Welcome to Psychiatryai.com: Latest Evidence - RAISR4D

Estimated reading time for CME/CPD: 2 mins

Identification and phenotypic profiling of subgroups with distinct cognitive aging trajectories

AI Summary
  • Data-driven subgroups of long-term cognitive aging trajectories identified in 696 dementia-free older adults over an average 13-year follow-up.
  • Favourable trajectories linked to faster gait speed, higher health-related quality of life, more physical and cognitive activity, and greater plant-based food intake.
  • Findings emphasise substantial heterogeneity in cognitive aging and indicate modifiable behavioural and health-related factors as targets for multidisciplinary prevention strategies.
Summarise with AI (MRCPsych/FRANZCP)

Geroscience. 2026 Aug 7. doi: 10.1007/s11357-026-02455-w. Online ahead of print.

ABSTRACT

Cognitive aging is shaped by genetic variation, environmental factors, and health-related conditions. Until now, it is largely unclear why some individuals maintain their cognitive function, and others show progressive cognitive decline. This study uncovered determinants of distinct cognitive aging trajectories in the older population. To approach the inter-individual variability in cognitive aging, we clustered n = 696 dementia-free individuals from the prospective TREND study based on their longitudinal changes in comprehensive cognitive testing every 2 years over 13 years on average. Identified subgroups of cognitive aging were tested for differences in general physical health, motor function, mental and neuropsychological health, personality, lifestyle, diet, and genetic and biofluid markers as observed at the phenotypes’ initial records. Comparing the best- and lowest-performing subgroups of cognitive aging, we found that individuals who maintain high cognitive function compared to those with low baseline and progressive cognitive decline showed significant faster gait speed, higher health-related quality of life, did sports and cognitive stimulating activities more frequently, and reported higher plant-based foods intake. Although there are fewer phenotypic differences involving the intermediate subgroups of cognitive aging, the best-performing subgroup compared to all other subgroups showed higher plant-based foods intake. Overall, this study identifies distinct, data-driven subgroups of long-term cognitive aging trajectories and reveals factors associated with these divergent paths using deeply phenotyped data. The findings highlight the substantial heterogeneity of cognitive aging and suggest that favorable trajectories are linked to modifiable behavioral and health-related characteristics, providing a foundation for future multidisciplinary strategies to promote healthy cognitive aging.

PMID:42566156 | DOI:10.1007/s11357-026-02455-w

Document this CPD

Share Evidence Blueprint

QR Code

Save to Google Notes

Search Google Scholar

Save as PDF

My Revision List

close chatgpt icon
ChatGPT

Enter your request.

Psychiatry AI: Real-Time AI Scoping Review
← →
RAISR4D CME/CPD Evidence Nodes
Swipe to navigate RAISR4D CME/CPD evidence nodes.
CME/CPD