Individuals who died with high AD neuropathology had a similar trajectory of global cognition and memory performance before death when compared to individuals with low AD neuropathology. We found evidence of learning effects in these participants; however, these learning effects were greater in individuals with lower AD neuropathology.
The relationship between neuropathology and cognition may be different for the oldest-old compared to younger elderly. Alternatively, it is possible that our participants may have been in the preclinical stages of AD14,15
and cognitive decline may have become apparent if the participants had lived longer. Supporting this notion, individuals with high levels of plaques or high levels of tangles tended to have poorer cognitive test scores and smaller learning effects compared to participants with low level of plaques or low level of tangles, but these results were not significant.14,15
An earlier study suggests that AD risk can be identified up to 15 years prior to clinical diagnosis of AD based on tests of visual memory cognitive performance.15
Some investigations found no association between AD neuropathology and rates of global cognitive decline among elderly without dementia; however, these studies did find differences in memory performance.16,17
In one study, 134 individuals with no cognitive impairment or dementia before death were examined,17
and there was a significant relationship between AD neuropathology and declines in episodic memory suggesting that memory was more susceptible to changes in AD neuropathology. Similarly, another study examined cognitive performance in 48 clinically normal individuals with varying degrees of AD neuropathology at autopsy.16
Significant differences in rates of decline were only found on a memory test (cued selective reminding test). Declines in memory may serve as an earlier indication of preclinical dementia, although we were not able to detect this in our sample.
Many studies have found1–4
a relationship between AD neuropathology and rates of cognitive decline in older populations. Some of these studies, however, differ from our study in several important ways. First, some investigations1,4
have included individuals with dementia. Individuals already diagnosed with dementia could be more likely to have more rapid rates of cognitive decline and may be driving the association. Second, some of the studies2,3
examined cognitive performance at only one time point, precluding longitudinal assessment. Third, some studies were conducted in younger elderly individuals16
and the relationship between neuropathology and cognition may change with age. For example, in a recent study18
of younger elderly participants (mean baseline age: 79.8 years) who were followed 7.5 years on average, cognitively normal individuals with high levels of AD neuropathology showed significant declines on cognitive tests of praxis, verbal fluency, and delayed word list. Finally, methodology varied among different studies.
Typically, studies of cognitive decline in the elderly have been quantified with a linear rate of change or have used change point analyses to tease apart terminal declines from age-related changes.19–21
In contrast to these studies, we examined differences in trajectories of cognitive performance by using a model that incorporated potential learning effects at subsequent visits in relation to baseline cognitive performance. This approach enabled us to examine differences in trajectories of cognitive performance resulting from differences in level of AD pathology without imposing linear trajectories. Learning effects on the MMSE and the CVLT would not be as evident if we used a model that derived a rate of change from linear slopes.
We found evidence of learning effects on cognitive tests in individuals with low and high AD neuropathology. These findings suggest that after age 90, individuals without dementia have the ability to learn and retain content from these cognitive tests particularly when given at frequent intervals. Three recent studies that examined learning effects in the elderly found differing results.22–24
Two of these investigations show that learning can occur over time, even in persons with MCI.23,24
Interestingly, the study with the oldest-old22
did not suggest significant learning effects. Frequency of testing (annually vs biannually), differences in cognitive tests (i.e., CERAD Recognition vs CVLT), and the statistical methodology (regression slopes and mean change vs random effects model) are all factors that may have contributed to the differences in observed learning effects between that study and our study.
The current study in The 90+ Autopsy Study participants is unique in several ways. Participants were without dementia and aged 90 and older throughout the entire study (at entry and at death). These individuals were followed longitudinally and given comprehensive neuropsychological examinations and neurologic evaluations biannually. In addition, the sample of this study is larger than some of the previous studies, particularly for the oldest-old population. The frequency of cognitive testing, every 6 months, enabled us to look at cognitive performance across a large number of visits.
Limitations of this study deserve attention. First, our investigation is in the oldest-old, limiting our ability to comment on younger elderly. Furthermore, The 90+ Study participants are predominantly Caucasian, and well-educated, from the community of Laguna Woods, in Orange County, CA. These characteristics limit our ability to generalize our findings to other ethnic and racial groups. However, a recent report from the Census Bureau on the oldest-old suggests that characteristics of 90+ Study participants are actually similar to those of the oldest-old in the United States,25
particularly in regards to sex and ethnicity. Second, it is possible that we did not have enough power to find a true association that did exist. Third, we may have found differences by AD pathology if we had examined other cognitive tests. Only the CVLT and 3MS were examined because we thought we would be more likely to find cognitive declines in memory and global cognition with respect to greater AD pathology. In addition, these 2 cognitive tests provided us with the most complete data. Factors such as sensory deficits and fatigue make it difficult for participants to complete the entire test battery. For instance, 72% of participants in The 90+ Study have sensory deficits (i.e., vision loss) and at least 20% of participants report being fatigued.26
Fourth, we did not examine comorbid pathologies such as hippocampal sclerosis or cerebrovascular disease given the low prevalence of these pathologies in our participants without dementia. Hippocampal sclerosis is not found in the brains of our participants without dementia and less than 12% have infarcts at autopsy.8
Finally, we have recently shown in people without dementia that amyloid area shared a better relationship to cognition than CERAD plaque staging.27
This finding suggests that amyloid area, compared to CERAD plaque staging, may be a better measure of plaque neuropathology in the oldest-old.
The present study shows that in oldest-old without dementia, AD neuropathology is common, but not related to trajectories of cognitive performance over 3 years. These findings suggest cognition may not be affected by high levels of AD neuropathology in the oldest-old. It is possible that oldest-old individuals have the ability to withstand and tolerate the adverse effects associated with AD neuropathology. Alternatively, perhaps these individuals did not live long enough to develop the clinical effects of AD neuropathology. Health and lifestyle factors as well as other brain pathologies may be relevant for the expression of cognitive performance in the oldest-old. Further research must be conducted to better understand the relationship between cognitive performance and AD neuropathology in this extreme age group.