Editorial: Retinal biomarkers of neurodegenerative diseases
Bibliographic record
Abstract
As the most prevalent type of dementia, Alzheimer's Disease (AD) continues to be a focus for retinal biomarker research. AD currently affects 1 in 6 of those aged 80 or above and its impact will likely grow with the ageing global population. Diagnosis of AD is based on cognitive functional deficit, although the molecular and structural signatures precede it by decades. Common scepticism about the value of an early biomarker of AD has been the lack of effective treatment. However, with the recent advances in amyloid beta (Ab)-targeting drugs, early diagnosis is more important than ever, in addition to the improved quality of care and support for the patients and caregivers. Marquie et al. examined the association between retinal vessel density from optical coherence tomography angiogram (OCTA) and cerebral spinal fluid (CSF) Ab and phosphorylated tau measure in the NORFACE cohort in Spain and found that the retinal vessel density parameters were not statistically significantly associated with the AT(N) groups of Normal, Alzheimer, and Suspected Alzheimer pathology or the CSF measures. This thorough study of a large cohort highlights among others the importance of publishing null results, the importance of nuance in the type and specification of retinal biomarkers that are clinically useful, and the challenge of considering a peripheral marker in reference to another marker that is more established and considered to be closer to the central pathophysiology. In contrast, Chen et al. performed a meta-analysis of 9 studies on the association between retinal layer thickness and hippocampal volume in normal control (NC), mild cognitive impairment (MCI), and AD, and found that there was a significant positive correlation between retinal nerve fibre layer thickness and hippocampal volume throughout all groups and that the correlation was much higher in the NC group than the AD group. The result suggests that there are both normative and pathological relationships between the retinal and hippocampal morphometrics, and while encouraging, poses the question of handling inter-individual variability and specificity of retinal layer thickness as a proxy marker of pathological hippocampal thinning.Wijesinghe et al. conducted a novel, ambitious study that delves into both the disease mechanism and potential treatment of AD by investigating the neuroprotective effect of ergothioneine (Ergo), a naturally occurring dietary antioxidant, on Ab clearance in an AD mouse model (5XFAD). The study found that the Ergo-treated mice had significantly lower Ab immunoreactivity, a lower number of visible Ab deposits, and an increased number of IBA1+ blood-derived phagocytic macrophages. Disrupted Ab clearance is a central process in AD pathophysiology and treatment targets, and understanding the role and dysfunction of glial cells in Ab clearance in AD is crucial. The study also is a great example of using the retina in research for developing novel drugs for neurodegenerative diseases.In a different topic, Berneshawi et al. examined a set of oculomotor measurements (oculometrics) in asymptomatic systemic lupus erythematosus (SLE) patients undergoing long-term hydroxychloroquine treatment which carries a risk of retinal toxicity. Interestingly, the SLE patients without any symptoms showed a significant reduction in multiple oculomotor functions in comparison to age-matched healthy controls. This potentially has important clinical implications as hydroxychloroquine retinopathy is asymptomatic in the early stage, and the resulting cellular damage is irreversible and may continue for some time even after the treatment is ceased, making early detection paramount. Furthermore, several of the oculometrics were linearly correlated with retinal thickness in the patients. Structure-function relationship is a major research topic in ophthalmology and visual science, and such a multi-modal / multi-domain approach will contribute to gaining novel insights into disease mechanisms as well as more sensitive and accurate diagnoses using a complementary and comprehensive set of metrics.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".