Brain Amyloid Burden Research Articles

Explainable artificial intelligence identifies an AQP4 polymorphism-based risk score associated with brain amyloid burden

Aquaporin-4 (AQP4) is hypothesized to be a component of the glymphatic system, a pathway for removing brain interstitial solutes like amyloid-β (Aβ). Evidence exists that genetic variation of AQP4 impacts Aβ clearance, clinical outcome in Alzheimer’s disease as well as sleep measures. We examined whether a risk score calculated from several AQP4 single-nucleotide polymorphisms (SNPs) is related to Aβ neuropathology in older cognitively unimpaired white individuals. We used a machine learning approach and explainable artificial intelligence to extract information on synergistic effects of AQP4 SNPs on brain amyloid burden from the ADNI cohort. From this information, we formulated a sex-specific AQP4 SNP-based risk score and evaluated it using data from the screening process of the A4 study. We found in both cohorts significant associations of the risk score with brain amyloid burden. The results support the hypothesis of an involvement of the glymphatic system, and particularly AQP4, in brain amyloid aggregation pathology. They suggest also that different AQP4 SNPs exert a synergistic effect on the build-up of brain amyloid burden.

The AHA/ASA and DSM-V diagnostic criteria for vascular cognitive impairment identify cases with predominant vascular pathology.

There are major challenges in determining the etiology of vascular cognitive impairment (VCI) clinically, especially in the presence of mixed pathologies, such as vascular and amyloid. Most recently, two criteria (American Heart Association/American Stroke Association (AHA/ASA) and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V)) have been proposed for the clinical diagnosis of VCI but have not as yet been validated using neuroimaging. This study aims to determine whether the AHA/ASA and DSM-V criteria for VCI can distinguish between cases with predominantly vascular pathology and cases with mixed pathology. A total of 186 subjects were recruited from a cross-sectional memory clinic-based study at the National University Hospital, Singapore. All subjects underwent clinical and neuropsychological assessment, magnetic resonance imaging (MRI) and carbon 11-labeled Pittsburgh Compound B ([11C] PiB) positron emission tomography (PET) scans. Diagnosis of the etiological subtypes of VCI (probable vascular mild cognitive impairment (VaMCI), possible VaMCI, non-VaMCI, probable vascular dementia (VaD), possible VaD, non-VaD) were performed following AHA/ASA and DSM-V criteria. Brain amyloid burden was determined for each subject with standardized uptake value ratio (SUVR) values ⩾1.5 classified as amyloid positive. Using κ statistics, both criteria had excellent agreement for probable VaMCI, probable VaD, and possible VaD (κ = 1.00), and good for possible VaMCI (κ = 0.71). Using the AHA/ASA criteria, the amyloid positivity of probable VaMCI (3.8%) and probable VaD (15%) was significantly lower compared to possible VaMCI (26.7%), non-VaMCI (33.3%), possible VaD (73.3%), and non-VaD (76.2%) (p < 0.001). Similarly, using the DSM-V criteria, the amyloid positivity of probable VaMCI (3.8%) and probable VaD (15%) was significantly lower compared to possible VaMCI (26.3%), non-VaMCI (32.1%), possible VaD (73.3%), and non-VaD (76.2%) (p < 0.001). In both criteria, there was good agreement in differentiating individuals with non-VaD and possible VaD, with significantly higher (p < 0.001) global [11C]-PiB SUVR, from individuals with probable VaMCI and probable VaD, who had predominant vascular pathology. The AHA/ASA and DSM-V criteria for VCI can identify VCI cases with little to no concomitant amyloid pathology, hence supporting the utility of AHA/ASA and DSM-V criteria in diagnosing patients with predominant vascular pathology. Data supporting this study are available from the Memory Aging and Cognition Center, National University of Singapore. Access to the data is subject to approval and a data sharing agreement due to University policy.

Non-invasive quantification of 18F-florbetaben with total-body EXPLORER PET

BackgroundKinetic modeling of 18F-florbetaben provides important quantification of brain amyloid deposition in research and clinical settings but its use is limited by the requirement of arterial blood data for quantitative PET. The total-body EXPLORER PET scanner supports the dynamic acquisition of a full human body simultaneously and permits noninvasive image-derived input functions (IDIFs) as an alternative to arterial blood sampling. This study quantified brain amyloid burden with kinetic modeling, leveraging dynamic 18F-florbetaben PET in aorta IDIFs and the brain in an elderly cohort.Methods18F-florbetaben dynamic PET imaging was performed on the EXPLORER system with tracer injection (300 MBq) in 3 individuals with Alzheimer’s disease (AD), 3 with mild cognitive impairment, and 9 healthy controls. Image-derived input functions were extracted from the descending aorta with manual regions of interest based on the first 30 s after injection. Dynamic time-activity curves (TACs) for 110 min were fitted to the two-tissue compartment model (2TCM) using population-based metabolite corrected IDIFs to calculate total and specific distribution volumes (VT, Vs) in key brain regions with early amyloid accumulation. Non-displaceable binding potential (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {BP}_{ND})$$\\end{document} was also calculated from the multi-reference tissue model (MRTM).ResultsAmyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {BP}_{ND}$$\\end{document} analysis. \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {BP}_{ND} $$\\end{document}and VT from kinetic models were correlated (r² = 0.46, P < 2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {e}^{-16})$$\\end{document} with a stronger positive correlation observed in amyloid-positive participants, indicating reliable model fits with the IDIFs. VT from 2TCM was highly correlated (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {r}^{2}$$\\end{document}= 0.65, P < 2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {e}^{-16}$$\\end{document}) with Logan graphical VT estimation.ConclusionNon-invasive quantification of amyloid binding from total-body 18F-florbetaben PET data is feasible using aorta IDIFs with high agreement between kinetic distribution volume parameters compared to \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {BP}_{ND} $$\\end{document}in amyloid-positive and amyloid-negative older individuals.

The association between posterior resting-state EEG alpha rhythms and functional MRI connectivity in older adults with subjective memory complaint

Resting-state eyes-closed electroencephalographic (rsEEG) alpha rhythms are dominant in posterior cortical areas in healthy adults and are abnormal in subjective memory complaint (SMC) persons with Alzheimer’s disease amyloidosis. This exploratory study in 161 SMC participants tested the relationships between those rhythms and seed-based resting-state functional magnetic resonance imaging (rs-fMRI) connectivity between thalamus and visual cortical networks as a function of brain amyloid burden, revealed by positron emission tomography and cognitive reserve, measured by educational attainment. The SMC participants were divided into 4 groups according to 2 factors: Education (Edu+ and Edu-) and Amyloid burden (Amy+ and Amy-). There was a statistical interaction (p < 0.05) between the two factors, and the subgroup analysis using estimated marginal means showed a positive association between the mentioned rs-fMRI connectivity and the posterior rsEEG alpha rhythms in the SMC participants with low brain amyloidosis and high CR (Amy-/Edu+). These results suggest that in SMC persons, early Alzheimer’s disease amyloidosis may contrast the beneficial effects of cognitive reserve on neurophysiological oscillatory mechanisms at alpha frequencies and connectivity between the thalamus and visual cortical networks.

Associations Between Mid-Life Psychosocial Measures and Estimated Late Life Amyloid Burden: The Atherosclerosis Risk in Communities (ARIC)-PET Study.

Psychosocial factors are modifiable risk factors for Alzheimer's disease (AD). One mechanism linking psychosocial factors to AD risk may be through biological measures of brain amyloid; however, this association has not been widely studied. To determine if mid-life measures of social support and social isolation in the Atherosclerosis Risk in Communities (ARIC) Study cohort are associated with late life brain amyloid burden, measured using florbetapir positron emission tomography (PET). Measures of social support and social isolation were assessed in ARIC participants (visit 2: 1990-1992). Brain amyloid was evaluated with florbetapir PET standardized uptake value ratios (SUVRs; visit 5: 2012-2014). Among 316 participants without dementia, participants with intermediate (odds ratio (OR), 0.47; 95% CI, 0.25-0.88), or low social support (OR, 0.43; 95% CI, 0.22-0.83) in mid-life were less likely to have elevated amyloid SUVRs, relative to participants with high social support. Participants with moderate risk for social isolation in mid-life (OR, 0.32; 95% CI, 0.14-0.74) were less likely to have elevated amyloid burden than participants at low risk for social isolation. These associations were not significantly modified by sex or race. Lower social support and moderate risk of social isolation in mid-life were associated with lower odds of elevated amyloid SUVR in late life, compared to participants with greater mid-life psychosocial measures. Future longitudinal studies evaluating mid-life psychosocial factors, in relation to brain amyloid as well as other health outcomes, will strengthen our understanding of the role of these factors throughout the lifetime.

NEIGHBORHOOD DISADVANTAGE, IMAGING BIOMARKERS OF ALZHEIMER’S DISEASE, AND COGNITION IN DIVERSE OLDER ADULTS

Abstract Neuroimaging biomarkers of Alzheimer’s disease (AD) are well-validated in White populations. However, it remains unclear how these biomarkers are associated with cognition in non-White populations disproportionately affected by systemic socioeconomic discrimination. We investigated whether neighborhood disadvantage modifies associations of neuroimaging biomarkers with cognition in a diverse cohort of 198 adults ≥50 years, 50% of whom are Black. Outcomes included cognitive impairment and neuropsychological test scores. Predictors were indices of neurodegeneration, vascular damage, and brain amyloid burden, quantified using MR-based measures of cortical thickness and white matter hyperintensities (WMH) and [11C]PiB PET, respectively. We measured neighborhood disadvantage using area deprivation index (ADI), a composite measurement of socioeconomic conditions in a census tract. In linear models, higher ADI, neurodegeneration, and WMH were separately associated with worse cognition. We found an ADI*neurodegeneration interaction on delayed recall memory (p=0.08). Neurodegeneration-positive participants had worse story delayed recall compared to neurodegeneration-negative regardless of ADI (β=-1.57, p=0.01). In neurodegeneration-negative participants, higher ADI is associated with worse delayed recall (β=-0.04, p=0.004): those with a high ADI exhibited low delayed recall, comparable to neurodegeneration-positive participants. ADI was not associated with cognition in neurodegeneration-positive participants. WMH and ADI interacted in models of impairment, visual memory, and visual copy (interaction p’s&amp;lt; 0.10). In those with high ADI, greater WMH was associated with worse cognition (β=-0.30, p=0.02) while participants with low ADI scored well regardless of WMH volume. Taken together, the relationship between neuroimaging biomarkers and cognition differs by neighborhood socioeconomic conditions, highlighting the need for clinical strategies that acknowledge structural disadvantage.

Prediction of cognitive decline in healthy aging based on neuropsychiatric symptoms and PET-biomarkers of Alzheimer's disease.

Neuropsychiatric symptoms (NPS) have been associated with a risk of accelerated cognitive decline or conversion to dementia of the Alzheimer's Disease (AD) type. Moreover, the NPS were also associated with higher AD biomarkers (brain tau and amyloid burden) even in non-demented patients. But the effect of the relationship between NPS and biomarkers on cognitive decline has not yet been studied. This work aims to assess the relationship between longitudinal cognitive changes and NPS, specifically depression and anxiety, in association with AD biomarkers in healthy middle-aged to older participants. The cohort consisted of 101 healthy participants aged 50-70years, 66 of whom had neuropsychological assessments of memory, executive functions, and global cognition at a 2-year follow-up. At baseline, NPS were assessed using the Beck Depression and Anxiety Inventories while brain tau and amyloid loads were measured using positron emission topography. For tau burden, THK5351 uptake is used as a proxy of tau and neuroinflammation. Participants, declining or remaining stable at follow-up, were categorized into groups for each cognitive domain. Group classification was investigated using binary logistic regressions based on combined AD biomarkers and the two NPS. The results showed that an association between anxiety and prefrontal amyloid burden significantly classified episodic memory decline, while the classification of global cognitive decline involved temporal and occipital amyloid burden but not NPS. Moreover, depression together with prefrontal and hippocampal tau burden were associated with a decline in memory. The classification of participants based on executive decline was related to depression and mainly prefrontal tau burden. These findings suggest that the combination of NPS and brain biomarkers of AD predicts the occurrence of cognitive decline in aging.

Lecanemab: A Humanized Monoclonal Antibody for the Treatment of Early Alzheimer Disease.

To review current pharmacology, pharmacokinetics/pharmacodynamics, safety, and efficacy of lecanemab in patients with Alzheimer disease. A literature search of PubMed (April 1, 2016-November 15, 2023) and ClinicalTrials.gov search were conducted using the following search terms: lecanemab and BAN2401. Additional articles were identified by hand from references. We included English-language clinical trials, randomized controlled trials, reviews, and systematic reviews evaluating lecanemab pharmacology, efficacy, or safety in humans for the management of Alzheimer disease. In the Clarity AD phase III trial, lecanemab led to a decrease in brain amyloid levels and showed moderate improvement in clinical measures of cognition and function. At 18 months, lecanemab 10 mg/kg biweekly exhibited a lower least squares mean change from baseline (1.21) compared to placebo (1.66) of Clinical Dementia Rating-Sum of Boxes score, signifying a significant difference of -0.45 (95% CI, -0.67 to -0.23; P < 0.001). In a subset of 698 participants, lecanemab reduced brain amyloid burden by -59.1 Centiloids (95% CI, -62.6 to -55.6). Lecanemab demonstrated favorable differences in Alzheimer Disease Assessment Scale-cognitive subscale 14, Alzheimer Disease Composite Score, and Alzheimer Disease Cooperative Study-Mild Cognitive Impairment-Activities of Daily Living scores. Adverse events included infusion-related reactions (26.4%) and amyloid-related imaging abnormalities (12.6%). Lecanemab reduces cognitive decline but raises concerns about intravenous administration, cost, and magnetic resonance imaging needs. Ongoing trials exploring subcutaneous dosing and positron emission tomography scans may offer solutions. Lecanemab is a humanized monoclonal antibody that is selective for soluble amyloid-beta (Aβ) aggregates. Lecanemab has exhibited a decrease in brain Aβ plaques and moderately less decline on clinical measures of cognitive function.

Predicting positron emission tomography brain amyloid positivity using interpretable machine learning models with wearable sensor data and lifestyle factors

BackgroundDeveloping a screening method for identifying individuals at higher risk of elevated brain amyloid burden is important to reduce costs and burden to patients in clinical trials on Alzheimer’s disease or the clinical setting. We developed machine learning models using objectively measured lifestyle factors to predict elevated brain amyloid burden on positron emission tomography.MethodsOur prospective cohort study of non-demented, community-dwelling older adults aged ≥ 65 years was conducted from August 2015 to September 2019 in Usuki, Oita Prefecture, Japan. One hundred and twenty-two individuals with mild cognitive impairment or subjective memory complaints (54 men and 68 women, median age: 75.50 years) wore wearable sensors and completed self-reported questionnaires, cognitive test, and positron emission tomography imaging at baseline. Moreover, 99 individuals in the second year and 61 individuals in the third year were followed up. In total, 282 eligible records with valid wearable sensors, cognitive test results, and amyloid imaging and data on demographic characteristics, living environments, and health behaviors were used in the machine learning models. Amyloid positivity was defined as a standardized uptake value ratio of ≥ 1.4. Models were constructed using kernel support vector machine, Elastic Net, and logistic regression for predicting amyloid positivity. The mean score among 10 times fivefold cross-validation repeats was utilized for evaluation.ResultsIn Elastic Net, the mean area under the receiver operating characteristic curve of the model using objectively measured lifestyle factors alone was 0.70, whereas that of the models using wearable sensors in combination with demographic characteristics and health and life environment questionnaires was 0.79. Moreover, 22 variables were common to all machine learning models.ConclusionOur machine learning models are useful for predicting elevated brain amyloid burden using readily-available and noninvasive variables without the need to visit a hospital.Trial registrationThis prospective study was conducted in accordance with the Declaration of Helsinki and was approved by the local ethics committee of Oita University Hospital (UMIN000017442). A written informed consent was obtained from all participants. This research was performed based on the Strengthening the Reporting of Observational Studies in Epidemiology reporting guideline.

Quantitative Transport Mapping Derived Tracer Velocity for Alzheimer’s Disease

AbstractBackgroundThe Alzheimer’s disease (AD), featured with extracellular beta‐amyloid plaque and intracellular tau tangles, are considered caused by the brain clearance function deficits. One anatomical representation of the fluid stasis is the enlargement of the perivascular space. Our hypothesis is that the fluid stasis will reduce the fluid velocity, and the reduced fluid velocity will drive the PET tracer slower than normal. We used the velocity map from our proposed quantitative transport mapping (QTM, L. Zhou MRM 2020.) to evaluate the PET tracer velocity in Alzheimer’s disease.MethodFifty‐seven subjects (age: 69.7±9.1, Female/male = 37/20, NL/MCI = 45/12) went through both 11C‐PIB and 18F‐MK‐6240 PET scan for Aβ and tau deposit measurements, and MRI scan for ROI parcellation. PIB SUVR, MK vCSF‐Slope (Y. Li Fluids Barriers CNS 2022), MK QTM are processed for the following analysis. Specifically, vCSF‐Slope was computed as the tracer turnover rate in lateral ventricle using the dynamic MK data between 10 to 30min, normalized by the whole brain AUC in 1 to 4min. QTM velocity was processed using the dynamic MK data between 40 to 55min using mass conservation equation. Regression model for predicting Aβ using QTM was conducted by controlling for age and sex. The relationship between QTM and vCSF was evaluated. The use of QTM to distinguish subjects groups are tested.ResultOur preliminary results showed that quantitative transport mapping(QTM) based on fluid mechanics is significantly associate the ventricular CSF clearance(vCSF) measured by dynamic PET data and brain amyloid(PiB PET). The regression model shows that cerebral cortex (GM) QTM velocity (p&lt;0.01, t = ‐2.76) and age (p&lt;0.05, t = 2.55) are significantly associated with the GM PIB SUVR as shown in Figure 1. This indicates that high Aβ deposit is associated with lower QTM velocity, i.e., clearance deficits. Figure 2 shows that in GM QTM velocity is correlated with the vCSF‐Slope (p&lt;0.05, r = 0.37). Figure 3 shows that QTM velocity in both GM and lateral ventricle are able to distinguish normal and MCI/AD groups.ConclusionThe tracer velocity in the brain tissue measured by QTM is associated with ventricular CSF turnover rate and brain amyloid burden. Acknowledgement: This study is supported by NIA grant AG057848

The effects of a 24‐weeks resistance exercise intervention on global brain amyloid beta levels: Preliminary results of AGUEDA randomized controlled trial

AbstractBackgroundAmyloid‐beta (Aβ) plaques are considered the initiating pathological hallmark of Alzheimer’s disease (AD). While animal studies suggest that physical exercise may have the potential to clear Aβ, there is limited research on humans, particularly in relation to resistance exercise. The aim of this study was to investigate the effect of a 24‐week resistance exercise program on brain Aβ accumulation in cognitively normal older adults.MethodThe study included 79 cognitively normal older adults with valid baseline and follow‐up data who were randomly assigned to either a 24‐weeks resistance exercise program (n = 42) or a wait‐list control group (n = 37) as part of the AGUEDA trial (NCT05186090) (Table 1). Participants underwent T1‐weighted Magnetic resonance imaging and [18F]Florbetaben amyloid‐PET (positron emission tomography) scans at baseline and after a 24‐weeks follow‐up period. Amyloid burden was quantified using the Centiloid (CL) method. Changes in amyloid burden between the groups were analyzed using analysis of covariance on an intention‐to‐treat basis including baseline CL values as covariateResultAt baseline, the CL for the entire sample was 7.27 ± 25.81, and the prevalence of amyloid positivity using a 12 CL cutoff was 21.5% (n = 17, 10 women), with no significant differences between exercise and control group (p = 0.120 and 0.399, respectively). The estimated marginal mean change after 6 months was 3.51 CL for the exercise group and 1.78 CL for the control group, with no significant differences between the groups (CL group difference: 1.73 ± 1.43 SE; z‐score = 0.032), 95% confidence interval (CI): ‐1.13 to 4.59, p = 0.233).ConclusionThe 24‐weeks resistance exercise program did not alter global amyloid brain burden in cognitively normal older adults. Further research with longer exercise interventions and different a manipulation of exercise parameters is needed to elucidate the role of exercise on brain amyloid burden in cognitively normal older adults.

Associations between gait velocity parameters and brain amyloid‐β levels in cognitive normal older adults: a cross‐sectional analysis from the AGUEDA trial

AbstractBackgroundAmyloid beta (Aβ) is a protein associated with dementia‐related pathologies such Alzheimer’s Disease (AD). The accumulation of Aβ in the brain leads to neurodegeneration, cognitive decline, and motor impairment. Those factors might appear years before the onset of apparent symptoms. There is evidence for an association between gait performance and Aβ levels. Previous studies showed that gait variability has been associated with amyloid in older adults with mild dementia. Moreover, reduced gait velocity, has been associated with greater brain Aβ accumulation in adults with spontaneous memory complaints. However, the nature of this relationship needs further investigation. Thus, the aim of this study was to examine the associations between gait velocity and gait velocity variability, and brain amyloid burden in cognitively normal older adults. Our hypothesis was that gait parameters might differently predict amyloid‐β levels.MethodEighty‐six cognitively normal older adults participated in this study. The Optogait system (Microgate,Italy) was used to assess gait parameters. Participants walked back and forth across a 5‐m long track made up of two bars set 1‐meter apart at their maximum walking pace for 5 minutes. The mean and coefficient of variation (CV) of gait velocity (m/s) were calculated as gait parameters. All participants underwent T1‐weighted MRI scans and [18F] Florbetaben amyloid‐PET (positron emission tomography) scans. PET images were quantified using the Centiloid (CL) method with a 12 CL cutoff for amyloid positivity. The associations between gait parameters and amyloid burden were assessed by individual linear regressions unadjusted and adjusted by age, sex, and education as covariates.ResultTable 1 shows descriptive characteristics of the participants (22% Aβ+; 19 participants). Results showed a positive trend for an association between gait variability and amyloid burden (unadjusted: β = 0.21, p = 0.05; adjusted: β = 0.20, p = 0.08). There was no association between gait velocity and amyloid burden (unadjusted: β = ‐0.08, p = 0.42; adjusted: β = ‐0.08, p = 0.54).ConclusionGreater gait velocity variability, but not gait velocity, was marginally associated with higher amyloid burden. This result suggests that gait velocity variability might be an important marker of amyloid burden in cognitively normal older adults.

Sensitivity of NIH Toolbox‐Cognition Battery task performance to amyloid positivity status in cognitively normal older adults

AbstractBackgroundAmong cognitively normal older adults, high brain amyloid burden may signal the presence of early Alzheimer’s disease processes. While research has shown subtle neuropsychological performance differences among cognitively intact older adults with and without elevated brain amyloid, early investigation has not found similar between‐group differences on the NIH Toolbox‐Cognition Battery (NIHTB‐CB; Snitz et al., 2020). Here, we utilize data from a longitudinal observational driving study to evaluate potential differences in NIHTB‐CB task performance among older adults determined to be cognitively normal via clinical research consensus, based on brain amyloid status.MethodData from cognitively normal adults age 65+ who completed an amyloid Positron Emission Tomography scan, NIHTB‐CB tasks, and additional neuropsychological testing through the Michigan Alzheimer’s Disease Research Center were analyzed. Amyloid positivity was determined based on a centiloid scale (≤10 indicating amyloid negativity; ≥20 amyloid positivity). Thirty participants were amyloid negative and 17 were amyloid positive. Nine individuals with intermediate amyloid values were excluded. Group differences in NIHTB‐CB performance were analyzed via independent sample t‐tests. Linear regressions were used to assess demographic and NIHTB‐CB task/neuropsychological performance predictors of amyloid positivity.ResultThere were no demographic differences between the groups. Overall, amyloid negative participants outperformed their amyloid positive peers on NIHTB‐CB List Sorting and backward Digit Span tasks (p’s&lt;0.05), both of which are measures of working memory. There were no other group differences in cognitive performance, including episodic memory. The final NIHTB‐CB regression model only included NIHTB List Sorting, which accounted for 16.2% of the variance in amyloid status (F = 8.69, p = 0.005). Digit Span backward similarly accounted for 16.6% of the variance in amyloid status (F = 6.39, p = 0.017).ConclusionAmong cognitively normal older adults with known amyloid status, working memory performance, but not episodic memory performance, differentiated amyloid positive and negative groups. This is consistent with research demonstrating an association between elevated amyloid and executive dysfunction, but not memory impairment, in cognitively normal adults (Tideman et al., 2022). NIHTB‐CB’s List Sorting Working Memory is a complex, challenging sequencing task that appears sensitive to amyloid positivity in older adults and task performance may serve as a marker for early prediction of Alzheimer’s disease.

CSF Biomarkers and [18F]flutemetamol PET‐Derived Centiloids in Patients with SCD or MCI

AbstractBackgroundCSF biomarkers are well characterised as surrogate markers for amyloid deposition and neurofibrillary tau tangles reflecting pathological features of Alzheimer’s disease. Amyloid PET images provide a visual and quantitative assessment of brain amyloid burden. In diagnostic workup these biomarkers are considered interchangeable, however their relationship is not fully understood.MethodCentiloid (CL) values for 387 [18F]flutemetamol images from the Swedish BioFINDER I study were derived following the methods of Klunk et.al. (Alzheimer’s &amp; Dementia, 2015). Subjects, comprising Controls, SCD and MCI (Table 1), were ranked by Centiloid values (lowest to highest) and the average for each consecutive group of 30 subjects calculated. Corresponding CSF biomarker values (Aß42/40 and pTau181) were plotted for each group.ResultSubjects in groups averaging ‐7.7 CL to 29.0 CL had a mean(±SD) Aß 42/40 ratio of 0.144 (±0.033, range 0.051 to 0.236, n = 240) with no statistically significant differences between groups (Fig. 1A). A statistically significant fall in CSF Aß42/40 ratio between the 29.0 CL and 47.3 CL groups (from 0.134 (+0.041, 0.066 to 0.236) to 0.088(+0.031, 0.045 to 0.183), p&lt;0.0001) was observed. The average CSF Aß42/40 ratio value for all subjects ranging from 66.3 Cl to129.8 CL was 0.072 (±0.017, 0.030 to 0.127, n = 117) with no statistically significant difference in CSF levels across these CL bands. Subjects in the groups averaging ‐7.7 CL to 29.0 CL had a mean(±SD) pTau181 value of 48.9 pg/mL (±15.9, 22 to 138) with no statistically significant difference between groups (Fig. 1B). A statistically significant (p&lt;0.05) increase between 29.0 CL (47.3±19.3, 24 to 116 pg/mL) and 47.3 CL groups (67.8±29.4, 24 to 175 pg/mL) was observed. For all Subjects from 66.3 CL to129.8 CL mean pTau181 levels were 79.6 (±30.3, 32 to 209 pg/mL) with no statistically significant difference across these CL bands.ConclusionComparison of [18F]flutemetamol image quantitation and CSF biomarkers indicates CSF Aß42/40 and pTau181 starts to show amyloid positivity at approximately 30‐40 CL units. Recent comparisons between visual rating and Centiloids from PET imaging indicate visual positivity from approximately 20 CL units indicating sensitivity of amyloid PET imaging for the detection of early amyloid deposition.

CSF Biomarkers and [18F]flutemetamol PET‐Derived Centiloids in Patients with SCD or MCI

AbstractBackgroundCSF biomarkers are well characterised as surrogate markers for amyloid deposition and neurofibrillary tau tangles reflecting pathological features of Alzheimer’s disease. Amyloid PET images provide a visual and quantitative assessment of brain amyloid burden. In diagnostic workup these biomarkers are considered interchangeable, however their relationship is not fully understood.MethodsCentiloid (CL) values for 387 [18F]flutemetamol images from the Swedish BioFINDER I study were derived following the methods of Klunk et.al. (Alzheimer’s &amp; Dementia, 2015). Subjects, comprising Controls, SCD and MCI (Table 1), were ranked by Centiloid values (lowest to highest) and the average for each consecutive group of 30 subjects calculated. Corresponding CSF biomarker values (Aβ42/40 and pTau181) were plotted for each group.ResultsSubjects in groups averaging ‐7.7 CL to 29.0 CL had a mean(±SD) Aβ 42/40 ratio of 0.144 (±0.033, range 0.051 to 0.236, n = 240) with no statistically significant differences between groups (Fig. 1A). A statistically significant fall in CSF Aβ42/40 ratio between the 29.0 CL and 47.3 CL groups (from 0.134 (±0.041, 0.066 to 0.236) to 0.088(±0.031, 0.045 to 0.183), p&lt;0.0001) was observed. The average CSF Aβ42/40 ratio value for all subjects ranging from 66.3 Cl to129.8 CL was 0.072 (±0.017, 0.030 to 0.127, n = 117) with no statistically significant difference in CSF levels across these CL bands.Subjects in the groups averaging ‐7.7 CL to 29.0 CL had a mean(±SD) pTau181 value of 48.9 pg/mL (±15.9, 22 to 138) with no statistically significant difference between groups (Fig. 1B). A statistically significant (p&lt;0.05) increase between 29.0 CL (47.3±19.3, 24 to 116 pg/mL) and 47.3 CL groups (67.8±29.4, 24 to 175 pg/mL) was observed. For all Subjects from 66.3 CL to129.8 CL mean pTau181 levels were 79.6 (±30.3, 32 to 209 pg/mL) with no statistically significant difference across these CL bands.ConclusionsComparison of [18F]flutemetamol image quantitation and CSF biomarkers indicates CSF Aβ42/40 and pTau181 starts to show amyloid positivity at approximately 30‐40 CL units. Recent comparisons between visual rating and Centiloids from PET imaging indicate visual positivity from approximately 20 CL units indicating sensitivity of amyloid PET imaging for the detection of early amyloid deposition.

Clinical and biological relevance of glial fibrillary acidic protein in Alzheimer’s disease

IntroductionThere is a tremendous need for identifying reliable blood-based biomarkers for Alzheimer’s disease (AD) that are tied to the biological ATN (amyloid, tau and neurodegeneration) framework as well as clinical assessment and progression.MethodsOne hundred forty-four elderly participants underwent 18F-AV45 positron emission tomography (PET) scan, structural magnetic resonance imaging (MRI) scan, and blood sample collection. The composite standardized uptake value ratio (SUVR) was derived from 18F-AV45 PET to assess brain amyloid burden, and the hippocampal volume was determined from structural MRI scans. Plasma glial fibrillary acidic protein (GFAP), phosphorylated tau-181 (ptau-181), and neurofilament light (NfL) measured by single molecular array (SIMOA) technology were assessed with respect to ATN framework, genetic risk factor, age, clinical assessment, and future functional decline among the participants.ResultsAmong the three plasma markers, GFAP best discriminated participants stratified by clinical diagnosis and brain amyloid status. Age was strongly associated with NfL, followed by GFAP and ptau-181 at much weaker extent. Brain amyloid was strongly associated with plasma GFAP and ptau-181 and to a lesser extent with plasma NfL. Moderate association was observed between plasma markers. Hippocampal volume was weakly associated with all three markers. Elevated GFAP and ptau-181 were associated with worse cognition, and plasma GFAP was the most predictive of future functional decline. Combining GFAP and ptau-181 together was the best model to predict brain amyloid status across all participants (AUC = 0.86) or within cognitively impaired participants (AUC = 0.93); adding NfL as an additional predictor only had a marginal improvement.ConclusionOur findings indicate that GFAP is of potential clinical utility in screening amyloid pathology and predicting future cognitive decline. GFAP, NfL, and ptau-181 were moderately associated with each other, with discrepant relevance to age, sex, and AD genetic risk, suggesting their relevant but differential roles for AD assessment. The combination of GFAP with ptau-181 provides an accurate model to predict brain amyloid status, with the superior performance of GFAP over ptau-181 when the prediction is limited to cognitively impaired participants.

Associations Between Amyloid Burden, Hypoxemia, Sleep Architecture, and Cognition in Obstructive Sleep Apnea.

Obstructive sleep apnea (OSA) is associated with an increased risk of amyloid-β (Aβ) burden, the hallmark of Alzheimer's disease, and cognitive decline. To determine the differential impacts of hypoxemia and slow-wave sleep disruption on brain amyloid burden, and to explore the effects of hypoxemia, slow-wave sleep disruption, and amyloid burden on cognition in individuals with and without OSA. Thirty-four individuals with confirmed OSA (mean±SD age 57.5±4.1 years; 19 males) and 12 healthy controls (58.5±4.2 years; 6 males) underwent a clinical polysomnogram, a NAV4694 positron emission tomography (PET) scan for Aβ burden, assessment of APOEɛ status and cognitive assessments. Linear hierarchical regressions were conducted to determine the contributions of demographic and sleep variables on amyloid burden and cognition. Aβ burden was associated with nocturnal hypoxemia, and impaired verbal episodic memory, autobiographical memory and set shifting. Hypoxemia was correlated with impaired autobiographical memory, and only set shifting performance remained significantly associated with Aβ burden when controlling for sleep variables. Nocturnal hypoxemia was related to brain Aβ burden in this sample of OSA participants. Aβ burden and hypoxemia had differential impacts on cognition. This study reveals aspects of sleep disturbance in OSA that are most strongly associated with brain Aβ burden and poor cognition, which are markers of early Alzheimer's disease. These findings add weight to the possibility that hypoxemia may be causally related to the development of dementia; however, whether they may be a therapeutic target for dementia prevention in OSA is yet to be determined.

P101 Brain Amyloid Burden and Autobiographical Memory in Obstructive Sleep Apnoea: A Cross-sectional Study.

Abstract Introduction Emerging literature reports an increased risk of Alzheimer’s disease in individuals with obstructive sleep apnoea (OSA). Established characteristics of Alzheimer’s disease include increased brain amyloid burden and impairment to episodic and autobiographical memory. Investigating these constructs in individuals with clinically confirmed OSA will contribute to understanding of OSA and neuronal implications. Aim The aim of the study was to explore the relationship between brain amyloid burden and autobiographical memory in cognitively-healthy individuals with OSA. Methods Thirty-four participants with OSA (mean age=57.7, SD=8.5, 19 males), and 12 controls (mean age=57.1, SD=8.1, 6 males) participated in the study. Participants underwent a 11C-PiB positron emission tomography (PET) scan to quantify amyloid burden, and an assessment of autobiographical memory. Brain amyloid burden was quantified using the standardised uptake value ratio (SUVR), and the Autobiographical Memory Test (AMT) was used to assess the ability of participants to recall specific memories from their life. Results Individuals with OSA recalled significantly fewer specific autobiographical memories (M=6.66, SD=2.91) compared to controls (M=10.25, SD=2.09, t(45)=-3.930, p&amp;lt;.001). There was no significant difference in SUVR between groups, t(44)=1.465, p=.150. Recall of non-specific memories was significantly positively correlated with SUVR, r=.331, p=.026. Discussion Levels of brain amyloid burden did not differ significantly between groups however the results support existing literature suggesting amyloid burden is associated with autobiographical memory in individuals with OSA. Longitudinal studies investigating the trajectory of these constructs in the context of disease development should be conducted to further explore the impacts of OSA.

Association of Sleep Disturbances With Brain Amyloid and Tau Burden, Cortical Atrophy, and Cognitive Dysfunction Across the AD Continuum.

Patients with Alzheimer disease (AD) frequently suffer from various sleep disturbances. However, how sleep disturbance is associated with AD and its progression remains poorly investigated. We investigated the association of total sleep time with brain amyloid and tau burden, cortical atrophy, cognitive dysfunction, and their longitudinal changes in the AD spectrum. In this retrospective cohort study, we enrolled participants on the AD spectrum who were positive on 18F-florbetaben (FBB) PET. All participants underwent the Pittsburgh Sleep Quality Index, brain MRI, FBB PET, 18F-flortaucipir (FTP) PET, and detailed neuropsychological testing. In addition, a subset of participants completed follow-up assessments. We analyzed the association of total sleep time with the baseline and longitudinal FBB-standardized uptake value ratio (SUVR), FTP-SUVR, cortical thickness, and cognitive domain composite scores. We examined 138 participants on the AD spectrum (15 with preclinical AD, 62 with prodromal AD, and 61 with AD dementia; mean age 73.4 ± 8.0 years; female 58.7%). Total sleep time was longer in the AD dementia group (7.4 ± 1.6 hours) compared with the preclinical (6.5 ± 1.4 hours; p = 0.026) and prodromal groups (6.6 ± 1.4 hours; p = 0.001), whereas other sleep parameters did not differ between groups. Longer total sleep time was not associated with amyloid accumulation but rather with tau accumulation, especially in the amygdala, hippocampus, basal forebrain, insular, cingulate, occipital, inferior temporal cortices, and precuneus. Longer total sleep time predicted faster tau accumulation in Braak regions V-VI (β = 0.016, p = 0.007) and disease progression to mild cognitive impairment or dementia (hazard ratio = 1.554, p = 0.024). Longer total sleep time was also associated with memory deficit (β = -0.19, p = 0.008). Prolonged total sleep time was associated with tau accumulation in sleep-related cortical and subcortical areas as well as memory dysfunction. It also predicted faster disease progression with tau accumulation. Our study highlights the clinical importance of assessing total sleep time as a marker for disease severity and prognosis in the AD spectrum.

Objective sleep was longitudinally associated with brain amyloid burden in mild cognitive impairment.

Understanding the longitudinal association of objective sleep and physical activity with brain amyloid burden and cortical glucose metabolism has critical clinical and public health implications for dementia prevention in later life. We enrolled 118 individuals aged ≥65 years with mild cognitive impairment, who were followed up on from August 2015 to September 2019. All participants continuously wore an accelerometer sensor for 7 consecutive days every 3 months and received annual 11 C-Pittsburgh compound-B and 18 F-fluorodeoxyglucose positron emission tomography (PET). Sleep and physical activity parameters were assessed using accelerometer sensor data andPET imaging was quantified using a standardized uptake-value ratio. Fifty-seven participants (48.3%) completed a lifestyle factor assessment and PET imaging over the 3-year period. A linear mixed-effects model was applied to examine the longitudinal association of sleep and physical activity parameters with PET imaging over the 3-year period, controlling for potential confounders. Sleep efficiency was inversely associated with amyloid uptake in the frontal lobe. Although sleep duration was positively associated with global amyloid uptake, particularly in the frontal lobe, their impact was extremely small. However, physical activity parameters were not significantly associated with the 11 C-Pittsburgh compound-B-uptake. Furthermore, sleep and physical activity parameters were not significantly associated with cortical glucose metabolism. Lower sleep efficiency could be an early symptom of greater brain amyloid burden at the mild cognitive impairment stage. Therefore, the assessment of sleep may be useful for identifying individuals at higher risk for brain amyloid burden. Future longer term observational studies are required to confirm these findings.