ArticleAlzheimer's & dementia (Amsterdam, Netherlands)
Association between BrainAGE and Alzheimer's disease biomarkers.
Article in Alzheimer's & dementia (Amsterdam, Netherlands). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Association of imaging-defined brain age with disease severity and adverse outcomes in CADASIL.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Spatial amyloid-informed multimodal brain age as an early marker of Alzheimer's-related vulnerability and risk stratification.The journal of prevention of Alzheimer's disease · 2026Article
- Regional brain age is decreased in children with sickle cell anemia.Blood advances · 2026Article
- Association between low-frequency oscillations in blood pressure variability and brain age derived from neuroimaging.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- BrainAge moderates associations between Alzheimer's disease biomarkers and cognitive decline: a meta-analysis across A4/LEARN, HABS and ADNI cohorts.medRxiv : the preprint server for health sciences · 2025Article
- Association between BrainAGE and Alzheimer's disease biomarkers: Comment.Alzheimer's & dementia (Amsterdam, Netherlands)Article
- From amyloid PET to plasma biomarkers: A multimodal imaging framework for early diagnosis and staging of Alzheimer's disease.Alzheimer's & dementia (Amsterdam, Netherlands)Review
- Association between BrainAGE and Alzheimer's disease biomarkers.Alzheimer's & dementia (Amsterdam, Netherlands)Article
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Authors and funding
17 authors.
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Abstract
introductionThe brain age gap estimation (BrainAGE) method uses a machine learning model to generate an age estimate from structural magnetic resonance imaging (MRI) scans. The goal was to study the association of brain age with Alzheimer's disease (AD) imaging and plasma biomarkers.
methodsOne hundred twenty-three individuals from the Indiana Memory and Aging Study underwent structural MRI, amyloid and tau positron emission tomography (PET), and plasma sampling. The MRI scans were processed using the software program BrainAgeR to receive a "brain age" estimate. Plasma biomarker concentrations were measured, and partial Pearson correlation models were used to evaluate their relationship with brain age gap (BAG) estimation (BrainAGE = chronological age - MRI estimated brain age).
resultsSignificant associations between BAG and amyloid and tau levels on PET and in plasma were observed depending on diagnostic categories. DISCUSSION: These findings suggest that BAG is potentially a biomarker of pathology in AD which can be applied to routine brain imaging. Highlights: Novel research that uses an artificial intelligence learning tool to estimate brain age.Findings suggest that brain age gap is associated with plasma and positron emission tomography Alzheimer's disease (AD) biomarkers.Differential relationships are seen in different stages of disease (preclinical vs. clinical).Results could play a role in early AD diagnosis and treatment.
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