Synaptic density and cognitive performance in Alzheimer's disease: A PET imaging study with [11 C]UCB-J.

INTRODUCTION: For 30 years synapse loss has been referred to as the major pathological correlate of cognitive impairment in Alzheimer's disease (AD). However, this statement is based on remarkably few patients studied by autopsy or biopsy. With the recent advent of synaptic vesicle glycoprotein 2A (SV2A) positron emission tomography (PET) imaging, we have begun to evaluate the consequences of synaptic alterations in vivo. METHODS: We examined the relationship between synaptic density measured by [11 C]UCB-J PET and neuropsychological test performance in 45 participants with early AD. RESULTS: Global synaptic density showed a significant positive association with global cognition and performance on five individual cognitive domains in participants with early AD. Synaptic density was a stronger predictor of cognitive performance than gray matter volume. CONCLUSION: These results confirm neuropathologic studies demonstrating a significant association between synaptic density and cognitive performance, and suggest that this correlation extends to the early stages of AD.

Effects of Normative Adjustments to the Montreal Cognitive Assessment.

OBJECTIVE: To investigate optimal cutoff scores and the effects of normative adjustments on the performance of the Montreal Cognitive Assessment (MoCA) as a screening instrument for Mild Cognitive Impairment (MCI) and dementia due to Alzheimer's disease (AD-dementia). METHODS: 499 adults 48 to 91 years-old enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI) and were administered the MoCA during baseline. Participants were classified as either cognitively normal (CN), MCI, or AD-dementia by clinical assessment. Receiver operating characteristic (ROC) analyses were performed using raw MoCA scores, education-adjusted MoCA scores, and a regression-based adjustment derived from the National Alzheimer's Coordinating Center data (NACC). Test performance characteristics were calculated for various cutoffs after each normative correction method. RESULTS: Areas under the curve (AUC) were similar for raw, education-adjusted, and NACC-adjusted MoCA scores, and demonstrated minimal improvement when adjustments of increasing complexity were applied. Our results suggest that the optimal cutoff score for distinguising MCI is 24 and for distinguising AD-dementia is 22. CONCLUSIONS: This study adds to the understanding of how normative adjustments affect the sensitivity and specificity of the MoCA. Suggested corrections based on education alone do not yield improved test characteristics, but small improvements are attained when a regression-based correction that accounts for age, sex, and education is applied. Furthermore, optimal cutoffs for distinguishing CN from MCI or CN from AD-dementia were lower than previously reported. Optimal cutoffs to detect MCI and AD-dementia may vary in different populations, and further study is needed to determine appropriate use of the MoCA as a screening tool.

Personality Predicts Mortality Risk: An Integrative Data Analysis of 15 International Longitudinal Studies.

This study examined the Big Five personality traits as predictors of mortality risk, and smoking as a mediator of that association. Replication was built into the fabric of our design: we used a Coordinated Analysis with 15 international datasets, representing 44,094 participants. We found that high neuroticism and low conscientiousness, extraversion, and agreeableness were consistent predictors of mortality across studies. Smoking had a small mediating effect for neuroticism. Country and baseline age explained variation in effects: studies with older baseline age showed a pattern of protective effects (HR<1.00) for openness, and U.S. studies showed a pattern of protective effects for extraversion. This study demonstrated coordinated analysis as a powerful approach to enhance replicability and reproducibility, especially for aging-related longitudinal research.