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Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study
Millar PR, Gordon BA, Luckett PH, Benzinger TLS, Cruchaga C, Fagan AM, Hassenstab JJ, Perrin RJ et al.. eLife, 2023-01-06
Topic: Amyloid, tau and blood-test diagnosis
Background Estimates of 'brain-predicted age' quantify apparent brain age compared to normative trajectories of neuroimaging features. The brain age gap (BAG) between predicted and chronological age is elevated in symptomatic Alzheimer disease (AD) but has not been well explored in presymptomatic AD. Prior studies have typically modeled BAG with structural MRI, but more recently other modalities, including functional connectivity (FC) and multimodal MRI, have been explored. Methods We trained three models to predict age from FC, structural (S), or multimodal MRI (S+FC) in 390 amyloid-negative cognitively normal (CN/A-) participants (18-89 years old). In independent samples of 144 CN/A-, 154 CN/A+, and 154 cognitively impaired (CI; CDR > 0) participants, we tested relationships between BAG and AD biomarkers of amyloid and tau, as well as a global cognitive composite. Results All models predicted age in the control training set, with the multimodal model outperforming the unimodal models. All three BAG estimates were significantly elevated in CI compared to controls. FC-BAG was significantly reduced in CN/A+ participants compared to CN/A-. In CI participants only, elevated S-BAG and S+FC BAG were associated with more advanced AD pathology and lower cognitive performance. Conclusions Both FC-BAG and S-BAG are elevated in CI participants. However, FC and structural MRI also capture complementary signals. Specifically, FC-BAG may capture a unique biphasic response to presymptomatic AD pathology, while S-BAG may capture pathological progression and cognitive decline in the symptomatic stage. A multimodal age-prediction model improves sensitivity to healthy age differences. Funding This work was supported by the National Institutes of Health (P01-AG026276, P01- AG03991, P30-AG066444, 5-R01-AG052550, 5-R01-AG057680, 1-R01-AG067505, 1S10RR022984-01A1, and U19-AG032438), the BrightFocus Foundation (A2022014F), and the Alzheimer's Association (SG-20-690363-DIAN).
Key findings
- Background Estimates of 'brain-predicted age' quantify apparent brain age compared to normative trajectories of neuroimaging features.
- Results All models predicted age in the control training set, with the multimodal model outperforming the unimodal models.
- All three BAG estimates were significantly elevated in CI compared to controls.
- FC-BAG was significantly reduced in CN/A+ participants compared to CN/A-.
- In CI participants only, elevated S-BAG and S+FC BAG were associated with more advanced AD pathology and lower cognitive performance.
Why it matters
Brain age gap estimates were elevated in cognitively impaired participants, and in those participants elevated structural and multimodal estimates were associated with more advanced Alzheimer disease pathology and lower cognitive performance. This is a cross-sectional observational study of brain age estimates, not a treatment, cure or prevention for Alzheimer's disease.
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Study details
- Evidence strengthLow
How this study scored 53/100
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.
| Component | Points | Why |
|---|---|---|
| Journal tier | 9 / 10 | Tier 2 — leading specialty journal (eLife) |
| Journal's citation record | 3 / 4 | ELife: journal h-index 311 (OpenAlex, 2026-10-29) |
| 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 | 3 / 5 | 2023 — within 6 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 | 4 / 7 | Cited 71 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 14.2 citations a year over 5 year(s) since 2023 |
| Impact for its field and year | 4 / 6 | Cited 12.8× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 2 / 6 | Cited by 3 other studies in this library |
| Still being cited | 3 / 4 | Cited 59 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Beau M. Ances: h-index 81 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | Washington University in St. Louis: institution h-index 1,962 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 9 institution(s) in 4 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 36607335) |
| Free to read | 2 / 2 | Free to read |
| Total | 53 / 100 | — |
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Read the original
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Millar, P. R., Gordon, B. A., Luckett, P. H., Benzinger, T. L. S., Cruchaga, C., Fagan, A. M., et al. (2023). Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study. eLife. https://doi.org/10.7554/elife.81869
Vancouver
Millar PR, Gordon BA, Luckett PH, Benzinger TLS, Cruchaga C, Fagan AM, et al. Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study. eLife. 2023. doi:10.7554/elife.81869. PMID: 36607335.
BibTeX
@article{millar2023-36607335,
author = {Millar, P. R. and Gordon, B. A. and Luckett, P. H. and Benzinger, T. L. S. and Cruchaga, C. and Fagan, A. M. and Hassenstab, J. J. and Perrin, R. J. and others},
title = {{Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study}},
journal = {eLife},
year = {2023},
doi = {10.7554/elife.81869},
pmid = {36607335},
url = {https://doi.org/10.7554/elife.81869}
}
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