Study of 2,698 Patients Maps Distinct Brain-Aging Signatures in Dementia and Addiction
Updated
Updated · Starts at 60 · Jul 21
Study of 2,698 Patients Maps Distinct Brain-Aging Signatures in Dementia and Addiction
3 articles · Updated · Starts at 60 · Jul 21
Summary
MRI analysis of 2,698 patients found Alzheimer’s disease and mild cognitive impairment had the strongest links to older-looking brains, using predictive age difference scores against actual age.
A 45,900-person control group showed addiction and psychiatric disorders also tracked with accelerated brain ageing, though less strongly, while ADHD and autism showed no meaningful brain-age gap.
The prefrontal cortex aged faster across almost all conditions, but the regional patterns diverged: dementia clustered in frontal and occipital areas, psychiatric disorders in frontal and temporal regions, and addiction in key brain networks plus the putamen and thalamus.
Gene-expression differences matched those regional patterns, adding biological support, though the PLOS Medicine study was correlational and overlapping diagnoses may blur condition-specific effects.
Researchers said the brain-age measure could eventually serve as a biomarker to detect or track disorders earlier and more precisely from routine brain scans.
Why do schizophrenia and depression age the brain, while developmental disorders like autism and ADHD do not?
A new scan can reveal your brain's 'true' age. Are we prepared for the ethical consequences of this knowledge?
If social inequality is a top driver of brain aging, what policies can best protect our neurological health?
Mapping Predictive Age Difference (PAD): Distinct Brain Aging Signatures Across Neurological and Psychiatric Disorders
Overview
In July 2026, Shile Qi and colleagues published a landmark international study in PLOS Medicine that analyzed a large number of structural MRI scans to map how different neurological and psychiatric conditions affect brain aging. Using advanced imaging and machine learning techniques, the researchers estimated each individual's 'brain age' and introduced the Predictive Age Difference (PAD) metric, which measures the gap between chronological and brain age. A higher PAD indicates accelerated brain aging. This approach provided crucial insights into the unique patterns of brain aging across various disorders, helping to better understand their impact on the brain.