Current epidemiology of diabetic retinopathy and diabetic macular edema

A novel hyperparameter search approach for accuracy and simplicity in disease prediction risk scoring

OBJECTIVE

Develop a novel technique to identify an optimal number of regression units corresponding to a single risk point, while creating risk scoring systems from logistic regression-based disease predictive models. The optimal value of this hyperparameter balances simplicity and accuracy, yielding risk scores of small scale and high accuracy for patient risk stratification.

MATERIALS AND METHODS

The proposed technique applies an adapted line search across all potential hyperparameter values. Additionally, DeLong test is integrated to ensure the selected value produces an accuracy insignificantly different from the best achievable risk score accuracy. We assessed the approach through two case studies predicting diabetic retinopathy (DR) within six months and hip fracture readmissions (HFR) within 30 days, involving cohorts of 90 400 diabetic patients and 18 065 hip fracture patients.

RESULTS

Our scores achieve accuracies insignificantly different from those obtained by existing approaches, reaching AUROCs of 0.803 and 0.645 for DR and HFR predictions, respectively. Regarding the scale, our scores ranged 0-53 for DR and 0-15 for HFR, while scores produced by existing methods frequently spanned hundreds or thousands.

DISCUSSION

According to the assessment, our risk scores offer simple and accurate predictions for diseases. Furthermore, our new DR score provides a competitive alternative to state-of-the-art risk scores for DR, while our HFR case study presents the first risk score for this condition.

CONCLUSION

Our technique offers a generalizable framework for crafting precise risk scores of compact scales, addressing the demand for user-friendly and effective risk stratification tool in healthcare.

Development and external validation of a predictive model for type 2 diabetic retinopathy

Diabetes retinopathy (DR) is a critical clinical disease with that causes irreversible visual damage in adults, and may even lead to permanent blindness in serious cases. Early identification and treatment of DR is critical. Our aim was to train and externally validate a prediction nomogram for early prediction of DR. 2381 patients with type 2 diabetes mellitus (T2DM) were retrospective study from the First Affiliated Hospital of Xinjiang Medical University in Xinjiang, China, hospitalised between Jan 1, 2019 and Jun 30, 2022. 962 patients with T2DM from the Suzhou BenQ Hospital in Jiangsu, China hospitalised between Jul 1, 2020 to Jun 30, 2022 were considered for external validation. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression was performed to identify independent predictors and establish a nomogram to predict the occurrence of DR. The performance of the nomogram was evaluated using a receiver operating characteristic curve (ROC), a calibration curve, and decision curve analysis (DCA). Neutrophil, 25-hydroxyvitamin D3 [25(OH)D3], Duration of T2DM, hemoglobin A1c (HbA1c), and Apolipoprotein A1 (ApoA1) were used to establish a nomogram model for predicting the risk of DR. In the development and external validation groups, the areas under the curve of the nomogram constructed from the above five factors were 0.834 (95%CI 0.820-0.849) and 0.851 (95%CI 0.829-0.874), respectively. The nomogram demonstrated excellent performance in the calibration curve and DCA. This research has developed and externally verified that the nomograph model shows a good predictive ability in assessing DR risk in people with type 2 diabetes. The application of this model will help clinicians to intervene early, thus effectively reducing the incidence rate and mortality of DR in the future, and has far-reaching significance in improving the long-term health prognosis of diabetes patients.

Risk factors affecting the utilization of eye care services evaluated by the CDC's behavior risk factor surveillance system from 2018 to 2021

When thinking about major health concerns in the U.S. and around the world, eye care ranks lower compared to cardiovascular disease, cancer, and diabetes. However, people do not think about the direct connection between diabetes and eye health. Untreated diabetes can lead to visual impairments such as blindness or difficulty seeing. Studies have found that eye health associated with nutrition, occupational exposure, diabetes, high blood pressure, and heart disease are some of the known risk factors. This study aimed to identify the potential risk factors that are associated with visual impairment (VI). The data used for this analysis were obtained from the Centers for Disease Control and Prevention (CDC) - Behavioral Risk Factor Surveillance System (BRFSS) from 2018 to 2021. We found important characteristics, such as the U.S. region, general health perception, employment status, income status, age, and health insurance source, that are associated with VI. Our study confirmed that the common demographical factors including age, race/ethnicity, the U.S. region, and gender are associated with VI. The study also highlights associations with additional risk factors such as health insurance source, general health perceptions, employment status, and income status. Using this information, we can reach out to communities with large numbers of individuals experiencing vision challenges and help educate them on prevention and treatment protocols, thereby effectively addressing VI and blindness challenges within our communities, neighborhoods, and finally, the broader society.

Timing of Switching to Steroid Implants in Cases of Recalcitrant Diabetic Macular Edema Not Responding to Anti-vascular Endothelial Growth Factor (VEGF) Therapy: A Real-World Study

Purpose The purpose of this study is to examine the impact of the timing of the steroid switch on both visual and anatomical outcomes in diabetic macular edema (DME) eyes that have shown an inadequate response to multiple intravitreal anti-vascular endothelial growth factor (anti-VEGF) injections. In the treatment of DME, anti-VEGF injections are typically the initial course of action. However, in cases where DME persists despite anti-VEGF treatment, intravitreal dexamethasone implants (Ozurdex®, Allergan Inc., Irvine, CA) are often utilized. Despite this, there remains a lack of consensus regarding the optimal timing for transitioning to steroid treatment. This study aims to shed light on the potential benefits of adjusting the timing of the steroid switch in cases of recalcitrant DME.  Methods The eyes (n = 105) of 77 patients with recalcitrant DME were included in this retrospective, interventional, comparative study comprising three groups: participants switched to steroid implants after three anti-VEGF injections (Group I), four to six anti-VEGF injections (Group II), and more than six anti-VEGF injections (Group III). Anti-VEGF treatment failure was defined as a central retinal thickness (CRT) of ≥300 microns and/or a lack of visual improvement (≤1 line of visual gain according to Snellen acuity). The last follow-up took place after 10-12 weeks of Ozurdex® injections. Results Improvement was observed in 19 eyes (46%), 17 eyes (50%), and 10 eyes (33%) in Groups I, II, and III, respectively, after switching to dexamethasone implants. The best overall results (an improvement in vision and stabilization) were seen in Group II (32 eyes, 94%). The decrease in CRT was statistically significant in all three groups.  Conclusion Intravitreal dexamethasone implants improved functional and morphological outcomes in anti-VEGF-resistant DME eyes. After four to six anti-VEGF injections, switching to a steroid implant resulted in the best functional results.

Real-World Evidence of the Long-Term Effectiveness of 0.2 μg/Day Fluocinolone Acetonide Implant in Persistent and Recurrent Diabetic Macular Edema - A Single Center Study

Purpose

To report the long-term functional, anatomical and safety outcomes of 0.2 μg/day fluocinolone acetonide 0.19mg in patients with persistent or recurrent diabetic macular edema (DME).

Methods

Retrospective, observational, single-center study of patients with recurrent or persistent DME. All patients received 0.2 μg/day of fluocinolone acetonide 0.19mg, and data were collected at baseline and months 1, 3, 6, 12, 24 and 36 after implantation. Outcomes measured included best-corrected visual acuity (BCVA), central macular thickness (CMT), intraocular pressure (IOP), and safety outcomes.

Results

A total of 28 eyes from 28 patients were included. The mean age was 66.5 years (95% CI 62.8-70.2) with a mean duration of DME of 8.8 years (95% CI 7.7-10.0). Only two eyes were phakic. Mean follow-up was 25.4 months (95% CI 21.2-29.6). Mean BCVA at baseline was 48.6 ETDRS letters (95% CI 41.3-55.8) and improved as early as month 1 of follow-up with a mean gain in BCVA of 7.8 (95% CI 4.3-11.3) ETDRS letters (p<0.001). Statistically significant improvements in BCVA were also observed at months 6, 12 and 24. At baseline, patients had a mean CMT of 530.5µm (95% CI 463.0-598.0), and a decrease in CMT was observed, starting at the first month of follow-up (mean CMT reduction of -170.5µm, 95% CI -223.8- -117.1; p<0.001). Statistically significant decreases in CMT were also observed at months 6, 12, 24, and 36, with the maximum decrease observed at month 12 (p<0.001). Mean IOP at baseline was 16.4mmHg (95% CI 15.3-17.5) and nine eyes (32.1%) had an IOP ≥21mmHg during follow-up.

Conclusion

Our results support the effectiveness and safety profile of fluocinolone acetonide. Although additional long-term real-world evidence is required, fluocinolone acetonide may represent a safe strategy for daily, low-dose, sustained and localized release to the posterior segment of the eye, providing both functional and anatomical benefits in DME.

An Eye for A Foot: Alarming Unawareness of Diabetic Retinopathy Among Diabetic Foot Patients

This study aims to determine the awareness of diabetic retinopathy in patients hospitalized for diabetic foot ulcers, examine their clinical and demographic characteristics, and evaluate their treatment needs. In this prospective study, 62 consequent patients with diabetic foot ulcers who were hospitalized for further treatment in Diabetic Foot Department between June and August 2023 were subjected to ophthalmological examinations. Detailed anterior and posterior segment examinations were performed. Clinical and demographic characteristics and HbA1c levels were recorded. Thirty-nine patients (62.9%) were male and 23 (37.1%) were female. The mean age was 61 ± 11.4 years. The patients had diabetes mellitus (DM) for an average of 19.2 ± 9.6 years. The average HbA1c value of the patients was 9 ± 2.3%. Minor amputation was performed in 35 of 62 patients (56.5%) during treatment. Thirty-one patients (50%) were unaware of the risk of diabetic retinopathy. Of those "unaware" 31 patients, 26 (83.9%) had diabetic retinopathy. Diabetic retinopathy was detected in 57 patients (91.9%) and 3-month interval ophthalmological follow-up screening was recommended for 77 eyes. Eighty percent of the patients never had ophthalmological examination. Intravitreal (IV) injection was performed in 44 eyes, panretinal photocoagulation (PRP) in 2 eyes, and intravenous injection + PRP + vitreoretinal surgery in one eye. Diabetic foot ulcers and diabetic retinopathy are often accompanied by each other. Patients should be informed about this and strongly encouraged to undergo routine ophthalmological examinations, especially when they have advanced diabetic foot disease. Diabetic foot surgeons should keep in mind that a poor eye cannot detect diabetic foot problems.

Tablet-based tests of everyday visual function in a diabetic macular oedema (DME) clinic waiting area: A feasibility study

PURPOSE

(1) To assess the feasibility of conducting tablet-based vision tests in hospital clinic waiting areas; (2) To test the hypothesis that increasing severity of diabetic macular oedema (DME) is associated with the performance of tablet-based surrogates of everyday tasks and self-reported visual function.

METHODS

Sixty-one people with mild (n = 28), moderate (n = 24) or severe (n = 9) DME performed two tablet-based tests of 'real-world' visual function (visual search and face recognition) while waiting for appointments in a hospital outpatient clinic. Participants also completed a tablet-based version of a seven-item, visual-functioning (VF-7) patient-reported outcome measure. Test performance was compared to previously published 99% normative limits for normally sighted individuals.

RESULTS

Thirty-four participants (56%; 95% confidence interval [CI] 43%-68%) exceeded normative limits for visual search, while eight (13%; 95% CI 65%-24%) exceeded normative limits for face discrimination. Search duration was significantly longer for people with severe DME than those with mild and moderate DME (p = 0.01). Face discrimination performance was not significantly associated with DME severity. VF-7 scores were statistically similar across DME severity groups. Median time to complete all elements (eligibility screening, both tablet-based tasks and the VF-7) was 22 (quartiles 19, 25) min. Further, 98% and 87% of participants, respectively, reported the search task and face discrimination task to be enjoyable, while 25% and 97%, respectively, reported finding the two tasks to be difficult.

CONCLUSIONS

Portable tablet-based tests are quick, acceptable to patients and feasible to be performed in a clinic waiting area with minimal supervision. They have the potential to be piloted in patients' homes for self-monitoring.

Quantitative evaluation of ocular vascularity and correlation analysis in patients with diabetic retinopathy by SMI and OCTA

AIMS

To find potential relation between retrobulbar vessels and fundus microvessels and to detect sensitive and effective clinical indicators in predicting the progress of diabetic retinopathy (DR), ocular hemodynamics were measured using superb microvascular imaging (SMI) and ultrawide-field optical coherence tomography angiography (UWF-OCTA).

METHODS

Observational, cross-sectional study evaluating ocular hemodynamics in patients with DR by SMI (Aplio i900, Canon Medical) and UWF-OCTA (BM-400 K BMizar, Tupai Medical Technology). The peak systolic velocity (PSV), end-diastolic velocity (EDV), and resistive index (RI) of the central retinal artery (CRA), posterior ciliary artery (PCA), and ophthalmic artery (OA) were measured by SMI. UWF-OCTA evaluated the fundus vascular parameters. A correlation analysis was used to determine the correlation between SMI and UWF-OCTA parameters.

RESULTS

One hundred thirty-nine eyes of 139 diabetic patients were included: 29 without DR (NDR), 36 with mild to moderate nonproliferative DR (M-NPDR), 37 with severe NPDR (S-NPDR), and 37 with proliferative DR (PDR). PSV and EDV of retrobulbar vessels decreased from NDR to S-NPDR while increasing PDR. RI of OA showed a decreasing trend in the progression of DR, but other vessels didn't show the same trend. ROC curve analysis showed that CRAPSV, CRAEDV, PCAEDV, OAPSV, and OAEDV had diagnostic value distinguishing M-NPDR and S-NPDR. The correlation analysis observed a significant association between the SMI parameters of CRA and PCA and UWF-OCTA parameters. CRA hemodynamics were more associated with fundus vascular parameters, especially the retina, in the NDR group than in the M-NPDR group. In contrast, PCA consistently correlated with fundus vascular parameters, especially in the choroid, from the NDR to the M-NPDR group. However, OA showed a poor correlation with OCTA parameters.

CONCLUSION

The velocity of retrobulbar vessels, mainly the CRA, may serve as a valuable predictor for assessing the progress of DR. The use of SMI in diabetic patients may help identify patients at risk of developing retinopathy.

Impact of Pachychoroid and DRIL on the Treatment of Diabetic Macular Oedema with Intravitreal Bevacizumab

PURPOSE

To evaluate the long-term outcome of intravitreal bevacizumab in eyes with diabetic macular oedema (DME) following a PRN (pro re nata) regimen. Additionally, we investigated the effect of the presence of disorganisation of the retinal inner layers (DRILs) and pachychoroid (PC) at baseline on clinical outcome.

METHODS

This retrospective study included 112 naïve eyes with DME that were followed up for 2 years. All eyes were treated with six initial bevacizumab injections at monthly intervals and then received treatment according to a PRN regimen. In case of poor response to bevacizumab, therapy was switched to other agents. Main outcome measures included: best-corrected visual acuity (BCVA), central macular thickness (CMT), and number of intravitreal injections (IVI s). In addition, we examined the effect of the presence of DRILs and PC at baseline on clinical outcome.

RESULTS

BVCA improved significantly and CMT decreased significantly during the first 2 years of treatment. The number of IVI s per eye was 11.1 ± 4.8 at the end of the second year. Treatment had to be switched to other agents in 47 eyes (42%). The timing of switching was 12.4 ± 6.1 months after a mean of 9.2 ± 3.3 IVI s. Patients with DRILs at baseline (29.5%) had significantly worse BCVA at all time points before and after treatment, although CMT was significantly lower before treatment and comparable to patients without DRILs during treatment. Patients with PC at baseline (35.7%) had no significant differences in BVCA and CMT at all time points compared with patients without PC.

CONCLUSIONS

This study demonstrates statistically significant functional and anatomical improvement in patients with DME treated with intravitreal bevacizumab after 2 years. However, more than 40% of eyes required a switch in therapy. The presence of DRILs at baseline had a negative effect whereas the presence of PC at baseline had no effect on clinical outcome.

Performance of Artificial Intelligence in Detecting Diabetic Macular Edema From Fundus Photography and Optical Coherence Tomography Images: A Systematic Review and Meta-analysis

BACKGROUND

Diabetic macular edema (DME) is the leading cause of vision loss in people with diabetes. Application of artificial intelligence (AI) in interpreting fundus photography (FP) and optical coherence tomography (OCT) images allows prompt detection and intervention.

PURPOSE

To evaluate the performance of AI in detecting DME from FP or OCT images and identify potential factors affecting model performances.

DATA SOURCES

We searched seven electronic libraries up to 12 February 2023.

STUDY SELECTION

We included studies using AI to detect DME from FP or OCT images.

DATA EXTRACTION

We extracted study characteristics and performance parameters.

DATA SYNTHESIS

Fifty-three studies were included in the meta-analysis. FP-based algorithms of 25 studies yielded pooled area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity of 0.964, 92.6%, and 91.1%, respectively. OCT-based algorithms of 28 studies yielded pooled AUROC, sensitivity, and specificity of 0.985, 95.9%, and 97.9%, respectively. Potential factors improving model performance included deep learning techniques, larger size, and more diversity in training data sets. Models demonstrated better performance when validated internally than externally, and those trained with multiple data sets showed better results upon external validation.

LIMITATIONS

Analyses were limited by unstandardized algorithm outcomes and insufficient data in patient demographics, OCT volumetric scans, and external validation.

CONCLUSIONS

This meta-analysis demonstrates satisfactory performance of AI in detecting DME from FP or OCT images. External validation is warranted for future studies to evaluate model generalizability. Further investigations may estimate optimal sample size, effect of class balance, patient demographics, and additional benefits of OCT volumetric scans.

Proteomic analysis of aqueous humor reveals novel regulators of diabetic macular edema

Diabetic macular edema (DME) is the most common cause of blindness in patients with diabetic retinopathy. To investigate the proteomic profiles of the aqueous humor (AH) of individuals with diabetic macular edema (DME), AH samples were collected from patients with non-diabetes mellitus (NDM), DM, nonproliferative diabetic retinopathy (NPDR), and DME. We performed comparative proteomic analyses using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and bioinformatics analyses. We identified 425 proteins in these AH samples, of which 113 showed changes in expression in DME compared with NDM, 95 showed changes in expression in DME vs. DM, and 84 showed changes in expression in DME compared with NPDR. The bioinformatics analysis suggested that DME is closely associated with platelet degranulation, oxidative stress-related pathway, and vascular-related pathways. Upregulation of haptoglobin (HP) and downregulation of fibrillin 1 (FBN1) were validated by ELISA. Receiver operating characteristic (ROC) analysis showed that HP and FBN1 could distinguish DME from NPDR with areas under the curve of 0.987 (p = 0.00608) and 0.791 (p = 0.00629), respectively. The findings provide potential clues for further analysis of the molecular mechanisms and the development of new treatments for DME. HP and FBN1 may be potential key proteins and therapeutic targets in human DME. The proteomics dataset generated has been deposited to the ProteomeXchange/iProX Consortium with Identifier: PXD033404/IPX0004353001.

A Review on Diabetic Retinopathy

Diabetic retinopathy is a well-recognised microvascular complication of diabetes and is among the leading cause of blindness all over the world. Over the last decade, there have been advances in the diagnosis of diabetic retinopathy and diabetic macular edema. At the same time, newer therapies for the management of diabetic retinopathy have evolved. As a result of these advances, a decline in severe vision loss due to diabetes has been witnessed in some developing countries. However, there is a steady increase in the number of people affected with diabetes, and is expected to rise further in the coming years. Therefore, it is prudent to identify diabetic retinopathy, and timely intervention is needed to decrease the burden of severe vision loss. An effort has been made to review all the existing knowledge regarding diabetic retinopathy in this article and summarize the present treatment options for diabetic retinopathy.

Clinically significant macular edema in an underserved population: Association with demographic factors and hemoglobin A1c

SIGNIFICANCE

Suspected clinically significant macular edema (SCSME) from exudates differed among ethnic groups in our underserved population. African American and Asian subjects had higher prevalence than Hispanics and non-Hispanic Caucasians, from the same clinics. Men had higher prevalence than women. Highly elevated blood glucose was frequent and associated with SCSME.

PURPOSE

We investigated the association between the presence of SCSME from exudates and hemoglobin A1c (HbA1c), as well as demographic factors such as age, sex, and ethnic group. Our population was underserved diabetic patients from the same geographic locations. Ethnic groups were White Hispanic, non-Hispanic Caucasian, African American, and Asian, with a high proportion of underrepresented minorities.

METHODS

In a diabetic retinopathy screening study at four community clinics in Alameda County, California, nonmydriatic 45° color fundus images were collected from underserved diabetic subjects following the EyePACS imaging protocol. Images were analyzed for SCSME from exudates by two certified graders. Logistic regression assessed the association between SCSME from exudates and age, sex, ethnic group, and HbA1c.

RESULTS

Of 1997 subjects, 147 (7.36%) had SCSME from exudates. The mean ± standard deviation age was 53.4 ± 10.5 years. The mean ± standard deviation HbA1c level was 8.26 ± 2.04. Logistic regression analysis indicated a significant association between presence of SCSME from exudates and HbA1c levels (p<0.001), sex (p=0.027), and ethnicity (p=0.030). African Americans (odds ratio [OR], 1.63; 95% confidence interval [CI], 1.06 to 2.50; p=0.025) and Asians (OR, 1.63; 95% CI, 1.05 to 2.54; p=0.029) had a higher risk than Hispanics. After adjusting for ethnicity, sex, and age, the odds of developing SCSME from exudates increased by 26.5% with every 1% increase in HbA1c level (OR, 1.26; 95% CI, 1.18 to 1.36; p<0.001).

CONCLUSIONS

In our underserved population, many diabetic patients had very high HbA1c values. Ethnic background (African American > Asians > Hispanics), sex (male > female), and HbA1c level were strong indicators for identifying who is at increased risk of developing SCSME from exudates.

Non-Invasive Treatment of Early Diabetic Macular Edema by Multiwavelength Photobiomodulation with the Valeda Light Delivery System

Purpose

Diabetes is associated with ocular complications including diabetic macular edema (DME). Current therapies are invasive and include repeated intravitreal injections and laser therapy. Photobiomodulation (PBM) is a treatment (Tx) that utilizes selected wavelengths of light to induce cellular benefits including reduction of inflammation and edema. This single-center, open-label, post-hoc analysis explored the utility of multiwavelength PBM in subjects with DME.

Methods

Analysis included review of data from patients undergoing standard clinical care with an approved and marketed PBM medical device, the Valeda® Light Delivery System. Subjects with early-stage DME with good vision (Best-corrected visual acuity (BCVA) > 20/25, logMAR > 0.1) were evaluated in clinic and treated with one series of multiwavelength PBM (Tx delivered 3x/week over 3-4 weeks; total of 9 Tx sessions). Clinical, anatomical, and safety parameters were assessed in addition to subjective quality of life.

Results

A total of 30 eyes (19 subjects) were analyzed. Subjects were predominately male (68.4%) with a mean age of 56 ± 14 years. Reductions in central retinal thickness (CRT), resolution of intraretinal fluid (IRF) and improvement in diabetic retinopathy severity scale scores were observed following PBM treatment in select patients. Baseline BCVA remained stable over the follow-up observation period of 3 months post-PBM. Approximately 64% of patients reported subjective improvements in their ocular condition and decreased influence in everyday life. Detailed OCT evaluations confirmed no safety issues related to phototoxicity up to 16 months.

Conclusion

Early-stage DME subjects treated with Valeda multiwavelength PBM showed improvements in clinical and anatomical parameters. The Valeda multiwavelength PBM approach demonstrates a favorable safety profile with no signs of phototoxicity following an independent OCT review. PBM therapy may offer an alternative, non-invasive treatment strategy with a unique mechanism and modality for patients with early-stage DME.

Exendin-4, a GLP-1 receptor agonist, suppresses diabetic retinopathy in vivo and in vitro

Diabetic retinopathy (DR) is a complication of diabetes and a leading cause of blindness in adults. Studies have shown that glucagon-like peptide-1 (GLP-1) exerts a protective effect on patients with DR. Here, we investigated the protective effects of Exendin-4, a GLP-1 analogue, on DR. We established a high-glucose-induced HREC cell model and an STZ-induced rat DR Model to study the effect of Exendin-4 in DR in vitro and in vivo. The qRT-PCR, CCK-8, TUNEL, western blotting, tube formation assays, and ELISA were performed. In addition, we overexpressed TGFB2 to observe whether the protective effect of Exendin-4 was reversed. Our results showed that Exendin-4 inhibited the progression of DR. Furthermore, the protective effect of Exendin-4 was suppressed in cells overexpressing TGFB2. Our findings suggest that Exendin-4 may be involved in the regulation of TGFB2 expression levels to inhibit DR. These results indicate that Exendin-4 could be an effective therapy for DR.

An effective and comprehensible method to detect and evaluate retinal damage due to diabetes complications

The leading cause of vision loss globally is diabetic retinopathy. Researchers are making great efforts to automatically detect and diagnose correctly diabetic retinopathy. Diabetic retinopathy includes five stages: no diabetic retinopathy, mild diabetic retinopathy, moderate diabetic retinopathy, severe diabetic retinopathy and proliferative diabetic retinopathy. Recent studies have offered several multi-tasking deep learning models to detect and assess the level of diabetic retinopathy. However, the explanation for the assessment of disease severity of these models is limited, and only stops at showing lesions through images. These studies have not explained on what basis the appraisal of disease severity is based. In this article, we present a system for assessing and interpreting the five stages of diabetic retinopathy. The proposed system is built from internal models including a deep learning model that detects lesions and an explanatory model that assesses disease stage. The deep learning model that detects lesions uses the Mask R-CNN deep learning network to specify the location and shape of the lesion and classify the lesion types. This model is a combination of two networks: one used to detect hemorrhagic and exudative lesions, and one used to detect vascular lesions like aneurysm and proliferation. The explanatory model appraises disease severity based on the severity of each type of lesion and the association between types. The severity of the disease will be decided by the model based on the number of lesions, the density and the area of the lesions. The experimental results on real-world datasets show that our proposed method achieves high accuracy of assessing five stages of diabetic retinopathy comparable to existing state-of-the-art methods and is capable of explaining the causes of disease severity.

Development and evaluation of a risk prediction model for diabetes mellitus type 2 patients with vision-threatening diabetic retinopathy

Objective

This study aims to develop and evaluate a non-imaging clinical data-based nomogram for predicting the risk of vision-threatening diabetic retinopathy (VTDR) in diabetes mellitus type 2 (T2DM) patients.

Methods

Based on the baseline data of the Guangdong Shaoguan Diabetes Cohort Study conducted by the Zhongshan Ophthalmic Center (ZOC) in 2019, 2294 complete data of T2DM patients were randomly divided into a training set (n=1605) and a testing set (n=689). Independent risk factors were selected through univariate and multivariate logistic regression analysis on the training dataset, and a nomogram was constructed for predicting the risk of VTDR in T2DM patients. The model was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC) in the training and testing datasets to assess discrimination, and Hosmer-Lemeshow test and calibration curves to assess calibration.

Results

The results of the multivariate logistic regression analysis showed that Age (OR = 0.954, 95% CI: 0.940-0.969, p = 0.000), BMI (OR = 0.942, 95% CI: 0.902-0.984, p = 0.007), systolic blood pressure (SBP) (OR =1.014, 95% CI: 1.007-1.022, p = 0.000), diabetes duration (10-15y: OR =3.126, 95% CI: 2.087-4.682, p = 0.000; >15y: OR =3.750, 95% CI: 2.362-5.954, p = 0.000), and glycated hemoglobin (HbA1C) (OR = 1.325, 95% CI: 1.221-1.438, p = 0.000) were independent risk factors for T2DM patients with VTDR. A nomogram was constructed using these variables. The model discrimination results showed an AUC of 0.7193 for the training set and 0.6897 for the testing set. The Hosmer-Lemeshow test results showed a high consistency between the predicted and observed probabilities for both the training set (Chi-square=2.2029, P=0.9742) and the testing set (Chi-square=7.6628, P=0.4671).

Conclusion

The introduction of Age, BMI, SBP, Duration, and HbA1C as variables helps to stratify the risk of T2DM patients with VTDR.

Elastic Deformation of Optical Coherence Tomography Images of Diabetic Macular Edema for Deep-Learning Models Training: How Far to Go?

- Objective: To explore the clinical validity of elastic deformation of optical coherence tomography (OCT) images for data augmentation in the development of deep-learning model for detection of diabetic macular edema (DME).

METHODS

Prospective evaluation of OCT images of DME (n = 320) subject to elastic transformation, with the deformation intensity represented by ([Formula: see text]). Three sets of images, each comprising 100 pairs of scans (100 original & 100 modified), were grouped according to the range of ([Formula: see text]), including low-, medium- and high-degree of augmentation; ([Formula: see text] = 1-6), ([Formula: see text] = 7-12), and ([Formula: see text] = 13-18), respectively. Three retina specialists evaluated all datasets in a blinded manner and designated each image as 'original' versus 'modified'. The rate of assignment of 'original' value to modified images (false-negative) was determined for each grader in each dataset.

RESULTS

The false-negative rates ranged between 71-77% for the low-, 63-76% for the medium-, and 50-75% for the high-augmentation categories. The corresponding rates of correct identification of original images ranged between 75-85% ([Formula: see text]0.05) in the low-, 73-85% ([Formula: see text]0.05 for graders 1 & 2, p = 0.01 for grader 3) in the medium-, and 81-91% ([Formula: see text]) in the high-augmentation categories. In the subcategory ([Formula: see text] = 7-9) the false-negative rates were 93-83%, whereas the rates of correctly identifying original images ranged between 89-99% ([Formula: see text]0.05 for all graders).

CONCLUSIONS

Deformation of low-medium intensity ([Formula: see text] = 1-9) may be applied without compromising OCT image representativeness in DME. Clinical and Translational Impact Statement-Elastic deformation may efficiently augment the size, robustness, and diversity of training datasets without altering their clinical value, enhancing the development of high-accuracy algorithms for automated interpretation of OCT images.

Fine-grained attention & knowledge-based collaborative network for diabetic retinopathy grading

Accurate diabetic retinopathy (DR) grading is crucial for making the proper treatment plan to reduce the damage caused by vision loss. This task is challenging due to the fact that the DR related lesions are often small and subtle in visual differences and intra-class variations. Moreover, relationships between the lesions and the DR levels are complicated. Although many deep learning (DL) DR grading systems have been developed with some success, there are still rooms for grading accuracy improvement. A common issue is that not much medical knowledge was used in these DL DR grading systems. As a result, the grading results are not properly interpreted by ophthalmologists, thus hinder the potential for practical applications. This paper proposes a novel fine-grained attention & knowledge-based collaborative network (FA+KC-Net) to address this concern. The fine-grained attention network dynamically divides the extracted feature maps into smaller patches and effectively captures small image features that are meaningful in the sense of its training from large amount of retinopathy fundus images. The knowledge-based collaborative network extracts a-priori medical knowledge features, i.e., lesions such as the microaneurysms (MAs), soft exudates (SEs), hard exudates (EXs), and hemorrhages (HEs). Finally, decision rules are developed to fuse the DR grading results from the fine-grained network and the knowledge-based collaborative network to make the final grading. Extensive experiments are carried out on four widely-used datasets, the DDR, Messidor, APTOS, and EyePACS to evaluate the efficacy of our method and compare with other state-of-the-art (SOTA) DL models. Simulation results show that proposed FA+KC-Net is accurate and stable, achieves the best performances on the DDR, Messidor, and APTOS datasets.

1,8-Cineole ameliorates diabetic retinopathy by inhibiting retinal pigment epithelium ferroptosis via PPAR-γ/TXNIP pathways

1,8-Cineole, the main component of volatile oil in aromatic plants, has diverse pharmacological properties, including antioxidant, anti-inflammatory, and anti-cancer properties. Diabetic retinopathy (DR) is a common microvascular complication of diabetes mellitus (DM). Here, we investigated the protective effect of 1,8-cineole on DR and found that 1,8-cineole treatment could alter the expression of several genes in both high glucose (HG)-induced ARPE-19 cells and retinal tissues of DM mice, as well as inhibit ferroptosis. Subsequent investigations into the molecular mechanisms underlying this inhibition revealed that expression of thioredoxin-interacting protein (TXNIP) was significantly upregulated while that of peroxisome proliferator-activated receptor γ (PPAR-γ) was significantly downregulated in HG-induced ARPE-19 cells, and treatment with 1,8-cineole could effectively reverse these changes. Treatment with a PPAR-γ pharmacological agonist (rosiglitazone), alone or combined with 1,8-cineole, significantly inhibited the transcription of TXNIP and ferroptosis in HG-induced ARPE-19 cells. Conversely, pretreatment with GW9662, a PPAR-γ inhibitor, upregulated the transcription and expression of TXNIP in HG-induced ARPE-19 cells; 1,8-cineole failed to reverse this upregulated expression. To explore these relationships, we constructed a PPAR-γ adenovirus shRNA to elucidate the effect of 1,8-cineole on the negative regulation of TXNIP by PPAR-γ. Taken together, the present findings indicate that HG-induced ferroptosis in retinal tissue plays an essential role in the pathogenesis of DR, which can be ameliorated by 1,8-cineole.

MicroRNA 9 Is a Regulator of Endothelial to Mesenchymal Transition in Diabetic Retinopathy

Purpose

Diabetic retinopathy (DR) is a significant cause of blindness. Most research around DR focus on late-stage developments rather than early changes such as early endothelial dysfunction. Endothelial-to-mesenchymal transition (EndMT), an epigenetically regulated process whereby endothelial cells lose endothelial characteristics and adopt mesenchymal-like phenotypes, contributes to early endothelial changes in DR. The epigenetic regulator microRNA 9 (miR-9) is suppressed in the eyes during DR. MiR-9 plays a role in various diseases and regulates EndMT-related processes in other organs. We investigated the role miR-9 plays in glucose-induced EndMT in DR.

Methods

We examined the effects of glucose on miR-9 and EndMT using human retinal endothelial cells (HRECs). We then used HRECs and an endothelial-specific miR-9 transgenic mouse line to investigate the effect of miR-9 on glucose-induced EndMT. Finally, we used HRECs to probe the mechanisms through which miR-9 may regulate EndMT.

Results

We found that miR-9 inhibition was both necessary and sufficient for glucose-induced EndMT. Overexpression of miR-9 prevented glucose-induced EndMT, whereas suppressing miR-9 caused glucose-like EndMT changes. We also found that preventing EndMT with miR-9 overexpression improved retinal vascular leakage in DR. Finally, we showed that miR-9 regulates EndMT at an early stage by regulating EndMT-inducing signals such as proinflammatory and TGF-β pathways.

Conclusions

We have shown that miR-9 is an important regulator of EndMT in DR, potentially making it a good target for RNA-based therapy in early DR.

Evaluating peripheral blood inflammatory and metabolic biomarkers as predictors in diabetic retinopathy and diabetic macular edema

Purpose

To determine the correlation between serum inflammatory and metabolic biomarkers of patients with diabetic retinopathy (DR) and diabetic macular edema (DME).

Methods

Serum samples were obtained from 100 diabetic patients. Patients were divided into three groups: group 1 (patients with no DR, n = 27), group 2 (DR with DME, n = 34), and group 3 (DR without DME, n = 39). Serum concentrations of C-reactive protein (CRP) and interleukin-6 (IL-6) were measured by quantitative turbidimetric immunoassay and sandwich chemiluminescence immunoassay, respectively. Metabolic parameters such as glycated hemoglobin (HbA1c), total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglyceride (TG), serum creatinine, and blood urea were determined by automated analyzer om-360 after standardization.

Results

The levels of IL-6 and CRP differed significantly in patients with DR and without DR (P < 0.001 and P = 0.045, respectively). We also found a positive correlation between IL-6 and CRP with the severity of DR. When DR patients with DME were compared to patients without DME, only IL-6 was observed to be significantly elevated (P < 0.001). None of the metabolic markers correlated significantly with DR and DME.

Conclusion

Significantly raised levels of serum inflammatory biomarkers can be used to elucidate the significant role of inflammation in the pathogenesis of DR. Therefore, circulating biomarkers can serve as diagnostic and therapeutic predictors for monitoring the onset and progression of DR and DME.

Association of glutathione S-transferase M1 and T1 polymorphisms on the susceptibility of diabetic retinopathy in the Bangladeshi population

Objectives

This study investigated the role of glutathione-S-transferase gene (GSTM1 and GSTT1) polymorphisms in the predisposition of type 2 diabetes mellitus (T2DM) with or without diabetic retinopathy (DR).

Methods

The case-control study included 188 subjects: 50 T2DM with DR, 63 T2DM without DR, and 75 healthy individuals' presenting no clinical signs or evidence of diabetes mellitus. Zinc and magnesium levels were measured using a flame atomic absorption spectrophotometer, and the lipid profile was evaluated using standard methods. The gene polymorphism of GSTs was performed by the multiplex-PCR method.

Results

Compared to the control, DR and T2DM had considerably greater total cholesterol, LDL-C, and decreased HDL-C levels. Magnesium levels were significantly lower in DR and T2DM than in control. Total cholesterol, LDL, TG, and magnesium levels didn't differ significantly between DR and T2DM groups. In DR, the GSTT1-null genotype was more prevalent than in T2DM subjects and controls (26.0%, 12.7%, and 10.7%, respectively). GSTT1-null genotype was considerably more common in DR than in controls and associated with 2.94-folds enhancing the chance of developing DR (OR = 2.94; 95% CI = 1.12-7.75; p = 0.02). However, the recurrence of GSTM1-null genotype was not clearly distinguishable among these three populations (28.0%, 38.1% and 29.3%, respectively) and not particularly prone to the risk of DR compared to T2DM subjects and controls (OR = 0.63; 95% CI = 0.28-1.41; p = 0.26; OR = 0.94; 95% CI = 0.42-2.07; p = 0.87, respectively).

Conclusions

Taken together, these findings suggest the potential role of GSTT1 deletion mutation as a risk factor for the vulnerability of DR among T2DM patients in the Bangladeshi population.

Serum apolipoprotein A1 and B are associated with 6-month persistent and incident diabetic macular oedema in type 2 diabetes

AIMS

To investigate the associations of baseline apolipoprotein A1 (ApoA1) and B (ApoB) levels with persistent and incident diabetic macular oedema (DMO) after 6 months of follow-up.

METHODS

This is a prospective cohort study of patients aged ≥30 years with untreated diabetic retinopathy. Examinations, fundus photography and spectral domain optical coherence tomography (SD-OCT) were assessed at baseline, 1, 3 and 6 months. Serum lipids and apolipoproteins were analysed at a pathology laboratory. DMO was confirmed using SD-OCT, classified as (1) incident DMO, (2) persistent DMO and (3) regressed DMO. Eye-specific data were used, controlling for covariates and cluster effect.

RESULTS

We recruited 53 patients but only 38 completed the study [(62 eyes), 20 eyes (32.3%) with DMO]. Higher quartile of ApoA1 was associated with lower risk of persistent/incident DMO (p for trend 0.02), while higher ApoB/A1 was associated with higher risk of persistent/incident DMO (p for trend 0.02). Every 10 mg/dL increase in ApoA1 levels was associated with lower risk of persistent/incident DMO (OR 0.69; 95% CI 0.49 to 0.92; p value 0.016), whereas every 0.2 increase in ApoB/A1 was significantly associated with higher risk of persistent/incident DMO (OR 1.4; 95% CI 1.1 to 1.9; p value 0.013) at the end of the study.

CONCLUSION

Individuals with diabetes with higher ApoA1 had lower risk of persistent/incident DMO and those with higher ApoB/A1 had higher risk of persistent/incident DMO at the end of 6 months. These suggest that serum ApoA1 and ApoB/A1 levels may be important risk factors for DMO and could be predictive of persistent/incident DMO despite anti-vascular endothelial growth factor treatment.

Diet and ideal food pyramid to prevent or support the treatment of diabetic retinopathy, age-related macular degeneration, and cataracts

Many eye diseases, such as diabetic retinopathy (DR), age-related macular degeneration (AMD), and cataracts are preventable and treatable with lifestyle. The objective of this review is to assess the most recent research on the ideal dietary approach to prevent or support the treatment of DR, AMD, and cataracts, as well as to construct a food pyramid that makes it simple for people who are at risk of developing these pathologies to decide what to eat. The food pyramid presented here proposes what should be consumed every day: 3 portions of low glycemic index (GI) grains (for fiber and zinc content), 5 portions (each portion: ≥200 g/day) of fruits and vegetables (spinach, broccoli, zucchini cooked, green leafy vegetables, orange, kiwi, grapefruit for folic acid, vitamin C, and lutein/zeaxanthin content, at least ≥42 μg/day, are to be preferred), extra virgin olive (EVO) oil (almost 20 mg/day for vitamin E and polyphenols content), nuts or oil seeds (20-30 g/day, for zinc content, at least ≥15.8 mg/day); weekly: fish (4 portions, for omega-3 content and eicosapentaenoic acid (EPA) + docosahexaenoic acid (DHA) 0.35-1.4 g/day), white meat (3 portions for vitamin B12 content), legumes (2 portions for vegetal proteins), eggs (2 portions for lutein/zeaxanthin content), light cheeses (2 portions for vitamin B6 content), and almost 3-4 times/week microgreen and spices (saffron and curcumin). At the top of the pyramid, there are two pennants: one green, which indicates the need for personalized supplementation (if daily requirements cannot be met through diet, omega-3, and L-methylfolate supplementation), and one red, which indicates that certain foods are prohibited (salt and sugar). Finally, 3-4 times per week, 30-40 min of aerobic and resistance exercises are required.

Relationship between Diabetic Nephropathy and Development of Diabetic Macular Edema in Addition to Diabetic Retinopathy

This study aimed to examine the relationship between diabetic retinopathy (DR) and systemic factors. We evaluated 261 patients (143 men, 118 women, aged 70.1 ± 10.1 years) with type 2 diabetes. All participants underwent a fundus examination, fundus photography using spectral domain optical coherence tomography (SD-OCT), and blood tests. For glycated hemoglobin (HbA1c) levels, the average and highest values in the past were used. We observed DR in 127 (70 men and 57 women) of 261 patients. Logistic regression analyses revealed a significant correlation between DR development and the duration of diabetes (OR = 2.40; 95% CI: 1.50), average HbA1c level (OR = 5.57; 95% CI: 1.27, 24.4), highest HbA1c level (OR = 2.46; 95% CI: 1.12, 5.38), and grade of diabetic nephropathy (DN) (OR = 6.23; 95% CI: 2.70, 14.4). Regression analyses revealed a significant correlation between the severity of DR and duration of diabetes (t = -6.66; 95% CI: 0.21, 0.39), average HbA1c level (t = 2.59; 95% CI: 0.14, 1.02), and severity of DN (t = 6.10; 95% CI: 0.49, 0.97). Logistic regression analyses revealed a significant correlation between diabetic macular edema (DME) development and DN grade (OR = 2.22; 95% CI: 1.33, 3.69). DN grade correlates with the development of DR and DME, and decreased renal function predicts the onset of DR.

Macular vascular features of different types of diabetic macular edema using ocular coherence tomography angiography- a comparative study

BACKGROUND

To compare the microvascular features of different subtypes of diabetic macular edema (DME) by optical coherence tomography angiography (OCTA).

METHODS

A cross-sectional study including treatment-naive patients with DME. Eyes were divided according to optical coherence tomography determined morphology into two groups: cystoid macular edema (CME) and diffuse retinal thickening (DRT), with further subdivision according to the presence of subretinal fluid. All patients underwent 3 × 3 and 6 × 6 mm OCTA scans of the macula to compare the foveal avascular zone (FAZ) area, vascular density (VD) of the superficial (SCP) and deep (DCP) capillary plexus and choriocapillaris flow (CF). Laboratory findings (HbA1C and triglyceride levels) were also correlated with the OCTA findings.

RESULTS

The study included 52 eyes, 27 had CME and 25 had DRT. There were no significant differences between the VD of the SCP (p = 0.684) and DCP (p = 0.437), FAZ of SCP (p = 0.574), FAZ of DCP (p = 0.563) and CF (p = 0.311). Linear regression analysis revealed that DME morphology was the strongest predictor for BCVA. Other significant predictors included HbA1C and triglyceride levels.

CONCLUSION

The morphology of DME, irrespective of SRF, was most significantly correlated with BCVA in treatment-naive patients and CME subtype could be an independent predictor of poor BCVA in patients with DME.

Azelaic acid and guanosine in tears improve discrimination of proliferative from non-proliferative diabetic retinopathy in type-2 diabetes patients: A tear metabolomics study

Background

Diabetic retinopathy (DR) is the microvascular ocular complication of diabetes mellitus (DM), which can lead to irreversible blindness and visual impairment if not properly treated. Tears can be collected non-invasively, and the compositions of tears could be the potential biomarkers for ocular diseases. Here we aimed to delineate the metabolomics signature in tears collected from Chinese type-2 DM patients with DR.

Methods

The metabolomics profiles of tear samples from 41 Chinese type-2 DM patients with DR and 21 non-diabetic subjects were determined by the untargeted liquid chromatography-mass spectrometry. The associated pathways of the differentially abundant metabolites were delineated, and the receiver operating characteristic curve analysis was conducted to identify the metabolites differentiating non-proliferative DR (NPDR) from proliferative DR (PDR).

Results

Total 14 differentially abundant metabolites were identified between total DR and non-diabetic subjects, and 17 differentially abundant metabolites were found between the NPDR and PDR subjects. Moreover, total 18 differentially abundant metabolites were identified between the NPDR and PDR subjects with stratification in DR duration and blood glucose level. d-Glutamine and d-glutamate metabolism was significantly highlighted in the PDR group as compared to the non-diabetic group. For the predictive performance, azelaic acid combined with guanosine achieved the area under receiver operating characteristic curve of 0.855 in the comparison between NPDR and PDR groups.

Conclusion

This study revealed the metabolomics changes in tear samples of DR patients. The metabolites in tears could be the potential biomarkers in the DR analysis.

The cGAS-STING pathway in diabetic retinopathy and age-related macular degeneration

Diabetic retinopathy and age-related macular degeneration are common retinal diseases with shared pathophysiology, including oxidative stress-induced inflammation. Cellular mechanisms responsible for converting oxidative stress into retinal damage are ill-defined but have begun to clarify. One common outcome of retinal oxidative stress is mitochondrial damage and subsequent release of mitochondrial DNA into the cytosol. This leads to activation of the cGAS-STING pathway, resulting in interferon release and disease-amplifying inflammation. This review summarizes the evolving link between aberrant cGAS-STING signaling and inflammation in common retinal diseases and provides prospective for targeting this system in diabetic retinopathy and age-related macular degeneration. Further defining the roles of this system in the retina is expected to reveal new disease pathology and novel therapeutic approaches.

The Comparison of Foveal Sensitivity Between Diabetic and Non-diabetic Patients by Using Standard Automated Perimetry 10-2 Protocol: A Cross-Sectional Study

Purpose The purpose of the study is to assess whether standard automated perimetry (SAP) was capable of detecting early neuroretinal changes by comparing foveal sensitivity in diabetic and non-diabetic subjects. Settings and design This is an observational and cross-sectional study that compared foveal sensitivity between a case group of 47 subjects with no or mild-to-moderate diabetic retinopathy (DR) without maculopathy and a control group of 43 healthy subjects. Materials and Methods After a thorough ocular examination, all patients were put through tests using a Humphrey visual field analyzer with the Swedish interactive threshold algorithm (SITA) standard system (10-2 software). The primary indicator of success was the age-adjusted foveal awareness-esteem difference. Mean deviation (MD) and pattern standard deviation (PSD) readings were the supplementary performance indicators. Results The mean age of the case and control group was 50.76 ± 13.20 years and 49.90 ± 12.20 years, respectively. The probability of cataract development was higher in the case group (p < 0.0001). In the control group, 95.3% had best-corrected visual acuity (BCVA) in the category of good visual acuity (VA) (p < 0.0001). The mean foveal sensitivity in the case group was 28.57 ± 7.54 and 32.16 ± 7.09 for the control group, and the difference was statistically significant (p < 0.023). The mean of MD in the case group was -6.05 ± 7.93, whereas in the control group, it was -3.28 ± 1.70, which was found significant (p = 0.027). There was no difference in PSD between the study groups. Conclusions Foveal sensitivity decreased in diabetics, even without maculopathy, so SAP helps identify a patient at risk of future vision loss.

Proportion of people with diabetic retinopathy and macular oedema varies by ethnicity in a tertiary retinal clinic in Australia: findings from the Liverpool Eye and Diabetes Study (LEADS)

OBJECTIVE

There are limited data on the influence of ethnicity on diabetic retinopathy (DR). We sought to determine the distribution of DR by ethnic group in Australia.

DESIGN

Clinic-based cross-sectional study.

SETTING

Participants with diabetes in a defined geographical region of Sydney, Australia, who attended a tertiary retina referral clinic.

PARTICIPANTS

The study recruited 968 participants.

INTERVENTION

Participants underwent a medical interview and retinal photography and scanning.

PRIMARY OUTCOME MEASURES

DR was defined from two-field retinal photographs. Diabetic macular oedema (DMO) was defined from spectral domain optical coherence tomography (OCT-DMO). The main outcomes were any DR, proliferative DR (PDR), clinically significant macular oedema (CSME), OCT-DMO and sight-threatening DR (STDR).

RESULTS

There was high proportion of any DR (52.3%), PDR (6.3%), CSME (19.7%), OCT-DMO (28.9%) and STDR (31.5%) in people attending a tertiary retinal clinic. Participants of Oceanian ethnicity had the highest proportion of any DR and STDR (70.4% and 48.1%, respectively), while the lowest proportion was in participants of East Asian ethnicity (38.3% and 15.8%, respectively). Proportion of any DR and STDR in Europeans was 54.5% and 30.3%, respectively. Independent predictive factors for diabetic eye disease were ethnicity, longer duration of diabetes, higher glycated haemoglobin and higher blood pressure. Even after adjusting for risk factors, Oceanian ethnicity remained associated with twofold higher odds of any DR (adjusted OR 2.10, 95% CI 1.10 to 4.00) and all other forms of DR including STDR (adjusted OR 2.22, 95% CI 1.19 to 4.15).

CONCLUSION

In people attending a tertiary retinal clinic, the proportion of people with DR varies among ethnic groups. The high proportion in persons of Oceanian ethnicity suggests a need for targeted screening of this at-risk group. In addition to traditional risks factors, ethnicity may be an additional independent predictor of DR.

Ultra-Wide-Field Fluorescein Angiography Assessment of Non-Perfusion in Patients with Diabetic Retinopathy Treated with Anti-Vascular Endothelial Growth Factor Therapy

Purpose: To follow the evolution of peripheral ischemia by fluorescein angiography (FA) on ultra-wide-field (UWF) images in diabetic patients treated with anti-vascular endothelial growth factor (anti-VEGF) for macular edema. Methods: Prospective, non-interventional cohort study analyzing UWF-FA images of 48 patients with diabetic retinopathy (48 eyes) treated for diabetic macular edema. UWF-FA was performed at baseline and after one year of anti-VEGF therapy (M12). The primary endpoint was the change in the non-perfusion index. Results: Of the 48 patients included in this study, 25 completed the one-year follow-up, and 20 had FA images of sufficient quality to be interpreted. The non-perfusion index did not significantly change from baseline after one year of anti-VEGF treatment (0.7% of the non-perfused area at baseline versus 0.5% at M12; p = 0.29). In contrast, the diabetic retinopathy severity score improved significantly between baseline and M12. Conclusions: Anti-VEGF treatment with aflibercept for diabetic macular edema had no impact on the retinal perfusion assessed by FA, but it allowed for artificially improving diabetic retinopathy severity scores.

Sulodexide Prevents Hyperglycemia-Induced Endothelial Dysfunction and Oxidative Stress in Porcine Retinal Arterioles

Diabetes mellitus may cause severe damage to retinal blood vessels. The central aim of this study was to test the hypothesis that sulodexide, a mixture of glycosaminoglycans, has a protective effect against hyperglycemia-induced endothelial dysfunction in the retina. Functional studies were performed in isolated porcine retinal arterioles. Vessels were cannulated and incubated with highly concentrated glucose solution (HG, 25 mM D-glucose) +/- sulodexide (50/5/0.5 μg/mL) or normally concentrated glucose solution (NG, 5.5 mM D-glucose) +/- sulodexide for two hours. Endothelium-dependent and endothelium-independent vasodilatation were measured by videomicroscopy. Reactive oxygen species (ROS) were quantified by dihydroethidium (DHE) fluorescence. Using high-pressure liquid chromatography (HPLC), the intrinsic antioxidant properties of sulodexide were investigated. Quantitative PCR was used to determine mRNA expression of regulatory, inflammatory, and redox genes in retinal arterioles, some of which were subsequently quantified at the protein level by immunofluorescence microscopy. Incubation of retinal arterioles with HG caused significant impairment of endothelium-dependent vasodilation, whereas endothelium-independent responses were not affected. In the HG group, ROS formation was markedly increased in the vascular wall. Strikingly, sulodexide had a protective effect against hyperglycemia-induced ROS formation in the vascular wall and had a concentration-dependent protective effect against endothelial dysfunction. Although sulodexide itself had only negligible antioxidant properties, it prevented hyperglycemia-induced overexpression of the pro-oxidant redox enzymes, NOX4 and NOX5. The data of the present study provide evidence that sulodexide has a protective effect against hyperglycemia-induced oxidative stress and endothelial dysfunction in porcine retinal arterioles, possibly by modulation of redox enzyme expression.

Epidemiology of Common Ocular Manifestations among Patients on Haemodialysis in West Bank, Palestine

Objectives

This study aimed to assess the prevalence of ocular manifestations and associated factors in patients on haemodialysis.

Methods

A cross-sectional study of patients on haemodialysis from a haemodialysis unit in Nablus, Palestine, was conducted. Medical examination for ocular manifestations (intraocular pressure, cataract, retinal changes and optic neuropathy) was performed using Tono-Pen, portable slit-lamp and indirect ophthalmoscope. Predictor variables were age, gender, smoking, medical comorbidities (diabetes, hypertension, ischaemic heart disease [IHD], peripheral arterial disease [PAD]) and use of antiplatelet or anti-coagulation medications.

Results

A total of 191 patients were included in this study. The prevalence of any ocular manifestation in at least one eye was 68%. The most common ocular manifestations were retinal changes (58%) and cataract (41%). The prevalence of non-proliferative diabetic retinopathy (NPDR), proliferative diabetic retinopathy (PDR) and NPDR or PDR was 51%, 16% and 65%. Two patients had PDR in one eye and NPDR in the other, and therefore, they were counted only once making the total for this category 71 rather than 73 patients. An increase in age by one year increased the odds of having cataract by 1.10 (95% confidence interval [CI] = 1.06-1.14). Patients with diabetes had higher odds of having cataract (odds ratio [OR] = 7.43, 95% CI: 3.26-16.95) and any retinal changes (OR = 109.48, 95% CI: 33.85-354.05) than patients without diabetes. Patients with diabetes and IHD or PAD had higher odds of having NPDR than those with diabetes without IHD or PAD (OR = 7.62, 95% CI: 2.07-28.03).

Conclusion

Retinal changes and cataract are common ocular manifestations among patients on haemodialysis. The findings emphasise the importance of periodic screening for ocular problems in this vulnerable population, especially older patients and those with diabetes, to prevent visual impartment and associated disability.

A risk prediction model for type 2 diabetes mellitus complicated with retinopathy based on machine learning and its application in health management

Objective

This study aimed to establish a risk prediction model for diabetic retinopathy (DR) in the Chinese type 2 diabetes mellitus (T2DM) population using few inspection indicators and to propose suggestions for chronic disease management.

Methods

This multi-centered retrospective cross-sectional study was conducted among 2,385 patients with T2DM. The predictors of the training set were, respectively, screened by extreme gradient boosting (XGBoost), a random forest recursive feature elimination (RF-RFE) algorithm, a backpropagation neural network (BPNN), and a least absolute shrinkage selection operator (LASSO) model. Model I, a prediction model, was established through multivariable logistic regression analysis based on the predictors repeated ≥3 times in the four screening methods. Logistic regression Model II built on the predictive factors in the previously released DR risk study was introduced into our current study to evaluate the model's effectiveness. Nine evaluation indicators were used to compare the performance of the two prediction models, including the area under the receiver operating characteristic curve (AUROC), accuracy, precision, recall, F1 score, balanced accuracy, calibration curve, Hosmer-Lemeshow test, and Net Reclassification Index (NRI).

Results

When including predictors, such as glycosylated hemoglobin A1c, disease course, postprandial blood glucose, age, systolic blood pressure, and albumin/urine creatinine ratio, multivariable logistic regression Model I demonstrated a better prediction ability than Model II. Model I revealed the highest AUROC (0.703), accuracy (0.796), precision (0.571), recall (0.035), F1 score (0.066), Hosmer-Lemeshow test (0.887), NRI (0.004), and balanced accuracy (0.514).

Conclusion

We have built an accurate DR risk prediction model with fewer indicators for patients with T2DM. It can be used to predict the individualized risk of DR in China effectively. In addition, the model can provide powerful auxiliary technical support for the clinical and health management of patients with diabetes comorbidities.

Risk of diabetic retinopathy and retinal neurodegeneration in individuals with type 2 diabetes: Beichen Eye Study

Objective

Our aim was to evaluate associations of different risk factors with odds of diabetic retinopathy (DR) diagnosis and retinal neurodegeneration represented by macular ganglion cell-inner plexiform layer (mGCIPL).

Methods

This cross-sectional study analyzed data from individuals aged over 50 years examined between June 2020 and February 2022 in the community-based Beichen Eye Study on ocular diseases. Baseline characteristics included demographic data, cardiometabolic risk factors, laboratory findings, and medications at enrollment. Retinal thickness in both eyes of all participants was measured automatically via optical coherence tomography. Risk factors associated with DR status were investigated using multivariable logistic regression. Multivariable linear regression analysis was performed to explore associations of potential risk factors with mGCIPL thickness.

Results

Among the 5037 included participants with a mean (standard deviation, SD) age of 62.6 (6.7) years (3258 women [64.6%]), 4018 (79.8%) were control individuals, 835 (16.6%) were diabetic individuals with no DR, and 184 (3.7%) were diabetic individuals with DR. The risk factors significantly associated with DR status were family history of diabetes (odds ratio [OR], 4.09 [95% CI, 2.44-6.85]), fasting plasma glucose (OR, 5.88 [95% CI, 4.66-7.43]), and statins (OR, 2.13 [95% CI, 1.03-4.43]) relative to the control individuals. Compared with the no DR, diabetes duration (OR, 1.17 [95% CI, 1.13-1.22]), hypertension (OR, 1.60 [95% CI, 1.26-2.45]), and glycated hemoglobin A1C (HbA1c) (OR, 1.27 [95% CI, 1.00-1.59]) were significantly correlated with DR status. Furthermore, age (adjusted β = -0.19 [95% CI, -0.25 to -0.13] μm; P < 0.001), cardiovascular events (adjusted β = -0.95 [95% CI, -1.78 to -0.12] μm; P = 0.03), and axial length (adjusted β = -0.82 [95% CI, -1.29 to -0.35] μm; P = 0.001) were associated with mGCIPL thinning in diabetic individuals with no DR.

Conclusion

Multiple risk factors were associated with higher odds of DR development and lower mGCIPL thickness in our study. Risk factors affecting DR status varied among the different study populations. Age, cardiovascular events, and axial length were identified as potential risk factors for consideration in relation to retinal neurodegeneration in diabetic patients.

Relationship Between Estimated Glucose Disposal Rate and Type 2 Diabetic Retinopathy

PURPOSE

To investigate the association between diabetic retinopathy (DR), DR intensity, and estimated glucose disposal rate (eGDR) in individuals with type 2 diabetes mellitus (T2DM).

PATIENTS AND METHODS

This study comprised 1762 T2DM patients who were admitted between January and December, 2021. Overall, the DR was identified in 430 patients. Based on the eGDR, the participants were divided into four study groups. One-way analysis of variance was used to compare the groups. The correlations between eGDR and DR risk, eGDR, and DR severity were analyzed using regression analysis. Furthermore, these relationships were analyzed in different sex groups.

RESULTS

Patients with T2DM had a 19.75% (348/1762) DR detection rate, whereas those with DR had a 22.41% (78/348) proliferative DR detection rate. The DR group had substantially reduced levels of eGDR compared with the non-DR group. Multivariate logistic regression analysis demonstrated that reduced eGDR was an independent risk factor for DR, after adjusting for confounding variables. eGDR correlated significantly with proliferative DR in women but not in men.

CONCLUSION

In Chinese individuals with T2DM, lower eGDR was independently associated with a higher risk of DR.

Axl, Immune Checkpoint Molecules and HIF Inhibitors from the Culture Broth of Lepista luscina

Two compounds 1 and 2 were isolated from the culture broth of Lepista luscina. This is the first time that compound 1 was isolated from a natural source. The structure of compound 1 was identified via 1D and 2D NMR and HRESIMS data. Compounds 1 and 2 along with 8-nitrotryptanthrin (4) were evaluated for their biological activities using the A549 lung cancer cell line. As a result, 1 and 2 inhibited the expression of Axl and immune checkpoint molecules. In addition, compounds 1, 2 and 4 were tested for HIF inhibitory activity. Compound 2 demonstrated statistically significant HIF inhibitory effects on NIH3T3 cells and 1 and 2 against ARPE19 cells.

CoT-XNet: contextual transformer with Xception network for diabetic retinopathy grading

Objective.Diabetic retinopathy (DR) grading is primarily performed by assessing fundus images. Many types of lesions, such as microaneurysms, hemorrhages, and soft exudates, are available simultaneously in a single image. However, their sizes may be small, making it difficult to differentiate adjacent DR grades even using deep convolutional neural networks (CNNs). Recently, a vision transformer has shown comparable or even superior performance to CNNs, and it also learns different visual representations from CNNs. Inspired by this finding, we propose a two-path contextual transformer with Xception network (CoT-XNet) to improve the accuracy of DR grading.Approach.The representations learned by CoT through one path and those by the Xception network through another path are concatenated before the fully connected layer. Meanwhile, the dedicated pre-processing, data resampling, and test time augmentation strategies are implemented. The performance of CoT-XNet is evaluated in the publicly available datasets of DDR, APTOS2019, and EyePACS, which include over 50 000 images. Ablation experiments and comprehensive comparisons with various state-of-the-art (SOTA) models have also been performed.Main results.Our proposed CoT-XNet shows better performance than available SOTA models, and the accuracy and Kappa are 83.10% and 0.8496, 84.18% and 0.9000 and 84.10% and 0.7684 respectively, in the three datasets (listed above). Class activation maps of CoT and Xception networks are different and complementary in most images.Significance.By concatenating the different visual representations learned by CoT and Xception networks, CoT-XNet can accurately grade DR from fundus images and present good generalizability. CoT-XNet will promote the application of artificial intelligence-based systems in the DR screening of large-scale populations.

Nomogram for prediction of diabetic retinopathy in patients with type 2 diabetes mellitus: A retrospective study

OBJECTIVE

To develop a nomogram for the risk of diabetic retinopathy (DR) among type 2 diabetes mellitus (T2DM).

METHODS

Questionnaires, physical examinations and biochemical tests were performed on 5900 T2DM patients in the Second Hospital of Shijiazhuang. The least absolute shrinkage and selection operator regression was used to optimize feature selection, and the importance of selected features was analyzed by random forest. Logistic regression was performed with selected features, and the nomogram was established based on the results. The Harrell's C-statistic, bootstrap-corrected C-statistic, area under curve (AUC), calibration curve, decision curve analysis (DCA) and clinical impact curve (CIC) were used to validate the discrimination, calibration and clinical usefulness of the nomogram, and further assessment was running by external validation.

RESULTS

Predictors included duration of diabetes, diabetic neuropathy, diabetic kidney disease, diabetic foot, hyperlipidemia, hypoglycemic drugs, glycated albumin, Lactate dehydrogenase. The model displayed medium predictive power with a Harrell's C-statistic of 0.820, bootstrap-corrected C-statistic of 0.813 and AUC of 0.820 in the training set, and which was respectively 0.842, 0.835 and 0.842 in the validation set. The calibration curve displayed good agreement (P > 0.05). The DCA and CIC showed that the nomogram could be applied clinically if the risk threshold is between 2 % and 75 % and 2 %-88 % in validation set.

CONCLUSIONS

This nomogram incorporating 8 features is useful to predict the risk of DR in T2DM patients.

Down-Regulation of circCOL1A2 Suppresses the Dysfunction of Diabetes-Related Retinal Microvascular Endothelial Cells via miR-646/FGF7 Axis

PURPOSE

Diabetic retinopathy (DR), the major complication of diabetes, is the leading cause of vision loss and blindness globally. Altered circular RNAs (circRNAs) expression has been found to be involved in DR process. Hence, this work aimed to explore the role and mechanism of circCOL1A2 in DR.

METHODS

Human retinal microvascular endothelial cells (RMECs) treated with high glucose (HG) were used for functional analysis. Levels of genes and proteins were detected using quantitative real-time polymerase chain reaction and western blotting. In vitro experiments were conducted by transwell, tube formation, CCK-8 assays and ELISA, respectively. The binding interaction between miR-646 and circCOL1A2 or FGF7 (Fibroblast Growth Factor 7) was confirmed using dual-luciferase reporter and RNA immunoprecipitation assays.

RESULTS

CircCOL1A2 was highly expressed in retinal tissues of DR patients and HG-induced RMECs. Then RMECs were exposed to HG treatment to mimic the diabetic conditions in vitro. Functionally, circCOL1A2 knockdown attenuated HG-evoked RMEC migration, proliferation, angiogenesis, blood-retina barrier (BRB) injury and inflammation. Mechanistically, circCOL1A2 functioned as a sponge for miR-646, and miR-646 directly targeted FGF7. Further rescue experiments showed that miR-646 inhibition abated the protective effects of circCOL1A2 knockdown on RMEC function under HG treatment. Besides that, miR-646 was decreased in HG-induced RMECs, re-expression of miR-646 reversed HG-evoked RMEC dysfunction, which was rescued by FGF7 overexpression.

CONCLUSION

CircCOL1A2 silencing can suppress HG-induced migration, proliferation, angiogenesis, BRB injury and inflammation in RMECs through miR-646/FGF7 axis, suggesting the potential involvement of circCOL1A2 in DR process.

Thirty-Year Time Trends in Diabetic Retinopathy and Macular Edema in Youth With Type 1 Diabetes

OBJECTIVE

To examine trends in diabetic retinopathy (DR) and diabetic macular edema (DME) in adolescents with type 1 diabetes between 1990 and 2019.

RESEARCH DESIGN AND METHODS

We analyzed 5,487 complication assessments for 2,404 adolescents (52.7% female, aged 12-20 years, diabetes duration >5 years), stratified by three decades (1990-1999, 2000-2009, 2010-2019). DR and DME were graded according to the modified Airlie House classification from seven-field stereoscopic fundal photography.

RESULTS

Over three decades, the prevalence of DR was 40, 21, and 20% (P < 0.001) and DME 1.4, 0.5, and 0.9% (P = 0.13), respectively, for 1990-1999, 2000-2009, and 2010-2019. Continuous subcutaneous insulin infusion (CSII) use increased (0, 12, and 55%; P < 0.001); mean HbA1c was bimodal (8.7, 8.5, and 8.7%; P < 0.001), and the proportion of adolescents meeting target HbA1c <7% did not change significantly (8.3, 7.7, and 7.1%; P = 0.63). In multivariable generalized estimating equation analysis, DR was associated with 1-2 daily injections (odds ratio 1.88, 95% CI 1.42-2.48) and multiple injections in comparison with CSII (1.38, 1.09-1.74); older age (1.11, 1.07-1.15), higher HbA1c (1.19, 1.05-1.15), longer diabetes duration (1.15, 1.12-1.18), overweight/obesity (1.27, 1.08-1.49) and higher diastolic blood pressure SDS (1.11, 1.01-1.21). DME was associated with 1-2 daily injections (3.26, 1.72-6.19), longer diabetes duration (1.26, 1.12-1.41), higher diastolic blood pressure SDS (1.66, 1.22-2.27), higher HbA1c (1.28, 1.03-1.59), and elevated cholesterol (3.78, 1.84-7.76).

CONCLUSIONS

One in five adolescents with type 1 diabetes had DR in the last decade. These findings support contemporary guidelines for lower glycemic targets, increasing CSII use, and targeting modifiable risk factors including blood pressure, cholesterol, and overweight/obesity.

Extracellular vesicles derived from human umbilical cord mesenchymal stem cells relieves diabetic retinopathy through a microRNA-30c-5p-dependent mechanism

AIMS

Extracellular vesicle (EV)-transferred microRNAs (miRNAs) are proved to be potentially therapeutic candidates. Here, we attempted to unveil the role of delivery of miR-30c-5p by human umbilical cord mesenchymal stem cells (hUCMSCs)-derived EVs in diabetic retinopathy (DR).

METHODS

miR-30c-5p and PLCG1 expression in streptozotocin-induced diabetes mellitus (DM) rats and high glucose (HG)-treated human retinal endothelial cells (HRECs) was quantified, followed by analysis on their interaction. EVs were isolated from hUCMSCs and co-cultured with HRECs. Through gain- and loss-of-function assays, the role of hUCMSCs-derived EV containing miR-30c-5p in DR involving PLCG1 and NF-κB pathway was analyzed in vitro and in vivo.

RESULTS

Elevated PLCG1 was found in DM rats and HG-treated HRECs where miR-30c-5p was reduced while increased in hUCMSC-derived EVs. PLCG1 was pinpointed as a target gene of miR-30c-5p, which consequently disrupted the PKC/NF-κB pathway. hUCMSC-derived EVs decreased inflammation reaction by transferring miR-30c-5p in DM rats and HG-treated HRECs. Furthermore, similar changing tendency was observed in HG-treated HRECs induced by overexpressed miR-30c-5p through downregulation of PLCG1 in vivo.

CONCLUSION

Overall, our findings underlined delivery of miR-30c-5p by hUCMSC-derived EVs as a novel suppressor in the inflammatory response following DR.

Proteomic analysis of vitreous humour of eyes with diabetic macular oedema: a systematic review

The pathophysiology of diabetic macular oedema (DME) remains poorly understood. Proteomic analysis of the vitreous using mass spectrometry (MS) can potentially identify proteins of pathophysiological importance. In this systematic review, we summarize the available evidence on protein changes in DME detected by MS. We systematically searched 13 literature databases on 19 September 2021. Eligible studies were defined as those using samples from human eyes with DME analysed with MS. Two authors assessed the studies for eligibility, extracted data and evaluated risk of bias independently. Six eligible studies were identified. All were designed in a cross-sectional fashion comparing results to either a non-diabetic control group or a control group without DME. A total of 62 eyes from 60 patients contributed as study group and 48 eyes from 48 patients served as control group. Proteomic analyses revealed significant differences in the vitreous protein levels in patients with DME when compared with controls. Three studies or more identified increased contents of apolipoprotein A-I, apolipoprotein A-II, apolipoprotein A-IV, apolipoprotein C-III, gelsolin, pigment epithelium-derived factor, serum albumin, transthyretin, vitamin D-binding protein in DME. Two studies found increased levels of complement factors B and C3. Protein changes reproduced across the studies suggested that DME was associated with retinal lipid accumulation, angiogenesis, retinal protective mechanisms, inflammation and complement activation. Proteome studies support the multifactorial pathogenesis of DME as proteins with highly different biological functions are regulated in DME. An important number of proteins differ, provide pathophysiological insight and suggest the direction for future research.

A high TSH level is associated with diabetic macular edema: a cross-sectional study of patients with type 2 diabetes mellitus

AIMS

In this study, we determined the association between thyroid-stimulating hormone (TSH) and diabetic macular edema (DME) by assessing the prevalence and risk factors for DME in type 2 diabetes mellitus (T2DM) patients with different thyroid dysfunctions.

METHODS

This was a retrospective cross-sectional study including 1003 euthyroid and 92 subclinical hypothyroidism (SCH) T2DM patients. DME status was detected by optical coherence tomography (OCT). The association between TSH and DME and the impact of TSH on DME were analyzed.

RESULTS

The DME prevalence was 28.3% in the SCH patients and 14.0% in the euthyroid population. The serum FT4 (P = 0.001) and FT3 (P < 0.001) levels were significantly higher in the non-DME group than in the DME group, and the TSH level (P < 0.001) was significantly lower. Four subgroups (G1-G4) were divided by TSH level, and the chi-square test indicated that even in the normal range, the TSH level was positively related to DME prevalence (P = 0.001). Subgroup data indicated that the association between TSH and DME detected by OCT (P = 0.001) was stronger than the correlation between TSH and diabetic retinopathy detected by digital retinal photographs (P = 0.027). The logistic regression model confirmed that elevated TSH was an independent risk factor for DME. The odds ratio was 1.53 (P = 0.02).

CONCLUSIONS

A high TSH level was an independent risk factor for DME. More attention should be given to the TSH level in T2DM patients due to its relationship with diabetic complications.

Gene Biomarkers Related to Th17 Cells in Macular Edema of Diabetic Retinopathy: Cutting-Edge Comprehensive Bioinformatics Analysis and In Vivo Validation

Background

Previous studies have shown that T-helper 17 (Th17) cell-related cytokines are significantly increased in the vitreous of proliferative diabetic retinopathy (PDR), suggesting that Th17 cells play an important role in the inflammatory response of diabetic retinopathy (DR), but its cell infiltration and gene correlation in the retina of DR, especially in diabetic macular edema (DME), have not been studied.

Methods

The dataset GSE160306 was downloaded from the Gene Expression Omnibus (GEO) database, which contains 9 NPDR samples and 10 DME samples. ImmuCellAI algorithm was used to estimate the abundance of Th17 cells in 24 kinds of infiltrating immune cells. The differentially expressed Th17 related genes (DETh17RGs) between NPDR and DME were documented by difference analysis and correlation analysis. Through aggregate analyses such as gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analysis, a protein-protein interaction (PPI) network was constructed to analyze the potential function of DETh17RGs. CytoHubba plug-in algorithm, Lasso regression analysis and support vector machine recursive feature elimination (SVM-RFE) were implemented to comprehensively identify Hub DETh17RGs. The expression archetypes of Hub DETh17RGs were further verified in several other independent datasets related to DR. The Th17RG score was defined as the genetic characterization of six Hub DETh17RGs using the GSVA sample score method, which was used to distinguish early and advanced diabetic nephropathy (DN) as well as normal and diabetic nephropathy. Finally, real-time quantitative PCR (qPCR) was implemented to verify the transcription levels of Hub DETh17RGs in the STZ-induced DR model mice (C57BL/6J).

Results

238 DETh17RGs were identified, of which 212 genes were positively correlated while only 26 genes were negatively correlated. Six genes (CD44, CDC42, TIMP1, BMP7, RHOC, FLT1) were identified as Hub DETh17RGs. Because DR and DN have a strong correlation in clinical practice, the verification of multiple independent datasets related to DR and DN proved that Hub DETh17RGs can not only distinguish PDR patients from normal people, but also distinguish DN patients from normal people. It can also identify the initial and advanced stages of the two diseases (NPDR vs DME, Early DN vs Advanced DN). Except for CDC42 and TIMP1, the qPCR transcription levels and trends of other Hub DETh17RGs in STZ-induced DR model mice were consistent with the human transcriptome level in this study.

Conclusion

This study will improve our understanding of Th17 cell-related molecular mechanisms in the progression of DME. At the same time, it also provides an updated basis for the molecular mechanism of Th17 cell crosstalk in the eye and kidney in diabetes.

Prediction of the Short-Term Therapeutic Effect of Anti-VEGF Therapy for Diabetic Macular Edema Using a Generative Adversarial Network with OCT Images

Purpose: To generate and evaluate individualized post-therapeutic optical coherence tomography (OCT) images that could predict the short-term response of anti-vascular endothelial growth factor (VEGF) therapy for diabetic macular edema (DME) based on pre-therapeutic images using generative adversarial network (GAN). Methods: Real-world imaging data were collected at the Department of Ophthalmology, Qilu Hospital. A total of 561 pairs of pre-therapeutic and post-therapeutic OCT images of patients with DME were retrospectively included in the training set, 71 pre-therapeutic OCT images were included in the validation set, and their corresponding post-therapeutic OCT images were used to evaluate the synthetic images. A pix2pixHD method was adopted to predict post-therapeutic OCT images in DME patients that received anti-VEGF therapy. The quality and similarity of synthetic OCT images were evaluated independently by a screening experiment and an evaluation experiment. Results: The post-therapeutic OCT images generated by the GAN model based on big data were comparable to the actual images, and the response of edema resorption was also close to the ground truth. Most synthetic images (65/71) were difficult to differentiate from the actual OCT images by retinal specialists. The mean absolute error (MAE) of the central macular thickness (CMT) between the synthetic OCT images and the actual images was 24.51 ± 18.56 μm. Conclusions: The application of GAN can objectively demonstrate the individual short-term response of anti-VEGF therapy one month in advance based on OCT images with high accuracy, which could potentially help to improve treatment compliance of DME patients, identify patients who are not responding well to treatment and optimize the treatment program.