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Purpose of ReviewThe aim of this review is to summarize current conceptual models of cognitive reserve (CR) and related concepts and to discuss evidence for these concepts within the context of aging and Alzheimer’s disease.Recent FindingsEvidence to date supports the notion that higher levels of CR, as measured by proxy variables reflective of lifetime experiences, are associated with better cognitive performance, and with a reduced risk of incident mild cognitive impairment/dementia. However, the impact of CR on longitudinal cognitive trajectories is unclear and may be influenced by a number of factors. Although there is promising evidence that some proxy measures of CR may influence structural brain measures, more research is needed.SummaryThe protective effects of CR may provide an important mechanism for preserving cognitive function and cognitive well-being with age, in part because it can be enhanced throughout the lifespan. However, more research on the mechanisms by which CR is protective is needed.

•3D velocity selective inversion based arterial spin labeling (VSI-ASL) achieved high reliability during the test-retest CBF measurement for detecting between-subject variations among healthy subjects using absolute CBF.•3D VSI-ASL achieved high reliability during the test-retest CBF measurement for detecting between-region variations among healthy subjects using relative CBF.•Physiology parameters partially explained the variability of CBF across subjects. Velocity-selective inversion (VSI) based velocity-selective arterial spin labeling (VSASL) has been developed to measure cerebral blood flow (CBF) with low susceptibility to the prolonged arterial transit time and high sensitivity to brain perfusion signal. The purpose of this magnetic resonance imaging study is to evaluate the test-retest reliability of a VSI-prepared 3D VSASL protocol with whole-brain coverage to detect baseline CBF variations among cognitively normal participants in different brain regions. Coefficients of variation (CoV) of both absolute and relative CBF across scans or sessions, subjects, and gray matter regions were calculated, and corresponding intraclass correlation coefficients (ICC) were computed. The higher between-subject CoV of absolute CBF (13.4 ± 2.0%) over within-subject CoV (within-session: 3.8 ± 1.1%; between-session: 4.9 ± 0.9%) yielded moderate to excellent ICC (within-session: 0.88±0.08; between-session: 0.77±0.14) to detect normal variations of individual CBF. The higher between-region CoV of relative CBF (11.4 ± 3.0%) over within-region CoV (within-session: 2.3 ± 0.9%; between-session: 3.3 ± 1.0%) yielded excellent ICC (within-session: 0.92±0.06; between-session: 0.85±0.12) to detect normal variations of regional CBF. Age, blood pressure, end-tidal CO2, and hematocrit partially explained the variability of CBF across subjects. Together these results show excellent test-retest reliability of VSASL to detect both between-subject and between-region variations supporting its clinical utility.

Several models have been proposed for the evolution of Alzheimer's disease (AD) biomarkers. The aim of this study was to identify changepoints in a range of biomarkers during the preclinical phase of AD. We examined nine measures based on cerebrospinal fluid (CSF), magnetic resonance imaging (MRI) and cognitive testing, obtained from 306 cognitively normal individuals, a subset of whom subsequently progressed to the symptomatic phase of AD. A changepoint model was used to determine which of the measures had a significant change in slope in relation to clinical symptom onset. All nine measures had significant changepoints, all of which preceded symptom onset, however, the timing of these changepoints varied considerably. A single measure, CSF t-tau, had an early changepoint (34 years prior to symptom onset). A group of measures, including the remaining CSF measures (CSF Abeta and phosphorylated tau) and all cognitive tests had changepoints 10-15 years prior to symptom onset. A second group is formed by medial temporal lobe shape composite measures, with a 6-year time difference between the right and left side (respectively nine and 3 years prior to symptom onset). These findings highlight the long period of time prior to symptom onset during which AD pathology is accumulating in the brain. There are several significant findings, including the early changes in cognition and the laterality of the MRI findings. Additional work is needed to clarify their significance.

The accumulation of neurofibrillary tau tangles, a neuropathological hallmark of Alzheimer's disease (AD), occurs in medial temporal lobe (MTL) regions early in the disease process, with some of the earliest deposits localized to subregions of the entorhinal cortex. Although functional specialization of entorhinal cortex subregions has been reported, few studies have considered functional associations with localized tau accumulation. In this study, stepwise linear regressions were used to examine the contributions of regional tau burden in specific MTL subregions, as measured by F-MK6240 PET, to individual variability in cognition. Dependent measures of interest included the Clinical Dementia Rating Sum of Boxes (CDR-SB), Mini Mental State Examination (MMSE), and composite scores of delayed episodic memory and language. Other model variables included age, sex, education, APOE4 status, and global amyloid burden, indexed by C-PiB. Tau burden in right Brodmann area 35 (BA35), left and right Brodmann area 36 (BA36), and age each uniquely contributed to the proportion of explained variance in CDR-SB scores, while right BA36 and age were also significant predictors of MMSE scores, and right BA36 was significantly associated with delayed episodic memory performance. Tau burden in both left and right BA36, along with education, uniquely contributed to the proportion of explained variance in language composite scores. Importantly, the addition of more inclusive ROIs, encompassing less granular segmentation of the entorhinal cortex, did not significantly contribute to explained variance in cognition across any of the models. These findings suggest that the ability to quantify tau burden in more refined MTL subregions may better account for individual differences in cognition, which may improve the identification of non-demented older adults who are on a trajectory of decline due to AD.

The current \"one size fits all\" approach to our cognitive aging population is not adequate to close the gap between cognitive health span and lifespan. In this review article, we present a novel model for understanding, preventing, and treating age-related cognitive impairment (ARCI) based on concepts borrowed from precision medicine. We will discuss how multiple risk factors can be classified into because of their interrelatedness in real life, the that increase sensitivity to, or ameliorate, risk for ARCI, and the or common mechanisms mediating brain aging. Rather than providing a definitive model of risk for ARCI and cognitive decline, the Precision Aging model is meant as a starting point to guide future research. To that end, after briefly discussing key risk categories, genetic risks, and brain drivers, we conclude with a discussion of steps that must be taken to move the field forward.

To examine the prospective association between blood biomarkers of immune functioning (i.e., innate immune activation, adaptive immunity, and inflammation) and subsequent cognitive decline and clinical progression to mild cognitive impairment (MCI) in cognitively normal individuals. The BIOCARD study is an observational cohort study of = 191 initially cognitively healthy participants (mean age 65.2 years). Blood plasma samples were assayed for markers of chronic inflammation (TNFR1, IL-6), adaptive immunity (CD25), and innate immune activation (CD14 and CD163). Participants were followed annually for ongoing clinical assessment and cognitive testing for up to 7.3 years. Primary study outcomes were progression to MCI and cognitive change over time, as measured by a global factor score encompassing multiple cognitive domains. Higher levels of plasma TNFR1 were associated with greater risk of progression from normal cognition to MCI (HR: 3.27; 95% confidence interval, CI: 1.27, 8.40). Elevated levels of TNFR1 were also associated with steeper rate of cognitive decline on follow-up but not with baseline cognitive performance. Baseline IL-6 levels and markers of innate and adaptive immune activation showed no relationship with MCI risk or cognitive decline. Inflammation, mediated by TNF signaling, may play a selective role in the early phase of AD. Accordingly, plasma TNFR1 may facilitate improved prediction of disease progression for individuals in the preclinical stage of AD.

BACKGROUND Alzheimer's disease (AD) is characterized by the abnormal accumulation of amyloid‐beta (Aβ) and tau that can be quantified in vivo through cerebrospinal fluid (CSF) sampling. Physical activity has emerged as a possible modifier of AD risk; however, its impact on CSF biomarkers and cognitive function is not yet fully understood. We examined whether higher levels of physical activity modifies associations between AD CSF biomarkers and cognitive function. METHODS One hundred and seventeen adults free of dementia from the BIOCARD study (mean age 72.2 ± 8.0 years, 70% women) wore a wrist accelerometer for 1 week, underwent lumbar puncture to collect CSF, and completed a comprehensive neuropsychological exam. Multivariable linear regression analyses were used to examine whether physical activity (total activity counts over the 10 most active hours of the day) moderates the association between AD CSF biomarkers [Aβ42/40, phosphorylated tau (p‐tau181), and total tau] and cognitive composite scores (episodic memory, executive function). RESULTS There were significant interactions between physical activity and p‐tau181 (p = 0.016) as well as between physical activity and total tau (p = 0.004) in relation to the executive function composite score. Among participants with higher levels of physical activity, the adverse relationship between CSF‐measured tau and executive function was diminished. In contrast, there were no significant interactions for episodic memory, and physical activity did not interact with Aβ42/40 (all interactions p > 0.05). CONCLUSION A physically active lifestyle may provide protection against AD‐related cognitive decline by reducing the impact of tau pathology. Highlights Older age was associated with lower levels of physical activity, worse CSF biomarker profiles, and poorer cognition. Physical activity moderates the impact of tau pathology on executive function but shows no significant effect on amyloid‐beta pathology. Physical activity may enhance cognitive reserve, thereby attenuating the influence of accumulating AD pathology on cognition.

Objective Examine whether cognitive reserve moderates the association of 1) vascular risk factors and 2) white matter hyperintensity burden with risk of clinical progression and longitudinal cognitive decline. Methods BIOCARD Study participants were cognitively normal and primarily middle‐aged (M = 57 years) at baseline and have been followed with annual cognitive and clinical assessments (M = 13 years). Baseline cognitive reserve was indexed with a composite score combining education with reading and vocabulary scores. Baseline vascular risk (N = 229) was assessed with a composite risk score reflecting five vascular risk factors. Baseline white matter hyperintensity load (N = 271) was measured with FLAIR magnetic resonance imaging. Cox regression models assessed risk of progression from normal cognition to onset of clinical symptoms of Mild Cognitive Impairment. Longitudinal mixed effects models measured the relationship of these variables to cognitive decline, using a global composite score, and executive function and episodic memory sub‐scores. Results Both vascular risk and white matter hyperintensities were associated with cognitive decline, particularly in executive function. Higher vascular risk, but not white matter hyperintensity burden, was associated with an increased risk of progression to Mild Cognitive Impairment. Higher cognitive reserve was associated with a reduced risk of symptom onset and higher levels of baseline cognition but did not modify the associations between the vascular risk score and white matter hyperintensities with clinical progression or cognitive decline. Interpretation Although cognitive reserve has protective effects on clinical and cognitive outcomes, it does not mitigate the negative impact of vascular risk and small vessel cerebrovascular disease on these same outcomes.