Association of Serum Zinc and Vitamin A Levels with Severity of Retinopathy in Type 2 Diabetic Patients: a Cross-Sectional Study

Effect of High-Sucrose Diet on the Occurrence and Progression of Diabetic Retinopathy and Dietary Modification Strategies

As the most serious of the many worse new pathological changes caused by diabetes, there are many risk factors for the occurrence and development of diabetic retinopathy (DR). They mainly include hyperglycemia, hypertension, hyperlipidemia and so on. Among them, hyperglycemia is the most critical cause, and plays a vital role in the pathological changes of DR. High-sucrose diets (HSDs) lead to elevated blood glucose levels in vivo, which, through oxidative stress, inflammation, the production of advanced glycation end products (AGEs) and vascular endothelial growth factor (VEGF), cause plenty of pathological damages to the retina and ultimately bring about loss of vision. The existing therapies for DR primarily target the terminal stage of the disease, when irreversible visual impairment has appeared. Therefore, early prevention is particularly critical. The early prevention of DR-related vision loss requires adjustments to dietary habits, mainly by reducing sugar intake. This article primarily discusses the risk factors, pathophysiological processes and molecular mechanisms associated with the development of DR caused by HSDs. It aims to raise awareness of the crucial role of diet in the occurrence and progression of DR, promote timely changes in dietary habits, prevent vision loss and improve the quality of life. The aim is to make people aware of the importance of diet in the occurrence and progression of DR. According to the dietary modification strategies that we give, patients can change their poor eating habits in a timely manner to avoid theoretically avoidable retinopathy and obtain an excellent prognosis.

The relationship between blood vitamin A levels and diabetic retinopathy: a population-based study

We assessed the relationship between blood vitamin A levels and the risk of diabetic retinopathy. The study was population-based epidemiological study for 11,727 participants aged 40 or older who participated in the Korean National Health and Nutrition Examination Survey. Vitamin A in the blood was classified into quartiles. Diabetic retinopathy was diagnosed by the Early Treatment for Diabetic Retinopathy Study. After adjusting confounding variables such as age, sex, smoking, cholesterol, diabetes prevalence period, glycated hemoglobin levels, and high blood pressure, the odd ratio (OR) of vitamin A at quartile level 4 for diabetic retinopathy was 0.32 (95% confidence interval [CI], 0.14-0.72, P for trend < 0.001). In male, the OR of quartile 3 level vitamin A for diabetic retinopathy was 0.11 (95% CI, 0.01-0.69, P for trend = 0.010). In adults under the age of 60, the OR of vitamin A at quartile level 3 for diabetic retinopathy was 0.10. (95% CI, 0.03-0.29, P for trend < 0.001). Serum vitamin A high levels are associated with low risk of diabetic retinopathy. Particularly, there is a more effective relationship in male and adults under the age of 60.

IFI44L and C1QTNF5 as promising biomarkers of proliferative diabetic retinopathy

Proliferative diabetic retinopathy (PDR) is a world-wide leading cause of blindness among adults and may be associated with the influence of genetic factors. It is significant to search for genetic biomarkers of PDR. In our study, we collected genomic data about PDR from gene expression omnibus (GEO) database. Differentially expressed gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA) were carried out. The gene module with the highest gene significance (GS) was defined as the key module. Hub genes were identified by Venn diagram. Then we verified the expression of hub genes in validation data sets and built a diagnostic model by least absolute shrinkage and selection operator (LASSO) regression. Enrichment analysis, including gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA) and construction of a protein-protein interaction (PPI) network were conducted. In GSE60436, we identified 466 DEGs. WGCNA established 14 gene modules, and the blue module (GS = 0.64), was the key module. Interferon (IFN)-induced protein 44-like (IFI44L) and complement C1q tumor necrosis factor-related protein 5 (C1QTNF5) were identified as hub genes. The expression of hub genes in GEO datasets was verified and a diagnostic model was constructed by LASSO as follows: index = IFI44L * 0.0432 + C1QTNF5 * 0.11246. IFI44L and C1QTNF5 might affect the disease progression of PDR by regulating metabolism-related and inflammatory pathways. IFI44L and C1QTNF5 may play important roles in the disease process of PDR, and a LASSO regression model suggested that the 2 genes could serve as promising biomarkers of PDR.

Nutraceutical Prevention of Diabetic Complications—Focus on Dicarbonyl and Oxidative Stress

Oxidative and dicarbonyl stress, driven by excess accumulation of glycolytic intermediates in cells that are highly permeable to glucose in the absence of effective insulin activity, appear to be the chief mediators of the complications of diabetes. The most pathogenically significant dicarbonyl stress reflects spontaneous dephosphorylation of glycolytic triose phosphates, giving rise to highly reactive methylglyoxal. This compound can be converted to harmless lactate by the sequential activity of glyoxalase I and II, employing glutathione as a catalyst. The transcription of glyoxalase I, rate-limiting for this process, is promoted by Nrf2, which can be activated by nutraceutical phase 2 inducers such as lipoic acid and sulforaphane. In cells exposed to hyperglycemia, glycine somehow up-regulates Nrf2 activity. Zinc can likewise promote glyoxalase I transcription, via activation of the metal-responsive transcription factor (MTF) that binds to the glyoxalase promoter. Induction of glyoxalase I and metallothionein may explain the protective impact of zinc in rodent models of diabetic complications. With respect to the contribution of oxidative stress to diabetic complications, promoters of mitophagy and mitochondrial biogenesis, UCP2 inducers, inhibitors of NAPDH oxidase, recouplers of eNOS, glutathione precursors, membrane oxidant scavengers, Nrf2 activators, and correction of diabetic thiamine deficiency should help to quell this.

Redoxisome and diabetic retinopathy: Pathophysiology and therapeutic interventions

Diabetic retinopathy (DR) is a chronic microvascular complication of diabetes mellitus (DM). It is a worldwide growing epidemic disease considered to be the leading cause of vision-loss and blindness in people with DM. Redox reactions occurring at the extra- and intracellular levels are essential for the maintenance of cellular homeostasis. Dysregulation of redox homeostasis are implicated in the onset and development of DR. Thioredoxin1 (TRX1) and Thioredoxin2 (TRX2) are cytoplasmic and mitochondrially localized antioxidant proteins ubiquitously expressed in various cells and control cellular reactive oxygen species (ROS) by reducing the disulfides into thiol groups. Thioredoxin-interacting protein (TXNIP) binds to TRX system and inhibits the active reduced form of TRX through disulfide exchange reaction. Recent studies indicate the association of TRX/TXNIP with redox signal transduction pathways including activation of Nod-like receptor pyrin domain containing protein-3 (NLRP3) inflammasome, apoptosis, autophagy/mitophagy, epigenetic modifications in a redox-dependent manner. Thus, it is important to gain a more in-depth understanding about the cellular and molecular mechanisms that links redoxisome and ER/Mitochondrial dysfunction to drive the progression of DR. The purpose of this review is to provide a mechanistic understanding of the complex molecular mechanisms and pathophysiological roles associated with redoxisome, the TRX/TXNIP redox signaling complex under oxidative stress in the development of DR. Also, the molecular targets of FDA approved drugs and clinical trials in addition to effective antioxidant strategies for the treatment of diabetic retinopathy are reviewed.

Micronutrients and Diabetic Retinopathy: Evidence From The National Health and Nutrition Examination Survey and a Meta-analysis

PURPOSE

To investigate the associations between circulating micronutrients (vitamins A, C, D, E, and carotenoids) and risk of diabetic retinopathy (DR).

DESIGN

Cross-sectional study and meta-analysis.

METHODS

The cross-sectional study included 517 diabetic participants aged ≥40 years in the 2005-2006 National Health and Nutrition Examination Survey. Serum vitamin D was converted to liquid chromatography-tandem mass spectrometry-equivalent results, while other micronutrients were measured using high-performance liquid chromatography. Presence of DR was determined based on non-mydriatic fundus photographs. A meta-analysis was subsequently performed, which included relevant studies published from January 01, 1990 to December 31, 2020.

RESULTS

Of the 517 included participants, DR was identified in 159 participants (25.17%). After adjusting for multiple confounders, only serum vitamin C was associated with a lower risk of DR (odds ratio [OR]: 0.60; 95% confidence interval [CI]: 0.38-0.95). A total of 35 studies were included in the subsequent meta-analysis. Comparing 1056 participants with DR to 920 controls, the pooled weighted mean difference (WMD) of vitamin C was -11.01 (95% CI: -19.35 to -2.67). Regarding vitamins D and E, the pooled WMD was -3.06 (95% CI: -5.15 to -0.96) and -3.03 (95% CI: -4.24 to -1.82), respectively. No associations were identified between DR and circulating vitamin A or carotenoids.

CONCLUSIONS

Lower levels of circulating vitamins C, D, and E were found in DR patients than those without. More high-quality studies are required to assess the real effects of micronutrients on DR.

Transthyretin and retinol-binding protein as discriminators of diabetic retinopathy in type 1 diabetes mellitus

PURPOSE

Diabetic retinopathy (DR) is one of the most common complications of diabetes mellitus (DM), which is still a major reason for blindness. Transthyretin (TTR) and retinol-binding protein (RBP) are thought to be related to the pathogenesis both in T2DM and T1DM. We aimed to investigate the association between serum levels of TTR, RBP, RBP/TTR ratio, and DR.

METHODS

This retrospective study involved 188 T1DM inpatients divided into two groups: patients with DR (n = 95) and patients without DR (n = 93). Data of serum levels on lipids and inflammation were collected. Multiple logistic regression analysis was performed to research the association between TTR, RBP, RBP/TTR, and diabetic retinopathy in T1DM.

RESULTS

Compared with patients without DR, those with DR have a higher level of TTR (207 versus 195 mg/L, p = 0.034) and RBP4 (36.85 versus 25.68 mg/L, p < 0.001). Significant differences were also observed between two groups with respect to body mass index (BMI), blood pressure (BP), total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL), homocysteine, apolipoprotein B (APOB), leucocyte, monocyte, neutrophil, and uric acid (p < 0.05 for all). TTR, RBP, and RBP/TTR were positively correlated with BP, BMI, TG, LDL, homocysteine, APOB, and uric acid. A multivariate logistic regression model revealed individuals with RBP4 level in the highest quartile had 58.95 times higher risk of developing diabetic retinopathy than those in the lowest quartile.

CONCLUSIONS

In conclusion, TTR, RBP, and RBP/TTR ratio are risk factors of DR in T1DM. They are potential markers and targets for diagnosis and treatment of DR.

Vitamin A and Diabetes

Recently, research data have shown that vitamin A (VA, retinol) as a micronutrient participates in the regulation of glucose and lipid metabolism. Since diabetes is a metabolic disease, it is imperative to reveal the relationship of VA and diabetes. This review was aimed to summarize the current understanding of VA and its metabolites in diabetes. Since April of 2020, the authors have searched the PubMed using key words and retrieved articles that focused on diabetes and VA or its metabolites. Based on the published data, it appears that the development of type 1 diabetes leads to reduction of blood VA level in human and animals, and increase of hepatic VA store in experimental animals. On the other hand, the mutual impacts of type 2 diabetes and VA intake and blood VA level on each other appear to be uncertain. Retinoic acid, the active metabolite of VA, has been studied extensively for the treatment of diabetic complications. The current data appear to indicate that the development of diabetes is associated with changes of VA metabolism. More carefully designed clinical and laboratory experiments are needed to reveal the impacts of diabetes on VA metabolism and the role of VA in the development and treatment of diabetes.

Association between retinol binding protein 4 and diabetic retinopathy among type 2 diabetic patients: a meta-analysis

AIMS

The aim of this study was to investigate the association between retinol-binding protein 4 (RBP4) and diabetic retinopathy (DR) among patients with type 2 diabetes mellitus (T2DM).

METHODS

Databases PubMed, Embase, Web of Science, Chinese National Knowledge Infrastructure, VIP, and Wangfang were searched to July 30, 2019. The Newcastle-Ottawa Scale was applied to assess the quality of all identified studies, and those qualified were included in the meta-analysis. The Chi squared Q test and I² statistics were conducted to evaluate heterogeneity. Standardized mean differences (SMD) and 95% confidence intervals (CI) among RBP4 within the DR and T2DM without retinopathy (DWR) groups were pooled using the random effects model depending on the heterogeneity. Subgroup analyses were conducted among the groups having different diabetes duration, detection methods, body mass index, and total cholesterol and triglyceride levels. The funnel plot was used to assess publication bias.

RESULTS

Nineteen observational studies were included in our meta-analysis. RBP4 was significantly higher in both nonproliferative DR (SMD: 0.72, 95% CI 0.48-0.95, P < 0.00001) and proliferative DR (SMD: 2.68, 95% CI 1.69-3.67, P < 0.00001) groups despite high heterogeneity (I² = 87 and 97% in DR and PDR groups, respectively). Significant differences were noted among most subgroups (P < 0.05). Among those accompanied by hypercholesterolemia, the association between RBP4 and DR were unclear (P = 0.09).

CONCLUSIONS

Elevated RBP4 is strongly associated with DR and may play an essential role in its progression. Additional large-scale controlled studies are needed to confirm these findings.

Study on the Risk Factors for Hyperuricaemia and Related Vascular Complications in Patients with Type 2 Diabetes Mellitus

Purpose

The study aimed to identify diseases that exhibit significant differences between hyperuricaemia (HUA) and non-hyperuricaemia (NHUA) groups and analyse the risk factors for HUA based on the related diseases in type 2 diabetes mellitus (T2DM).

Methods

A total of 3264 T2DM patients were investigated from 2013 to 2017 in the Jinyang and Sanlin communities by obtaining basic data from the electronic medical record system (EMRS). From September 2018 to July 2019, 3000 patients (264 patients were missing during follow-up) were investigated with questionnaires, physical examinations and biochemical index tests. After removing missing values, 2899 patients were divided into HUA and NHUA groups. The chi-square test was used to identify diseases with differences. Using Lasso analysis and logistic regression analysis, risk factors for HUA based on the related diseases were obtained. The C-index, receiver operating characteristic (ROC) curve and calibration plot were used to validate the discrimination and accuracy of the factors.

Results

The chi-square test showed that there were significant differences in coronary heart disease (CHD) and diabetic nephropathy (DN) between the HUA group and the NHUA group. Through Lasso regression, glycosylated haemoglobin A1c (HbA1c), triglyceride (TG), blood urea nitrogen (BUN) and serum creatinine (SCR) were screened in the CHD group. Body mass index (BMI), HbA1c, total cholesterol (TC), TG, BUN, SCR and urine microalbumin (UMA) were screened in the DN group. The P-value of all the variables was less than 0.05. Through the C-index, calibration, and ROC curve analyses, these risk factors had medium accuracy.

Conclusion

HUA was significantly related to CHD and DN. The level of UA was correlated with HbA1c, TG, BUN, and SCR based on CHD. The level of UA was associated with BMI, HbA1c, TC, TG, BUN, SCR, and UMA based on DN.

Adjuvant Therapies in Diabetic Retinopathy as an Early Approach to Delay Its Progression: The Importance of Oxidative Stress and Inflammation

Diabetes mellitus (DM) is a progressive disease induced by a sustained state of chronic hyperglycemia that can lead to several complications targeting highly metabolic cells. Diabetic retinopathy (DR) is a multifactorial microvascular complication of DM, with high prevalence, which can ultimately lead to visual impairment. The genesis of DR involves a complex variety of pathways such as oxidative stress, inflammation, apoptosis, neurodegeneration, angiogenesis, lipid peroxidation, and endoplasmic reticulum (ER) stress, each possessing potential therapeutic biomarkers. A specific treatment has yet to be developed for early stages of DR since no management is given other than glycemic control until the proliferative stage develops, offering a poor visual prognosis to the patient. In this narrative review article, we evaluate different dietary regimens, such as the Mediterranean diet, Dietary Pattern to Stop Hypertension (DASH) and their functional foods, and low-calorie diets (LCDs). Nutraceuticals have also been assessed in DR on account of their antioxidant, anti-inflammatory, and antiangiogenic properties, which may have an important impact on the physiopathology of DR. These nutraceuticals have shown to lower reactive oxygen species (ROS), important inflammatory factors, cytokines, and endothelial damage biomarkers either as monotherapies or combined therapies or concomitantly with established diabetes management or nonconventional adjuvant drugs like topical nonsteroidal anti-inflammatory drugs (NSAIDs).

Nomogram for the Risk of Diabetic Nephropathy or Diabetic Retinopathy Among Patients with Type 2 Diabetes Mellitus Based on Questionnaire and Biochemical Indicators: A Cross-Sectional Study

PURPOSE

This study aimed to develop a diabetic nephropathy (DN) or diabetic retinopathy (DR) incidence risk nomogram in China's population with type 2 diabetes mellitus (T2DM) based on a community-based sample.

METHODS

We carried out questionnaire evaluations, physical examinations and biochemical tests among 4219 T2DM patients in Shanghai. According to the incidence of DN and DR, 4219 patients in our study were divided into groups of T2DM patients with DN or DR, patients with both, and patients without any complications. We successively used least absolute shrinkage and selection operator regression analysis and logistic regression analysis to optimize the feature selection for DN and DR. To ensure the accuracy of the results, we carried out multivariable logistic regression analysis of the above significant risk factors on the sample data for both DN and DR. The selected features were included to establish a prediction model. The C-index, calibration plot, curve analysis and internal validation were used to validate the distinction, calibration, and clinical practicality of the model.

RESULTS

The predictors in the prediction model included disease course, body mass index (BMI), total triglycerides (TGs), systolic blood pressure (SBP), postprandial blood glucose (PBG), haemoglobin A1C (HbA1c) and blood urea nitrogen (BUN). The model displayed moderate predictive power with a C-index of 0.807 and an area under the receiver operating characteristic curve of 0.807. In internal verification, the C-index reached 0.804. The risk threshold was 16-75% according to the analysis of the decision curve, and the nomogram could be applied in clinical practice.

CONCLUSION

This DN or DR incidence risk nomogram incorporating disease course, BMI, TGs, SBP, PBG, HbA1c and BUN can be used to predict DN or DR incidence risk in T2DM patients. The research team has developed an online app based on a clinical prediction model incorporating risk factors for rapid and simple prediction.