Proliferative DR Research Articles

Causal relationships between blood metabolites and diabetic retinopathy: a two-sample Mendelian randomization study

BackgroundDiabetic retinopathy (DR) is a microvascular complication of diabetes, severely affecting patients’ vision and even leading to blindness. The development of DR is influenced by metabolic disturbance and genetic factors, including gene polymorphisms. The research aimed to uncover the causal relationships between blood metabolites and DR.MethodsThe two-sample mendelian randomization (MR) analysis was employed to estimate the causality of blood metabolites on DR. The genetic variables for exposure were obtained from the genome-wide association study (GWAS) dataset of 486 blood metabolites, while the genetic predictors for outcomes including all-stage DR (All DR), non-proliferative DR (NPDR) and proliferative DR (PDR) were derived from the FinnGen database. The primary analysis employed inverse variance weighted (IVW) method, and supplementary analyses were performed using MR-Egger, weighted median (WM), simple mode and weighted mode methods. Additionally, MR-Egger intercept test, Cochran’s Q test, and leave-one-out analysis were also conducted to guarantee the accuracy and robustness of the results. Subsequently, we replicated the MR analysis using three additional datasets from the FinnGen database and conducted a meta-analysis to determine blood metabolites associated with DR. Finally, reverse MR analysis and metabolic pathway analysis were performed.ResultsThe study identified 13 blood metabolites associated with All DR, 9 blood metabolites associated with NPDR and 12 blood metabolites associated with PDR. In summary, a total of 21 blood metabolites were identified as having potential causal relationships with DR. Additionally, we identified 4 metabolic pathways that are related to DR.ConclusionThe research revealed a number of blood metabolites and metabolic pathways that are causally associated with DR, which holds significant importance for screening and prevention of DR. However, it is noteworthy that these causal relationships should be validated in larger cohorts and experiments.

Autonomous screening for laser photocoagulation in fundus images using deep learning

BackgroundDiabetic retinopathy (DR) is a leading cause of blindness in adults worldwide. Artificial intelligence (AI) with autonomous deep learning algorithms has been increasingly used in retinal image analysis, particularly for...

Circulating metabolomic markers in association with overall burden of microvascular complications in type 1 diabetes

IntroductionDiabetic retinopathy (DR), diabetic kidney disease (DKD) and distal symmetric polyneuropathy (DSPN) share common pathophysiology and pose an additive risk of early mortality.Research design and methodsIn adults with type 1...

Metabolomic analysis of retinopathy stages and amputation in type 2 diabetes

BackgroundDiabetic retinopathy (DR) and limb amputation are frequent complications of diabetes that cannot always be explained by blood glucose control. Metabolomics is a science that is currently being explored in the search for biomarkers or profiles that identify clinical conditions of interest. ObjectiveThis study aimed to analyze, using a metabolomic approach, peripheral blood samples from type 2 diabetes mellitus (DM2) individuals, compared with those with diabetic retinopathy and limb amputation. MethodsThe sample consisted of 128 participants, divided into groups: control, DM2 without DR (DM2), non-proliferative DR (DRNP), proliferative DR (DRP), and DM2 amputated (AMP). Metabolites from blood plasma were classified by spectra using nuclear magnetic resonance (NMR), and the metabolic routes of each group using metaboanalyst. ResultsWe identified that the metabolism of phenylalanine, tyrosine, and tryptophan was discriminant for the DRP group. Histidine biosynthesis, on the other hand, was statistically associated with the AMP group. The results of this work consolidate metabolites such as glutamine and citrulline as discriminating for DRP, and the branched-chain amino acids as important for DR. ConclusionsThe results demonstrate the relationship between the metabolism of ketone bodies, with acetoacetate metabolite being discriminating for the DRP group and histidine being a significant metabolite in the AMP group, when compared to the DM2 group.

Retinal vasculature of different diameters and plexuses exhibit distinct vulnerability in varying severity of diabetic retinopathy.

To study the changes in vessel densities (VD) stratified by vessel diameter in the retinal superficial and deep vascular complexes (SVC/DVC) using optical coherence tomography angiography (OCTA) images obtained from people with diabetes and age-matched healthy controls. We quantified the VD based on vessel diameter categorized as <10, 10-20 and >20 μm in the SVC/DVC obtained on 3 × 3 mm2 OCTA scans using a deep learning-based segmentation and vascular graph extraction tool in people with diabetes and age-matched healthy controls. OCTA images obtained from 854 eyes of 854 subjects were divided into 5 groups: healthy controls (n = 555); people with diabetes with no diabetic retinopathy (DR, n = 90), mild and moderate non-proliferative DR (NPDR) (n = 96), severe NPDR (n = 42) and proliferative DR (PDR) (n = 71). Both SVC and DVC showed significant decrease in VD with increasing DR severity (p < 0.001). The largest difference was observed in the <10 μm vessels of the SVC between healthy controls and no DR (13.9% lower in no DR, p < 0.001). Progressive decrease in <10 μm vessels of the SVC and DVC was seen with increasing DR severity (p < 0.001). However, 10-20 μm vessels only showed decline in the DVC, but not the SVC (p < 0.001) and there was no change observed in the >20 μm vessels in either plexus. Our findings suggest that OCTA is able to demonstrate a distinct vulnerability of the smallest retinal vessels in both plexuses that worsens with increasing severity of DR.

Inner retinal oxygen delivery and metabolism in progressive stages of diabetic retinopathy

Previous studies have reported increased retinal venous oxygen saturation and decreased retinal blood flow and oxygen metabolism in non-proliferative diabetic retinopathy (NPDR). The current study aimed to determine alterations in both inner retinal oxygen delivery (DO2) and metabolism (MO2) in proliferative DR (PDR) as well as at stages of NPDR. A total of 123 subjects participated in the study and were categorized into five groups: non-diabetic control (N = 32), diabetic with no diabetic retinopathy (NDR, N = 34), mild NPDR (N = 31), moderate to severe NPDR (N = 17), or PDR (N = 9). Multi-modal imaging was performed to measure oxygen saturation and blood flow, which were used for derivation of DO2 and MO2. There were significant associations of groups with DO2 and MO2. DO2 was lower in PDR and not significantly different in NDR and NPDR stages as compared to the non-diabetic control group. MO2 was decreased in PDR and moderate to severe NPDR as compared to the control group, and not significantly reduced in NDR and mild NPDR. The findings demonstrate reductions in both DO2 and MO2 in PDR and MO2 in moderate to severe NPDR, suggesting their potential as biomarkers for monitoring progression and treatment of DR.

Wide-field imaging with smartphone based fundus camera: grading of severity of diabetic retinopathy and locating peripheral lesions in diabetic retinopathy

AimTo assess the performance of smartphone based wide-field retinal imaging (WFI) versus ultra-wide-field imaging (UWFI) for assessment of sight-threatening diabetic retinopathy (STDR) as well as locating predominantly peripheral lesions (PPL) of DR.MethodsIndividuals with type 2 diabetes with varying grades of DR underwent nonmydriatic UWFI with Daytona Plus camera followed by mydriatic WFI with smartphone-based Vistaro camera at a tertiary care diabetes centre in South India in 2021–22. Grading of DR as well as identification of PPL (DR lesions beyond the posterior pole) in the retinal images of both cameras was performed by senior retina specialists. STDR was defined by the presence of severe non-proliferative DR, proliferative DR or diabetic macular oedema (DME). The sensitivity and specificity of smartphone based WFI for detection of PPL and STDR was assessed. Agreement between the graders for both cameras was compared.ResultsRetinal imaging was carried out in 318 eyes of 160 individuals (mean age 54.7 ± 9 years; mean duration of diabetes 16.6 ± 7.9 years). The sensitivity and specificity for detection of STDR by Vistaro camera was 92.7% (95% CI 80.1–98.5) and 96.6% (95% CI 91.5–99.1) respectively and 95.1% (95% CI 83.5–99.4) and 95.7% (95% CI 90.3–98.6) by Daytona Plus respectively. PPL were detected in 89 (27.9%) eyes by WFI by Vistaro camera and in 160 (50.3%) eyes by UWFI. However, this did not translate to any significant difference in the grading of STDR between the two imaging systems. In both devices, PPL were most common in supero-temporal quadrant (34%). The prevalence of PPL increased with increasing severity of DR with both cameras (p < 0.001). The kappa comparison between the 2 graders for varying grades of severity of DR was 0.802 (p < 0.001) for Vistaro and 0.753 (p < 0.001) for Daytona Plus camera.ConclusionMydriatic smartphone-based widefield imaging has high sensitivity and specificity for detecting STDR and can be used to screen for peripheral retinal lesions beyond the posterior pole in individuals with diabetes.

Potential disease biomarkers for diabetic retinopathy identified through Mendelian randomization analysis.

Diabetic retinopathy (DR), a leading cause of vision loss, has limited options for effective prevention and treatment. This study aims to utilize genomics and proteomics data to identify potential drug targets for DR. We utilized plasma protein quantitative trait loci data from the Atherosclerosis Risk in Communities Study and the Icelandic Decoding Genetics Study for discovery and replication, respectively. Genetic associations with DR, including its subtypes, were derived from the FinnGen study. Mendelian Randomization (MR) analysis estimated associations between protein levels and DR risk, complemented by colocalization analysis to examine shared causal variants. Our MR analysis identified significant associations of specific plasma proteins with DR and proliferative DR (PDR). Elevated genetically predicted levels of WARS (OR = 1.16; 95% CI = 0.095-0.208, FDR = 1.31×10-4) and SIRPG (OR = 1.15; 95% CI = 0.071-0.201, FDR = 1.46×10-2) were associated with higher DR risk, while increased levels of ALDOC (OR = 1.56; 95% CI = 0.246-0.637, FDR = 5.48×10-3) and SIRPG (OR = 1.15; 95% CI = 0.068-0.208, FDR = 4.73×10-2) were associated with higher PDR risk. These findings were corroborated by strong colocalization evidence. Our study highlights WARS, SIRPG, and ALDOC as significant proteins associated with DR and PDR, providing a basis for further exploration in drug development. Additional studies are needed to validate these proteins as disease biomarkers across diverse populations.

THE CONTENT OF ENDOTHELIN-1 IN THE BLOOD PLASMA OF PATIENTS WITH DIABETIC RETINOPATHY ON THE BACKGROUND OF TYPE 2 DIABETES DEPENDING ON THE POLYMORPHIC VARIANTS OF THE MTHFR, MTRR AND MTR GENES

Backround. The vascular and extravascular microcirculation of the eye is a rich source of endothelin-1 (ET-1), which can contribute to abnormal retinal hemodynamics in diabetic retinopathy. In patients with type 2 diabetes mellitus (T2DM), an increase in the level of circulating ET-1 was found, and a positive correlation between its levels in the blood was found and degree of microangiopathy. Strengthens the development of endothelial dysfunction and microvascular complications, a high level of homocysteine, which occurs due to a genetically determined deficiency of enzymes of the folate cycle, determines in the body what, because homocysteine ​​causes a violation of the structure of endothelial cells.&#x0D; Aim: to study the ET-1 content in the blood plasma of patients with diabetic retinopathy against the background of type 2 diabetes, depending on the polymorphic variants of the MTHFR, MTRR and MTR genes, as an important pathogenetic pathway for the development of endothelial dysfunction.&#x0D; Materials and methods. The study included 83 patients (83 eyes) with T2DM, in whom non-proliferative and proliferative DR were found according to the results of an ophthalmological examination using the ETDRS scale. The control group (CG) included 35 people without diabetes, who were matched with patients by gender, age, and body mass index. Gene polymorphism was determined using real-time PCR on the automatic amplifier Gene Amp® PCR System 7500, the content of ET-1 was determined in blood plasma by the ELISA method.&#x0D; Conclusion. The SS genotype of the rs1801133 gene, the GG genotype of the rs1805087 gene, the AS polymorphism, and the SS genotype of the rs1801131 gene can be considered potential risk factors for the development of DR on the background of type 2 diabetes.&#x0D; The SS genotype of the rs1801133 gene was accompanied by a maximum 14-fold increase in ET-1 in patients with DR. The minor GG genotype of the rs1805087 gene was found only in patients with DR, and was characterized by the maximum content of ET-1. In the carriers of AS polymorphism of the rs1801131 gene, an 8-fold increase in ET-1 was found during the development of DR.&#x0D; The minor GG genotype of the rs1805087 gene was found only in patients with DR, and was characterized by the maximum content of ET-1. In the carriers of AS polymorphism of the rs1801131 gene, an 8-fold increase in ET-1 was found during the development of DR. The minor SS genotype of this gene was twice as common in patients, and the ET-1 content increased 5 times with the development of DR.&#x0D; The presence of ST polymorphism of the rs1801133 gene and the AA genotype of rs1801131 are probably factors that prevent the development of DR. The ST gene rs1801133 polymorphism was accompanied by the lowest ET-1 content. The AA genotype of the rs1801131 gene was 1.3 times less frequent, the ET-1 content in these individuals was the lowest and practically did not change during the development of DR.

Serum microRNA-126 expression as a biomarker of diabetic retinopathy

BackgroundDiabetic retinopathy (DR) is a microvascular complication of diabetes mellitus (DM). Diabetic retinopathy causes permanent blindness in the productive age group and has a multifactorial pathogenesis. MicroRNA-126 (miRNA-126) regulates the expression of the vascular endothelial growth factor (VEGF) gene at the post-transcriptional level, VEGF being an important angiogenic protein regulating inflammation in DR development. This study aimed to determine serum miRNA-126 expression as a biomarker in DM patients with DR. MethodsThis was a cross-sectional study involving 4 healthy persons and 21 type 2 DM patients. Subjects consisted of 4 groups: i) healthy controls, ii) DM patients without diabetic retinopathy (NDR), iii) DM patients with non-proliferative DR (NPDR) and iv) DM patients with proliferative DR (PDR). Venous blood was collected from subjects for miRNA-126 examination by real-time polymerase chain reaction (PCR). MiRNA-126 in each group was analyzed using the One Way Anova test and p&lt;0.05 was considered to be statistically significant. ResultsMean miRNA-126 expression was significantly decreased in PDR (1.86±1.03) and NPDR (1.01±0.43 ) groups when compared to healthy control (2.44±1.29) and NDR groups (2.15± 0.48) (p=0.027). MiRNA-126 values of less than 1.81 can differentiate NDR from the control group (sensitivity 83%, specificity 75%) and miRNA-126 of less than 1.56 can be used to predict NPDR when compared to the control group (sensitivity 86%, specificity 75%). ConclusionSerum miRNA-126 is a potential biomarker for screening of NPDR and NDR in type 2 DM patients, and could be considered a non-invasive diagnostic parameter.

Role of cystatin C in the detection of sight-threatening diabetic retinopathy in Asian Indians with type 2 diabetes

AimTo study the association between cystatin C and sight-threatening diabetic retinopathy (STDR) in Asian Indians with type 2 diabetes (T2DM). MethodsIn a cross-sectional study carried out at two tertiary centres in India in 2022, individuals with T2DM underwent clinical and ophthalmic assessments and estimation of serum cystatin C. Grading of DR was done by retina specialists. STDR was defined by the presence of severe non-proliferative DR (NPDR), proliferative DR (PDR) and/or diabetic macular edema. Receiver operating characteristic (ROC) curves were used to identify cystatin C cut-off value for detecting STDR. ResultsAmong 420 individuals with T2DM (mean age 56 ± 9 years; mean duration of diabetes 14.5 ± 7.9 years), 121 (24.1 %) had No-DR, 119 (28.3 %) had No-STDR and 200 (49.6 %) had STDR. Mean cystatin C level was significantly higher in individuals with STDR compared to those with no-STDR and No-DR (1.34 vs 1.06 vs 0.93 mg/L, p < 0.001). Cystatin C cut-off value ≥1.11 mg/L had a C statistic of 0.944 (95 % CI: 0.909–0.968, p < 0.001), 96.8 % sensitivity and 78.2 % specificity for detection of STDR. ConclusionElevated serum cystatin C was strongly associated with STDR and could possibly be used as a biomarker for screening for sight-threatening diabetic retinopathy.

Achromatic and chromatic contrast discrimination in patients with type 2 diabetes

Effects of type 2 diabetes on achromatic and chromatic contrast sensitivity (CS) are still controversial. In this study, we aimed to investigate CS in patients without diabetic retinopathy (no-DR) and in those with non-proliferative DR (NPDR) and proliferative DR (PDR) using psychophysical methods with transient and sustained achromatic stimuli and color patches. Achromatic CS was measured with the pulsed pedestal (PP) paradigm (7, 12, and 19 cd/m2) and pedestal-△-pedestal (P-△-P) paradigm (11.4, 18, and 28.5 cd/m2). A chromatic discrimination paradigm that assesses protan, deutan, and tritan color vision was adopted. Forty-two patients (no-DR n = 24, NPDR n = 12, PDR = 6; male n = 22, mean age = 58.1 y/o) and 38 controls (male n = 18, mean age = 53.4 y/o) participated. In patients, mean thresholds were higher than in controls and linear trends were significant in most conditions. For the PP paradigm, differences were significant in the PDR and NPDR groups in the 7 and 12 cd/m2 condition. For the P-△-P paradigm, differences were only significant in the PDR group in the 11 cd/m2 condition. Chromatic contrast loss was significant in the PDR group along the protan, deutan and tritan axes. The results suggest independent involvements of achromatic and chromatic CS in diabetic patients.

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

BackgroundDiabetic retinopathy (DR) is the microvascular ocular complication of diabetes mellitus (DM), which can lead to irreversible blindness and visual impairment if not properly treated. Tears can be collected non-invasively, and the compositions of tears could be the potential biomarkers for ocular diseases. Here we aimed to delineate the metabolomics signature in tears collected from Chinese type-2 DM patients with DR. MethodsThe metabolomics profiles of tear samples from 41 Chinese type-2 DM patients with DR and 21 non-diabetic subjects were determined by the untargeted liquid chromatography-mass spectrometry. The associated pathways of the differentially abundant metabolites were delineated, and the receiver operating characteristic curve analysis was conducted to identify the metabolites differentiating non-proliferative DR (NPDR) from proliferative DR (PDR). ResultsTotal 14 differentially abundant metabolites were identified between total DR and non-diabetic subjects, and 17 differentially abundant metabolites were found between the NPDR and PDR subjects. Moreover, total 18 differentially abundant metabolites were identified between the NPDR and PDR subjects with stratification in DR duration and blood glucose level. d-Glutamine and d-glutamate metabolism was significantly highlighted in the PDR group as compared to the non-diabetic group. For the predictive performance, azelaic acid combined with guanosine achieved the area under receiver operating characteristic curve of 0.855 in the comparison between NPDR and PDR groups. ConclusionThis study revealed the metabolomics changes in tear samples of DR patients. The metabolites in tears could be the potential biomarkers in the DR analysis.

Retinal age as a predictive biomarker of the diabetic retinopathy grade

ObjectiveTo apply artificial intelligence (AI) techniques, through deep learning algorithms, for the development and optimization of a system for predicting the age of a person based on a color retinography and to study a possible relationship between the evolution of retinopathy diabetes and premature ageing of the retina. MethodsA convolutional network was trained to calculate the age of a person based on a retinography. Said training was carried out on a set of retinographies of patients with diabetes previously divided into three subsets (training, validation and test). The difference between the chronological age of the patient and the biological age of the retina was defined as the retinal age gap. ResultsA set of 98,400 images was used for the training phase, 1000 images for the validation phase and 13,544 for the test phase.The retinal gap of the patients without DR was 0.609 years and that of the patients with DR was 1905 years (p < 0.001), with the distribution by degree of DR being: mild DR: 1541 years, moderate DR: 3017 years, DR severe: 3117 years and proliferative DR: 8583 years. ConclusionsThe retinal age gap shows a positive mean difference between diabetics with DR versus those without DR, and it increases progressively, according to the degree of DR. These results could indicate the existence of a relationship between the evolution of the disease and premature ageing of the retina.

Prevalence of diabetic retinopathy in patients with diabetes in Alexandria and North-West Delta, Egypt

PurposeThe purpose of this research was to estimate the prevalence of DR in Alexandria and the North-West Delta region.MethodsAll diabetic patients attending the general ophthalmology clinics (Group 1), diabetic internal medicine clinics (Group 2), or reached out in the local communities (Group 3) were eligible to participate. Fundus photographs were graded according to the Scottish DR grading system by three independent UK-certified graders. Adjudication by a consultant was done when needed.ResultsOut of 11,033 screened patients, 10,811 had a gradable fundus photograph in at least one eye and were included. The numbers of cases in groups 1, 2 and 3 were 3940, 2826, and 4045, respectively. Males represented 38.35% of the cases. Mean age was 55 ± 12.63. For the whole sample, groups 1, 2 and 3, the DR prevalence was 32.49, 46.4%, 29.13%, and 21.29%, respectively. The prevalence of proliferative DR (grade R4) was 6.16%, 11.83%, 5.02%, and 1.45%, respectively, and of referable maculopathy (Grade M2) was 19.95%, 31.42%, 15.92%, and 11.59%, respectively.In univariate analysis, older age, higher random blood glucose, and longer DM duration were associated with a higher risk of both DR and referable diabetic maculopathy. This association was maintained in multivariate analysis for the high random blood glucose level and the longer duration of DM (but not for the older age).ConclusionA significantly higher prevalence of DR, grades R4 and M2 was found in the hospital-recruited patients than in diabetics from the local communities.

Detection and Classification of Diabetic Retinopathy using Deep Learning

Detection of Diabetic Retinopathy at the early stages could significantly reduce the need for complicated and expensive surgeries. The availability of large datasets has fuelled research in this field. In this project, diabetic retinopathy is detected and classified into five stages: no DR, severe DR, Moderate DR, Proliferative DR, and mild DR. This is made possible with the help of various deep learning techniques. A trained model (ResNet-50 architecture) is used for the extraction of various features from the images. This model gives an accuracy of 0.47% in testing. The dataset used is the Aptos 2019 dataset which is available on Kaggle.

Proteomics profiling of vitreous humor reveals complement and coagulation components, adhesion factors, and neurodegeneration markers as discriminatory biomarkers of vitreoretinal eye diseases.

Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are leading causes of visual impairment and blindness in people aged 50 years or older in middle-income and industrialized countries. Anti-VEGF therapies have improved the management of neovascular AMD (nAMD) and proliferative DR (PDR), no treatment options exist for the highly prevalent dry form of AMD. To unravel the biological processes underlying these pathologies and to find new potential biomarkers, a label-free quantitative (LFQ) method was applied to analyze the vitreous proteome in PDR (n=4), AMD (n=4) compared to idiopathic epiretinal membranes (ERM) (n=4). Post-hoc tests revealed 96 proteins capable of differentiating among the different groups, whereas 118 proteins were found differentially regulated in PDR compared to ERM and 95 proteins in PDR compared to dry AMD. Pathway analysis indicates that mediators of complement, coagulation cascades and acute phase responses are enriched in PDR vitreous, whilst proteins highly correlated to the extracellular matrix (ECM) organization, platelet degranulation, lysosomal degradation, cell adhesion, and central nervous system development were found underexpressed. According to these results, 35 proteins were selected and monitored by MRM (multiple reaction monitoring) in a larger cohort of patients with ERM (n=21), DR/PDR (n=20), AMD (n=11), and retinal detachment (n=13). Of these, 26 proteins could differentiate between these vitreoretinal diseases. Based on Partial least squares discriminant and multivariate exploratory receiver operating characteristic (ROC) analyses, a panel of 15 discriminatory biomarkers was defined, which includes complement and coagulation components (complement C2 and prothrombin), acute-phase mediators (alpha-1-antichymotrypsin), adhesion molecules (e.g., myocilin, galectin-3-binding protein), ECM components (opticin), and neurodegeneration biomarkers (beta-amyloid, amyloid-like protein 2).

Residential greenness exposure and decreased prevalence of diabetic retinopathy: A nationwide analysis in China

ObjectiveDiabetic retinopathy (DR) is a leading cause of vision impairment and blindness among diabetics. We aimed to explore whether long-term exposure to residential greenness was beneficial to DR. Research design and methodsWe used data from a large-scale, cross-sectional screening survey conducted in 129 cities of 27 provincial regions of China from 2018 to 2021 among patients with diabetes. We measured residential greenness exposure as the 3-year average of annual maximum Normalized Difference Vegetation Index (NDVI) at a spatial resolution of 250 m. DR was assessed by ophthalmologists based on fundus photographs. The primary outcome was DR, and secondary outcome included DR severity status (i.e., nonproliferative and proliferative), hallmarks of retinal lesions and macular oedema. ResultsA total of 484,380 adult participants with diabetes were included in the current analysis, and 15.7% of them were diagnosed with DR. NDVI was inversely and linearly associated with DR prevalence, and an increment of 0.1 NDVI was associated with a 10% (9%–10%) decrease in DR prevalence. Significant and inverse associations were further found for nonproliferative and proliferative DR, hallmarks of lesions and macular oedema. The association between greenness and DR was stronger among participants who were older, obese, lived in the south, had longer duration of diabetes or did not take antidiabetic medications. ConclusionsThis large-scale nationwide study provides the first-hand epidemiological evidence on the associations of residential greenness with DR. Our findings highlight the importance of residential greenness in alleviating DR risk especially in an era of aging and urbanization.

Effect of vitamin E on oxidative stress indicated by serum malondialdehyde and Paroxonase level in type 2 diabetes mellitus with retinopathy

Background: Type 2 diabetes mellitus is a progressive condition in which the body becomes resistant to the normal effects of insulin and/or gradually loses the capacity to produce enough insulin the pancreas. Objectives: This case-control study was conducted to assess the effect of vitamin E on oxidative stress indicated by malondialdehyde and paronxanase 1 level on T2DM patients with retinopathy. Patients and Methods: Two equal groups each consisted of thirty patients; the 1st group was T2DM without retinopathy (control) and the 2nd one was T2DM with retinopathy (case). Results: There was statistically significant positive correlation Oppositely, paroxanase 1 level was statistically significantly negatively correlated with hydroperoxidase. As. Also, there was statistically significant increase on paroxanase 1 level after 3-month vitamin E application as an antioxidant among the T2DM with retinopathy group. Conclusion: Serum MDA levels were associated with DR stage, suggesting that oxidative stress play a significant role in DR progression. On the other hand, MDA levels were reduced and proliferative DR patients after vitamin E intake for 3 months.

Association of polymorphisms in the erythropoietin gene with diabetic retinopathy: a case–control study and systematic review with meta-analysis

BackgroundDiabetic retinopathy (DR) is characterized by ischemia, hypoxia, and angiogenesis. Erythropoietin (EPO), an angiogenic hormone, is upregulated in DR, and the association of EPO genetic variants with DR is still uncertain, as conflicting results have been reported. Therefore, we performed a case–control study followed by a meta-analysis to investigate whether the rs1617640, rs507392, and rs551238 polymorphisms in EPO gene are associated with DR.MethodsThe case–control study included 1042 Southern Brazilians with type 2 diabetes (488 without DR and 554 with DR). Eligible studies for the meta-analysis were searched from electronic databases up to June 1, 2021. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for five genetic inheritance models.ResultsThe minor alleles of the EPO polymorphisms had nearly the same frequency in all groups of patients (35%), and no association was detected with DR in the case–control study. The meta-analysis included 14 independent sets of cases and controls with 9117 subjects for the rs1617640 polymorphism and nine independent sets with more than 5000 subjects for the rs507392 and rs551238 polymorphisms. The G allele of the rs1617640 polymorphism was suggestively associated with DR under the dominant (OR = 0.82, 95% CI: 0.68–0.98), heterozygous additive (OR = 0.82, 95% CI: 0.69–0.97), and overdominant (OR = 0.88, 95% CI: 0.79–0.97) models. In the subgroup analyses, the G allele was also suggestively associated with proliferative DR (PDR), non-proliferative DR (NPDR), and DR (PDR + NPDR) among patients with type 1 diabetes (T1DM) or non-Asian ancestry. After considering the Bonferroni correction for multiple comparisons, the G allele remained associated with NPDR and DR in T1DM. Regarding the rs507392 and rs551238 polymorphisms, no association was found between these variants and DR.ConclusionOur findings provide additional support to EPO as a susceptibility gene for DR, with the rs1617640 polymorphism deserving further investigation.