal cortex (PFC) tissue from brain repositories of 12 ADRC and generated bulk RNA sequencing (RNA‐seq) data for 179 samples that met QC and inclusion criteria. Previously generated PFC RNAseq data were obtained for 28 additional AA donors from the Columbia University ADRC. Differential gene expression was evaluated among 125 donors with a neuropathological diagnosis of AD (NIA‐Reagan intermediate or high likelihood) and 82 neuropathologically confirmed controls using regression models including covariates for age at death, sex, cell‐type frequencies, and RNA integrity number (RIN) calculated with Limma. FDR‐corrected p‐values (padj) were calculated to control for the 33,611 genes examined.ResultA total of 482 genes surpassed the multiple‐testing threshold. The most significant, ADAMTS2 (p = 2.96 × 10‐8, padj = 0.001), showed increased expression in AD cases (see Table/Figure). We note that ADAMTS2 was differentially expressed in a prior EA study of neuropathologically confirmed AD cases and controls (Panitch et al. Molecular Psychiatry 2021). Additionally, a recent analysis of cognitive resilience in EA neuropathological AD cases identified a strong association with ADAMTS2 (See Li et al. AAIC2024 abstract). Of the differentially expressed genes observed in the Panitch et al. EA study, 385 (35%) were nominally significant,65 (5.8%) were corrected significant, and most (89%) of these genes had the same effect direction in the AA cohort. Some of the observed associations appear to be AA specific (e.g., EFR3B, IRS4, and CA12; see Table). Additionally, we found nominally significant (p<0.05) associations with expression of APOE (Log2 fold change [L2FC = ‐0.20, p = 0.012) and several other established AD genes including SORL1 (L2FC = ‐0.10, p = 0.014) and IGF1R(L2FC = 0.11, p = 0.0013).ConclusionThis largest‐ever (to our knowledge) gene expression study of AD in postmortem brain tissue from AA donors implicates many more genes as having a role in AD in this population than previously identified in genome‐wide association studies and provides insight into trans‐ancestry differences risk for AD.

AbstractBackgroundCognitive resilience, the discrepancy observed in individuals with high Alzheimer’s disease (AD) neuropathology and near‐normal cognition, is a growing area of study, wherein multiple factors are responsible. Currently, the role of the microglial activation in cognitive resilience is unknown. Herein described is a case report characterizing the amyloid responsive microglia (ARM) in an 88‐year‐old male decedent homozygous for APOE E4, clinically cognitively intact, and found to have AD neuropathologic change (ADNC) upon autopsy.MethodThe participant was enrolled in the Mayo Clinic Study of Aging (MCSA) and continuously followed for 14 years from 73‐ to 87‐years‐old, wherein serial MRI and clinical assessments were obtained. An autopsy was performed upon death, and routine neuropathologic sections were taken. Formalin‐fixed, paraffin‐embedded sections were stained with H&E, and single immunohistochemistry was performed using antibodies against tau (AT8), beta‐amyloid (6F3D), alpha‐synuclein (LB509), TDP‐43 (pS409/410), and CD163 (10D6). Digital image analysis was performed on dorsolateral prefrontal cortex sections scanned at 40x (Leica GT450). ARM (CD163% area) and beta‐amyloid (% area) measurements were obtained using QuPath threshold classifiers. Descriptive statistics were performed (Graphpad).ResultThe decedent was an 88‐year‐old male, homozygous for APOE E4, with a history of three cardiovascular and metabolic conditions, and lifelong smoking. His MMSE (average 28/30) and global cognition (average ‐0.51) were relatively stable (Figure 1), with no clinical concerns for cognitive impairment. Cortical thickness was normal (temporal meta‐ROI>3 mm) on four serial MRIs. The participant reported high cognitive, physical activities, and education‐occupation scores (upper quartile for the 70+ population). Neuropathologic evaluation was notable for severe cerebral amyloid angiopathy, high ADNC (A3B3C3), and remote microinfarcts. CD163‐positive ARM were observed in the neocortices and perivascular spaces, and the ARM:beta‐amyloid ratio was 0.26 (Figure 1). This ARM:beta‐amyloid ratio trended upwards (>90th percentile) compared to APOE E4/E4‐matched‐ and age‐matched controls provided from the University of Pennsylvania.ConclusionThis case report demonstrates a cognitively resilient individual with an elevated ARM:amyloid ratio. Conversely, lower ARM ratios were observed in a cognitively impaired cohort, raising the possibility ARM may associate with cognition. ARM may represent a protective and phagocytic population, and further studies correlating microglia, cognition, and putative mechanism are required.

AbstractBackgroundOur understanding of the biological changes in the brain associated with Alzheimer’s disease (AD) pathology and cognitive impairment remains incomplete. Unbiased discovery proteomic analysis of AD brain can help to increase our understanding of these changes.MethodWe analyzed dorsolateral prefrontal cortex, precuneus, and temporal cortex of control, asymptomatic AD, and AD brains from multiple different centers by label‐free quantitative mass spectrometry and weighted protein co‐expression analysis to obtain a consensus protein co‐expression network of AD brain. We also analyzed cerebrospinal fluid to investigate potential biomarkers related to this network.ResultThe network consisted of 13 protein co‐expression modules. Six of these modules correlated with amyloid‐β plaque burden, tau neurofibrillary tangle burden, cognitive function, and clinical functional status, and were altered in asymptomatic AD, AD, or in both disease states. These six modules reflected synaptic, mitochondrial, sugar metabolism, extracellular matrix, cytoskeletal, and RNA binding/splicing biological functions. The identified protein network modules were preserved in a community‐based cohort analyzed by a different quantitative mass spectrometry approach. They were also preserved in temporal lobe and precuneus brain regions. Some of the modules were influenced by aging, and showed changes in other neurodegenerative diseases such as frontotemporal dementia and corticobasal degeneration. The module most strongly associated with AD pathology and cognitive impairment was the sugar metabolism module. This module was enriched in AD genetic risk factors, and was also highly enriched in microglia and astrocyte protein markers associated with an anti‐inflammatory state, suggesting that the biological functions it represents may serve a protective role in AD. Proteins from the sugar metabolism module were increased in cerebrospinal fluid from asymptomatic AD and AD cases, highlighting their potential as biomarkers of the altered brain network.ConclusionIn this study of >2000 brains and nearly 400 cerebrospinal fluid samples by quantitative proteomics, we identify proteins and biological processes in AD brain that may serve as therapeutic targets and fluid biomarkers for the disease.