Novel approaches to address cognitive aging and to delay or prevent cognitive decline in older individuals will require a better understanding of the biological and environmental factors that contribute to it. Studies in animal models-in particular, animals whose cognitive trajectory across their life span closely tracks that of humans-can provide important insights into the factors that contribute to the accumulation of reserve and ways in which it is preserved or depleted. A better understanding of the molecular processes that underlie these elements would enhance and guide not only research but also treatment approaches to these issues. These treatment approaches may include noninvasive brain stimulation and drug treatments to promote youthfulness or combat the aging process. It is important to realize, however, that these processes occur in the context of the human experience, and studies of them must consider the complexity and individuality of each person's life.

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.

Background and objectives

This study aimed to examine whether baseline CSF measures of Alzheimer disease (AD)-related pathology are associated with the time to onset of mild cognitive impairment (MCI) and whether these associations differ by age, sex, Apolipoprotein E (ApoE4) status, and proximal (≤7 years) vs distal (>7 years) time to symptom onset.

Methods

Measures of amyloid (Aβ1-42 and Aβ1-40), phospho-tau (ptau181), and total tau (t-tau) were determined from CSF samples obtained at baseline from participants in an ongoing longitudinal project, known as the Biomarkers for Older Controls at Risk for Alzheimer Disease study (BIOCARD) study. The fully automated, Lumipulse G immunoassay was used to analyze the specimens. Cox regression models were used to examine the relationship of baseline biomarker levels with time to symptom onset of MCI and interactions with age, sex, and ApoE allelic status in subjects who progressed from normal cognition to MCI.

Results

Analyses included 273 participants from the BIOCARD cohort, who were cognitively normal and predominantly middle-aged at baseline, and have been followed for an average of 16 years (max = 23.6). During follow-up, 94 progressed to MCI (median time to symptom onset = 6.9 years). In Cox regression models, elevated ptau181 and t-tau levels were associated with time to MCI symptom onset if it occurred within 7 years of baseline (HR 1.386 and 1.329; p = 0.009 and 0.017, respectively), while a lower Aβ42/Aβ40 ratio was associated with symptom onset if it occurred >7 years from baseline (HR 0.596, p = 0.003). There were also significant 3-way CSF × age × sex interactions for ptau181 and Aβ42/Aβ40, with follow-up analyses indicating that associations between these biomarkers and progression to MCI were stronger among men than among women, but this difference between sexes diminished with increasing age.

Discussion

The lengthy follow-up of BIOCARD participants permitted an examination of time-varying associations between CSF AD biomarkers with MCI symptom onset and the influence of sex, baseline age, and ApoE4 genotype on these associations. These factors may inform clinical trial enrollment strategies, or trial duration and outcomes, which may use these measures as surrogate markers of treatment response.

Introduction

With expansion of clinical trials to individuals across the spectrum of Alzheimer disease (AD) from preclinical to symptomatic phases, it is increasingly important to quantify AD severity using methods that capture underlying pathophysiology.

Methods

We derived an AD severity measure based on biomarkers from brain imaging, neuropathology, and cognitive testing using latent variable modeling. We used data from ADNI-1 (N = 822) and applied findings to BIOCARD study (N = 349). We evaluated criterion validity for distinguishing diagnostic groups and construct validity by evaluating rates of change in AD severity.

Results

The AD severity factor cross-sectionally distinguishes cognitively normal participants from MCI (AUC = 0.87) and AD dementia (AUC = 0.94). Among ADNI MCI subjects, worsening scores predict faster progression to AD dementia (HR = 1.17; 95% CI, 1.13-1.22). In ADNI and BIOCARD, the pace of change in AD severity is steepest among progressors, with persisting differences by baseline diagnosis.

Discussion

Our content-valid latent variable measurement model is a reasonable approach for grading AD severity across a broad spectrum beginning at preclinical stages of AD.

Background

An association between visual impairment and cognitive outcomes has been documented, but there is limited research examining this relationship using multiple measures of vision.

Methods

Participants included non-demented individuals in Year 3 of the Visual impairment was assessed using visual acuity, contrast sensitivity, and stereo acuity. Cognitive function was defined using the digit symbol test and the Modified Mini-Mental State Examination (3MS). Incident cognitive impairment was defined as a 3MS score <80 or a decline >5 points following Year 3. Linear mixed effects models examined longitudinal associations adjusting for year, age, sex, race, education, smoking, depression, diabetes, study site, as well as interaction terms between the vision parameters and years in study, between baseline age and years in study, and quadratic terms of baseline age and years in study. Discrete Cox regression models examined the risk of incident cognitive impairment.

Results

Analyses included 2,444 participants (mean age = 74). Visual acuity, contrast sensitivity, and stereo acuity impairments were not associated with statistically significant changes in annual digit symbol test scores over 7 years of follow-up, as compared to those without these impairments. However, visual acuity, contrast sensitivity, and stereo acuity impairments were associated with greater declines in annual 3MS scores over 9 years. Participants with impaired visual acuity, contrast sensitivity, and stereo acuity had a greater risk of incident cognitive impairment.

Conclusions

Our results suggest that visual acuity, contrast sensitivity, and stereo acuity impairments may be risk factors for cognitive decline.

We examined whether cognitive reserve (CR) impacts level of, or rate of change in, biomarkers of Alzheimer's disease (AD) and small-vessel cerebrovascular disease in >250 individuals who were cognitively normal and middle-aged and older at the baseline. The four primary biomarker categories commonly examined in studies of AD were measured longitudinally: cerebrospinal fluid measures of amyloid (A) and tau (T); cerebrospinal fluid and neuroimaging measures of neuronal injury (N); and neuroimaging measures of white matter hyperintensities (WMHs) to assess cerebrovascular pathology (V). CR was indexed by a composite score including years of education, reading, and vocabulary test performance. Higher CR was associated with lower levels of WMHs, particularly among those who subsequently progressed from normal cognition to MCI. CR was not associated with WMH trajectories. In addition, CR was not associated with either levels of, or rate of change in, A/T/N biomarkers. This may suggest that higher CR is associated with lifestyle factors that reduce levels of cerebrovascular disease, allowing individuals with higher CR to better tolerate other types of pathology.

Objective

Recent studies suggest that white matter hyperintensities (WMH) on MRI, which primarily reflect small vessel cerebrovascular disease, may play a role in the evolution of Alzheimer disease (AD). In a longitudinal study, we investigated whether WMH promote the progression of AD pathology, or alter the association between AD pathology and risk of progression from normal cognition to mild cognitive impairment (MCI).

Methods

Two sets of analyses were conducted. The relationship between whole brain WMH load, based on fluid-attenuated inversion recovery MRI, obtained in initially cognitively normal participants (n = 274) and time to onset of symptoms of MCI (n = 60) was examined using Cox regression models. In a subset of the participants with both MRI and CSF data (n = 204), the interaction of WMH load and CSF AD biomarkers was also evaluated.

Results

Baseline WMH load interacted with CSF total tau (t-tau) with respect to symptom onset, but not with CSF β-amyloid 1-42 or phosphorylated tau (p-tau) 181. WMH volume was associated with time to symptom onset of MCI among individuals with low t-tau (hazard ratio [HR] 1.35, confidence interval [CI] 1.06-1.73, p = 0.013), but not those with high t-tau (HR 0.86, CI 0.56-1.32, p = 0.47). The rate of change in the CSF biomarkers over time was not associated with the rate of change in WMH volumes.

Conclusion

These results suggest that WMH primarily affect the risk of progression when CSF measures of neurodegeneration or neuronal injury (as reflected by t-tau) are low. However, CSF biomarkers of amyloid and p-tau and WMH appear to have largely independent and nonsynergistic effects on the risk of progression to MCI.

Introduction

Racial and ethnic groups are under-represented among research subjects who assent to brain donation in Alzheimer disease research studies. There has been little research on this important topic. Although there are some studies that have investigated the barriers to brain donation among African American study volunteers, there is no known research on the factors that influence whether or not Asians or Latinos are willing to donate their brains for research.

Methods

African American, Caucasian, Asian, and Latino research volunteers were surveyed at 15 Alzheimer Disease Centers to identify predictors of willingness to assent to brain donation.

Results

Positive predictors included older age, Latino ethnicity, understanding of how the brain is used by researchers, and understanding of what participants need to do to ensure that their brain will be donated. Negative predictors included African/African American race, belief that the body should remain whole at burial, and concern that researchers might not be respectful of the body during autopsy.

Discussion

The predictive factors identified in this study may be useful for researchers seeking to increase participation of diverse ethnic groups in brain donation.

This study examines the atrophy rates of subjects with mild cognitive impairment (MCI) compared to controls in four regions within the medial temporal lobe: the transentorhinal cortex (TEC), entorhinal cortex (ERC), hippocampus, and amygdala. These regions were manually segmented and then corrected for undesirable longitudinal variability via Large Deformation Diffeomorphic Metric Mapping (LDDMM) based longitudinal diffeomorphometry. Diffeomorphometry techniques were used to compare thickness measurements in the TEC with the ERC. There were more significant changes in thickness atrophy rate in the TEC than medial regions of the entorhinal cortex. Volume measures were also calculated for all four regions. Classifiers were constructed using linear discriminant analysis to demonstrate that average thickness and atrophy rate of TEC together was the most discriminating measure compared to the thickness and volume measures in the areas examined, in differentiating MCI from controls. These findings are consistent with autopsy findings demonstrating that initial neuronal changes are found in TEC before spreading more medially in the ERC and to other regions in the medial temporal lobe. These findings suggest that the TEC thickness could serve as a biomarker for Alzheimer's disease in the prodromal phase of the disease.