ArticleAlzheimer's & dementia (Amsterdam, Netherlands)
NeuropsychBrainAge: A biomarker for conversion from mild cognitive impairment to Alzheimer's disease.
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 13 papers.
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Who cites it
13 citing papers in PubMed, 15 citations in OpenAlex.
- Source-space EEG alpha activity reveals brain age gaps due to neurodegeneration and disparity.Communications biology · 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
- Clinical impact of the Alzheimer's Disease Neuroimaging Initiative: A review of studies using ADNI data (2023 to June 2025).Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Review
- Article
- Cognitive Age Delta as a Marker of Healthy and Pathological Cognitive Aging: The Role of Lifestyle, Cognitive Reserve, and Vascular Risk.Journal of clinical medicine · 2025Article
- Aging as an active player in Alzheimer's disease classification: Insights from feature selection in BrainAge models.NeuroImage · 2025Article
- Aging as an active player in Alzheimer's Disease Classification: Insights from feature selection in BrainAge Models.medRxiv : the preprint server for health sciences · 2025Article
- Mind the Gap: Does Brain Age Improve Alzheimer's Disease Prediction?Human brain mapping · 2025Article
- Advanced Brain Age Prediction Using Multi-Head Self-Attention: A Comparative Analysis of Western and Middle Eastern MRI Datasets.Research square · 2025Article
- Brain age as a biomarker for pathological versus healthy ageing - a REMEMBER study.Alzheimer's research & therapy · 2024Article
- Age-disproportionate atrophy in Alzheimer's disease and Parkinson's disease spectra.Alzheimer's & dementia (Amsterdam, Netherlands)Article
- Game-Based Cognitive Aging Assessment: Toward a Digital Biomarker of Cognitive Health.Digital biomarkersArticle
- NeuropsychBrainAge: A biomarker for conversion from mild cognitive impairment to Alzheimer's disease.Alzheimer's & dementia (Amsterdam, Netherlands)Article
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Authors and funding
3 authors at 2 institutions in 1 country.
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Abstract
introductionBrainAge models based on neuroimaging data have diagnostic classification power but have replicability issues due to site and patient variability. BrainAge models trained on neuropsychological tests could help distinguish stable mild cognitive impairment (sMCI) from progressive MCI (pMCI) to Alzheimer's disease (AD).
methodsA linear regressor BrainAge model was trained on healthy controls using neuropsychological tests and neuroimaging features separately. The BrainAge delta, predicted age minus chronological age, was used to distinguish between sMCI and pMCI.
resultsThe cross-validated area under the receiver-operating characteristic (ROC) curve for sMCI versus pMCI was 0.91 for neuropsychological features in contrast to 0.68 for neuroimaging features. The BrainAge delta was correlated with the time to conversion, the time taken for a pMCI subject to convert to AD. DISCUSSION: The BrainAge delta from neuropsychological tests is a good biomarker to distinguish between sMCI and pMCI. Other neurological and psychiatric disorders could be studied using this strategy. Highlights: BrainAge models based on neuropsychological tests outperform models based on neuroimaging features when distinguishing between stable mild cognitive impairment (sMCI) from progressive MCI (pMCI) to Alzheimer's disease (AD).The combination of neuropsychological tests with neuroimaging features does not lead to an improvement in sMCI versus pMCI classification compared to using neuropsychological tests on their own.BrainAge delta of both neuroimaging and neuropsychological models was correlated with the time to conversion, the time taken for a pMCI subject to convert to AD.
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