Biomarkers Of Diabetic Retinopathy Research Articles

Evaluating the role of serum cystatin C as a circulating biomarker of diabetic retinopathy from a rural Indian population

Abstract PURPOSE: This study aimed to evaluate serum cystatin C as a potential biomarker for diabetic retinopathy (DR) in a rural Indian population, addressing the urgent need for effective screening tools amidst rising diabetes prevalence. MATERIALS AND METHODS: A cross-sectional study recruited 112 patients with diabetes mellitus from Sambalpur, Odisha, India, categorized into groups with and without DR. Serum cystatin C levels were measured alongside clinical and demographic parameters, using established diagnostic methods. RESULTS: Patients with DR exhibited significantly higher serum cystatin C levels compared to those without DR (mean: 0.99 ± 0.50 mg/L vs. 0.80 ± 0.36 mg/L, P = 0.027). Adjusted analysis showed a notable association between higher cystatin C tertiles and DR (adjusted odd’s ratio: 7.65, 95% confidence interval: 1.49–39.08, P = 0.01), highlighting its potential as an independent predictor. CONCLUSION: Elevated serum cystatin C levels were strongly associated with the presence of DR, suggesting its utility as a biomarker for early identification and risk stratification in diabetic patients. Integration of cystatin C measurement into routine clinical practice may enhance DR screening and management strategies, offering potential benefits in reducing vision loss and improving patient outcomes. This study underscores the need for further longitudinal research to validate these findings and elucidate the temporal relationship between cystatin C levels and DR progression.

Retinal Vascular Permeability in Diabetic Subjects without Retinopathy Compared to Mild Diabetic Retinopathy and Healthy Controls

ObjectivesTo investigate retinal vascular permeability mapping as a potential biomarker for diabetic retinopathy in subjects with diabetes with no signs of retinopathy and with mild non-proliferative retinopathy. DesignThis is a case-control study. SubjectsParticipants included seven healthy controls, twenty-two subjects with diabetes mellitus and no clinical signs of retinopathy (DMnoDR), and seven subjects with mild non-proliferative diabetic retinopathy (NPDR). MethodsAll participants underwent routine retinal fluorescein videoangiography (FVA). Each FVA dataset was analyzed with the dynamic tracer kinetic model (DTKM) method to estimate five parameters: extraction fraction, blood flow, arrival time, transit time, and rate constant defined via adiabatic solution. The DTKM method was based on indicator dilution theory, including sequential use of two prominent kinetic models: the plug flow model and the adiabatic approximation to the tissue homogeneity model. Main Outcome MeasuresExtraction fraction (E), i.e., the fluorescein dye leakage measured during one pass through surrounding retinal tissue, is extracted via DTKM method and directly relates to retinal vascular permeability. Thus, E represents the pre-clinical biomarker, retinal vascular permeability. ResultsThe three diagnostic groups were found to have significantly different permeability (p = 0.003). Despite having no clinical signs of retinopathy, the mean rank of average vascular extraction fractions (E) was significantly higher in DMnoDR subjects compared to healthy controls (p = 0.04), as was the mean rank of E for mild NPDR subjects (p = 0.002). The average E for mild NPDR, DMnoDR, and control subjects was 0.1 ± 0.04, 0.07 ± 0.04, and 0.04 ± 0.01, respectively. ConclusionsThe vascular permeability extracted from FVA datasets using the DTKM method is a promising biomarker for detecting preclinical retinal pathology in patients with diabetes. Longitudinal studies are ongoing to explore the ability of this biomarker to distinguish those subjects with diabetes who will progress to clinically apparent retinopathy from those who will not.

An ultra-sensitive suboptimal protospacer adjacent motif enhanced rolling circle amplification assay based on CRISPR/Cas12a for detection of miR-183.

MicroRNAs (miRNAs) have been recognized as promising diagnostic biomarkers for Diabetic Retinopathy (DR) due to their notable upregulation in individuals with the condition. However, the development of highly sensitive miRNAs assays for the rapid diagnosis of DR in clinical settings remains a challenging task. In this study, we introduce an enhanced CRISPR/Cas12a assay, leveraging suboptimal PAM (sPAM)-mediated Cas12a trans-cleavage in conjunction with rolling circle amplification (RCA). sPAM was found to perform better than canonical PAM (cPAM) in the detection of Cas12a-mediated ssDNA detection at low concentrations and was used instead of canonical PAM (cPAM) to mediate the detection. The parameters of reactions have also been optimized. In comparison with cPAM, sPAM has higher sensitivity in the detection of ssDNA at concentrations lower than 10 pM by Cas12a. By replacing cPAM with sPAM in the padlock template of RCA, ultra-high sensitivity for miR-183 detection is achieved, with a detection limit of 0.40 aM. within 25min and a linear range spanning from 1 aM. to 1 pM. Our assay also exhibits exceptional specificity in detecting miR-183 from other miRNAs. Furthermore, the applicability of our assay for the sensitive detection of miR-183 in clinical serum samples is also validated. This study introduces a groundbreaking assay with excellent performance through a simple modification, which not only addresses existing diagnostic challenges, but also opens exciting new avenues for clinical diagnosis in the realm of DR.

Choroidal thickness in type 2 diabetes mellitus patients using spectral domain optical coherence tomography

To measure the choroidal thickness in patients with type 2 diabetes mellitus and its comparison to healthy age-matched individuals.This prospective comparative study conducted at departments of Ophthalmology, Shri B.M. Patil Medical College, Hospital and Research Centre, Vijayapura. Study included 192 patients, 96 with diabetes and 96 age-matched controls. Data acquired comprised demographics, a thorough eye examination, fundus photography and spectral domain optical coherence tomography measurements of choroidal thickness using enhanced depth imaging.Mean age was 60.17±7.727 years with male predominance in both cases and controls. The mean duration of diabetes was 5.67±3.39 years. Positive correlation was noted between duration of diabetes and severity of retinopathy (p = 0.001). 21 patients did not have any evidence of diabetic retinopathy, while 75 patents had features of non-proliferative diabetic retinopathy, of which (31) had mild, (21) moderate, (12) severe and (11) with proliferative diabetic retinopathy. Mean choroidal thickness of controls was 327.308±18.945 microns, as compared to thinner choroids 295±15.082 microns in cases without retinopathy and 271 ± 36.122, 242 ±30.048, 193±15.748 microns in mild, moderate, severe non-proliferative diabetic retinopathy respectively and 191.492± 23.834 microns in proliferative diabetic retinopathy. Statistically significant differences were noted on comparing choroidal thickness between controls and cases (p = 0.001).Choroidal thickness was maximum in control group with a p value of <0.001, while cases showed overall thinner choroids with increasing severity of retinopathy. Thinnest choroids were observed in patient with proliferative diabetic retinopathy. Choroidal thickness can be used as a non-invasive prognostic bio marker for diabetic retinopathy.

Assessment of Serum MicroRNA-1281 Expression as a Circulating Biomarker of Diabetic Retinopathy in Patients with Type 2 Diabetes

Assessment of Serum MicroRNA-1281 Expression as a Circulating Biomarker of Diabetic Retinopathy in Patients with Type 2 Diabetes

Detection of a Diagnostic Model and Comprehensive Examination of Diabetic Retinopathy Utilizing Genes Linked to Endoplasmic Reticulum Stress.

The aim of this study was to reveal the biological functionalities associated with endoplasmic reticulum stress (ERS)-related genes (ERSGs) in the context of diabetic retinopathy (DR). Differentially expressed genes (DEGs) within the DR group and the Control group were identified and then integrated with ERSGs. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) methodologies were used to investigate potential biological mechanisms. A diagnostic model for ERS and a nomogram were formulated based on biomarkers selected through the Least Absolute Shrinkage and Selection Operator method. The diagnostic efficacy of this model was thoroughly evaluated. ERS-associated subtypes were identified, and the Single-Sample GSEA (ssGSEA) and CIBERSORT algorithms were used to assess immune infiltration. We identified 10 ERS-related DEGs (ERSRDEGs) within the DR Group. Subsequently, a diagnostic model was constructed based on 5 ERS genes, namely CCND1, IGFBP2, TLR4, TXNIP, and VIM. The validation analysis demonstrated the commendable diagnostic performance of the model. Analysis of the ssGSEA immune characteristics revealed a positive correlation in the DR group between myeloid-derived suppressor cells (MDSC), regulatory T cells (Tregs), and CCND1 TXNIP. Furthermore, a significant negative correlation was observed between central memory CD4 T cells and CCND1. In the context of CIBERSORT, the results indicated a positive correlation between macrophages and IGFBP2, as well as Tregs and IGFBP2 in the DR group. Notably, a conspicuous negative correlation was identified between resting mast cells and IGFBP2. The present study provides novel diagnostic biomarkers for DR from an ERS perspective.

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

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. 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. 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). 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.

Statistical Methods for Best and Worst Eye Measurements.

The focus is often on the best and worst eyes to detect early predictive and non-invasive biomarkers of diabetic retinopathy. Typically, such data have been dealt with in a case-control setting, which applies two-sample tests and ignores the correlation between the fellow eyes. Practitioners are mostly unaware that such measurements hide the labels of the fellow eyes, which rules out standard tools, such as paired t or signed-rank tests. This report discusses the problems with such data on best and worst eye measurements, and illustrates alternative paired tests for equality of means or locations using a case-control dataset. This report illustrates that methods which ignore the correlation between fellow eyes result in grossly conservative tests. A battery of Z-tests which consider this correlation can resolve this issue. This finding emphasizes the importance of selecting an appropriate control group for the detection of possible markers. Further, it cites an example to show that using data from fellow eyes and adjusting for their correlation may not always be the best option, contrary to common perception.

Advances in Structural and Functional Retinal Imaging and Biomarkers for Early Detection of Diabetic Retinopathy.

Diabetic retinopathy (DR), a vision-threatening microvascular complication of diabetes mellitus (DM), is a leading cause of blindness worldwide that requires early detection and intervention. However, diagnosing DR early remains challenging due to the subtle nature of initial pathological changes. This review explores developments in multimodal imaging and functional tests for early DR detection. Where conventional color fundus photography is limited in the field of view and resolution, advanced quantitative analysis of retinal vessel traits such as retinal microvascular caliber, tortuosity, and fractal dimension (FD) can provide additional prognostic value. Optical coherence tomography (OCT) has also emerged as a reliable structural imaging tool for assessing retinal and choroidal neurodegenerative changes, which show potential as early DR biomarkers. Optical coherence tomography angiography (OCTA) enables the evaluation of vascular perfusion and the contours of the foveal avascular zone (FAZ), providing valuable insights into early retinal and choroidal vascular changes. Functional tests, including multifocal electroretinography (mfERG), visual evoked potential (VEP), multifocal pupillographic objective perimetry (mfPOP), microperimetry, and contrast sensitivity (CS), offer complementary data on early functional deficits in DR. More importantly, combining structural and functional imaging data may facilitate earlier detection of DR and targeted management strategies based on disease progression. Artificial intelligence (AI) techniques show promise for automated lesion detection, risk stratification, and biomarker discovery from various imaging data. Additionally, hematological parameters, such as neutrophil-lymphocyte ratio (NLR) and neutrophil extracellular traps (NETs), may be useful in predicting DR risk and progression. Although current methods can detect early DR, there is still a need for further research and development of reliable, cost-effective methods for large-scale screening and monitoring of individuals with DM.

Ferrous ascorbate as a potential biomarker for diabetic retinopathy: a vitreous humour metabolomics study

BackgroundThis study aimed to explore differences in vitreous humour metabolites and metabolic pathways between patients with and without diabetic retinopathy (DR) and identify potential metabolite biomarkers.MethodsClinical data and vitreous fluid samples were collected from 125 patients (40 without diabetes, 85 with DR). The metabolite profiles of the vitreous fluid samples were analysed using ultra-high performance liquid chromatography, Q-Exactive mass spectrometry, and multivariate statistical analysis. A machine learning model based on Least Absolute Shrinkage and Selection Operator Regularized logistic regression was used to build a risk scoring model based on selected metabolite levels. Candidate metabolites were regressed to glycated haemoglobin levels by a logistic regression model.ResultsTwenty differential metabolites were identified between the DR and control groups and were significantly enriched in five Kyoto Encyclopedia of Genes and Genomes pathways (arginine biosynthesis; tricarboxylic acid cycle; alanine, aspartate, and glutamate metabolism; tyrosine metabolism; and D-glutamate metabolism). Ferrous ascorbate significantly contributes to poorer glycaemic control outcomes, offering insights into potential new pathogenic pathways in DR.ConclusionsDisorders in the metabolic pathways of arginine biosynthesis, tricarboxylic acid cycle, alanine, aspartate, glutamate metabolism, tyrosine metabolism, and D-glutamate metabolism were associated with DR. Risk scores based on vitreous fluid metabolites can be used for the diagnosis and management of DR. Ferrous ascorbate can provide insights into potential new pathogenic pathways for DR.

Association Between Triglyceride-Glucose Index and Waist-To-Hip Ratio with Type 2 Diabetic Retinopathy in the Chinese Population: A Cross-Sectional Study

ABSTRACT Background The triglyceride-glucose (TyG) index serves as a convenient indicator of insulin resistance, which has been demonstrated to be associated with diabetic retinopathy(DR). However, the relationship between TyG-WHR, a novel index combining TyG with the central obesity indicator WHR, and retinopathy in patients with type 2 diabetes remains unclear. Therefore, this study aims to investigate the correlation between TyG-WHR and DR in adult patients with type 2 diabetes. Methods This cross-sectional study included 1702 patients with T2DM. Logistic regression analysis was performed to examine the associations between TyG-WHR and DR. Additionally, the receiver operating characteristic curve (ROC curve) was utilized to assess the predictive efficacy of TyG-WHR for DR. Results Patients in higher TyG-WHR quartiles demonstrated an increased presence of DR, and TyG-WHR increased with the severity of DR. Moreover, TyG-WHR remained significantly associated with a higher odds ratio (OR) for DR (OR 1.223, 95% confidence interval [CI] 1.078–1.387, p < 0.05) after multivariate adjustment. Additionally, receiver operating characteristic curve analysis indicated that the optimal cutoff value for TyG-WHR in predicting DR presence was 8.8983, with a sensitivity of 61.00%, specificity of 48.50%, and area under the curve (AUC) of 0.555. Conclusions In patients with T2DM, TyG-WHR was significantly elevated in those with DR and independently associated with an increased risk of DR presence in Chinese patients. This implies that TyG-WHR could potentially serve as a valuable and dependable biomarker for DR, underscoring the importance of giving greater consideration to T2DM patients with elevated TyG-WHR to effectively prevent and mitigate the onset of DR and associated adverse health outcomes.

Exploring the Associated Genetic Causes of Diabetic Retinopathy as a Model of Inflammation in Retinal Diseases.

To investigate potential biomarkers and biological processes associated with diabetic retinopathy (DR) using transcriptomic and proteomic data. The OmicsPred PheWAS application was interrogated to identify genes and proteins associated with DR and diabetes mellitus (DM) at a false discovery rate (FDR)-adjusted p-value of <0.05 and also <0.005. Gene Ontology PANTHER analysis and STRING database analysis were conducted to explore the biological processes and protein interactions related to the identified biomarkers. The interrogation identified 49 genes and 22 proteins associated with DR and/or DM; these were divided into those uniquely associated with diabetic retinopathy, uniquely associated with diabetes mellitus, and the ones seen in both conditions. The Gene Ontology PANTHER and STRING database analyses highlighted associations of several genes and proteins associated with diabetic retinopathy with adaptive immune response, valyl-TRNA aminoacylation, complement activation, and immune system processes. Our analyses highlight potential transcriptomic and proteomic biomarkers for DR and emphasize the association of known aspects of immune response, the complement system, advanced glycosylation end-product formation, and specific receptor and mitochondrial function with DR pathophysiology. These findings may suggest pathways for future research into novel diagnostic and therapeutic strategies for DR.

APAF1 Silencing Ameliorates Diabetic Retinopathy by Suppressing Inflammation, Oxidative Stress, and Caspase-3/GSDME-Dependent Pyroptosis.

Diabetic retinopathy (DR) can cause permanent blindness with unstated pathogenesis. We aim to find novel biomarkers and explore the mechanism of apoptotic protease activating factor 1 (APAF1) in DR. Differential expression genes (DEGs) were screened based on GSE60436 dataset to find hub genes involved in pyroptosis after comprehensive bioinformatics analysis. DR mice model was constructed by streptozotocin injection. The pathological structure of retina was observed using hematoxylin-eosin staining. The enzyme-linked immunosorbent assay was applied to assess inflammatory factors, vascular endothelial growth factor (VEGF), and oxidative stress. The mRNA and protein expression levels were detected using quantitative real-time polymerase-chain reaction and Western blot. Cell counting kit and flow cytometry were employed to detect proliferation and apoptosis in high glucose-induced ARPE-19 cells. Total 71 pyroptosis-related DEGs were screened. BIRC2, CXCL8, APAF1, PPARG, TP53, and CYCS were identified as hub genes of DR. APAF1 was selected as a potential regulator of DR, which was up-regulated in DR mice. APAF1 silencing alleviated retinopathy and inhibited pyroptosis in DR mice with decreased levels of inflammatory factors, VEGF, and oxidative stress. Moreover, APAF1 silencing promoted proliferation while inhibiting apoptosis and caspase-3/GSDME-dependent pyroptosis with a decrease in TNF-α, IL-1β, IL-18, and lactate dehydrogenase in high glucose-induced ARPE-19 cells. Additionally, caspase-3 activator reversed the promotion effect on proliferation and inhibitory effect on apoptosis and pyroptosis after APAF1 silencing in high glucose-induced ARPE-19 cells. APAF1 is a novel biomarker for DR and APAF1 silencing inhibits the development of DR by suppressing caspase-3/GSDME-dependent pyroptosis.

Optical Fiber Ball Resonator Biosensor as a Platform for Detection of Diabetic Retinopathy Biomarkers in Tears

Optical Fiber Ball Resonator Biosensor as a Platform for Detection of Diabetic Retinopathy Biomarkers in Tears

Two ferroptosis-specific expressed genes NOX4 and PARP14 are considered as potential biomarkers for the diagnosis and treatment of diabetic retinopathy and atherosclerosis

ObjectivesBoth Diabetic retinopathy (DR) and Atherosclerosis (AS) are common complications in patients with diabetes, and they share major pathophysiological similarities and have a common pathogenesis. Studies performed to date have demonstrated that ferroptosis plays a vital part in the occurrence and development of DR and AS, but its mechanism in the two diseases remains poorly understood.MethodsDR Chip data (GSE60436 and GSE102485) and AS chip data (GSE100927 and GSE57691) were obtained from the Gene Expression Omnibus (GEO) database. The screening of the differential expression genes (DEGs) was analyzed using the limma package, and the genes related to ferroptosis were obtained from the FerrDb V2 database. Two key genes (NOX4 and PARP14) were identified through external datasets validation and receiver operating characteristic (ROC) curve analysis. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) were used to conduct a functional enrichment analysis, and miRNA-mRNA networks were established. The CIBERSORT algorithm was applied to identify the immune cell infiltration between the disease group and control group. Next, the correlations between key genes and infiltrating immune cells were investigated by the Spearman method. Finally, the correlation between 2 key genes and ferroptosis markers was confirmed.ResultsNine ferroptosis differentially expressed genes (DE-FRGs) between DR and AS were identified in this study. NOX4 and PARP14 were selected as key genes for further analysis by external datasets and ROC curve analysis. The key genes NOX4, PARP14 and their correlated genes (such as CYBA, NOX1, NOX3, CYBB, PARP9, PARP10, and PARP15) are mainly enriched in oxidoreductase activity, protein ADP-ribosylation, superoxide metabolic process, reactive oxygen species metabolic process, PID pathway, and VEGFA-VEGFR2 pathway. A miRNA-mRNA network was constructed, and we got 12 miRNAs correlated with the target gene NOX4, 38 miRNAs correlated with the target gene PARP14. Three common miRNAs (hsa-miR-1-3p, hsa-miR-129-2-3p, and hsa-miR-155-5p) were observed in the network. Immune infiltration analysis displayed that activated B cell, MDSC, and Type 17 T helper cell are the common immune cells involved in the immune infiltration process of DR and AS. The results revealed that there are significant correlations between two key genes and most ferroptosis marker genes no matter in DR or AS.ConclusionFerroptosis-related genes NOX4 and PARP14 may be common biomarkers of DR and AS. Both were associated with immune infiltration in patients with DR and AS. Our data provide a theoretical basis for the early diagnosis and immunotherapy of the two diseases.

Proteomic analysis of diabetic retinopathy identifies potential plasma-protein biomarkers for diagnosis and prognosis.

To identify molecular pathways and prognostic- and diagnostic plasma-protein biomarkers for diabetic retinopathy at various stages. This exploratory, cross-sectional proteomics study involved plasma from 68 adults, including 15 healthy controls and 53 diabetes patients for various stages of diabetic retinopathy: non-diabetic retinopathy, non-proliferative diabetic retinopathy, proliferative diabetic retinopathy and diabetic macular edema. Plasma was incubated with peptide library beads and eluted proteins were tryptic digested, analyzed byliquid chromatography-tandem mass-spectrometry followed by bioinformatics. In the 68 samples, 248 of the 731 identified plasma-proteins were present in all samples. Analysis of variance showed differential expression of 58 proteins across the five disease subgroups. Protein-Protein Interaction network (STRING) showed enrichment of various pathways during the diabetic stages. In addition, stage-specific driver proteins were detected for early and advanced diabetic retinopathy. Hierarchical clustering showed distinct protein profiles according to disease severity and disease type. Molecular pathways in the cholesterol metabolism, complement system, and coagulation cascade were enriched in patients at various stages of diabetic retinopathy. The peroxisome proliferator-activated receptor signaling pathway and systemic lupus erythematosus pathways were enriched in early diabetic retinopathy. Stage-specific proteins for early- and advanced diabetic retinopathy as determined herein could be 'key' players in driving disease development and potential 'target' proteins for future therapies. For type 1 and 2 diabetes mellitus, the proteomic profiles were especially distinct during the early disease stage. Validation studies should aim to clarify the role of the detected molecular pathways, potential biomarkers, and potential 'target' proteins for future therapies in diabetic retinopathy.

Multiplatform tear proteomic profiling reveals novel non-invasive biomarkers for diabetic retinopathy.

To investigate a comprehensive proteomic profile of the tear fluid in patients with diabetic retinopathy (DR) and further define non-invasive biomarkers. A cross-sectional, multicentre study that includes 46 patients with DR, 28 patients with diabetes mellitus (DM), and 30 healthy controls (HC). Tear samples were collected with Schirmer strips. As for the discovery set, data-independent acquisition mass spectrometry was used to characterize the tear proteomic profile. Differentially expressed proteins between groups were identified, with gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes enrichment analysis further developed. Classifying performance of biomarkers for distinguishing DR from DM was compared by the combination of three machine-learning algorithms. The selected biomarker panel was tested in the validation cohort using parallel reaction monitoring mass spectrometry. Among 3364 proteins quantified, 235 and 88 differentially expressed proteins were identified for DR when compared to HC and DM, respectively, which were fundamentally related to retina homeostasis, inflammation and immunity, oxidative stress, angiogenesis and coagulation, metabolism, and cellular adhesion processes. The biomarker panel consisting of NAD-dependent protein deacetylase sirtuin-2 (SIR2), amine oxidase [flavin-containing] B (AOFB), and U8 snoRNA-decapping enzyme (NUD16) exhibited the best diagnostic performance in discriminating DR from DM, with AUCs of 0.933 and 0.881 in the discovery and validation set, respectively. Tear protein dysregulation is comprehensively revealed to be associated with DR onset. The combination of tear SIR2, AOFB, and NUD16 can be a novel potential approach for non-invasive detection or pre-screening of DR. Chinese Clinical Trial Registry Identifier: ChiCTR2100054263. https://www.chictr.org.cn/showproj.html?proj=143177 . Date of registration: 2021/12/12.

MicroRNA-150 (miR-150) as a Potential Biomarker for Diabetic Retinopathy

Diabetic retinopathy (DR) is a known chronic complication of diabetes mellitus and is one of the leading causes of visual impairment. The chronic inflammation associated with DR poses large risks not only for the vasculature but also for the surrounding neuronal tissue. Potential biomarkers, especially those surrounding microRNAs (miRNAs), have been proposed to indicate the progression of DR. Levels of certain miRNAs have been shown to be either down or upregulated in type 1 diabetes patients and have shown correlations with specific types of DR. MicroRNA-150 (miR-150) has also been shown to have protective effects on cells in hypoxic environments, but when downregulated, miR-150 actually induces apoptosis. And, it has been shown to be downregulated in patients with type 1 and type 2 diabetes as well as patients with obesity. We hypothesize then that the levels of miR-150 from a peripheral blood sample should be indicative of the progression of DR and may be used for potential early intervention. In this project, we assessed miR-150 levels in the peripheral blood mononuclear cells (MNCs) of individuals with different severities of DR by isolating mononuclear cells and extracting RNA. We then reverse-transcribed the RNA into cDNA and used RT-qPCR to measure the levels of miR-150 in individuals with varying DR severity. MiR-150 levels in the MNCS were decreased in individuals with diabetes with no retinopathy, moderate NPDR and severe NPDR groups when compared to control individuals; however, there was a marginal increase in the miR-150 mild NPDR group. The data could show evidence that a peripheral blood draw could be used as a less invasive approach to assessing the severity of diabetic retinopathy in patients. This would change the disease management and future treatments individually.

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.

Biomarkers in diabetic retinopathy

Diabetic retinopathy (DR) is a leading cause of blindness in working‐age adults worldwide, affecting up to 80% of patients who have had diabetes for more than 10 years. Biomarkers are measurable indicators that can be used to diagnose diseases or monitor their progression. In DR, biomarkers can be found in various structures of the eye, including the retina, vitreous, and aqueous humour.One of the most commonly used biomarkers in DR is glycated haemoglobin (HbA1c), which reflects long‐term blood glucose control. Elevated HbA1c levels are associated with an increased risk of developing DR, and strict glycemic control can help to prevent or delay its onset.Other biomarkers in DR include imaging techniques such as optical coherence tomography (OCT) and fundus photography, which can provide detailed images of the retina and allow for the detection of microaneurysms, haemorrhages, and exudates. OCT angiography (OCTA) can also visualize changes in retinal blood flow, which may be indicative of early DR.In addition to structural biomarkers, there are also functional biomarkers that can be used to evaluate visual function, such as contrast sensitivity and visual field testing. These measures are often used to monitor the progression of DR and assess the efficacy of treatment.Recent advances in biomarker research have led to the discovery of new markers for DR, including genetic markers, inflammatory markers, and metabolic markers. Genetic markers, such as single nucleotide polymorphisms (SNPs), have been associated with an increased risk of developing DR. Inflammatory markers, such as cytokines and chemokines, are elevated in the aqueous humour and vitreous of patients with DR and may contribute to the development and progression of the disease. Metabolic markers, such as advanced glycation end‐products (AGEs), are elevated in patients with DR and may play a role in the pathogenesis of the disease.Overall, biomarkers are an important tool in the diagnosis, monitoring, and management of DR. They may also help to improve our understanding of the disease and facilitate the development of new therapies. By identifying patients at high risk of developing DR, biomarkers may enable earlier interventions to prevent or delay the onset of vision loss.