Abstract Purpose To determine whether early visual acuity response to ranibizumab in diabetic macular edema is associated with long-term outcome. Design Post-hoc analysis of ...randomized-controlled-trial data Methods Pooled data from the ranibizumab plus prompt and deferred laser treatment arms of the Diabetic Retinopathy Clinical Research Network’s Protocol I study were used to explore the relationship between early (week 12) and late (weeks 52‒156) visual acuity response mean change from baseline in best-corrected visual acuity (CFB BCVA); categorized improvement (<5, 5‒9, or ≥10 Early Treatment Diabetic Retinopathy Study ETDRS letters) in BCVA. Results In the analysis population (340 eyes), <5, 5‒9, and ≥10-letter BCVA improvements occurred in 39.7%, 23.2% and 37.1% of eyes, respectively, at 12 weeks, and 34.2%, 16.5% and 49.3% of eyes at 156 weeks. Within each early BCVA response category (<5, 5‒9, and ≥10 letter- improvement at 12 weeks), mean CFB BCVA at 52‒156 weeks varied by <5 letters from that at 12 weeks. CFB BCVA and <5-letter improvement at 12 weeks showed significant positive and negative association, respectively, with CFB BCVA and ≥10-letter improvement at 52 and 156 weeks. Similar relationships were demonstrated in eyes with baseline BCVA <69 letters, and associations remained significant after multivariate adjustment for potential confounders. Conclusions Ranibizumab ± laser therapy resulted in similar rates (∼40%) of suboptimal (<5-letter) and pronounced (≥10-letter) BCVA improvement at 12 weeks. Eyes with suboptimal early BCVA response showed poorer long-term visual outcomes than eyes with pronounced early response (mean improvement 3.0 vs 13.8 letters at 156 weeks).
Introduction: Diabetic retinopathy (DR) is the leading cause of vision loss in the working age population of the developed world. DR encompasses a complex pathology, and one that is reflected in the ...variety of currently available treatments, which include laser photocoagulation, glucocorticoids, vitrectomy and agents which neutralize vascular endothelial growth factor (VEGF). Whilst these options demonstrate modest clinical benefits, none is yet to fully attenuate clinical progression or reverse damage to the retina.
This has led to an interest in developing novel therapies for the condition, such as mediators of angiopoietin signaling axes, immunosuppressants, nonsteroidal anti-inflammatory drugs (NSAIDs), oxidative stress inhibitors and vitriol viscosity inhibitors. Further, preclinical research suggests that gene therapy treatment for DR could provide significant benefits over existing treatments options.
Areas covered: Here we review the pathophysiology of DR and provide an overview of currently available treatments. We then outline recent advances made towards improved patient outcomes and highlight the potential of the gene therapy paradigm to revolutionize DR management.
Expert opinion: Whilst significant progress has been made towards our understanding of DR, further research is required to enable the development of a detailed spatiotemporal model of the disease. In addition, we hope that improvements in our knowledge of the condition facilitate therapeutic innovations that continue to address unmet medical need and improve patient outcomes, with a focus on the development of targeted medicines.
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
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.
Diabetic retinopathy (DR) is one of the serious complications that occurs in diabetic patients that frequently causes blindness. Long noncoding RNAs (lncRNAs) have been associated with DR pathology. ...This study aimed to determine the underlying mechanism of lncRNA maternally expressed gene 3 (MEG3) in association with DNA methyltransferase 1 (DNMT1) in the endothelial-mesenchymal transition (endMT) that occurs in DR. A rat model of DR was induced by streptozotocin (STZ) injection, and a high-glucose (HG)-induced cell model was established by exposing microvascular endothelial cells obtained from retina of rats to HG. Subsequently, MEG3 was overexpressed in rat and cell models to characterize its impact on endMT in DR and the involvement of the phosphatidylinositol 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) signaling pathway. Furthermore, the methylation level of MEG3 promoter region was determined with the application of methylation-specific polymerase chain reaction, followed by chromatin immunoprecipitation assay for methyltransferase enrichment. Finally, we examined the regulation of DNMT1 on MEG3 methylation and endMT in the HG-induced cell model. The results obtained revealed downregulated MEG3 expression in DR rat and cell models. Overexpressed MEG3 was shown to suppress endMT in DR rat and cell models through the inhibition of the PI3K/Akt/mTOR signaling pathway. Notably, DNMT1 could promote MEG3 promoter methylation to inhibit MEG3 expression by recruiting methyltransferase, which activated the PI3K/Akt/mTOR signaling pathway to accelerate endMT in DR. These findings further highlighted the inhibitory effect of MEG3 on endMT in DR, thus presenting a novel therapeutic target candidate for DR treatment.
Diabetes is a global eye health issue. Given the rising in diabetes prevalence and ageing population, this poses significant challenge to perform diabetic retinopathy (DR) screening for these ...patients. Artificial intelligence (AI) using machine learning and deep learning have been adopted by various groups to develop automated DR detection algorithms. This article aims to describe the state-of-art AI DR screening technologies that have been described in the literature, some of which are already commercially available. All these technologies were designed using different training datasets and technical methodologies. Although many groups have published robust diagnostic performance of the AI algorithms for DR screening, future research is required to address several challenges, for examples medicolegal implications, ethics, and clinical deployment model in order to expedite the translation of these novel technologies into the healthcare setting.
The increased prevalence of type 2 diabetes mellitus (T2DM) and life expectancy of diabetic patients fosters the worldwide prevalence of retinopathy and nephropathy, two major microvascular ...complications that have been difficult to treat with contemporary glucose-lowering medications. The gut microbiota (GM) has become a lively field research in the last years; there is a growing recognition that altered intestinal microbiota composition and function can directly impact the phenomenon of ageing and age-related disorders. In fact, human GM, envisaged as a potential source of novel therapeutics, strongly modulates host immunity and metabolism. It is now clear that gut dysbiosis and their products (e.g. p-cresyl sulfate, trimethylamine‑N‑oxide) dictate a secretory associated senescence phenotype and chronic low-grade inflammation, features shared in the physiological process of ageing (“inflammaging”) as well as in T2DM (“metaflammation”) and in its microvascular complications. This review provides an in-depth look on the crosstalk between GM, host immunity and metabolism. Further, it characterizes human GM signatures of elderly and T2DM patients. Finally, a comprehensive scrutiny of recent molecular findings (e.g. epigenetic changes) underlying causal relationships between GM dysbiosis and diabetic retinopathy/nephropathy complications is pinpointed, with the ultimate goal to unravel potential pathophysiological mechanisms that may be explored, in a near future, as personalized disease-modifying therapeutic approaches.
•Gut microbiota (GM) dysbiosis correlates with ageing and type 2 diabetes.•GM dictates an “inflammaging/metaflammation” scenario via immunosenescence.•GM-induced epigenetic changes may be paramount for microvascular diabetic complications.•GM dysbiosis may play chief roles on diabetic retinopathy progression.•Uremic toxins and microbial products contribute to diabetic nephropathy progression.
Disease staging involves the assessment of disease severity or progression and is used for treatment selection. In diabetic retinopathy, disease staging using a wide area is more desirable than that ...using a limited area. We investigated if deep learning artificial intelligence (AI) could be used to grade diabetic retinopathy and determine treatment and prognosis.
The retrospective study analyzed 9,939 posterior pole photographs of 2,740 patients with diabetes. Nonmydriatic 45° field color fundus photographs were taken of four fields in each eye annually at Jichi Medical University between May 2011 and June 2015. A modified fully randomly initialized GoogLeNet deep learning neural network was trained on 95% of the photographs using manual modified Davis grading of three additional adjacent photographs. We graded 4,709 of the 9,939 posterior pole fundus photographs using real prognoses. In addition, 95% of the photographs were learned by the modified GoogLeNet. Main outcome measures were prevalence and bias-adjusted Fleiss' kappa (PABAK) of AI staging of the remaining 5% of the photographs.
The PABAK to modified Davis grading was 0.64 (accuracy, 81%; correct answer in 402 of 496 photographs). The PABAK to real prognosis grading was 0.37 (accuracy, 96%).
We propose a novel AI disease-staging system for grading diabetic retinopathy that involves a retinal area not typically visualized on fundoscopy and another AI that directly suggests treatments and determines prognoses.
Purpose
This study aims to assess the effect of statins on progression from nonproliferative diabetic retinopathy (NPDR) to vision‐threatening diabetic retinopathy (VTDR), proliferative diabetic ...retinopathy (PDR) or diabetic macular edema (DME).
Methods
Two cohort studies using a U.S. medical claims database from 2002 to 2019 including NPDR patients 18 years or older. A risk factor analysis performed a time‐updating cox regression model assessing statin usage. A second new‐user active comparator design analysis replicating a previously published study. Main outcomes included a new diagnosis of VTDR (composite of either PDR or DME) or DME and PDR individually for the risk factor study and included additional outcomes of new DR, NPDR, vitreous hemorrhage (VH) and tractional retinal detachment (TRD) for the new user study.
Results
Risk factor analysis included 66 617 statin users with NPDR at baseline and 83 365 nonstatin users. Of these, 27 325 (18.2%) progressed to VTDR, 4086 (2.71%) progressed to PDR, and 22 750 (15.1%) progressed to DME. After multivariable analysis, no protective effect of statin use was found for progression to VTDR, PDR, or DME (HR = 1.01–3, p >0.33 for all comparisons). Replicated new user design analysis also showed no protective effect for statins on risk of development of DR (HR = 1.03, 95% CI: 0.99–1.07, p = 0.13), PDR (HR = 0.89, 95% CI: 0.79–1.02, p = 0.09), DME (HR = 0.94, 95% CI: 0.86–1.03, p = 0.21), VH (HR = 1.00, 95% CI: 0.86–1.16, p = 0.99), and TRD (HR = 1.11, 95% CI: 0.89–1.38, p = 0.36).
Conclusion
Statin use was found not to be protective for progression of DR regardless of study methodology. These results suggest that the specifics of the population studied rather than differing study methodology are important in assessing the effect of statins on DR progression.
Aims
To evaluate diabetic retinopathy (DR) data from across the SUSTAIN clinical trial programme.
Materials and methods
The SUSTAIN clinical trial programme evaluated the efficacy and safety of ...semaglutide, a glucagon‐like peptide‐1 analogue, for the treatment of type 2 diabetes (T2D). In SUSTAIN 6, a 2‐year, pre‐approval cardiovascular outcomes trial, semaglutide was associated with a significant increase in the risk of DR complications (DRC) vs placebo. DR data from across the SUSTAIN trials were evaluated, and post hoc analyses of the SUSTAIN 6 data were conducted. These included subgroup analyses to identify at‐risk patients and a mediation analysis with initial change in glycated haemoglobin (HbA1c; percentage‐points at week 16) as a covariate, to examine the role of the magnitude of reduction in HbA1c as an intermediate factor affecting risk of DRC.
Results
There was no imbalance in DR adverse events across the SUSTAIN 1 to 5 and Japanese trials. The majority of the effect with semaglutide vs placebo in SUSTAIN 6 may be attributed to the magnitude and rapidity of HbA1c reduction during the first 16 weeks of treatment in patients who had pre‐existing DR and poor glycaemic control at baseline, and who were treated with insulin.
Conclusions
Early worsening of DR is a known phenomenon associated with the rapidity and magnitude of improvement in glycaemic control with insulin; the DRC findings in SUSTAIN 6 are consistent with this. Guidance regarding the early worsening of DR is recommended with insulin. Similar recommendations may be appropriate for semaglutide.
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