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Association between BrainAGE and Alzheimer's disease biomarkers
Abughofah Y, Deardorff R, Vosmeier A, Hottle S, Dage JL, Dempsey D, Apostolova LG, Brosch J et al.. Alzheimer's & dementia (Amsterdam, Netherlands), 2025-01-01
Topic: Amyloid, tau and blood-test diagnosis
Introduction The 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. Methods One 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). Results Significant 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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APA 7th
Abughofah, Y., Deardorff, R., Vosmeier, A., Hottle, S., Dage, J. L., Dempsey, D., et al. (2025). Association between BrainAGE and Alzheimer's disease biomarkers. Alzheimer's & dementia (Amsterdam, Netherlands). https://doi.org/10.1002/dad2.70094
Vancouver
Abughofah Y, Deardorff R, Vosmeier A, Hottle S, Dage JL, Dempsey D, et al. Association between BrainAGE and Alzheimer's disease biomarkers. Alzheimer's & dementia (Amsterdam, Netherlands). 2025. doi:10.1002/dad2.70094. PMID: 40018325.
BibTeX
@article{abughofah2025-40018325,
author = {Abughofah, Y. and Deardorff, R. and Vosmeier, A. and Hottle, S. and Dage, J. L. and Dempsey, D. and Apostolova, L. G. and Brosch, J. and others},
title = {{Association between BrainAGE and Alzheimer's disease biomarkers}},
journal = {Alzheimer's \& dementia (Amsterdam, Netherlands)},
year = {2025},
doi = {10.1002/dad2.70094},
pmid = {40018325},
url = {https://doi.org/10.1002/dad2.70094}
}
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Key findings
- Results Significant 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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Study details
- Evidence strengthLow
How this study scored 48/100
Published in a leading specialty journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 28 of the 58 points we could judge it on, which is 48 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 9 / 10 | Tier 2 — leading specialty journal (Alzheimer's & dementia (Amsterdam, Netherlands)) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 40018325) |
| Free to read | 2 / 2 | Free to read |
| Points | 28 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 28 of the 58 points we could judge it on is 48 out of 100. |
| Total | 48 / 100 | — |
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