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A deep‐learning retinal aging biomarker for cognitive decline and incident dementia
Ming Ann Sim, Yih Chung Tham, Simon Nusinovici, Ten Cheer Quek, Marco Yu, Can Can Xue, Miao Li Chee, Qing Peng et al.. Alzheimer s & Dementia, 2025-03-01
Topic: Risk, prevention and care in population studies
Of 510 memory-clinic subjects(N = 155 cognitive decline), RetiPhenoAge associated with incident cognitive decline (subdistribution hazard ratio [SHR] 1.34, 95% confidence interval [CI] 1.10-1.64, p = 0.004), and incident dementia (SHR 1.43, 95% CI 1.02-2.01, p = 0.036). In the UK Biobank (N = 33 495), RetiPhenoAge similarly predicted incident dementia (SHR 1.25, 95% CI 1.09-1.41, p = 0.008). RetiPhenoAge significantly associated with CSVD, brain atrophy, and plasma proteomic signatures related to aging. RetiPhenoAge may provide a non-invasive prognostic screening tool for cognitive decline and dementia. HIGHLIGHTS: RetiPhenoAge, a retinal aging marker, was studied in an Asian memory clinic cohort. Older RetiPhenoAge predicted future cognitive decline and incident dementia. It also linked to neuropathological markers, and plasma proteomic profiles of aging. UK Biobank replication found that RetiPhenoAge predicted 12-year incident dementia. Future studies should validate RetiPhenoAge as a prognostic biomarker for dementia.
Key findings
- Of 510 memory-clinic subjects(N = 155 cognitive decline), RetiPhenoAge associated with incident cognitive decline (subdistribution hazard ratio [SHR] 1.34, 95% confidence interval [CI] 1.10-1.64, p = 0.004), and incident dementia (SHR 1.43, 95% CI 1.02-2.01, p = 0.036).
- In the UK Biobank (N = 33 495), RetiPhenoAge similarly predicted incident dementia (SHR 1.25, 95% CI 1.09-1.41, p = 0.008).
- RetiPhenoAge significantly associated with CSVD, brain atrophy, and plasma proteomic signatures related to aging.
- RetiPhenoAge may provide a non-invasive prognostic screening tool for cognitive decline and dementia.
- HIGHLIGHTS: RetiPhenoAge, a retinal aging marker, was studied in an Asian memory clinic cohort.
Why it matters
This study found that a deep-learning retinal aging biomarker, RetiPhenoAge, was associated with incident cognitive decline and dementia in a memory-clinic cohort and predicted incident dementia in the UK Biobank. It may provide a non-invasive prognostic screening tool, but future studies should validate it as a prognostic biomarker for dementia.
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Study details
- Participants155
- Effect sizeHR 1.43; HR 1.25
- Evidence strengthModerate
How this study scored 56/100
Published in a peer-reviewed journal. Scored zero for study design and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Alzheimer s & Dementia) |
| Journal's citation record | 2 / 4 | Alzheimer s & Dementia: journal h-index 228 (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 | 3 / 5 | Rated “moderate” 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 | 2 / 4 | 155 participants |
| Effect reported | 3 / 3 | Effect reported with a statistic (interval, p-value, ratio or similar) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 3 / 7 | Cited 23 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 7.7 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 4 / 6 | Cited 14.6× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 2 / 4 | Cited 23 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Christopher Chen: h-index 90 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | National University of Singapore: institution h-index 1,166 (OpenAlex) |
| Multi-centre collaboration | 3 / 3 | OpenAlex lists 10 institution(s) in 3 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 40042460) |
| Free to read | 2 / 2 | Free to read |
| Total | 56 / 100 | — |
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Read the original
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
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
Sim, M. A., Tham, Y. C., Nusinovici, S., Quek, T. C., Yu, M., Xue, C. C., et al. (2025). A deep‐learning retinal aging biomarker for cognitive decline and incident dementia. Alzheimer s & Dementia. https://doi.org/10.1002/alz.14601
Vancouver
Sim MA, Tham YC, Nusinovici S, Quek TC, Yu M, Xue CC, et al. A deep‐learning retinal aging biomarker for cognitive decline and incident dementia. Alzheimer s & Dementia. 2025. doi:10.1002/alz.14601. PMID: 40042460.
BibTeX
@article{sim2025-40042460,
author = {Sim, Ming Ann and Tham, Yih Chung and Nusinovici, Simon and Quek, Ten Cheer and Yu, Marco and Xue, Can Can and Chee, Miao Li and Peng, Qing and others},
title = {{A deep‐learning retinal aging biomarker for cognitive decline and incident dementia}},
journal = {Alzheimer s \& Dementia},
year = {2025},
doi = {10.1002/alz.14601},
pmid = {40042460},
url = {https://doi.org/10.1002/alz.14601}
}
Studies this one cites
Referenced by this study and also in the alzhub library, so you can read them here.