Insights
25 August 2021
Investigating the role of cognitive reserve in cognitive aging
Can you tell us more about your research group?
The Biomarker Development for Postoperative Cognitive Impairment (BioCog) Consortium is a multi-disciplinary study group with partners in five European countries. We recruited around 1,000 older surgical patients and tracked their clinical and cognitive status from pre-surgery to several months thereafter. For our recent publication ‘Contribution of IQ in young adulthood to the associations of education and occupation with cognitive ability in older age’, we used our pre-operative study data and determined the association of typical cognitive reserve parameters with patients’ level of cognitive function.
What is the rationale behind your study?
As people grow older, they experience cognitive decline. They become a little slower, a little more forgetful, and so on, but cognitive ageing is a highly individual experience with inter-individual differences in rate and trajectories of this decline. Additionally, people also reach different peak levels in young adulthood.
Interestingly, it has been found that people with a higher cognitive reserve – a concept describing a higher ability to functionally “buffer” any age-related neuropathological changes in the brain – are more protected from cognitive decline. For instance, they have a lower risk of dementia. Typical cognitive reserve parameters include the highest level of education, the highest level of occupation, but also proxy measures such as socioeconomic status, income, or postcode.
Our group was keen to add to this evidence and to associate cognitive reserve not only with global cognitive ability in our sample of older adults but to additionally look at individual cognitive domains, such as memory, executive function or processing speed, to determine any domain-specific associations. We also wanted to tease out any potentially protective roles of education and occupation in preserving cognitive function into older age and did so by controlling for an estimate of peak pre-morbid ability at age 30. Thereby, we were able to investigate associations of education and occupation with old-age cognitive function with pre-morbid ability held constant.
We had previously validated our battery of cognitive tests, which included a mixture of CANTAB measures and more conventional tasks (Feinkohl et al., 2020)[1]. This meant that we could be confident that the battery was appropriate and that our results were valid.
Which methods did you use?
We included data from 623 BioCog participants. Participants were 65 years and older and scheduled for elective surgery in hospital sites in Berlin, Germany, and Utrecht, the Netherlands. All performed the cognitive test battery during the days before surgery and at several follow-up sessions thereafter. The battery included four CANTAB tests: Paired Associates Learning (PAL); Verbal Recognition Memory (VRM); Spatial Span (SSP); Simple Reaction Time (SRT) and two conventional paper-pencil tests (Grooved Pegboard; Trail-Making). Scores were treated as individual outcome measures and were additionally combined into a ‘g’ factor score of global cognitive ability. A vocabulary-based test estimated cognitive ability around age 30. Self-reported education and self-reported occupation (or if retired previous occupation) measured cognitive reserve.
Tell us about your key findings?
We found that people with a higher level of education had a higher level of cognitive function in older age, even when age, sex, cognitive function at age 30, and depressive symptoms were controlled for. In addition to the global ability factor ‘g’, this was seen for the Trail-Making test of executive function, and for the Spatial Span test and Paired Associates Learning from the CANTAB battery. The pattern of results indicated that the finding was driven by participants in the highest education group (tertiary education), whereas there was no real difference in late-life cognitive function among the lower education groups (primary to post-secondary, non-tertiary) in our statistical model. For occupation, the results were less consistent.
What are the implications of your study?
We can speculate that there may be a beneficial effect of spending a longer time in education on late-life cognitive function. We would need RCTs to truly test this hypothesis, but unfortunately, such study designs would be unethical and are thus impossible to conduct in this context.We found that people with a higher level of education had a higher level of cognitive function in older age, even when age, sex, cognitive function at age 30, and depressive symptoms were controlled for. In addition to the global ability factor ‘g’, this was seen for the Trail-Making test of executive function, and for the Spatial Span test and Paired Associates Learning from the CANTAB battery. The pattern of results indicated that the finding was driven by participants in the highest education group (tertiary education), whereas there was no real difference in late-life cognitive function among the lower education groups (primary to post-secondary, non-tertiary) in our statistical model. For occupation, the results were less consistent.
Why did you choose CANTAB?
Our research examines individual differences in abilities in a population that is affected not only by age-related cognitive deficits but also by age-related diseases such as arthritis, and by computer anxiety, which both severely complicate computerised assessment. We also included participants from two countries speaking two different languages. Thus, we required cognitive tests that are easily administered, avoid substantial interaction of participants with computers (i.e., can be performed on hand-held devices), are multi-lingual, and are capable of producing reliable, electronically saved results. CANTAB fulfilled all of these prerequisites.
What are the next steps for your research?
We are tracking the BioCog participants longitudinally. Our future work will determine the role of education and occupation in participants’ risk of developing postoperative cognitive impairment during the days to months after surgery.
We also measured genetic and blood biomarkers in BioCog and will next find out whether these factors are related to participants’ individual cognitive risk before and after surgery, and whether they may interact with cognitive reserve in doing so. Ultimately, we may be able to identify patients who are most at risk.
References
1. Feinkohl I, Borchers F, Burkhardt S, Krampe H, Kraft A, Speidel S, Kant IMJ, van Montfort SJT, Aarts E, Kruppa J, Slooter A, Winterer G, Pischon T, Spies C (2020) Stability of neuropsychological test performance in older adults serving as normative controls for a study on postoperative cognitive dysfunction. BMC Research Notes 13(1):55. doi: 10.1186/s13104-020-4919-3.
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