Natural Trajectories of Cognitive Aging in Cognitively Normal Older Adults

Identifying patterns of cognitive change over time is critical for understanding the aging process and detecting early signs of decline. In this study, we analyzed longitudinal data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to uncover distinct patterns of cognitive trajectories among cognitively unimpaired older adults. Participants’ composite cognitive scores across multiple domains were examined (e.g., executive function and memory) using a data-driven clustering approach to group individuals with similar patterns of change across repeated assessments. This enables us to capture the heterogeneity in cognitive trajectories without predefined assumptions about the shape and direction of change. To better understand the characteristics associated with these trajectories, we compared clinical characteristics, genetic profiles (APOE status), and blood biomarkers related to neurodegeneration between the latent groups. Our findings highlight the potential of clustering longitudinal cognitive data to characterize diverse patterns of cognitive aging in cognitively normal older adults. This approach provides a framework for exploring factors that may contribute to cognitive maintenance or decline. Such insights may inform targeted strategies for early risk detection, personalized intervention, and a deeper understanding of cognitive aging.