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BackgroundWith the aging global population and the rising burden of Alzheimer disease and related dementias (ADRDs), there is a growing focus on identifying mild cognitive impairment (MCI) to enable timely interventions that could potentially slow down the onset of clinical dementia. The production of speech by an individual is a cognitively complex task that engages various cognitive domains. The ease of audio data collection highlights the potential cost-effectiveness and noninvasive nature of using human speech as a tool for cognitive assessment. ObjectiveThis study aimed to construct a machine learning pipeline that incorporates speaker diarization, feature extraction, feature selection, and classification to identify a set of acoustic features derived from voice recordings that exhibit strong MCI detection capability. MethodsThe study included 100 MCI cases and 100 cognitively normal controls matched for age, sex, and education from the Framingham Heart Study. Participants' spoken responses on neuropsychological tests were recorded, and the recorded audio was processed to identify segments of each participant's voice from recordings that included voices of both testers and participants. A comprehensive set of 6385 acoustic features was then extracted from these voice segments using OpenSMILE and Praat software. Subsequently, a random forest model was constructed to classify cognitive status using the features that exhibited significant differences between the MCI and cognitively normal groups. The MCI detection performance of various audio lengths was further examined. ResultsAn optimal subset of 29 features was identified that resulted in an area under the receiver operating characteristic curve of 0.87, with a 95% CI of 0.81-0.94. The most important acoustic feature for MCI classification was the number of filled pauses (importance score=0.09, P=3.10E–08). There was no substantial difference in the performance of the model trained on the acoustic features derived from different lengths of voice recordings. ConclusionsThis study showcases the potential of monitoring changes to nonsemantic and acoustic features of speech as a way of early ADRD detection and motivates future opportunities for using human speech as a measure of brain health.

BackgroundCerebral microbleeds (CMB) increase the risk for Alzheimer disease. Current neuroimaging methods that are used to detect CMB are costly and not always accessible. ObjectiveThis study aimed to explore whether the digital clock-drawing test (DCT) may provide a behavioral indicator of CMB. MethodsIn this study, we analyzed data from participants in the Framingham Heart Study offspring cohort who underwent both brain magnetic resonance imaging scans (Siemens 1.5T, Siemens Healthcare Private Limited; T2*-GRE weighted sequences) for CMB diagnosis and the DCT as a predictor. Additionally, paper-based clock-drawing tests were also collected during the DCT. Individuals with a history of dementia or stroke were excluded. Robust multivariable linear regression models were used to examine the association between DCT facet scores with CMB prevalence, adjusting for relevant covariates. Receiver operating characteristic (ROC) curve analyses were used to evaluate DCT facet scores as predictors of CMB prevalence. Sensitivity analyses were conducted by further including participants with stroke and dementia. ResultsThe study sample consisted of 1020 (n=585, 57.35% female) individuals aged 45 years and older (mean 72, SD 7.9 years). Among them, 64 (6.27%) participants exhibited CMB, comprising 46 with lobar-only, 11 with deep-only, and 7 with mixed (lobar+deep) CMB. Individuals with CMB tended to be older and had a higher prevalence of mild cognitive impairment and higher white matter hyperintensities compared to those without CMB (P

Abstract INTRODUCTION Alzheimer's disease (AD) is a heterogeneous disorder characterized by complex underlying neuropathology that is not fully understood. This study aimed to identify cognitive progression subtypes and examine their correlation with clinical outcomes. METHODS Participants of this study were recruited from the Framingham Heart Study. The Subtype and Stage Inference (SuStaIn) method was used to identify cognitive progression subtypes based on eight cognitive domains. RESULTS Three cognitive progression subtypes were identified, including verbal learning (Subtype 1), abstract reasoning (Subtype 2), and visual memory (Subtype 3). These subtypes represent different domains of cognitive decline during the progression of AD. Significant differences in age of onset among the different subtypes were also observed. A higher SuStaIn stage was significantly associated with increased mortality risk. DISCUSSION This study provides a characterization of AD heterogeneity in cognitive progression, emphasizing the importance of developing personalized approaches for risk stratification and intervention. Highlights We used the Subtype and Stage Inference (SuStaIn) method to identify three cognitive progression subtypes. Different subtypes have significant variations in age of onset. Higher stages of progression are associated with increased mortality risk.

Background Smartphone‐based digital technology is increasingly being recognized as a cost‐effective, scalable, and noninvasive method of collecting longitudinal cognitive and behavioral data. Accordingly, a state‐of‐the‐art 3‐year longitudinal project focused on collecting multimodal digital data for early detection of cognitive impairment was developed. Methods and Results A smartphone application collected 2 modalities of cognitive data, digital voice and screen‐based behaviors, from the FHS (Framingham Heart Study) multigenerational Generation 2 (Gen 2) and Generation 3 (Gen 3) cohorts. To understand the feasibility of conducting a smartphone‐based study, participants completed a series of questions about their smartphone and app use, as well as sensory and environmental factors that they encountered while completing the tasks on the app. Baseline data collected to date were from 537 participants (mean age=66.6 years, SD=7.0; 58.47% female). Across the younger participants from the Gen 3 cohort (n=455; mean age=60.8 years, SD=8.2; 59.12% female) and older participants from the Gen 2 cohort (n=82; mean age=74.2 years, SD=5.8; 54.88% female), an average of 76% participants agreed or strongly agreed that they felt confident about using the app, 77% on average agreed or strongly agreed that they were able to use the app on their own, and 81% on average rated the app as easy to use. Conclusions Based on participant ratings, the study findings are promising. At baseline, the majority of participants are able to complete the app‐related tasks, follow the instructions, and encounter minimal barriers to completing the tasks independently. These data provide evidence that designing and collecting smartphone application data in an unsupervised, remote, and naturalistic setting in a large, community‐based population is feasible.

Background Smartphone‐based cognitive assessments have emerged as promising tools, bridging gaps in accessibility and reducing bias in Alzheimer disease and related dementia research. However, their congruence with traditional neuropsychological tests and usefulness in diverse cohorts remain underexplored. Methods and Results A total of 406 FHS (Framingham Heart Study) and 59 BHS (Bogalusa Heart Study) participants with traditional neuropsychological tests and digital assessments using the Defense Automated Neurocognitive Assessment (DANA) smartphone protocol were included. Regression models investigated associations between DANA task digital measures and a neuropsychological global cognitive Z score (Global Cognitive Score [GCS]), and neuropsychological domain‐specific Z scores. FHS participants’ mean age was 57 (SD, 9.75) years, and 44% (179) were men. BHS participants' mean age was 49 (4.4) years, and 28% (16) were men. Participants in both cohorts with the lowest neuropsychological performance (lowest quartile, GCS1) demonstrated lower DANA digital scores. In the FHS, GCS1 participants had slower average response times and decreased cognitive efficiency scores in all DANA tasks (P

IntroductionAlthough brain magnetic resonance imaging (MRI) is a valuable tool for investigating structural changes in the brain associated with neurodegeneration, the development of non-invasive and cost-effective alternative methods for detecting early cognitive impairment is crucial. The human voice has been increasingly used as an indicator for effectively detecting cognitive disorders, but it remains unclear whether acoustic features are associated with structural neuroimaging.MethodsThis study aims to investigate the association between acoustic features and brain volume and compare the predictive power of each for mild cognitive impairment (MCI) in a large community-based population. The study included participants from the Framingham Heart Study (FHS) who had at least one voice recording and an MRI scan. Sixty-five acoustic features were extracted with the OpenSMILE software (v2.1.3) from each voice recording. Nine MRI measures were derived according to the FHS MRI protocol. We examined the associations between acoustic features and MRI measures using linear regression models adjusted for age, sex, and education. Acoustic composite scores were generated by combining acoustic features significantly associated with MRI measures. The MCI prediction ability of acoustic composite scores and MRI measures were compared by building random forest models and calculating the mean area under the receiver operating characteristic curve (AUC) of 10-fold cross-validation.ResultsThe study included 4,293 participants (age 57 ± 13 years, 53.9% women). During 9.3 ± 3.7 years follow-up, 106 participants were diagnosed with MCI. Seven MRI measures were significantly associated with more than 20 acoustic features after adjusting for multiple testing. The acoustic composite scores can improve the AUC for MCI prediction to 0.794, compared to 0.759 achieved by MRI measures.DiscussionWe found multiple acoustic features were associated with MRI measures, suggesting the potential for using acoustic features as easily accessible digital biomarkers for the early diagnosis of MCI.

BackgroundHuman voice has increasingly been recognized as an effective indicator for the detection of cognitive disorders. However, the association of acoustic features with specific cognitive functions and mild cognitive impairment (MCI) has yet to be evaluated in a large community-based population. ObjectiveThis study aimed to investigate the association between acoustic features and neuropsychological (NP) tests across multiple cognitive domains and evaluate the added predictive power of acoustic composite scores for the classification of MCI. MethodsThis study included participants without dementia from the Framingham Heart Study, a large community-based cohort with longitudinal surveillance for incident dementia. For each participant, 65 low-level acoustic descriptors were derived from voice recordings of NP test administration. The associations between individual acoustic descriptors and 18 NP tests were assessed with linear mixed-effect models adjusted for age, sex, and education. Acoustic composite scores were then built by combining acoustic features significantly associated with NP tests. The added prediction power of acoustic composite scores for prevalent and incident MCI was also evaluated. ResultsThe study included 7874 voice recordings from 4950 participants (age: mean 62, SD 14 years; 4336/7874, 55.07% women), of whom 453 were diagnosed with MCI. In all, 8 NP tests were associated with more than 15 acoustic features after adjusting for multiple testing. Additionally, 4 of the acoustic composite scores were significantly associated with prevalent MCI and 7 were associated with incident MCI. The acoustic composite scores can increase the area under the curve of the baseline model for MCI prediction from 0.712 to 0.755. ConclusionsMultiple acoustic features are significantly associated with NP test performance and MCI, which can potentially be used as digital biomarkers for early cognitive impairment monitoring.

Abstract Background Identification of reliable, affordable, and easy-to-use strategies for detection of dementia is sorely needed. Digital technologies, such as individual voice recordings, offer an attractive modality to assess cognition but methods that could automatically analyze such data are not readily available. Methods and findings We used 1264 voice recordings of neuropsychological examinations administered to participants from the Framingham Heart Study (FHS), a community-based longitudinal observational study. The recordings were 73 min in duration, on average, and contained at least two speakers (participant and examiner). Of the total voice recordings, 483 were of participants with normal cognition (NC), 451 recordings were of participants with mild cognitive impairment (MCI), and 330 were of participants with dementia (DE). We developed two deep learning models (a two-level long short-term memory (LSTM) network and a convolutional neural network (CNN)), which used the audio recordings to classify if the recording included a participant with only NC or only DE and to differentiate between recordings corresponding to those that had DE from those who did not have DE (i.e., NDE (NC+MCI)). Based on 5-fold cross-validation, the LSTM model achieved a mean (±std) area under the receiver operating characteristic curve (AUC) of 0.740 ± 0.017, mean balanced accuracy of 0.647 ± 0.027, and mean weighted F1 score of 0.596 ± 0.047 in classifying cases with DE from those with NC. The CNN model achieved a mean AUC of 0.805 ± 0.027, mean balanced accuracy of 0.743 ± 0.015, and mean weighted F1 score of 0.742 ± 0.033 in classifying cases with DE from those with NC. For the task related to the classification of participants with DE from NDE, the LSTM model achieved a mean AUC of 0.734 ± 0.014, mean balanced accuracy of 0.675 ± 0.013, and mean weighted F1 score of 0.671 ± 0.015. The CNN model achieved a mean AUC of 0.746 ± 0.021, mean balanced accuracy of 0.652 ± 0.020, and mean weighted F1 score of 0.635 ± 0.031 in classifying cases with DE from those who were NDE. Conclusion This proof-of-concept study demonstrates that automated deep learning-driven processing of audio recordings of neuropsychological testing performed on individuals recruited within a community cohort setting can facilitate dementia screening.

Aim:Impaired sleep quality and sleep oxygenation are common sleep pathologies. This study assessed the impact of these abnormalities on white matter (WM) integrity in an epidemiological cohort. Methods:The target population was the Framingham Heart Study Generation-2/Omni-1 Cohorts. Magnetic resonance imaging (diffusion tensor imaging) was used to assess WM integrity. Wearable digital devices were used to assess sleep quality: the (M1-SleepImageTM system) and the Nonin WristOx for nocturnal oxygenation. The M1 device collects trunk actigraphy and the electrocardiogram (ECG); sleep stability indices were computed using cardiopulmonary coupling using the ECG. Two nights of recording were averaged. Results:Stable sleep was positively associated with WM health. Actigraphic periods of wake during the sleep period were associated with increased mean diffusivity. One marker of sleep fragmentation which covaries with respiratory chemoreflex activation was associated with reduced fractional anisotropy and increased mean diffusivity. Both oxygen desaturation index and oxygen saturation time under 90% were associated with pathological directions of diffusion tensor imaging signals. Gender differences were noted across most variables, with female sex showing the larger and significant impact. Conclusions:Sleep quality assessed by a novel digital analysis and sleep hypoxia was associated with WM injury, especially in women.

BackgroundThe digital Clock Drawing Test (dCDT) has been recently used as a more objective tool to assess cognition. However, the association between digitally obtained clock drawing features and structural neuroimaging measures has not been assessed in large population-based studies. ObjectiveWe aimed to investigate the association between dCDT features and brain volume. MethodsThis study included participants from the Framingham Heart Study who had both a dCDT and magnetic resonance imaging (MRI) scan, and were free of dementia or stroke. Linear regression models were used to assess the association between 18 dCDT composite scores (derived from 105 dCDT raw features) and brain MRI measures, including total cerebral brain volume (TCBV), cerebral white matter volume, cerebral gray matter volume, hippocampal volume, and white matter hyperintensity (WMH) volume. Classification models were also built from clinical risk factors, dCDT composite scores, and MRI measures to distinguish people with mild cognitive impairment (MCI) from those whose cognition was intact. ResultsA total of 1656 participants were included in this study (mean age 61 years, SD 13 years; 50.9% women), with 23 participants diagnosed with MCI. All dCDT composite scores were associated with TCBV after adjusting for multiple testing (P value

Aim: Human voice contains rich information. Few longitudinal studies have been conducted to investigate the potential of voice to monitor cognitive health. The objective of this study is to identify voice biomarkers that are predictive of future dementia. Methods: Participants were recruited from the Framingham Heart Study. The vocal responses to neuropsychological tests were recorded, which were then diarized to identify participant voice segments. Acoustic features were extracted with the OpenSMILE toolkit (v2.1). The association of each acoustic feature with incident dementia was assessed by Cox proportional hazards models. Results: Our study included 6, 528 voice recordings from 4, 849 participants (mean age 63 ± 15 years old, 54.6% women). The majority of participants (71.2%) had one voice recording, 23.9% had two voice recordings, and the remaining participants (4.9%) had three or more voice recordings. Although all asymptomatic at the time of examination, participants who developed dementia tended to have shorter segments than those who were dementia free (P < 0.001). Additionally, 14 acoustic features were significantly associated with dementia after adjusting for multiple testing (P < 0.05 / 48 = 1 × 10–3). The most significant acoustic feature was jitterDDP_sma_de (P = 7.9 × 10–7), which represents the differential frame-to-frame Jitter. A voice based linear classifier was also built that was capable of predicting incident dementia with area under curve of 0.812. Conclusions: Multiple acoustic and linguistic features are identified that are associated with incident dementia among asymptomatic participants, which could be used to build better prediction models for passive cognitive health monitoring.

Background: Surgeons who lack experience with total ankle arthroplasty (TAA) may remain hesitant to introduce this procedure owing to previously published results of high complication rates during initial cases. The purpose of the present study was to report the development of a TAA program through intermediate outcomes and complications for an initial consecutive series of TAA patients of a single community-based foot and ankle fellowship–trained orthopedic surgeon with little TAA experience using a co-surgeon with similar training and TAA exposure. Methods: The initial 20 patients following third-generation TAA with a single surgeon were reviewed. Clinical outcomes were measured and radiographs were evaluated to determine postoperative implant and ankle position. Complications were also measured including intraoperative, early (

Recent longitudinal PET imaging studies have established methods to estimate the age at which amyloid becomes abnormal at the level of the individual. Here we recontextualized amyloid levels into the temporal domain to better understand the downstream Alzheimer's disease processes of tau neurofibrillary tangle (NFT) accumulation and cognitive decline. This cohort study included a total of 601 individuals from the Wisconsin Registry for Alzheimer's Prevention and Wisconsin Alzheimer's Disease Research Center that underwent amyloid and tau PET, longitudinal neuropsychological assessments and met clinical criteria for three clinical diagnosis groups: cognitively unimpaired (n = 537); mild cognitive impairment (n = 48); or dementia (n = 16). Cortical 11C-Pittsburgh compound B (PiB) distribution volume ratio (DVR) and sampled iterative local approximation were used to estimate amyloid positive (A+; global PiB DVR > 1.16 equivalent to 17.1 centiloids) onset age and years of A+ duration at tau PET (i.e. amyloid chronicity). Tau PET burden was quantified using 18F-MK-6240 standardized uptake value ratios (70-90 min, inferior cerebellar grey matter reference region). Whole-brain and region-specific approaches were used to examine tau PET binding along the amyloid timeline and across the Alzheimer's disease clinical continuum. Voxel-wise 18F-MK-6240 analyses revealed that with each decade of A+, the spatial extent of measurable tau spread (i.e. progressed) from regions associated with early to late NFT tau stages. Regional analyses indicated that tau burden in the entorhinal cortex was detectable, on average, within 10 years of A+ onset. Additionally, the entorhinal cortex was the region most sensitive to early amyloid pathology and clinical impairment in this predominantly preclinical sample. Among initially cognitively unimpaired (n = 472) individuals with longitudinal cognitive follow-up, mixed effects models showed significant linear and non-linear interactions of A+ duration and entorhinal tau on cognitive decline, suggesting a synergistic effect whereby greater A+ duration, together with a higher entorhinal tau burden, increases the likelihood of cognitive decline beyond their separable effects. Overall, the amyloid time framework enabled a spatiotemporal characterization of tau deposition patterns across the Alzheimer's disease continuum. This approach, which examined cross-sectional tau PET data along the amyloid timeline to make longitudinal disease course inferences, demonstrated that A+ duration explains a considerable amount of variability in the magnitude and topography of tau spread, which largely recapitulated NFT staging observed in human neuropathological studies. By anchoring disease progression to the onset of amyloid, this study provides a temporal disease context, which may help inform disease prognosis and timing windows for anti-amyloid therapies., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Cognitive decline in Alzheimer's disease and other dementias typically begins long before clinical impairment. Identifying people experiencing subclinical decline may facilitate earlier intervention. This study developed cognitive trajectory clusters using longitudinally based random slope and change point parameter estimates from a Preclinical Alzheimer's disease Cognitive Composite and examined how baseline and most recently available clinical/health-related characteristics, cognitive statuses and biomarkers for Alzheimer's disease and vascular disease varied across these cognitive clusters. Data were drawn from the Wisconsin Registry for Alzheimer's Prevention, a longitudinal cohort study of adults from late midlife, enriched for a parental history of Alzheimer's disease and without dementia at baseline. Participants who were cognitively unimpaired at the baseline visit with ≥3 cognitive visits were included in trajectory modelling ( n = 1068). The following biomarker data were available for subsets: positron emission tomography amyloid (amyloid: n = 367; [ 11 C]Pittsburgh compound B (PiB): global PiB distribution volume ratio); positron emission tomography tau (tau: n = 321; [ 18 F]MK-6240: primary regions of interest meta-temporal composite); MRI neurodegeneration (neurodegeneration: n = 581; hippocampal volume and global brain atrophy); T 2 fluid-attenuated inversion recovery MRI white matter ischaemic lesion volumes (vascular: white matter hyperintensities; n = 419); and plasma pTau217 ( n = 165). Posterior median estimate person-level change points, slopes' pre- and post-change point and estimated outcome (intercepts) at change point for cognitive composite were extracted from Bayesian Bent-Line Regression modelling and used to characterize cognitive trajectory groups ( K -means clustering). A common method was used to identify amyloid/tau/neurodegeneration/vascular biomarker thresholds. We compared demographics, last visit cognitive status, health-related factors and amyloid/tau/neurodegeneration/vascular biomarkers across the cognitive groups using ANOVA, Kruskal-Wallis, χ 2 , and Fisher's exact tests. Mean (standard deviation) baseline and last cognitive assessment ages were 58.4 (6.4) and 66.6 (6.6) years, respectively. Cluster analysis identified three cognitive trajectory groups representing steep, n = 77 (7.2%); intermediate, n = 446 (41.8%); and minimal, n = 545 (51.0%) cognitive decline. The steep decline group was older, had more females, APOE e4 carriers and mild cognitive impairment/dementia at last visit; it also showed worse self-reported general health-related and vascular risk factors and higher amyloid, tau, neurodegeneration and white matter hyperintensity positive proportions at last visit. Subtle cognitive decline was consistently evident in the steep decline group and was associated with generally worse health. In addition, cognitive trajectory groups differed on aetiology-informative biomarkers and risk factors, suggesting an intimate link between preclinical cognitive patterns and amyloid/tau/neurodegeneration/vascular biomarker differences in late middle-aged adults. The result explains some of the heterogeneity in cognitive performance within cognitively unimpaired late middle-aged adults., Competing Interests: S.C.J. has received research funding from Cerveau Technologies for unrelated work. In the past 3 years, he has served as consultant to Merck, Roche, Eisai, Prothena and AlzPath. No other disclosures were reported., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Introduction: Our objective was determining the optimal combinations of cerebrospinal fluid (CSF) biomarkers for predicting disease progression in Alzheimer's disease (AD) and other neurodegenerative diseases., Methods: We included 1,983 participants from three different cohorts with longitudinal cognitive and clinical data, and baseline CSF levels of Aβ42, Aβ40, phosphorylated tau at threonine-181 (p-tau), neurofilament light (NfL), neurogranin, α-synuclein, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), glial fibrillary acidic protein (GFAP), YKL-40, S100b, and interleukin 6 (IL-6) (Elecsys NeuroToolKit)., Results: Change of modified Preclinical Alzheimer's Cognitive Composite (mPACC) in cognitively unimpaired (CU) was best predicted by p-tau/Aβ42 alone (R 2 ≥ 0.31) or together with NfL (R 2  = 0.25), while p-tau/Aβ42 (R 2 ≥ 0.19) was sufficient to accurately predict change of the Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI) patients. P-tau/Aβ42 (AUC ≥ 0.87) and p-tau/Aβ42 together with NfL (AUC ≥ 0.75) were the best predictors of conversion to AD and all-cause dementia, respectively., Discussion: P-tau/Aβ42 is sufficient for predicting progression in AD, with very high accuracy. Adding NfL improves the prediction of all-cause dementia conversion and cognitive decline., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background Characterizing cerebrovascular hemodynamics in older adults is important for identifying disease and understanding normal neurovascular aging. Four-dimensional (4D) flow MRI allows for a comprehensive assessment of cerebral hemodynamics in a single acquisition. Purpose To establish reference intracranial blood flow and pulsatility index values in a large cross-sectional sample of middle-aged (45-65 years) and older (>65 years) adults and characterize the effect of age and sex on blood flow and pulsatility. Materials and Methods In this retrospective study, patients aged 45-93 years (cognitively unimpaired) underwent cranial 4D flow MRI between March 2010 and March 2020. Blood flow rates and pulsatility indexes from 13 major arteries and four venous sinuses and total cerebral blood flow were collected. Intraobserver and interobserver reproducibility of flow and pulsatility measures was assessed in 30 patients. Descriptive statistics (mean ± SD) of blood flow and pulsatility were tabulated for the entire group and by age and sex. Multiple linear regression and linear mixed-effects models were used to assess the effect of age and sex on total cerebral blood flow and vessel-specific flow and pulsatility, respectively. Results There were 759 patients (mean age, 65 years ± 8 [SD]; 506 female patients) analyzed. For intra- and interobserver reproducibility, median intraclass correlation coefficients were greater than 0.90 for flow and pulsatility measures across all vessels. Regression coefficients β ± standard error from multiple linear regression showed a 4 mL/min decrease in total cerebral blood flow each year (age β = -3.94 mL/min per year ± 0.44; P < .001). Mixed effects showed a 1 mL/min average annual decrease in blood flow (age β = -0.95 mL/min per year ± 0.16; P < .001) and 0.01 arbitrary unit (au) average annual increase in pulsatility over all vessels (age β = 0.011 au per year ± 0.001; P < .001). No evidence of sex differences was observed for flow (β = -1.60 mL/min per male patient ± 1.77; P = .37), but pulsatility was higher in female patients (sex β = -0.018 au per male patient ± 0.008; P = .02). Conclusion Normal reference values for blood flow and pulsatility obtained using four-dimensional flow MRI showed correlations with age. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Steinman in this issue.

Importance: Alzheimer disease (AD) pathology starts with a prolonged phase of β-amyloid (Aβ) accumulation without symptoms. The duration of this phase differs greatly among individuals. While this disease phase has high relevance for clinical trial designs, it is currently unclear how to best predict the onset of clinical progression., Objective: To evaluate combinations of different plasma biomarkers for predicting cognitive decline in Aβ-positive cognitively unimpaired (CU) individuals., Design, Setting, and Participants: This prospective population-based prognostic study evaluated data from 2 prospective longitudinal cohort studies (the Swedish BioFINDER-1 and the Wisconsin Registry for Alzheimer Prevention [WRAP]), with data collected from February 8, 2010, to October 21, 2020, for the BioFINDER-1 cohort and from August 11, 2011, to June 27, 2021, for the WRAP cohort. Participants were CU individuals recruited from memory clinics who had brain Aβ pathology defined by cerebrospinal fluid (CSF) Aβ42/40 in the BioFINDER-1 study and by Pittsburgh Compound B (PiB) positron emission tomography (PET) in the WRAP study. A total of 564 eligible Aβ-positive and Aβ-negative CU participants with available relevant data from the BioFINDER-1 and WRAP cohorts were included in the study; of those, 171 Aβ-positive participants were included in the main analyses., Exposures: Baseline P-tau181, P-tau217, P-tau231, glial fibrillary filament protein, and neurofilament light measured in plasma; CSF biomarkers in the BioFINDER-1 cohort, and PiB PET uptake in the WRAP cohort., Main Outcomes and Measures: The primary outcome was longitudinal measures of cognition (using the Mini-Mental State Examination [MMSE] and the modified Preclinical Alzheimer Cognitive Composite [mPACC]) over a median of 6 years (range, 2-10 years). The secondary outcome was conversion to AD dementia. Baseline biomarkers were used in linear regression models to predict rates of longitudinal cognitive change (calculated separately). Models were adjusted for age, sex, years of education, apolipoprotein E ε4 allele status, and baseline cognition. Multivariable models were compared based on model R2 coefficients and corrected Akaike information criterion., Results: Among 171 Aβ-positive CU participants included in the main analyses, 119 (mean [SD] age, 73.0 [5.4] years; 60.5% female) were from the BioFINDER-1 study, and 52 (mean [SD] age, 64.4 [4.6] years; 65.4% female) were from the WRAP study. In the BioFINDER-1 cohort, plasma P-tau217 was the best marker to predict cognitive decline in the mPACC (model R2 = 0.41) and the MMSE (model R2 = 0.34) and was superior to the covariates-only models (mPACC: R2 = 0.23; MMSE: R2 = 0.04; P < .001 for both comparisons). Results were validated in the WRAP cohort; for example, plasma P-tau217 was associated with mPACC slopes (R2 = 0.13 vs 0.01 in the covariates-only model; P = .01) and MMSE slopes (R2 = 0.29 vs 0.24 in the covariates-only model; P = .046). Sparse models were identified with plasma P-tau217 as a predictor of cognitive decline. Power calculations for enrichment in hypothetical clinical trials revealed large relative reductions in sample sizes when using plasma P-tau217 to enrich for CU individuals likely to experience cognitive decline over time., Conclusions and Relevance: In this study, plasma P-tau217 predicted cognitive decline in patients with preclinical AD. These findings suggest that plasma P-tau217 may be used as a complement to CSF or PET for participant selection in clinical trials of novel disease-modifying treatments.

An accurate blood test for Alzheimer's disease that is sensitive to preclinical proteinopathy and cognitive decline has clear implications for early detection and secondary prevention. We assessed the performance of plasma phosphorylated tau 217 ( pTa u 217 ) against brain PET markers of amyloid [ [ 11 C ] -labelled Pittsburgh compound B (PiB)] and tau ( [ 18 F ] MK-6240) and its utility for predicting longitudinal cognition. Samples were analysed from a subset of participants with up to 8 years follow-up in the Wisconsin Registry for Alzheimer's Prevention (WRAP; 2001-present; plasma 2011-present), a longitudinal cohort study of adults from midlife, enriched for parental history of Alzheimer's disease. Participants were a convenience sample who volunteered for at least one PiB scan, had usable banked plasma and were cognitively unimpaired at first plasma collection. Study personnel who interacted with participants or samples were blind to amyloid status. We used mixed effects models and receiver-operator characteristic curves to assess concordance between plasma pTa u 217 and PET biomarkers of Alzheimer's disease and mixed effects models to understand the ability of plasma pTa u 217 to predict longitudinal performance on WRAP's preclinical Alzheimer's cognitive composite (PACC-3). The primary analysis included 165 people (108 women; mean age = 62.9 ± 6.06; 160 still enrolled; 2 deceased; 3 discontinued). Plasma pTa u 217 was strongly related to PET-based estimates of concurrent brain amyloid ( β ^ = 0.83 (0.75, 0.90), P < 0.001). Concordance was high between plasma pTa u 217 and both amyloid PET (area under the curve = 0.91, specificity = 0.80, sensitivity = 0.85, positive predictive value = 0.58, negative predictive value = 0.94) and tau PET (area under the curve = 0.95, specificity = 1, sensitivity = 0.85, positive predictive value = 1, negative predictive value = 0.98). Higher baseline pTa u 217 levels were associated with worse cognitive trajectories ( β ^ p T a u × a g e = -0.07 (-0.09, -0.06), P < 0.001). In a convenience sample of unimpaired adults, plasma pTa u 217 levels correlate well with concurrent brain Alzheimer's disease pathophysiology and with prospective cognitive performance. These data indicate that this marker can detect disease before clinical signs and thus may disambiguate presymptomatic Alzheimer's disease from normal cognitive ageing., Competing Interests: O.H. has acquired research support (for the institution) from ADX, Avid Radiopharmaceuticals, Biogen, Eli Lilly, Eisai, Fujirebio, GE Healthcare, Pfizer and Roche. In the past 2 years, he has received consultancy/speaker fees from AC Immune, Amylyx, ALZpath, BioArctic, Biogen, Cerveau, Fujirebio, Genentech, Novartis, Roche and Siemens. S.C.J. has served as a consultant to Eisai and Roche Diagnostics, has received an equipment grant from Roche Diagnostics and has received support (sponsoring of an observational study and provision of precursor for tau imaging) from Cerveau Technologies. E.M.J., S.J., K.A.C., R.L.K., L.D., N.A.C., N.M.C., K.J.H., B.T.C. and T.J.B. have nothing to disclose., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Previous studies suggest associations between self-reported sleep problems and poorer health, cognition, Alzheimer's disease pathology and dementia-related outcomes. It is important to develop a deeper understanding of the relationship between these complications and sleep disturbance, a modifiable risk factor, in late midlife, a time when Alzheimer's disease pathology may be accruing. The objectives of this study included application of unsupervised machine learning procedures to identify distinct subgroups of persons with problematic sleep and the association of these subgroups with concurrent measures of mental and physical health, cognition and PET-identified amyloid. Dementia-free participants from the Wisconsin Registry for Alzheimer's Prevention ( n = 619) completed sleep questionnaires including the Insomnia Severity Index, Epworth Sleepiness Scale and Medical Outcomes Study Sleep Scale. K-means clustering analysis identified discrete sleep problem groups who were then compared across concurrent health outcomes (e.g. depression, self-rated health and insulin resistance), cognitive composite indices including episodic memory and executive function and, in a subset, Pittsburgh Compound B PET imaging to assess amyloid burden. Significant omnibus tests ( P < 0.05) were followed with pairwise comparisons. Mean (SD) sample baseline sleep assessment age was 62.6 (6.7). Cluster analysis identified three groups: healthy sleepers [ n = 262 (42.3%)], intermediate sleepers [ n = 229 (37.0%)] and poor sleepers [ n = 128 (20.7%)]. All omnibus tests comparing demographics and health measures across sleep groups were significant except for age, sex and apolipoprotein E e4 carriers; the poor sleepers group was worse than one or both of the other groups on all other measures, including measures of depression, self-reported health and memory complaints. The poor sleepers group had higher average body mass index, waist-hip ratio and homeostatic model assessment of insulin resistance. After adjusting for covariates, the poor sleepers group also performed worse on all concurrent cognitive composites except working memory. There were no differences between sleep groups on PET-based measures of amyloid. Sensitivity analyses indicated that while different clustering approaches resulted in different group assignments for some (predominantly the intermediate group), between-group patterns in outcomes were consistent. In conclusion, distinct sleep characteristics groups were identified with a sizable minority (20.7%) exhibiting poor sleep characteristics, and this group also exhibited the poorest concurrent mental and physical health and cognition, indicating substantial multi-morbidity; sleep group was not associated with amyloid PET estimates. Precision-based management of sleep and related factors may provide an opportunity for early intervention that could serve to delay or prevent clinical impairment., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Menopause is associated with adverse changes in vascular health coinciding with an increased risk of stroke and vascular cognitive impairment. However, there is significant variation in the age at menopause. The present study examined how the age at natural menopause impacts cerebrovascular reactivity and structural biomarkers of brain aging. Thirty-five healthy postmenopausal women were classified as early-onset menopause (Early; n = 19, age at menopause: 47 ± 2 yr) or later-onset menopause (Late; n = 16, age at menopause: 55 ± 2 yr). Middle cerebral artery blood velocity (MCAv), mean arterial blood pressure (MAP), and end-tidal carbon dioxide (ETCO 2 ) were recorded during a stepped hypercapnia protocol. Reactivity was calculated as the slope of the relationship between ETCO 2 and each variable of interest. Brain volumes and white matter hyperintensities (WMHs) were obtained with 3T MRI. Resting MAP was greater in the Early group (99 ± 9 mmHg) compared with the Late group (90 ± 12 mmHg; P = 0.02). Cerebrovascular reactivity, assessed using MCAv, was blunted in the Early group (1.87 ± 0.92 cm/s/mmHg) compared with the Late group (2.37 ± 0.75 cm/s/mmHg; P = 0.02). Total brain volume did not differ between groups (Early: 1.08 ± 0.07 L vs. Late: 1.07 ± 0.06 L; P = 0.66), but the Early group demonstrated greater WMH fraction compared with the Late group (Early: 0.36 ± 0.14% vs. Late: 0.25 ± 0.14%; P = 0.02). These results suggest that age at natural menopause impacts cerebrovascular function and WMH burden in healthy postmenopausal women.

Introduction: While it is generally appreciated that amyloid precedes symptomatic Alzheimer's disease (AD) by decades, a greater understanding of this timeline may increase prognostic accuracy, planning, and care of persons who are on the AD continuum., Methods: We examined trajectories of Clinical Dementia Rating-Sum of Boxes (CDR-SB) relative to estimated years of amyloid positivity (A+) in n  = 123 participants who were all A+ based on [C-11]Pittsburgh compound B positron emission tomography., Results: The average amyloid chronicity at CDR-SB of 2.5 was 20.1 years. The average trajectory of CDR-SB accelerated after 10 years of elevated amyloid and varied greatly between 10 and 30 years. Exploratory analyses suggested that older age and higher volume of white matter hyperintensities shortened the interval between amyloid onset and cognitive impairment., Discussion: The recontextualization of amyloid burden into the time domain will facilitate studies of disease progression, the influence of co-pathology, and factors that hasten or slow cognitive impairment., Competing Interests: Sterling C. Johnson has served on advisory boards for Roche Diagnostics and Eisai. Robert J. Przybelski has served on a speaking panel for Biogen. The remaining authors have no relevant disclosures. Author disclosures are available in the supporting information., (© 2022 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Introduction: Modifiable health and lifestyle factors increase risk of dementia, but whether modifiable factors, when measured in late-midlife, impact the emergence or progression of Alzheimer's disease (AD) pathophysiologic or cognitive changes remains unresolved., Methods: In initially cognitively unimpaired, late middle-aged participants ( N  = 1215; baseline age, M [standard deviation] = 59.3 [6.7] years) from the Wisconsin Registry for Alzheimer's Prevention (WRAP), we investigated the influence of the Lifestyle for Brain Health (LIBRA) index, a lifestyle-based dementia risk score, on AD-related cognitive trajectories and amyloid beta (Aβ) plaque accumulation., Results: Overall, lower baseline LIBRA, denoting healthier lifestyle and lower dementia risk, was related to better overall cognitive performance, but did not moderate apolipoprotein E ε4 or Aβ-related longitudinal cognitive trajectories. LIBRA was not significantly associated with Aβ accumulation or estimated age of Aβ onset., Discussion: In WRAP, late-midlife LIBRA scores were related to overall cognitive performance, but not AD-related cognitive decline or Aβ accumulation in the preclinical timeframe., Highlights: The Lifestyle for Brain Health (LIBRA) index was associated with cognitive performance in late-midlife.LIBRA did not moderate apolipoprotein E ε4 or amyloid-related cognitive decline.LIBRA was not associated with the onset or accumulation of amyloid plaques., Competing Interests: Dr. Johnson has participated on an advisory panel for and received an equipment grant from Roche Diagnostics, and he has received support (sponsoring of an observational study and provision of precursor for tau imaging) from Cerveau Technologies. No other disclosures were reported. Author disclosures are available in the supporting information., (© 2022 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Vascular dysfunction may occur prior to declines in cognitive function and accumulation of neuropathology. White matter hyperintensities (WMH) develop due to cerebral ischemia and elevated blood pressure in midlife. The purpose of this study was to evaluate associations between cardiovascular and cerebrovascular responses to sympathoexcitatory stimuli and WMH burden in cognitively unimpaired middle-aged and older adults. Sixty-eight adults (age = 63 ± 4y, men = 20, women = 48) participated in this study. Participants completed isometric handgrip exercise (IHG) exercise at 40% of maximal voluntary contraction until fatigue followed by a 90s period of post-exercise ischemia. Heart rate (HR), mean arterial pressure (MAP), middle cerebral artery blood velocity (MCAv), and end-tidal CO 2 were continuously measured throughout the protocol. Cerebrovascular resistance index (CVRi) was calculated as MAP/MCAv. WMH lesion volume and intracranial volume (ICV) were measured using a FLAIR and T1 scan on a 3T MRI scanner, respectively. WMH fraction was calculated as (WMH lesion volume/ICV)*100 and cubic root transformed. Multiple linear regressions were used to determine the association between cardiovascular and cerebrovascular responses to IHG exercise and post-exercise ischemia and WMH fraction. Multiple linear regression models were adjusted for age, sex, apolipoprotein ε4 status, and total work performed during IHG exercise. During IHG exercise, there were significant increases from baseline in HR (25 ± 12%), MAP (27 ± 11%), MCAv (5 ± 10%), and CVRi (22 ± 17%; P < 0.001 for all). During post-exercise ischemia, HR (8 ± 7%), MAP (22 ± 9%), and CVRi (23 ± 16%) remained elevated ( P < 0.001) while MCAv (0 ± 10%) was not different compared to baseline. There was an inverse association between the percent change in HR (r = -0.42, P = 0.002), MAP (r = -0.41, P = 0.002), and CVRi (r = -0.31, P = 0.045), but not MCAv (r = 0.19, P = 0.971) in response to IHG exercise and WMH fraction. There were no associations between responses to post-exercise ischemia and WMH fraction. Lower sympathoexcitatory responses to IHG exercise are associated with greater WMH burden in middle-aged to older adults. These findings suggest that individuals who demonstrate smaller increases in HR, MAP, and CVRi in response to sympathoexcitatory stress have greater WMH burden., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Pearson, Miller, Corkery, Eisenmann, Howery, Cody, Chin, Johnson and Barnes.)

Importance: Characterization of early tau deposition in individuals with preclinical Alzheimer disease (AD) is critical for prevention trials that aim to select individuals at risk for AD and halt the progression of disease., Objective: To evaluate the prevalence of cortical tau positron emission tomography (PET) heterogeneity in a large cohort of clinically unimpaired older adults with elevated β-amyloid (A+)., Design, Setting, and Participants: This cross-sectional study examined prerandomized tau PET, amyloid PET, structural magnetic resonance imaging, demographic, and cognitive data from the Anti-Amyloid Treatment in Asymptomatic AD (A4) Study from April 2014 to December 2017. Follow-up analyses used observational tau PET data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the Harvard Aging Brain Study (HABS), and the Wisconsin Registry for Alzheimer's Prevention and the Wisconsin Alzheimer's Disease Research Center (together hereinafter referred to as Wisconsin) to evaluate consistency. Participants were clinically unimpaired at the study visit closest to the tau PET scan and had available amyloid and tau PET data (A4 Study, n = 447; ADNI, n = 433; HABS, n = 190; and Wisconsin, n = 328). No participants who met eligibility criteria were excluded. Data were analyzed from May 11, 2021, to January 25, 2022., Main Outcomes and Measures: Individuals with preclinical AD with heterogeneous cortical tau PET patterns (A+T cortical+) were identified by examining asymmetrical cortical tau signal and disproportionate cortical tau signal relative to medial temporal lobe (MTL) tau. Voxelwise tau patterns, amyloid, neurodegeneration, cognition, and demographic characteristics were examined., Results: The 447 A4 participants (A+ group, 392; and normal β-amyloid group, 55), with a mean (SD) age of 71.8 (4.8) years, included 239 women (54%). A total of 36 individuals in the A+ group (9% of the A+ group) exhibited heterogeneous cortical tau patterns and were further categorized into 3 subtypes: asymmetrical left, precuneus dominant, and asymmetrical right. A total of 116 individuals in the A+ group (30% of the A+ group) showed elevated MTL tau (A+T MTL+). Individuals in the A+T cortical+ group were younger than those in the A+T MTL+ group (t61.867 = -2.597; P = .03). Across the A+T cortical+ and A+T MTL+ groups, increased regional tau was associated with reduced hippocampal volume and MTL thickness but not with cortical thickness. Memory scores were comparable between the A+T cortical+ and A+T MTL+ groups, whereas executive functioning scores were lower for the A+T cortical+ group than for the A+T MTL+ group. The prevalence of the A+T cortical+ group and tau patterns within the A+T cortical+ group were consistent in ADNI, HABS, and Wisconsin., Conclusions and Relevance: This study suggests that early tau deposition may follow multiple trajectories during preclinical AD and may involve several cortical regions. Staging procedures, especially those based on neuropathology, that assume a uniform trajectory across individuals are insufficient for disease monitoring with tau imaging.

Introduction: Individuals with Down syndrome (DS) are at an increased risk of developing Alzheimer's Disease (AD). One of the early underlying mechanisms in AD pathology is the accumulation of amyloid protein plaques, which are deposited in extracellular gray matter and signify the first stage in the cascade of neurodegenerative events. AD-related neurodegeneration is also evidenced as microstructural changes in white matter. In this work, we explored the correlation of white matter microstructure with amyloid load to assess amyloid-related neurodegeneration in a cohort of adults with DS., Methods: In this study of 96 adults with DS, the relation of white matter microstructure using diffusion tensor imaging (DTI) and amyloid plaque burden using [ 11 C]PiB PET were examined. The amyloid load (Aβ L ) derived from [ 11 C]PiB was used as a global measure of amyloid burden. Aβ L and DTI measures were compared using tract-based spatial statistics (TBSS) and corrected for imaging site and chronological age., Results: TBSS of the DTI maps showed widespread age-by-amyloid interaction with both fractional anisotropy (FA) and mean diffusivity (MD). Further, diffuse negative association of FA and positive association of MD with amyloid were observed., Discussion: These findings are consistent with the white matter microstructural changes associated with AD disease progression in late onset AD in non-DS populations., (Copyright © 2021. Published by Elsevier Inc.)

Introduction: This work investigated the relationship between cerebrovascular disease (CVD) markers and Alzheimer's disease (AD) biomarkers of amyloid beta deposition, and neurofibrillary tau tangles in subjects spanning the AD clinical spectrum., Methods: A total of 136 subjects participated in this study. Four groups were established based on AD biomarker positivity from positron emission tomography (amyloid [A] and tau [T]) and clinical diagnosis (cognitively normal [CN] and impaired [IM]). CVD markers were derived from structural and quantitative magnetic resonance imaging data., Results: Transcapillary pulse wave delay was significantly longer in controls compared to AT biomarker-confirmed groups (A+/T-/CN P  < .001, A+/T+/CN P  < .001, A+/T+/IM P  = .003). Intracranial low-frequency oscillations were diminished in AT biomarker-confirmed groups both CN and impaired (A+/T-/CN P  = .039, A+/T+/CN P  = .007, A+/T+/IM P  = .011). A significantly higher presence of microhemorrhages was measured in A+/T+/CN compared to controls ( P  = .006)., Discussion: Cerebrovascular markers indicate increased vessel stiffness and reduced vasomotion in AT biomarker-positive subjects during preclinical AD., Competing Interests: K.A. Cody, T. Reher, and R.V. Cadman have nothing to disclose. L.A. Rivera‐Rivera's effort on this work was supported by the Alzheimer's Association AARFD‐20‐678095 paid to the institution. L. Eisenmenger's effort on this work was supported by the Clinical and Translational Science Award (CTSA) program, through the NIH National Center for Advancing Translational Sciences (NCATS), grant UL1TR002373 and KL2TR002374, as well as the Wisconsin Alzheimer's Disease Research Center grant P30‐AG062715 paid to the institution. T. Betthauser has also received grant support outside the submitted work from Alzheimer's Association AARF‐19‐614533 paid to the institution. H.A. Rowley has received consulting fees from GE HealthCare, iSchemaView and for accredited lectures and podcasts for Northwest Imaging Forums and the Data Safety Monitoring Board of HL Gore. H.A. Rowley has also received grant support outside the submitted work from the Radiological Society of North America, Fellow Grant paid to the institution. C.M. Carlsson has received payments for her participation in an NIH study at UCLA (D‐CARE) and study drugs from Amarin Corporation (Vascepa and placebo) for VA Merit Study. C.M. Carlsson has also received grant support outside the submitted work from NIH/Lilly, NIH/Esai, VA Merit, and NIH to the institution. N.A. Chin has received payments for being a member of the Med‐Sci committee for the WI Alzheimer's Association and member of the Med‐Sci committee for the Alzheimer's Foundation of America. S.C. Johnson serves on an advisory board for Roche Diagnostics for which he receives an honorarium and is principal investigator of an equipment grant from Roche. He receives research funding from Cerveau Technologies. K.M. Johnson has received royalties for patents licensed by the institution (UW‐Madison) unrelated to this project. K.M. Johnson has also received grant support outside the submitted work from NIH and GE Healthcare as research support to the institution., (© 2021 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Clinical evidence shows vascular factors may co-occur and complicate the expression of Alzheimer's disease (AD); yet, the pathologic mechanisms and involvement of different compartments of the vascular network are not well understood. Diseases such as arteriosclerosis diminish vascular compliance and will lead to arterial stiffness, a well-established risk factor for cardiovascular morbidity. Arterial stiffness can be assessed using pulse wave velocity (PWV); however, this is usually done from carotid-to-femoral artery ratios. To probe the brain vasculature, intracranial PWV measures would be ideal. In this study, high temporal resolution 4D flow MRI was used to assess transcranial PWV in 160 subjects including AD, mild cognitive impairment (MCI), healthy controls, and healthy subjects with apolipoprotein ɛ4 positivity (APOE4+) and parental history of AD dementia (FH+). High temporal resolution imaging was achieved by high temporal binning of retrospectively gated data using a local-low rank approach. Significantly higher transcranial PWV in AD dementia and MCI subjects was found when compared to old-age-matched controls (AD vs. old-age-matched controls: P  <0.001, AD vs. MCI: P  = 0.029, MCI vs. old-age-matched controls P  = 0.013). Furthermore, vascular changes were found in clinically healthy middle-age adults with APOE4+ and FH+ indicating significantly higher transcranial PWV compared to controls ( P  <0.001).

Adults with Down syndrome have an increased risk for both disordered sleep and Alzheimer's disease (AD). In the general population, disrupted sleep has been linked to beta amyloid accumulation, an early pathophysiologic feature of AD. In this study, the association among sleep, beta amyloid, and measures of AD-related cognitive decline was examined in 47 non-demented adults with Down syndrome (aged 26-56 years). Sleep was measured using actigraphy over 7 nights. Pittsburgh Compound B positron emission tomography was used to assess global and striatal beta amyloid burden. Participants had the following clinical AD status: 7 (15%) mild cognitive impairment and 40 (85%) cognitively unaffected. Average length of night-time awakenings was significantly positively associated with striatal beta amyloid and decreased cognitive performance in executive functioning and motor planning and coordination. Findings suggest that disrupted sleep is associated with beta amyloid accumulation and cognitive features of preclinical AD in Down syndrome. Early identification and treatment of sleep problems could be a lifestyle intervention that may delay beta amyloid accumulation and cognitive decline in this AD vulnerable group., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Introduction: Individuals with Down syndrome (DS) show enhanced amyloid beta (Aβ) deposition in the brain. A new positron emission tomography (PET) index of amyloid load ( Aβ L ) was recently developed as an alternative to standardized uptake value ratios (SUVrs) to quantify Aβ burden with high sensitivity for detecting and tracking Aβ change. 1 ., Methods: Aβ L was calculated in a DS cohort (N = 169, mean age ± SD = 39.6 ± 8.7 years) using [C-11]Pittsburgh compound B (PiB) PET imaging. DS-specific PiB templates were created for Aβ carrying capacity ( K ) and non-specific binding ( NS )., Results: The highest values of Aβ carrying capacity were found in the striatum and precuneus. Longitudinal changes in Aβ L displayed less variability when compared to SUVrs., Discussion: These results highlight the utility of Aβ L for characterizing Aβ deposition in DS. Rates of Aβ accumulation in DS were found to be similar to that observed in late-onset Alzheimer's disease (AD; ≈3% to 4% per year), suggesting that AD progression in DS is of earlier onset but not accelerated., Competing Interests: The authors declare no conflicts of interest., (© 2020 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, Inc. on behalf of the Alzheimer's Association.)

Introduction: This study applies a novel algorithm to longitudinal amyloid positron emission tomography (PET) imaging to identify age-heterogeneous amyloid trajectory groups, estimate the age and duration (chronicity) of amyloid positivity, and investigate chronicity in relation to cognitive decline and tau burden., Methods: Cognitively unimpaired participants ( n = 257) underwent one to four amyloid PET scans (Pittsburgh Compound B, PiB). Group-based trajectory modeling was applied to participants with longitudinal scans ( n = 171) to identify and model amyloid trajectory groups, which were combined with Bayes theorem to estimate age and chronicity of amyloid positivity. Relationships between chronicity, cognition, clinical progression, and tau PET (MK-6240) were investigated using regression models., Results: Chronicity explained more heterogeneity in amyloid burden than age and binary amyloid status. Chronicity was associated with faster cognitive decline, increased risk of abnormal cognition, and higher entorhinal tau., Discussion: Amyloid chronicity provides unique information about cognitive decline and neurofibrillary tangle development and may be useful to investigate preclinical Alzheimer's disease., Competing Interests: [18F]MK‐6240 precursor and reference standard used in this study were provided by Cerveau Technologies. Dr. Sterling C. Johnson is principal investigator for a separate ongoing study using MK‐6240 sponsored by Cerveau Technologies. Dr. Sterling C. Johnson served on an advisory board for Roche Diagnostics in 2018. Dr. Howard Rowley is a consultant for GE HealthCare and has equity interest in ImageMoverMD. None of the other authors has any relevant disclosures., (© 2020 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, Inc. on behalf of the Alzheimer's Association.)

Recent modeling and experimental evidence suggests clearance of soluble metabolites from the brain can be driven by low frequency flow oscillations (LFOs) through the intramural periarterial drainage (IPAD) pathway. This study investigates the use of 4D flow MRI to derive LFOs from arterial and venous measures of blood flow. 3D radial 4D flow MRI data were acquired on a 3.0 T scanner and reconstructed using a low-rank constraint to produce time resolved measurements of blood flow. Physical phantom experiments were performed to validate the time resolved 4D flow against a standard 2D phase contrast (PC) approach. To evaluate the ability of 4D flow to distinguish physiologic flow changes from noise, healthy volunteers were scanned during a breath-hold (BH) maneuver and compared against 2D PC measures. Finally, flow measures were performed in intracranial arteries and veins of 112 participants including subjects diagnosed with Alzheimer's disease (AD) clinical syndrome (n = 23), and healthy controls (n = 89) on whom apolipoprotein ɛ4 positivity (APOE4+) and parental history of AD dementia (FH+) was known. To assess LFOs, flow range, standard deviation, demeaned temporal flow changes, and power spectral density were quantified from the time series. Group differences were assessed using ANOVA followed by Tukey-Kramer method for pairwise comparison for adjusted means (P < 0.05). Significantly lower LFOs as measured from flow variation range and standard deviations were observed in the arteries of AD subjects when compared to age-matched controls (P = 0.005, P = 0.011). Results suggest altered vascular function in AD subjects. 4D flow based spontaneous LFO measures might hold potential for longitudinal studies aimed at predicting cognitive trajectories in AD and study disease mechanisms., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

This study investigated differences in retrospective cognitive trajectories between amyloid and tau PET biomarker stratified groups in initially cognitively unimpaired participants sampled from the Wisconsin Registry for Alzheimer's Prevention. One hundred and sixty-seven initially unimpaired individuals (baseline age 59 ± 6 years; 115 females) were stratified by elevated amyloid-β and tau status based on 11C-Pittsburgh compound B (PiB) and 18F-MK-6240 PET imaging. Mixed effects models were used to determine if longitudinal cognitive trajectories based on a composite of cognitive tests including memory and executive function differed between biomarker groups. Secondary analyses investigated group differences for a variety of cross-sectional health and cognitive tests, and associations between 18F-MK-6240, 11C-PiB, and age. A significant group × age interaction was observed with post hoc comparisons indicating that the group with both elevated amyloid and tau pathophysiology were declining approximately three times faster in retrospective cognition compared to those with just one or no elevated biomarkers. This result was robust against various thresholds and medial temporal lobe regions defining elevated tau. Participants were relatively healthy and mostly did not differ between biomarker groups in health factors at the beginning or end of study, or most cognitive measures at study entry. Analyses investigating association between age, MK-6240 and PiB indicated weak associations between age and 18F-MK-6240 in tangle-associated regions, which were negligible after adjusting for 11C-PiB. Strong associations, particularly in entorhinal cortex, hippocampus and amygdala, were observed between 18F-MK-6240 and global 11C-PiB in regions associated with Braak neurofibrillary tangle stages I-VI. These results suggest that the combination of pathological amyloid and tau is detrimental to cognitive decline in preclinical Alzheimer's disease during late middle-age. Within the Alzheimer's disease continuum, middle-age health factors likely do not greatly influence preclinical cognitive decline. Future studies in a larger preclinical sample are needed to determine if and to what extent individual contributions of amyloid and tau affect cognitive decline. 18F-MK-6240 shows promise as a sensitive biomarker for detecting neurofibrillary tangles in preclinical Alzheimer's disease., (© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain.)

The present study provided an investigation of associations between leisure activity and early Alzheimer's disease neuropathology (i.e., brain β-amyloid) and episodic memory in a sample of 65 adults with Down syndrome (aged 30-53 years), at baseline and follow-up, approximately three years apart. Findings indicated that leisure activity at baseline was not associated with brain β-amyloid at baseline or change in brain β-amyloid from baseline to follow-up. Greater cognitively stimulating leisure activity at baseline was associated with better episodic memory at baseline, and greater social leisure activity at baseline was associated with less decline in episodic memory from baseline to follow-up. High (as opposed to low) levels of social and overall leisure activity at baseline moderated the association between increase in brain β-amyloid and decline in episodic memory, from baseline to follow-up. Findings suggest that cognitively stimulating and social leisure activity could protect against the effect of Alzheimer's disease neuropathology on episodic memory in adults with Down syndrome., (© 2019 Wiley Periodicals, Inc.)

The focus of Alzheimer's disease (AD) neuroimaging research has shifted towards an investigation of the earliest stages of AD pathogenesis, which manifests in every young adult with Down syndrome (DS; trisomy 21) resulting from a deterministic genetic predisposition to amyloid precursor protein overproduction. Due to morphological differences in brain structure in the DS population, special consideration must be given to processing pipelines and the use of normative atlases developed for the non-DS population. Further, the use of typical MRI to MRI template spatial normalization is less desirable in this cohort due to a greater presence of motion artefacts in MRI images. The diffuse nature of PiB uptake and comparatively lower spatial resolution of the PET image permits the purposing of this modality as a template for spatial normalization, which can substantially improve the robustness of this procedure in the cases of MRI images with motion. The aim of this work was to establish standardized methods for spatial normalization and tissue type segmentation using DS specific templates in order to perform voxel-wise analyses. A total of 72 adults with DS underwent [ 11 C]PiB PET to assess brain amyloid burden and volumetric MRI imaging. A DS specific PiB template for spatial normalization and a set of DS specific prior probability templates were created with two-pass methods. With implementation of this DS specific PiB template, no participants were excluded due to poor spatial normalization, thus maximizing the sample size for PiB analyses in standardized space. In addition, difference images between prior probability templates created from the general population and the DS population reflected known morphological differences, particularly in the frontal cortex. In conclusion, DS specific templates that account for unique challenges improve spatial normalization and tissue type segmentation, and provide a framework for reliable voxel-wise analysis of AD biomarkers in this atypical population.

Tau PET imaging has potential for elucidating changes in the deposition of neuropathological tau aggregates that are occurring during the progression of Alzheimer disease (AD). This work investigates in vivo kinetics, quantification strategies, and imaging characteristics of a novel tau PET radioligand 18 F-MK-6240 in humans. Methods: Fifty-one individuals ranging from cognitively normal young controls to persons with dementia underwent T1-weighted MRI as well as 11 C-PiB and 18 F-MK-6240 PET imaging. PET data were coregistered to the MRI, and time-activity curves were extracted from regions of interest to assess 18 F-MK-6240 kinetics. The pons and inferior cerebellum were investigated as potential reference regions. Reference tissue methods (Logan graphical analysis [LGA] and multilinear reference tissue method [MRTM2]) were investigated for quantification of 18 F-MK-6240 distribution volume ratios (DVRs) in a subset of 19 participants. Stability of DVR methods was evaluated using truncated scan durations. SUV ratio (SUVR) estimates were compared with DVR estimates to determine the optimal timing window for SUVR analysis. Parametric SUVR images were used to identify regions of potential off-target binding and to compare binding patterns with neurofibrillary tau staging established in neuropathology literature. Results: SUVs in the pons and the inferior cerebellum indicated consistent clearance across all 51 subjects. LGA and MRTM2 DVR estimates were similar, with LGA slightly underestimating DVR compared with MRTM2. DVR estimates remained stable when truncating the scan duration to 60 min. SUVR determined 70-90 min after injection of 18 F-MK-6240 indicated linearity near unity when compared with DVR estimates and minimized potential spill-in from uptake outside the brain. 18 F-MK-6240 binding patterns in target regions were consistent with neuropathological neurofibrillary tau staging. Off-target binding regions included the ethmoid sinus, clivus, meninges, substantia nigra, but not the basal ganglia or choroid plexus. Conclusion: 18 F-MK-6240 is a promising PET radioligand for in vivo imaging of neurofibrillary tau aggregates in AD with minimal off-target binding in the human brain., (© 2019 by the Society of Nuclear Medicine and Molecular Imaging.)

The relation between verticality perception and body balance as influenced by perceptual style, age, and sex was investigated in 100 subjects. Perceptual style was measured by the Rod and Frame Test. Body balance data were obtained by two electromechanical force plates. The results of the measurements of perceptual style indicated that the younger groups were more accurate in estimating verticality than the older groups and that men were more accurate than women. With regard to the body balance shift data, however, no significant differences relative to age, sex, or perceptual style were found. The rejection of the hypothesis concerning body balance shift was interpreted in terms of the dominant influence of proprioceptive cues over visual cues in maintaining body balance. In normal standing activities, as long as the neuromuscular system is intact, conflicting stimuli from the visual field appear to have little effect on modifying body balance.