The circular RNA circSLC16A10 alleviates diabetic retinopathy by improving mitochondrial function via the miR-761-5p/MFN2 axis.

It has been demonstrated that circular RNAs (circRNAs) are associated with the development of diabetic retinopathy (DR). Nevertheless, the function of circSLC16A10 in the development of DR remains unclear. In order to investigate the role of circSLC16A10, we employed cell and animal models of DR. An analysis of a public database revealed that hsa_circSLC16A10 was expressed at lower levels in DR patients than in diabetic patients without DR or healthy controls. Additionally, the level of hsa_circSLC16A10 was lower in high glucose (HG)-exposed ARPE-19 cells and diabetic mice. hsa_circSLC16A10 was observed to be mainly distributed in the cytoplasm. Moreover, overexpression of hsa_circSLC16A10 alleviated HG-induced endoplasmic reticulum stress and cell apoptosis in vitro. Furthermore, overexpression of hsa_circSLC16A10 ameliorated HG-induced mitochondrial dysfunction, as evidenced by improvements in mitochondrial structure and function. hsa_circSLC16A10 acted as a hsa-miR-761-5p sponge to increase MFN2 expression. MFN2 knockdown or hsa-miR-761-5p overexpression partially reversed the protective effect of hsa_circSLC16A10 in vitro. The protective effect of mmu_circSLC16A10 against DR was confirmed in an animal model of DR. These findings indicate that circSLC16A10 may regulate DR progression by improving mitochondrial function via the miR-761-5p/MFN2 axis.

Determinants of progression of diabetic retinopathy in pregnancy.

AIMS: To assess the rate of diabetic retinopathy (DR) progression in an Australian cohort and to identify the determinants of DR progression in pregnancy. METHODS: A total of 367 pregnancies of women with Type 1 or 2 diabetes mellitus attending King Edward Memorial Hospital, Western Australia, between June 2020 and July 2023 were included. These women were screened for the presence and severity of DR in the first trimester and/or at 28-32 weeks gestation via retinal imaging with a DRS camera. RESULTS: DR was seen in 121 (33 %) pregnancies at baseline and DR progression was seen in 62 (17 %) pregnancies. Only 11 (4 %) women with no baseline DR developed DR and none of these progressed to more than moderate non-proliferative DR. A total of 51 (42 %) women with baseline DR had DR progression. The presence of baseline DR was the only significant predictor for DR progression on multivariate analysis (OR 9.88 (4.43-22.07), p < 0.001). CONCLUSIONS: Women without DR at baseline are unlikely to progress to more severe forms of DR and usually do not require treatment. The presence of DR at baseline screening during pregnancy is a strong predictor of DR progression during pregnancy.

Mesenchymal stem cells-derived exosomes alleviate senescence of retinal pigment epithelial cells by activating PI3K/AKT-Nrf2 signaling pathway in early diabetic retinopathy.

Diabetic retinopathy (DR) is a major cause of vision loss and blindness in adults. Cellular senescence was involved in the pathogenesis of early-stage DR and is positively correlated with progression. Thus, our study aimed at exploring the effect and potential mechanism of Mesenchymal stem cells-derived exosomes (MSCs-EXOs) on Retinal Pigment Epithelial (RPE) cells senescence at an early stage of DR in vivo and in vitro. ARPE-19 cells were incubated in high glucose (HG) medium mixed with MSCs-EXOs to observe the changes in cell viability. Senescence-associated ß-galactosidase (SA-ß-gal) staining, western blot and qRT-PCR were used to assess the expression of senescence-related genes and antioxidant mediators. Quantitative Real-Time polymerase chain reaction (qRT-PCR), Optical coherence tomography (OCT) Hematoxylin and eosin (HE) staining and Electroretinogram (ERG) were respectively used to verify cellular senescence, the structure and function of the retina. Our findings demonstrated that MSCs-EXOs inhibited HG-induced senescence in ARPE-19 cells. Furthermore, MSCs-EXOs reduced HG-induced cell apoptosis and oxidative stress levels while promoting cell proliferation. Mechanistically, HG suppressed PI3K/AKT phosphorylation as well as nuclear factor erythroid 2-related factor 2 (Nrf2) expression along with its downstream target gene expression in ARPE-19 cells. However, MSCs-EXOs reversed these changes by alleviating cellular senescence while enhancing antioxidant activity. In line with our results in vitro, MSCs-EXOs significantly ameliorated hyperglycemia-induced senescence in DR mice by downregulating mRNA expression of P53, P21, P16, and SASP. Additionally, MSCs-EXOs improved the functional and structural integrity of the retina in DR mice. Our study revealed the protective effect of MSCs-EXOs on cellular senescence, offering new insights for the treatment of DR.

Relationship Between the Hemoglobin, Albumin, Lymphocyte Count, Platelet Count (HALP) Score and Type 2 Diabetes Retinopathy.

Purpose: To explore the correlation between hemoglobin, albumin, lymphocyte count, platelet count (HALP) score and type 2 diabetic retinopathy (DR). Methods: The study was conducted on 674 patients with type 2 diabetes (T2DM). According to the results of the fundus examination, they were divided into non-diabetic retinopathy group (NDR, n=388) and diabetic retinopathy group (DR, n=286). Collected patients baseline data, calculated HALP score, analyzed the correlation between HALP score and DR. Results: In all patients, male patients and female patients, the HALP score of the DR group was lower than that of the NDR group (P<0.001), and the HALP score was negatively correlated with the incidence of DR (P<0.05). HALP score was independent risk factors for DR, regardless of gender. In male patients, HALP score and DR had a linear relationship, but in female patients, HALP score and DR showed a nonlinear relationship, and HALP score was more sensitive to the onset of DR in male patients. The combined diagnostic model of HALP score, course of disease, SBP and BUN was used to diagnose DR, and it was found that the diagnostic value was the highest among male patients, with AUC of 0.761, sensitivity of 58.3% and specificity of 80.3%. Conclusion: HALP score was an independent risk factor for DR, attention should be paid to monitoring HALP score, especially in male T2DM patients. The accuracy of HALP score, disease course, SBP and BUN combined model diagnosis of DR was high, which can become a biological indicator for early screening of DR.

Insulin resistance in the retina: possible implications for certain ocular diseases.

Insulin resistance (IR) is becoming a worldwide medical and public health challenge as an increasing prevalence of obesity and metabolic disorders. Accumulated evidence has demonstrated a strong relationship between IR and a higher incidence of several dramatically vision-threatening retinal diseases, including diabetic retinopathy, age-related macular degeneration, and glaucoma. In this review, we provide a schematic overview of the associations between IR and certain ocular diseases and further explore the possible mechanisms. Although the exact causes explaining these associations have not been fully elucidated, underlying mechanisms of oxidative stress, chronic low-grade inflammation, endothelial dysfunction and vasoconstriction, and neurodegenerative impairments may be involved. Given that IR is a modifiable risk factor, it may be important to identify patients at a high IR level with prompt treatment, which may decrease the risk of developing certain ocular diseases. Additionally, improving IR through the activation of insulin signaling pathways could become a potential therapeutic target.

Effect of a self-care promoting program on engagement in self-care behaviors and health-related outcomes among persons with type 2 diabetes and diabetic retinopathy: A single-blind randomized controlled trial.

Background: Diabetic retinopathy (DR) is the most common microvascular complication of diabetes, leading to visual impairment and eventual blindness. Promoting self-care behaviors is crucial in controlling DR progression and preventing blindness. Objective: This study aimed to investigate the effects of a Self-Care Promoting Program (SCPP) on engagement in self-care behaviors, HbA1c levels, visual acuity (VA), severity of DR, and vision-related quality of life (VRQoL) among individuals with type 2 diabetes and DR. Methods: This study employed a single-blind randomized controlled trial design to compare SCPP with conventional diabetic care interventions (standard care). The SCPP was based on the Self-Care of Chronic Illness Theory, Self-efficacy theory, and the Association of Diabetic Care and Education Specialist (ADCES) guidelines incorporating health education, self-care maintenance, monitoring, and management skills training over 12 weeks. Ninety-eight participants were randomly allocated to the experimental or control group (n = 49 per group). While the experimental group received SCPP alongside standard care, the control group received standard care alone. Data collection occurred between May 2022 and March 2023 and included demographic information, the Self-Care of Diabetes Index questionnaire (SCODI), the self-care for diabetes eye care questionnaire (SCFDE), the impact of visual impairment questionnaire (IVI-Thai version), and retinal images for DR severity grading. Data analysis utilized descriptive statistics, Chi-Square tests, t-tests, and MANOVA. Results: Following 8 and 16 weeks of SCPP, the experimental group had significantly higher mean scores in engagement with self-care and eye-care behaviors compared to the control group (p <0.001). The highest scores were observed in self-care and eye-care confidence behaviors, followed by maintenance, monitoring, and management. Furthermore, HbA1c levels and VRQoL significantly decreased and were lower than those of the control group at week 16 (p <0.001 and p <0.05, respectively). However, there were no significant differences in VA, and DR severity increased in both groups by week 16. Conclusion: SCPP benefits individuals with DR, enhancing their confidence and ability to perform, monitor, and manage self-care behaviors. These strategies contribute to improved diabetes management, enhanced quality of life, and reduced DR-related blindness. Integrating SCPP into routine DR management is recommended, with nurses playing a pivotal role in overseeing and driving this integration, highlighting the critical role of nurses in managing this widespread global disease. Trial Registry Number: Thai Clinical Trials Registration (TCTR20230302002).

Mendelian randomization study and mediation analysis about the relation of inflammatory bowel disease and diabetic retinopathy: the further exploration of gut-retina axis.

Background: The concept of the gut-retinal axis proposed by previous scholars primarily focused on the relationship between intestinal microbiota and retinal diseases, and few further expanded the relationship between intestinal diseases and retinal diseases. To further substantiate the concept of the gut-retinal axis, we analyzed inflammatory bowel disease (IBD) and diabetic retinopathy (DR) using Mendelian randomization (MR), and use mediation analysis to further explore the potential substances that influence this causal relationship. Methods: The genome-wide association study's (GWAS) summary statistics for genetic variations were utilized in a Mendelian randomization (MR) investigation. GWAS data on IBD (including ulcerative colitis (UC), Crohn's disease (CD), and IBD) for non-Finnish Europeans (NFE) were sourced from published articles. In contrast, data on DR (including DR and diabetic maculopathy (DMP)) were obtained from FinnGen R9. The causal relationship has been investigated using inverse variance weighted (IVW), MR-Egger, and weighted median and sensitivity analysis was applied to verify the stability of the results. In addition, we applied mediation analysis to investigate whether circulating inflammatory proteins and plasma lipids played a mediating role, and calculated its effect ratio. Results: The causal relationship between IBD and DR was discovered by employing the inverse variance weighted (IVW) method and weighted median method. In forward MR, UC was significantly associated with lower risk of DR (IVW: OR=0.874; 95%CI= 0.835-0.916; P value= 1.28E-08) (Weighted median: OR=0.893; 95%CI= 0.837-0.954; P value= 7.40E-04). In reverse MR, it was shown that DR (IVW: OR=0.870; 95%CI= 0.828-0.914; P value= 2.79E-08)(Weighted median: OR=0.857; 95%CI= 0.801-0.916; P value= 6.40E-06) and DMP (IVW: OR=0.900; 95%CI= 0.865-0.937; P value= 3.34E-07)(Weighted median: OR=0.882; 95%CI= 0.841-0.924; P value= 1.82E-07) could reduce the risk of CD. What's more, DR is associated with a lower risk of IBD according to genetic prediction (IVW: OR=0.922; 95%CI= 0.873-0.972; P value= 0.002) (Weighted median: OR=0.924; 95%CI= 0.861-0.992; P value= 0.029). Fibroblast growth factor 21 (FGF21), phosphatidylcholine (PC), and triacylglycerol (TG) serve as mediators in these relationships. Conclusions: Our research offers novel insights and sources for investigating the gut-retina axis in the genetic relationship between IBD and DR. We discover four mediators and more about the association between the intestine and retinal disorders and provide more evidence for the gut-retinal axis theory.

Single-Cell RNA Sequencing Reveals Transcriptional Signatures and Cell-Cell Communication in Diabetic Retinopathy.

BACKGROUND: Diabetic retinopathy (DR) is a major cause of vision loss in workingage individuals worldwide. Cell-to-cell communication between retinal cells and retinal pigment epithelial cells (RPEs) in DR is still unclear, so this study aimed to generate a single-cell atlas and identify receptor‒ligand communication between retinal cells and RPEs. METHODS: A mouse single-cell RNA sequencing (scRNA-seq) dataset was retrieved from the GEO database (GSE178121) and was further analyzed with the R package Seurat. Cell cluster annotation was performed to further analyze cell‒cell communication. The differentially expressed genes (DEGs) in RPEs were explored through pathway enrichment analysis and the protein‒ protein interaction (PPI) network. Core genes in the PPI were verified by quantitative PCR in ARPE-19 cells. RESULTS: We observed an increased proportion of RPEs in STZ mice. Although some overall intercellular communication pathways did not differ significantly in the STZ and control groups, RPEs relayed significantly more signals in the STZ group. In addition, THBS1, ITGB1, COL9A3, ITGB8, VTN, TIMP2, and FBN1 were found to be the core DEGs of the PPI network in RPEs. qPCR results showed that the expression of ITGB1, COL9A3, ITGB8, VTN, TIMP2, and FBN1 was higher and consistent with scRNA-seq results in ARPE-19 cells under hyperglycemic conditions. CONCLUSION: Our study, for the first time, investigated how signals that RPEs relay to and from other cells underly the progression of DR based on scRNA-seq. These signaling pathways and hub genes may provide new insights into DR mechanisms and therapeutic targets.

Prostanoid signaling in retinal vascular diseases.

The vasculature of the retina is exposed to systemic and local factors that have the capacity to induce several retinal vascular diseases, each of which may lead to vision loss. Prostaglandin signaling has arisen as a potential therapeutic target for several of these diseases due to the diverse manners in which these lipid mediators may affect retinal blood vessel function. Previous reports and clinical practices have investigated cyclooxygenase (COX) inhibition by nonsteroidal anti-inflammatory drugs (NSAIDs) to address retinal diseases with varying degrees of success; however, targeting individual prostanoids or their distinct receptors affords more signaling specificity and poses strong potential for therapeutic development. This review offers a comprehensive view of prostanoid signaling involved in five key retinal vascular diseases: retinopathy of prematurity, diabetic retinopathy, age-related macular degeneration, retinal occlusive diseases, and uveitis. Mechanistic and clinical studies of these lipid mediators provide an outlook for therapeutic development with the potential to reduce vision loss in each of these conditions.

Artificial intelligence in diabetic retinopathy screening: from idea to a medical device in clinical practice.

With the growing significance of artificial intelligence in healthcare, new perspectives are emerging in primary care. Diabetic retinopathy, a microvascular complication of diabetes mellitus, often remains unnoticed until patient is facing complications. Artificial intelligence presents a promising solution that can enhance the accessibility of diabetic retinopathy screening for a broader range of patients. The key challenge lies in successfully integrating the solution into clinical practice, a demanding process with multiple phases to ensure the resulting medical device is effective and safe for patient use. Aireen software uses artificial intelligence to perform diabetic retinopathy screening on retinal images captured by optical fundus cameras. The medical device complies with European Medical Device Regulation 2017/745 and was introduced to the market in 2023. Collaboration between physicians and the development team played a crucial role throughout the entire lifecycle of the medical device. Physicians were engaged in defining the intended use of the medical device, risk analysis, data annotation for training and software validation, as well as throughout a clinical trial. A clinical trial was conducted on 1,274 patients with type 1 and type 2 diabetes mellitus, where Aireen medical device achieved a sensitivity of 94.0% and a specificity of 90.7% compared to the reference evaluation. This clinical trial confirmed the potential of Aireen to enhance the availability of diabetic retinopathy screening and early disease detection.

tRNA-derived fragment tRF-30 propels diabetes-induced retinal microvascular complications by regulating STAT3 signaling.

Transfer RNA-derived fragments (tRFs) represent a novel class of non-coding RNA transcripts that possess specific biological functions. However, the involvement of tRFs in retinal microvascular diseases remains poorly understood. In this study, we aimed to reveal whether modulation of tRF-30 expression could attenuate pathological retinal neovascular diseases. Our findings demonstrate a significant upregulation of tRF-30 expression levels in both in vivo models of diabetic retinopathy (DR) and in vitro endothelial sprouting models. Conversely, inhibition of tRF-30 expression suppressed the formation of abnormal neovascularization in the retina in vivo, while reducing the proliferation and migration activity of retinal vascular endothelial cells in vitro. We also found that tRF-30 modulates retinal neovascularization through the tRF-30/TRIB3/signal transducer and activated transcription 3 signaling pathway. Furthermore, we validated a significant upregulation of tRF-30 expression levels in the vitreous humor of DR patients, with high levels of both validity and specificity in diagnostic testing. Collectively, our findings highlight a pro-angiogenic role for tRF-30 in DR. Intervening in the tRF-30 signaling pathway may represent a promising prevention and treatment strategy for retinal angiogenesis.

Prediction of proliferative diabetic retinopathy using machine learning in Latino and non-Hispanic black cohorts with routine blood and urine testing.

PURPOSE: The objective was to predict proliferative diabetic retinopathy (PDR) in non-Hispanic Black (NHB) and Latino (LA) patients by applying machine learning algorithms to routinely collected blood and urine laboratory results. METHODS: Electronic medical records of 1124 type 2 diabetes patients treated at the Bronxcare Hospital eye clinic between January and December 2019 were analysed. Data collected included demographic information (ethnicity, age and sex), blood (fasting glucose, haemoglobin A1C [HbA1c] high-density lipoprotein [HDL], low-density lipoprotein [LDL], serum creatinine and estimated glomerular filtration rate [eGFR]) and urine (albumin-to-creatinine ratio [ACR]) test results and the outcome measure of retinopathy status. The efficacy of different machine learning models was assessed and compared. SHapley Additive exPlanations (SHAP) analysis was employed to evaluate the contribution of each feature to the model's predictions. RESULTS: The balanced random forest model surpassed other models in predicting PDR for both NHB and LA cohorts, achieving an AUC (area under the curve) of 83%. Regarding sex, the model exhibited remarkable performance for the female LA demographic, with an AUC of 87%. The SHAP analysis revealed that PDR-related factors influenced NHB and LA patients differently, with more pronounced disparity between sexes. Furthermore, the optimal cut-off values for these factors showed variations based on sex and ethnicity. CONCLUSIONS: This study demonstrates the potential of machine learning in identifying individuals at higher risk for PDR by leveraging routine blood and urine test results. It allows clinicians to prioritise at-risk individuals for timely evaluations. Furthermore, the findings emphasise the importance of accounting for both ethnicity and sex when analysing risk factors for PDR in type 2 diabetes individuals.

Screening for diabetic retinopathy with artificial intelligence: a real world evaluation.

AIM: Periodic screening for diabetic retinopathy (DR) is effective for preventing blindness. Artificial intelligence (AI) systems could be useful for increasing the screening of DR in diabetic patients. The aim of this study was to compare the performance of the DAIRET system in detecting DR to that of ophthalmologists in a real-world setting. METHODS: Fundus photography was performed with a nonmydriatic camera in 958 consecutive patients older than 18 years who were affected by diabetes and who were enrolled in the DR screening in the Diabetes and Endocrinology Unit and in the Eye Unit of ULSS8 Berica (Italy) between June 2022 and June 2023. All retinal images were evaluated by DAIRET, which is a machine learning algorithm based on AI. In addition, all the images obtained were analysed by an ophthalmologist who graded the images. The results obtained by DAIRET were compared with those obtained by the ophthalmologist. RESULTS: We included 958 patients, but only 867 (90.5%) patients had retinal images sufficient for evaluation by a human grader. The sensitivity for detecting cases of moderate DR and above was 1 (100%), and the sensitivity for detecting cases of mild DR was 0.84 ± 0.03. The specificity of detecting the absence of DR was lower (0.59 ± 0.04) because of the high number of false-positives. CONCLUSION: DAIRET showed an optimal sensitivity in detecting all cases of referable DR (moderate DR or above) compared with that of a human grader. On the other hand, the specificity of DAIRET was low because of the high number of false-positives, which limits its cost-effectiveness.

The Role of Widefield Optical Coherence Tomography Angiography in Assessing the Severity of Diabetic Retinopathy.

INTRODUCTION: Physicians need an accurate understanding of diabetic retinopathy (DR) severity to optimally manage patients. The aim of this prospective study is to correlate the severity of macular and peripheral retinal vascular abnormalities seen on widefield (WF) optical coherence tomography angiography (OCTA) with DR grading based on WF fundus photography. METHODS: The study included 150 eyes from 82 patients with treatment-naïve DR. All patients were imaged with WF fundus photography and swept-source WF OCTA. Quantitative and qualitative analyses of the foveal avascular zone (FAZ) size and shape, and measurement of capillary nonperfusion (CNP) areas, were performed from the OCTA images. The mixed-effects model was used to compare the DR grading from WF photography with the vascular changes seen on WF-OCTA, and Bonferroni correction was applied to the gradings. RESULTS: The mean [± standard deviation (SD)] age of patients was 55.5 (± 9.4) years. The WF-OCTA showed that an increasing size of the FAZ (from 0.442 (± 0.059) µm to 0.933 (± 0.086) µm) correlated with increasing severity of the DR (as determined with WF photography). The deep capillary plexus, FAZ size, and CNP areas in eyes with proliferative diabetic retinopathy (PDR) differed from those with mild nonproliferative diabetic retinopathy (NPDR) (p < 0.001). Most eyes with severe nonproliferative DR were found to have CNP in four quadrants [superficial capillary plexus (SCP) 60%, deep capillary plexus (DCP) 50%]. The WF-OCTA detected subtle neovascularization of the disc (NVD) in 7 eyes (10%) and neovascularization elsewhere (NVE) in 13 eyes (18%) that had been diagnosed with only moderate NPDR on WF photography. CONCLUSIONS: FAZ and CNP areas as measured by WF-OCTA correlate with DR severity. WF-OCTA can also detect subtle NVE and NVD that cannot be seen with fundus photography.

Peripheral retinal lesions in diabetic retinopathy on ultra-widefield imaging.

Peripheral retinal imaging plays a crucial role in the diagnosis, management, and prognosis of diabetic retinopathy (DR). Traditional fundus imaging techniques have limited coverage of the retina, resulting in missed peripheral lesions. The advent of ultra-widefield (UWF) imaging has revolutionized the assessment of the peripheral retina. UWF imaging modalities provide comprehensive visualization of the retina, enabling the detection of peripheral lesions without the need for mydriasis. Integration of UWF imaging with other modalities, including fluorescein angiography (FA), indocyanine green angiography, pseudocolor imaging, and fundus autofluorescence, further enhances our understanding of peripheral retinal lesions. UWF imaging has demonstrated improved detection of DR lesions and presumably more accurate management of DR compared to traditional fundus photography and dilated fundus examination. UWF-FA and UWF-optical coherence tomography angiography have emerged as valuable tools for assessing retinal and choroidal vascular abnormalities, nonperfusion areas, neovascularization, and microvascular abnormalities. The presence and increasing extent of predominantly peripheral lesions detected using UWF FA are associated with a higher risk of DR progression and proliferative DR. UWF imaging provides a comprehensive evaluation of DR severity, aiding in more accurate risk stratification and treatment decision-making. Overall, UWF imaging modalities have significantly advanced our understanding of peripheral retinal lesions in DR, facilitating early detection and targeted management for better visual outcomes.

The role of ultra-widefield imaging with navigated central and peripheral cross-sectional and three-dimensional swept source optical coherence tomography in ophthalmology: Clinical applications.

PURPOSE: To assess central and peripheral retinal and choroidal diseases using ultra-widefield (UWF) fundus imaging in combination with navigated central and peripheral cross-sectional and three-dimensional (3D) swept source optical coherence tomography (SS-OCT) scans. METHODS: Retrospective study involving 332 consecutive patients, with a nearly equal distribution of males and females. The mean age of patients was 52 years (range 18-92 years). Average refractive error was -3.80 D (range +7.75 to -20.75 D). RESULTS: The observations in this study demonstrate the efficacy of peripheral navigated SS-OCT in assessing various ocular conditions. The technology provides high-quality images of the peripheral vitreous, vitreoretinal interface, retina, and choroid, enabling visualization of vitreous floaters and opacities, retinal holes and tears, pigmented lesions, and peripheral retinal degenerations. 3D OCT scans enhance the visualization of these abnormalities and improve diagnostic and therapeutic decisions. CONCLUSION: Navigated central and peripheral cross-sectional and 3D SS-OCT scans offer significant complementary benefits in the assessment and management of retinal diseases. Their addition to UWF imaging provides a comprehensive view of central and peripheral ocular structures, aiding in early detection, precise anatomical measurements, and objective monitoring of disease progression. In addition, this technology serves as a valuable tool for patient education, a teaching tool for trainees, and documentation for medico-legal purposes.

Thyroid Hormone Signaling in Retinal Development and Function: Implications for Diabetic Retinopathy and Age-Related Macular Degeneration.

Thyroid Hormones (THs) play a central role in the development, cell growth, differentiation, and metabolic homeostasis of neurosensory systems, including the retina. The coordinated activity of various components of TH signaling, such as TH receptors (THRs) and the TH processing enzymes deiodinases 2 and 3 (DIO2, DIO3), is required for proper retinal maturation and function of the adult photoreceptors, Müller glial cells, and pigmented epithelial cells. Alterations of TH homeostasis, as observed both in frank or subclinical thyroid disorders, have been associated with sight-threatening diseases leading to irreversible vision loss i.e., diabetic retinopathy (DR), and age-related macular degeneration (AMD). Although observational studies do not allow causal inference, emerging data from preclinical models suggest a possible correlation between TH signaling imbalance and the development of retina disease. In this review, we analyze the most important features of TH signaling relevant to retinal development and function and its possible implication in DR and AMD etiology. A better understanding of TH pathways in these pathological settings might help identify novel targets and therapeutic strategies for the prevention and management of retinal disease.

Hybrid Explainable Artificial Intelligence Models for Targeted Metabolomics Analysis of Diabetic Retinopathy.

BACKGROUND: Diabetic retinopathy (DR) is a prevalent microvascular complication of diabetes mellitus, and early detection is crucial for effective management. Metabolomics profiling has emerged as a promising approach for identifying potential biomarkers associated with DR progression. This study aimed to develop a hybrid explainable artificial intelligence (XAI) model for targeted metabolomics analysis of patients with DR, utilizing a focused approach to identify specific metabolites exhibiting varying concentrations among individuals without DR (NDR), those with non-proliferative DR (NPDR), and individuals with proliferative DR (PDR) who have type 2 diabetes mellitus (T2DM). METHODS: A total of 317 T2DM patients, including 143 NDR, 123 NPDR, and 51 PDR cases, were included in the study. Serum samples underwent targeted metabolomics analysis using liquid chromatography and mass spectrometry. Several machine learning models, including Support Vector Machines (SVC), Random Forest (RF), Decision Tree (DT), Logistic Regression (LR), and Multilayer Perceptrons (MLP), were implemented as solo models and in a two-stage ensemble hybrid approach. The models were trained and validated using 10-fold cross-validation. SHapley Additive exPlanations (SHAP) were employed to interpret the contributions of each feature to the model predictions. Statistical analyses were conducted using the Shapiro-Wilk test for normality, the Kruskal-Wallis H test for group differences, and the Mann-Whitney U test with Bonferroni correction for post-hoc comparisons. RESULTS: The hybrid SVC + MLP model achieved the highest performance, with an accuracy of 89.58%, a precision of 87.18%, an F1-score of 88.20%, and an F-beta score of 87.55%. SHAP analysis revealed that glucose, glycine, and age were consistently important features across all DR classes, while creatinine and various phosphatidylcholines exhibited higher importance in the PDR class, suggesting their potential as biomarkers for severe DR. CONCLUSION: The hybrid XAI models, particularly the SVC + MLP ensemble, demonstrated superior performance in predicting DR progression compared to solo models. The application of SHAP facilitates the interpretation of feature importance, providing valuable insights into the metabolic and physiological markers associated with different stages of DR. These findings highlight the potential of hybrid XAI models combined with explainable techniques for early detection, targeted interventions, and personalized treatment strategies in DR management.

Serum neopterin and orexin-A levels in different stages of diabetic retinopathy.

CLINICAL RELEVANCE: Retinopathy is one of the most common microvascular complications of diabetes mellitus and is the leading cause of vision loss in the working middle-aged population. BACKGROUND: This study aimed to investigate the value of neopterin and orexin-A levels in patients with diabetes mellitus with different stages of diabetic retinopathy and without diabetic retinopathy and to compare those findings with results from healthy individuals without diabetes mellitus. METHODS: In total, 65 patients with type 2 diabetes mellitus and 22 healthy individuals without diabetes mellitus were enrolled in this prospective study. The participants were separated into four subgroups. The first subgroup included 25 patients without diabetic retinopathy, the second subgroup included 20 patients non-proliferative diabetic retinopathy, the third subgroup included 20 patients with proliferative diabetic retinopathy, and the fourth subgroup included 22 healthy individuals without diabetes mellitus as controls. Serum neopterin and orexin-A levels were analysed and compared among the groups. RESULTS: The age and gender of the participants between the four subgroups were not statistically significantly different (p > 0.05). The mean neopterin levels were significantly higher in patients included in the diabetes mellitus subgroups compared with the controls (p < 0.001). Neopterin levels significantly increased as diabetic retinopathy progressed within the diabetes mellitus subgroups. Mean orexin-A levels were significantly lower in the diabetes mellitus subgroups compared with the controls (p < 0.001); however, orexin-A levels were not significantly different within the diabetes mellitus subgroups (p > 0.05). CONCLUSION: Patients with diabetes mellitus have higher serum neopterin and lower serum orexin-A levels compared with healthy individuals without diabetes mellitus. Moreover, serum neopterin levels increase with progression of diabetic retinopathy.

Quantitative Biomarkers of Diabetic Retinopathy Using Ultra-Widefield Fluorescein Angiography.

Introduction: Diabetic retinopathy (DR) is a leading cause of blindness. Retinal imaging is an important tool to monitor the progression of DR. While seven-standard retinal fields are the traditional method for evaluating DR, ultra-widefield (UWF) imaging allows for improved visualization of peripheral areas of nonperfusion (NP) and neovascularization (NV), which could be used as biomarkers to monitor and predict progression of DR. Methods: A retrospective, cross-sectional study was conducted on 651 eyes from 363 patients diagnosed with type 1 or type 2 diabetes who received UWF-FA over 10 years. Fluorescein Angiography (FA) images were segmented, and surface areas of NP and NV were analyzed using multivariate regression to determine if biomarkers of DR and DR severity are associated with increasing areas of NP and NV. Results: Each additional year with a diagnosis of DR was associated with a 10.75 mm2 increase in the total NP (95% CI, 1.94-19.56; P = 0.02) and 7.87 mm2 increase in NP far-periphery (95% CI, 1.62-14.13; P = 0.01). A one-unit change in severity as defined by the Early Treatment of Diabetic Retinopathy Study (ETDRS) classification was associated with a 25.75 mm2 increase in total NP (95% CI, 11.16-40.33; P = 0.001), a 13.15 mm2 increase in mid-periphery NP (95% CI, 6.93-19.38; P < 0.0001), and a 12.29 mm2 increase in far-periphery NP (95% CI, 3.62-20.97; P = 0.01). Discussion: Biomarkers identified through UWF imaging such as total and regional areas of NP can be used to monitor and predict the progression of DR. This may provide a quantitative method for prognostication in patients with DR.