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AbstractINTRODUCTIONPrimary age‐related tauopathy (PART) is characterized by neurofibrillary tangles and minimal β‐amyloid deposition, diagnosed postmortem. This study investigates 18F‐flortaucipir (FTP) PET imaging for antemortem PART diagnosis.METHODSWe analyzed FTP PET scans from 50 autopsy‐confirmed PART and 13 control subjects. Temporal lobe uptake was assessed both qualitatively and quantitatively. Demographic and clinicopathological characteristics and voxel‐level uptake using SPM12 were compared between FTP‐positive and FTP‐negative cases. Intra‐reader reproducibility was evaluated with Krippendorff's alpha.RESULTSMinimal/mild and moderate FTP uptake was seen in 32% of PART cases and 62% of controls, primarily in the left inferior temporal lobe. No demographic or clinicopathological differences were found between FTP‐positive and FTP‐negative cases. High intra‐reader reproducibility (α = 0.83) was noted.DISCUSSIONFTP PET imaging did not show a specific uptake pattern for PART diagnosis, indicating that in vivo PART identification using FTP PET is challenging. Similar uptake in controls suggests non‐specific uptake in PART.Highlights 18F‐flortaucipir (FTP) PET scans were analyzed for diagnosing PART antemortem. 32% of PART cases had minimal/mild FTP uptake in the left inferior temporal lobe. Similar to PART FTP uptake was found in 62% of control subjects. No specific uptake pattern was found, challenging in vivo PART diagnosis.

AbstractINTRODUCTIONUnderstanding the relationship between amyloid beta (Aβ) positron emission tomography (PET) and Aβ cerebrospinal fluid (CSF) biomarkers will define their potential utility in Aβ treatment. Few population‐based or neuropathologic comparisons have been reported.METHODSParticipants 50+ years with Aβ PET and Aβ CSF biomarkers (phosphorylated tau [p‐tau]181/Aβ42, n = 505, and Aβ42/40, n = 54) were included from the Mayo Clinic Study on Aging. From these participants, an autopsy subgroup was identified (n = 47). The relationships of Aβ PET and Aβ CSF biomarkers were assessed cross‐sectionally in all participants and longitudinally in autopsy data.RESULTSCross‐sectionally, more participants were Aβ PET+ versus Aβ CSF− than Aβ PET− versus Aβ CSF+ with an incremental effect when using Aβ PET regions selected for early Aβ deposition. The sensitivity for the first detection of Thal phase ≥ 1 in longitudinal data was higher for Aβ PET (89%) than p‐tau181/Aβ42 (64%).DISCUSSIONAβ PET can detect earlier cortical Aβ deposition than Aβ CSF biomarkers. Aβ PET+ versus Aβ CSF− findings are several‐fold greater using regional Aβ PET analyses and in peri‐threshold‐standardized uptake value ratio participants.Highlights Amyloid beta (Aβ) positron emission tomography (PET) has greater sensitivity for Aβ deposition than Aβ cerebrospinal fluid (CSF) in early Aβ development. A population‐based sample of participants (n = 505) with PET and CSF tests was used. Cortical regions showing early Aβ on Aβ PET were also used in these analyses. Neuropathology was used to validate detection of Aβ by Aβ PET and Aβ CSF biomarkers.

Abstract Obstructive sleep apnoea (OSA) is associated with an increased risk for cognitive impairment and dementia, which likely involves Alzheimer’s disease pathology. Non-rapid eye movement slow-wave activity (SWA) has been implicated in amyloid clearance, but it has not been studied in the context of longitudinal amyloid accumulation in OSA. This longitudinal retrospective study aims to investigate the relationship between polysomnographic and electrophysiological SWA features and amyloid accumulation. From the Mayo Clinic Study of Aging cohort, we identified 71 participants ≥60 years old with OSA (mean baseline age = 72.9 ± 7.5 years, 60.6% male, 93% cognitively unimpaired) who had at least 2 consecutive Amyloid Pittsburgh Compound B (PiB)-PET scans and a polysomnographic study within 5 years of the baseline scan and before the second scan. Annualized PiB-PET accumulation [global ΔPiB(log)/year] was estimated by the difference between the second and first log-transformed global PiB-PET uptake estimations divided by the interval between scans (years). Sixty-four participants were included in SWA analysis. SWA was characterized by the mean relative spectral power density (%) in slow oscillation (SO: 0.5–0.9 Hz) and delta (1–3.9 Hz) frequency bands and by their downslopes (SO-slope and delta-slope, respectively) during the diagnostic portion of polysomnography. We fit linear regression models to test for associations among global ΔPiB(log)/year, SWA features (mean SO% and delta% or mean SO-slope and delta-slope), and OSA severity markers, after adjusting for age at baseline PiB-PET, APOE ɛ4 and baseline amyloid positivity. For 1 SD increase in SO% and SO-slope, global ΔPiB(log)/year increased by 0.0033 (95% CI: 0.0001; 0.0064, P = 0.042) and 0.0069 (95% CI: 0.0009; 0.0129, P = 0.026), which were comparable to 32% and 59% of the effect size associated with baseline amyloid positivity, respectively. Delta-slope was associated with a reduction in global ΔPiB(log)/year by −0.0082 (95% CI: −0.0143; −0.0021, P = 0.009). Sleep apnoea severity was not associated with amyloid accumulation. Regional associations were stronger in the pre-frontal region. Both slow-wave slopes had more significant and widespread regional associations. Annualized PiB-PET accumulation was positively associated with SO and SO-slope, which may reflect altered sleep homeostasis due to increased homeostatic pressure in the setting of unmet sleep needs, increased synaptic strength, and/or hyper-excitability in OSA. Delta-slope was inversely associated with PiB-PET accumulation, suggesting it may represent residual physiological activity. Further investigation of SWA dynamics in the presence of sleep disorders before and after treatment is necessary for understanding the relationship between amyloid accumulation and SWA physiology.

AbstractThe emergence of the United States Food and Drug Administration (FDA)‐approved amyloid‐targeting therapies for Alzheimer's disease challenges clinicians and healthcare providers with a transformative landscape. Effectively communicating the risks, benefits, burdens, costs, and available support associated with these novel disease‐modifying treatments to patients, families, and other healthcare providers is essential but complex. In response, the Alzheimer's Association's Clinical Meaningfulness Workgroup has proposed language surrounding treatment eligibility, benefits, amyloid‐related imaging abnormalities (ARIA), apolipoprotein E (APOE) genotyping, and treatment costs, serving as a resource to healthcare professionals in navigating discussions with patients and their families. As the landscape evolves with the approval of new Alzheimer's therapies, this resource stands poised for updates, ensuring its continued relevance in facilitating informed and meaningful patient‐provider dialogues.Highlights Effective communication of risks, benefits, burdens, and costs of FDA‐approved amyloid‐targeting antibodies is essential to patients, families, and healthcare providers. The Alzheimer's Association's Clinical Meaningfulness Workgroup provides language for physicians and healthcare providers around treatment eligibility, benefits, ARIA, APOE genotyping, and treatment costs. This supplementary resource may be updated as new AD therapies become approved.

Abstract There is increasing interest in Alzheimer’s disease related plasma biomarkers due to their accessibility and scalability. We hypothesized that integrating plasma biomarkers with other commonly used and available participant data (MRI, cardiovascular factors, lifestyle, genetics) using machine learning (ML) models can improve individual prediction of cognitive outcomes. Further, our goal was to evaluate the heterogeneity of these predictors across different age strata. This longitudinal study included 1185 participants from the Mayo Clinic Study of Aging who had complete plasma analyte work-up at baseline. We used the Quanterix Simoa immunoassay to measure neurofilament light, Aβ1–42 and Aβ1–40 (used as Aβ42/Aβ40 ratio), glial fibrillary acidic protein, and phosphorylated tau 181 (p-tau181). Participants’ brain health was evaluated through gray and white matter structural MRIs. The study also considered cardiovascular factors (hyperlipidemia, hypertension, stroke, diabetes, chronic kidney disease), lifestyle factors (area deprivation index, body mass index, cognitive and physical activities), and genetic factors (APOE, single nucleotide polymorphisms, and polygenic risk scores). An ML model was developed to predict cognitive outcomes at baseline and decline (slope). Three models were created: a base model with groups of risk factors as predictors, an enhanced model included socio-demographics, and a final enhanced model by incorporating plasma and socio-demographics into the base models. Models were explained for three age strata: younger than 65 years, 65–80 years, and older than 80 years, and further divided based on amyloid positivity status. Regardless of amyloid status the plasma biomarkers showed comparable performance (R² = 0.15) to MRI (R² = 0.18) and cardiovascular measures (R² = 0.10) when predicting cognitive decline. Inclusion of cardiovascular or MRI measures with plasma in the presence of socio-demographic improved cognitive decline prediction (R² = 0.26 and 0.27). For amyloid positive individuals Aβ42/Aβ40, glial fibrillary acidic protein and p-tau181 were the top predictors of cognitive decline while Aβ42/Aβ40 was prominent for amyloid negative participants across all age groups. Socio-demographics explained a large portion of the variance in the amyloid negative individuals while the plasma biomarkers predominantly explained the variance in amyloid positive individuals (21% to 37% from the younger to the older age group). Plasma biomarkers performed similarly to MRI and cardiovascular measures when predicting cognitive outcomes and combining them with either measure resulted in better performance. Top predictors were heterogeneous between cross-sectional and longitudinal cognition models, across age groups, and amyloid status. Multimodal approaches will enhance the usefulness of plasma biomarkers through careful considerations of a study population’s socio-demographics, brain and cardiovascular health.

AbstractINTRODUCTIONWe evaluated preliminary feasibility of a digital, culturally‐informed approach to recruit and screen participants for the Alzheimer's Disease Neuroimaging Initiative (ADNI4).METHODSParticipants were recruited using digital advertising and completed digital surveys (e.g., demographics, medical exclusion criteria, 12‐item Everyday Cognition Scale [ECog‐12]), Novoic Storyteller speech‐based cognitive test). Completion rates and assessment performance were compared between underrepresented populations (URPs: individuals from ethnoculturally minoritized or low education backgrounds) and non‐URPs.RESULTSOf 3099 participants who provided contact information, 654 enrolled in the cohort, and 595 completed at least one assessment. Two hundred forty‐seven participants were from URPs. Of those enrolled, 465 met ADNI4 inclusion criteria and 237 evidenced possible cognitive impairment from ECog‐12 or Storyteller performance. URPs had lower ECog and Storyteller completion rates. Scores varied by ethnocultural group and educational level.DISCUSSIONPreliminary results demonstrate digital recruitment and screening assessment of an older diverse cohort, including those with possible cognitive impairment, are feasible. Improving engagement and achieving educational diversity are key challenges.Highlights A total of 654 participants enrolled in a digital cohort to facilitate ADNI4 recruitment. Culturally‐informed digital ads aided enrollment of underrepresented populations. From those enrolled, 42% were from underrepresented ethnocultural and educational groups. Digital screening tools indicate > 50% of participants likely cognitively impaired. Completion rates and assessment performance vary by ethnocultural group and education.

Abstract The Alzheimer's Disease Neuroimaging Initiative (ADNI) Clinical Core is responsible for coordination of all clinical activities at the ADNI sites, including project management, regulatory oversight, and site management and monitoring, as well as the collection of all clinical data and management of all study data. The Clinical Core is also charged with determining the clinical classifications and criteria for enrollment in evolving AD trials and enabling the ongoing characterization of the cross‐sectional features and longitudinal trajectories of the ADNI cohorts with application of these findings to optimal clinical trial designs. More than 2400 individuals have been enrolled in the cohorts since the inception of ADNI, facilitating refinement of our understanding of the AD trajectory and allowing academic and industry investigators to model therapeutic trials across the disease spectrum from the presymptomatic stage through dementia. Highlights Since 2004, the Alzheimer's Disease Neuroimaging Initiative (ADNI) Clinical Core has overseen the enrollment of > 2400 participants with mild cognitive impairment, mild Alzheimer's disease (AD) dementia, and normal cognition. The longitudinal dataset has elucidated the full cognitive and clinical trajectory of AD from its presymptomatic stage through the onset of dementia. The ADNI data have supported the design of most major trials in the field.

ImportanceBlack or African American (hereinafter, Black) and Hispanic or Latino/a/x (hereinafter, Latinx) adults are disproportionally affected by Alzheimer disease, but most research studies do not enroll adequate numbers of both of these populations. The Alzheimer’s Disease Neuroimaging Initiative-3 (ADNI3) launched a diversity taskforce to pilot a multipronged effort to increase the study inclusion of Black and Latinx older adults.ObjectiveTo describe and evaluate the culturally informed and community-engaged inclusion efforts to increase the screening and enrollment of Black and Latinx older adults in ADNI3.Design, Setting, and ParticipantsThis cross-sectional study used baseline data from a longitudinal, multisite, observational study conducted from January 15, 2021, to July 12, 2022, with no follow-up. The study was conducted at 13 ADNI3 sites in the US. Participants included individuals aged 55 to 90 years without cognitive impairment and those with mild cognitive impairment or Alzheimer disease.ExposuresEfforts included (1) launch of an external advisory board, (2) changes to the study protocol, (3) updates to the digital prescreener, (4) selection and deployment of 13 community-engaged research study sites, (5) development and deployment of local and centralized outreach efforts, and (6) development of a community-science partnership board.Main Outcomes and MeasuresScreening and enrollment numbers from centralized and local outreach efforts, digital advertisement metrics, and digital prescreener completion.ResultsA total of 91 participants enrolled in the trial via centralized and local outreach efforts, of which 22 (24.2%) identified as Latinx and 55 (60.4%) identified as Black (median [IQR] age, 65.6 [IQR, 61.5-72.5] years; 62 women [68.1%]). This represented a 267.6% increase in the monthly rate of enrollment (before: 1.11 per month; during: 4.08 per month) of underrepresented populations. For the centralized effort, social media advertisements were run between June 1, 2021, and July 31, 2022, which resulted in 2079 completed digital prescreeners, of which 1289 met criteria for subsequent site-level screening. Local efforts were run between June 1, 2021, to July 31, 2022. A total of 151 participants underwent site-level screening (100 from local efforts, 41 from centralized efforts, 10 from other sources).Conclusions and RelevanceIn this cross-sectional study of pilot inclusion efforts, a culturally informed, community-engaged approach increased the inclusion of Black and Latinx participants in an Alzheimer disease cohort study.

AbstractINTRODUCTIONAge‐related and Alzheimer's disease (AD) dementia–related neurodegeneration impact brain health. While morphometric measures from T1‐weighted scans are established biomarkers, they may be less sensitive to earlier changes. Neurite orientation dispersion and density imaging (NODDI), offering biologically meaningful interpretation of tissue microstructure, may be an advanced brain health biomarker.METHODSWe contrasted regional gray matter NODDI and morphometric evaluations concerning their correlation with (1) age, (2) clinical diagnosis stage, and (3) tau pathology as assessed by AV1451 positron emission tomography.RESULTSOur study hypothesizes that NODDI measures are more sensitive to aging and early AD changes than morphometric measures. One NODDI output, free water fraction (FWF), showed higher sensitivity to age‐related changes, generally better effect sizes in separating mild cognitively impaired from cognitively unimpaired participants, and stronger associations with regional tau deposition than morphometric measures.DISCUSSIONThese findings underscore NODDI's utility in capturing early neurodegenerative changes and enhancing our understanding of aging and AD.Highlights Neurite orientation dispersion and density imaging can serve as an effective brain health biomarker for aging and early Alzheimer's disease (AD). Free water fraction has higher sensitivity to normal brain aging. Free water fraction has stronger associations with early AD and regional tau deposition.

[ 18 F]-Flortaucipir positron emission tomography (PET) is considered a good biomarker of Alzheimer’s disease. However, it is unknown how flortaucipir is associated with the distribution of tau across brain regions and how these associations are influenced by amyloid-β. It is also unclear whether flortaucipir can detect tau in definite primary age–related tauopathy (PART). We identified 248 individuals at Mayo Clinic who had undergone [ 18 F]-flortaucipir PET during life, had died, and had undergone an autopsy, 239 cases of which also had amyloid-β PET. We assessed nonlinear relationships between flortaucipir uptake in nine medial temporal and cortical regions, Braak tau stage, and Thal amyloid-β phase using generalized additive models. We found that flortaucipir uptake was greater with increasing tau stage in all regions. Increased uptake at low tau stages in medial temporal regions was only observed in cases with a high amyloid-β phase. Flortaucipir uptake linearly increased with the amyloid-β phase in medial temporal and cortical regions. The highest flortaucipir uptake occurred with high Alzheimer’s disease neuropathologic change (ADNC) scores, followed by low-intermediate ADNC scores, then PART, with the entorhinal cortex providing the best differentiation between groups. Flortaucipir PET had limited ability to detect PART, and imaging-defined PART did not correspond with pathologically defined PART. In summary, spatial patterns of flortaucipir mirrored the histopathological tau distribution, were influenced by the amyloid-β phase, and were useful for distinguishing different ADNC scores and PART.