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A study published in PLOS Medicine analyzed brain MRIs from roughly 48,600 people and found that Alzheimer’s disease, mild cognitive impairment, addiction and psychiatric disorders were associated with brains appearing older than expected. Different conditions showed distinct regional aging patterns, but the research is correlational and does not prove causation.
A study published in the open-access journal PLOS Medicine has found that people with dementia, mild cognitive impairment, alcohol addiction and psychiatric conditions such as schizophrenia may show signs of accelerated brain aging, with different disorders linked to distinct patterns of aging across brain regions. The research, led by Shile Qi of Nanjing University of Aeronautics and Astronautics in China, compared structural MRI scans from 45,900 controls against scans from 2,698 people with a range of neurological and psychiatric diagnoses. The authors suggest the findings could eventually support new biomarkers for common brain disorders, while cautioning that the results do not show these conditions directly cause faster brain aging.
The researchers used a measure called predictive age difference (PAD), which compares a person’s chronological age with an age estimated from brain imaging. A positive PAD means the brain appears older than would typically be expected for that person’s age. The team analyzed structural MRI data from 45,900 controls drawn from several brain imaging databases, then compared those scans with data from people diagnosed with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), alcohol or tobacco addiction, Alzheimer’s disease (AD), mild cognitive impairment (MCI), schizophrenia, bipolar disorder or major depressive disorder.
Among the conditions examined, the neurodegenerative disorders Alzheimer’s disease and MCI showed the strongest associations with higher PAD values, suggesting the greatest degree of accelerated brain aging, according to the study. Addiction and psychiatric disorders were also associated with increased PAD. By contrast, the researchers found no overall differences in PAD between controls and people with ADHD or ASD.
The study also mapped PAD across individual brain regions. The prefrontal cortex showed higher PAD across multiple brain disorders. Psychiatric disorders were associated with elevated PAD in the frontal and temporal lobes, while dementia was linked to higher PAD in the frontal and occipital cortex. Addiction showed a different pattern, with higher PAD observed in the default mode network, the salience network, the putamen and the thalamus. The researchers additionally identified differences in gene transcription associated with particular conditions, suggesting the observed aging patterns may be linked to distinct underlying biological processes.
Why Faster Brain Aging Patterns Matter
The study’s main value lies in showing that brain disorders may leave measurable, region-specific signatures on the brain aging clock rather than a uniform pattern of decline. If validated, this could help researchers distinguish the biological pathways involved in different conditions — for example, separating the mechanisms driving neurodegeneration in Alzheimer’s disease from those associated with addiction or schizophrenia.
The authors suggest that studying PAD more closely could eventually help identify biomarkers associated with common brain disorders. Biomarkers of this kind could in principle aid earlier diagnosis or help track disease progression, though any clinical application remains speculative at this stage. The finding that ADHD and ASD showed no overall PAD differences also adds information about which conditions do and do not align with accelerated structural brain aging.
How Scientists Measure Brain Age
Researchers can estimate whether a person’s brain appears older or younger than expected for their chronological age using brain imaging. The PAD measure used in this study compares a person’s actual age with an age predicted from their MRI scans. Machine-learning models trained on large sets of healthy brain scans learn what a typical brain at a given age looks like, then estimate an individual’s brain age; the gap between predicted and actual age serves as an index of accelerated or decelerated aging.
The study drew on aggregated data from multiple brain imaging databases to build its control sample of 45,900 people, alongside the 2,698 participants with diagnosed conditions. The work was supported by the Key Research and Development Plan of Jiangsu Province, China (BE2023668) and the National Natural Science Foundation of China (62376124), both awarded to Shile Qi. The funders had no role in study design, data collection and analysis, the decision to publish, or preparation of the manuscript.
“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.”
— Study authors, PLOS Medicine
Causation Still Unproven
The study is correlational and does not demonstrate that any of these conditions directly cause accelerated brain aging. It remains possible that other factors — including shared underlying biology, medication effects, or lifestyle differences — contribute to the observed PAD differences.
The authors also note that some conditions, particularly psychiatric disorders and addiction, frequently occur together, which can make their individual effects difficult to separate. It is not yet clear whether the identified gene transcription differences are a cause or a consequence of the regional aging patterns. The study also does not establish whether PAD can predict individual clinical outcomes, and no diagnostic or clinical use of the measure has been validated.
Path Toward Clinical Biomarkers
The researchers suggest that further study of PAD could help identify biomarkers associated with common brain disorders and provide new clues about the biological pathways involved. Follow-up work would likely need to test whether the condition-specific regional patterns hold in independent datasets, disentangle the overlapping effects of co-occurring psychiatric and addiction conditions, and examine whether higher PAD predicts future cognitive decline in individuals. No timeline for clinical applications was given.
Key Questions
What is predictive age difference (PAD)?
PAD compares a person’s chronological age with an age estimated from brain imaging. A positive PAD means the brain appears older than typically expected for that person’s age.
Which conditions were linked to the fastest brain aging?
Alzheimer’s disease and mild cognitive impairment showed the strongest associations with higher PAD. Alcohol and tobacco addiction and psychiatric disorders such as schizophrenia were also associated with increased PAD.
Did ADHD or autism show accelerated brain aging?
No. The researchers found no overall differences in PAD between controls and people with ADHD or autism spectrum disorder in this study.
Does this mean these disorders cause the brain to age faster?
No. The study is correlational, and the authors state the findings do not show that these conditions directly cause accelerated brain aging. Co-occurring conditions also make individual effects hard to separate.
Could this lead to a diagnostic test?
Not yet. The authors suggest PAD research could eventually help identify biomarkers for common brain disorders, but no clinical application has been developed or validated.
Source: rss
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