Predictive value of the Alzheimer polygenic risk score on cognitive decline in patients with mild cognitive impairment and Alzheimer's disease dementia
Abstract
Background Polygenic risk scores for Alzheimer’s disease (AD-PRS) are widely used to estimate genetic susceptibility to AD, but their relationship with the rate of cognitive decline (CD) after clinical onset remains insufficiently characterized. Objectives To examine the association between AD-PRS and longitudinal CD across the AD spectrum and to evaluate the predictive contribution of individual AD-PRS variants. Design Large longitudinal observational study in a single-center cohort, with an external cohort to assess generalizability. Setting Memory clinic cohort from Ace Alzheimer Center Barcelona (Ace) with external cohort using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Participants The study included 7,233 patients from Ace and 863 from ADNI, with a mean follow-up of 5.4 years in Ace and 3.6 years in ADNI. A biomarker sub-cohort included 1075 participants from Ace and 569 from ADNI. Measurements CD was quantified as the annual change in Mini-Mental State Examination (MMSE) scores estimated using linear mixed-effects models. Associations between AD-PRS and longitudinal MMSE trajectories were tested adjusting for clinical and sociodemographic (CSD) variables and APOE genotype. Machine learning models and SHapley Additive exPlanations (SHAP) were used to evaluate the predictive relevance of individual variants. Results Higher AD-PRS was associated with faster CD in the full clinical cohort and in biomarker subset, independently of APOE genotype. AD-PRS was not associated with baseline MMSE. APOE ε4 was associated with lower baseline MMSE and faster CD only in the full clinical sample. Genetic predictors provided limited improvement beyond CSD variables, and model performance showed limited reproducibility across cohorts. Conclusions AD-PRS is associated with longitudinal CD across the AD spectrum. Although polygenic burden contributes to variability in cognitive trajectories, its added predictive value beyond routinely available clinical variables remains modest.