Biomarkers for Alzheimer's disease are upregulated in patients with diabetic retinopathy
Bibliographic record
Abstract
Background Diabetes has been linked to increased prevalence of dementia, but the link between diabetic retinopathy (DR) and Alzheimer's disease (AD) remains unclear. Objective This study aimed to evaluate potential associations between DR and AD-related protein biomarkers in plasma and ocular fluid. Methods A prospective, cross-sectional study collected human blood, vitreous, aqueous, and tear samples and measured amyloid-β (Aβ 40 , Aβ 42 ), total-tau (t-tau), phosphorylated-tau (ptau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) by digital immunoassays. Results The study included 79 eyes (79 patients) [41 females (59.4%); mean (SD) age 57.1 (12.2) years] of which DR was present in 44 (55.7%). All six biomarkers were significantly higher in plasma in participants with DR compared to those without DR [Aβ 40 p = 0.002, Aβ 42 p = 0.002, t-tau = 0.013, ptau181 p = 0.005, GFAP p = 0.010, and NfL p < 0.001]. Within vitreous, DR participants had significantly elevated t-tau (p = 0.002), ptau181 (p = 0.049), and NfL (p = 0.006); and within aqueous, higher NfL (p = < 0.001). Neuropsychological testing scores were lower in participants with DR than those without but did not reach statistical significance (Montreal-Cognitive-Assessment: p = 0.070; Mini-Mental-State-Exam: p = 0.057). Conclusions This study showed significant increases of AD associated protein biomarkers in plasma, vitreous, and aqueous in patients with DR. These results support a potential biological link between DR and AD pathology and suggest that DR, which tends to occur in younger individuals, may be a predictive factor for AD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".