Editorial: Retinal biomarkers of neurodegenerative diseases
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».