Amyloid-positive Individuals Research Articles

White matter hyperintensities contribute to early cortical thinning in addition to tau in aging.

While tau pathology is closely associated with neurodegeneration in Alzheimer's disease (AD), our prior work using multi-modality imaging revealed that mismatch between tau (T) and neurodegeneration (N) may reflect contributions from non-AD processes. The medial temporal lobe (MTL), an early site of AD pathology, is also a common target of co-pathologies such as limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC), often following an anterior-posterior atrophy gradient. Given the susceptibility of MTL to co-pathologies, here we explored T-N mismatch specifically within MTL using plasma ptau 217 and MTL morphometry for identifying vulnerabilities and resilience in cognitively impaired or unimpaired AD patients. We parcellated the MTL into 100 spatially contiguous segments and calculated their T-N mismatch using plasma ptau 217 as a measure for T and thickness as a marker of N. Based on these mismatch profiles, we clustered 447 amyloid-positive individuals from ADNI cohort into data-driven T-N phenotypes. We characterized the T-N phenotypes by examining their cross-sectional and longitudinal atrophy both within the MTL and across the whole brain, as well as cognitive trajectories. This framework was replicated in an independent cohort and finally translated to a real-world clinical sample of 50 patients undergoing anti-amyloid therapy. Clustering identified three T-N phenotypes with different MTL T-N mismatch profiles, atrophy patterns, and cognitive outcomes, despite comparable AD severity. The "canonical" group, characterized by low T-N residuals (N ∼ T), showed AD-like neurodegeneration patterns. The "vulnerable" group, characterized by disproportionately greater neurodegeneration than tau (N > T), showed atrophy primarily in the anterior MTL that extended into temporal-limbic regions, both in cross-sectional and longitudinal analyses. This group also exhibited neurodegeneration that preceded estimated tau onset and experienced faster cognitive decline across multiple domains, aligning with the typical characteristics of mixed LATE-NC with AD. In contrast, the "resilient" group (N < T) showed minimal atrophy and preserved cognitive function. These phenotypes were reproducible in an independent research cohort. Importantly, in a feasibility study applying the model developed from ADNI to a clinical cohort of patients receiving lecanemab, we identified vulnerable individuals with LATE-like atrophy patterns. This highlights its potential utility for identifying individuals with co-pathology in clinical settings. Our findings demonstrate that T-N mismatch within MTL using MRI and plasma biomarkers can reveal AD groups with varying vulnerability/resilience, with the vulnerable group displaying structural and cognitive outcomes suggestive of LATE-NC. This approach offers a cost-effective strategy for clinical trial stratification and precision medicine for AD therapeutics.

Association of microplastics in human cerebrospinal fluid with Alzheimer's disease-related changes.

Alzheimer's disease (AD) progression varies widely among individuals. Identifying factors influencing timing of pathology and clinical progression is crucial for optimizing early intervention trials. To investigate how estimated age at amyloid and tau PET positivity, and the time interval between amyloid and tau PET positivity ("amyloid-tau interval"), relate to symptom onset and clinical progression, and whether APOE- ε4 status and sex modify these associations. Longitudinal observational study. Multicenter study using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). ADNI participants with at least one positive amyloid PET scan (n=792) or at least one positive tau PET scan (n=212) were included. Both cognitively unimpaired and impaired individuals were included and all had information on sex, APOE- ε4 status, and longitudinal cognitive assessments. 18 F-florbetapir or 18 F-florbetaben amyloid PET, 18 F-flortaucipir tau PET, CDR global, CDR-SB. We examined the influence of APOE -ε4 status, sex, and their interaction on the age at biomarker positivity and the amyloid-tau interval. Accelerated Failure Time (AFT) models were used to predict time to symptom onset based on biomarker positivity age and the amyloid-tau interval. Linear mixed-effects (LME) models evaluated differences in the rate of cognitive decline over five years following symptom onset, by biomarker positivity age and amyloid-tau interval duration. Additional models included interaction terms with sex or APOE -ε4 status. APOE- ε,4 carriers and women had earlier amyloid and tau PET positivity ages. APOE- ε,4 carriers, women, and those with older age at amyloid PET positivity had a shorter amyloid-tau interval. An older age at amyloid or tau PET positivity and a shorter amyloid-tau interval predicted earlier symptom onset. An older age at amyloid or tau PET positivity was also associated with slower rate of cognitive decline after symptom onset. The amyloid-tau interval did not influence time until symptom onset after tau PET positivity or rate of cognitive decline. APOE- ε4 and sex influenced the timing of amyloid and tau PET positivity and the amyloid-tau interval, which in turn affected symptom onset and clinical progression. These factors should guide the identification of amyloid-positive individuals at highest risk of rapid AD progression, enabling more efficient selection of participants for clinical trials.

To evaluate the predictive utility of baseline plasma biomarkers and neuropsychological measures in identifying cognitively unimpaired older adults at risk of cognitive and functional decline over five years. The clinical and biological heterogeneity observed in Alzheimer's disease (AD) complicates design of trials and the identification of appropriate participants. Identifying practical tools to define more homogenous subgroups could enhance clinical trial enrichment and improve early detection. We analyzed data from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) trial and its companion Evaluation of Amyloid Risk and Neurodegeneration (LEARN) observational study. The sample included 866 cognitively unimpaired, amyloid-positive individuals from the A4 trial (comprising participants randomized to receive Solanezumab or placebo) and 343 cognitively unimpaired, amyloid-negative individuals from LEARN. Cognitive/functional decline was defined as an increase of ≥0.5 in Clinical Dementia Rating-Global Score (CDR-GS) during a 240-week period. Using multiple logistic regression models, we evaluated the predictive value of demographic variables, APOE4 status, amyloid PET SUVR, plasma P-tau217, and Alzheimer's Disease Cooperative Study-Preclinical Alzheimer's Cognitive Composite (ADCS-PACC) in three groups: A4-Solanezumab, A4-placebo and LEARN. In a sub-study including 656 participants with available data, we assessed the incremental value of additional plasma biomarkers (Aβ42/Aβ40 ratio, GFAP, and NfL). Both plasma P-tau217 and ADCS-PACC significantly improved predictive performance over a base model with demographics and APOE4. The full model combining all predictor variables yielded the highest AUCs across A4 Solanezumab (0.80 ± 0.06), A4 Placebo (0.80 ± 0.06), and LEARN (0.78 ± 0.08). Adding other plasma biomarkers yielded small but consistent improvements in AUC (1-3%). Plasma P-tau217 and ADCS-PACC, individually and in combination, improved prediction of cognitive/functional decline in asymptomatic older adults. Predictive models incorporating these scalable and non-invasive measures improved clinical trial enrichment and earlier identification of at-risk individuals preclinical AD.

This study aims to support early diagnosis of Alzheimer's disease and detection of amyloid accumulation by leveraging the microstructural information available in multi-shell diffusion MRI (dMRI) data, using a vision transformer-based deep learning framework. We present a classification pipeline that employs the Swin Transformer, a hierarchical vision transformer model, on multi-shell dMRI data for the classification of Alzheimer's disease and amyloid presence. Key metrics from DTI and NODDI were extracted and projected onto 2D planes to enable transfer learning with ImageNet-pretrained models. To efficiently adapt the transformer to limited labeled neuroimaging data, we integrated Low-Rank Adaptation. We assessed the framework on diagnostic group prediction (cognitively normal, mild cognitive impairment, Alzheimer's disease dementia) and amyloid status classification. The framework achieved competitive classification results within the scope of multi-shell dMRI-based features, with the best balanced accuracy of 95.2% for distinguishing cognitively normal individuals from those with Alzheimer's disease dementia using NODDI metrics. For amyloid detection, it reached 77.2% balanced accuracy in distinguishing amyloid-positive mild cognitive impairment/Alzheimer's disease dementia subjects from amyloid-negative cognitively normal subjects, and 67.9% for identifying amyloid-positive individuals among cognitively normal subjects. Grad-CAM-based explainability analysis identified clinically relevant brain regions, including the parahippocampal gyrus and hippocampus, as key contributors to model predictions. This study demonstrates the promise of diffusion MRI and transformer-based architectures for early detection of Alzheimer's disease and amyloid pathology, supporting biomarker-driven diagnostics in data-limited biomedical settings.

Cognitive resilience refers to maintaining cognitive function despite Alzheimer's disease (AD) pathophysiology. We analyzed amyloid-positive individuals across clinical stages of AD in two cohorts: the Amsterdam Dementia Cohort (ADC, N=1036) and Alzheimer's Disease Neuroimaging Initiative (ADNI, N=685). Cognitive resilience was conceptualized from a canonical correlation analysis of magnetic resonance imaging and neuropsychological data in each cohort separately. Model validation involved education as a resilience proxy and key genetic factors (apolipoprotein E [APOE] ε4 and APOE ε2) of AD. We explored associations between 83 AD risk loci and cognitive resilience. Resilience was correlated with education (ADC: β=0.144, p<0.001; ADNI: β=0.149, p<0.001) and APOE ε4 (βmeta-analysis=-0.052, p=0.014). Exploratory single nucleotide polymorphism meta-analysis identified potential involvement of genetic variants around genes UNC5CL, USP6NL, and TPCN1 in lower, and genes COX7C and MINDY2 in higher resilience. Our novel resilience approach showed conceptual validity and potential for future discovery of resilience-related genetic variants. ·We define a novel approach to resilience using canonical correlation analysis (CCA). ·Apolipoprotein E ε4 is linked to lower resilience, suggesting increased vulnerability. ·Genetic loci around COX7C and MINDY2 are potentially involved in higher resilience. ·This novel approach may be used for multi-cohort studies such as genome-wide association studies in the future.

The independent contributions of baseline and longitudinal tau positron emission tomography (PET) and magnetic resonance imaging (MRI) to cognitive decline remain unclear. We included n=761 amyloid-positive individuals from the Swedish BioFINDER-2 study with [18F]RO948-tau-PET, 3-Tesla structural-MRI, and cognition (n=322 with longitudinal imaging data). Linear-mixed-models with random-intercepts and -slopes or linear-regressions were adjusted for age, sex, education, diagnosis, and other-imaging-modality. Tau-PET showed stronger associations with cognitive decline than MRI, showing the strongest associations in a neocortical-composite-region with a cognitive composite (β=-0.25±0.02, p<0.001) for baseline and longitudinal tau-PET (β=-0.62±0.05, p<0.001). Baseline tau-PET explained the largest proportion of cognitive decline (54.0%-94.0%), with modest mediation effects for longitudinal tau-PET or MRI pathways (2.0%-15.0%). Simulated reductions of tau-PET-slopes (up to 100%) were associated with marginally altered cognitive trajectories. The strong associations between baseline tau-PET and longitudinal cognition, with marginal contributions of longitudinal tau-PET and MRI, emphasize the importance of baseline tau aggregates for prognostics and treatments in Alzheimer's disease (AD). Baseline and longitudinal regional tau-PET uptake were more closely associated than structural MRI with longitudinal cognitive decline. Baseline tau-PET was a stronger determinant of longitudinal cognitive decline than longitudinal tau-PET. Simulated reductions of tau-PET accumulation showed limited alterations of cognitive trajectories, with potential implications for tau-targeting therapies.

18F-PI-2620 is a newer tau-PET tracer with minimal off-target binding in thechoroid plexus. Defining tau cut-points to differentiate between cognitively unimpaired andimpaired individuals is crucial for both biomarker validation and clinical use, but researchusing18F-PI-2620 is limited. In 675 participants (mean age: 64, 64% Female, 186Hispanic, 209 non-Hispanic Black, and 280 non-Hispanic White) from the Health and Aging BrainStudy-Health Disparities, we used the area under the receiver operating characteristic curve toidentify a region of interest and corresponding cut-point at which18F-PI-2620standardized uptake value ratio best distinguished between amyloid negative cognitivelyunimpaired and amyloid-positive cognitively-impaired individuals. The regional or compositestandardized uptake value ratio that maximized sensitivity and specificity (measured by theYouden index) was selected as the best-performing region of interest and was further evaluatedusing Gaussian mixture modeling. We evaluated the performance of the chosen region of interestand cut-point in the three ethnoracial groups. The best-performing region of interest was themedial temporal composite, with a cut-point of 1.26. This region performed well in Hispanic andnon-Hispanic White subgroups, but not in the non-Hispanic Black subgroup. The data show theutility of this region to identify clinically relevant levels of tau. Future work shouldexplore the relationship of tau to comorbid conditions across ethnic and racial groups.

Depressive/anxiety symptoms are common in subjective cognitive decline (SCD) and may relate to Alzheimer's pathology, potentially modulated by personality characteristics. Depressive/anxiety symptoms were assessed over 4 ± 2 years in 329 SCD (88 amyloid-positive/241 amyloid-negative) using Geriatric Depression Scale-15 (GDS), Center for Epidemiological Studies-Depression (CES-D), and Hospital Anxiety and Depression Scale-Anxiety (HADS-A). Mixed-effects models assessed associations between amyloid status and these symptoms, with neuroticism and somatization as effect-modifiers. Amyloid status was not directly associated with GDS, CES-D or HADS-A. However, neuroticism modified the association between amyloid status and GDS (p<0.05). In lower neuroticism, amyloid positivity was associated with GDS increase (β:0.10 ± 0.08), but not in higher neuroticism (β:-0.04 ± 0.12). Somatization modified the association between amyloid status and CES-D (p<0.05). In lower somatization, amyloid positivity was associated with CES-D increase (β:0.65 ± 0.23), but not in higher somatization (β:-0.12 ± 0.29). Amyloid-positive individuals with lower neuroticism/somatization increased more in depressive symptoms over time, suggesting a preclinical AD-related depressive phenotype.

Background and ObjectivesThe amyloid cascade hypothesis posits that Alzheimer disease (AD) progresses from amyloid deposition to tau deposition, neurodegeneration, and eventually cognitive impairment and is the foundation of the revised criteria of Alzheimer's Association Workgroup 2024 (AA-2024). To account for copathologies and cognitive resilience that affect the penetrance of the AD cascade, AA-2024 introduced a 2-dimensional biological-clinical staging framework. We aimed to estimate the proportion of persons along the AD continuum whose biological and clinical trajectories align with the amyloid cascade.MethodsCross-sectional data of the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort were tested in the 4 × 4 biological/clinical staging matrix adapted from the AA-2024 criteria. Biological stages were defined by amyloid and tau-PET burden: stage A (amyloid positivity, A+), stage B (medial temporal tau, A+/T2MTL+), stage C (moderate neocortical tau, A+/T2MOD+), and stage D (high neocortical tau, A+/T2HIGH+). Clinical stages were cognitively unimpaired (stage 1), subtle cognitive impairment (stage 2), mild cognitive impairment (stage 3), and dementia (stages 4–6). Tau-PET cutoffs were defined through the implementation of 5 distinct methods. Participants were categorized into (1) compliant with the amyloid cascade (matrix diagonal), (2) resilient (advanced biological stage—early clinical stage), and (3) copathologic (early biological stage—advanced clinical stage). Observed distributions were compared with hypothetical scenarios with zero and high amyloid cascade penetrance using the χ2 test, and differences among the 5 methods were tested using the Cochran Q test.ResultsTwo-hundred and fifty-six amyloid-positive individuals (mean age: 72.7 years; 51% female) from the ADNI cohort were considered. The proportion of participants compliant with the amyloid cascade was between 31% (95% CI 25%–37%) and 36% (95% CI 30%–42%) depending on the tau-PET cutoff method. The observed number of individuals compliant with the amyloid cascade was higher than in the zero-penetrance scenario but lower than in the high-penetrance distribution (p < 0.01). The proportion of copathologic (17%–63%) and resilient (6%–52%) individuals varied widely by tau-PET cutoff (p < 0.001).DiscussionOnly approximately one-third of persons with an AA-2024 diagnosis of AD complied with the predictions of the amyloid cascade hypothesis. These results suggest the heterogeneity in how clinical symptoms and pathology are coupled along the AD continuum, which has significant implications for interpreting completed antiamyloid clinical trials and designing future studies.

Females have an increased risk of developing Alzheimer's disease (AD). The innate immune system plays a key role in AD pathology, and sex differences in innate immune responses may contribute to differences in disease risk and progression. This study investigated sex differences in innate immune responses among participants without cerebrospinal fluid (CSF) determined amyloid pathology [A-; cognitively normal (CN), n = 83] and those with amyloid pathology (A+, n = 202), further stratified into preclinical (CN with A+, n = 72) and mild cognitive impairment (MCI with A+, n = 130). Participants were drawn from the Norwegian Dementia Disease Initiation cohort (n = 285). We measured plasma glial fibrillary acidic protein (GFAP) and CSF concentrations of nine innate immune markers: soluble triggering receptor expressed on myeloid cells 2 (sTREM2), monocyte chemoattractant protein 1 (MCP-1), fractalkine, chitinase 3-like 1 (YKL-40), clusterin, interferon gamma (IFN-γ), interleukin-6 (IL-6), IL-10, and IL-18. Linear regression was used, adjusted for multiple comparisons using the false discovery rate. In A+ cases (n = 202, females = 105), females had lower MCP-1 (P < 0.01), IL-6 and IL-18 (both P < 0.05) than males, while no sex differences were observed in A- cases (n = 83, females = 39). Among A+ participants, no sex differences were observed in CN cases (n = 72, females = 37), but females (n = 68) with MCI had lower MCP-1 and IL-6 (both P < 0.05) than males (n = 62) with MCI. Moreover, A+ females exhibited stronger positive associations between sTREM2 and clusterin with CSF total tau (P < 0.001; P < 0.05) and Neurofilament light chain (P < 0.01; P < 0.01) than males. These findings suggest sex-specific differences in innate immune responses, which may contribute to disease progression in amyloid-positive individuals.

Amyloid-beta (Aβ) plaque formation in Alzheimer’s disease (AD) pathology is morphologically diverse. Understanding the association of polymorphic Aβ pathology with AD pathogenesis and progression is critical in light of emerging Aβ-targeting therapies. In this work, functional amyloid microscopy enhanced by deep learning was integrated with mass spectrometry imaging to delineate polymorphic plaques and to identify their associated Aβ make-up. In both sporadic AD (n = 12) and familial AD (n = 6), dense-core plaques showed higher levels of Aβ1-40 and N-terminal pyroglutamated Aβx-42 compared to diffuse plaques and plaques in non-demented, amyloid positive individuals (n = 5). Notably, a distinct dense-core plaque subtype, coarse-grained plaque, was observed in AD but not in non-demented, amyloid positive patients. Coarse-grained plaques were more abundant in early onset AD, showed increased neuritic dystrophy and higher levels of Aβ1-40 and Aβ3pE-40, an Aβ-pattern similar to cerebral amyloid angiopathy. The correlative chemical imaging paradigm presented here allowed to link structural and biochemical characteristics of Aβ plaque polymorphism across various AD etiologies.

Subjective cognitive decline (SCD) is proposed as an indicator of transitional disease stage 2 in the Alzheimer’s disease (AD) continuum. However, molecular and particularly longitudinal fluid biomarker data for this stage are still limited. This study aimed to determine whether blood-based biomarkers in amyloid-positive individuals with SCD (A + SCD) support the notion of stage 2 as a distinct stage between stages 1 and 3 of AD and to identify those at high risk for clinical progression. In a prospective multicenter study (DELCODE) involving 457 participants across the AD continuum, we analyzed plasma phospho-tau 181 (p181) and neurofilament light chain (NfL) and assessed their association with longitudinal cognition, hippocampal atrophy, and AD clinical stage transition. The results showed that baseline plasma p181 levels were elevated and increased more rapidly in A + SCD individuals compared to amyloid-positive cognitively unimpaired (A + CU) individuals (stage 1). NfL levels rose across A + CU, A + SCD, and amyloid-positive mild cognitive impairment (A + MCI, stage 3). In A + SCD, but not in A + CU, higher p181 levels predicted cognitive decline (PACC5) and transition to MCI. In conclusion, plasma p181 provides molecular biomarker evidence supporting A + SCD as a pre-dementia AD stage (stage 2) distinct from A + CU (stage 1) and helps identify individuals at risk for cognitive decline early in the AD continuum.

BackgroundIt remains unclear whether cerebrospinal fluid (CSF) VGF (non-acronymic) is associated with the onset and progression of Alzheimer's disease (AD).ObjectiveTo assess the levels of CSF VGF throughout the AD continuum, and its association with primary AD pathology, cognition, brain atrophy, and brain metabolism.MethodsWe studied a total of 526 individuals including 377 amyloid-positive individuals (76 preclinical AD, 200 prodromal AD, and 101 AD dementia) and 149 amyloid-negative cognitively normal individuals. VGF peptide in CSF was analyzed using mass spectrometry.ResultsWe observed decreased CSF VGF in preclinical, prodromal, and AD dementia individuals than amyloid-negative cognitively normal individuals. Reduced CSF VGF was associated with cognitive decline, hippocampal atrophy, ventricle enlargement, and glucose hypometabolism at baseline, and it predicted a more marked deterioration over time.ConclusionsOur findings support the important contributions of VGF to disease pathogenesis and progression in the early stages of AD. Exploring the biologics modulating VGF might be a promising approach for AD prevention and early treatment.

Vascular endothelial growth factor receptor-1 (FLT1) interactions with amyloid-beta in Alzheimer's disease: A putative biomarker of amyloid-induced vascular damage.

Objectively defined subtle cognitive decline (Obj-SCD) is an emerging classification that may identify individuals at risk for future decline and progression to Alzheimer's disease prior to a diagnosis of mild cognitive impairment (MCI). Growth-associated protein 43 (GAP-43), a cerebrospinal fluid (CSF) marker of synaptic dysfunction, has been shown to relate to an increased risk of converting to dementia, although it is unclear whether GAP-43 alterations may be detected in pre-MCI stages. Therefore, in the present study, we examined CSF GAP-43 levels among individuals with Obj-SCD cross-sectionally and also examined whether baseline GAP-43 predicts future functional decline. Six hundred forty-four participants from the Alzheimer's Disease Neuroimaging Initiative were divided into six groups based on (a) cognitive status (cognitively unimpaired [CU], Obj-SCD, or MCI) and (b) Aβ status (+ or -). The CU- group had lower baseline GAP-43 than all Aβ+ groups, but not the other Aβ- groups. Higher GAP-43 levels were associated with faster decline across the entire sample. When moderation by group was examined, higher GAP-43 at baseline predicted faster functional decline for the Obj-SCD+ and MCI+ groups, compared to the CU- group. Results extend prior work investigating biomarker associations in Obj-SCD to GAP-43 and show that high baseline CSF GAP-43 is associated with a faster rate of functional decline in Aβ+ individuals who are classified as Obj-SCD or MCI. Importantly, our findings further demonstrate that CSF GAP-43 is associated with early and subtle cognitive changes detectable before the onset of MCI. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Imaging studies showed early atrophy of the cholinergic basal forebrain in prodromal sporadic Alzheimer's disease and reduced posterior basal forebrain functional connectivity in amyloid positive individuals with subjective cognitive decline. Similar investigations in familial cases of Alzheimer's disease are still lacking. To test whether presenilin-1 E280A mutation carriers have reduced basal forebrain functional connectivity and whether this is linked to amyloid pathology. This is a cross-sectional study that analyzes baseline functional imaging data. We obtained data from the Colombia cohort Alzheimer's Prevention Initiative Autosomal-Dominant Alzheimer's Disease Trial. We analyzed data from 215 asymptomatic subjects carrying the presenilin-1 E280A mutation [64% female; 147 carriers (M = 35 years), 68 noncarriers (M = 40 years)]. We extracted functional magnetic resonance imaging data using seed-based connectivity analysis to examine the anterior and posterior subdivisions of the basal forebrain. Subsequently, we performed a Bayesian Analysis of Covariance to assess the impact of carrier status on functional connectivity in relation to amyloid positivity. For comparison, we also investigated hippocampus connectivity. We found no effect of carrier status on anterior (Bayesian Factor10 = 1.167) and posterior basal forebrain connectivity (Bayesian Factor10 = 0.033). In carriers, we found no association of amyloid positivity with basal forebrain connectivity. We falsified the hypothesis of basal forebrain connectivity reduction in preclinical mutation carriers with amyloid pathology. If replicated, these findings may not only confirm a discrepancy between familial and sporadic Alzheimer's disease, but also suggest new potential targets for future treatments.

BackgroundCognivue Clarity® is an FDA-cleared computerized cognitive test to screen for cognitive impairment included in the Bio-Hermes Study to test blood-based and digital biomarkers’ ability to screen for mild cognitive impairment (MCI) and Alzheimer's disease (AD). A subset of cognitively normal individuals have amyloid deposition (Preclinical AD) but no current assessment can identify these individuals in the absence of expensive biomarkers.ObjectiveWe examined differences in Cognivue Clarity performance between amyloid positive and amyloid negative individuals and whether Cognivue Clarity could differentiate True Controls (cognitively normal/amyloid negative), Preclinical AD (cognitively normal/amyloid positive), and MCI due to AD (MCI-AD, cognitively impaired/amyloid positive).MethodsCognivue Clarity was administered to all participants in the Bio-Hermes Study who also had amyloid PET and blood-based biomarkers. Performance was compared between biomarker-defined groups: True Controls (n = 297), Preclinical AD (n = 95), and MCI-AD (n = 113).ResultsCognivue Clarity global scores distinguished amyloid positive individuals from amyloid negative individuals (p < 0.001) and differentiated True Controls versus Preclinical AD (p = 0.014) and Preclinical AD versus MCI-AD (p < 0.001). Three subtests [Shape Discrimination (p = 0.004), Visual Salience (p = 0.008), Adaptive Motor Control (p = 0.004)] and the 3-test mean (p < 0.001) differentiated True Controls from Preclinical AD. The 3-test composite correlated with Amyloid PET (r = −0.433) and pTau217 (r = −0.400). The 3-test mean identified Preclinical AD in both White and Black participants.ConclusionsCognivue Clarity, a 10-min computerized battery, screens for individuals with cognitive impairment, characterizes amyloid positive individuals, and identifies Preclinical AD. This has great potential as a cost- and time-effective strategy to screen and enroll in AD prevention trials.

Supplemental Material for Growth-Associated Protein 43 Is Associated With Faster Functional Decline Among Amyloid-Positive Individuals With Objectively Defined Subtle Cognitive Decline and Mild Cognitive Impairment