Introduction : This thesis intends to explore brain and cognitive resilience as measured by the residual method in individuals at risk of Alzheimer's disease (AD). We assess demographic, clinical, cognitive, brain, genetic, and blood biomarker factors that have been associated with markers of resilience. Additionally, we investigate the impact of resilience on cognitive trajectories over time.
Methods : We included 109 participants with a diagnosis of mild cognitive impairment (MCI) recruited at the Geneva Memory Center (GMC). Linear models were performed: The first model was built using normalized hippocampal volumes as dependent variable and amyloid centiloid value and global tau SUVr as independent variables. Standardized residuals from this model was used as measure of brain resilience (BR). The second model was performed using Mini Mental State Examination (MMSE) as dependent variable and amyloid centiloid value and global tau SUVr as independent variables. Standardized residuals were used as measures of cognitive resilience (CR). Bivariate linear models were then performed to assess associations between measures of
resilience and age, sex, number of years of education, smoke and alcohol consumption, hypertension, hypercholesterolemia, cardiovascular disease, depression and anxiety, Immediate Recall score, medial temporal lobe atrophy (MTA), APOE ε4 carrier, plasma NfL(Neurofilament light chain) and plasma GFAP (Glial Fibrillary Acidic Protein), which have either been associated to markers of resilience or to risk/protective factors against AD. Finally, longitudinal analysis was conducted using linear mixed models to test the association of our measures of resilience with cognitive changes over time.
Results : BR was significantly associated with age (stβ = -0.44; p < .001), plasma NfL (stβ = -0.39; p < .001) and plasma GFAP (stβ = -0.41; p < .001). A significant association was found between CR and Immediate Recall score (stβ = 0.28; p 0.004). Separate linear mixed models showed that changes in MMSE scores were associated with measures of continuous BR and continuous CR over time (β [SE] =0.70 [0.26]; p = .006; 2.31 [0.11]; p < .001) and a significant association between time and CR was found (-0.466 [0.21]; p = 0.029; -0.46 [0.22]; p = 0.038).
Conclusion : Our findings showed that BR was associated with neurodegeneration and neuroinflammation markers (NfL and GFAP). BR predicts cognitive decline but not cognitive decline rate, while higher CR predicts faster decline. However, CR's weak associations with proxies such as education that has been commonly used in previous studies call for more investigations.
Gaining a deeper understanding of resilience in Alzheimer's disease has the potential to inform and refine dementia prevention strategies.
