Alzheimer's Research & Therapy

BackgroundP-glycoprotein (P-gp/ABCB1) is a key efflux transporter that maintains barrier integrity by clearing xenobiotics and toxic metabolites. At the feto-maternal interface, trophoblast-derived extracellular vesicles (CTC-EVs) naturally and transiently transfer functional P-gp to maternal decidual cells, restoring lost and or reduced P-gp function (exofection) to sustain pregnancy homeostasis. A similar loss of P-gp at the blood brain barrier (BBB) contributes to impaired amyloid-{beta} (A{beta}) clearance and neuroinflammation in Alzheimers disease. We investigated whether CTC-EV-mediated exofection could restore P-gp function in human brain endothelial cells (hBECs) and enhance A{beta} clearance under inflammatory and neurodegenerative conditions. MethodsCTC-EVs were isolated and characterized by nanoparticle tracking analysis and western blotting for P-gp and EV markers. Transcriptomic profiling of CTC-EVs identified enrichment of transporter-related genes, including solute carriers and ABC transporters, along with inflammatory mediators. Network analysis revealed coordinated modules linking EV cargo to transporter regulation, endocytosis/trafficking pathways, and inflammatory remodeling processes converging on BBB efflux activity. hBECs were exposed to LPS (500 ng/mL, 48 h) with or without CTC-EVs. P-gp expression was assessed by immunofluorescence (mean fluorescence intensity, MFI) and western blotting, while functional efflux was measured using Calcein-AM assays. A{beta} oligomer transport was evaluated using a transwell hBEC model. In vivo, 3xTg-AD mice received intravenous CTC-EVs (1x10L/day for 5 days), followed by assessment of P-gp expression, A{beta} burden, and neuroinflammatory markers. Pharmacokinetic studies in P-gp knockout mice were conducted to confirm functional transporter recovery. ResultsLPS exposure significantly reduced P-gp expression in hBECs (41.3% decrease in MFI, p=0.0084), which was restored by CTC-EVs (46.7% increase vs. LPS, p=0.0121). Exofection increased P-gp by a 2.1-fold following EV treatment as determined by western blot. Functional assays demonstrated enhanced efflux, with a 38.5% reduction in intracellular Calcein fluorescence (p<0.001). Network-informed mechanisms supported coordinated regulation of transporter and trafficking pathways. CTC-EVs improved A{beta} transport across inflamed hBEC monolayers. In vivo, EV-treated 3xTg-AD mice exhibited increased P-gp expression in the frontal cortex (38.6%) and hippocampus (42.1%), reduced A{beta} plaque burden (27.9%), and decreased inflammatory markers (IL-1{beta} and TNF-, p<0.05). In P-gp knockout mice, EVs reduced brain drug accumulation by 22.4% (p=0.032), confirming restoration of transporter function. ConclusionCTC derived EVs are natural carriers of functional transporter proteins and restore efflux capacity in compromised endothelial barriers. Integration of transcriptomic and network analyses highlights coordinated regulation of transporter, trafficking, and inflammatory pathways underlying exofection. This reproductive biology inspired strategy offers a promising therapeutic approach for enhancing A{beta} clearance and mitigating neuroinflammation in Alzheimers disease.

Understanding the time course of Alzheimer's disease biomarkers of amyloid and tau pathology and their temporal relation to clinical symptoms is key to identifying optimal windows for disease intervention and planning future drug trials. The goal of this work was to determine the extent to which Sampled Iterative Local Approximation (SILA), an algorithm extensively validated for amyloid PET, is capable of modeling longitudinal tau (T) PET trajectories and estimating person-level tau positivity onset ages in two commonly analyzed brain regions and two tracers from two different cohorts. Methods: 385 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI; mean (SD) age = 73.4 (7.3) years) with longitudinal flortaucipir tau PET and 288 participants from the Wisconsin Registry for Alzheimer's Prevention and Wisconsin Alzheimer's Disease Research Center (collectively referred to as WISC; mean (SD) age = 67.4 (6.7) years) with longitudinal MK-6240 tau PET were included in the study. Standard uptake value ratios (SUVRs) in the entorhinal cortex and a meta-temporal ROI were modeled with SILA separately, for each cohort and region. Forward and backward SUVR and T+/- prediction were characterized with ten-fold cross-validation and in-sample validation techniques. Accuracy of estimated T+ onset ages (ETOA) was characterized in T- to T+ converters. Differences in ETOA were tested between APOE-e4 carriers and non-carriers, as well as differences in time T+ between levels of cognitive impairment. Results: SILA was able to accurately estimate retrospective change in tau SUVR in the meta-temporal region regardless of age, sex, APOE-e4 carriage, tau SUVR, and dementia (p >0.05) whereas dementia was associated with model residuals in entorhinal cortex (p [&le;] 0.05; ADNI). In subsets of observed T- to T+ converters, the difference between "observed" and estimated meta-temporal T+ onset age [95% CI] was 0.12 [-0.27, 0.52] years for ADNI and -0.09 [0.93, 0.74] years for WISC. ETOA was significantly earlier, and odds of SILA-estimated T+ status were higher amongst APOE-e4 carriers (p <0.05) and those with dementia (p <0.05). Conclusions: Our results suggest SILA can be used to accurately model longitudinal tau PET trajectories and retrospectively estimate individual T+ onset ages in the meta-temporal region. The accuracy of SILA time estimates in entorhinal cortex worsened amongst those with dementia in ADNI suggesting entorhinal cortex may only be suitable for studying the temporal progression of tau during the preclinical time frame.

Background: Cardiovascular health factors are associated with cognitive decline and risk of dementia, including Alzheimer disease (AD); however, this has been mostly studied in late life. We investigated whether vascular and lifestyle factors are associated with AD plasma and imaging biomarkers in midlife. Methods: We investigated 1,406 participants from the Coronary Artery Risk Development in Young Adults (CARDIA) study with information on vascular and lifestyle factors framed from the American Heart Association (AHA) life's essential 8 (LE8) guidelines for cardiovascular health at early midlife (mean age 45.0 SD 3.6) and AD biomarkers in late midlife (mean age 60 SD 3.5). LE8 was calculated and categorized into poor (0-49), intermediate (50-79), and ideal (80-100) cardiovascular health, based on 8 components including smoking, diet, body mass index (BMI), sleep, fasting glucose, blood pressure, cholesterol, and physical activity. We assessed the AD plasma biomarkers phosphorylated tau 217 (ptau-217) and amyloid beta 42/40 ratio (A{beta}42/40) and the Spatial Pattern of Abnormality for Recognition of Early AD (SPARE-AD), an algorithm that characterizes AD-like brain atrophy on brain MRI. We used linear regression to examine the association between LE8 and log-transformed and standardized AD biomarker measures adjusting for age, sex, race, education, and kidney function. Results: Compared to ideal LE8, intermediate (67.9% of participants) and poor (12.6%) LE8 was associated with lower A {beta}42/40 (adjusted mean difference: -2.37, 95% CI: -2.38 to -2.36 and -2.38, 95% CI: -2.40 to -2.36, respectively). There was no association between the LE8 group and ptau-217 level. Moreover, compared to ideal LE8 participants, those with poor LE8 had higher SPARE-AD atrophy pattern (adjusted mean difference: -0.71, 95% CI: -0.81 to -0.62). Conclusion: These findings indicate that poor cardiovascular health in midlife, as defined by the AHA LE8, is linked to less favorable early AD biomarker profiles, particularly reflecting greater amyloid burden and structural brain changes.

Alzheimer s disease (AD) and other tauopathies are characterized by the hyperphosphorylation of tau (pTau), leading to its aggregation in the brain, a process strongly predictive of neurodegeneration and future cognitive decline. Currently, tau positron emission tomography (PET) is the only validated method for detecting tau aggregates in vivo. However, its high cost, invasiveness, and limited accessibility restrict its use in clinical settings and preclude large-scale screening. Moreover, existing plasma biomarkers that quantify the level of pTau at specific sites (e.g., pTau217) have limited specificity for confirming AD-related tau aggregation, partly due to the heterogeneous and irregular phosphorylation patterns of pTau. Besides, the concentration of pTau is frequently elevated in the context of isolated amyloid-{beta} pathology, which is less strongly associated with cognitive decline in the absence of aggregated tau. There is therefore an urgent need for a reliable and scalable blood-based biomarker of tau pathology. A key mechanism underlying AD tau pathology is the ability of pathologically active pTau (PA pTau) to bind to and seed normal tau, facilitating prion-like propagation of insoluble tau aggregates. Here, we assessed the diagnostic performance of the VeraBIND Tau assay, the first functional assay to detect PA pTau seeding activity in plasma. Seventy-nine cognitively unimpaired (CU) and 66 cognitively impaired older adults underwent blood sampling, cognitive assessment, amyloid-PET or cerebrospinal fluid (CSF) analysis, and [18F]-MK6240 tau-PET imaging. Plasma pTau217 concentrations were quantified using the Lumipulse platform (Fujirebio). The VeraBIND Tau assay isolated PA pTau from plasma and evaluated its ability to bind recombinant normal tau using a tagged-tau chemiluminescent readout. VeraBIND Tau demonstrated 94.2% sensitivity and 96.1% specificity for predicting tau-PET positivity (AUC=0.97). It outperformed plasma pTau217 in CU individuals (PPV=85.9%), regardless of the pTau217 threshold used (maximal PPV of 57.5% using the 0.256pg/mL pTau217 threshold). This higher VeraBIND Tau diagnostic accuracy was driven by early tau-PET stages (Braak-like tau-PET stages 1-3; AUC=0.96 vs. 0.74 for pTau217, p=0.003). Moreover, both cross-sectional values and annual changes in VeraBIND Tau were significantly correlated with cognitive performance and entorhinal tau-PET signal (all absolute Spearman r[&ge;]0.23, p<0.05). These findings highlight the strong potential of VeraBIND Tau as a scalable and accurate screening tool to detect AD tau pathology in the general population. The assay may also help enrich clinical trials with tau-PET positive CU individuals, enhance clinical diagnostic workflows and support monitoring of tau-targeted therapies. Future work should evaluate its utility in optimizing triage and early-intervention strategies.

Early detection of disease progression using clinically-relevant biomarkers in animal models is important for mechanistic studies and for developing therapeutics in neurodegenerative diseases including Alzheimers disease (AD). The preclinical stage of AD, when amyloid-{beta} (A{beta}) starts to accumulate before cognitive decline, provides a critical window for disease modification. In humans, decreases in cerebrospinal fluid (CSF) A{beta}42 and the A{beta}42/A{beta}40 ratio in preclinical AD are considered to reflect the preferential sequestration of aggregation-prone A{beta}42 into {beta}-sheet-rich deposition in the brain, with corresponding changes being detectable in plasma. However, the extent to which these biomarker-pathology relationships are recapitulated in AD model mice remains incompletely defined. Here we show that CSF and plasma A{beta}42 and the A{beta}42/A{beta}40 ratio decline with age in parallel with the progression of {beta}-sheet-rich A{beta} deposition in preclinical 5XFAD mice, one of the most widely used AD mouse models, as assessed through monthly profiling of these biomarkers. Notably, the CSF A{beta}42/A{beta}40 ratio showed a negative correlation with {beta}-sheet-rich A{beta} deposition in the brain, whereas CSF A{beta}40 did not show a comparable association. In addition, the plasma A{beta}42/A{beta}40 ratio showed a positive correlation with the CSF A{beta}42/A{beta}40 ratio, suggesting that the plasma A{beta}42/A{beta}40 ratio may also reflect brain A{beta} deposition in this model. The strength of these correlations differed by sex, suggesting that sex-dependent differences in the A{beta} kinetics in this model may influence how closely fluid biomarkers reflect pathological progression. These findings support the potential utility of fluid A{beta} as a pathology-linked, translatable biomarker in preclinical 5XFAD mice. Highlights- Fluid A{beta} biomarkers are associated with early A{beta} deposition in preclinical 5XFAD mice. - The CSF A{beta}42/A{beta}40 ratio negatively correlates with {beta}-sheet-rich brain A{beta} deposition. - The plasma A{beta}42/A{beta}40 ratio positively correlates with the CSF A{beta}42/A{beta}40 ratio. - Monthly profiling defines fluid A{beta} biomarker dynamics in preclinical 5XFAD mice. - Sex differences may affect biomarker-pathology relationships in these mice.

Background and Aims: Plasma phosphorylated tau 217 (p-tau217), including %p-tau217, has emerged as a robust biomarker of Alzheimer's disease (AD) pathology, with increasing interest in its longitudinal behavior. In "Predicting onset of symptomatic Alzheimer's disease with plasma p-tau217 clocks," Petersen et al. applied disease clock models, Sampled Iterative Local Approximation (SILA) and Temporal Integration of Rate Accumulation (TIRA), to estimate age at plasma %p-tau217 positivity and reported that this measure predicts age at onset of symptomatic AD. We aimed to determine whether this apparent predictive performance reflects biomarker information or arises from structural artifacts in the analysis. Methods: We analyzed digitized data from published figures and decomposed the clock-derived predictor into baseline age and estimated time from %p-tau217 positivity. We quantified shared and unique explained variance between baseline age and the clock-derived predictor using commonality analysis. To further disentangle structural and biomarker contributions, we evaluated a null scenario in which the biomarker-derived timing component was replaced with randomly generated values drawn over the observed range, preserving the predictor distribution while removing biomarker information. Results: The reported predictive performance was largely driven by structural artifacts arising from bounded follow up and constraints among the variables. Restriction to individuals who progressed during limited follow up, together with constraints on the allowable timing of events, induced a strong association between baseline age and age at symptom onset. In ADNI, baseline age alone explained substantially more variance in age at onset than the clock-derived predictors (R2=0.78 vs. 0.337 and 0.470 for TIRA and SILA). The estimated time from %p-tau217 positivity contributed minimal additional information, and randomized predictors yielded comparable performance to baseline age alone (R2=0.79). Conclusion: The apparent predictive ability of plasma %p-tau217 disease clocks is driven largely by structural age relationships rather than independent biomarker signal. The plasma %p-tau217 timing component provided minimal predictive value, and its combination with age obscured these structural dependencies. These findings underscore the need for careful evaluation of constructed predictors and outcomes in longitudinal analyses of disease progression.

Biological staging models are a key tool for assessing the severity of Alzheimer's disease (AD), supporting personalized medicine and playing a critical role in clinical trial design. Recently, researchers have leveraged positron emission tomography (PET) to inform data-driven staging models of brain pathology related to AD. However, most approaches have focused on staging either amyloid or tau progressions separately, while both pathologies constitute defining factors of AD. Here, we aimed to derive a data-driven staging model which encompasses the spatial spread of both amyloid and tau. We assembled a large sample (n=3,293) of individuals with both amyloid and tau PET imaging stemming from 8 neuroimaging studies of AD and aging. We applied unsupervised machine learning to estimate brain areas which showed coordinated pathological accumulation across our sample, and we used these regions to inform a data-driven model for staging amyloid and tau. The resulting six stage model showed two stages of amyloid progression followed by four stages of tau spread, which were associated with cross-sectional and longitudinal assessments of cognitive decline. Comparison of our biological staging model with clinical disease stages recommended by the Alzheimer's Association showed evidence of heterogenous symptom profiles. Replication of results in holdout data demonstrated the generalizability and prognostic value of our staging model. Together, these findings establish a comprehensive and rigorously validated biological staging model that jointly characterizes amyloid and tau progression, advances beyond global or anatomically predefined summaries, and provides a scalable framework for studying disease heterogeneity and progression in AD.

Identifying individuals in the preclinical stages of Alzheimer's disease (AD) is necessary for inclusion into future prevention trials. AD pathology occurs in the brain 20 or more years before diagnosis. In a nested 1:1 matched case-control sample of 426 participants selected from 19,500 members of the EPIC-Oxford cohort, we found that higher blood-based brain-derived and total p-tau 181, 217, and 231, as well as GFAP, were associated with AD over up to 25 years of follow-up (median=19.4, interquartile range 16.8-21.9 years). Of these seven biomarkers, LASSO regression selected brain derived p-tau 217 as the strongest discriminator of AD cases from controls. The AUC for brain derived p-tau 217 accounting for age, sex, and time of blood draw was 0.80, which increased to 0.82, 0.83, 0.84, after further addition of 1) APOE-e4 carrier status, 2) sociodemographic and lifestyle factors, and 3) both, respectively. Blood-based biomarkers, including the novel brain-derived p-tau 217, could identify individuals at-risk of AD two decades pre-diagnosis.

Alzheimers disease (AD) is characterized by early synaptic dysfunction followed by progressive amyloid-{beta} (A{beta}) accumulation, neuroinflammation, and cognitive decline. We previously identified Secreted Frizzled-Related Protein 1 (SFRP1) as a multifactorial contributor to AD pathogenesis and provided initial evidence that its neutralization ameliorates pathological AD-like traits in mice. Here, we evaluate the pharmacodynamics, biodistribution, and therapeutic window of an -SFRP1 monoclonal antibody (-SFRP1) in APP/PS1 mice. Pharmacokinetics and target engagement of -SFRP1 were assessed in different groups of APP/PS1 mice using biotinylated or 89Zr-labelled antibodies, with tissue distribution and -SFRP1 levels quantified by in-house ELISA or PET/CT. Therapeutic efficacy was evaluated by administering -SFRP1 or the SFRP1 inhibitor WAY-316606 at different stages of disease progression via retro-orbital injection, followed by analysis of AD-like pathology using ELISA and immunofluorescence assays followed by quantifications and statistical analysis. Using 89Zr-labelled antibodies, we show that intravenously administered -SFRP1 engages its target systemically and reaches the brain, although at substantially lower levels and with a rapid 24-hour clearance. Treatment with -SFRP1 had no apparent systemic side effects, but its therapeutic efficacy against AD-like brain pathology was strongly dependent on disease stage. While early administration reduced amyloid pathology in previous studies, treatment initiated at intermediate or advanced stages showed minimal benefit at standard doses. Higher antibody doses reduced amyloid burden and dystrophic neurites but were associated with increased mortality with time. Pharmacological inhibition of SFRP1 using a small-molecule inhibitor similarly failed to ameliorate pathology at intermediate stages. Together, these findings demonstrate that SFRP1 remains a relevant therapeutic target in AD, but its effective modulation is constrained by limited brain exposure and a narrow therapeutic window, underscoring the importance of early intervention and prompting the search for improved brain-targeted delivery strategies.

AbstractNeuroinflammation, along with amyloid beta (A{beta}) deposition, phospho-tau (ptau) accumulation, blood-brain barrier (BBB) disruption, and cognitive decline are recognized components of Alzheimers disease (AD). However, the timing and nature of peripheral immune changes across AD biological and clinical stages remain poorly understood. Here we performed mass cytometry profiling of whole blood and cerebrospinal fluid (CSF) immune cells from 351 human samples across two independent clinical cohorts spanning the AD continuum. We identify coordinated peripheral immune signaling signatures that emerge during preclinical stage of AD and precede significant elevation of plasma ptau217, CSF ptau181 and BBB disruption measured by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). AD-enriched immune features, including increased phospho-Akt signaling in nai ve T killer cells and phospho-PLC{gamma}2 signaling in granulocytes, were not observed in patients with Frontotemporal lobar degeneration or treatment-nai ve multiple sclerosis. Furthermore, these immune signaling states could be induced in healthy donor immune cells following exposure to plasma or CSF from individuals with AD, indicating that circulating factors can drive these peripheral immune alterations. Together, our findings demonstrate that dynamic peripheral immune state changes arise early in AD and precede canonical biomarker and vascular changes, highlighting immune signaling pathways as potential targets for early therapeutic intervention. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=187 HEIGHT=200 SRC="FIGDIR/small/716122v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@f5060corg.highwire.dtl.DTLVardef@600ba7org.highwire.dtl.DTLVardef@19d281dorg.highwire.dtl.DTLVardef@b4a36a_HPS_FORMAT_FIGEXP M_FIG Early peripheral immune signaling precedes tau elevation and blood-brain barrier disruption in Alzheimers disease. C_FIG

BackgroundIndividual clinical cognitive assessments (CCA) for Alzheimers disease (AD) provide broad disease stratification but are limited in sensitivity and specificity, requiring integration of multiple CCA for optimal disease staging. Recent work from our lab suggests that neuro-metabolic and vascular dysregulation (MVD) occurs early in AD, prior to clinical symptoms, and may provide higher sensitivity and specificity than CCA alone. In this study, we combined three widely accepted CCA with MVD readouts and developed a multimodal ensemble machine learning approach across the AD spectrum to predict disease stage and grade. MethodsAD subjects (N=372) across the disease spectrum with imaging (PET:18F-FDG, MRI:T1w, T2 FLAIR, ASL) and CCAs (ADAS-Cog, CDR, MoCA) data were analyzed from ADNI. Imaging data were registered to MNI152+, z-scored relative to cognitively normal controls, and processed for MVD. A clinical-set-enrichment analysis (CSEA) was developed to link regional brain changes with CCA scores, map changes to functional categories, project them into a 3D Cartesian space, and model trajectories, thus revealing at-risk and resilient regions. In addition, an ensemble machine-learning approach was utilized for disease stage classification, and a disease grading scheme across the AD spectrum was developed to further stratify within disease stages. FindingsRegional data followed an MVD pattern across AD stages stratified by CSEA scores. Females showed greater stage separation along the CCA axis within each region, indicating faster disease progression. Moreover, progression in at-risk brain regions (e.g., mid- and inf-temporal gyri, amygdala) was associated with longer disease path lengths, whereas progression in resilient brain regions (supramarginal gyrus) was not. Moreover, our classification and grading approach can predict AD stage and grade independent of amyloid-beta and tau with high precision and accuracy. InterpretationA framework was developed to evaluate MVD and CCA variations across the AD spectrum, thereby distinguishing at-risk and resilient brain regions. Distinct disease trajectories were identified, and a new data-driven grading scheme was proposed to highlight the potential for precision medicine and therapeutic evaluation. FundingNIH T32AG071444

Sharp-wave ripple (SWR) oscillations are crucial for memory consolidation and deteriorate in Alzheimers disease (AD). Tau oligomers are suggested to lead to synaptic and neuronal degeneration in AD, but their effects on SWRs are unknown. To study this, we prepared mouse and human hippocampal slices and bath-applied tau oligomer preparations after spontaneous SWR generation. In human slices, acute exposure to tau resulted in decreased ripple duration, whereas in mouse slices it was SWR rate, amplitude, and power that decreased, sparing duration. In a different set of experiments, mouse slices were pre-incubated directly in either tau-ACSF or control-ACSF right after slicing for 2.5-5.5 hours, resulting only in diminished SWR rate. These effects were specific to the presence of {beta}-sheets, as a different tau preparation that lacked {beta}-sheets failed to alter SWRs. This method is therefore suitable to study SWR alterations after short-term exposure to different tau and/or A{beta} species, allows a higher throughput screening of possible therapeutics compared to in vivo animal experiments, and permits direct comparison of SWR alterations in mice and humans.

INTRODUCTIONAlzheimers disease (AD) manifests a specific spatial progression pattern, but its propagation mechanisms remain unclear. METHODSWe employed nine brain connectomes spanning multiple biological levels to investigate the mechanisms underlying cortical atrophy propagation in AD. Individual gray matter atrophy maps were quantified using normative modeling and were then mapped onto the connectomes by assessing the relationship between regional atrophy and the atrophy of neighboring regions defined by each connectome. RESULTSCross-sectionally, node-neighbor relationship was weak in the preclinical stage, suggesting limited influence of connectome architecture. Longitudinally, atrophy became progressively more aligned with the neurotransmitter receptor similarity connectome in individuals with MCI converting to AD dementia and dementia patients. DISCUSSIONOur findings described a stage-dependent shift in cortical atrophy propagation, with neurotransmitter receptor similarity playing an increasing role as AD progresses.

INTRODUCTION: Bilingualism is a proposed cognitive reserve factor that delays symptom onset in Alzheimer's disease (AD), though current evidence lacks biomarker confirmation. This retrospective study examined bilingualism's association with symptom onset across AD clinical stages, including biomarker-confirmed cases. METHODS: Participants from the Sant Pau Memory Unit spanning amnestic mild cognitive impairment (MCI), amnestic dementia, and biomarker-confirmed AD were analyzed, with balanced representation of active and passive Spanish-Catalan bilinguals. Linear regression models evaluated associations between bilingualism and reported age at symptom onset, controlling for education, sex, and disease severity. RESULTS: Active bilingualism was associated with delayed symptom onset in amnestic MCI (2.21 years), amnestic dementia (1.42 years), and biomarker-confirmed AD (1.45 years; ps < .05). Higher education was associated with earlier onset, likely representing healthcare seeking behavior. DISCUSSION: Bilingualism protects against earlier symptom manifestation in MCI and AD, supporting bilingualism as a contributor to cognitive reserve.

Alzheimer's disease (AD) is increasingly recognized to have systemic physiological correlates alongside central neurodegeneration. Here, we explored brain-organ network (BON) connectivity in AD (n=28) and healthy controls (n=23) using time-resolved quasi-dynamic analysis of plateau-phase total-body 18F-tau-PET. We found that AD-related pathophysiology was linked not only to cerebral tau aggregation, but also to altered signal synchronization across the brain-organ network, despite comparable body tracer distribution. Network topology analyses revealed the occipitotemporal cortex and the spinal cord as key nodes in this altered systemic network. Furthermore, exploratory mediation analyses demonstrated that BON dysregulation is cross-sectionally linked to cognitive deficits, with statistical associations observed for both cortical tau burden and imaging markers of impaired glymphatic clearance. This total-body PET study provides first-ever direct evidence repositioning AD as a multi-organ disorganization disease. These findings provide a novel framework for investigating brain-body interactions and systemic vulnerabilities in neurodegenerative disorders.

Background: Social determinants of health (SDOH) are increasingly recognized as contributors to Alzheimer disease (AD) risk, yet the impact of multidimensional social disadvantage early AD-related pathophysiology remains poorly understood. Methods: We studied 1,466 participants from the Coronary Artery Risk Development in Young Adults (CARDIA) cohort with SDOH assessed in early midlife (mean age 40, SD 3.6 years) and plasma AD biomarkers measured 20 years later. A comprehensive SDOH index was constructed from 12 indicators spanning five domains (economic stability, education, neighborhood and physical environment, community and social context, and health care access). We examined associations between SDOH quartile and log-transformed, standardized plasma phosphorylated tau 217 (p-tau217), neurofilament light chain (NfL), and amyloid-lower case Greek beta42/40 (Alower case Greek beta42/40) using linear regression adjusted for age, sex, race, and estimated glomerular filtration rate. Linear trends across SDOH quartile were also evaluated. Results: Participants in the most disadvantaged SDOH quartile had higher p-tau217, higher NfL and lower Alower case Greek beta42/40 level compared with those in the least disadvantaged quartile (p-tau 217: lower case Greek beta = 0.12, 95% CI 0.03-0.21, p = 0.008; NfL: lower case Greek beta = 0.20, 95% CI 0.05-0.35, p = 0.009; lower case Greek beta42/40: lower case Greek beta = -0.15, 95% CI -0.30-0.00, p=0.05). There was also a significant trend across quartile (p-tau 217: p for trend = 0.012; NfL: p for trend= 0.001). Analyses of individual SDOH domains indicated that lower economic stability, poorer health care access, and lower education were associated with higher NfL, and poorer health care access was associated with higher p-tau217. Conclusions: Greater SDOH disadvantage in early midlife was associated with higher levels of plasma AD biomarkers reflecting AD pathology and neurodegeneration decades later. These findings suggest that social disadvantage during midlife may contribute to early AD-related biological changes and highlight potentially modifiable social factors relevant for dementia prevention.

Chronic inflammation is a common feature of aging and is observed across various age-related neurodegenerative diseases, including Alzheimers disease (AD). It has, however, been challenging to develop measurements of brain structure directly linked to peripheral measures of neuroinflammation. This cross-sectional study examined whether plasma levels of markers related to inflammation are associated with diffusion magnetic resonance imaging (dMRI) measures of white matter microstructure: mean diffusivity (MD) and Neurite Orientation Dispersion and Density Imaging (NODDI) free water fraction (FWF) and orientation dispersion index (ODI). Participants included 457 dementia-free individuals (mean age=63.82, SD=7.63). Blood plasma markers related to inflammation included two measures of systemic inflammation, (1) high-sensitivity C-reactive protein (CRP), and (2) a composite of pro-inflammatory cytokines (IL-1, IL-1{beta}, IL-2, IL-6, IL-8, TNF-, TNF-{beta}), as well as (3) glial fibrillary acidic protein (GFAP), a measure of astrocytic activation. Higher cytokine composite levels were associated with higher values of all three measures (FWF, ODI, MD) in cerebral white matter, and with higher ODI in the cerebellar peduncles. Higher CRP levels were associated with higher ODI in cerebral and cerebellar white matter. Associations with GFAP were not significant after adjusting for multiple comparisons. Results were consistent after accounting for plasma biomarkers of AD pathology (p-tau181/A{beta}42). Thus, higher levels of peripheral pro-inflammatory markers are associated with white matter microstructure (higher FWF, ODI, and MD), supporting the view that these dMRI-based metrics are sensitive to inflammatory processes. Additionally, the sensitivity of dMRI-based measures to inflammation may differ by inflammatory marker types.

Twice as many women develop Alzheimers disease (AD) compared to men. Several key aspects, such as genetic risk factors, hormonal vulnerability, social responsibilities, and differences in longevity, contribute to the strong female bias in AD. To assess whether sex differences can be detected during the onset of AD, we examined the amyloid-{beta} (A{beta}) plaque burden--one of the hallmarks of AD--and microglial states in young 5XFAD mouse models of amyloid pathology. We hypothesized that an increase in microglial cell number and phagocytic activity will directly correlate with an elevated A{beta} burden and shape the appearance of compact dense-core plaques in the cortex from 2 to 6 months of age. As expected, no change in microglial density and phenotype was found in A{beta} plaque-free hypothalamus of 5XFAD male and female mice when compared to age-matched wildtype controls. By quantifying the number and coverage of diffuse and dense-core plaques in the cortex, we discovered a pronounced increase in A{beta} plaques and microglial clustering in 4-month-old female 5XFAD compared to male mice. By 6 months, no sex difference in plaque load and microglial density was observed. Our spatiotemporal characterization of microglial Clec7a/Dectin-1 and CD68 expression revealed sex differences in the upregulation of these phagocytic markers in plaque-proximal microglia. In 2-months-old males, greater phagolysosomal activity around diffuse plaques may benefit A{beta} clearance. However, in females, the lower initial microglial reactivity and subsequent rise in Dectin-1-driven phagocytic activity may have led to the increase in dense-core plaques at 4 months. Our results suggest that during early amyloidosis, sex differences in CD68-associated lysosomal activity and microglia-driven plaque compaction may cause disproportionate AD risk and severity that is compounded by other exacerbating factors during aging. Taken together, sex-specific targeting of microglial proliferation and phagocytic activity may be a promising intervention in presymptomatic patients with known AD risks.

BackgroundAlzheimers disease (AD) causes progressive decline in language and cognition. Automated speech analysis has emerged as a promising screening tool, yet clinical data scarcity limits progress. To address this, we generated a large-scale simulated speech dataset to model linguistic and acoustic deterioration across cognitive stages, Control, Mild Cognitive Impairment (MCI), and AD. MethodsUsing Monte Carlo simulations, we emulated the Pitt DementiaBank "Cookie Theft" narratives. Acoustic features (speech rate, pause duration, jitter, shimmer) and linguistic features (type-token ratio, unique-word count, filler usage) were synthetically sampled from real-world DementiaBank distributions. We trained an XGBoost classifier to distinguish diagnostic groups, and applied SHAP (Shapley Additive exPlanations) to assess feature importance. ResultsThe model achieved high discriminative performance (AUC {approx} 0.94; accuracy {approx} 85%). Compared to controls, simulated MCI and AD groups showed progressive declines in fluency and lexical diversity, and increases in disfluencies and voice instability. SHAP analysis revealed that key predictors included reduced type-token ratio, higher pause and filler rates, and elevated jitter/shimmer. Classification was most accurate for Control vs. AD; MCI misclassifications highlighted intermediate profiles. InterpretationOur framework, FMN (Forget Me Not), captures clinically relevant speech changes using simulated data, offering an explainable and scalable approach for cognitive screening. While not a substitute for real datasets, FMN validates a pipeline that mirrors known AD markers and can guide future real-world deployments. External validation remains a key next step for translational impact.

BACKGROUND: Increasing evidence suggests that accurate prediction of Alzheimer disease (AD) symptom onset requires more than amyloid- and tau-centric biomarkers such as cerebrospinal fluid (CSF) A{beta}42/40, total tau and p-tau181 and plasma p-tau217. Autosomal dominant AD (ADAD), caused by pathogenic PSEN1, PSEN2 and APP mutations with predictable age at symptom onset, presents a unique opportunity to characterize the chronological changes in proteins beyond amyloid and tau and clarify them as early biomarkers of disease onset or as biomarkers related to disease staging and progression monitoring. METHODS: We measured 972 CSF samples corresponding to 484 participants of the Dominantly Inherited Alzheimer Disease Network (DIAN) using the NULISASeq 120 CNS Disease Panel. We first benchmarked the technology against gold-standard measurements followed by the identification of proteins that were differentially abundant in relation to mutation status and symptomatology. Next, we determined the chronological emergence of protein changes in relation to the estimated years to onset (EYO). Finally, we assessed whether specific protein measures improved the prediction of EYO in the ADAD. FINDINGS: NULISA measurements were comparable to those previously published. We demonstrated that known early alterations in CSF amyloid and tau were followed by inflammatory and neurodegenerative responses suggesting that clinical manifestation of AD happens before the inflammatory processes is fully developed. Finally, we found a multi-protein composite approach for predicting EYO that outperformed single biomarker values. INTERPRETATION: Our results suggest that the main CSF proteomic landscape changes in ADAD are due to the presence of a pathogenic mutation and occur prior to symptom onset. Improved performance of multi-protein composite to predict EYO compared to single biomarker values highlights the added value of multiplex proteomic signatures for biomarker panel development. FUNDING: National Institute on Aging, Alzheimers Association, German Center for Neurodegenerative Diseases, Raul Carrea Institute for Neurological Research, Japan Agency for Medical Research and Development, Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea, Spanish Institute of Health Carlos III.