Clinical Manifestations.

Background: Although it has been estimated that modifiable risk factors account for around 40% of population variability in dementia risk, understanding how risk factors are related to one another and to brain pathology and cognition has been challenging. We used a clustering approach to examine patterns of risk factor interrelationships and to investigate how these patterns affect relationships between pathology and cognition.

Method: We collected risk factor data concerning health, lifestyle, sleep, and personality from 149 cognitively normal older adults (73±6.2 years), as well as PET-measured amyloid (11C-Pittsburgh compound-B, PiB) and, in a subsample (n = 126), PET-measured tau (18F-Flortaucipir, FTP). All participants completed longitudinal neuropsychological testing (follow-up 8.1±4.2 years). K-means clustering was used to assign participants to different risk profiles that reflected how risk factors were interrelated. Linear mixed-effects models were used to assess associations between decline in 1) episodic memory (EM) and 2) non-memory (NM) cognition composite scores, with cluster assignment and PiB-status (±) or entorhinal FTP uptake as predictors. Analyses were age and sex adjusted.

Result: K-means clustering generated 3 distinct risk-related profiles, with more favorable profiles seen for participants in cluster 1 (physical/cognitive activity, education) and cluster 2 (sleep, depression, personality) than cluster 3 (Figure 1). In a model predicting NM decline with PiB-status as a predictor, we observed a significant three-way interaction between PiB-status, cluster, and time (p<0.01) with an attenuated effect of Aβ on NM decline in cluster 1 (β = 3.7, p<0.01) and cluster 2 (β = 3.7, p<0.01) compared to cluster 3. A model predicting EM revealed no significant interaction between cluster, PiB-status and time (Figure 2). While a significant entorhinal tau x time effect was observed in a model predicting EM decline, cluster assignment did not modify this relationship. Results were similar when APOE4 status was included in the models.

Conclusion: Favorable risk profiles (cluster 1 and 2) attenuated the effect of Aβ, but not tau, on cognitive decline. These findings suggest that different risk profiles moderate pathology-cognition relationships, and demonstrate that different factors may operate together in reducing risk. This highlights the role of groups of modifiable resilience factors in mitigating the effects of Aβ deposition.