The Eye as a Window to Neuroinflammation in Psychiatric Disorders?: A Meta-Analysis of Retinal Structural and Vascular Biomarkers
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Notice bibliographique
Résumé
Introduction: Psychiatric disorders like schizophrenia, bipolar disorder (BD), and major depressive disorder (MDD) represent major global health challenges with complex pathophysiology, potentially involving neuroinflammation. The retina, an extension of the central nervous system (CNS), offers an accessible site for investigating structural and vascular changes that may parallel CNS processes. Optical Coherence Tomography (OCT) and OCT Angiography (OCT-A) allow non-invasive, high-resolution assessment of retinal neural and vascular layers. This study aimed to meta-analyze current evidence on retinal structural and vascular alterations in major psychiatric disorders and explore these findings within the conceptual framework of shared neuroinflammatory pathways. Methods: A systematic literature search was conducted in PubMed, Scopus, and Web of Science databases for studies published between January 1st, 2013, and December 31st, 2024. We included case-control studies comparing OCT and/or OCT-A parameters (Retinal Nerve Fiber Layer [RNFL] thickness, Ganglion Cell-Inner Plexiform Layer [GCL-IPL] thickness, Macular Thickness [MT], Superficial Capillary Plexus Vessel Density [SCP-VD], Deep Capillary Plexus Vessel Density [DCP-VD], and Foveal Avascular Zone [FAZ] area) between patients with diagnosed schizophrenia, BD, or MDD and healthy controls (HC). Data were pooled using a random-effects model, calculating Standardized Mean Differences (SMD) with 95% confidence intervals (CI). Heterogeneity was assessed using I² statistics. The risk of bias was evaluated using the Newcastle-Ottawa Scale (NOS). Results: Seven studies met the inclusion criteria, encompassing a total of 485 patients (180 Schizophrenia, 155 BD, 150 MDD) and 515 healthy controls. Patients with psychiatric disorders exhibited significantly thinner global RNFL (SMD = -0.68; 95% CI [-0.95, -0.41]; p < 0.00001; I²=75%), GCL-IPL (SMD = -0.75; 95% CI [-1.08, -0.42]; p < 0.0001; I²=80%), and reduced macular SCP-VD (SMD = -0.55; 95% CI [-0.88, -0.22]; p = 0.001; I²=72%) compared to HC. DCP-VD also showed a trend towards reduction (SMD = -0.40; 95% CI [-0.85, 0.05]; p = 0.08; I²=79%). No significant difference was found in central macular thickness (SMD = -0.15; 95% CI [-0.45, 0.15]; p = 0.33; I²=60%) or FAZ area (SMD = 0.20; 95% CI [-0.10, 0.50]; p = 0.19; I²=55%). High heterogeneity was observed across most analyses. Study quality varied, with NOS scores ranging from 6 to 8. Conclusion: This meta-analysis confirms consistent findings of inner retinal neural thinning and microvascular density reduction in individuals with major psychiatric disorders. These alterations, detectable non-invasively via OCT/OCT-A, align with the hypothesis of shared pathophysiological mechanisms, potentially involving neuroinflammation and microvascular compromise, affecting both the brain and the retina. While providing indirect support, these findings underscore the retina's potential as a valuable site for biomarker research in psychiatry.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,012 |
| 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 | 0,000 | 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 découle