Citations

Abstract INTRODUCTION Risk factors associated with sporadic non‐amnestic and early‐onset Alzheimer's disease (AD) remain underexamined. METHODS We investigated a large, clinically heterogeneous, AD cohort for frequencies of established risk factors (hypertension, hypercholesterolemia, diabetes mellitus) alongside novel factors (non–right‐handedness, learning disability, seizures, autoimmune disease). RESULTS Early‐onset AD possessed lower frequencies of established risk factors (hypertension, hypercholesterolemia, diabetes mellitus, all p < 0.001) and higher frequencies of novel factors (non–right‐handedness, learning disability, active seizure, all p < 0.001; remote seizure, p = 0.002; and autoimmune disease, p = 0.007). An age at onset < 70 maximally distinguished novel from typical factors. Principal component analysis loaded novel factors into two components, non–right‐handedness and learning disability versus seizure and autoimmune disease, which combined, resulted in an exponential decrease in age at onset from one factor alone. DISCUSSION Identifying novel factors enriched in early‐onset and non‐amnestic AD introduces new theories of AD susceptibility and phenotypic heterogeneity, with significant implications for disease prediction and treatment. Highlights We identified a suite of novel factors overrepresented in early‐onset and non‐amnestic AD. These factors can be broadly conceptualized as neurodevelopmental (non–right‐handedness and learning disability) and neural environmental (seizure and autoimmunity). The combination of these factors produced exponential decreases in AD age at onset, compared to each alone, supporting a new theoretical framework for understanding AD risk with implications for disease prediction, prevention, and therapeutic intervention.

Abstract 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.

AbstractINTRODUCTIONPlasma amyloid beta42/amyloid beta40 (Aβ42/Aβ40) and phosphorylated tau217 (p‐tau217) identify individuals with primary Alzheimer's disease (AD). They may detect AD co‐pathology in the setting of other primary neurodegenerative diseases, but this has not been systematically studied.METHODSWe compared the clinical, neuroimaging, and neuropathological associations of plasma Aβ42/Aβ40 (mass spectrometry), p‐tau217 (electrochemiluminescence), and neurofilament light ([NfL], single molecule array [Simoa]), as markers of AD co‐pathology, in a sporadic frontotemporal dementia (FTD) cohort (n = 620).RESULTSAβ42/Aβ40 showed no clinicopathological associations. High p‐tau217 was present in amnestic dementia (AmD) presumed to be due to FTD, logopenic primary progressive aphasia (lvPPA), and APOEε4 carriers, and correlated with worse baseline and longitudinal clinical scores, lower hippocampal volumes, and more severe AD co‐pathology (Braak Stage). NfL was elevated in all FTD phenotypes, and correlated with clinical scores and frontotemporal brain volumes.DISCUSSIONPlasma p‐tau217 has clinical, neuroimaging, and neuropathological correlates in sporadic FTD and may identify FTD cases with AD co‐pathology.Highlights Alzheimer's disease (AD) features could be identified with plasma phosphorylated tau217 (p‐tau217) in frontotemporal lobar degeneration (FTLD). Plasma p‐tau217 is a better discriminator of AD co‐pathology and AD‐associated features in FTLD than plasma amyloid beta42/amyloid beta40 (Aβ42/Aβ40) and neurofilament light (NfL). In FTLD, plasma p‐tau217, but not Aβ42/Aβ40 or neurofilament light, has phenotypical, neurocognitive, and neuroimaging correlates suggestive of AD co‐pathology.

AbstractBackgroundIndividuals meeting neuropathological criteria for Alzheimer’s disease (AD) may manifest with atypical clinical syndromes. Past work showed that the neurobiological basis for these differences is related to specific neuronal vulnerabilities for tau pathology. For instance, amnestic cases have a higher burden of neurofibrillary changes in CA1. In contrast, logopenic variant primary progressive aphasia (lvPPA) cases have a higher tau burden in the superior temporal gyrus (STG). Single‐cell technology enables investigations on the molecular basis of differential neuronal vulnerability in AD. Consequently, we delved into the factors that underlie this selective vulnerability by analyzing brain samples from individuals exclusively afflicted with AD but exhibiting diverse clinical manifestations.MethodsnRNA Sequencing using the Chromium Single Cell 3′ (10X Genomics, USA) on nuclei cells extracted from the CA1 sector and posterior STG of postmortem brain tissue of 48 individuals either meeting pathological criteria for AD (A3B3C3; 24 amnestic and eleven lvPPA) and healthy controls (A≤1B≤1C≤1; n = 13) (Table 1, Fig. 1A/B). Bioinformatics analyses were conducted using Cell Ranger and R software. Comparisons between cell subpopulations were conducted with the Wald statistical test, and p‐values < .05 were considered significant.ResultAfter quality control, we recovered more than 250k nuclei with a mean of 2,130 genes per nuclei. Upon cross‐sample alignment and t‐stochastic neighborhood embedding clustering (Fig. 1C), we found 21 excitatory neuronal subpopulations (Exc‐sub) in CA1 and 26 in STG, and 22 and 25 inhibitory neuronal subpopulations (Inh‐sub) in CA1 and STG, respectively; 16 astrocytes subpopulations in both areas and 20 microglia subpopulations in CA1 and 17 in STG (Fig. 2). One STG Exc‐sub, expressing CUX2 and LAMP5 genes showed vulnerability in lvPPA patients. Also, one STG Inh‐sub, expressing the ADARB2 gene, showed vulnerability for all AD patients.ConclusionOur preliminary study identified a vulnerable population of excitatory neurons related to lvPPA. We are conducting validation studies using quantitative pathology to confirm these results. Furthermore, analysis of a higher number of cases is ongoing and will continue to inform on factors associated with neuronal vulnerability.

Abstract The pathophysiological mechanisms driving disease progression of frontotemporal lobar degeneration (FTLD) and corresponding biomarkers are not fully understood. We leveraged aptamer-based proteomics (> 4,000 proteins) to identify dysregulated communities of co-expressed cerebrospinal fluid proteins in 116 adults carrying autosomal dominant FTLD mutations (C9orf72, GRN, MAPT) compared to 39 noncarrier controls. Network analysis identified 31 protein co-expression modules. Proteomic signatures of genetic FTLD clinical severity included increased abundance of RNA splicing (particularly in C9orf72 and GRN) and extracellular matrix (particularly in MAPT) modules, as well as decreased abundance of synaptic/neuronal and autophagy modules. The generalizability of genetic FTLD proteomic signatures was tested and confirmed in independent cohorts of 1) sporadic progressive supranuclear palsy-Richardson syndrome and 2) frontotemporal dementia spectrum syndromes. Network-based proteomics hold promise for identifying replicable molecular pathways in adults living with FTLD. ‘Hub’ proteins driving co-expression of affected modules warrant further attention as candidate biomarkers and therapeutic targets.

AbstractBackgroundIndividuals with neuropathological criteria for Alzheimer’s disease (AD) may manifest with atypical clinical syndromes. Past work showed that the neurobiological basis for these differences is related to specific neuronal vulnerabilities for tau pathology. For instance, amnestic cases have a higher burden of neurofibrillary changes in CA1. In contrast, logopenic variant primary progressive aphasia (lvPPA) cases have a higher tau burden in the superior temporal gyrus (STG). Single‐cell technology enables investigations on the molecular basis of differential neuronal vulnerability in AD. Therefore, we investigated factors underlying selective vulnerability using brain samples from individuals with pure AD with different clinical manifestations.MethodsnRNA Sequencing using the Chromium Single Cell 3′ (10X Genomics, USA) on nuclei cells extracted from the CA1 sector and posterior STG of postmortem brain tissue of 24 individuals either meeting pathological criteria for AD (A3B3C3; 12 amnestic and eight lvPPA) and healthy controls (A≤1B≤1C≤1; n = 4) (Table 1, Fig. 1A/B). Bioinformatics analyses were conducted using Cell Ranger and R software. Comparisons between cell subpopulations were conducted with Wald statistical test, and p‐values < .05 were considered significant.ResultAfter quality control, we recovered 98,180 nuclei with a mean of 2,130 genes per nuclei. Upon cross‐sample alignment and t‐stochastic neighborhood embedding clustering (Fig. 1C), we found 21 excitatory neuronal subpopulations (Exc‐sub) in CA1 and 26 in STG, and 22 and 27 inhibitory neuronal subpopulations (Inh‐sub) in CA1 and STG, respectively; 16 astrocytes subpopulations in both areas and 20 microglia subpopulations in CA1 and 17 in STG (Fig. 2). One STG Exc‐sub, expressing CUX2 and LAMP5 genes showed vulnerability in lvPPA patients. Also, one STG Inh‐sub, expressing the ADARB2 gene, showed vulnerability for all AD patients. Furthermore, two astrocytes subpopulations (one in both areas and one in STG) and three STG microglia subpopulations showed proportional composition changes comparing AD patients and HC.ConclusionOur preliminary study identified a vulnerable population of excitatory neurons related to lvPPA. We are conducting validation studies using quantitative pathology to confirm these results. Furthermore, analysis of a higher number of cases is ongoing and will continue to inform on factors associated with neuronal vulnerability.