Using AI to Identify Brain and Immune Biomarkers in Older Adults at Risk of Dementia for Better Prevention Strategies

What this Trial Is About

Researchers are investigating the diversity of cognitive conditions known as Subjective Cognitive Decline SCD and Mild Cognitive Impairment MCI, which may lead to different types of dementia. The study uses advanced data analysis on brain imaging and inflammatory markers to identify groups of older adults at high risk of progressing to dementia. This approach hopes to develop personalized early interventions by understanding brain structure, blood flow, and immune cell activity related to cognitive decline. Participants include older adults diagnosed with MCI or SCD, along with healthy volunteers. The study divides participants into groups receiving either a 7-month multidomain training program or no training. The training involves supervised cognitive exercises, physical aerobic activity, and music therapy, scheduled as multiple weekly sessions. Brain scans using MR imaging and blood samples are collected at various times to assess brain structure, blood flow, and immune markers, with follow-ups extending up to 28 months. Throughout the study, participants undergo cognitive testing assessing memory, attention, and executive function at several time points. Brain imaging and blood tests are performed to monitor changes in brain volume, cerebral blood flow, and inflammation. The study compares outcomes between trained and untrained groups at 7, 14, and 28 months to evaluate short-term training effects and sample stratification. This comprehensive monitoring aims to identify biomarkers and patterns to better inform prevention strategies against dementia.

Identification of Neuroinflammation and Neuroimaging Biomarkers Through Data Driven Artificial Intelligence Techniques for Unraveling the Heterogeneity of Aged Subjects at Risk of Dementia and to Better Inform Prevention Strategies