Metabolomic analysis of retinopathy stages and amputation in type 2 diabetes.

BACKGROUND: Diabetic 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. OBJECTIVE: This 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. METHODS: The 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. RESULTS: We 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. CONCLUSIONS: The 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.

Exploration of potential novel drug targets for diabetic retinopathy by plasma proteome screening.

The aim of this study is to identify novel potential drug targets for diabetic retinopathy (DR). A bidirectional two-sample Mendelian randomization (MR) analysis was performed using protein quantitative trait loci (pQTL) of 734 plasma proteins as the exposures and clinically diagnosed DR as the outcome. Genetic instruments for 734 plasma proteins were obtained from recently published genome-wide association studies (GWAS), and external plasma proteome data was retrieved from the Icelandic Decoding Genetics Study and UK Biobank Pharma Proteomics Project. Summary-level data of GWAS for DR were obtained from the Finngen Consortium, comprising 14,584 cases and 202,082 population controls. Steiger filtering, Bayesian co-localization, and phenotype scanning were used to further verify the causal relationships calculated by MR. Three significant (p < 6.81 × 10-5) plasma protein-DR pairs were identified during the primary MR analysis, including CFH (OR = 0.8; 95% CI 0.75-0.86; p = 1.29 × 10-9), B3GNT8 (OR = 1.09; 95% CI 1.05-1.12; p = 5.9 × 10-6) and CFHR4 (OR = 1.11; 95% CI 1.06-1.16; p = 1.95 × 10-6). None of the three proteins showed reverse causation. According to Bayesian colocalization analysis, CFH (coloc.abf-PPH4 = 0.534) and B3GNT8 (coloc.abf-PPH4 = 0.638) in plasma shared the same variant with DR. All three identified proteins were validated in external replication cohorts. Our research shows a cause-and-effect connection between genetically determined levels of CFH, B3GNT8 and CFHR4 plasma proteins and DR. The discovery implies that these proteins hold potential as drug target in the process of developing drugs to treat DR.

Lipidomic studies revealing serological markers associated with the occurrence of retinopathy in type 2 diabetes.

PURPOSE: The duration of type 2 diabetes mellitus (T2DM) and blood glucose levels have a significant impact on the development of T2DM complications. However, currently known risk factors are not good predictors of the onset or progression of diabetic retinopathy (DR). Therefore, we aimed to investigate the differences in the serum lipid composition in patients with T2DM, without and with DR, and search for potential serological indicators associated with the development of DR. METHODS: A total of 622 patients with T2DM hospitalized in the Department of Endocrinology of the First Affiliated Hospital of Xi'an JiaoTong University were selected as the discovery set. One-to-one case-control matching was performed according to the traditional risk factors for DR (i.e., age, duration of diabetes, HbA1c level, and hypertension). All cases with comorbid chronic kidney disease were excluded to eliminate confounding factors. A total of 42 pairs were successfully matched. T2DM patients with DR (DR group) were the case group, and T2DM patients without DR (NDR group) served as control subjects. Ultra-performance liquid chromatography-mass spectrometry (LC-MS/MS) was used for untargeted lipidomics analysis on serum, and a partial least squares discriminant analysis (PLS-DA) model was established to screen differential lipid molecules based on variable importance in the projection (VIP) > 1. An additional 531 T2DM patients were selected as the validation set. Next, 1:1 propensity score matching (PSM) was performed for the traditional risk factors for DR, and a combined 95 pairings in the NDR and DR groups were successfully matched. The screened differential lipid molecules were validated by multiple reaction monitoring (MRM) quantification based on mass spectrometry. RESULTS: The discovery set showed no differences in traditional risk factors associated with the development of DR (i.e., age, disease duration, HbA1c, blood pressure, and glomerular filtration rate). In the DR group compared with the NDR group, the levels of three ceramides (Cer) and seven sphingomyelins (SM) were significantly lower, and one phosphatidylcholine (PC), two lysophosphatidylcholines (LPC), and two SMs were significantly higher. Furthermore, evaluation of these 15 differential lipid molecules in the validation sample set showed that three Cer and SM(d18:1/24:1) molecules were substantially lower in the DR group. After excluding other confounding factors (e.g., sex, BMI, lipid-lowering drug therapy, and lipid levels), multifactorial logistic regression analysis revealed that a lower abundance of two ceramides, i.e., Cer(d18:0/22:0) and Cer(d18:0/24:0), was an independent risk factor for the occurrence of DR in T2DM patients. CONCLUSION: Disturbances in lipid metabolism are closely associated with the occurrence of DR in patients with T2DM, especially in ceramides. Our study revealed for the first time that Cer(d18:0/22:0) and Cer(d18:0/24:0) might be potential serological markers for the diagnosis of DR occurrence in T2DM patients, providing new ideas for the early diagnosis of DR.

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

Background: Diabetic 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. Methods: The 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. Results: The 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. Conclusion: The 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.

LncRNA XIST promotes neovascularization in diabetic retinopathy by regulating miR-101-3p/VEGFA.

Objective: This study sought to investigate the regulation of long noncoding RNA (lncRNA) XIST on the microRNA (miR)-101-3p/vascular endothelial growth factor A (VEGFA) axis in neovascularization in diabetic retinopathy (DR). Materials and methods: Serum of patients with DR was extracted for the analysis of XIST, miR-101-3p, and VEGFA expression levels. High glucose (HG)-insulted HRMECs and DR model rats were treated with lentiviral vectors. MTT, transwell, and tube formation assays were performed to evaluate cell viability, migration, and angiogenesis, and ELISA was conducted to detect the levels of inflammatory cytokines. Dual-luciferase reporter, RIP, and RNA pull-down experiments were used to validate the relationships among XIST, miR-101-3p, and VEGFA. Results: XIST and VEGFA were upregulated and miR-101-3p was downregulated in serum from patients with DR. XIST knockdown inhibited proliferation, migration, vessel tube formation, and inflammatory responsein HG-treated HRMECs, whereas the above effects were nullified by miR-101-3p inhibition or VEGFA overexpression. miR-101-3p could bind to XIST and VEGFA. XIST promoted DR development in rats by regulating the miR-101-3p/VEGFA axis. Conclusion: LncRNA XIST promotes VEGFA expression by downregulating miR-101-3p, thereby stimulating angiogenesis and inflammatory response in DR.

Meta-analysis of the relationship between ocular and peripheral serum IL-17A and diabetic retinopathy.

Purpose: A systematic evaluation and Meta-analysis were performed to determine the relationship between IL-17A levels in ocular aqueous and peripheral venous serum samples and diabetic retinopathy (DR). Methods: PubMed, Embase, Web of Science, and CNKI databases were searched from the time of library construction to 2023-09-20.The results were combined using a random-effects model, sensitivity analyses were performed to determine whether the arithmetic was stable and reliable, and subgroup analyses were used to look for possible sources of heterogeneity. Results: A total of 7 case-control studies were included. The level of IL-17A was higher in the Nonproliferative DR(NPDR) group than in the Non-DR(NDR) group [SMD=2.07,95%CI(0.45,3.68),P=0.01], and the level of IL-17A in the proliferating DR(PDR) group was higher than that of the NDR group [SMD=4.66,95%CI(1.23,8.08),P<0.00001]. IL-17A levels in peripheral serum and atrial fluid were significantly higher in NPDR and PDR patients than in non-DR patients in subgroup analyses, and detection of peripheral serum IL-17A concentrations could help to assess the risk of progression from NPDR to PDR. Sensitivity analyses suggested that the results of the random-effects arithmetic were stable and reliable. Subgroup analyses based on assay method and sample source showed that the choice of these factors would largely influence the relationship between IL-17A levels and DR. Conclusion: Elevated peripheral serum and ocular aqueous humor IL-17A levels in diabetic patients are associated with the risk of DR, IL-17A may serve as a potential predictor or therapeutic target for DR, and IL-17A may be an important predictor of inflammation for the progression of NPDR to PDR. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42024532900.

Association between HDL cholesterol with diabetic retinopathy in diabetic patients: a cross-sectional retrospective study.

OBJECTIVE: Diabetic patients are often comorbid with dyslipidemia, however, the relationship between high-density lipoprotein cholesterol(HDL-C) and diabetic retinopathy (DR) in the adult diabetic population remains to be fully elucidated.The aim of this study is to evaluate the associations between HDL-C and DR in the United States adults with diabetes. METHODS: A total of 1708 participants from the National Health and Nutrition Examination Survey (NHANES) 2005-2008 were enrolled in the present study. Fundus images of all study subjects were captured and evaluated using a digital camera and an ophthalmic digital imaging system, and the diagnosis of DR was made by the severity scale of the Early Treatment Diabetic Retinopathy Study (ETDRS).Roche Diagnostics were used to measure serum HDL-C concentration. The relationship of DR with HDL-C was investigated using multivariable logistic regression. The potential non-line correlation was explored with smooth curve fitting approach. RESULTS: The fully-adjusted model showed that HDL-C positively correlated with DR(OR:1.69, 95%CI: 1.25-2.31).However, an inverted U-shaped association between them was observed by applying the smooth curve fitted method. The inflection point of HDL-C(1.99mmol/l) was calculated by utilizing the two-piecewise logistic regression model. In the subgroup analysis, the inverted U-shaped nonlinear correlation between HDL-C and DR was also found in female, Non-Hispanic White, and lower age groups. CONCLUSION: Our study revealed an inverted U-shaped positive relationship between HDL-C and DR.The findings may provide us with a more comprehensive understanding of the association between HDL-C and DR.

Causal association of circulating metabolites with diabetic retinopathy: a bidirectional Mendelian randomization analysis.

Introduction: The retina is a highly metabolically active tissue, and there is a lack of clarity about the relationship between metabolites and diabetic retinopathy (DR). This study used two-sample bidirectional Mendelian randomization (MR) analyses to identify causal relationships between metabolites and DR. Methods: Genetic variants were selected from the open-access Genome-Wide Association Studies (GWAS) summary database as proxies for the 1400 most recently published metabolites. MR analysis was performed to examine associations between these metabolite traits and DR. Single nucleotide polymorphism (SNP) data that were significantly associated with exposure were screened through association analysis. Validated instrumental variables (IVs) were obtained by removing SNPs with linkage disequilibrium (LD) and F-statistic values below 10. MR analyses were performed using the inverse variance weighted (IVW) method as the primary approach. The robustness of the results was verified by sensitivity analyses, including assessments of heterogeneity, horizontal pleiotropy, and the leave-one-out method. Results: In the IVW approach and in the primary analysis of several sensitivity analyses, genetically determined glycolithocholate sulfate levels, androstenediol (3 beta, 17 beta) monosulfate (1) levels, 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4) levels, 1-oleoyl-2-arachidonoyl-GPE (18:1/20:4) levels, 1-oleoyl-2-linoleoyl-GPE (18:1/18:2) levels, X-26109 levels, N6-methyllysine levels, (N6,N6-dimethyllysine levels), and (N2-acetyl,N6,N6-dimethyllysine levels) were negatively associated with the risk of DR. 5-hydroxymethyl-2-furoylcarnitine levels and the glutamate-to-alanine ratio were positively associated with the risk of DR. No reverse causal association was found between DR and metabolites. Discussion: This MR study suggests that nine metabolites may have a protective effect in DR, while two metabolites may be associated with an increased risk of DR. However, further research is needed to confirm these findings. Supplementation with beneficial metabolites may reduce DR risk and could potentially be a novel therapeutic approach to DR treatment.

Association between blood urea nitrogen levels and diabetic retinopathy in diabetic adults in the United States (NHANES 2005-2018).

Objective: To investigate the association between blood urea nitrogen (BUN) levels and diabetic retinopathy (DR) in adults with diabetes mellitus (DM). Methods: Seven cycles of cross-sectional population information acquired from NHANES(national health and nutrition examination surveys) 2005-2018 were collected, from which a sample of diabetic adults was screened and separated into two groups based on whether or not they had DR, followed by weighted multivariate regression analysis. This study collected a complete set of demographic, biological, and sociological risk factor indicators for DR. Demographic risk factors comprised age, gender, and ethnicity, while biological risk factors included blood count, blood pressure, BMI, waist circumference, and glycated hemoglobin. Sociological risk factors included education level, deprivation index, smoking status, and alcohol consumption. Results: The multiple regression model revealed a significant connection between BUN levels and DR [odds ratio =1.04, 95% confidence interval (1.03-1.05), p-value <0.0001],accounting for numerous variables. After equating BUN levels into four groups, multiple regression modeling showed the highest quartile (BUN>20 mg/dl) was 2.22 times more likely to develop DR than the lowest quartile [odds ratio =2.22, 95% confidence interval (1.69-2.93), p- value <0.0001]. Subgroup analyses revealed that gender, race, diabetes subtype, and duration of diabetes had a regulating effect on the relationship between BUN and DR. Conclusion: BUN levels were related with an increased prevalence of DR, particularly in individuals with BUN >20 mg/dl. These findings highlight the significance of BUN level in assessing the risk of DR.

The L-shape relationship between hemoglobin, albumin, lymphocyte, platelet score and the risk of diabetic retinopathy in the US population.

Background: The primary aim of this study was to investigate the correlation between diabetic retinopathy (DR) and the HALP score (hemoglobin, albumin, lymphocyte, and platelet) in individuals with diabetes within the United States population. Methods: This cross-sectional investigation was based on the National Health and Nutrition Examination Survey (NHANES) database from 2003-2018. The following module calculated the HALP score: HALP score = [lymphocytes (/L) × hemoglobin (g/L) × albumin (g/L)]/platelets (/L). By performing the receiver operating characteristic (ROC) analysis, the optimal cutoff value of HALP was ascertained. Restricted cubic splines (RCS), multivariable logistic regression analysis, sensitivity analysis, and subgroup analysis were conducted to evaluate the effect of the HALP score on DR patients. Finally, the decision curve analysis (DCA) and clinical impact curve (CIC) were conducted to estimate the predictive power and clinical utility of the HALP score with clinical indicators. Results: According to the cutoff value (42.9) determined by the ROC curve, the participants were stratified into a lower HALP group (HALPlow) and a higher HALP group (HALPhigh). An L-shaped relationship between HALP score and DR risk was presented in the RCS model (P for nonlinearity <0.001). The DR risk sharply decreased with the increase of HALP, and the decline reached a plateau when HALP was more than 42.9. After fully adjustment, the multivariate logistic regression analysis found that HALPlow was an independent risk factor for DR (OR = 1.363, 95% CI: 1.111-1.671, P < 0.001). Besides, sensitivity analysis showed consistent results. Furthermore, the combination of HALP score and clinical indicators demonstrated predictive power and clinical utility, as shown by the ROC curve, DCA, and CIC. Conclusion: The HALP score has an L-shaped correlation with the risk of DR, and thus, the HALP score may contribute to the timely intervention of diabetes patients.

Association between AST/ALT ratio and diabetic retinopathy risk in type 2 diabetes: a cross-sectional investigation.

Objective: This study aimed to explore the association between the aspartate aminotransferase to alanine aminotransferase ratio (AST/ALT ratio) and diabetic retinopathy (DR) in patients with type 2 diabetes. Methods: In this cross-sectional study, clinical data from 3002 patients with type 2 diabetes admitted to the Department of Endocrinology of our hospital between January 1, 2021, and December 1, 2022, were retrospectively collected. Measurements of AST and ALT were conducted and diabetes-related complications were screened. The association between AST/ALT ratio and diabetic retinopathy was assessed using multivariate logistic regression, and a generalized additive model (GAM) was used to investigate nonlinear relationships. Subgroup analyses and interaction tests were also conducted. Results: Among the 3002 patients, 1590 (52.96%) were male and 1412 (47.04%) were female. The mean AST/ALT ratio was 0.98 ± 0.32, ranging from 0.37 (Min) to 2.17 (Max). Diabetic retinopathy was present in 40.47% of the patients. After multivariate adjustments, for each 0.1 unit increase in AST/ALT ratio, the risk of DR increased by 4% (OR = 1.04, 95% CI: 1.01-1.07, p=0.0053). Higher AST/ALT ratio quartiles were associated with Higher prevalence of DR (OR vs. Q1: Q4 = 1.34 (CI: 1.03-1.75, p=0.0303).The GAM and smoothed curve fit indicated a linear relationship between AST/ALT ratio and DR risk, with no significant interaction effects across different subgroups. Conclusion: Our study demonstrates a positive correlation between the AST/ALT ratio and diabetic retinopathy risk in type 2 diabetes, suggesting its potential role in assessing DR risk.

Comparison of HIF-1α and survivin levels in patients with diabetes and retinopathy of varying severity.

PURPOSE: This study measured serum hypoxia--inducible factor-1 (HIF-1α) and survivin levels in patients with diabetes and investigated their association with the severity of retinopathy. METHODS: This study included 88 patients with type 2 diabetes mellitus who underwent routine eye examinations. Three groups were created. Group 1 consisted of patients without diabetic retinopathy. Group 2 included patients with non-proliferative diabetic retinopathy. Group 3 included patients with proliferative diabetic retinopathy. To measure serum HIF-1α and survivin levels, venous blood samples were collected from patients. RESULTS: The mean HIF-1α levels in groups 1, 2, and 3 were 17.30 ± 2.19, 17.79 ± 2.34, and 14.19 ± 2.94 pg/ml, respectively. Significant differences were detected between groups 1 and 3 (p=0.01) and between groups 2 and 3 (p=0.01). The mean survivin levels in groups 1, 2, and 3 were 42.65 ± 5.37, 54.92 ± 5.55, and 37.46 ± 8.09 pg/ml, respectively. A significant difference was only detected between groups 2 and 3 (p=0.002). CONCLUSION: The present study revealed that serum HIF-1α and survivin levels are increased in patients with non-proliferative diabetic retinopathy compared to those in patients without diabetic retinopathy.

Association of the systemic immuno-inflammation index, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio with diabetic microvascular complications.

Background: The systemic immuno-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) are widely used and have been shown to be predictive indicators of various diseases. Diabetic nephropathy (DN), retinopathy (DR), and peripheral neuropathy (DPN) are the most prominent and common microvascular complications, which have seriously negative impacts on patients, families, and society. Exploring the associations with these three indicators and diabetic microvascular complications are the main purpose. Methods: There were 1058 individuals with type 2 diabetes mellitus (T2DM) in this retrospective cross-sectional study. SII, NLR, and PLR were calculated. The diseases were diagnosed by endocrinologists. Logistic regression and subgroup analysis were applied to evaluate the association between SII, NLP, and PLR and diabetic microvascular complications. Results: SII, NLR, and PLR were significantly associated with the risk of DN [odds ratios (ORs): 1.52, 1.71, and 1.60, respectively] and DR [ORs: 1.57, 1.79, and 1.55, respectively] by multivariate logistic regression. When NLR ≥2.66, the OR was significantly higher for the risk of DPN (OR: 1.985, 95% confidence interval: 1.29-3.05). Subgroup analysis showed no significant positive associations across different demographics and comorbidities, including sex, age, hypertension, HbA1c (glycated hemoglobin), and dyslipidemia. Conclusion: This study found a positive relationship between NLR and DN, DR, and DPN. In contrast, SII and PLR were found to be only associated with DN and DR. Therefore, for the diagnosis of diabetic microvascular complications, SII, NLR and PLR are highly valuable.

The non-linear relationship between serum albumin and diabetic retinopathy in type 2 diabetes mellitus: a secondary analysis based on a cross-sectional study.

BACKGROUND: Most studies had shown a linear relationship between serum albumin (sALB) and the prevalence of diabetic retinopathy (DR). Thus, the purpose of this study is to investigate whether their relationship is non-linear. METHODS: We included 426 patients with type 2 diabetes who were hospitalized in Guangdong Provincial People's Hospital from December 2017 to November 2018. The outcome was the prevalence of DR. A two-piecewise logistics regression model was performed to identify the non-linear relationship between sALB and the prevalence of DR. The inflection point was calculated to determine the saturation effect through the maximum likelihood ratio and a recursive algorithm. RESULTS: DR was diagnosed in 167 of 426 type 2 diabetic patients. The relationship between sALB and DR was nonlinear. When sALB was less than 38.10 g/L, a significant negative association was observed (OR = 0.82; 95% CI, 0.72-0.94; P = 0.0037), while no significant association was observed when sALB was greater than 38.10 g/L (OR = 1.12; 95% CI, 0.92-1.35; P = 0.2637). CONCLUSIONS: The relationship between sALB and the prevalence of DR is non-linear. sALB is negatively associated with the prevalence of DR when sALB is less than 38.10 g/L. Our findings need to be confirmed by further prospective research.

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

OBJECTIVES: To identify molecular pathways and prognostic- and diagnostic plasma-protein biomarkers for diabetic retinopathy at various stages. METHODS: 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 by liquid chromatography-tandem mass-spectrometry followed by bioinformatics. RESULTS: 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. CONCLUSIONS: 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.

Dysregulated 24 h melatonin secretion associated with intrinsically photosensitive retinal ganglion cell function in diabetic retinopathy: a cross-sectional study.

AIMS/HYPOTHESIS: The aim of this study was to explore whether diabetic retinopathy is associated with alterations of the circadian system, and to examine the role of reduced intrinsically photosensitive retinal ganglion cell (ipRGC) function. METHODS: Participants with type 2 diabetes, with diabetic retinopathy (n=14) and without diabetic retinopathy (n=9) underwent 24 h blood sampling for melatonin and cortisol under controlled laboratory conditions. ipRGC function was inferred from the post-illumination pupil response (PIPR). Habitual sleep duration, efficiency and variability were assessed by actigraphy. RESULTS: Participants with diabetic retinopathy compared to participants without diabetic retinopathy had smaller PIPR (p=0.007), lower 24 h serum melatonin output (p=0.042) and greater day-to-day sleep variability (p=0.012). By contrast, 24 h cortisol profiles, sleep duration and efficiency were similar in both groups. Six individuals with diabetic retinopathy had no detectable dim-light melatonin onset. PIPR correlated with 24 h mean melatonin levels (r=0.555, p=0.007). CONCLUSIONS/INTERPRETATION: ipRCG dysfunction in diabetic retinopathy is associated with disruptions of the 24 h melatonin rhythm, suggesting circadian dysregulation in diabetic retinopathy.

Clinically relevant stratification of patients with type 2 diabetes by using continuous glucose monitoring data.

AIM: The wealth of data generated by continuous glucose monitoring (CGM) provides new opportunities for revealing heterogeneities in patients with type 2 diabetes mellitus (T2DM). We aimed to develop a method using CGM data to discover T2DM subtypes and investigate their relationship with clinical phenotypes and microvascular complications. METHODS: The data from 3119 patients with T2DM who wore blinded CGM at an academic medical centre was collected, and a glucose symbolic pattern (GSP) metric was created that combined knowledge-based temporal abstraction with numerical vectorization. The k-means clustering was applied to GSP to obtain subgroups of patients with T2DM. Clinical characteristics and the presence of diabetic retinopathy and albuminuria were compared among the subgroups. The findings were validated in an independent population comprising 773 patients with T2DM. RESULTS: By using GSP, four subgroups were identified with distinct features in CGM profiles and parameters. Moreover, the clustered subgroups differed significantly in clinical phenotypes, including indices of pancreatic ß-cell function and insulin resistance (all p < .001). After adjusting for confounders, group C (the most insulin resistant) had a significantly higher risk of albuminuria (odds ratio = 1.24, 95% confidence interval: 1.03-1.39) relative to group D, which had the best glucose control. These findings were confirmed in the validation set. CONCLUSION: Subtyping patients with T2DM using CGM data may help identify high-risk patients for microvascular complications and provide insights into the underlying pathophysiology. This method may help refine clinically meaningful stratification of patients with T2DM and inform personalized diabetes care.

Joint modeling of time to diabetic retinopathy and change in fasting blood sugar among type 2 diabetic patients, Northwest Ethiopia.

This study aimed to assess changes in fasting blood sugar (FBS) levels, time to diabetic retinopathy (DR) and its predictors among type 2 diabetes patients in Ethiopia. An institution-based retrospective follow-up study was conducted at the University of Gondar Comprehensive Specialized Hospital. The linear mixed effect model and Cox proportional hazard models were fitted separately, and later, the two models were fitted jointly using R software. Variables with a p value < 0.05 were considered significant predictors in the adjusted analysis. The incidence rate of DR was 2 per 100-person year of observation with a median follow-up time of 90.8 months (IQR 63.4). The current value and rate of change in FBS level were significant predictors of time to DR (AHR = 1.35; 95% CI 1.12-1.63) and (AHR = 1.70; 95% CI 1.21-2.39), respectively. Hypertension (AHR = 2.49; 95% CI 1.32-4.66), taking > 1 antidiabetic oral agent (AHR = 4.90; 95% CI 1.07-20.0) and more than 10 years duration (AHR = 0.17, 95% CI 0.06-0.46) were predictors of time to DR. This study revealed that the current value of FBS and the rate of FBS change were significantly associated with the time to DR.

High remnant cholesterol level is relevant to diabetic retinopathy in type 2 diabetes mellitus.

BACKGROUND: Diabetic retinopathy (DR) is the primary oculopathy causing blindness in diabetic patients. Currently, there is increasing interest in the role of lipids in the development of diabetic retinopathy, but it remains controversial. Remnant cholesterol (RC) is an inexpensive and easily measurable lipid parameter; however, the relationship between RC and DR in type 2 diabetes mellitus (T2DM) has not been elucidated. This research investigates the relevance between RC levels and DR severity while building a risk prediction model about DR. METHODS: In this single-centre retrospective cross-sectional study. Each hospitalised T2DM patient had no oral lipid-lowering drugs in the past three months, and coronary angiography showed epicardial coronary artery stenosis of less than 50% and completed seven-field stereo photographs, fluorescein fundus angiography, and optical coherence tomography detection. The RC value is calculated according to the internationally recognised formula. Binary logistic regression was used to correct confounding factors, and the receiver operating characteristic (ROC) analysis was used to identify risk factors and assess the nomogram's diagnostic efficiency. RESULTS: A total of 456 T2DM patients were included in the study. The RC levels in the DR team was higher [0.74 (0.60-1.12) mmo/l vs 0.54 (0.31-0.83) mmol/l P < 0.001] in the non-DR team. After adjusting for confounding elements, RC levels are still associated with DR risk (OR = 5.623 95%CI: 2.996-10.556 P < 0.001). The ratio of DR in every stage (except mild non-proliferative diabetic retinopathy) and DME in the high RC level team were further increased compared to the low-level team (all P < 0.001). After ROC analysis, the overall risk of DR was predicted by a nomogram constructed for RC, diabetes duration, and the neutrophil-lymphocyte ratio as 0.758 (95%CI 0.714-0.802 P < 0.001). CONCLUSIONS: High RC levels may be a potential risk factor for diabetic retinopathy, and the nomogram does better predict DR. Despite these essential findings, the limitation of this study is that it is single-centred and small sample size analysis.

Hypermethylation of miRNA-17-92 cluster in peripheral blood mononuclear cells in diabetic retinopathy.

BACKGROUND AND AIMS: Diabetic retinopathy (DR) is the most common complication of diabetes. The inflammatory milieu of diabetes results in changes throughout the body. This study asked whether epigenetic changes in peripheral blood mononuclear cells (PBMCs) reflect DR severity. METHODS: PBMCs were separated from the whole blood of DR individuals using density gradient centrifugation. DNA was isolated, and methylation of micro-RNA (miR)-17-92 cluster was evaluated. RESULTS: We observed that the miR-17-92 cluster was hypermethylated in DR individuals; specifically, this change was most remarkable with proliferative-DR (PDR). CONCLUSIONS: miR-17-92 methylation in PBMCs could help understand DR's pathogenesis and identify individuals at the risk of severe DR for early intervention.