Abstract
A number of studies have observed a remarkable and high heterogeneity in brain and cognitive aging, with some people showing the ability to better cope with brain pathology than others. Indeed, some individuals are less susceptible to age-related or neurodegenerative processes and are capable of preserving cognitive abilities despite emerging pathologic changes. Such findings led to the wide use of the terms cognitive resilience and/or brain resilience, which refer to the relative preservation of function (e.g., cognition) or brain structure (e.g., cortical thickness) in the face of Alzheimer disease (AD)–related significant pathologic burden. Given the substantial lack of effective drugs for most of the neurodegenerative diseases, understanding the determinants of brain resilience can be considered a holy grail of neuroscience. AD is characterized clinically by a gradual decline in cognitive functions that have an impact on everyday activities. Dementia is preceded by progressive neurodegeneration and the deposition of extracellular beta-amyloid (Aβ) aggregates and intracellular accumulation of hyperphosphorylated tau-containing neurofibrillary tangles. These proteinopathies are believed to be responsible for the impairment in neuronal function and cognitive abilities that define the disease, with tau pathology being more strongly associated with clinical severity and neurodegeneration.
Although resilience can be considered a robust scientific finding, its underlying mechanisms are still poorly understood. Current theories encompass various potential mechanisms, such as a greater preexisting neurobiological capacity, a more optimal utilization of cerebral resources, and/or the supplementary activation of cerebral networks through compensatory mechanisms. Previous studies investigated the relationship between different variables and cognitive status and neuropathology, including demographic (e.g., age and gender), genetic (APOE-e4 genotype), neuroimaging (cortical atrophy), and reserve-related (education, intracranial volume [ICV]) data in AD. Such studies mainly rely on cross-sectional measures of cognitive performance and neural structure, which are indicators of the current state of the brain, encompassing both functional and structural aspects. However, this state is contingent upon the premorbid level of individuals, such as their initial cognitive abilities or the extent of their brain resources, as well as the rate at which cognitive decline or brain atrophy occurs over time. Therefore, for any factor potentially associated with resilience in a cross-sectional manner, the specific pathway through which this is achieved remains unclear. As such, longitudinal studies are needed to disentangle whether determinants of resilience yield a baseline advantage (i.e., “difference in intercepts” or “preserved differentiation”) or provide a longitudinal advantage (i.e., “difference in slopes” or “differential preservation”).
To this aim, Bocancea and colleagues (2023) report on a remarkable longitudinal study, published in a very recent issue of Brain, in which they investigated whether age, sex, APOE-ε4 status, education, ICV, and cortical thickness relate to cognitive and brain resilience, with an effort on segregating longitudinal from cross-sectional effects. In particular, the authors evaluated whether these variables moderate the association of baseline tau burden with longitudinal cognitive decline or cortical thinning and whether they are directly related to rates of change above and beyond the effects of tau or rather to cross-sectional cognition and cortical thickness. A total of 371 participants Aβ-positive individuals with mild cognitive impairment (MCI, n = 152) and AD-type dementia (n = 219) were included across five cohorts: the Swedish BioFINDER-1 study at Lund University, the University of California San Francisco AD Research Center, the Alzheimer Disease Neuroimaging Initiative, and the Avid Radiopharmaceuticals studies. All selected participants underwent a tau positron emission tomography (PET) scan, a medical history assessment and neurological examination, structural magnetic resonance imaging, and neuropsychological assessments, including the Mini-Mental State Examination (MMSE), mostly at two time points. Cognitive and brain resilience were operationalized as the degree to which either cognition or cortical thickness showed relative preservation over time given the degree of tau pathology observed at baseline. The authors used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. The models assessed whether age, sex, years of education, APOE-ε4 status, and ICV (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. The results showed that uptake in the temporal meta-regions of interest (ROI) showed a significant negative association with cognitive decline. Interaction analyses indicated that older age, higher education, and higher ICV were associated with a stronger (more negative) effect of temporal ROI tau burden on longitudinal decline in the MMSE. All three variables also moderated the association of global tau PET with cognitive decline. These models additionally revealed a conditional main effect of age and education on baseline levels of cognitive performance. Thus, at a given level of tau pathology, being older at the time of the tau PET was associated with worse cognitive performance. In contrast, higher education was associated with better cross-sectional cognition, while higher ICV was not related to cognitive performance at baseline. There was no significant interaction with tau burden for cortical thickness, sex, and APOE-ε4 status. The analyses also revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness. To sum up, this longitudinal multicohort study of clinically impaired participants with underlying AD neuropathology found that age, education, ICV, and cortical thickness play a role in cognitive resilience, while age and education contribute to brain resilience. Interestingly, the results show that level of education is positively associated with baseline cognitive performance while it negatively moderates the impact of tau burden on cognitive decline.
Educational attainment has long been linked with increased cognitive function over the life span, less microstructural damage in AD-related brain areas, and lowered risk of AD. Education works to help improve childhood cognition and, through that, lifetime cognitive ability but is not generally believed to be associated with the rate of normal cognitive aging. Indeed, several lines of evidence suggest that education might delay the onset of symptoms of neuropathology, through compensative processes, until the neuropathology progresses to a threshold where cognitive decline can no longer be masked, and cognitive decline is, thereafter, more rapid than would be predicted by a normal aging trajectory. The study by Bocancea and colleagues (2023) is in line with previous literature, revealing a positive association between education and cross-sectional cognition at comparable levels of tau (i.e., difference in intercepts) but a detrimental interactive association between education and tau burden on cognitive decline (i.e., difference in slopes). Thus, the association of education with cognition and decline in the presence of tau pathology can be best summarized as “reduced differentiation.”
Although the study suffers from a number of limitations (e.g., the lack of specific cognitive measures, the absence of tau longitudinal data, and the possible heterogeneity given by the multisite nature of the study), its results have important implications for future clinical trials in AD. With the emergence of therapeutics that specifically target tau, individuals who already possess tau pathological alterations in the brain are being recruited for both current and forthcoming trials. It is critically important to attain the capability of predicting the progression and deterioration of these individuals with greater precision, particularly during the duration of the trial. This is crucial in order to properly observe the potential advantages of medication on clinical outcomes and select suitable covariates for the efficacy analyses.