Spleen Tyrosine Kinase Mediates Microglial Activation in Mice With Diabetic Retinopathy

Association between diabetic retinopathy and diabetic foot ulcer in patients with diabetes: A meta-analysis

This study aimed to explore the relationship between diabetic retinopathy (DR) and diabetic foot ulcers (DFUs) to provide evidence for the prevention of diabetic complications. PubMed, EMBASE, Web of Science, Cochrane Library, China National Knowledge Infrastructure, Chinese Biomedical Literature Database and Wanfang Data databases were searched from their inception until March 2023 for studies on the relationship between DR and DFU. Two researchers independently screened the literature and extracted data according to the inclusion and exclusion criteria. The meta-analysis was performed using the RevMan 5.3 software. Eleven articles referring to 10 208 patients were included, of whom 2191 patients had DFU and 8017 patients did not have DFU. The meta-analysis results showed that DR significantly increased the incidence of DFU (47.94% vs. 16.38%; OR, 4.13; 95% CI, 2.33-7.33; p < 0.001). The results of this study suggest that patients with DR have a higher risk of developing DFU, highlighting the importance of regular screening for these two complications to prevent serious adverse outcomes of diabetes. However, further high-quality studies are required to validate the conclusions of the present study.

Transcriptomic Analysis of Retinal Gene in Experimental Retinal Detachment Rats and Exploration of S100A9 and TLR4 in Human Vitreous

PURPOSE

To screen for the differentially expressed genes in experimental retinal detachment rats, and to explore the expression of S100 calcium-binding protein A9 and Toll-like receptor 4 in the vitreous of rhegmatogenous retinal detachment patients.

METHODS

Three rats of experimental retinal detachment and three normal rats were enrolled in the study. Transcriptomics (RNAseq) sequencing technology was used to screen differentially expressed genes in the retinas of the experimental retinal detachment group and the normal group. The selected differentially expressed genes for gene ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis were performed. In addition, the vitreous of 15 patients with rhegmatogenous retinal detachment and six patients with the control group were collected. The expressions of S100 calcium-binding protein A9 and Toll-like receptor 4 were detected by Elisa, and the differences in expression levels were analyzed statistically.

RESULTS

A total of 198 differentially expressed genes were screened by RNAseq sequencing, including 118 upregulated genes and 80 downregulated genes. Kyoto Encyclopedia of Genes and Genomes analysis confirmed that the most enriched pathway was the mitogen-activated protein kinase signaling pathway. Compared to the normal group, the expressions of suppressor of cytokine signaling-3, Storkhead box-2, S100 calcium-binding protein A9, Spi-1 proto-oncogene, phosphodiesterase 1B, and kinesin-light chain 1 mRNA in the retinas of the experimental retinal detachment rats were up-regulated, and the expressions of Max interacting protein 1 and the voltage-gated sodium 1 were down-regulated. Compared to the control group, the expressions of S100 calcium-binding protein A9 and Toll-like receptor 4 were upregulated by Elisa in the vitreous humor of rhegmatogenous retinal detachment patients with a statistically significant difference (p all <.05).

CONCLUSION

The differentially expressed genes of experimental retinal detachment rats were suppressor of cytokine signaling-3, Storkhead box-2, S100 calcium-binding protein A9, Spi-1 proto-oncogene, phosphodiesterase 1B, kinesin-light chain 1, Max interacting protein 1, voltage-gated sodium 1, etc. The differences of S100 calcium-binding protein A9 and Toll-like receptor 4 expressions between the rhegmatogenous retinal detachment patients and the control group were statistically significant, indicating that they may play a potential role in the inflammatory process of rhegmatogenous retinal detachment.

Retinal inflammation in murine models of type 1 and type 2 diabetes with diabetic retinopathy

AIMS/HYPOTHESIS

The loss of pericytes surrounding the retinal vasculature in early diabetic retinopathy underlies changes to the neurovascular unit that lead to more destructive forms of the disease. However, it is unclear which changes lead to loss of retinal pericytes. This study investigated the hypothesis that chronic increases in one or more inflammatory factors mitigate the signalling pathways needed for pericyte survival.

METHODS

Loss of pericytes and levels of inflammatory markers at the mRNA and protein levels were investigated in two genetic models of diabetes, Ins2Akita/+ (a model of type 1 diabetes) and Leprdb/db (a model of type 2 diabetes), at early stages of diabetic retinopathy. In addition, changes that accompany gliosis and the retinal vasculature were determined. Finally, changes in retinal pericytes chronically incubated with vehicle or increasing amounts of IFNγ were investigated to determine the effects on pericyte survival. The numbers of pericytes, microglia, astrocytes and endothelial cells in retinal flatmounts were determined by immunofluorescence. Protein and mRNA levels of inflammatory factors were determined using multiplex ELISAs and quantitative reverse transcription PCR (qRT-PCR). The effects of IFNγ on the murine retinal pericyte survival-related platelet-derived growth factor receptor β (PDGFRβ) signalling pathway were investigated by western blot analysis. Finally, the levels of cell death-associated protein kinase C isoform delta (PKCδ) and cleaved caspase 3 (CC3) in pericytes were determined by western blot analysis and immunocytochemistry.

RESULTS

The essential findings of this study were that both type 1 and 2 diabetes were accompanied by a similar progression of retinal pericyte loss, as well as gliosis. However, inflammatory factor expression was dissimilar in the two models of diabetes, with peak expression occurring at different ages for each model. Retinal vascular changes were more severe in the type 2 diabetes model. Chronic incubation of murine retinal pericytes with IFNγ decreased PDGFRβ signalling and increased the levels of active PKCδ and CC3.

CONCLUSIONS/INTERPRETATION

We conclude that retinal inflammation is involved in and sustains pericyte loss as diabetic retinopathy progresses. Moreover, IFNγ plays a critical role in reducing pericyte survival in the retina by reducing activation of the PDGFRβ signalling pathway and increasing PKCδ levels and pericyte apoptosis.

Identifying C1QB, ITGAM, and ITGB2 as potential diagnostic candidate genes for diabetic nephropathy using bioinformatics analysis

Background

Diabetic nephropathy (DN), the most intractable complication in diabetes patients, can lead to proteinuria and progressive reduction of glomerular filtration rate (GFR), which seriously affects the quality of life of patients and is associated with high mortality. However, the lack of accurate key candidate genes makes diagnosis of DN very difficult. This study aimed to identify new potential candidate genes for DN using bioinformatics, and elucidated the mechanism of DN at the cellular transcriptional level.

Methods

The microarray dataset GSE30529 was downloaded from the Gene Expression Omnibus Database (GEO), and the differentially expressed genes (DEGs) were screened by R software. We used Gene Ontology (GO), gene set enrichment analysis (GSEA), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to identify the signal pathways and genes. Protein-protein interaction (PPI) networks were constructed using the STRING database. The GSE30122 dataset was selected as the validation set. Receiver operating characteristic (ROC) curves were applied to evaluate the predictive value of genes. An area under curve (AUC) greater than 0.85 was considered to be of high diagnostic value. Several online databases were used to predict miRNAs and transcription factors (TFs) capable of binding hub genes. Cytoscape was used for constructing a miRNA-mRNA-TF network. The online database 'nephroseq' predicted the correlation between genes and kidney function. The serum level of creatinine, BUN, and albumin, and the urinary protein/creatinine ratio of the DN rat model were detected. The expression of hub genes was further verified through qPCR. Data were analyzed statistically using Student's t-test by the 'ggpubr' package.

Results

A total of 463 DEGs were identified from GSE30529. According to enrichment analysis, DEGs were mainly enriched in the immune response, coagulation cascades, and cytokine signaling pathways. Twenty hub genes with the highest connectivity and several gene cluster modules were ensured using Cytoscape. Five high diagnostic hub genes were selected and verified by GSE30122. The MiRNA-mRNA-TF network suggested a potential RNA regulatory relationship. Hub gene expression was positively correlated with kidney injury. The level of serum creatinine and BUN in the DN group was higher than in the control group (unpaired t test, t = 3.391, df = 4, p = 0.0275, r = 0.861). Meanwhile, the DN group had a higher urinary protein/creatinine ratio (unpaired t test, t = 17.23, df = 16, p < 0.001, r = 0.974). QPCR results showed that the potential candidate genes for DN diagnosis included C1QB, ITGAM, and ITGB2.

Conclusions

We identified C1QB, ITGAM and ITGB2 as potential candidate genes for DN diagnosis and therapy and provided insight into the mechanisms of DN development at transcriptome level. We further completed the construction of miRNA-mRNA-TF network to propose potential RNA regulatory pathways adjusting disease progression in DN.

Effects of diabetes on microglial physiology: a systematic review of in vitro, preclinical and clinical studies

Diabetes mellitus is a heterogeneous chronic metabolic disorder characterized by the presence of hyperglycemia, commonly preceded by a prediabetic state. The excess of blood glucose can damage multiple organs, including the brain. In fact, cognitive decline and dementia are increasingly being recognized as important comorbidities of diabetes. Despite the largely consistent link between diabetes and dementia, the underlying causes of neurodegeneration in diabetic patients remain to be elucidated. A common factor for almost all neurological disorders is neuroinflammation, a complex inflammatory process in the central nervous system for the most part orchestrated by microglial cells, the main representatives of the immune system in the brain. In this context, our research question aimed to understand how diabetes affects brain and/or retinal microglia physiology. We conducted a systematic search in PubMed and Web of Science to identify research items addressing the effects of diabetes on microglial phenotypic modulation, including critical neuroinflammatory mediators and their pathways. The literature search yielded 1327 records, including 18 patents. Based on the title and abstracts, 830 papers were screened from which 250 primary research papers met the eligibility criteria (original research articles with patients or with a strict diabetes model without comorbidities, that included direct data about microglia in the brain or retina), and 17 additional research papers were included through forward and backward citations, resulting in a total of 267 primary research articles included in the scoping systematic review. We reviewed all primary publications investigating the effects of diabetes and/or its main pathophysiological traits on microglia, including in vitro studies, preclinical models of diabetes and clinical studies on diabetic patients. Although a strict classification of microglia remains elusive given their capacity to adapt to the environment and their morphological, ultrastructural and molecular dynamism, diabetes modulates microglial phenotypic states, triggering specific responses that include upregulation of activity markers (such as Iba1, CD11b, CD68, MHC-II and F4/80), morphological shift to amoeboid shape, secretion of a wide variety of cytokines and chemokines, metabolic reprogramming and generalized increase of oxidative stress. Pathways commonly activated by diabetes-related conditions include NF-κB, NLRP3 inflammasome, fractalkine/CX3CR1, MAPKs, AGEs/RAGE and Akt/mTOR. Altogether, the detailed portrait of complex interactions between diabetes and microglia physiology presented here can be regarded as an important starting point for future research focused on the microglia-metabolism interface.

Spleen Tyrosine Kinase Contributes to Müller Glial Expression of Proangiogenic Cytokines in Diabetes

Purpose

Neuroglial dysfunction occurs early in the progression of diabetic retinopathy. In response to diabetes or hypoxia, Müller glia secrete cytokines and growth factors that contribute to disease progression. This study was designed to examine common signaling pathways activated in Müller glia by both type 1 and pre-/type 2 diabetes.

Methods

RiboTag (Pdgfra-cre;HA-Rpl22) mice were used to compare the impact of streptozotocin (STZ) and a high-fat, high-sucrose (HFHS) diet on ribosome association of mRNAs in Müller glia by RNA sequencing analysis. Human MIO-M1 Müller cells were exposed to either hyperglycemic or hypoxic culture conditions. Genetic manipulation and pharmacologic inhibition were used to interrogate signaling pathways.

Results

Association of mRNAs encoding triggering receptor expressed on myeloid cells 2 (TREM2), DNAX-activating protein 12 kDa (DAP12), and colony stimulating factor 1 receptor (CSF1R) with ribosomes isolated from Müller glia was upregulated in both STZ diabetic mice and mice fed an HFHS diet. The TREM2/DAP12 receptor-adaptor complex signals in coordination with CSF1R to activate spleen tyrosine kinase (SYK). SYK activation was enhanced in the retina of diabetic mice and in human MIO-M1 Müller cell cultures exposed to hyperglycemic or hypoxic culture conditions. DAP12 knockdown reduced SYK autophosphorylation in Müller cells exposed to hyperglycemic or hypoxic conditions. SYK inhibition or DAP12 knockdown suppressed hypoxia-induced expression of the transcription factor hypoxia-inducible factor 1⍺ (HIF1⍺), as well as expression of vascular endothelial growth factor and angiopoietin-like 4.

Conclusions

The findings support TREM2/DAP12 receptor-adaptor complex signaling via SYK to promote HIF1α stabilization and increased angiogenic cytokine production by Müller glia.

Potential Biomarkers and Drugs for Nanoparticle-Induced Cytotoxicity in the Retina: Based on Regulation of Inflammatory and Apoptotic Genes

The eye is a superficial organ directly exposed to the surrounding environment. Thus, the toxicity of nanoparticle (NP) pollutants to the eye may be potentially severer relative to inner organs and needs to be monitored. However, the cytotoxic mechanisms of NPs on the eyes remain rarely reported. This study was to screen crucial genes associated with NPs-induced retinal injuries. The gene expression profiles in the retina induced by NPs [GSE49371: Au20, Au100, Si20, Si100; GSE49048: presumptive therapeutic concentration (PTC) TiO₂, 10PTC TiO₂] and commonly used retinal cell injury models (optic nerve injury procedure: GSE55228, GSE120257 and GSE131486; hypoxia exposure: GSE173233, GSE151610, GSE135844; H₂O₂ exposure: GSE122270) were obtained from the Gene Expression Omnibus database. A total of 381 differentially expressed genes (including 372 mRNAs and 9 lncRNAs) were shared between NP exposure and the optic nerve injury model when they were compared with their corresponding controls. Function enrichment analysis of these overlapped genes showed that Tlr2, Crhbp, Ccl2, Cxcl10, Fas, Irf8, Socs3, Stat3, Gbp6, Casp1 and Syk were involved in inflammatory- and apoptotic-related processes. Protein-protein interaction network analysis revealed eight of them (Tlr2, Ccl2, Cxcl10, Irf8, Socs3, Stat3, Casp1 and Syk) were hub genes. Moreover, Socs3 could interact with upstream Stat3 and downstream Fas/Casp1/Ccl2/Cxcl10; Irf8 could interact with upstream Tlr2, Syk and downstream Cxcl10. Competing endogenous RNAs network analysis identified Socs3, Irf8, Gdf6 and Crhbp could be regulated by lncRNAs and miRNAs (9330175E14Rik-mmu-miR-762-Socs3, 6430562O15Rik-mmu-miR-207-Irf8, Gm9866-mmu-miR-669b-5p-Gdf6, 4933406C10Rik-mmu-miR-9-5p-Crhbp). CMap-CTD database analyses indicated the expression levels of Tlr2, Ccl2, Cxcl10, Fas, Irf8, Socs3, Stat3, Gbp6, Casp1 and Syk could be reversed by folic acid. Crhbp and Gdf6 were also verified to be downregulated, while Tlr2, Ccl2, Irf8, Socs3 and Stat3 were upregulated in hypoxia/H₂O₂-induced retinal injury models. Hereby, our findings suggest that Crhbp, Irf8, Socs3 and Gdf6 as well as their upstream mRNAs, lncRNAs and miRNAs may be potential monitoring biomarkers and therapeutic targets for NP-induced retinal injuries. Folic acid supplementation may be a preventive and therapeutic approach.

Bioinformatics Analysis of the Mechanisms of Diabetic Nephropathy via Novel Biomarkers and Competing Endogenous RNA Network

Diabetic nephropathy (DN) is one of the common chronic complications of diabetes with unclear molecular mechanisms, which is associated with end-stage renal disease (ESRD) and chronic kidney disease (CKD). Our study intended to construct a competing endogenous RNA (ceRNA) network via bioinformatics analysis to determine the potential molecular mechanisms of DN pathogenesis. The microarray datasets (GSE30122 and GSE30529) were downloaded from the Gene Expression Omnibus database to find differentially expressed genes (DEGs). GSE51674 and GSE155188 datasets were used to identified the differentially expressed microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), respectively. The DEGs between normal and DN renal tissues were performed using the Linear Models for Microarray (limma) package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to reveal the mechanisms of DEGs in the progression of DN. The protein-protein interactions (PPI) of DEGs were carried out by STRING database. The lncRNA-miRNA-messenger RNA (mRNA) ceRNA network was constructed and visualized via Cytoscape on the basis of the interaction generated through the miRDB and TargetScan databases. A total of 94 significantly upregulated and 14 downregulated mRNAs, 31 upregulated and 121 downregulated miRNAs, and nine upregulated and 81 downregulated lncRNAs were identified. GO and KEGG pathways enriched in several functions and expression pathways, such as inflammatory response, immune response, identical protein binding, nuclear factor kappa b (NF-κB) signaling pathway, and PI3K-Akt signaling pathway. Based on the analysis of the ceRNA network, five differentially expressed lncRNAs (DElncRNAs) (SNHG6, KCNMB2-AS1, LINC00520, DANCR, and PCAT6), five DEmiRNAs (miR-130b-5p, miR-326, miR-374a-3p, miR-577, and miR-944), and five DEmRNAs (PTPRC, CD53, IRF8, IL10RA, and LAPTM5) were demonstrated to be related to the pathogenesis of DN. The hub genes were validated by using receiver operating characteristic curve (ROC) and real-time PCR (RT-PCR). Our research identified hub genes related to the potential mechanism of DN and provided new lncRNA-miRNA-mRNA ceRNA network that contributed to diagnostic and potential therapeutic targets for DN.

CD8+T Cell-Related Gene Biomarkers in Macular Edema of Diabetic Retinopathy

BACKGROUND

CD8+T lymphocytes have a strong pro-inflammatory effect in all parts of the tissue, and some studies have demonstrated that its concentration in the vitreous increased significantly, suggesting that CD8+T cells play a pivotal role in the inflammatory response of diabetic retinopathy (DR). However, the infiltration of CD8+T cells in the DR retina, especially in diabetic macular edema (DME), and its related genes are still unclear.

METHODS

Download the GSE16036 dataset from the Gene Expression Omnibus (GEO) database. The ImmuCellAI program was performed to evaluate the abundance of 24 immune cells including CD8+T cells. The CD8+T cell-related genes (DECD8+TRGs) between non-proliferative diabetic retinopathy (NPDR) and DME were detected via difference analysis and correlation analysis. Enrichment analysis and protein-protein interaction (PPI) network mapping were implemented to explore the potential function of DECD8+TRGs. Lasso regression, support vector machine recursive feature elimination (SVM-RFE), CytoHubba plug-in and MCODE plug-in in Cytoscape software, and Weighted Gene Co-Expression Network Analysis (WGCNA) were performed to comprehensively analyze and obtain Hub DECD8+TRGs. Hub DECD8+TRGs expression patterns were further validated in other two DR-related independent datasets. The CD8+TRG score was defined as the genetic characterization of Hub DECD8+TRGs using the GSVA sample scoring method, which can be administered to distinguish early and advanced diabetic nephropathy (DN) as well as normal and DN. Finally, the transcription level of DECD8+TRGs in DR model mouse were verified by quantitative real-time PCR (qPCR).

RESULTS

A total of 371 DECD8+TRGs were identified, of which 294 genes were positively correlated and only 77 genes were negatively correlated. Eight genes (IKZF1, PTPRC, ITGB2, ITGAX, TLR7, LYN, CD74, SPI1) were recognized as Hub DECD8+TRGs. DR and DN, which have strong clinical correlation, have been proved to be associated with CD8+T cell-related hub genes by multiple independent data sets. Hub DECD8+TRGs can not only distinguish PDR from normal and DN from normal, but also play a role in the early and progressive stages of the two diseases (NPDR vs DME, Early DN vs Advanced DN). The qPCR transcription level and trend of Hub DECD8+TRGs in DR mouse model was basically the same as that in human transcriptome.

CONCLUSION

This study not only increases our understanding of the molecular mechanism of CD8+T cells in the progression of DME, but also expands people's cognitive vision of the molecular mechanism of crosstalk of CD8+T cells in the eyes and kidneys of patients with diabetes.