Self-reported mid- to late-life physical and recreational activities: Associations with late-life cognition.

OBJECTIVE: Physical and recreational activities are behaviors that may modify risk of late-life cognitive decline. We sought to examine the role of retrospectively self-reported midlife (age 40) physical and recreational activity engagement - and self-reported change in these activities from age 40 to initial study visit - in predicting late-life cognition. METHOD: Data were obtained from 898 participants in a longitudinal study of cognitive aging in demographically and cognitively diverse older adults (Age: range = 49-93 years, M = 75, SD = 7.19). Self-reported physical and recreational activity participation at age 40 and at the initial study visit were quantified using the Life Experiences Assessment Form. Change in activities was modeled using latent change scores. Cognitive outcomes were obtained annually (range = 2-17 years) using the Spanish and English Neuropsychological Assessment Scales, which measure verbal episodic memory, semantic memory, visuospatial processing, and executive functioning. RESULTS: Physical activity engagement at age 40 was strongly associated with cognitive performance in all four domains at the initial visit and with global cognitive slope. However, change in physical activities after age 40 was not associated with cognitive outcomes. In contrast, recreational activity engagement - both at age 40 and change after 40 - was predictive of cognitive intercepts and slope. CONCLUSIONS: Retrospectively self-reported midlife physical and recreational activity engagement were strongly associated with late-life cognition - both level of performance and rate of future decline. However, the data suggest that maintenance of recreational activity engagement (e.g., writing, taking classes, reading) after age 40 is more strongly associated with late-life cognition than continued maintenance of physical activity levels.

A novel neuroimaging signature for ADRD risk stratification in the community.

INTRODUCTION: Early risk stratification for clinical dementia could lead to preventive therapies. We identified and validated a magnetic resonance imaging (MRI) signature for Alzheimer's disease (AD) and related dementias (ARDR). METHODS: An MRI ADRD signature was derived from cortical thickness maps in Framingham Heart Study (FHS) participants with AD dementia and matched controls. The signature was related to the risk of ADRD and cognitive function in FHS. Results were replicated in the University of California Davis Alzheimer's Disease Research Center (UCD-ADRC) cohort. RESULTS: Participants in the bottom quartile of the signature had more than three times increased risk for ADRD compared to those in the upper three quartiles (P < 0.001). Greater thickness in the signature was related to better general cognition (P < 0.01) and episodic memory (P = 0.01). Results replicated in UCD-ADRC. DISCUSSION: We identified a robust neuroimaging biomarker for persons at increased risk of ADRD. Other cohorts will further test the validity of this biomarker.

Racial and ethnic differences in the association between depressive symptoms and cognitive outcomes in older adults: Findings from KHANDLE and STAR.

INTRODUCTION: Depressive symptoms are associated with higher risk of dementia, but how they impact cognition in diverse populations is unclear. METHODS: Asian, Black, Latino, or White participants (n = 2227) in the Kaiser Healthy Aging and Diverse Life Experiences (age 65+) and the Study of Healthy Aging in African Americans (age 50+) underwent up to three waves of cognitive assessments over 4 years. Multilevel models stratified by race/ethnicity were used to examine whether depressive symptoms were associated with cognition or cognitive decline and whether associations differed by race/ethnicity. RESULTS: Higher depressive symptoms were associated with lower baseline verbal episodic memory scores (-0.06, 95% CI: -0.12, -0.01; -0.15, 95% CI: -0.25, -0.04), and faster decline annually in semantic memory (-0.04, 95% CI: -0.07, -0.01; -0.10, 95% CI: -0.15, -0.05) for Black and Latino participants. Depressive symptoms were associated with lower baseline but not decline in executive function. DISCUSSION: Depressive symptoms were associated with worse cognitive outcomes, with some evidence of heterogeneity across racial/ethnic groups. HIGHLIGHTS: We examined whether baseline depressive symptoms were differentially associated with domain-specific cognition or cognitive decline by race/ethnicity. Depressive symptoms were associated with worse cognitive scores for all racial/ethnic groups across different domains examined. Higher depressive symptoms were associated with faster cognitive decline for semantic memory for Black and Latino participants. The results suggest a particularly harmful association between depressive symptoms and cognition in certain racial/ethnic groups.

Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients.

INTRODUCTION: White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-ß1-42 (Aß42)-positive status. METHODS: Individual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume. RESULTS: VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and Aß42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001). DISCUSSION: Vascular risk factors and Aß42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and Aß42 pathology affect the brain's white matter. HIGHLIGHTS: Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aß42 status in 11 memory clinic cohorts. Aß42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns.

Vascular Risk Predicts Plasma Amyloid ß 42/40 Through Cerebral Amyloid Burden in Apolipoprotein E ε4 Carriers.

BACKGROUND: Understanding the neurobiological underpinnings between established multimodal dementia risk factors and noninvasive blood-based biomarkers may lead to greater precision and earlier identification of older adults at risk of accelerated decline and dementia. We examined whether key vascular and genetic risk impact the association between cerebral amyloid burden and plasma aß (amyloid ß) 42/40 in nondemented older adults. METHODS: We used nondemented older adults from the UCD-ADRC (University of California, Davis-Alzheimer's Disease Research Center) study (n=96) and Alzheimer's Disease Neuroimaging Initiative (n=104). Alzheimer's Disease Neuroimaging Initiative was examined as confirmatory study cohort. We followed a cross-sectional design and examined linear regression followed by mediation analyses. Vascular risk score was obtained as the sum of hypertension, diabetes, hyperlipidemia, coronary artery disease, and cerebrovascular disease. Apolipoprotein E (APOE) ε4+ risk was genotyped, and plasma aß42 and aß40 were assayed. Cerebral amyloid burden was quantified using Florbetapir-PET scans. Baseline age was included as a covariate in all models. RESULTS: Vascular risk significantly predicted cerebral amyloid burden in Alzheimer's Disease Neuroimaging Initiative but not in the UCD-ADRC cohort. Cerebral amyloid burden was associated with plasma aß 42/40 in both cohorts. Higher vascular risk increased cerebral amyloid burden was indirectly associated with reduced plasma aß 42/40 in Alzheimer's Disease Neuroimaging Initiative but not in UCD-ADRC cohort. However, when stratified by APOE ε4+ risk, we consistently observed this indirect relationship only in APOE ε4+ carriers across both cohorts. CONCLUSIONS: Vascular risk is indirectly associated with the level of plasma aß 42/40 via cerebral amyloid burden only in APOE ε4+ carriers. Nondemented older adults with genetic vulnerability to dementia and accelerated decline may benefit from careful monitoring of vascular risk factors directly associated with cerebral amyloid burden and indirectly with plasma aß 42/40.

Toward a statistical validation of brain signatures as robust measures of behavioral substrates.

The "brain signature of cognition" concept has garnered interest as a data-driven, exploratory approach to better understand key brain regions involved in specific cognitive functions, with the potential to maximally characterize brain substrates of behavioral outcomes. Previously we presented a method for computing signatures of episodic memory. However, to be a robust brain measure, the signature approach requires a rigorous validation of model performance across a variety of cohorts. Here we report validation results and provide an example of extending it to a second behavioral domain. In each of two discovery data cohorts, we derived regional brain gray matter thickness associations for two domains: neuropsychological and everyday cognition memory. We computed regional association to outcome in 40 randomly selected discovery subsets of size 400 in each cohort. We generated spatial overlap frequency maps and defined high-frequency regions as "consensus" signature masks. Using separate validation datasets, we evaluated replicability of cohort-based consensus model fits and explanatory power by comparing signature model fits with each other and with competing theory-based models. Spatial replications produced convergent consensus signature regions. Consensus signature model fits were highly correlated in 50 random subsets of each validation cohort, indicating high replicability. In comparisons over each full cohort, signature models outperformed other models. In this validation study, we produced signature models that replicated model fits to outcome and outperformed other commonly used measures. Signatures in two memory domains suggested strongly shared brain substrates. Robust brain signatures may therefore be achievable, yielding reliable and useful measures for modeling substrates of behavioral domains.

Strategic white matter hyperintensity locations for cognitive impairment: A multicenter lesion-symptom mapping study in 3525 memory clinic patients.

INTRODUCTION: Impact of white matter hyperintensities (WMH) on cognition likely depends on lesion location, but a comprehensive map of strategic locations is lacking. We aimed to identify these locations in a large multicenter study. METHODS: Individual patient data (n = 3525) from 11 memory clinic cohorts were harmonized. We determined the association of WMH location with attention and executive functioning, information processing speed, language, and verbal memory performance using voxel-based and region of interest tract-based analyses. RESULTS: WMH in the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus were significantly related to domain-specific impairment, independent of total WMH volume and atrophy. A strategic WMH score based on these tracts inversely correlated with performance in all domains. DISCUSSION: The data show that the impact of WMH on cognition is location-dependent, primarily involving four strategic white matter tracts. Evaluation of WMH location may support diagnosing vascular cognitive impairment. HIGHLIGHTS: We analyzed white matter hyperintensities (WMH) in 3525 memory clinic patients from 11 cohorts The impact of WMH on cognition depends on location We identified four strategic white matter tracts A single strategic WMH score was derived from these four strategic tracts The strategic WMH score was an independent determinant of four cognitive domains.

A robust brain signature region approach for episodic memory performance in older adults.

The brain signature concept aims to characterize brain regions most strongly associated with an outcome of interest. Brain signatures derive their power from data-driven searches that select features based solely on performance metrics of prediction or classification. This approach has important potential to delineate biologically relevant brain substrates for prediction or classification of future trajectories. Recent work has used exploratory voxel-wise or atlas-based searches, with some using machine learning techniques to define salient features. These have shown undoubted usefulness, but two issues remain. The preponderance of recent work has been aimed at categorical rather than continuous outcomes, and it is rare for non-atlas reliant voxel-based signatures to be reported that would be useful for modelling and hypothesis testing. We describe a cross-validated signature region model for structural brain components associated with baseline and longitudinal episodic memory across cognitively heterogeneous populations including normal, mild impairment and dementia. We used three non-overlapping cohorts of older participants: from the UC Davis Aging and Diversity cohort (n = 255; mean age 75.3 ± 7.1 years; 128 cognitively normal, 97 mild cognitive impairment, 30 demented and seven unclassified); from Alzheimer's Disease Neuroimaging Initiative (ADNI) 1 (n = 379; mean age 75.1 ± 7.2; 82 cognitively normal, 176 mild cognitive impairment, 121 Alzheimer's dementia); and from ADNI2/GO (n = 680; mean age 72.5 ± 7.1; 220 cognitively normal, 381 mild cognitive impairment and 79 Alzheimer's dementia). We used voxel-wise regression analysis, correcting for multiple comparisons, to generate an array of regional masks corresponding to different association strength levels of cortical grey matter with baseline memory and brain atrophy with memory change. Cognitive measures were episodic memory using Spanish and English Neuropsychological Assessment Scales instruments for UC Davis and ADNI-Mem for ADNI 1 and ADNI2/GO. Performance metric was the adjusted R2 coefficient of determination of each model explaining outcomes in two cohorts other than where it was computed. We compared within-cohort performances of signature models against each other and against other recent signature models of episodic memory. Findings were: (i) two independently generated signature region of interest models performed similarly in a third separate cohort; (ii) a signature region of interest generated in one imaging cohort replicated its performance level when explaining cognitive outcomes in each of other, separate cohorts; and (iii) this approach better explained baseline and longitudinal memory than other recent theory-driven and data-driven models. This suggests our approach can generate signatures that may be easily and robustly applied for modelling and hypothesis testing in mixed cognition cohorts.

Comparison of Education and Episodic Memory as Modifiers of Brain Atrophy Effects on Cognitive Decline: Implications for Measuring Cognitive Reserve.

OBJECTIVE: This study compared the level of education and tests from multiple cognitive domains as proxies for cognitive reserve. METHOD: The participants were educationally, ethnically, and cognitively diverse older adults enrolled in a longitudinal aging study. We examined independent and interactive effects of education, baseline cognitive scores, and MRI measures of cortical gray matter change on longitudinal cognitive change. RESULTS: Baseline episodic memory was related to cognitive decline independent of brain and demographic variables and moderated (weakened) the impact of gray matter change. Education moderated (strengthened) the gray matter change effect. Non-memory cognitive measures did not incrementally explain cognitive decline or moderate gray matter change effects. CONCLUSIONS: Episodic memory showed strong construct validity as a measure of cognitive reserve. Education effects on cognitive decline were dependent upon the rate of atrophy, indicating education effectively measures cognitive reserve only when atrophy rate is low. Results indicate that episodic memory has clinical utility as a predictor of future cognitive decline and better represents the neural basis of cognitive reserve than other cognitive abilities or static proxies like education.

Differential Item Functioning of the Everyday Cognition (ECog) Scales in Relation to Racial/Ethnic Groups.

OBJECTIVE: The Everyday Cognition (ECog) scales measure cognitively based across domains of everyday abilities that are affected early in the course of neurodegenerative disorders such as Alzheimer's disease. However, the degree to which the ECog may be differentially influenced by ethnic/racial background is unknown. This study evaluates measurement invariance of the ECog across non-Hispanic White (NHW), Black, and Hispanic individuals. METHODS: Participants included 1177 NHW, 243 Black, and 216 Hispanic older adults from the UC Davis Alzheimer's Disease Center Cohort who had an ECog. Differential item functioning (DIF) for each ECog domain was evaluated separately for Black and Hispanic participants compared to NHW participants. An iterative multiple group confirmatory factor analysis approach for ordinal scores was used to identify items whose measurement properties differed across groups and to adjust scores for DIF. Adjusted scores were then evaluated to test whether they were more strongly associated with cognitive function (concurrent and longitudinal change in cognition) and brain volumes (measured by brain imaging). RESULTS: Varying levels, patterns, and impacts of DIF were found across domains and groups. However, the impact of DIF was relatively small, and DIF effects on scores generally were less than one-half standard error of measurement. There were no meaningful differences in associations with cognition and brain injury between DIF adjusted and unadjusted scores. CONCLUSIONS: Varying patterns of DIF were observed across the Black and Hispanic participants across select ECog domains. Overall, DIF effects were relatively small and did not change the relationship between the ECog and other indicators of disease.

Aortic Stiffness, Increased White Matter Free Water, and Altered Microstructural Integrity: A Continuum of Injury.

BACKGROUND AND PURPOSE: Previous reports from the Framingham Heart Study have identified cross-sectional associations of arterial stiffness, as reflected by carotid-femoral pulse wave velocity (CFPWV) and systolic blood pressure with vascular brain injury. The purpose of this study is to examine free water (FW), fractional anisotropy (FA), and white matter hyperintensities (WMH) in relation to arterial stiffness among subjects of the Framingham Offspring and Third-Generation cohorts. METHODS: In 2422 participants aged 51.3±11.6 years, FA, FW, and WMH were related to CFPWV using voxel-based linear and generalized linear regressions, adjusting for relevant covariables. Mean FW, mean FA, and WMH burden (log transformed) were computed within white matter (WM) region and related to systolic blood pressure and CFPWV using multiple mediation analyses. RESULTS: CFPWV was found to be associated with higher FW, lower FA, and higher WMH incidence in WM areas covering, respectively, 356.1, 211.8, and 10.9 mL of the WM mask. Mediation analyses revealed that the effect of systolic blood pressure on FW was mediated by CFPWV (direct and indirect effects: a=0.040; P<0.001, and a'=0.020; P>0.05). Moreover, the effect of CFPWV on FA was mediated by FW (direct and indirect effects: b=-0.092; P<0.001, and b'=0.012; P>0.05), whose effect on WMH was, in turn, mediated by FA (direct and indirect effects: c=0.246; P<0.001, and c'=0.116; P>0.05). CONCLUSIONS: From these data, we propose a biomechanical hypothesis designed for future research experiments to explain how hemodynamic alteration may lead to WM injury by impacting cerebral water content and more subtly WM integrity, to finally lead to WMH development.

Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2.

INTRODUCTION: Alzheimer's Disease Neuroimaging Initiative (ADNI) is now in its 10th year. The primary objective of the magnetic resonance imaging (MRI) core of ADNI has been to improve methods for clinical trials in Alzheimer's disease (AD) and related disorders. METHODS: We review the contributions of the MRI core from present and past cycles of ADNI (ADNI-1, -Grand Opportunity and -2). We also review plans for the future-ADNI-3. RESULTS: Contributions of the MRI core include creating standardized acquisition protocols and quality control methods; examining the effect of technical features of image acquisition and analysis on outcome metrics; deriving sample size estimates for future trials based on those outcomes; and piloting the potential utility of MR perfusion, diffusion, and functional connectivity measures in multicenter clinical trials. DISCUSSION: Over the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in AD and will continue to do so in the future.

White matter hyperintensities and their penumbra lie along a continuum of injury in the aging brain.

BACKGROUND AND PURPOSE: Aging is accompanied by clinically silent cerebral white matter injury identified through white matter hyperintensities (WMHs) on fluid-attenuated inversion recovery (FLAIR)- and diffusion tensor imaging-based measures of white matter integrity. The temporal course of FLAIR and diffusion tensor imaging changes within WMHs and their less-injured periphery (ie, their penumbra), however, has not been fully studied. We used longitudinal diffusion tensor imaging and FLAIR to explore these changes. METHODS: One hundred fifteen participants, aged 73.7±6.7 years, received clinical evaluations and MRIs on 2 dates. WMHs and fractional anisotropy (FA) maps were produced from FLAIR and diffusion tensor imaging and coregistered to a standardized space. Each distinct WMH was categorized as growing, stagnant, or noncontiguous incident. The penumbra of each WMH was similarly categorized as corresponding to a stagnant, growing, or noncontiguous incident WMH. Linear mixed-effect models were used to assess whether FA and FLAIR measurements changed between baseline and follow-up and differed between tissue categories. RESULTS: Baseline FA differed significantly by tissue category, with the following ordering of categories from highest to lowest FA: penumbra of noncontiguous incident, then stagnant, then growing WMHs; noncontiguous incident, then stagnant, then growing WMHs. Despite differences in baseline values, all tissue categories experienced declines in FA over time. Only noncontiguous incident WMHs showed significant FLAIR signal increases over time, and FLAIR signal significantly decreased in stagnant WMHs. CONCLUSIONS: WMHs and their penumbra vary in severity and together span a continuous spectrum of white matter injury that worsens with time. FLAIR fails to capture this continuous injury process fully but does identify a subclass of lesions that seem to improve over time.

Trends in Intracranial and Cerebral Volumes of Framingham Heart Study Participants Born 1930 to 1970.

Importance: Human brain development and maintenance is under both genetic and environmental influences that likely affect later-life dementia risk. Objective: To examine environmental influences by testing whether time-dependent secular differences occurred in cranial and brain volumes and cortical thickness over birth decades spanning 1930 to 1970. Design, Setting, and Participants: This cross-sectional study used data from the community-based Framingham Heart Study cohort for participants born in the decades 1930 to 1970. Participants did not have dementia or history of stroke and had magnetic resonance imaging (MRI) obtained from March 18, 1999, to November 15, 2019. The final analysis dataset was created in October 2023. Exposure: Years of birth ranging from 1925 to 1968. Main Measures: Cross-sectional analysis of intracranial, cortical gray matter, white matter, and hippocampal volumes as well as cortical surface area and cortical thickness. The secular measure was the decade in which the participant was born. Covariates included age at MRI and sex. Results: The main study cohort consisted of 3226 participants with a mean (SD) age of 57.7 (7.8) years at the time of their MRI. A total of 1706 participants were female (53%) and 1520 (47%) were male. The birth decades ranged from the 1930s to 1970s. Significant trends for larger intracranial, hippocampal, and white matter volumes and cortical surface area were associated with progressive birth decades. Comparing the 1930s birth decade to the 1970s accounted for a 6.6% greater volume (1234 mL; 95% CI, 1220-1248, vs 1321 mL; 95% CI, 1301-1341) for ICV, 7.7% greater volume (441.9 mL; 95% CI, 435.2-448.5, vs 476.3 mL; 95% CI, 467.0-485.7) for white matter, 5.7% greater value (6.51 mL; 95% CI, 6.42-6.60, vs 6.89 mL; 95% CI, 6.77-7.02) for hippocampal volume, and a 14.9% greater value (1933 cm2; 95% CI, 1908-1959, vs 2222 cm2; 95% CI, 2186-2259) for cortical surface area. Repeat analysis applied to a subgroup of 1145 individuals of similar age range born in the 1940s (mean [SD] age, 60.0 [2.8] years) and 1950s (mean [SD] age, 59.0 [2.8] years) resulted in similar findings. Conclusion and Relevance: In this study, secular trends for larger brain volumes suggested improved brain development among individuals born between 1930 and 1970. Early life environmental influences may explain these results and contribute to the declining dementia incidence previously reported in the Framingham Heart Study cohort.

Associations between personality and psychological characteristics and cognitive outcomes among older adults.

Prior research has shown that some personality traits are associated with cognitive outcomes and may confirm risk or protection against cognitive decline. The present study expands on previous work to examine the association between a more comprehensive set of psychological characteristics and cognitive performance in a diverse cohort of older adults. We also examine whether controlling for brain atrophy influences the association between psychological characteristics and cognitive function. A total of 157 older adults completed a battery of psychological questionnaires (Openness to Experience, Conscientiousness, Agreeableness, Neuroticism, Extraversion, positive affect, negative affect-sadness, negative affect-anger, sense of purpose, loneliness, grit, and self-efficacy). Cognitive outcomes were measured across multiple domains: episodic memory, semantic memory, executive function, and spatial ability. Baseline brain (MRI) variables included gray matter, hippocampus, and total white matter hyperintensity volume. Parallel process, multilevel models yielded intercept (individual cognitive domain scores) and linear slope (global cognitive change) random effects for the cognitive outcomes. Positive affect (ß = 0.013, SE = 0.005, p = .004) and Openness (ß = 0.018, SE = 0.007, p = .009) were associated with less cognitive change, independent of baseline brain variables and covariates. Greater sadness predicted more cognitive decline when controlling for covariates, but not brain atrophy. A variety of psychological characteristics were associated with the cross-sectional measures of cognition. This study highlights the important impact of positive and negative affect on reducing or enhancing the risk of longitudinal cognitive decline. Such findings are especially important, given the available efficacious interventions that can improve affect. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Associations of Amyloid Burden, White Matter Hyperintensities, and Hippocampal Volume With Cognitive Trajectories in the 90+ Study.

BACKGROUND AND OBJECTIVES: Amyloid pathology, vascular disease pathology, and pathologies affecting the medial temporal lobe are associated with cognitive trajectories in older adults. However, only limited evidence exists on how these pathologies influence cognition in the oldest old. We evaluated whether amyloid burden, white matter hyperintensity (WMH) volume, and hippocampal volume (HV) are associated with cognitive level and decline in the oldest old. METHODS: This was a longitudinal, observational community-based cohort study. We included participants with 18F-florbetapir PET and MRI data from the 90+ Study. Amyloid load was measured using the standardized uptake value ratio in the precuneus/posterior cingulate with eroded white matter mask as reference. WMH volume was log-transformed. All imaging measures were standardized using sample means and SDs. HV and log-WMH volume were normalized by total intracranial volume using the residual approach. Global cognitive performance was measured by the Mini-Mental State Examination (MMSE) and modified MMSE (3MS) tests, repeated every 6 months. We used linear mixed-effects models with random intercepts; random slopes; and interaction between time, time squared, and imaging variables to estimate the associations of imaging variables with cognitive level and cognitive decline. Models were adjusted for demographics, APOE genotype, and health behaviors. RESULTS: The sample included 192 participants. The mean age was 92.9 years, 125 (65.1%) were female, 71 (37.0%) achieved a degree beyond college, and the median follow-up time was 3.0 years. A higher amyloid load was associated with a lower cognitive level (ßMMSE = -0.82, 95% CI -1.17 to -0.46; ß3MS = -2.77, 95% CI -3.69 to -1.84). A 1-SD decrease in HV was associated with a 0.70-point decrease in the MMSE score (95% CI -1.14 to -0.27) and a 2.27-point decrease in the 3MS score (95% CI -3.40 to -1.14). Clear nonlinear cognitive trajectories were detected. A higher amyloid burden and smaller HV were associated with faster cognitive decline. WMH volume was not significantly associated with cognitive level or decline. DISCUSSION: Amyloid burden and hippocampal atrophy are associated with both cognitive level and cognitive decline in the oldest old. Our findings shed light on how different pathologies contributed to driving cognitive function in the oldest old.

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

BACKGROUND: Kinetic 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. METHODS: 18F-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 ([Formula: see text] was also calculated from the multi-reference tissue model (MRTM). RESULTS: Amyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with [Formula: see text] analysis. [Formula: see text]and VT from kinetic models were correlated (r² = 0.46, P < 2[Formula: see text] with a stronger positive correlation observed in amyloid-positive participants, indicating reliable model fits with the IDIFs. VT from 2TCM was highly correlated ([Formula: see text]= 0.65, P < 2[Formula: see text]) with Logan graphical VT estimation. CONCLUSION: Non-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 [Formula: see text]in amyloid-positive and amyloid-negative older individuals.

Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging.

Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants' T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning derived Imaging Phenotypes (UDIPs). GWAS of these UDIPs in held-out UKBB subjects (n = 22,880 discovery and n = 12,359/11,265 replication cohorts for T1/T2) identified 9457 significant SNPs organized into 97 independent genetic loci of which 60 loci were replicated. Twenty-six loci were not reported in earlier T1 and T2 IDP-based UK Biobank GWAS. We developed a perturbation-based decoder interpretation approach to show that these loci are associated with UDIPs mapped to multiple relevant brain regions. Our results established unsupervised deep learning can derive robust, unbiased, heritable, and interpretable brain imaging phenotypes.

Enhancing Cognitive Performance Prediction through White Matter Hyperintensity Connectivity Assessment: A Multicenter Lesion Network Mapping Analysis of 3,485 Memory Clinic Patients.

Introduction: White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating cognitive health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. We propose that lesion network mapping (LNM), enables to infer if brain networks are connected to lesions, and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed this approach to test the following hypotheses: (1) LNM-informed markers surpass WMH volumes in predicting cognitive performance, and (2) WMH contributing to cognitive impairment map to specific brain networks. Methods & results: We analyzed cross-sectional data of 3,485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in 4 cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity across 480 atlas-based gray and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. The capacity of total and regional WMH volumes and LNM scores in predicting cognitive function was compared using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention and executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater disruptive effects of WMH on regional connectivity, in gray and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Conclusion: Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network effects, particularly in attentionrelated brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.