Overview

• Analysis of more than 50,000 standard MRI scans identified cortical thickness and grey matter volume as predictors of individual brain aging pace and linked faster aging to cognitive decline, frailty, disease and death
• DunedinPACNI, an AI model trained on midlife MRIs from over 1,000 Dunedin Study participants, estimates biological brain age from a single scan using correlations with a composite Pace of Aging score
• Participants flagged as “fast agers” by DunedinPACNI were 60 percent more likely to develop dementia, 18 percent more likely to receive a chronic disease diagnosis and 40 percent more likely to die over follow-up periods
• Researchers highlight that MRI-derived structural biomarkers capture aspects of brain aging that blood-based and molecular clocks cannot, complementing existing ageing measures
• Investigators caution that further research and validation are required before MRI-based aging assessments and DunedinPACNI can be integrated into clinical practice