Background: To develop and assess usability of a smartphone-based visual acuity (VA) test with an automatic distance calibration (ADC) function, the iOS version of WHOeyes. Methods: The WHOeyes was an upgraded version with a distinct feature of ADC of an existing validated VA testing APP called V@home. Three groups of Chinese participants with different ages (≤20, 20-40, >40 years) were recruited for distance and near VA testing using both an Early Treatment Diabetic Retinopathy Study (ETDRS) chart and the WHOeyes. The ADC function would determine the testing distance. Infrared rangefinder was used to determine the testing distance for the ETDRS, and actual testing distance for the WHOeyes. A questionnaire-based interview was administered to assess satisfaction. Results: The actual testing distance determined by the WHOeyes ADC showed an overall good agreement with the desired testing distance in all three age groups (p > 0.50). Regarding the distance and near VA testing, the accuracy of WHOeyes was equivalent to ETDRS. The mean difference between the WHOeyes and ETDRS ranged from -0.084 to 0.012 log^MAR, and the quadratic weighted kappa (QWK) values were greater than 0.75 across all groups. The test-retest reliability of WHOeyes was high for both near and distance VA, with a mean difference ranging from -0.040 to 0.004 log^MAR and QWK all greater than 0.85. The questionnaire revealed an excellent user experience and acceptance of WHOeyes. Conclusion: WHOeyes could provide accurate measurement of the testing distance as well as the distance and near VA when compared to the gold standard ETDRS chart.

Objective: To investigate the correlation between imaging manifestations and laboratory indicators of peripheral blood in patients with diabetic macular edema (DME). Method: One hundred patients with DME were selected to undergo fundus imaging examination, with peripheral blood taken for testing to analyze the correlation between imaging manifestations and laboratory indicators of peripheral blood. Result:Reduced red blood cell count was correlated with ellipsoid band disruption (p=0.040) and capsular cavity formation (p=0.015). Reduced hemoglobin was correlated with intraretinal fluid (p=0.046). Elevated low-density lipoprotein was correlated with capsular cavity formation (p=0.011), outer membrane disruption (p=0.018), and intraretinal fluid (p=0.020), while elevated apolipoprotein B was correlated with hard exudates (p=0.025). Elevated creatinine was correlated with disorganization of inner retinal layer (p=0.009). Diabetic retinopathy severity score was negatively correlated with platelet count (p=0.001, r=-0.314). Hyperreflective foci were positively correlated with neutrophil count (p=0.001, r=0.324).Conclusion: It was found that certain imaging manifestations in patients with DME were correlated with laboratory indicators, which is helpful to elucidate the pathophysiologic mechanisms of diabetic macular edema and guide clinical treatment.

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.

Background: To develop and assess usability of a smartphone-based visual acuity (VA) test with an automatic distance calibration (ADC) function, the iOS version of WHOeyes. Methods: The WHOeyes was an upgraded version with a distinct feature of ADC of an existing validated VA testing APP called V@home. Three groups of Chinese participants with different ages (≤20, 20-40, >40 years) were recruited for distance and near VA testing using both an Early Treatment Diabetic Retinopathy Study (ETDRS) chart and the WHOeyes. The ADC function would determine the testing distance. Infrared rangefinder was used to determine the testing distance for the ETDRS, and actual testing distance for the WHOeyes. A questionnaire-based interview was administered to assess satisfaction. Results: The actual testing distance determined by the WHOeyes ADC showed an overall good agreement with the desired testing distance in all three age groups (p > 0.50). Regarding the distance and near VA testing, the accuracy of WHOeyes was equivalent to ETDRS. The mean difference between the WHOeyes and ETDRS ranged from -0.084 to 0.012 logMAR, and the quadratic weighted kappa (QWK) values were greater than 0.75 across all groups. The test-retest reliability of WHOeyes was high for both near and distance VA, with a mean difference ranging from -0.040 to 0.004 logMAR and QWK all greater than 0.85. The questionnaire revealed an excellent user experience and acceptance of WHOeyes. Conclusions: WHOeyes could provide accurate measurement of the testing distance as well as the distance and near VA when compared to the gold standard ETDRS chart. Keywords: smartphone-based; visual acuity test; WHOeyes, V@home; ETDRS;

Purpose: To identify plasma proteins that are causally related to primary open-angle glaucoma (POAG) for potential therapeutic targeting. Methods: 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, followed by a systematic evaluation of protein druggability. 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). Five proteins (SEL1L, ROBO1, AXL, NID1, GFER) demonstrated strong genetic linkage to POAG. Further, validation analyses identified nine proteins causally related to POAG traits, with five (IL18R1, IL1R1, PLCG1, RNASE1, SPINK6) revealing consistent directional associations. In addition, 18 causal proteins were highlighted for their druggability, 5 of which are either approved drugs or under clinical trial. 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.

Objective: To analyze the influencing factors of refusal of vitrectomy in patients with proliferative diabetic retinopathy (PDR).Methods: A total of 517 patients with PDR who underwent vitrectomy in Xingtai City from January 2021 to August 2022 were selected and divided into two groups according to whether they underwent surgical treatment.The personal and disease characteristics of the patients were collected. Logistic regression was used to analyze the influencing factors of non-vitrectomy.Results: 126 patients (24%) did not undergo vitrectomy. There were statistically significant differences in the proportion of patients received retinal photocoagulation, combined with other serious systemic diseases, and preoperative visual acuity improvement between the two groups (P<0.05).Multivariate analysis showed that no previous retinal photocoagulation treatment(OR=0.414,95% CI0.236-0.724, p=0.002), combined with other serious systemic diseases(OR=11.812,95% CI6.446-21.646, p<0.001), and preoperative visual acuity improvement(OR=21.317,95% CI11.756-38.653, p<0.001) were the influencing factors for patients who did not undergo vitrectomy.Conclusions:Previously not receiving retinal photocoagulation treatment, combined with other serious systemic diseases, and preoperative visual acuity improvement are the influencing factors for patients not undergoing vitrectomy. Early knowledge popularization should be strengthened, targeted communication with patients should be carried out, and patients' confidence in surgery should be established.

Background: Diabetic retinopathy (DR) urgently needs novel and effective therapeutic targets. Integrated analyses of plasma proteomic and genetic markers can clarify the causal relevance of proteins and discover novel targets for diseases, but no systematic screening for DR has been performed.

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. DR data were sourced from the largest FinnGen study, comprising 10,413 DR cases and 308,633 European controls. Genetic instrumental variables were identified using multiple filters. In the two-sample MR analysis, Wald ratio and inverse variance-weighted (IVW) MR were utilized to investigate the

causality of plasma proteins with DR. Bidirectional MR, Bayesian Co-localization, and phenotype scanning were employed to test for potential reverse causality and confounding factors in the main MR analyses. By systemically searching druggable gene lists, the ChEMBL database, DrugBank, and Gene Ontology database, the druggability and relevant functional pathways of the identified proteins were systematically evaluated.

Results: Genetically predicted levels of 24 proteins were significantly associated with DR risk at a false discovery rate <0.05 including 11 with positive associations and 13 with negative associations. For each standard deviation increase in plasm protein levels, the odds ratios (ORs) for DR varied from 0.51 (95% CI: 0.36-0.73; P=2.22×10-5) for tubulin polymerization-promoting protein family member 3 (TPPP3) to 2.02 (95% CI: 1.44-2.83; P=5.01×10-5) for olfactomedin like 3 (OLFML3). Bidirectional MR indicated there was no reverse causality that interfered with the results of the main MR analyses. Four proteins exhibited strong co-localization evidence (PH4 ≥0.8): cytoplasmic tRNA synthetase (WARS), acrosin binding protein(ACRBP), and intercellular adhesion molecule 1 (ICAM1) were negatively associated with DR risk, while neurogenic locus notch homolog protein 2 (NOTCH2) showed a positive association. No confounding factors were detected between pQTLs and DR according to the phenotypic scan. Drugability assessments highlighted 6 proteins already in drug development endeavor and 18 novel drug targets, with metalloproteinase inhibitor 3 (TIMP) currently in phase I clinical trials for DR. GO analysis identified 18 of 24 plasma proteins enriching 22 pathways related to cell differentiation and proliferation regulation.

Conclusions:Twenty-four promising drug targets for DR were identified, including four plasma proteins with particular co-localization evidence. These findings offer new insights into DR's etiology and therapeutic targeting, exemplifying the value of genomic and proteomic data in drug target discovery.

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Aims: To identify plasma proteins with causal links to diabetic retinopathy (DR) for potential therapeutic targets. Materials and methods: Summary statistics of plasma protein quantitative trait loci (pQTL) were derived from two extensive GWAS datasets and one systematic review, with over 100 thousand participants covering thousands of plasma proteins. DR data were sourced from the largest FinnGen study, comprising 10,413 DR cases and 30,863 European controls. Two-sample MR approach was utilized to investigate the causality of plasma proteins with DR, followed by bidirectional MR, Bayesian Co-localization analysis, and phenotype scanning to ensure robustness of the MR results. Druggability of the identified proteins were systematically evaluated. Results: Genetically predicted levels of 24 proteins were significantly associated with DR risk after multiple testing correction. For each standard deviation increase in plasm protein levels, the odds ratio (OR) for DR varied from 0.51 (95% CI: 0.36-0.73; P=2.22×10-5) for Tubulin Polymerization-Promoting Protein Family Member 3 (TPPP3) to 2.02 (95% CI: 1.44-2.83; P=5.01×10-5) for Olfactomedin like 3 (OLFML3). Four proteins exhibited strong co-localization evidence (PH4 ≥0.8): WARS, ACRBP, and ICAM1 were negatively associated with DR risk, while NOTCH2 showed a positive association. Drugability assessments highlighted these 24 proteins as potential DR targets, with two of them currently in phase I clinical trials. Conclusions: Twenty-four promising drug targets for DR were identified, including four plasma proteins with particularly promise. These findings offer new insights into DR's etiology and therapeutic targeting, exemplifying the value of genomic and proteomic data in drug target discovery.