Purpose: To identify plasma proteins that are causally related to primary open-angle glaucoma (POAG) for potential therapeutic targeting. Methods: Summary statistics of plasma protein quantitative trait loci (pQTL) were derived from two extensive genome-wide analysis study (GWAS) datasets and one systematic review, with over 100 thousand participants covering thousands of plasma proteins. POAG data were sourced from the largest FinnGen study, comprising 8,530 DR cases and 391,275 European controls. A two-sample MR analysis, supplemented by bidirectional MR, Bayesian co-localization analysis, and phenotype scanning, was conducted to examine the causal relationships between plasma proteins and POAG. The analysis was validated by identifying associations between plasma proteins and POAG-related traits, including intraocular pressure (IOP), retinal nerve fibre layer (RNFL), and ganglion cell and inner plexiform layer (GCIPL). By searching druggable gene lists, the ChEMBL database, and the ClinicalTrials.gov database, the druggability and clinical development activity of the identified proteins were systematically evaluated. Results: Eighteen proteins were identified with significant associations with POAG risk after multiple comparison adjustments. The ORs per standard deviation increase in protein levels ranged from 0.39 (95% CI: 0.24–0.62; P = 7.70×10-5) for phospholipase C gamma 1 (PLCG1) to 1.29 (95% CI: 1.16–1.44; P = 6.72×10-6) for nidogen-1 (NID1). Bidirectional MR indicated that reverse causality did not interfere with the results of the main MR analyses. Five proteins exhibited strong co-localization evidence (PH4 ≥ 0.8): protein sel-1 homolog 1 (SEL1L), tyrosine-protein kinase receptor UFO (AXL), nidogen-1 (NID1) and FAD-linked sulfhydryl oxidase ALR (GFER) were negatively associated with POAG risk, while roundabout homolog 1 (ROBO1) showed a positive association. The phenotype scanning did not reveal any confounding factors between pQTLs and POAG. Further, validation analyses identified nine proteins causally related to POAG traits, with five proteins including interleukin-18 receptor 1 (IL18R1), interleukin-1 receptor type 1 (IL1R1), phospholipase C gamma 1 (PLCG1), ribonuclease pancreatic (RNASE1), serine protease inhibitor Kazal-type 6 (SPINK6) revealing consistent directional associations. In addition, 18 causal proteins were highlighted for their druggability, of which 5 proteins are either already approved drugs or in clinical trials and 13 proteins are novel drug targets. Conclusions: This study identifies 18 plasma proteins as potential therapeutic targets for POAG, particularly emphasizing the role of genomic and proteomic integration in drug discovery. Future experimental and clinical studies should be conducted to validate the efficacy of these proteins and to conduct more comprehensive proteomic explorations, thus taking a significant leap toward innovative POAG treatments.

Purpose: To identify plasma proteins that are causally related to primary open-angle glaucoma (POAG) for potential therapeutic targeting. Methods: Summary statistics of plasma protein quantitative trait loci (pQTL) were derived from two extensive genome-wide analysis study (GWAS) datasets and one systematic review, with over 100 thousand participants covering thousands of plasma proteins. POAG data were sourced from the largest FinnGen study, comprising 8,530 DR cases and 391,275 European controls. A two-sample MR analysis, supplemented by bidirectional MR, Bayesian co-localization analysis, and phenotype scanning, was conducted to examine the causal relationships between plasma proteins and POAG. The analysis was validated by identifying associations between plasma proteins and POAG-related traits, including intraocular pressure (IOP), retinal nerve fibre layer (RNFL), and ganglion cell and inner plexiform layer (GCIPL). By searching druggable gene lists, the ChEMBL database, and the ClinicalTrials.gov database, the druggability and clinical development activity of the identified proteins were systematically evaluated. Results: Eighteen proteins were identified with significant associations with POAG risk after multiple comparison adjustments. The ORs per standard deviation increase in protein levels ranged from 0.39 (95% CI: 0.24–0.62; P = 7.70×10-5) for phospholipase C gamma 1 (PLCG1) to 1.29 (95% CI: 1.16–1.44; P = 6.72×10-6) for nidogen-1 (NID1). Bidirectional MR indicated that reverse causality did not interfere with the results of the main MR analyses. Five proteins exhibited strong co-localization evidence (PH4 ≥ 0.8): protein sel-1 homolog 1 (SEL1L), tyrosine-protein kinase receptor UFO (AXL), nidogen-1 (NID1) and FAD-linked sulfhydryl oxidase ALR (GFER) were negatively associated with POAG risk, while roundabout homolog 1 (ROBO1) showed a positive association. The phenotype scanning did not reveal any confounding factors between pQTLs and POAG. Further, validation analyses identified nine proteins causally related to POAG traits, with five proteins including interleukin-18 receptor 1 (IL18R1), interleukin-1 receptor type 1 (IL1R1), phospholipase C gamma 1 (PLCG1), ribonuclease pancreatic (RNASE1), serine protease inhibitor Kazal-type 6 (SPINK6) revealing consistent directional associations. In addition, 18 causal proteins were highlighted for their druggability, of which 5 proteins are either already approved drugs or in clinical trials and 13 proteins are novel drug targets. Conclusions: This study identifies 18 plasma proteins as potential therapeutic targets for POAG, particularly emphasizing the role of genomic and proteomic integration in drug discovery. Future experimental and clinical studies should be conducted to validate the efficacy of these proteins and to conduct more comprehensive proteomic explorations, thus taking a significant leap toward innovative POAG treatments.

Aims: Divided nevus of the eyelid is a congenital pigmented nevus that impacts eyelid function and aesthetics. While surgical excision and laser ablation are current treatment options, they have limitations when dealing with large lesions. This study aims to investigate the efficacy and safety of carbon dioxide (CO₂) laser excision treatment for divided nevus of the eyelid. Methods: This retrospective study included 10 patients (5 males, 5 females) with a mean age of 23.7 years (9-54 years). All underwent CO₂ laser excision and were followed up for 12 months. Treatment outcomes were assessed through clearance and recurrence rates, evaluated using digital photography. Postoperative complications were closely monitored throughout the 12-month follow-up period. Patient satisfaction was assessed using a comprehensive questionnaire. Results:All patients presented with unilateral divided nevus of the eyelid, with lesion diameters ranging from 25 to 50 mm and heights ranging from 0.3 to 6 mm (mean: 3.93 mm). Patients received between 1 and 5 laser treatment sessions. At the 12-month follow-up, a 100% clearance rate was achieved, with no recurrence observed in any patient. All patients maintained a continuous eyelid margin with acceptable irregularity. Complications were minimal, with partial eyelash loss in 8 patients, hyperpigmentation in 2 patients, and mild upper eyelid trichiasis in 1 patient. No severe complications, such as ectropion, eyelid margin notching, corneal erosion, or significant scar hypertrophy, were reported. All patients expressed being "very satisfied" with the functional and cosmetic outcomes in a questionnaire. Conclusions: CO₂ laser excision offers a simple, precise, and effective treatment approach for divided nevus of the eyelid. This innovative technique simplifies the treatment process, achieves excellent cosmetic outcomes, and eliminates the need for skin grafting, making it a promising option for the management of large divided nevus.

Aims: Divided nevus of the eyelid is a congenital pigmented nevus that impacts eyelid function and aesthetics. While surgical excision and laser ablation are current treatment options, they have limitations when dealing with large lesions. This study aims to investigate the efficacy and safety of carbon dioxide (CO₂) laser excision treatment for divided nevus of the eyelid. Methods: This retrospective study included 10 patients (5 males, 5 females) with a mean age of 23.7 years (9-54 years). All underwent CO₂ laser excision and were followed up for 12 months. Treatment outcomes were assessed through clearance and recurrence rates, evaluated using digital photography. Postoperative complications were closely monitored throughout the 12-month follow-up period. Patient satisfaction was assessed using a comprehensive questionnaire. Results: All patients presented with unilateral divided nevus of the eyelid, with lesion diameters ranging from 25 to 50 mm and heights ranging from 0.3 to 6 mm (mean: 3.93 mm). Patients received between 1 and 5 laser treatment sessions. At the 12-month follow-up, a 100% clearance rate was achieved, with no recurrence observed in any patient. All patients maintained a continuous eyelid margin with acceptable irregularity. Complications were minimal, with partial eyelash loss in 8 patients, hyperpigmentation in 2 patients, and mild upper eyelid trichiasis in 1 patient. No severe complications, such as ectropion, eyelid margin notching, corneal erosion, or significant scar hypertrophy, were reported. All patients expressed being "very satisfied" with the functional and cosmetic outcomes in a questionnaire. Conclusions: CO₂ laser excision offers a simple, precise, and effective treatment approach for divided nevus of the eyelid. This innovative technique simplifies the treatment process, achieves excellent cosmetic outcomes, and eliminates the need for skin grafting, making it a promising option for the management of large divided nevus.

Meibomian gland dysfunction (MGD) manifests through two main clinical presentations, characterized by the meibomian gland (MG) ductal obstruction or acinar dropout. While previous research has predominantly associated MGD pathogenesis with hyperkeratinization-related MG ductal obstruction and subsequent acinar atrophy, recent cases have shown significant functional acinar loss in the absence of apparent ductal keratinization or blockage. The deterioration of either MG obstruction or dropout exacerbates the condition of the other, suggesting an independent yet interconnected relationship that perpetuates the vicious cycle of MGD. Understanding the distinct pathological features of MG obstruction and dropout is crucial for delineating their etiology and identifying targeted therapeutic strategies. This review explores the nuanced interrelations of MG obstruction and dropout, elucidating potential pathological mechanisms to establish a foundation for early MGD diagnosis and intervention.

Meibomian gland dysfunction (MGD) manifests through two main clinical presentations, characterized by the meibomian gland (MG) ductal obstruction or acinar dropout. While previous research has predominantly associated MGD pathogenesis with hyperkeratinization-related MG ductal obstruction and subsequent acinar atrophy, recent cases have shown significant functional acinar loss in the absence of apparent ductal keratinization or blockage. The deterioration of either MG obstruction or dropout exacerbates the condition of the other, suggesting an independent yet interconnected relationship that perpetuates the vicious cycle of MGD. Understanding the distinct pathological features of MG obstruction and dropout is crucial for delineating their etiology and identifying targeted therapeutic strategies. This review explores the nuanced interrelations of MG obstruction and dropout, elucidating potential pathological mechanisms to establish a foundation for early MGD diagnosis and intervention.

Purpose: Artificial intelligence (AI) significantly enhances the screening and diagnostic processes for retinopathy of prematurity (ROP). In this article,we focused on the application and performance of AI in detecting ROP and distinguishing plus disease (PLUS) in ROP. Methods: We searched PubMed, Embase, Medline, Web of Science, and Ovid for studies published from January 2018 to July 2024. Studies evaluating the diagnostic performance of AI with expert ophthalmologists’judgment as a reference standard were included. The risk of bias was assessed using the QUADAS-2 tool and QUADAS-AI tool.Statistical analysis included data pooling, forest plot construction, heterogeneity testing, and meta-regression. Results: Fourteen of the 186 studies were included.The pooled sensitivity, specificity and the area under the curve (AUC) of the AI diagnosing ROP were 0.95 (95% CI 0.93-0.96), 0.97 (95% CI 0.94-0.98) and 0.97 (95% CI 0.95-0.98), respectively.The pooled sensitivity, specificity and the AUC of the AI distinguishing PLUS were 0.92 (95% CI 0.80-0.97),0.95 (95% CI 0.91-0.97) and 0.98 (95% CI 0.96-0.99), respectively.Cochran’s Q test (P < 0.01) andHiggins I ² heterogeneity index revealed considerable heterogeneity. The country of study, number of centers, data source and the number of doctors were responsible for the heterogeneity. For ROP diagnosing, researches conducted in China using private data in single center with less than 3 doctors showed higher sensitivity and specificity. For PLUS distinguishing, researches in multiple centers with less than 3 doctors showed higher sensitivity. Conclusions: This study revealed the powerful role of AI in diagnosing ROP and distinguishing PLUS. However, significant heterogeneity was noted among all included studies, indicating challenges in the application of AI for ROP diagnosis in real-world settings. More studies are needed to address these disparities, aiming to fully harness AI’s potential in augmenting medical care for ROP.

Purpose: Artificial intelligence (AI) significantly enhances the screening and diagnostic processes for retinopathy of prematurity (ROP). In this article,we focused on the application and performance of AI in detecting ROP and distinguishing plus disease (PLUS) in ROP. Methods: We searched PubMed, Embase, Medline, Web of Science, and Ovid for studies published from January 2018 to July 2024. Studies evaluating the diagnostic performance of AI with expert ophthalmologists’judgment as a reference standard were included. The risk of bias was assessed using the QUADAS-2 tool and QUADAS-AI tool.Statistical analysis included data pooling, forest plot construction, heterogeneity testing, and meta-regression. Results: Fourteen of the 186 studieswere included.The pooled sensitivity, specificity and the area under the curve (AUC) of the AI diagnosing ROP were 0.95 (95% CI 0.93-0.96), 0.97 (95% CI 0.94-0.98) and 0.97 (95% CI 0.95-0.98), respectively.The pooled sensitivity, specificity and the AUC of the AI distinguishing PLUS were 0.92 (95% CI 0.80-0.97),0.95 (95% CI 0.91-0.97) and 0.98 (95% CI 0.96-0.99), respectively.Cochran’s Q test (P < 0.01) andHiggins I ² heterogeneity index revealed considerable heterogeneity. The country of study, number of centers, data source and the number of doctors were responsible for the heterogeneity. For ROP diagnosing, researches conducted in China using private data in single center with less than 3 doctors showed higher sensitivity and specificity. For PLUS distinguishing, researches in multiple centers with less than 3 doctors showed higher sensitivity. Conclusions: This study revealed the powerful role of AI in diagnosing ROP and distinguishing PLUS. However, significant heterogeneity was noted among all included studies, indicating challenges in the application of AI for ROP diagnosis in real-world settings. More studies are needed to address these disparities, aiming to fully harness AI’s potential in augmenting medical care for ROP.