INTRODUCTION: Alzheimer's disease (AD) prevention trials have multiple steps to identify cognitively unimpaired individuals with AD biomarker evidence. Cognitive/functional screening tests may be biased in ethnoracial minorities, impacting trial eligibility. METHODS: A total of 6669 participants screened for the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) study were grouped by ethnoracial background and testing language. Ethnoracial/language differences in ineligibility reason, cognitive/functional test performance, and amyloid positivity rates were examined. RESULTS: Ethnoracial minorities were least likely to meet eligibility criteria. Patterns of incorrect Mini-Mental State Examination items and impaired Clinical Dementia Rating functional domains differed between ethnoracial/language groups, suggesting potential test biases. The Free and Cued Selective Reminding Test yielded more similar exclusion rates across groups than Logical Memory. Cognitive/functional screening biases may impact subsequent biomarker screening as amyloid positivity rates were lowest in ethnoracial minorities. DISCUSSION: Biases in cognitive/functional screening tests may be contributing to disproportionate exclusion of ethnoracial minorities in AD clinical trials.

Ten years after the original publication, the Centiloid framework is now broadly used to harmonize amyloid-PET quantification, facilitate data sharing and comparison across cohorts, and even assist visual interpretation in clinical settings. We evaluated the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds across cohorts. We gathered data from publicly available cohorts and reached out to investigators across the world to collect cross-sectional Centiloids, demographic and clinical information, and visual read data. Gaussian mixture models (GMM, k=2) were fitted to Centiloid values for each cohort and cutoffs were calculated as mean + 2SD of the lower Gaussian. When visual reads were available, we determined Centiloid cutoffs that maximized correspondence with visual reads (Cohen’s kappa). Data was combined across cohorts using random effects meta-analyses. As of January 2025, we included 37 cohorts ( n  = 41,678 participants) with heterogeneous pipelines, radiotracers, and clinical and demographic characteristics (Table-1). The low Gaussian peaks ranged from -9 to 10CL; the meta-analysis identified a common peak at 1CL. The second peaks were more heterogeneous (range=38-102CL; meta-analysis outcome=64CL). Across cohorts, the proportion of cognitively unimpaired versus impaired participants impacted the position of both peaks, with better separation in cohorts enriched in impaired individuals (Figure-1C). The meta-analysis indicated a GMM-based cutoff of 19CL (95%CI: 16-21CL, Figure-1B); subgroup analyses showed no evidence of significant effect between single versus multicenter settings (17 versus 20CL, p  = 0.30), MRI-based or PET-only processing (18 versus 19CL, p  = 0.88), and no evidence of difference across radiotracers (Flutemetamol: 16CL; PIB: 17CL, Flutafuranol: 18CL, Florbetaben: 19CL, Florbetapir: 20CL, p  = 0.78). In a subset of 29,496 participants with visual reads available, binary visual reads corresponded well to Centiloids (common kappa=0.86, Figure-2A). The visual read-based cutoff of 24CL (95%CI: 21-27CL, Figure-2B) maximized correspondence between visual read and quantification and was slightly higher than the GMM-based cutoff. All meta-analysis models showed high non-random heterogeneity (I 2 >80%) across studies, suggesting non-random differences in peaks and cutoffs. Meta-analysis-based cutoffs align well with thresholds from the existing literature. High heterogeneity among studies underscores the need to investigate contributing factors, raising concerns about applying common cutoffs.

Abstract Background Biological Staging for Alzheimer’s disease (AD) in clinically unimpaired (CU) individuals is critical for early detection efforts. In this study, we evaluated whether Core 1 biomarkers (plasma p-tau217 and amyloid-PET) within Biological Stage A, the earliest biological stage of AD, predict progression of downstream biomarkers and cognition. Methods We used baseline plasma p-tau217 and amyloid-PET, and longitudinal tau-PET, atrophy, and cognition data from the recently completed Anti-Amyloid Treatment in Asymptomatic Alzheimer’s (A4) Study. PET data were used to identify participants within AD Biological Stage A (amyloid-PET positive and medial temporal tau-PET negative). Within these Stage A participants, linear mixed effects models were used to examine associations between baseline levels of plasma p-tau217 and amyloid-PET burden with longitudinal regional tau-PET, atrophy, and cognition. We additionally evaluated whether p-tau217 and amyloid-PET burden within this group were associated with higher risk of progression to Biological Stage B+ (tau-PET positive in the medial temporal lobe). In our statistical models, we included covariates for age, sex, and APOE4 carriage. Results Of 335 A4 participants with complete biomarker data, 222 were identified as being in Biological Stage A. Among Biological Stage A CU, baseline plasma p-tau217 and amyloid-PET burden were associated with faster tau-PET accumulation and atrophy in AD-relevant regions (mean [SD] follow-up time for tau-PET: 4.2 [2.1] years and MRI: 4.2 [1.9] years), as well as faster cognitive decline (mean [SD] follow-up time for PACC: 5.7 [1.6] years) (all p < 0.05). Plasma p-tau217 and amyloid-PET burden were also associated with higher risk of progression to Biological Stage B+. Discussion In CU individuals in the initial stage of AD (Biological Stage A), early changing AD biomarkers provide prognostic information of downstream markers of disease. Evaluation of the utility of these measures in a real-world setting is warranted. Trial registration The A4 study was submitted for registration to clinicaltrials.gov on December 6th, 2013. The study is registered with ID NCT02008357. Screening and data collection for the study began in April 2014.

Approximately 10% of clinically unimpaired individuals with abnormal amyloid (A+; preclinical Alzheimer's disease) have "divergent" cortical tau pathology (A+TCortical+), defined as greater than expected tau in cortical regions relative to medial temporal lobe and/or cortical asymmetry on tau PET in addition to or instead of traditional medial temporal lobe tau burden. Although these A+TCortical+ individuals have subtle cognitive deficits at baseline, the longitudinal imaging and clinical outcomes are unknown. We aimed to characterize longitudinal trajectories of A+TCortical+ individuals compared to other biomarker-defined clinically unimpaired groups given that identifying those at highest risk for decline is critical for informing prevention trials and understanding early disease mechanisms. In this longitudinal study, we examined tau PET, MRI, cognitive, and functional data from 395 clinically unimpaired participants, ages 65 to 85 years, enrolled in the Anti-Amyloid Treatment in Asymptomatic AD (A4) Study. Participants had 2-5 flortaucipir scans over a mean (standard deviation) follow-up period of 4.7 (1.6) years. Change in regional and voxelwise tau patterns, atrophy, cognition, and functioning were examined. Longitudinal trajectories from A+TCortical+ (n=34) were compared to preclinical Alzheimer's disease with elevated tau PET signal in medial temporal lobe only (A+TMTL+, n=102), preclinical Alzheimer's disease without significant tau (A+TMTL-, n=210), and those without amyloid or tau (A-TMTL-, n=49). Cortical tau accumulation was fastest in A+TCortical+ (0.018-0.034 standardized uptake value ratios per year), whereas medial temporal lobe tau accumulation was comparable across A+TCortical+, A+TMTL+, and A+TMTL- groups (0.010-0.013 standardized uptake value ratios per year). Tau continued to accumulate in affected regions and contralateral homotopic regions in A+TCortical+ participants with asymmetrical tau at baseline such that asymmetrical patterns were maintained over time. Younger A+TCortical+ participants had an especially fast cortical accumulation rate. The A+TCortical+ group showed significantly greater neurodegeneration and faster clinical decline (Clinical Dementia Rating Scale Sum of Boxes = 0.610 points per year; Mini-Mental State Examination = -0.780 points per year) than all other biomarker-defined subgroups (Clinical Dementia Rating Scale Sum of Boxes = 0.048-0.182 points per year; Mini-Mental State Examination = -0.189-0.006 points per year). In summary, individuals with divergent cortical tau patterns continue to accumulate cortical tau at a faster rate, show greater neurodegeneration, and have faster cognitive and functional decline than other preclinical Alzheimer's disease subgroups. Clinical trials and research examining tau progression and clinical decline in preclinical Alzheimer's disease without subtyping may be disproportionately influenced by this small, high-risk subgroup.

INTRODUCTION:α-Synuclein is the hallmark pathology of Parkinson's disease and dementia with Lewy bodies, described together as Lewy body disease (LBD). We investigated effects of α-syn biomarker positivity in clinically unimpaired (CU) individuals. METHODS:We assessed α-syn status (α-syn ±) in 269 CU individuals using a cerebrospinal fluid (CSF) seed amplification assay (SAA). Fifty-six participants with AD and 85 LBD spectrum participants were included for comparison. We compared α-syn SAA results with demographics, fluid biomarkers, cognitive performance, and clinical measures. RESULTS:α -Syn positivity was detected in 9% of CU individuals, a lower rate than in clinically impaired participants with AD (16%) and LBD diagnoses (81%). Compared to α-syn-, α-syn+ CU individuals were older, showed lower synaptic integrity, performed worse on tests of executive function and working memory, and reported more LBD-related non-motor symptoms. DISCUSSION:Further work is needed to understand the timeline of neural and clinical changes in α-syn+ CU individuals and heterogeneity in disease progression.

Interest in acoustic voice features as digital biomarkers of underlying Alzheimer's disease (AD) has been increasing. However, lacking confirmation of AD specificity and reference values or normative information, particularly in relation to AD-specific biomarkers, greatly limits the ability to determine measurement thresholds that are clinically meaningful. We present preliminary normative values of acoustic voice features for those who are positron emission tomography (PET) beta amyloid positive (Aß+) and negative (Aß-). This study included 268 cognitively unimpaired participants (mean age 57.2 ± 9.9 years; 50.4% female) from the Framingham Heart Study Brain Aging Program who had voice recordings of neuropsychological assessment obtained within one year before amyloid PET imaging. Sixty-five acoustic features (i.e., prosodic, spectral, and sound quality voice features) were extracted from recordings during the Wechsler Memory Scale Logical Memory Delayed recall tests using open-source Speech and Music Interpretation by Large-space Extraction (OpenSMILE). Reference values were established at the 2.5th, 25th, 50th, 75th, and 97.5th percentiles for each acoustic feature within the entire sample, amyloid-positive (Aß+) and amyloid-negative (Aß-) groups. Differences between the Aß+ and Aß- groups were evaluated using Mann-Whitney U tests. Of the 268 participants, 30 (11%) were Aß+. Reference values for all 65 acoustic features were established across all percentile thresholds within the whole sample, the Aß+ and Aß- groups (see Table). Four acoustic features differed between the Aß+ and Aß- groups: voicingFinalUnclipped ( P  = 0.03), pcm_fftMag_spectralKurtosis ( P  = 0.04), MFCC[5] ( P  = 0.02), and MFCC[10] ( P  = 0.03). Three of them have higher median values in Aß+ group. As a sound quality measure, VoicingFinalUnclipped indicates the voicing probability of the final fundamental frequency candidate without zero-clipping. The pcm_fftMag_spectralKurtosis represents magnitude of spectral kurtosis. MFCCs reflect the power spectrum of a sound and are mathematical representations of essential human speech characteristics. These results suggest acoustic features may be an effective marker for preclinical AD screening of older adults who are Aß+. Future studies should stratify based on biomarker status to refine reference values and expand doing so with more diverse populations.

Amyloid-β (Aβ) accumulation is a continuous process central to pathological aging that begins decades before cognitive impairment emerges. While subthreshold Aβ levels have been linked to future decline in cognitive control, the neural mechanisms connecting this early accumulation to its neurocognitive impact are poorly understood. Brain circuit dynamics, which are essential for cognitive function, may offer a sensitive lens into these initial pathological changes. Here, we tested whether brain state dynamics could serve as sensitive markers for cognitive impairment at an early stage of Aβ burden. Using the Bayesian Switching Dynamic System (BSDS) model, we identified 4 distinct latent brain states from high-temporal-resolution (800 ms) fMRI data acquired from 116 older adults, including 72 cognitively normal (CN) individuals and 44 with mild cognitive impairment (MCI), during an N-back working-memory task. Adopting a dimensional approach, we examined how latent brain state dynamics relate to early amyloid burden, cognitive performance, and clinical symptoms. While Aβ levels failed to differentiate clinical groups or predict clinical symptoms and task performance, the dynamics of latent brain states proved highly sensitive to both early Aβ accumulation and cognition. Canonical correlation analysis revealed a significant relationship between brain state dynamics and early Aβ burden. Furthermore, the temporal properties of brain states were significantly predictive of working memory performance in CN individuals, a relationship that was selectively disrupted in the MCI group. The features of brain dynamics can also successfully predict cognitive impairment. Our findings establish brain state dynamics as sensitive neural markers of initial Aβ accumulation and early cognitive impairment, offering a new framework for developing predictive models to identify individuals at risk for future cognitive decline.

INTRODUCTION:We standardized positron emission tomography (PET) data across multiple cohorts and tracers to characterize the frequency of amyloid and tau PET severity along the clinical continuum. METHODS:Clinical stage was defined using cohort-specific criteria and included cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia. Amyloid severity was staged using Centiloids (CL). Tau severity was staged using a hierarchical Braak-based schema. The cumulative probabilities of PET-based stages were estimated using ordinal logistic regressions. RESULTS:Among 10,396 individuals (mean [standard deviation] age: 71.9 [7.1] years), amyloid levels ≥ 25 CL increased with age among CU and MCI, while amyloid levels ≥ 100 CL were most common in dementia. In 3295 with tau PET, tau severity increased with amyloid and clinical stage and showed complex associations with age. Within each clinical stage, the full spectrum of amyloid and tau PET severity was observed. DISCUSSION:PET-based staging revealed heterogeneous amyloid and tau burden along the clinical continuum. HIGHLIGHTS:PET-based staging is feasible across multiple cohorts and PET tracers. There is heterogeneity in amyloid and tau severity across the clinical spectrum. The frequency of amyloid and tau PET severity increased with clinical severity. The likelihood of tau PET severity differed by age, amyloid, and clinical severity.

Multiple proteinopathies commonly coexist in neurodegenerative diseases, making it essential to evaluate plasma biomarker performance in these complex diseases. While plasma biomarkers accurately detect amyloid-β pathology in Alzheimer's disease (AD), their performance is unknown in neuronal synuclein disease (NSD). We aimed to determine the accuracy of plasma pTau217, pTau181, Aβ42/40, GFAP, and NfL to detect amyloid-β in NSD, then establish and validate cut points for the most promising marker. We included 253 participants (180 discovery; 73 validation). In the discovery cohort, NSD status was defined by CSF α-synuclein seed amplification assay and amyloid-β status by CSF Aβ42/40. Participants included individuals with clinical Lewy body disease (LBD), AD, and cognitively unimpaired. Validation cohorts consisted of clinically diagnosed LBD participants. In the discovery cohort, plasma pTau217, pTau181, Aβ42/40, and GFAP significantly differed by amyloid-β status regardless of NSD status, while NfL was highest in NSD+/Aβ+ participants. Among all biomarkers, plasma pTau217 showed the best diagnostic performance (AUC = 0.92, 95% CI = 0.81-0.98). Applying plasma pTau217 cut points to pre-screen clinically diagnosed LBD participants reduced the need for confirmatory amyloid-β PET or CSF in 41-56%. These findings support plasma pTau217 as a minimally-invasive tool for identifying pathological amyloid-β in neuronal synucleinopathies with mixed Alzheimer's disease pathology.

Decline in episodic memory and proper name retrieval are common in aging and may be linked to early Alzheimer’s pathology in medial and ventral temporal cortex. We investigated associations between regional tau PET, associative memory, and proper name retrieval in a normal aging cohort. Participants were 59 cognitively unimpaired older adults (mean age = 75.97 ± 6.04 years, 61% female) from the Stanford Aging and Memory Study (SAMS). Participants completed a word‐picture (famous face or place) associative memory task concurrent with fMRI and a post‐scan cued‐recall test for word‐image associations. Proper name recall for face and place stimuli from the memory test was assessed on a separate visit 3.6 ± 3.82 months following the associative memory paradigm. Regional Tau accumulation was measured using 18F‐PI2620 PET, and standardized uptake value ratios (SUVRs) were extracted from the entorhinal cortex (ERC) and ventral temporal cortex (VTC; comprised of parahippocampal, inferior temporal, and fusiform gyrus). Linear and logistic mixed‐effects models assessed the associations between name recall, associative memory and tau PET controlling for age, sex, education, category, and random intercepts for subject. Regional Tau in ERC (β = ‐0.52, p < .01) and VTC (β = ‐0.68, p < .01) was negatively associated with naming scores, with a stronger association for face stimuli (Tau x Category: p = 0.02; Figure 1). ERC Tau was negatively related to associative d’ (in‐scan category memory) (β = ‐1.52, p = 0.037; Figure 2). Within individuals, item‐level analyses revealed a positive association between proper name recall and post‐scan test word‐image pair cued‐recall, with a stronger association observed for face stimuli (β = 1.2, p < .01; Figure 3A). Across individuals, naming score was positively associated with both associative d’ (β = 0.97, p = 0.028; Figure 3B) and word‐image pair recall (β = 0.28, p < 0.01; Figure 3C). These findings suggest early tau burden is linked to impairments in episodic memory and proper name retrieval in aging. Furthermore, proper name retrieval is positively related to associative memory both within and across individuals, suggesting an influence of semantic knowledge on episodic memory.

Importance:Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. Objective:To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. Data Sources:PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Study Selection:Studies were included if they provided Centiloids, radiotracer, age, and sex. Data Extraction and Synthesis:Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures:Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. Results:This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I2 = 80%). Conclusions and Relevance:In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.

Sex, education and race/ethnicity are all associated with risk of Alzheimer's disease dementia. Here, we assess the effects of self-reported sex, educational attainment and race/ethnicity on amyloid-positivity, and tau-PET-positivity in 12,048 (7,394 cognitively unimpaired [CU], 2,177 MCI, and 2,477 dementia) individuals from 42 cohorts worldwide. Logistic generalized estimating equations were used to estimate frequency of amyloid-positivity (using cohort-specific thresholds for amyloid-PET [84%] or CSF) and tau-PET-positivity (cohort-specific thresholds of 2SD above mean temporal uptake in amyloid-negative controls). We assessed: i) sex and APOEε4 ( N  = 10,098) associations, to complement earlier findings of a higher frequency of tau-positivity in females, ii) effects of lower/higher education ( N  = 10,970; cohort-specific median-split), and iii) effects of race/ethnicity (non-Hispanic White [hereafter: White], N  = 4880; Asian, N  = 116; Black or African-American [hereafter: Black], N  = 353; Hispanic, N  = 356, only from Northern-American cohorts). Outcomes were frequency of amyloid-positivity in CU individuals only, and tau-PET-positivity in both amyloid-positive (AB+) CU and cognitively impaired (CI, i.e. MCI and dementia) individuals. Interaction effects on the relationship between age and amyloid/tau-positivity were assessed and only retained in the models when significant. Female sex was associated with an APOEε4 -independent increased frequency of amyloid-positivity (β=0.51[0.22], p  = 0.02) in CU and increase of tau-positivity in both AB+CU (β=0.27[0.08]) and AB+CI (β=0.37[0.08], both p  <0.01). Remarkably, tau-positivity frequencies of female APOEε4 non-carriers were equivalent to male APOEε4 carriers in AB+CI (Figure 1). No significant sex* APOE interactions were observed. In CU, higher education was associated with lower amyloid-positivity frequency (β=-0.12[0.05], p  = 0.02). In contrast, among AB+CU, there was an age*education interaction effect that indicated more pronounced age effects on tau-positivity in individuals with higher education (age*education:β interaction =0.03[0.01], p  <0.01). There were no education effects in AB+CI (Figure 2). In CU, an age*race/ethnicity interaction effect was observed across all non-White groups compared to White (Hispanic:β interaction =-0.05[0.01], p  <0.01; Black:-0.04[0.01], p  <0.01; Asian:-0.02[0.01], p  = 0.04). This suggests that the impact of age on amyloid-positivity was less pronounced in non-White groups. Furthermore, in AB+CI, Hispanic ethnicity was related to higher tau-positivity frequency than White (β=0.51[0.22], p  = 0.02; Figure 3). In this multi-center initiative comprised of clinical and community-based cohorts, we observed that self-reported sex, educational attainment and race/ethnicity were related to positivity-frequencies of Alzheimer's disease pathology.

BACKGROUND:Speech features (e.g., between-utterance pause duration, speech rate) derived from Logical Memory Delay Recall (LMd) tests were shown to be associated with early tau burden. Various software tools can generate these features but may use different methods. We aim to validate the robustness of speech features by comparing analogous features generated by two software tools and assessing their associations with tau pathology. METHOD:We analyzed data from Framingham Heart Study participants who completed amyloid and tau PET imaging within a year of their LMd test. Five speech features were generated using ki:elements' SIGMA platform and the CLAN software. Ki:elements' tool derived three features (duration of utterances, duration of between-utterance pauses, number of between-utterance pauses) fully automatically from voice recordings. Other Ki:elements features and all CLAN features were derived from manual transcription. Correlations between ki:elements and CLAN features were assessed by Spearman's correlation coefficients. Associations between speech features and tau standardized uptake value ratio (SUVR) in five brain regions were examined using multiple linear regression, adjusting for age, sex, education, and amyloid status. RESULT:Data from 237 participants (mean age: 54.6±8.7 years; 51.1% female) were analyzed (Table 1). All pairs of speech features were correlated (p <0.001, Table 2). They also demonstrated compatible patterns in their associations with tau SUVR, showing consistency in the direction of association across all cases and in significance levels in most cases (Table 3). In particular, longer between-utterance pause duration was associated with higher tau SUVR in entorhinal (Ki:elements: beta=1.93, p = 0.03;CLAN: beta=2.74, p = 0.002), inferior temporal (IT) (Ki:elements: beta=2.34, p = 0.03; CLAN: beta=2.34, p = 0.03), and inferior parietal (IP) (Ki:elements: beta=3.45, p <0.001; CLAN: beta=3.23, p <0.001) regions. More words per second was associated with reduced tau SUVR in entorhinal (Ki:elements: beta=-2.18, p = 0.02; CLAN: beta=-2.74, p = 0.002) and IT (Ki:elements: beta=-3.10, p = 0.006; CLAN: beta=-2.51, p = 0.02) regions. CONCLUSION:Simple speech features (including fully automated ones) generated using two methods exhibited compatible patterns in their associations with early tau burden. Other automated linguistic and semantic features will be further investigated. With continued validation, automated speech features have the potential to offer a scalable approach with limited loss of findings relative to manual transcriptions.

It is increasingly clear that delaying the onset of Alzheimer’s disease (AD) dementia by several years can meaningfully lower its prevalence. The goal of the present study is to examine the relationship between lifestyle activities and cognition function as well as cerebrospinal fluid (CSF) biomarkers of AD to determine whether these activities can serve as protective factors for AD resistance and resilience. 173 cognitively normal older individuals (mean ± SD, 69 ± 6.4 years) were recruited to the Stanford Aging and Memory Study (SAMS) and completed the Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire regarding current social, cognitive, and physical activity (Table 1). They also underwent APOE genetic testing and a detailed neuropsychological evaluation. The following cognitive domains were evaluated after conversion to z-scores: global cognition (cognitive composite), executive function, working memory, attention, episodic memory, visuospatial function, and language (see Table 2 for definitions). 127 participants completed lumbar punctures, and levels of Aβ-40, Aβ-42, p-tau181, and total tau were measured in the CSF. Cross-sectional regression models included age, sex, years of education, and APOE status as co-variates. Benjamini-Hochberg corrections for multiple hypotheses were completed. There was a significant association between social activity (frequency/week) and global cognition (β = 0.20, p = 0.03), executive function (β = 0.15, p<0.05), and working memory (β = 0.26, p = 0.01) but not episodic memory, visuospatial function, or language function. There was also a significant association with attention prior to correction for multiple hypotheses (β = 0.17, p = 0.04) but not afterward (Table 2). Additionally, there was a significant association between cognitive activity (hours/week) and global cognition (β = 0.19, p = 0.03) as well as executive function (β = 0.25, p = 0.007) but not with other cognitive domains tested (Table 3). There was no association between light or moderate caloric expenditure and cognitive measures. There was also no significant relationship between CSF biomarkers and levels of social, cognitive, and physical activity. In a well-characterized cohort of cognitively normal older adults, higher levels of social and cognitive activity were associated with higher cognitive scores on tasks of executive function but not episodic memory. The mechanism mediating this relationship appears to be independent of both Aβ and tau burden.

Lewy body disease (LBD) often co-occurs with Alzheimer’s disease neuropathological change (ADNC), which can be detected using plasma pTau181 and pTau217. Few studies have investigated these biomarkers in LBD, nor have studies investigated plasma pTau217 in Parkinson’s disease (PD) cognitively normal patients (LBD-CN), or in alpha-synuclein positive (asyn-positive) participants. Furthermore, uncertainties remain regarding LBD-specific cut-points for these biomarkers. We aimed to determine whether there is a difference in the diagnostic performance of plasma pTau181 and pTau217 for detecting ADNC and amyloidosis in LBD. We also determine whether cut-points for these biomarkers in LBD differ from those for AD. Finally, we conducted a sensitivity analysis in asyn-positive participants. We included 230 Stanford research participants: 110 cognitively normal (CN), 43 LBD-CN, 41 LBD with cognitive impairment (LBD-CI), and 36 AD. Plasma pTau181 was measured with the Lumipulse G platform, and pTau217 with the ALZpath pTau217 assay. A-syn positivity was assessed in CSF with SYNTap®. Diagnostic accuracy of pTau181 and pTau271 in distinguishing ADNC (determined by CSF pTau181/Aβ42) and amyloidosis (determined by CSF Aβ42/Aβ40 or amyloid-β PET) were evaluated with receiver-operating characteristic (ROC) analyses. The Youden index was used to determine optimal cut-points in distinguishing ADNC and amyloidosis, and the DeLong test to compare model performance. In the LBD-CI group, plasma pTau181 and pTau217 had similar diagnostic performance in distinguishing ADNC+ from ADNC- (Figure 1A). Similarly, in the LBD-CN and LBD-CI groups, both biomarkers had similar diagnostic performance in distinguishing Aβ+ from Aβ- participants (Figure 1B). However, in the sensitivity analysis, pTau217 outperformed pTau181 for detecting Aβ+ in asyn-positive participants (AUC: 0.88, 95%-CI: 0.77-1 vs 0.77, 95%-CI: 0.64-0.90, p=0.045) (Figure 2B). Finally, plasma pTau181 and pTau217 cut-points for detecting ADNC and amyloidosis in LBD differed from those for AD (Figures 1-3). We present, for the first time, the diagnostic accuracy of plasma pTau217 in LBD-CN and asyn-positive participants. Our results indicate that plasma pTau181 and pTau217 reliably detect concomitant ADNC and amyloidosis in LBD. Particularly, plasma pTau217 appears more sensitive for detecting amyloidosis in asyn-positive participants. Additionally, our findings underscore the importance of establishing LBD-specific cut-points for AD biomarkers.

Staging the severity of Alzheimer's disease pathology using biomarkers is central to early detection and therapeutic trial design. In this cross-sectional study, we standardized amyloid and tau PET data across multiple cohorts to characterize the frequency of amyloid and tau PET-based stages across the clinical continuum. We examined amyloid and tau severity in 10,396 participants (mean [SD] age, 71.9 [7.1] years) with amyloid PET imaging and a subset (n = 3,295) with tau PET imaging. Clinical stage was defined using cohort-specific criteria and categorized as cognitively unimpaired (n = 7,764), mild cognitive impairment (n = 1,480), or dementia (n = 1,152). Amyloid positivity was defined as ≥25 centiloids and amyloid severity was staged using centiloids bins (e.g., <10, 10-24, 25-49, 50-74, 75-99, ≥100). Tau PET severity was staged using a hierarchical Braak staging schema (e.g., T-, T12+, T34+, T56+), and combined with amyloid status to operationalize PET-based Alzheimer's disease biological stages (e.g., Stage A: A+T-; Stage B: A+T12+; Stage C: A+T34+; Stage D: A+T56+). The cumulative probabilities of PET-based stages were estimated using ordinal logistic regression models. In cognitively unimpaired individuals, the frequency of amyloid levels ≥10 centiloids increased with age. Similarly, amyloid levels ≥25 centiloids increased with age in mild cognitive impairment. Overall, elevated amyloid (≥25 CL) was more likely with increasing age among non-demented individuals. By contrast, this age association was attenuated in dementia where severe amyloid burden (e.g., ≥100 CL) was most common. In the tau PET subsample (n = 3,295), there was a three-way interaction between amyloid, age, and clinical impairment on likelihood of tau severity. Both higher amyloid and greater clinical impairment were associated with increased tau severity; however, the strength and direction of these associations varied with age. At lower amyloid levels, the odds of tau severity increased with older age among cognitively unimpaired and mild cognitive impairment. Conversely, at higher amyloid levels, the odds of higher tau severity (e.g., T56+) decreased with older age in mild cognitive impairment and dementia. A similar age-related pattern was observed in the frequency of biological stages (n = 1,154), where Stage D (e.g., A+T56+) was most frequent in younger individuals with dementia. These findings underscore the dual importance of amyloid and tau PET severity as biomarkers for staging and characterizing Alzheimer's disease progression. They also demonstrate the feasibility of applying PET-based staging frameworks for the diagnosis of Alzheimer's disease across multiple tracers and cohorts.

Type 2 diabetes and glucose metabolism have previously been linked to cognitive decline and higher risk of developing Alzheimer’s disease (AD) dementia. Yet, the relation of glucose metabolism with amyloid and tau pathology remains unclear. This knowledge will help understanding the importance of glucose regulation in relation to AD. Therefore, we aimed to investigate whether earlier age glucose metabolism measures are associated with later age amyloid and tau measures on PET. We included 288 participants (mean age= 43.1, SD=10.7, range 20-70 years) without dementia from the Framingham Heart Study (FHS), who had data available on glucose metabolism measures, i.e. continuous plasma glucose, elevated plasma glucose (>100mg/dl), plasma insulin, and homeostatic model assessment for insulin resistance (HOMA-IR), and a PET measure of global amyloid and/or temporal tau 14 years later (range 11-17 years). We performed linear regression analyses to test associations of each glucose metabolism measure with amyloid or tau uptake on PET, adjusted for age, sex, and exact years of time interval. For significant findings, we explored whether age, sex, ApoE-ε4 allele carriership or amyloid load modified the associations. Demographics are shown in Table 1. Our findings indicated that elevated plasma glucose was associated with greater tau load in the brain 14 years later (B [95%CI] = 0.03 [0.01 – 0.05], p = 0.006). Findings were independent from age, sex, and amyloid load. The association was only observed in ApoE-ε4 non-carriers (B [95%CI] = -0.08 [-0.12 – -0.03], p=0.001, Figure 1). Higher plasma insulin and HOMA-IR were associated with decreased amyloid load after 14 years (B [95%CI] = -0.01 [-0.02 – -0.00], p = 0.035 and B [95%CI] = -0.01 [-0.02 – -0.00], p = 0.034, respectively), but this association attenuated after false discovery rate (FDR) correction (both p=0.07) and adjustment for ApoE-ε4 carriership (insulin p=0.057 and HOMA-IR p=0.053). No other associations were found (Table 2). Our findings suggest that impaired glucose metabolism is associated with increased tau pathology later in life, independent from amyloid pathways. These findings suggest that glucose metabolism regulation is important to prevent neuropathology later in life.

18F-Florbetaben (FBB) uptake in the supratentorial cortex is indicative of amyloid positivity. Due to PET’s low spatial resolution, image noise, and spill-over of signal from adjacent white-matter into gray-matter, trained readers may provide inconsistent reads and quantitative calculations like Centiloids (CLs) are also affected. A set of 264 18F-Florbetaben (amyloid) PET/MRI exams were reconstructed using conventional ordered subset expectation maximization (OSEM) method and MRguided block sequential regularized expectation maximization (MRgBSREM) method. Three trained readers evaluated the images from these 264 patients, which were reconstructed using the OSEM method. Fifty-three exams were rated inconsistently and were mixed with another 53 exams which were rated consistently. These 106 subjects were then rated by our readers using the MRgBSREM PET reconstruction method. CLs were measured using both reconstruction methods. There is significant correlation between CL measured by OSEM and MRgBSREM methods with R2=0.99. The number of inconsistent exams dropped by 64% using MRgBSREM method as compared with OSEM method. Using Fleiss-Kappa statistical test, the agreement between readers was raised from “Fair” to “Significant” in the 106-subjects subset. PET reconstruction with MR priors can significantly improve the consistency of ratings among trained readers. Given the prevalence of inconsistent ratings in amyloid PET, methods that enhance the ability to distinguish intermediate amyloid levels could be valuable for the widespread adoption of this modality.

Coexistence of amyloidosis (Aβ), tauopathy, and alpha-synucleinopathy (αSyn) is common in neurodegenerative disease and drives heterogeneity in clinical presentation, disease progression, and treatment response. Understanding how in vivo biomarkers perform within the context of multiple underlying neuropathologies is therefore critical. While novel plasma biomarkers accurately detect Aβ, their application in the presence of αSyn remains underexplored. This study investigated the diagnostic accuracy of plasma biomarkers for detecting Aβ in individuals with and without αSyn pathology. Five plasma biomarkers were analyzed (pTau181, pTau217, Aβ42/40, GFAP, and NfL) in a cohort of 180 Stanford research participants (mean age = 69); 48% were asymptomatic (healthy controls) and 52% were symptomatic (clinically diagnosed along the Alzheimer's or Lewy body disease spectra). The CSF SAAmplify-αSYN test and Aβ42/40 ratio (Lumipulse G platform) were used to determine αSyn status (αSyn+ and αSyn-) and Aβ status (Aβ+ and Aβ-). Descriptive comparisons were conducted for plasma biomarkers across Aβ/aSyn groups (αSyn-/Aβ-, n  = 60; αSyn-/Aβ+, n  = 53; αSyn+/Aβ-, n  = 35; and αSyn+/Aβ+, n  = 32). Diagnostic accuracies of plasma biomarkers in predicting Aβ status were evaluated in αSyn+ and αSyn- individuals with receiver-operating characteristic (ROC) curve analyses and compared with the DeLong test. Plasma pTau181, pTau217, Aβ42/40, and GFAP levels were abnormal in Aβ+ groups, regardless of αSyn status (Figure 1). Plasma NfL levels were higher in the αSyn+/Aβ+ group compared to other groups. Plasma pTau217 showed the largest median fold change between Aβ+ and Aβ- participants. In αSyn+ participants, plasma pTau217 and Aβ42/40 individually showed the highest accuracies (AUC values up to 0.92) in detecting Aβ (Figure 2). In αSyn- participants, individual and combined biomarker models performed similarly, with no biomarker significantly outperforming another. Including age, sex, and APOE4 status did not improve model accuracy for detecting Aβ in αSyn+ participants, but improved plasma NfL's accuracy for detecting Aβ in aSyn- participants. Plasma pTau217 (individually and combined with other biomarkers) accurately detects Aβ in αSyn+ participants. These findings highlight potential for using plasma pTau217 as a tool for Aβ screening and stratification in clinical trials for alpha-synucleinopathies such as dementia with Lewy bodies and Parkinson's disease.

Importance:Developing disease-modifying treatments is a priority for Alzheimer disease research. Objective:To determine the potential of plasma phosphorylated tau 217 (p-tau217) and tau positron emission tomography (PET) to assess disease modification in treatment trials. Design, Setting, and Participants:This diagnostic/prognostic study used longitudinal data from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) study collected from April 2014 to June 2023. Recruited from 67 sites in the US, Canada, Australia, and Japan, participants included older individuals (age 65-85 years) who were cognitively unimpaired at screening and underwent an amyloid PET scan. Participants without elevated amyloid PET were included from a companion to the A4 study, the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) study. Exposure:18F-florbetapir PET imaging. Main Outcomes and Measures:18F-florbetapir PET imaging was used to classify participants as having elevated amyloid β (Aβ+). Measures of tau included longitudinal plasma p-tau217 and 18F-flortaucipir PET. Cognition was assessed using the Preclinical Alzheimer Cognitive Composite (PACC). Results:A total of 1169 individuals were included from A4 Study and 538 without elevated amyloid PET were included from the LEARN Study. Among these 1707 participants, the baseline mean (SD) age was 71.5 (4.7) years, 1024 (60%) were female, and 683 (40%) male; 1169 participants were Aβ+, and the mean (SD) Mini-Mental State Examination score was 28.8 (1.2). The tau PET substudy included 443 participants; plasma p-tau217 levels were available for 1643 participants. The largest effect size of longitudinal tau PET accumulation at 36 months in Aβ+ participants was in the inferior temporal gyrus. Baseline associations with longitudinal change in PACC score in Aβ+ participants were strongest in the entorhinal cortex (correlation [ρ] = -0.55; 95% CI, -0.63 to -0.45) and plasma p-tau217 levels (ρ = -0.47; 95% CI, -0.56 to -0.37). Tau PET changes in frontoparietal regions were strongly correlated with concurrent cognitive changes. Levels of plasma p-tau217 increased significantly in Aβ+ participants before showing significant deceleration (χ2 = 21.7; P < .001) and were not associated with concurrent cognitive change in the tau PET substudy (ρ = -0.03; 95% CI, -0.23 to 0.16) but were modestly associated with concurrent cognitive changes in the full plasma sample (n = 1119; ρ = -0.24; 95% CI, -0.34 to -0.14). Conclusions and Relevance:This study found that tau PET is valuable for both prognostic and real-time tracking of disease progression. Plasma p-tau217 predicts cognitive changes prior to overt cognitive impairment and can efficiently guide participant selection. Imaging-based tau measures may enhance detection of disease-modifying effects and refine therapeutic targets in future Alzheimer disease trials.