Global Prevalence of Diabetic Retinopathy and Projection of Burden through 2045: Systematic Review and Meta-analysis

Pain control during panretinal photocoagulation for diabetic retinopathy

This is a protocol for a Cochrane Review (intervention). The objectives are as follows:

To assess the effects (benefits and harms) of different interventions aimed at controlling pain associated with panretinal photocoagulation, in people with severe non‐proliferative diabetic retinopathy and proliferative diabetic retinopathy, according to the classification of ETDRS 1991 .

KESTREL and KITE: 52-Week Results From Two Phase III Pivotal Trials of Brolucizumab for Diabetic Macular Edema

PURPOSE

To compare the efficacy and safety of brolucizumab with aflibercept in patients with diabetic macular edema (DME).

DESIGN

Double-masked, 100-week, multicenter, active-controlled, randomized trials.

METHODS

Subjects were randomized 1:1:1 to brolucizumab 3 mg/6 mg or aflibercept 2 mg in KESTREL (n = 566) or 1:1 to brolucizumab 6 mg or aflibercept 2 mg in KITE (n = 360). Brolucizumab groups received 5 loading doses every 6 weeks (q6w) followed by 12-week (q12w) dosing, with optional adjustment to every 8 weeks (q8w) if disease activity was identified at predefined assessment visits; aflibercept groups received 5 doses every 4 weeks (q4w) followed by fixed q8w dosing. The primary endpoint was best-corrected visual acuity (BCVA) change from baseline at Week 52; secondary endpoints included the proportion of subjects maintained on q12w dosing, change in Diabetic Retinopathy Severity Scale score, and anatomical and safety outcomes.

RESULTS

At Week 52, brolucizumab 6 mg was noninferior (NI margin 4 letters) to aflibercept in mean change in BCVA from baseline (KESTREL: +9.2 letters vs +10.5 letters; KITE: +10.6 letters vs +9.4 letters; P < .001), more subjects achieved central subfield thickness (CSFT) <280 µm, and fewer had persisting subretinal and/or intraretinal fluid vs aflibercept, with more than half of brolucizumab 6 mg subjects maintained on q12w dosing after loading. In KITE, brolucizumab 6 mg showed superior improvements in change of CSFT from baseline over Week 40 to Week 52 vs aflibercept (P = .001). The incidence of ocular serious adverse events was 3.7% (brolucizumab 3 mg), 1.1% (brolucizumab 6 mg), and 2.1% (aflibercept) in KESTREL; and 2.2% (brolucizumab 6 mg) and 1.7% (aflibercept) in KITE.

CONCLUSION

Brolucizumab 6 mg showed robust visual gains and anatomical improvements with an overall favorable benefit/risk profile in patients with DME.

Associations between diabetic retinopathy and modifiable risk factors: An umbrella review of meta-analyses

AIMS

Several modifiable risk factors have been meta-analysed for diabetic retinopathy (DR), such as physical activity and vitamin D status. To date, these factors have not been systematically aggregated and the credibility of evidence assessed. Therefore, the aim of this umbrella review was to aggregate all modifiable risks of DR and assess the credibility of the evidence.

METHODS

An umbrella review of meta-analyses was undertaken. For each meta-analytic association, random-effects effect size, 95% confidence intervals (CIs), heterogeneity, small-study effects, excess significance bias and 95% prediction intervals were calculated. The credibility of significant evidence (p < 0.05) was graded from I to IV, using pre-defined criteria.

RESULTS

After initial searches, 13 studies were included covering 34 independent outcomes (total participants = 824,372). Positive associations were found between insulin usage and diabetic macular oedema (RR = 4.5; 95% CI 3.1-6.6), and DR risk (RR = 2.3; 95% CI 1.4-3.9) in people with type 2 diabetes. Vitamin D deficiency was associated with DR risk (OR = 2.8; 95% CI 1.1-7.1), as was obesity (RR = 1.34; 95% CI 1.06-1.68) and sedentary behaviour (RR = 1.22; 95%CI 1.03-1.44). Intensive blood pressure targets (RR = 0.8 95%CI 0.8-1.0), and moderate physical activity (RR = 0.69; 95%CI 0.53-0.91) yielded significant protective associations with DR.

CONCLUSIONS

People with type 2 diabetes on insulin have a high risk of macular oedema and DR. Vitamin D deficiency yielded almost three times greater odds of DR, while intensive blood pressure control reduces DR risk by 20% and moderate physical activity by 31%. Healthcare professionals should use this evidence to identify those people most at risk to ensure that proper treatment and healthy lifestyles are recommended.

Prevalence of diabetic retinopathy in urban and rural India: A systematic review and meta-analysis

A systematic review and meta-analysis were conducted to estimate the prevalence of diabetic retinopathy (DR) in India’s urban and rural areas. Medline, Scopus, and ScienceDirect databases were searched for population-based studies published in English between January 1990 and April 2021, wherein the prevalence of DR among Indian residents with type 2 diabetes mellitus (DM) was reported. A random-effects model was used to estimate the overall, rural, and urban prevalence. Data from 10 eligible studies were aggregated for meta-analysis. The prevalence of DR was 17.44% (95% confidence interval [CI], 14.33–20.55) in urban and 14.00% (95% CI: 9.13–18.86) in rural population (P = 0.24). The overall DR prevalence was 16.10% (95% CI: 13.16–24.32), and the population prevalence was 1.63% [95% CI: 0.94–2.32]. Prevalence of DR in people with diabetes was lower in the age group of 40–49 years [13.57% (95% CI: 7.16–19.98)] than in the age group of 50–59 years [16.72% (95% CI: 12.80–20.64)] and the age group of 60 years and above [16.55% (95% CI: 12.09–21.00)]. Variability in studies was high: urban (I² = 88.90%); rural (I² = 92.14%). Pooled estimates indicate a narrow difference in DR prevalence among people with diabetes in rural and urban India. The fast urbanization and increasing diabetes prevalence in rural areas underscore the need for providing equitable eye care at the bottom of the health pyramid.

Opportunities of Digital Infrastructures for Disease Management-Exemplified on COVID-19-Related Change in Diagnosis Counts for Diabetes-Related Eye Diseases

Background: Retrospective research on real-world data provides the ability to gain evidence on specific topics especially when running across different sites in research networks. Those research networks have become increasingly relevant in recent years; not least due to the special situation caused by the COVID-19 pandemic. An important requirement for those networks is the data harmonization by ensuring the semantic interoperability. Aims: In this paper we demonstrate (1) how to facilitate digital infrastructures to run a retrospective study in a research network spread across university and non-university hospital sites; and (2) to answer a medical question on COVID-19 related change in diagnostic counts for diabetes-related eye diseases. Materials and methods: The study is retrospective and non-interventional and runs on medical case data documented in routine care at the participating sites. The technical infrastructure consists of the OMOP CDM and other OHDSI tools that is provided in a transferable format. An ETL process to transfer and harmonize the data to the OMOP CDM has been utilized. Cohort definitions for each year in observation have been created centrally and applied locally against medical case data of all participating sites and analyzed with descriptive statistics. Results: The analyses showed an expectable drop of the total number of diagnoses and the diagnoses for diabetes in general; whereas the number of diagnoses for diabetes-related eye diseases surprisingly decreased stronger compared to non-eye diseases. Differences in relative changes of diagnoses counts between sites show an urgent need to process multi-centric studies rather than single-site studies to reduce bias in the data. Conclusions: This study has demonstrated the ability to utilize an existing portable and standardized infrastructure and ETL process from a university hospital setting and transfer it to non-university sites. From a medical perspective further activity is needed to evaluate data quality of the utilized real-world data documented in routine care and to investigate its eligibility of this data for research.

Multicenter Evaluation of Diagnostic Circulating Biomarkers to Detect Sight-Threatening Diabetic Retinopathy

Question

Can circulating serum biomarkers distinguish people with sight-threatening diabetic retinopathy (STDR) from those with no DR?

Findings

This multicenter cross-sectional study of 538 participants found an incremental benefit of circulating cystatin C beyond the standard clinical variables in discriminating STDR from no DR. Cystatin C outperformed 12 other biomarkers found to be distinguished in STDR in previous research.

Meaning

Results of this study suggest the consideration of circulating cystatin C levels as a triage test in prioritizing people with type 2 diabetes from the community for retinal screening in resource-restricted settings.

Importance

It is a global challenge to provide regular retinal screening for all people with diabetes to detect sight-threatening diabetic retinopathy (STDR).

Objective

To determine if circulating biomarkers could be used to prioritize people with type 2 diabetes for retinal screening to detect STDR.

Design, Setting, and Participants

This cross-sectional study collected data from October 22, 2018, to December 31, 2021. All laboratory staff were masked to the clinical diagnosis, assigned a study cohort, and provided with the database containing the clinical data. This was a multicenter study conducted in parallel in 3 outpatient ophthalmology clinics in the UK and 2 centers in India. Adults 40 years and older were categorized into 4 groups: (1) no history of diabetes, (2) type 2 diabetes of at least 5 years’ duration with no evidence of DR, (3) nonproliferative DR with diabetic macular edema (DME), or (4) proliferative DR. STDR comprised groups 3 and 4.

Exposures

Thirteen previously verified biomarkers were measured using enzyme-linked immunosorbent assay.

Main Outcomes and Measures

Severity of DR and presence of DME were diagnosed using fundus photographs and optical coherence tomography. Weighted logistic regression and receiver operating characteristic curve analysis (ROC) were performed to identify biomarkers that discriminate STDR from no DR beyond the standard clinical parameters of age, disease duration, ethnicity (in the UK) and hemoglobin A_1c.

Results

A total of 538 participants (mean [SD] age, 60.8 [9.8] years; 319 men [59.3%]) were recruited into the study. A total of 264 participants (49.1%) were from India (group 1, 54 [20.5%]; group 2, 53 [20.1%]; group 3, 52 [19.7%]; group 4, 105 [39.8%]), and 274 participants (50.9%) were from the UK (group 1, 50 [18.2%]; group 2, 70 [25.5%]; group 3, 55 [20.1%]; group 4, 99 [36.1%]). ROC analysis (no DR vs STDR) showed that in addition to age, disease duration, ethnicity (in the UK) and hemoglobin A_1c, inclusion of cystatin C had near-acceptable discrimination power in both countries (area under the receiver operating characteristic curve [AUC], 0.779; 95% CI, 0.700-0.857 in 215 patients in the UK with complete data; AUC, 0.696; 95% CI, 0.602-0.791 in 208 patients in India with complete data).

Conclusions and Relevance

Results of this cross-sectional study suggest that serum cystatin C had good discrimination power in the UK and India. Circulating cystatin-C levels may be considered as a test to identify those who require prioritization for retinal screening for STDR.

Gut microbiome and retinal diseases: an updated review

PURPOSE OF REVIEW

The gut microbiome, trillions of microorganisms residing in our digestive tract, is now believed to play a significant role in retinal diseases. Breakthroughs in computational biology and specialized animal models have allowed researchers not only to characterize microbes associated with retinal diseases, but also to provide early insights into the function of the microbiome in relation to biological processes in the retinal microenvironment. This review aims to provide an update on recent advances in the current knowledge on the relationship between the gut microbiome and retinal disorders.

RECENT FINDINGS

Recent work demonstrates distinct gut microbial compositions associated with retinal diseases such as agerelated macular degeneration and retinopathy of prematurity. Currently, it is believed that gut dysbiosis leads to increased gut permeability, elevated circulation of bacterial products, microbial metabolites and inflammatory mediators that result in immune dysregulation at distant anatomic sites including the retina.

SUMMARY

Emerging evidence for the gut-retina axis can elucidate previously unknown pathways involved in retinal diseases and also presents an exciting potential therapeutic avenue. Further preclinical and clinical studies are necessary to establish causation and delineate the precise relationship of the gut microbiome with retinal disorders.

Retinal Diseases: The Next Frontier in Pharmacodelivery

The future continuous growth of the global older population augments the burden of retinal diseases worldwide. Retinal characteristics isolating and protecting the sensitive neuro-retina from the rest of the ocular tissues challenge drug delivery and promote research and development toward new horizons. In this review, we wish to describe the unmet medical needs, discuss the novel modes of delivery, and disclose to the reader a spectrum of older-to-novel drug delivery technologies, innovations, and the frontier of pharmacodelivery to the retina. Treating the main retinal diseases in the everlasting war against blindness and its associated morbidity has been growing steadily over the last two decades. Implants, new angiogenesis inhibitor agents, micro- and nano-carriers, and the anchored port delivery system are becoming new tools in this war. The revolution and evolution of new delivery methods might be just a few steps ahead, yet its assimilation in our daily clinical work may take time, due to medical, economical, and regulatory elements that need to be met in order to allow successful development and market utilization of new technologies. Therefore, further work is warranted, as detailed in this Pharmaceutics Special Issue.

Multimodal image encoding pre-training for diabetic retinopathy grading

Diabetic retinopathy is an increasingly prevalent eye disorder that can lead to severe vision impairment. The severity grading of the disease using retinal images is key to provide an adequate treatment. However, in order to learn the diverse patterns and complex relations that are required for the grading, deep neural networks require very large annotated datasets that are not always available. This has been typically addressed by reusing networks that were pre-trained for natural image classification, hence relying on additional annotated data from a different domain. In contrast, we propose a novel pre-training approach that takes advantage of unlabeled multimodal visual data commonly available in ophthalmology. The use of multimodal visual data for pre-training purposes has been previously explored by training a network in the prediction of one image modality from another. However, that approach does not ensure a broad understanding of the retinal images, given that the network may exclusively focus on the similarities between modalities while ignoring the differences. Thus, we propose a novel self-supervised pre-training that explicitly teaches the networks to learn the common characteristics between modalities as well as the characteristics that are exclusive to the input modality. This provides a complete comprehension of the input domain and facilitates the training of downstream tasks that require a broad understanding of the retinal images, such as the grading of diabetic retinopathy. To validate and analyze the proposed approach, we performed an exhaustive experimentation on different public datasets. The transfer learning performance for the grading of diabetic retinopathy is evaluated under different settings while also comparing against previous state-of-the-art pre-training approaches. Additionally, a comparison against relevant state-of-the-art works for the detection and grading of diabetic retinopathy is also provided. The results show a satisfactory performance of the proposed approach, which outperforms previous pre-training alternatives in the grading of diabetic retinopathy.

Macular Choroidal Thickness and the Risk of Referable Diabetic Retinopathy in Type 2 Diabetes: A 2-Year Longitudinal Study

Purpose

The purpose of this study was to evaluate the associations between choroidal thickness (CT) and the 2-year incidence of referable diabetic retinopathy (RDR).

Methods

This was a prospective cohort study. Patients with type 2 diabetes in Guangzhou, China, aged 30 to 80 years underwent comprehensive examinations, including standard 7-field fundus photography. Macular CT was measured using a commercial swept-source optical coherence tomography (SS-OCT) device (DRI OCT Triton; Topcon, Tokyo, Japan). The relative risk (RR) with 95% confidence intervals (CIs) was used to quantify the association between CT and new-onset RDR. The prognostic value of CT was assessed using the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

Results

A total of 1345 patients with diabetes were included in the study, and 120 (8.92%) of them had newly developed RDR at the 2-year follow-up. After adjusting for other factors, the increased RDR risk was associated with greater HbA1c (RR = 1.35, 95% CI = 1.17-1.55, P < 0.001), higher systolic blood pressure (SBP; RR = 1.02, 95% CI = 1.01-1.03, P = 0.005), lower triglyceride (TG) level (RR = 0.81, 95% CI = 0.69-0.96, P = 0.015), presence of diabetic retinopathy (DR; RR = 8.16, 95% CI = 4.47-14.89, P < 0.001), and thinner average CT (RR = 0.903, 95% CI = 0.871-0.935, P < 0.001). The addition of average CT improved NRI (0.464 ± 0.096, P < 0.001) and IDI (0.0321 ± 0.0068, P < 0.001) for risk of RDR, and it also improved the AUC from 0.708 (95% CI = 0.659-0.757) to 0.761 (95% CI = 0.719-0.804).

Conclusions

CT thinning measured by SS-OCT is an early imaging biomarker for the development of RDR, suggesting that alterations in CT play an essential role in DR occurrence.

Time Trends of Etiologies of Blindness in Israel 2009-2020:Have Methods to Decrease Leading Causes of Blindness Been Exhausted?

PURPOSE

To perform a nationwide analysis of trends in the incidence of etiologies for legal blindness in Israel during 2009-2020, and to compare the results with those of the previous decade.

DESIGN

Descriptive, retrospective population-based trend study.

METHODS

Data were retrieved from the Israeli National Registry of the Blind during 2009-2020. Data obtained included demographics, years of registration, and causes. Primary and secondary outcomes were the incidence of new certified blindness cases and its comparison with that of the previous decade, respectively.

RESULTS

The age-standardized incidence rate of blindness in Israel decreased from 15.76 per 100,000 residents in 2009 to 11.83 in 2020, a 24.9% drop. The mean annual decline was evident until 2013 (P < .001, 6.15%), but subsequently flattened (P = .71, 0.42%). Age-related macular degeneration (AMD), glaucoma, optic atrophy, and cataract decreased until 2014, and reached a plateau that was maintained until the end of the study period. Diabetic retinopathy (DR) incidence rates diminished throughout the decade (P < .001, 9.2%), with attenuation of the rate of decline after 2014.

CONCLUSIONS

The impact of efforts to reduce the incidence of preventable causes of blindness may have nearly reached saturation for most of the leading causes of blindness in Israel, namely, AMD, glaucoma and cataract. The incidence of DR has been maintained; however, attenuation has been observed. New modalities to detect and treat these causes may have to emerge before a resurgence of improvement can occur.

Loranthus regularis Ameliorates Neurodegenerative Factors in the Diabetic Rat Retina

Diabetic retinopathy remains a primary source of blindness with the growing pandemic of diabetes. Numerous studies have shown that early neurodegeneration caused by elevated oxidative stress may initiate microvascular damage in the diabetic retina during the last few decades. A variety of preventive and treatment strategies using phytochemicals that possess high antioxidants have shown great promise in reducing diabetes-induced neurodegeneration retinal damage. In this investigation, we employed an extract of Loranthus regularis, a traditional medicinal herb which is found to improve diabetes and associated complications in experimental studies. We orally treated STZ-induced diabetic rats with L. regularis and analyzed the neurodegenerative factors in the retina. After treatments, we used Western blotting techniques to analyze the protein content of neurotrophic factors (NGF, BDNF, TrkB), apoptotic factors (cytochrome c, Bcl-2, Bax), and phosphorylation of AKT in the diabetic retina. Additionally, we used ELISA methods to measure the contents of BDNF and the activity of Caspase-3 and biochemical procedures to determine the levels of glutathione and lipid peroxidation (TBARS). Our findings show that L. regularis treatments resulted in a considerable increase in neurotrophic factors and a decrease in apoptotic factors in the diabetic retina. Furthermore, in diabetic retina treated with L. regularis, the level of Bcl-2 protein increased, while the phosphor-AKT signaling improved. As a result, L. regularis may protect against diabetic-induced retinal neuronal damage by increasing neurotrophic support and reducing oxidative stress and apoptosis. Therefore, this study suggests that in diabetic retinopathy, L. regularis could be a potential therapy option for preventing neuronal cell death.

The clustering of Cardiovascular, Renal, Adipo-Metabolic Eye and Liver disease with type 2 diabetes

Type 2 diabetes is associated with an increased risk of cardiovascular disease, heart failure, chronic kidney disease, fatty liver disease, eye and foot disease. But equally, these conditions are associated with an increased risk of type 2 diabetes. Rather than being simply considered complications of diabetes, as exists within a 'pure' type 1 diabetes paradigm, both type 2 diabetes and its comorbidities are primarily caused by a failure to efficiently sequester excess energy leading to the accumulation of sick fat (adiposopathy). Type 2 diabetes is a symptom of a chronic disease complex, just as cardiovascular, renal, eye, foot and/or liver disease, are. In addition, each of these conditions feed forward so that dysfunction in one system accelerates dysfunction in another, partly through their shared pathogenesis and partly due dysfunction that follows in their wake. This review will explore the sticky, brittle conglomeration of CArdiac, Renal, Adipo-Metabolic, Eye and Liver disease (hereafter collectively known as CARAMEL disease) that is coincident in most patients with type 2 diabetes and contextualise the recent changes in diabetes guidelines that now specifically focus on identifying and aggressively managing these high-risk individuals with it.

Review of Studies Comparing Panretinal Photocoagulation and Anti-Vascular Endothelial Growth Factor Therapy in the Treatment of Proliferative Diabetic Retinopathy

Diabetic retinopathy (DR) is among the leading causes of blindness at the global level. A review of studies between 2015 and 2018 found that about 1.7% of the general population with any type of diabetes mellitus suffered from proliferative diabetic retinopathy (PDR). Since the 1960s, panretinal photocoagulation (PRP) has been the mainstay of treatment for PDR. During this period, PRP has been credited with a significant degree of success and a relatively low complication rate. However, the advent of anti-vascular endothelial growth factor (anti-VEGF) therapy with the beginning of the new millennium provided a treatment modality that was noninferior to PRP. A decade-long period of comparisons and debates between these two treatment modalities repeatedly favored anti-VEGF over PRP, as studies demonstrated that the former provided potentially superior outcomes to PRP. The aim of this review is to briefly discuss and compare the relevant studies and evidence supporting these two treatments.

Minimum Effective Dose of DPP-4 Inhibitors for Treating Early Stages of Diabetic Retinopathy in an Experimental Model

The neurovascular unit (NVU) plays an essential role in the development of diabetic retinopathy (DR). We previously reported that the topical administration (eye drops) of sitagliptin and saxagliptin, two dipeptidyl peptidase-4 inhibitors (DPP-4i), prevents retinal neurodegeneration and vascular leakage in db/db mice. The aim of the present study is to evaluate the minimum effective dose of the topical administration of these DPP-4i. For this purpose, sitagliptin and saxagliptin were tested at different concentrations (sitagliptin: 1 mg/mL, 5 and 10 mg/mL, twice per day; saxagliptin: 1 and 10 mg/mL, once or twice per day) in db/db mice. As end points of efficacy, the hallmarks of NVU impairment were evaluated: reactive gliosis, neural apoptosis, and vascular leakage. These parameters were assessed by immunohistochemistry, cell counting, and the Evans blue method, respectively. Our results demonstrated that the minimum effective dose is 5 mg/mL twice per day for sitagliptin, and 10 mg/mL twice per day for saxagliptin. In conclusion, this study provides useful results for the design of future preclinical regulatory studies and for planning clinical trials.

Understanding Neurodegeneration from a Clinical and Therapeutic Perspective in Early Diabetic Retinopathy

Recent evidence indicates that neurodegeneration is a critical element of diabetic retinopathy (DR) pathogenesis. The neuronal cells’ apoptosis contributes to microvascular impairment and blood–retinal barrier breakdown. Therefore, neurodegeneration represents an early intervention target to slow and prevent the development of microvascular alterations visible on clinical examination. Multimodal imaging features and functional assessment can permit the identification of neuronal damage in a subclinical stage before the recognition of DR signs. Clinical features of neurodegeneration are crucial in identifying patients at high risk of developing a vascular impairment and, thus, serve as outcome measures to understand the efficacy of supplementation. The optimal approach for targeting neurodegeneration contemplates the use of topical compounds that possibly act on different elements of the pathogenic cascade. To date, clinical trials available on humans tested three different topical agents, including brimonidine, somatostatin, and citicoline, with promising results.

Longitudinal associations of ocular biometric parameters with onset and progression of diabetic retinopathy in Chinese adults with type 2 diabetes mellitus

AIMS

To investigate the associations of ocular biometric parameters with incident diabetic retinopathy (DR), incident vision-threatening DR (VTDR) and DR progression.

METHODS

This community-based prospective cohort study recruited participants with type 2 diabetes aged 35-80 years from 2017 to 2019 in Guangzhou, China. Refractive error and ocular biometric parameters were measured at baseline, including axial length (AL), axial length-to-corneal radius (AL/CR) ratio, corneal curvature (CC), lens thickness (LT), anterior chamber depth (ACD), lens power and corneal diameter (CD).

RESULTS

A total of 1370 participants with a mean age of 64.3±8.1 years were followed up for two consecutive years. During the follow-up period, 342 out of 1195 (28.6%) participants without DR at baseline had incident DR, 15 out of 175 (8.57%) participants with baseline DR had DR progression and 11 of them progressed to VTDR. After multiple adjustments, a longer AL (OR=0.76; 95% CI, 0.66 to 0.86; p<0.001) and a larger AL/CR ratio (OR=0.20; 95% CI, 0.07 to 0.55; p=0.002) were associated with significantly reduced risks of incident DR but were not associated with incident VTDR or DR progression. Refractive status and other ocular biometric parameters investigated, including ACD, CC, CD, lens power and LT were not associated with any of the DR outcomes (all p>0.05).

CONCLUSIONS

A longer AL and a larger AL/CR ratio are protective against incident DR. These parameters may be incorporated into future DR risk prediction models to individualise the frequency of DR screening and prevention measures.

Deep Learning Prediction of Response to Anti-VEGF among Diabetic Macular Edema Patients: Treatment Response Analyzer System (TRAS)

Diabetic macular edema (DME) is the most common cause of visual impairment among patients with diabetes mellitus. Anti-vascular endothelial growth factors (Anti-VEGFs) are considered the first line in its management. The aim of this research has been to develop a deep learning (DL) model for predicting response to intravitreal anti-VEGF injections among DME patients. The research included treatment naive DME patients who were treated with anti-VEGF. Patient’s pre-treatment and post-treatment clinical and macular optical coherence tomography (OCT) were assessed by retina specialists, who annotated pre-treatment images for five prognostic features. Patients were also classified based on their response to treatment in their post-treatment OCT into either good responder, defined as a reduction of thickness by >25% or 50 µm by 3 months, or poor responder. A novel modified U-net DL model for image segmentation, and another DL EfficientNet-B3 model for response classification were developed and implemented for predicting response to anti-VEGF injections among patients with DME. Finally, the classification DL model was compared with different levels of ophthalmology residents and specialists regarding response classification accuracy. The segmentation deep learning model resulted in segmentation accuracy of 95.9%, with a specificity of 98.9%, and a sensitivity of 87.9%. The classification accuracy of classifying patients’ images into good and poor responders reached 75%. Upon comparing the model’s performance with practicing ophthalmology residents, ophthalmologists and retina specialists, the model’s accuracy is comparable to ophthalmologist’s accuracy. The developed DL models can segment and predict response to anti-VEGF treatment among DME patients with comparable accuracy to general ophthalmologists. Further training on a larger dataset is nonetheless needed to yield more accurate response predictions.

Connexin 43: A Target for the Treatment of Inflammation in Secondary Complications of the Kidney and Eye in Diabetes

Of increasing prevalence, diabetes is characterised by elevated blood glucose and chronic inflammation that precedes the onset of multiple secondary complications, including those of the kidney and the eye. As the leading cause of end stage renal disease and blindness in the working population, more than ever is there a demand to develop clinical interventions which can both delay and prevent disease progression. Connexins are membrane bound proteins that can form pores (hemichannels) in the cell membrane. Gated by cellular stress and injury, they open under pathophysiological conditions and in doing so release 'danger signals' including adenosine triphosphate into the extracellular environment. Linked to sterile inflammation via activation of the nod-like receptor protein 3 inflammasome, targeting aberrant hemichannel activity and the release of these danger signals has met with favourable outcomes in multiple models of disease, including secondary complications of diabetes. In this review, we provide a comprehensive update on those studies which document a role for aberrant connexin hemichannel activity in the pathogenesis of both diabetic eye and kidney disease, ahead of evaluating the efficacy of blocking connexin-43 specific hemichannels in these target tissues on tissue health and function.

Plasma Apolipoproteins Predicting the Occurrence and Severity of Diabetic Retinopathy in Patients With Type 2 Diabetes Mellitus

OBJECTIVE

Apolipoproteins are amphipathic molecules and the major components of plasma lipoproteins. This study aims to investigate the effects of dysregulated apolipoprotein (apo) profiles and their ratios on type 2 diabetes mellitus (T2DM) and diabetic retinopathy (DR) further to test the hypothesis that altered serum level of apolipoproteins is strong biomarkers for DR.

RESEARCH DESIGN AND METHODS

This case-control study consists of 157 patients with T2DM including DM without DR, non-proliferative DR (NPDR), and proliferative DR (PDR). Fifty-eight age- and sex-matched healthy subjects were enrolled as normal controls. Blood biochemistry profile including serum levels of glucose, glycated hemoglobin (HbA1c), lipid profile [total cholesterol (TC), Triglycerides (TG), high and low-density lipoprotein (HDL-C and LDL-C)] was estimated. Apolipoproteins (apos, A-I, A-II, B, C-II, C-III, and E) was evaluated by protein chips (Luminex technology). Apolipoprotein ratios and arteriosclerosis-associated plasma indices were calculated. The Kruskal-Wallis test, independent sample t-test or Mann-Whitney U test, and multivariate regression analysis were performed to investigate the association of serum lipid biomarkers and the DR severity.

RESULTS

Serum level of apoA-I was negatively correlated with TC-(HDL-C)/HDL-C (p < 0.001), fasting glucose (p < 0.001), HbA1c (p < 0.001), and (p<0.001), while apoE, apoC-II/apoC-III, apoA-II/apoA-I were positively correlated with above traditional biomarkers (p < 0.001). Single variable logistic analysis results showed that body mass index (BMI) (p = 0.023), DM duration (p < 0.001), apoE (p < 0.001), apoC-II/apo C-III (p < 0.001), apoE/apoC-II (p < 0.001), atherogenic index (p = 0.013), fasting glucose (p < 0.001), HbA1c (p < 0.001), LPA (p = 0.001), and LDL-C/HDL-C (p = 0.031) were risk factors for the occurrence and severity of DR. Multivariate logistic regression mode showed that apoC-II/apoC-III and apoB/non-HDL-C (p < 0.001) as well as apoE/apoC-II (p = 0.001) were the independent risk factors for the occurrence and severity of DR-apopA-I and apoA-II are protective factors for DR-after controlling for the duration of DM, HbA1c, fasting glucose, and LPA.

CONCLUSIONS

apoE, apoC-II/apoC-III, apoE/apoC-II, and apoB/non-HDL-C could be used as novel biomarkers for occurrence and severity of DR, whereas apoA-I and apoA-II resulted as protective factors for DR.

Development and validation of a predictive risk model based on retinal geometry for an early assessment of diabetic retinopathy

AIMS

This study aimed to develop and validate a risk nomogram prediction model based on the retinal geometry of diabetic retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM) and to investigate its clinical application value.

METHODS

In this study, we collected the clinical data of 410 patients with T2DM in the Second Affiliated Hospital of Chongqing Medical University between October 2020 and March 2022. Firstly, the patients were randomly divided into a development cohort and a validation cohort in a ratio of 7:3. Then, the modeling factors were selected using the least absolute shrinkage and selection operator (LASSO). Subsequently, a nomogram prediction model was built with these identified risk factors. Two other models were constructed with only retinal vascular traits or only clinical traits to confirm the performance advantage of this nomogram model. Finally, the model performances were assessed using the area under the receiver operating characteristic curve (AUC), calibration plot, and decision curve analysis (DCA).

RESULTS

Five predictive variables for DR among patients with T2DM were selected by LASSO regression from 33 variables, including fractal dimension, arterial tortuosity, venular caliber, duration of diabetes mellitus (DM), and insulin dosage (P< 0.05). A predictive nomogram model based on these selected clinical and retinal vascular factors presented good discrimination with an AUC of 0.909 in the training cohort and 0.876 in the validation cohort. By comparing the models, the retinal vascular parameters were proven to have a predictive value and could improve diagnostic sensitivity and specificity when combined with clinical characteristics. The calibration curve displayed high consistency between predicted and actual probability in both training and validation cohorts. The DCA demonstrated that this nomogram model led to net benefits in a wide range of threshold probability and could be adapted for clinical decision-making.

CONCLUSION

This study presented a predictive nomogram that might facilitate the risk stratification and early detection of DR among patients with T2DM.

Long-Term Oral Administration of Salidroside Alleviates Diabetic Retinopathy in db/db Mice

Diabetic retinopathy (DR), a microvascular complication of diabetes mellitus, is the leading cause of vision loss in the working-age population worldwide. Unfortunately, current clinical treatments cannot completely prevent the occurrence and development of DR. Salidroside (Sal) is a medicinal supplement that has antioxidative and cytoprotective properties. This study aimed to investigate the therapeutic effect of Sal on DR. Briefly, Sal treatment was applied to wide-type mice and db/db mice (a widely used diabetic mice) at 25 mg/kg by oral gavage once daily from 8 weeks to 20 weeks. Mice's bodyweight, blood glucose, total cholesterol, triglyceride, high density lipoprotein and low density lipoprotein were recorded and analyzed. Retinal trypsin digestion and evans blue dye assay were used to detect retinal microvessel changes and function. Retinal glutathione and malondialdehyde content measurements were applied to assess retinal oxidative stress. Full-length transcriptome analysis was performed to explore the underlying mechanisms of Sal protection. Our results found that Sal treatment could successfully relieve blood glucose and blood lipid abnormalities, and reduce retinal oxidative stress level in diabetic mice. Also, Sal treatment repaired the abnormal transcriptome caused by diabetes, alleviated the microvascular lesion of the fundus in diabetic mice, and protected retinal normal barrier function. This study enriches the indications of Sal in the treatment of diabetic diseases, providing practical research ideas for the comprehensive preventions and treatments of DR.

Monocyte/High-Density Lipoprotein Cholesterol Ratio Predicts Vitamin D Deficiency in Male Patients with Type 2 Diabetes Mellitus

PURPOSE

This study aimed to investigate the relationship between monocyte/high-density lipoprotein cholesterol ratio (MHR) and 25-hydroxyvitamin D [25(OH) D] level in patients with type 2 diabetes mellitus (T2DM), the risk factors for vitamin D deficiency, and the clinical value of MHR as a predictor of vitamin D deficiency in this population.

PATIENTS AND METHODS

This was a cross-sectional study of 260 patients with T2DM from May 2021 to October 2021. Based on internationally used criteria for defining vitamin D levels, the patients were divided according to sex and levels of vitamin D into the following four groups: Group A1 (male patients with vitamin D levels <20 ng/mL), group A2 (male patients with vitamin D levels ≥20 ng/mL), group B1 (female patients with vitamin D levels <20 ng/mL), and group B2 (female patients with vitamin D levels≥20 ng/mL). The MHR was calculated as a monocyte/high-density cholesterol lipoprotein ratio.

RESULTS

The vitamin D level was independently and negatively correlated with the MHR in male patients with T2DM, but not in female patients. The MHR was an independent risk factor and predictor for the development of vitamin D deficiency in male patients, but not in female patients, with T2DM. High-density lipoprotein (HDL) was an independent protective factor for vitamin D deficiency in female patients with T2DM.

CONCLUSION

This study suggested that the MHR was a new marker for predicting vitamin D deficiency in male patients with T2DM. Alleviating inflammation, improving lipid metabolism, and increasing HDL levels in patients with T2DM might help improve vitamin D levels, which might be important for preventing and managing T2DM. The MHR might help as a new marker to predict vitamin D deficiency in China, where primary hospitals lack the capacity for vitamin D testing on a large scale.

Diabetic retinopathy: Looking forward to 2030

Diabetic retinopathy (DR) is the major ocular complication of diabetes mellitus, and is a problem with significant global health impact. Major advances in diagnostics, technology and treatment have already revolutionized how we manage DR in the early part of the 21^st century. For example, the accessibility of imaging with optical coherence tomography, and the development of anti-vascular endothelial growth factor (VEGF) treatment are just some of the landmark developments that have shaped the DR landscape over the last few decades. Yet, there are still more exciting advances being made. Looking forward to 2030, many of these ongoing developments are likely to further transform the field. First, epidemiologic projections show that the global burden of DR is not only increasing, but also shifting from high-income countries towards middle- and low-income areas. Second, better understanding of disease pathophysiology is placing greater emphasis on retinal neural dysfunction and non-vascular aspects of diabetic retinal disease. Third, a wealth of information is becoming available from newer imaging modalities such as widefield imaging systems and optical coherence tomography angiography. Fourth, artificial intelligence for screening, diagnosis and prognostication of DR will become increasingly accessible and important. Fifth, new pharmacologic agents targeting other non-VEGF-driven pathways, and novel therapeutic strategies such as gene therapy are being developed for DR. Finally, the classification system for diabetic retinal disease will need to be continually updated to keep pace with new developments. In this article, we discuss these major trends in DR that we expect to see in 2030 and beyond.

Molecular investigation of candidate genes for pyroptosis-induced inflammation in diabetic retinopathy

BACKGROUND

Diabetic retinopathy is a diabetic microvascular complication. Pyroptosis, as a way of inflammatory death, plays an important role in the occurrence and development of diabetic retinopathy, but its underlying mechanism has not been fully elucidated. The purpose of this study is to identify the potential pyroptosis-related genes in diabetic retinopathy by bioinformatics analysis and validation in a diabetic retinopathy model and predict the microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) interacting with them. Subsequently, the competing endogenous RNA (ceRNA) regulatory network is structured to explore their potential molecular mechanism.

METHODS

We obtained mRNA expression profile dataset GSE60436 from the Gene Expression Omnibus (GEO) database and collected 51 pyroptosis-related genes from the PubMmed database. The differentially expressed pyroptosis-related genes were obtained by bioinformatics analysis with R software, and then eight key genes of interest were identified by correlation analysis, Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction (PPI) network analysis. Then, the expression levels of these key pyroptosis-related genes were validated with quantitative real-time polymerase chain reaction (qRT-PCR) in human retinal endothelial cells with high glucose incubation, which was used as an in vitro model of diabetic retinopathy. Western blot was performed to measure the protein levels of gasdermin D (GSDMD), dasdermin E (GSDME) and cleaved caspase-3 in the cells. Moreover, the aforementioned genes were further confirmed with the validation set. Finally, the ceRNA regulatory network was structured, and the miRNAs and lncRNAs which interacted with CASP3, TLR4, and GBP2 were predicted.

RESULTS

A total of 13 differentially expressed pyroptosis-related genes were screened from six proliferative diabetic retinopathy patients and three RNA samples from human retinas, including one downregulated gene and 12 upregulated genes. A correlation analysis showed that there was a correlation among these genes. Then, KEGG pathway and GO enrichment analyses were performed to explore the functional roles of these genes. The results showed that the mRNA of these genes was mainly related to inflammasome complex, interleukin-1 beta production, and NOD-like receptor signaling pathway. In addition, eight hub genes-CASP3, TLR4, NLRP3, GBP2, CASP1, CASP4, PYCARD, and GBP1-were identified by PPI network analysis using Cytoscape software. High glucose increased the protein level of GSDMD and GSDME, as critical effectors of pyroptosis, in retinal vascular endothelial cells. Verified by qRT-PCR, the expression of all these eight hub genes in the in vitro model of diabetic retinopathy was consistent with the results of the bioinformatics analysis of mRNA chip. Among them, CASP4, GBP1, CASP3, TLR4, and GBP2 were further validated in the GSE179568 dataset. Finally, 20 miRNAs were predicted to target three key genes-CASP3, GBP2, and TLR4, and 22 lncRNAs were predicted to potentially bind to these 20 miRNAs. Then, we constructed a key ceRNA network that is expected to mediate cellular pyroptosis in diabetic retinopathy.

CONCLUSION

Through the data analysis of the GEO database by R software and verification by qRT-PCR and validation set, we successfully identified potential pyroptosis-related genes involved in the occurrence of diabetic retinopathy. The key ceRNA regulatory network associated with these genes was structured. These findings might improve the understanding of molecular mechanisms underlying pyroptosis in diabetic retinopathy.

Awareness of diabetic retinopathy among diabetes mellitus patients visiting a hospital of North India

Context:

Diabetic retinopathy (DR) is a major cause of visual disability leading to irreversible blindness. Awareness of diabetes and its ocular co-morbidities may help in preventing vision loss.

Aim:

To assess the awareness of diabetic retinopathy among diabetic mellitus patients visiting a hospital in North India.

Setting and Design:

Cross-sectional study conducted at an outpatient clinic of ophthalmology department of a hospital.

Materials and Methods:

An interviewer-administered, pre-tested, semi-structured questionnaire was used to evaluate the awareness of DR for the period from July 2020 to January 2021.

Results:

A total of 272 patients with diabetes mellitus (44.4% females and 55.5% males) were included in the study. The mean age of the study population was 53.4 ± 10 years. Of the 272 patients, 79% were aware that diabetes can affect the eyes, and 69.5% knew that DR can lead to blindness. Regarding prevention and treatment of DR, 58.1% of patients were aware that good glycemic control prevents DR and 52.6% knew that DR can be treated. Physicians were the main source of information in 47.4% of patients. The participants were not compliant with a routine retinal assessment with only 26.5% of them having previous fundus examination for DR screening.

Conclusion:

Most of the participants were aware of DR but there existed major deficits in the knowledge and behavior of diabetic patients toward management of DR. There is a need to create awareness about DR and emphasize the importance of retinal screening to reduce visual disability caused by diabetes.

Circulating MicroRNAs as Potential Diagnostic Biomarkers for Diabetic Retinopathy: A Meta-Analysis

OBJECTIVE

Diabetic retinopathy (DR) is a common diabetic microvascular complication and a major cause of acquired vision loss. Finding effective biomarkers for the early identification and diagnosis of DR is crucial. This study aimed to comprehensively evaluate the accuracy of microRNAs (miRNAs) in the diagnosis of DR via a meta-analysis of previously published diagnostic studies. This study has been registered on the PROSPERO website, with the number CRD42022323238.

METHODS

We searched PubMed, Cochrane Library, Embase, Web of Science, China Wanfang database, and China Knowledge Network database to identify relevant articles published from the time of database creation to April 10, 2022. Stata 14.0 software was used to calculate the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic ratio (DOR), and area under the summary receiver operating characteristic (ROC) curve to assess the accuracy of miRNAs in the diagnosis of DR. Heterogeneity between studies was assessed using Cochran-Q test and I² statistic for quantitative analysis. The random-effect model was selected due to significant heterogeneity. Subgroup analysis and regression analysis were also performed to determine the potential sources of heterogeneity.

RESULTS

We included 25 articles detailing 52 studies with 1987 patients with DR and 1771 non-DR controls. The findings demonstrated overall sensitivity (0.82, 95% CI: 0.78 ~ 0.85), specificity (0.84, 95% CI: 0.81 ~ 0.86), PLR (5.0, 95% CI: 4.2 ~ 5.9), NLR (0.22, 95% CI: 0.18 ~ 0.26), and the area under the summary ROC curve (0.90, 95% CI: 0.87 ~ 0.92). Furthermore, we performed subgroup analysis and found that panels of multiple miRNAs could enhance the pooled sensitivity (sensitivity, specificity, and AUC values were 0.89, 0.87, and 0.94, respectively).

CONCLUSION

The meta-analysis showed that miRNAs can be used as potential diagnostic markers for DR, with high accuracy of diagnoses observed with the detection of miRNAs in plasma and serum.

The effects of acute angle closure crisis on corneal endothelial cells in patients with type 2 diabetes mellitus

OBJECTIVE

This study investigated the effects of acute angle closure crisis (AACC) on the corneal endothelial cells in patients with type 2 diabetes mellitus (DM) to identify the factors that cause corneal endothelial cell injury.

METHODS

We examined 154 patients who visited Qingdao Eye Hospital for AACC in one eye (154 eyes; 28 men and 126 women; mean age of 68 ± 8 years). We divided the participants into non-DM, DM well-control, and DM poor-control groups, with the unaffected eyes used as controls. Each participant was evaluated at the hospital while under AACC. We measured the relevant index and corneal parameters of the participants for statistical analysis.

RESULTS

There were significant statistical differences in corneal parameters among the three groups. The decreased levels of central endothelial cell density (CD) and the percentage of hexagonal cells (6A) were statistically relevant among the groups (P<0.05). The AACC duration was correlated with CD loss rate among the groups (P<0.05). The DM duration was correlated with CD loss rate in the DM well-control group. Compared with the non-DM group, the level of 6A decreased more significantly in the DM group after AACC (P<0.05). The AACC duration in the DM well-control group was significantly shorter than in the non-DM and DM poor-control groups (P<0.001). The DM poor-control group showed significantly worse visual acuity when compared with the other groups (P<0.05).

CONCLUSIONS

DM may impact the functional status of corneal endothelial cells. AACC can worsen the corneal endothelium damage in patients with DM. Blood glucose levels and the duration of intraocular hypertension are closely related to the severity of corneal endothelial injury.

Secreted Protein Acidic and Rich in Cysteine Mediates the Development and Progression of Diabetic Retinopathy

BACKGROUNDS

Diabetic retinopathy (DR) is one of the most severe microvascular complications of diabetes mellitus (DM). Secreted protein acidic and rich in cysteine (SPARC) has been found to play an important role in many diseases, but its role and mechanism in DR remain unknown.

METHODS

We studied the role of SPARC and integrin β1 in vascular pathophysiology and identified potential therapeutic translation. The SPARC levels were tested in human serum and vitreous by ELISA assay, and then the Gene Expression Omnibus (GEO) dataset was used to understand the key role of the target gene in DR. In human retinal capillary endothelial cells (HRCECs), we analyzed the mRNA and protein level by RT-PCR, immunohistochemistry, and Western blotting. The cell apoptosis, cell viability, and angiogenesis were analyzed by flow cytometry, CCK-8, and tube formation.

RESULTS

In this study, we investigated the role of SPARC in the development and progression of human DR and high glucose-induced HRCEC cells and found that the SPARC-ITGB1 signaling pathway mimics early molecular and advanced neurovascular pathophysiology complications of DR. The result revealed that DR patients have a high-level SPARC expression in serum and vitreous. Knockdown of SPARC could decrease the expressions of inflammatory factors and VEGFR, inhibit cell apoptosis and angiogenesis, and increase cell viability by regulating integrin β1 in HRCECs.

CONCLUSION

SPARC promotes diabetic retinopathy via the regulation of integrin β1. The results of this study can provide a potential therapeutic application for the treatment of DR.

Protective effects of safranal on diabetic retinopathy in human microvascular endothelial cells and related pathways analyzed with transcriptome sequencing

AIM

To determine the effect of safranal on diabetic retinopathy in vitro and its possible mechanisms.

METHODS

We used human retinal microvascular endothelial cells (HRMECs) to test the influence of safranal in vitro. High glucose damage was established and an safranal was tested at various concentrations for its potential to reduce cell viability using the MTT assay. We also employed apoptosis detection, cell cycle detection, a transwell test, and a tube formation assay to look into safranal's inhibitory effects on high glucose damage at various doses. Furthermore, mRNA transcriptome sequencing was performed. mRNA expression levels in a high glucose damage model, a high glucose damage model treated with safranal, and a blank control were compared to find the possible signaling pathway. Western blotting was used to confirm the expressions of several molecules and the levels of phosphorylation in each for the newly discovered pathway.

RESULTS

Cell proliferation was inhibited under a high glucose condition but could be protected by safranal at different concentrations (P<0.001). Flow cytometry results suggested safranal also protected cells from apoptosis (P=0.006). A transwell test demonstrated reduced invasiveness of safranal-treated cells in a high glucose condition (P<0.001). In a tube formation investigation, there were noticeably more new branches in the high gloucose group compared to a high glucose treated with safranal group (P<0.001). In mRNA expression patterns on transcriptome sequencing, the MAPK signaling pathway showed an expression ratio. With western blotting, the phosphorylation level of p38-AKT was elevated under a high glucose condition but could be inhibited by safranal. The expression of molecules associated with cell adhesion, including E-cadherin, N-cadherin, Snail, Twist, and fibronectin also changed significantly after safranal treatment under a high glucose condition.

CONCLUSION

Safranal can protect diabetic retinopathy in vitro, and the p38-AKT signaling pathway was found to be involved in the pathogenesis of diabetic retinopathy and could be inhibited by safranal. This pathway may play a role by influencing cell migration and adhesion.

CD8+T Cell-Related Gene Biomarkers in Macular Edema of Diabetic Retinopathy

BACKGROUND

CD8+T lymphocytes have a strong pro-inflammatory effect in all parts of the tissue, and some studies have demonstrated that its concentration in the vitreous increased significantly, suggesting that CD8+T cells play a pivotal role in the inflammatory response of diabetic retinopathy (DR). However, the infiltration of CD8+T cells in the DR retina, especially in diabetic macular edema (DME), and its related genes are still unclear.

METHODS

Download the GSE16036 dataset from the Gene Expression Omnibus (GEO) database. The ImmuCellAI program was performed to evaluate the abundance of 24 immune cells including CD8+T cells. The CD8+T cell-related genes (DECD8+TRGs) between non-proliferative diabetic retinopathy (NPDR) and DME were detected via difference analysis and correlation analysis. Enrichment analysis and protein-protein interaction (PPI) network mapping were implemented to explore the potential function of DECD8+TRGs. Lasso regression, support vector machine recursive feature elimination (SVM-RFE), CytoHubba plug-in and MCODE plug-in in Cytoscape software, and Weighted Gene Co-Expression Network Analysis (WGCNA) were performed to comprehensively analyze and obtain Hub DECD8+TRGs. Hub DECD8+TRGs expression patterns were further validated in other two DR-related independent datasets. The CD8+TRG score was defined as the genetic characterization of Hub DECD8+TRGs using the GSVA sample scoring method, which can be administered to distinguish early and advanced diabetic nephropathy (DN) as well as normal and DN. Finally, the transcription level of DECD8+TRGs in DR model mouse were verified by quantitative real-time PCR (qPCR).

RESULTS

A total of 371 DECD8+TRGs were identified, of which 294 genes were positively correlated and only 77 genes were negatively correlated. Eight genes (IKZF1, PTPRC, ITGB2, ITGAX, TLR7, LYN, CD74, SPI1) were recognized as Hub DECD8+TRGs. DR and DN, which have strong clinical correlation, have been proved to be associated with CD8+T cell-related hub genes by multiple independent data sets. Hub DECD8+TRGs can not only distinguish PDR from normal and DN from normal, but also play a role in the early and progressive stages of the two diseases (NPDR vs DME, Early DN vs Advanced DN). The qPCR transcription level and trend of Hub DECD8+TRGs in DR mouse model was basically the same as that in human transcriptome.

CONCLUSION

This study not only increases our understanding of the molecular mechanism of CD8+T cells in the progression of DME, but also expands people's cognitive vision of the molecular mechanism of crosstalk of CD8+T cells in the eyes and kidneys of patients with diabetes.

Long Noncoding RNAs and Mitochondrial Homeostasis in the Development of Diabetic Retinopathy

Retinopathy is one of the most devastating complications of diabetes, which a patient fears the most. Hyperglycemic environment results in many structural, functional, molecular and biochemical abnormalities in the retina, and overproduction of mitochondrial superoxide, induced by hyperglycemic milieu, is considered to play a central role in the development of diabetic retinopathy. Expression of many genes associated with maintaining mitochondrial homeostasis is also altered. Recent research has shown that several long noncoding RNAs, RNAs with more than 200 nucleotides but without any reading frames, are aberrantly expressed in diabetes, and altered expression of these long noncoding RNAs is now being implicated in the development of diabetes and its complications including retinopathy. This review focuses the role of long noncoding RNAs in the development of diabetic retinopathy, with a special emphasis on the maintenance of mitochondrial homeostasis.

Association Between Diabetic Retinopathy and Insomnia Risk: A Nationwide Population-Based Study

BACKGROUND

Previous studies have suggested a close link between sleep disturbances and diabetic retinopathy (DR). However, to date, no confirmatory findings have been reported. We aimed to explore the risk of insomnia in DR by considering demographic factors and diabetes mellitus (DM)-related variables.

METHODS

A nationwide population-based cohort of 2,206,619 patients with type 2 diabetes from the Korean National Insurance Service Database was followed up for insomnia incidence. DR, non-proliferative DR (NPDR), and proliferative DR (PDR) were defined according to ICD-10 codes. The interactive effects of sex, age, and DM-related variables were analyzed to evaluate their impact on insomnia risk in DR.

RESULTS

Compared with the non-DR group, insomnia risk was increased in the DR [(adjusted hazard ratio (aHR): 1.125, 95% confidence interval (CI):1.108-1.142), NPDR (aHR:1.117, 95% CI:1.099-1.134), and PDR (aHR:1.205, 95% CI: 1.156-1.256), even after controlling for comorbidities, lifestyle factors, and DM-related variables. The men and youngest age groups (<40 years) were most vulnerable to insomnia risk. Sex, age, DM duration, and chronic kidney disease (CKD) status exerted interactive effects with DR status in increasing the insomnia risk. In the PDR group, sex, age, DM duration, insulin therapy status, and CKD status exerted interactive effects that increased the risk of insomnia.

CONCLUSION

Insomnia risk is significantly higher in patients with DR, and clinical attention is warranted.

Gender difference in ocular diseases, risk factors and management with specific reference to role of sex steroid hormones

Our eyes are windows to the world and to our soul. The approach to them offers an incredible space for conducting research to learn more about gender differences in ocular health and disease. There is inadequate data about gender differences to accurately plan and implement strategies to address the gender disparities. In this article, we discuss several conditions with ocular manifestations, focusing on those that disproportionately affect women more, with a specific emphasis on the role of sex hormones and the management of the conditions. Articles in the past two and a half decades were selected for this mini-review from the MEDLINE/PubMed database. The search terms used were: “Age Related Macular Degeneration,” “Blindness,” “Cataract,” “Diabetic Retinopathy,” “Dry Eye,” “Glaucoma,” “Ocular Diseases.” To restrict the articles found, we limited search results with the terms: “Estrogen,” “Gender difference,” “Hormone,” “Menopause,” “Sex Steroid Hormones.”

GLP-1 RA Improves Diabetic Retinopathy by Protecting the Blood-Retinal Barrier through GLP-1R-ROCK-p-MLC Signaling Pathway

BACKGROUND

GLP-1 receptor agonists (GLP-1RA) are common clinical agents that are clinically protective against diabetic complications, such as diabetic retinopathy (DR). Previous studies have shown that the RhoA/ROCK pathway plays an important role in the development of DR. However, the specific mechanism of action between GLP-1RA and DR remains unclear. The aim of this study was thus to investigate the main mechanism involved in the protective effect of GLP-1RA on DR.

METHODS

Type 2 diabetic mice were fed a high-sugar, high-fat diet. Changes in the retinal structure were observed via HE staining and transmission electron microscopy. The expression of retinal GLP-1R, blood-retinal barrier- (BRB-) related proteins, inflammatory factors, and related pathway proteins were studied via Western blot or immunohistochemistry/immunofluorescence analysis.

RESULTS

GLP-1RA treatment reduced the blood glucose and lipid levels as well as the body weight of the diabetic mice while also improving retinal thickness, morphology, and vascular ultrastructure. Moreover, restored GLP-1R expression, increased Occludin and ZO-1 levels, and decreased albumin expression led to reduced retinal leakage and improved the BRB by inhibiting the RhoA/ROCK pathway.

CONCLUSIONS

We found that the protective effect of GLP-1RA on the retina may be realized through the GLP-1R-ROCK-p-MLC signaling pathway.

Prevalence and clinical characteristics of T2DM patients with OTUD3 gene rs78466831 SNP at a single academic center in China

BACKGROUND

A novel, rare OTUD3 c.863G>A (rs78466831) in humans has been reported associated with diabetes, but the prevalence and clinical characteristics of T2DM patients with rs78466831 have not been reported before.

OBJECTIVE

To investigate the prevalence and clinical characteristics of T2DM patients with rs78466831 and provide a basis for clinical diagnosis and treatment.

METHODS

OTUD3 gene rs78466831 SNP was detected by Sanger sequencing in all the collected specimens of laboratory-confirmed T2DM patients and healthy people. Clinical characteristics indexes inconsisting of fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglyceride (TG) and a body mass index (BMI), T2DM-associated chronic complications (myocardial infarction, cerebrovascular disease, retinopathy, arterial plaque, peripheral neuropathy and nephropathy) were obtained from the clinical laboratory information systems and electronic medical record system. Clinical characteristic indicators were compared between the wild-type and variant (rs78466831) patients with T2DM.

RESULTS

The prevalence of rs78466831 in the T2DM patients group was significantly higher than the healthy control in our academic center. The general characteristic indicators were not significantly different between the wild-type and rs78466831 patients with T2DM, except the family history of diabetes. Clinical laboratory indicators including HbA1c, FBG, OGTT, TC, HDL-C, LDL-C and CP had no significant difference between the two groups. The therapeutic drug and target achievement rates were not significantly different between the two groups. The incidence of diabetic retinopathy in the variant group was significantly higher than the wild-type group.

CONCLUSIONS

The OTUD3 gene rs78466831 was associated with T2DM and may be a biological risk factor of diabetes retinopathy.

Association between lncRNAs in plasma exosomes and diabetic retinopathy

BACKGROUND

Long noncoding RNA (lncRNA) in plasma exosomes is a potential non-invasive diagnostic biomarker for diabetic retinopathy (DR). However, the changes in plasma exosomal lncRNAs and diagnostic relevance in patients with DR patients remain unclear.

METHODS

A case-control study with type 2 diabetes mellitus (T2DM) and patients with comorbid DR were enrolled, and their clinical information and blood samples were collected. Plasma exosomes were extracted, and the relative expression levels of representative differentially expressed exosomal lncRNAs were determined. A logistic regression model was used to analyze the relationships of DR with relative lncRNA expression and DR-related factors, and receiver operating characteristic (ROC) curve analysis was used to evaluate the value of exosomal lncRNAs for DR diagnosis.

RESULTS

Sixty-two patients with T2DM and sixty-two patients with DR were matched by age, sex, and disease duration. The fasting blood glucose concentration, glycosylated hemoglobin level (HbA_1c), and relative expression of the plasma exosomal lncRNA DLX6-AS1 were significantly higher in the DR group than in the T2DM group, whereas the 2-h C-peptide concentration and relative expression of the lncRNAs PRINS and FAM190A-3 were lower in the DR group. After adjusting for relevant confounders, the fasting blood glucose concentration, HbA_1c level, 2-h C-peptide concentration, and relative expression of lncRNA DLX6-AS1, PRINS, and FAM190A-3 were found to be associated with DR. Both DLX6-AS1 [area under the curve (AUC): 0.658 (0.562-0.754)], PRINS [AUC: 0.798 (0.722-0.873)], and FAM190A-3 [AUC: 0.603 (0.503-0.702)] expression had predictive value for DR diagnosis. The combination of DLX6-AS1 and PRINS yielded an AUC of 0.813 (0.740-0.886). In males, the combination of DLX6-AS1 and PRINS yielded an AUC of 0.860 (0.780-0.940).

CONCLUSION

The fasting blood glucose concentration, HbA_1c level, and exosomal DLX6-AS1 expression were identified as risk factors for DR, whereas the 2-h C-peptide concentration and exosomal PRINS and FAM190A-3 were identified as protective against DR. The combination of exosomal DLX6-AS1 and PRINS had good diagnostic value for DR in the general population and males. More attention should be paid to the role of exosomal PRINS expression as a predictive and diagnostic DR biomarker in females.

Metabolomics of various samples advancing biomarker discovery and pathogenesis elucidation for diabetic retinopathy

Diabetic retinopathy (DR) is a universal microvascular complication of diabetes mellitus (DM), which is the main reason for global sight damage/loss in middle-aged and/or older people. Current clinical analyses, like hemoglobin A1c, possess some importance as prognostic indicators for DR severity, but no effective circulating biomarkers are used for DR in the clinic currently, and studies on the latent pathophysiology remain lacking. Recent developments in omics, especially metabolomics, continue to disclose novel potential biomarkers in several fields, including but not limited to DR. Therefore, based on the overview of metabolomics, we reviewed progress in analytical technology of metabolomics, the prominent roles and the current status of biomarkers in DR, and the update of potential biomarkers in various DR-related samples via metabolomics, including tear as well as vitreous humor, aqueous humor, retina, plasma, serum, cerebrospinal fluid, urine, and feces. In this review, we underscored the in-depth analysis and elucidation of the common biomarkers in different biological samples based on integrated results, namely, alanine, lactate, and glutamine. Alanine may participate in and regulate glucose metabolism through stimulating N-methyl-D-aspartate receptors and subsequently suppressing insulin secretion, which is the potential pathogenesis of DR. Abnormal lactate could cause extensive oxidative stress and neuroinflammation, eventually leading to retinal hypoxia and metabolic dysfunction; on the other hand, high-level lactate may damage the structure and function of the retinal endothelial cell barrier via the G protein-coupled receptor 81. Abnormal glutamine indicates a disturbance of glutamate recycling, which may affect the activation of Müller cells and proliferation via the PPP1CA-YAP-GS-Gln-mTORC1 pathway.

Exploring the Immune Infiltration Landscape and M2 Macrophage-Related Biomarkers of Proliferative Diabetic Retinopathy

BACKGROUNDS

Diabetic retinopathy (DR), especially proliferative diabetic retinopathy (PDR), is the major cause of irreversible blindness in the working-age population. Increasing evidence indicates that immune cells and the inflammatory microenvironment play an important role during PDR development. Herein, we aim to explore the immune landscape of PDR and then identify potential biomarkers correlated with specific infiltrating immune cells.

METHODS

We mined and re-analyzed PDR-related datasets from the Gene Expression Omnibus (GEO) database. Using the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm, we investigated the infiltration of 22 types of immune cells in all selected samples; analyses of differences and correlations between infiltrating cells were used to reveal the immune landscape of PDR. Thereafter, weighted gene co-expression network analysis (WGCNA) and differential expression analysis were applied to identify the hub genes on M2 macrophages that may affect PDR progression.

RESULTS

Significant differences were found between infiltration levels of immune cells in fibrovascular membranes (FVMs) from PDR and normal retinas. The percentages of follicular helper T cells, M1 macrophages, and M2 macrophages were increased significantly in FVMs. Integrative analysis combining the differential expression and co-expression revealed the M2 macrophage-related hub genes in PDR. Among these, COL5A2, CALD1, COL6A3, CORO1C, and CALU showed increased expression in FVM and may be potential biomarkers for PDR.

CONCLUSIONS

Our findings provide novel insights into the immune mechanisms involved in PDR. COL5A2, CALD1, COL6A3, CORO1C, and CALU are M2 macrophage-related biomarkers, further study of these genes could inform novel ideas and basis for the understanding of disease progression and targeted treatment of PDR.

Expressions of Serum lncRNAs in Diabetic Retinopathy - A Potential Diagnostic Tool

With increasing incidence of diabetes worldwide, there is an ever-expanding number of patients with chronic diabetic complications such as diabetic retinopathy (DR), one of the leading causes of blindness in the working age population. Early screening for the onset and severity of DR is essential for timely intervention. With recent advancements in genomic technologies, epigenetic alterations in DR are beginning to unravel. Long non-coding RNAs (lncRNAs), which are key epigenetic mediators, have demonstrated implications in several (DR) related processes. Based on the previous research, we have developed a serum-based, multi-panel PCR test using 9 lncRNAs (ANRIL, MALAT1, WISPER, ZFAS1, H19, HOTAIR, HULC, MEG3, and MIAT) to identify and validate whether this panel could be used as a diagnostic and prognostic tool for DR. We initially used a cell culture model (human retinal endothelial cells) and confirmed that 25 mM glucose induces upregulations of ANRIL, HOTAIR, HULC, MALAT1, and ZFAS1, and downregulation of H19 compared to 5 mM glucose controls. Then as an initial proof-of-concept, we tested vitreous humor and serum samples from a small cohort of non-diabetic (N=10) and diabetic patients with proliferative retinopathy (PDR, N=11) and measured the levels of the 9 lncRNAs. Differential expressions of lncRNAs were found in the vitreous and serum of patients and showed significant correlations. We expanded our approach and assessed the same lncRNAs using samples from a larger cohort of diabetic (n= 59; M/F:44/15) and non-diabetic patients (n= 11; M/F:4/7). Significant increased lncRNA expressions of ANRIL, H19, HOTAIR, HULC, MIAT, WISPER and ZFAS1 were observed in the serum of diabetic patients (with varying stages of DR) compared to non-diabetics. No significant correlations were demonstrated between lncRNA expressions and creatinine or glycated hemoglobin (HbA1C) levels. Using ROC and further analyses, we identified distinct lncRNA phenotype combinations, which may be used to identify patients with DR. Data from this study indicate that a panel of serum lncRNAs may be used for a potential screening test for DR. Further large-scale studies are needed to validate this notion.

Neurovascular Impairment and Therapeutic Strategies in Diabetic Retinopathy

Diabetic retinopathy has recently been defined as a highly specific neurovascular complication of diabetes. The chronic progression of the impairment of the interdependence of neurovascular units (NVUs) is associated with the pathogenesis of diabetic retinopathy. The NVUs consist of neurons, glial cells, and vascular cells, and the interdependent relationships between these cells are disturbed under diabetic conditions. Clinicians should understand and update the current knowledge of the neurovascular impairments in diabetic retinopathy. Above all, neuronal cell death is an irreversible change, and it is directly related to vision loss in patients with diabetic retinopathy. Thus, neuroprotective and vasoprotective therapies for diabetic retinopathy must be established. Understanding the physiological and pathological interdependence of the NVUs is helpful in establishing neuroprotective and vasoprotective therapies for diabetic retinopathy. This review focuses on the pathogenesis of the neurovascular impairments and introduces possible neurovascular protective therapies for diabetic retinopathy.

Decorin Concentrations in Aqueous Humor of Patients with Diabetic Retinopathy

Diabetic retinopathy (DR) is a microvascular complication of diabetes in the retina. Chronic hyperglycemia damages retinal microvasculature embedded into the extracellular matrix (ECM), causing fluid leakage and ischemic retinal neovascularization. Current treatment strategies include intravitreal anti-vascular endothelial growth factor (VEGF) or steroidal injections, laser photocoagulation, or vitrectomy in severe cases. However, treatment may require multiple modalities or repeat treatments due to variable response. Though DR management has achieved great success, improved, long-lasting, and predictable treatments are needed, including new biomarkers and therapeutic approaches. Small-leucine rich proteoglycans, such as decorin, constitute an integral component of retinal endothelial ECM. Therefore, any damage to microvasculature can trigger its antifibrotic and antiangiogenic response against retinal vascular pathologies, including DR. We conducted a cross-sectional study to examine the association between aqueous humor (AH) decorin levels, if any, and severity of DR. A total of 82 subjects (26 control, 56 DR) were recruited. AH was collected and decorin concentrations were measured using an enzyme-linked immunosorbent assay (ELISA). Decorin was significantly increased in the AH of DR subjects compared to controls (p = 0.0034). AH decorin levels were increased in severe DR groups in ETDRS and Gloucestershire classifications. Decorin concentrations also displayed a significant association with visual acuity (LogMAR) measurements. In conclusion, aqueous humor decorin concentrations were found elevated in DR subjects, possibly due to a compensatory response to the retinal microvascular changes during hyperglycemia.

Screening Referable Diabetic Retinopathy Using a Semi-automated Deep Learning Algorithm Assisted Approach

Purpose: To assess the accuracy and efficacy of a semi-automated deep learning algorithm (DLA) assisted approach to detect vision-threatening diabetic retinopathy (DR).

Methods: We developed a two-step semi-automated DLA-assisted approach to grade fundus photographs for vision-threatening referable DR. Study images were obtained from the Lingtou Cohort Study, and captured at participant enrollment in 2009–2010 (“baseline images”) and annual follow-up between 2011 and 2017. To begin, a validated DLA automatically graded baseline images for referable DR and classified them as positive, negative, or ungradable. Following, each positive image, all other available images from patients who had a positive image, and a 5% random sample of all negative images were selected and regraded by trained human graders. A reference standard diagnosis was assigned once all graders achieved consistent grading outcomes or with a senior ophthalmologist's final diagnosis. The semi-automated DLA assisted approach combined initial DLA screening and subsequent human grading for images identified as high-risk. This approach was further validated within the follow-up image datasets and its time and economic costs evaluated against fully human grading.

Results: For evaluation of baseline images, a total of 33,115 images were included and automatically graded by the DLA. 2,604 images (480 positive results, 624 available other images from participants with a positive result, and 1500 random negative samples) were selected and regraded by graders. The DLA achieved an area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy of 0.953, 0.970, 0.879, and 88.6%, respectively. In further validation within the follow-up image datasets, a total of 88,363 images were graded using this semi-automated approach and human grading was performed on 8975 selected images. The DLA achieved an AUC, sensitivity, and specificity of 0.914, 0.852, 0.853, respectively. Compared against fully human grading, the semi-automated DLA-assisted approach achieved an estimated 75.6% time and 90.1% economic cost saving.

Conclusions: The DLA described in this study was able to achieve high accuracy, sensitivity, and specificity in grading fundus images for referable DR. Validated against long-term follow-up datasets, a semi-automated DLA-assisted approach was able to accurately identify suspect cases, and minimize misdiagnosis whilst balancing safety, time, and economic cost.

Usefulness of Machine Learning for Identification of Referable Diabetic Retinopathy in a Large-Scale Population-Based Study

Purpose: To development and validation of machine learning-based classifiers based on simple non-ocular metrics for detecting referable diabetic retinopathy (RDR) in a large-scale Chinese population–based survey.

Methods: The 1,418 patients with diabetes mellitus from 8,952 rural residents screened in the population-based Dongguan Eye Study were used for model development and validation. Eight algorithms [extreme gradient boosting (XGBoost), random forest, naïve Bayes, k-nearest neighbor (KNN), AdaBoost, Light GBM, artificial neural network (ANN), and logistic regression] were used for modeling to detect RDR in individuals with diabetes. The area under the receiver operating characteristic curve (AUC) and their 95% confidential interval (95% CI) were estimated using five-fold cross-validation as well as an 80:20 ratio of training and validation.

Results: The 10 most important features in machine learning models were duration of diabetes, HbA1c, systolic blood pressure, triglyceride, body mass index, serum creatine, age, educational level, duration of hypertension, and income level. Based on these top 10 variables, the XGBoost model achieved the best discriminative performance, with an AUC of 0.816 (95%CI: 0.812, 0.820). The AUCs for logistic regression, AdaBoost, naïve Bayes, and Random forest were 0.766 (95%CI: 0.756, 0.776), 0.754 (95%CI: 0.744, 0.764), 0.753 (95%CI: 0.743, 0.763), and 0.705 (95%CI: 0.697, 0.713), respectively.

Conclusions: A machine learning–based classifier that used 10 easily obtained non-ocular variables was able to effectively detect RDR patients. The importance scores of the variables provide insight to prevent the occurrence of RDR. Screening RDR with machine learning provides a useful complementary tool for clinical practice in resource-poor areas with limited ophthalmic infrastructure.