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Background: In cognitively unimpaired (CU) older adults, the presence of a subjective cognitive decline (SCD) combined with evidence of abnormal b‐amyloid (Ab) is proposed as stage 2 of Alzheimer's disease (AD) by the NIA‐AA framework (Jack et al., 2018). However, the associations found between SCD and preclinical AD are inconsistent across studies, highlighting the importance of better understanding which specific SCD features are associated with either Ab or tau burden. Methods: The present study includes cross‐sectional data from 9 independent cohorts with a total of 7217 CU older adults (57% female), aged 69.34 (1.20) years, recruited from general and memory‐clinic populations. Ab and tau biomarkers were measured by positron emission tomography (PET) or cerebrospinal fluid (CSF). Using established cut‐offs, 28% of participants were Aβ+, and 12% were Aβ+T+ (approximately one‐third of the sample had available tau data). We examined four SCD‐plus criteria as well as the mean number of SCD criteria met (i.e., mean SCD‐severity) in relation to both biomarker status and levels in logistic/linear regressions adjusted for age and sex for each cohort. Summary statistics were extracted for meta‐analyses. Results: The overall frequency of stage 2 AD varied from 7‐16% [4‐26%] according to each SCD‐plus criterion endorsement. Only 1‐5% [0‐8%] of participants meeting the SCD‐plus criteria also had both high Aβ and tau burden (Fig.1). The presence of self‐reported memory decline (SMD), an associated concern/worry, and a higher mean SCD‐severity were each associated with high Ab (status and continuous). Only the latter was associated with high tau status (Fig.2). Onset of SCD within the last 5 years, and feeling of worse performance than same‐age peers, were not associated with AD biomarkers at a Bonferroni‐corrected threshold. Conclusions: Our results suggest that widespread endorsement of multiple SCD features is more powerful than a single criterion alone in identifying both Aβ and tau in CU older adults. We found that the isolated SCD criterion was particularly sensitive to elevated Aβ, even after adjustment for tau, supporting the power of SCD as a very early behavioral marker of preclinical AD. [ABSTRACT FROM AUTHOR]

Introduction: While the influence of cross-sectional β-amyloid (Aβ) on longitudinal changes in cognition is well established, longitudinal change-on-change between Aβ and cognition is less explored., Methods: A series of bivariate latent change score models (LCSM) examined the relationship between changes in 11 C-Pittsburgh Compound-B (PiB) positron emission tomography (PET) and the Preclinical Alzheimer's Cognitive Composite-5 (PACC-5) while adjusting for covariates, including cross-sectional medial temporal lobe (MTL) tau-PET burden. We selected 352 clinically normal older participants with up to 9 years of PiB-PET and PACC-5 data from the Harvard Aging Brain Study (HABS)., Results: Aβ accumulation was associated with subsequent cognitive decline beyond the effects of cross-sectional Aβ burden. Within this model including covariates such as age, sex, and apolipoprotein ε4 (APOEε4) status, we found no evidence supporting previously published associations between cross-sectional tau-PET and cognitive intercept/slope., Discussion: Short-term Aβ changes are significantly associated with cognitive decline in clinically normal older adults and may eclipse the effect of cross-sectional Aβ and MTL tau., Highlights: Aβ accumulation is associated with subsequent cognitive decline. High Aβ burden is not the sole metric signaling impending cognitive decline. Contrary to prior work, MTL tau-PET and cognition were not associated in our models. Models of bivariate latent Aβ and cognitive change may eclipse the effects of MTL tau., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Cognitive resilience describes the phenomenon of individuals evading cognitive decline despite prominent Alzheimer's disease neuropathology. Operationalization and measurement of this latent construct is non-trivial as it cannot be directly observed. The residual approach has been widely applied to estimate CR, where the degree of resilience is estimated through a linear model's residuals. We demonstrate that this approach makes specific, uncontrollable assumptions and likely leads to biased and erroneous resilience estimates. We propose an alternative strategy which overcomes the standard approach's limitations using machine learning principles. Our proposed approach makes fewer assumptions about the data and construct to be measured and achieves better estimation accuracy on simulated ground-truth data., Competing Interests: Conflict of interest Paul Maruff is a full-time employee of Cogstate Ltd. Samuel N. Lockhart is a full time employee of Invicro LLC. SCJ has served in the past three years as a consultant to ALZPath and Enigma Biomedical.

The Face Name Associative Memory Exam (FNAME) was introduced into the NIH Toolbox as part of the ARMADA study and establishes normative data for diverse participants, ages 64 to 85+, and proposes cutoff scores between biomarker positive versus negative (+/-) groups. The FNAME was administered to 257 participants across the clinical spectrum with 122 having amyloid biomarkers. Linear regression explored the association between demographics and FNAME and between amyloid (+/-) groups. Receiver operating characteristic curves (ROC) identified performance thresholds that best discriminated between biomarker (+/-) individuals. Lower FNAME scores occurred in males, older ages, Black/African Americans, Hispanics, and biomarker-positive participants. ROC analyses demonstrated acceptable accuracy (0.73 to 0.77) but only when combined with clinical status. The diagnostic discrimination of amyloid positivity was acceptable but not excellent, suggesting the FNAME may be a better screening indicator of clinical status rather than amyloid deposition in cognitively normal individuals. Normative data are provided., Competing Interests: AS., C.F., O.R.S., H.M.K., and S.A. report no disclosures relevant to this manuscript. D.R. received salary support as a co‐PI on the ARMADA grant No. 1U2CAG057441. D.P. has been a paid consultant to FACIT, Debiopharm Beta6. D.R. has also served as a paid consultant for Biogen Idec, Digital Cognition Technologies, and Neurotrack. Author disclosures are available in the supporting information., (© 2023 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)