Exploring the Association between Amyloid-ß and Memory Markers for Alzheimer's Disease in Cognitively Unimpaired Older Adults.

BACKGROUND: Memory tests vary in their sensitivity for detection of pre-symptomatic Alzheimer's disease (AD). The Visual Short-Term Memory Binding Test (VSTMBT) identifies AD-related performance deficits in older adults who are otherwise cognitively unimpaired. OBJECTIVE: We investigated the association of this psychometric measure with brain amyloidosis and atrophy. DESIGN: Cross-sectional mixed and correlational. SETTING: Cognitive Reserve Study from Columbia University. PARTICIPANTS: a sample of 39 cognitively unimpaired older adults (Age: M=65.3, SD=3.07) was obtained from the above study. MEASUREMENTS: Extensive neuropsychological and neuroimaging (MRI and amyloid-ß PET) assessments were carried out. RESULTS: Performance on the VSTMBT allowed us to split the sample into Low Binding Cost (LBC, N=21) and High Binding Cost (HBC, N=18). Groups were matched according to age [p=0.702], years of education [0.071], and sex [p=0.291]. HBC's performance was comparable to that seen in symptomatic AD. Groups only differed in their amyloid-ß deposition on PET in regions of the right ventral stream linked to visual cognition and affected early in AD pathogenesis (lateral-occipital cortex, p = 0.008; fusiform gyrus, p = 0.017; and entorhinal cortex, p = 0.046). Other regions known to be linked to low-level visual integration function also revealed increased amyloid-ß deposition in HBC. CONCLUSIONS: VSTMB deficits are associated with neuropathogenesis (i.e., amyloid-ß deposition) in the earliest affected regions in pre-symptomatic AD. The VSTMB test holds potential for the identification of cognitively unimpaired older adults with very early AD pathogenesis and may thus be a useful tool for early intervention trials or other forms of clinical research.

Polygenic indices for cognition in healthy aging; the role of brain measures.

Background: Genome-wide association studies (GWAS) have identified large numbers of genetic variants associated with cognition. However, little is known about how these genetic discoveries impact cognitive aging. Methods: We conducted polygenic-index (PGI) analysis of cognitive performance in n = 168 European-ancestry adults aged 20-80. We computed PGIs based on GWAS of cognitive performance in young/middle-aged and older adults. We tested associations of the PGI with cognitive performance, as measured through neuropsychological evaluation. We explored whether these associations were accounted for by magnetic resonance imaging (MRI) measures of brain-aging phenotypes: total gray matter volume (GM), cortical thickness (CT), and white matter hyperintensities burden (WMH). Results: Participants with higher PGI values performed better on cognitive tests (B = 0.627, SE = 0.196, p = 0.002) (age, sex, and principal components as covariates). Associations remained significant with inclusion of covariates for MRI measures of brain aging; B = 0.439, SE: 0.198, p = 0.028). PGI associations were stronger in young and middle-aged (age<65) as compared to older adults. For further validation, linear regression for Cog PGI and cognition in the fully adjusted model and adding the interaction between age group and Cog PGI, showed significant results (B = 0.892, SE: 0.325, p = 0.007) driven by young and middle-aged adults (B = -0.403, SE: 0.193, p = 0.039). In ancillary analysis, the Cognitive PGI was not associated with any of the brain measures. Conclusions: Genetics discovered in GWAS of cognition are associated with cognitive performance in healthy adults across age, but most strongly in young and middle-aged adults. Associations were not explained by brain-structural markers of brain aging. Genetics uncovered in GWAS of cognitive performance may contribute to individual differences established relatively early in life and may not reflect genetic mechanisms of cognitive aging.

Identifying a task-invariant cognitive reserve network using task potency.

Cognitive reserve (CR) is thought to protect against the consequence of age- or disease-related structural brain changes across multiple cognitive domains. The neural basis of CR may therefore comprise a functional network that is actively involved in many different cognitive processes. To investigate the existence of such a "task-invariant" CR network, we measured functional connectivity in a cognitively normal sample between 20 and 80 years old (N â€‹= â€‹265), both at rest and during the performance of 11 separate tasks that aim to capture four latent cognitive abilities (i.e. vocabulary, episodic memory, processing speed, and fluid reasoning). For each individual, we determined the change in functional connectivity from the resting state to each task state, which is referred to as "task potency" (Chauvin et al., 2018, 2019). Task potency was calculated for each pair among 264 nodes (Power et al., 2012) and then summarized across tasks reflecting the same cognitive ability. Subsequently, we established the correlation between task potency and IQ or education (i.e. CR factors). We identified a set of 57 pairs in which task potency showed significant correlations with IQ, but not education, across all four cognitive abilities. These pairs were included in a principal component analysis, from which we extracted the first component to obtain a latent variable reflecting task potency in this task-invariant CR network. This task potency variable was associated with better episodic memory (ߠ​= â€‹0.19, p â€‹< â€‹.01) and fluid reasoning performance (ߠ​= â€‹0.17, p â€‹< â€‹.01) above and beyond the effects of cortical thickness (range [absolute] ߠ​= â€‹0.28-0.32, p â€‹< â€‹.001). Our identification of this task-invariant network contributes to a better understanding of the mechanism underlying CR, which may facilitate the development of CR-enhancing treatments. Our work also offers a useful alternative operational measure of CR for future studies.

A Dopamine Receptor genetic variant enhances perceptual speed in cognitive healthy subjects.

Cognition is under strong genetic control, yet the specific genes are unknown. To investigate genetic influences on specific cognitive domains, 153 cognitive healthy subjects of European ancestry from the Reference Abilities Study (RANN) were genotyped for 1,160 variants within 446 neuropsychiatric genes. Adjusted linear regression models evaluated the association between the genetic variants and four reference abilities, which capture variance in age-related cognitive function (Vocabulary, Episodic Memory, Perceptual Speed, and Reasoning). 159 variants nominally significant in the RANN cohort were then re-evaluated in an independent cohort of 868 cognitive healthy subjects from the Religious Orders Study and Rush Memory Aging Project. Meta-analysis yielded a Bonferroni adjusted statistically significant association between perceptual speed and a variant located in the promoter of the dopamine receptor D4 gene, rs3756450 (ß=0.23, SE=0.05, P meta =2.3 × 10-5). Our data suggest that genetic variation in a dopamine pathway gene influences perceptual speed performance in cognitively healthy individuals.

Cognitive Reserve and Brain Maintenance: Orthogonal Concepts in Theory and Practice.

Cognitive Reserve and Brain Maintenance have traditionally been understood as complementary concepts: Brain Maintenance captures the processes underlying the structural preservation of the brain with age, and might be assessed relative to age-matched peers. Cognitive Reserve, on the other hand, refers to how cognitive processing can be performed regardless of how well brain structure has been maintained. Thus, Brain Maintenance concerns the "hardware," whereas Cognitive Reserve concerns "software," that is, brain functioning explained by factors beyond mere brain structure. We used structural brain data from 368 community-dwelling adults, age 20-80, to derive measures of Brain Maintenance and Cognitive Reserve. We found that Brain Maintenance and Cognitive were uncorrelated such that values on one measure did not imply anything about the other measure. Further, both measures were positively correlated with verbal intelligence and education, hinting at formative influences of the latter to both measures. We performed extensive split-half simulations to check our derived measures' statistical robustness. Our approach enables the out-of-sample quantification of Brain Maintenance and Cognitive Reserve for single subjects on the basis of chronological age, neuropsychological performance and structural brain measures. Future work will investigate the prognostic power of these measures with regard to future cognitive status.

The Reference Ability Neural Network Study: Life-time stability of reference-ability neural networks derived from task maps of young adults.

Analyses of large test batteries administered to individuals ranging from young to old have consistently yielded a set of latent variables representing reference abilities (RAs) that capture the majority of the variance in age-related cognitive change: Episodic Memory, Fluid Reasoning, Perceptual Processing Speed, and Vocabulary. In a previous paper (Stern et al., 2014), we introduced the Reference Ability Neural Network Study, which administers 12 cognitive neuroimaging tasks (3 for each RA) to healthy adults age 20-80 in order to derive unique neural networks underlying these 4 RAs and investigate how these networks may be affected by aging. We used a multivariate approach, linear indicator regression, to derive a unique covariance pattern or Reference Ability Neural Network (RANN) for each of the 4 RAs. The RANNs were derived from the neural task data of 64 younger adults of age 30 and below. We then prospectively applied the RANNs to fMRI data from the remaining sample of 227 adults of age 31 and above in order to classify each subject-task map into one of the 4 possible reference domains. Overall classification accuracy across subjects in the sample age 31 and above was 0.80±0.18. Classification accuracy by RA domain was also good, but variable; memory: 0.72±0.32; reasoning: 0.75±0.35; speed: 0.79±0.31; vocabulary: 0.94±0.16. Classification accuracy was not associated with cross-sectional age, suggesting that these networks, and their specificity to the respective reference domain, might remain intact throughout the age range. Higher mean brain volume was correlated with increased overall classification accuracy; better overall performance on the tasks in the scanner was also associated with classification accuracy. For the RANN network scores, we observed for each RANN that a higher score was associated with a higher corresponding classification accuracy for that reference ability. Despite the absence of behavioral performance information in the derivation of these networks, we also observed some brain-behavioral correlations, notably for the fluid-reasoning network whose network score correlated with performance on the memory and fluid-reasoning tasks. While age did not influence the expression of this RANN, the slope of the association between network score and fluid-reasoning performance was negatively associated with higher ages. These results provide support for the hypothesis that a set of specific, age-invariant neural networks underlies these four RAs, and that these networks maintain their cognitive specificity and level of intensity across age. Activation common to all 12 tasks was identified as another activation pattern resulting from a mean-contrast Partial-Least-Squares technique. This common pattern did show associations with age and some subject demographics for some of the reference domains, lending support to the overall conclusion that aspects of neural processing that are specific to any cognitive reference ability stay constant across age, while aspects that are common to all reference abilities differ across age.

Remediation of sleep-deprivation-induced working memory impairment with fMRI-guided transcranial magnetic stimulation.

Repetitive transcranial magnetic stimulation (rTMS) was applied to test the role of selected cortical regions in remediating sleep-deprivation-induced deficits in visual working memory (WM) performance. Three rTMS targets were chosen using a functional magnetic resonance imaging (fMRI)-identified network associated with sleep-deprivation-induced WM performance impairment: 2 regions from the network (upper left middle occipital gyrus and midline parietal cortex) and 1 nonnetwork region (lower left middle occipital gyrus). Fifteen participants underwent total sleep deprivation for 48 h. rTMS was applied at 5 Hz during a WM task in a within-subject sham-controlled design. The rTMS to the upper-middle occipital site resulted in a reduction of the sleep-induced reaction time deficit without a corresponding decrease in accuracy, whereas stimulation at the other sites did not. Each subject had undergone fMRI scanning while performing the task both pre- and postsleep deprivation, and the degree to which each individual activated the fMRI network was measured. The degree of performance enhancement with upper-middle occipital rTMS correlated with the degree to which each individual failed to sustain network activation. No effects were found in a subset of participants who performed the same rTMS procedure after recovering from sleep deprivation, suggesting that the performance enhancements seen following sleep deprivation were state dependent.

APOE related alterations in cerebral activation even at college age.

BACKGROUND: Associations between the APOE genotype and various medical conditions have been documented at a very young age. The association between the APOE genotype and cognitive performance varies at different ages. APOE related changes in brain activation have been recently reported for middle aged and elderly subjects. OBJECTIVE: To explore APOE related alterations during cognitive activation in a population of young adults. METHODS: Using H2(15)O positron emission tomography (PET), imaging was carried out in 20 healthy young adults (age 19 to 28 years; four epsilon4 carriers and 16 non-epsilon4 carriers) during a non-verbal memory task. Voxel-wise multiple regression analyses were undertaken, with the activation difference PET counts as the dependent variable and the APOE genotype as the independent variable. RESULTS: Brain regions were identified where epsilon4 carriers showed significantly lower or higher activation than non-carriers. CONCLUSIONS: The results suggest that APOE dependent modulation of cerebral flow may be present even at a young age. This may reflect an APOE related physiological heterogeneity which may or may not predispose to brain disease in the ensuing decades or, less likely, the effect of very early Alzheimer's disease related pathological changes.

APOE-dependent PET patterns of brain activation in Alzheimer disease.

Using H2(15)O PET, the authors imaged 13 patients with Alzheimer disease (AD) while performing a serial nonverbal recognition memory task. Patterns of brain activation differed as a function of APOE genotype: epsilon4 carriers exhibited lower activation in the left lingual gyrus and higher activation in left cuneus, precuneus, parahippocampal, and right precentral gyrus. The APOE genotype seems to play a role in cerebral physiologic activity even after onset of clinical manifestations of AD.