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A study in PLOS Medicine found that dementia, mild cognitive impairment, alcohol addiction and several psychiatric conditions were associated with higher estimates of brain age relative to chronological age. The analysis found different patterns across brain regions, but it cannot show that the conditions cause faster brain aging.
A study published in PLOS Medicine found that people with dementia, mild cognitive impairment, alcohol addiction and some psychiatric conditions had higher estimates of brain age than controls, based on structural MRI scans. The findings link these conditions to distinct patterns across brain regions, but do not establish that any condition causes the brain to age faster.
Led by Shile Qi of Nanjing University of Aeronautics and Astronautics in China, the research compared brain scans from 2,698 people with a range of conditions and differences against scans from 45,900 controls drawn from several imaging databases. The conditions included Alzheimer’s disease, mild cognitive impairment, schizophrenia, bipolar disorder, major depressive disorder, alcohol or tobacco addiction, ADHD and autism spectrum disorder.
The researchers used predictive age difference (PAD), a measure comparing a person’s chronological age with an age estimated from brain imaging. A positive PAD indicates that the brain appears older than expected for that person’s age. Among the conditions studied, Alzheimer’s disease and mild cognitive impairment had the strongest associations with higher PAD. Addiction and psychiatric disorders were also associated with higher values. The study found no overall PAD differences between controls and people with ADHD or autism.
The analysis also examined estimates in specific brain regions and compared them with gene-expression patterns. The prefrontal cortex showed higher PAD across multiple disorders. Psychiatric conditions were associated with higher PAD in frontal and temporal areas, while dementia was associated with higher PAD in frontal and occipital regions. Addiction showed a different distribution, including the default mode and salience networks, putamen and thalamus.
Brain Age Estimates Differ by Disorder
The findings suggest that a single estimate of brain age may not capture the same pattern across all conditions. The researchers report that different disorders were associated with differences in different brain regions, which could help investigators study how conditions relate to brain structure and underlying biology.
The work may inform research into future biomarkers, or measurable signals that could help characterize disorders. The study does not establish that PAD can diagnose a condition, predict an individual’s future health or guide treatment. Its results describe associations across groups, and further research would be needed to determine whether these estimates are useful in clinical settings.
How Researchers Estimate Brain Age
Brain-age estimates use imaging data to predict a person’s age from features of the brain. Researchers can then compare that estimate with the person’s actual age. In this study, the difference was expressed as predictive age difference; a positive value means the estimated brain age was higher than chronological age.
The analysis drew on MRI scans from several databases and assessed a range of neurological and psychiatric conditions, along with addiction and neurodevelopmental differences. The authors also examined gene transcription patterns to explore whether regional findings might align with distinct biological processes. These analyses identify patterns for further study; they do not show that gene-expression differences caused the PAD results.
““Different neurological disorders appear to leave different signatures on the brain aging clock, which may help researchers better understand the neural and biological pathways involved in these conditions.””
— The study authors
Limits of the Brain Age Findings
The study is correlational, so it cannot determine whether the conditions contribute to higher PAD, whether other factors influence both, or whether the relationship runs in another direction. Psychiatric disorders and addiction can also occur together, making it difficult to isolate the association for any one condition.
The report does not establish that an individual’s PAD can be used to diagnose a disorder or measure its severity. It also does not show whether the observed estimates change over time. The analysis reports group-level associations, and the clinical meaning of PAD remains to be established.
Further Studies Needed on PAD
The authors suggest that closer study of predictive age difference could help researchers investigate potential biomarkers and biological pathways associated with brain disorders. Further research will need to examine how well the patterns hold across other groups and whether PAD can provide reliable information about individuals.
The study was supported by the Key Research and Development Plan of Jiangsu Province and the National Natural Science Foundation of China. The report says the funders had no role in the study’s design, data collection or analysis, decision to publish, or manuscript preparation. No specific next study or clinical application was announced in the report.
Key Questions
Which conditions were associated with higher brain-age estimates?
The study found higher predictive age difference associated with Alzheimer’s disease, mild cognitive impairment, addiction and psychiatric disorders. Alzheimer’s disease and mild cognitive impairment showed the strongest associations among the conditions examined.
Did the study find higher estimates for ADHD or autism?
The researchers found no overall PAD differences between controls and people with ADHD or autism spectrum disorder in this analysis.
Does the research show that these disorders cause faster brain aging?
No. The study found correlations between conditions and brain-age estimates. It cannot establish that a condition causes the brain to age faster.
What does a positive predictive age difference mean?
A positive predictive age difference means the age estimated from brain imaging is higher than the person’s chronological age.
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