Identification of the Relationship between Hub Genes and Immune Cell Infiltration in Vascular Endothelial Cells of Proliferative Diabetic Retinopathy Using Bioinformatics Methods

Identification of immune-related endoplasmic reticulum stress genes in proliferative diabetic retinopathy using bioinformatics analysis

Background

Proliferative diabetic retinopathy (PDR) is a severe complication of diabetes, and understanding its molecular mechanisms is crucial. Endoplasmic reticulum (ER) stress has been implicated in various diseases, including diabetic complications. This study aims to elucidate ER stress-related biomarkers in PDR, providing insights into the underlying molecular pathways.

Methods

We analyzed two independent PDR datasets, GSE102485 and GSE60436. The GSE102485 dataset (22 PDR and 3 normal samples) was the primary dataset for comprehensive analyses, including differential expression, functional enrichment, PPI network construction, immune cell infiltration, and drug prediction. The GSE60436 dataset (6 PDR and 3 normal samples) was used for validation. In vitro experiments using human umbilical vein endothelial cells (HUVECs) in a high-glucose environment were conducted to validate key bioinformatics outcomes. Western blotting assessed protein levels of ER stress markers (TRAM1 and TXNIP).

Results

Differential expression analysis identified 2451 genes, including 328 ER stress-related genes. Functional analysis revealed enrichment in ER stress-related processes and pathways. Hub genes (BCL2, CCL2, IL-1β, TLR4, TNF, TP53) were identified, and immune infiltration analysis showed altered immune cell proportions. Validation in GSE60436 and in vitro confirmed ER stress gene dysregulation. Drug prediction suggested potential small molecules targeting ER stress markers.

Conclusion

This study provides a comprehensive molecular characterization of ER stress in PDR, highlighting altered biological processes, immune changes, and potential therapeutic targets. The identified hub genes and small molecules offer avenues for further investigation and therapy development, enhancing understanding of PDR pathogenesis and aiding targeted intervention creation.

Macrophage activation contributes to diabetic retinopathy

Diabetic retinopathy (DR) is recognized as a neurovascular complication of diabetes, and emerging evidence underscores the pivotal role of inflammation in its pathophysiology. Macrophage activation is increasingly acknowledged as a key contributor to the onset and progression of DR. Different populations of macrophages originating from distinct sources contribute to DR-associated inflammation. Retinal macrophages can be broadly categorized into two main groups based on their origin: intrinsic macrophages situated within the retina and vitreoretinal interface and macrophages derived from infiltrating monocytes. The former comprises microglia (MG), perivascular macrophages, and macrophage-like hyalocytes. Retinal MG, as the principal population of tissue-resident population of mononuclear phagocytes, exhibits high heterogeneity and plasticity while serving as a crucial connector between retinal capillaries and synapses. This makes MG actively involved in the pathological processes across various stages of DR. Activated hyalocytes also contribute to the pathological progression of advanced DR. Additionally, recruited monocytes, displaying rapid turnover in circulation, augment the population of retinal macrophages during DR pathogenesis, exerting pathogenic or protective effect based on different subtypes. In this review, we examine novel perspectives on macrophage biology based on recent studies elucidating the diversity of macrophage identity and function, as well as the mechanisms influencing macrophage behavior. These insights may pave the way for innovative therapeutic strategies in the management of DR.

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

Objective

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.

Methods

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.

Results

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.

Conclusion

APAF1 is a novel biomarker for DR and APAF1 silencing inhibits the development of DR by suppressing caspase-3/GSDME-dependent pyroptosis.

Diabetes and high-glucose could upregulate the expression of receptor for activated C kinase 1 in retina

BACKGROUND

Diabetic retinopathy (DR) is a major ocular complication of diabetes mellitus, leading to visual impairment. Retinal pigment epithelium (RPE) injury is a key component of the outer blood retinal barrier, and its damage is an important indicator of DR. Receptor for activated C kinase 1 (RACK1) activates protein kinase C-ε (PKC-ε) to promote the generation of reactive oxygen species (ROS) in RPE cells, leading to apoptosis. Therefore, we hypothesize that the activation of RACK1 under hypoxic/high-glucose conditions may promote RPE cell apoptosis by modulating PKC-ε/ROS, thereby disrupting the barrier effect of the outer blood retinal barrier and contributing to the progression of DR.

AIM

To investigate the role and associated underlying mechanisms of RACK1 in the development of early DR.

METHODS

In this study, Sprague-Dawley rats and adult RPE cell line-19 (ARPE-19) cells were used as in vivo and in vitro models, respectively, to explore the role of RACK1 in mediating PKC-ε in early DR. Furthermore, the impact of RACK1 on apoptosis and barrier function of RPE cells was also investigated in the former model.

RESULTS

Streptozotocin-induced diabetic rats showed increased apoptosis and up-regulated expression of RACK1 and PKC-ε proteins in RPE cells following a prolonged modeling. Similarly, ARPE-19 cells exposed to high glucose and hypoxia displayed elevated mRNA and protein levels of RACK1 and PKC-ε, accompanied by an increases in ROS production, apoptosis rate, and monolayer permeability. However, silencing RACK1 significantly downregulated the expression of PKC-ε and ROS, reduced cell apoptosis and permeability, and protected barrier function.

CONCLUSION

RACK1 plays a significant role in the development of early DR and might serve as a potential therapeutic target for DR by regulating RPE apoptosis and barrier function.

Integrative analysis of Mendelian randomization and gene expression profiles reveals a null causal relationship between adiponectin and diabetic retinopathy

Observational studies have been conducted to investigate the correlation between adiponectin and diabetic retinopathy (DR), but no consistent relationship has been established. In this study, we employed an integrative analysis that combined Mendelian randomization (MR) and bioinformatics analyses to comprehensively explore the association between DR and adiponectin, aiming to provide a unified answer of their relationship. Using the inverse-variance weighted (IVW) method, the odd ratio (OR) of developing DR per 1 mg/dL increment in genetically predicted log-transformed adiponectin concentration was estimated to be 0.949 (P = 0.557). Other robust MR methods produced consistent results, confirming the absence of a causal effect of adiponectin on DR. Additionally, the expression levels of the six adiponectin-related genes showed no significant differences among normal controls, individuals with diabetes but without DR, and those with DR Furthermore, the biological pathways enriched by these genes were not strongly relevant to DR. At both the individual gene and pathway levels, there were no overlaps between the adiponectin-related genes and the differentially expressed genes, indicating a lack of association between adiponectin and DR based on gene expression profiles. In summary, the integrative analysis, which combined MR and bioinformatics data mining, yielded compelling evidence supporting the notion that adiponectin is not a risk factor for DR.

The Notch signaling-regulated angiogenesis in rheumatoid arthritis: pathogenic mechanisms and therapeutic potentials

Angiogenesis plays a key role in the pathological process of inflammation and invasion of the synovium, and primarily drives the progression of rheumatoid arthritis (RA). Recent studies have demonstrated that the Notch signaling may represent a new therapeutic target of RA. Although the Notch signaling has been implicated in the M1 polarization of macrophages and the differentiation of lymphocytes, little is known about its role in angiogenesis in RA. In this review, we discourse the unique roles of stromal cells and adipokines in the angiogenic progression of RA, and investigate how epigenetic regulation of the Notch signaling influences angiogenesis in RA. We also discuss the interaction of the Notch-HIF signaling in RA's angiogenesis and the potential strategies targeting the Notch signaling to improve the treatment outcomes of RA. Taken together, we further suggest new insights into future research regarding the challenges in the therapeutic strategies of RA.

Identification of biomarkers associated with immune scores in diabetic retinopathy

Background

Diabetic retinopathy (DR) causes irreversible visual impairment in diabetes mellitus (DM) patients. Immunity played a crucial role in DR. Nevertheless, the triggering mechanism of DR was not yet thorough enough. Herein, we aim to identify the immune-associated genes as biomarkers associated with immune scores that can distinguish early DR from DM without DR.

Methods

In this study, total RNA of peripheral blood mononuclear cell (PBMC) samples from 15 non-proliferative DR patients and 15 DM patients without DR were collected and the transcriptome sequencing data were extracted. Firstly, the target genes were obtained by intersecting the differentially expressed genes (DEGs), which were screened by "limma", and the module genes (related to immune scores), which were screened by "WGCNA". In order to screen for the crucial genes, three machine learning algorithms were implemented, and a receiver operating characteristic (ROC) curve was used to obtain the diagnostic genes. Moreover, the gene set enrichment analysis (GSEA) was performed to understand the function of diagnostic genes, and analysis of the proportions of immune cells and their association with diagnostic genes was performed to analyze the pathogenesis of DR. Furthermore, the regulatory network of TF-mRNA-miRNA was built to reveal the possible regulation of diagnostic genes. Finally, the quantitative real-time polymerase chain reaction (qRT-PCR) was performed to verify the mRNA level of diagnostic genes.

Results

A total of three immune-associated diagnostic genes, namely, FAM209B, POM121L1P, and PTGES, were obtained, and their expression was increased in PBMC samples of DR, and qRT-PCR results confirmed these results. Moreover, the functions of these genes were associated with immune response. The expression of POM121L1P and PTGES was significantly negatively associated with naive B cells, and the expression of FAM209B was significantly negatively associated with immature dendritic cells. Moreover, ESR1 could regulate both FAM209B and PTGES.

Conclusion

This study identified three immune-associated diagnostic genes, FAM209B, POM121L1P, and PTGES, as biomarkers associated with immune scores in DR for the first time. This finding might proffer a novel perspective of the triggering mechanism of DR, and help to understand the role of immune-associated genes in the molecular mechanism of DR more deeply.

Immune responses of different COVID-19 vaccination strategies by analyzing single-cell RNA sequencing data from multiple tissues using machine learning methods

Multiple types of COVID-19 vaccines have been shown to be highly effective in preventing SARS-CoV-2 infection and in reducing post-infection symptoms. Almost all of these vaccines induce systemic immune responses, but differences in immune responses induced by different vaccination regimens are evident. This study aimed to reveal the differences in immune gene expression levels of different target cells under different vaccine strategies after SARS-CoV-2 infection in hamsters. A machine learning based process was designed to analyze single-cell transcriptomic data of different cell types from the blood, lung, and nasal mucosa of hamsters infected with SARS-CoV-2, including B and T cells from the blood and nasal cavity, macrophages from the lung and nasal cavity, alveolar epithelial and lung endothelial cells. The cohort was divided into five groups: non-vaccinated (control), 2*adenovirus (two doses of adenovirus vaccine), 2*attenuated (two doses of attenuated virus vaccine), 2*mRNA (two doses of mRNA vaccine), and mRNA/attenuated (primed by mRNA vaccine, boosted by attenuated vaccine). All genes were ranked using five signature ranking methods (LASSO, LightGBM, Monte Carlo feature selection, mRMR, and permutation feature importance). Some key genes that contributed to the analysis of immune changes, such as RPS23, DDX5, PFN1 in immune cells, and IRF9 and MX1 in tissue cells, were screened. Afterward, the five feature sorting lists were fed into the feature incremental selection framework, which contained two classification algorithms (decision tree [DT] and random forest [RF]), to construct optimal classifiers and generate quantitative rules. Results showed that random forest classifiers could provide relative higher performance than decision tree classifiers, whereas the DT classifiers provided quantitative rules that indicated special gene expression levels under different vaccine strategies. These findings may help us to develop better protective vaccination programs and new vaccines.

Multifaceted functions of RPS27a: An unconventional ribosomal protein

The ribosomal protein S27a (RPS27a) is cleaved from the fusion protein ubiquitin-RPS27a (Ub-RPS27a). Generally, Ub and RPS27a are coexpressed as a fusion protein but function independently after Ub is cleaved from RPS27a by a deubiquitinating enzyme. As an RP, RPS27a assembles into ribosomes, but it also functions independently of ribosomes. RPS27a is involved in the development and poor prognosis of various cancers, such as colorectal cancer, liver cancer, chronic myeloid leukemia, and renal carcinoma, and is associated with poor prognosis. Notably, the murine double minute 2/P53 axis is a major pathway through which RPS27a regulates cancer development. Moreover, RPS27a maintains sperm motility, regulates winged aphid indirect flight muscle degeneration, and facilitates plant growth. Additionally, RPS27a is a metalloprotein and mercury (Hg) biomarker. In the present review, we described the origin, structure, and biological functions of RPS27a.

Probable Treatment Targets for Diabetic Retinopathy Based on an Integrated Proteomic and Genomic Analysis

Purpose

Using previously approved medications for new indications can expedite the lengthy and expensive drug development process. We describe a bioinformatics pipeline that integrates genomics and proteomics platforms to identify already-approved drugs that might be useful to treat diabetic retinopathy (DR).

Methods

Proteomics analysis of vitreous humor samples from 12 patients undergoing pars plana vitrectomy for DR and a whole genome dataset (UKBiobank TOPMed-imputed) from 1330 individuals with DR and 395,155 controls were analyzed independently to identify biological pathways associated with DR. Common biological pathways shared between both datasets were further analyzed (STRING and REACTOME analyses) to identify target proteins for probable drug modulation. Curated target proteins were subsequently analyzed by the BindingDB database to identify chemical compounds they interact with. Identified chemical compounds were further curated through the Expasy SwissSimilarity database for already-approved drugs that interact with target proteins.

Results

The pathways in each dataset (proteomics and genomics) converged in the upregulation of a previously unknown pathway involved in DR (RUNX2 signaling; constituents MMP-13 and LGALS3), with an emphasis on its role in angiogenesis and blood-retina barrier. Bioinformatics analysis identified U.S. Food and Drug Administration (FDA)-approved medications (raltitrexed, pemetrexed, glyburide, probenecid, clindamycin hydrochloride, and ticagrelor) that, in theory, may modulate this pathway.

Conclusions

The bioinformatics pipeline described here identifies FDA-approved drugs that can be used for new alternative indications. These theoretical candidate drugs should be validated with experimental studies.

Translational Relevance

Our study suggests possible drugs for DR treatment based on an integrated proteomics and genomics pipeline. This approach can potentially expedite the drug discovery process by identifying already-approved drugs that might be used for new indications.

Identification of SMIM1 and SEZ6L2 as Potential Biomarkers for Genes Associated with Intervertebral Disc Degeneration in Pyroptosis

Background. Inflammatory reactions and pyroptosis play an important role in the pathology of intervertebral disc degeneration (IDD). The aim of the present study was to investigate pyroptosis in the nucleus pulposus cells (NPCs) of inflammatory induced IDD by bioinformatic methods and to search for possible diagnostic biomarkers. Methods. Gene expression profiles related to IDD were downloaded from the GEO database to identify differentially expressed genes (DEGs) between inflammation-induced IDD and non-inflammatory intervention samples. Pyroptosis genes were then searched for, and their expression in IDD was analyzed. Weighted gene co-expression network analysis (WGCNA) was then used to search for modules of IDD genes associated with pyroptosis and intersected with DEGs to discover candidate genes that would be diagnostically valuable. A LASSO model was developed to screen for genes that met the requirements, and ROC curves were created to clarify the diagnostic value of the genetic markers. Ultimately, the screened genes were further validated, and their diagnostic value assessed by selecting gene sets from the GEO database. RT-PCR was used to assess the mRNA expression of diagnostic markers in the nucleus pulposus (NP). Pan-cancer analysis was applied to demonstrate the expression and prognostic value of the screened genes in various tumors. Results. A total of 733 DEGs were identified in GSE41883 and GSE27494, which were mainly enriched in transmembrane receptor protein serine/threonine, kinase signaling pathway, response to lipopolysaccharide, and other biological processes, and they were mainly related to TGF beta signaling pathway, toll-like receptor signaling pathway, and TNF signaling pathway. A total of 81 genes related to pyroptosis were identified in the literature, and eight genes related to IDD were identified in the Veen diagram, namely, IL1A, IL1B, NOD2, GBP1, IL6, AK1, EEF2K, and PYCARD. Eleven candidate genes were obtained after locating the intersection of pyroptosis-related module genes and DEGs according to WGCNA analysis. A total of six valid genes were obtained after constructing a machine learning model, and five key genes were finally identified after correlation analysis. GSE23132 and GSE56081 validated the candidate genes, and the final IDD-related diagnostic markers were obtained as SMIM1 and SEZ6L2. RT-PCR results indicated that the mRNA expression of both was significantly elevated in IDD. The pan-cancer analysis demonstrated that SMIM1 and SEZ6L2 have important roles in the expression and prognosis of various tumors. Conclusion. In conclusion, this research identifies SMIM1 and SEZ6L2 as important biomarkers of IDD associated with pyroptosis, which will help to unravel the development and pathogenesis of IDD and determine potential therapeutic targets.

Molecular investigation of candidate genes for pyroptosis-induced inflammation in diabetic retinopathy

BACKGROUND

Diabetic retinopathy is a diabetic microvascular complication. Pyroptosis, as a way of inflammatory death, plays an important role in the occurrence and development of diabetic retinopathy, but its underlying mechanism has not been fully elucidated. The purpose of this study is to identify the potential pyroptosis-related genes in diabetic retinopathy by bioinformatics analysis and validation in a diabetic retinopathy model and predict the microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) interacting with them. Subsequently, the competing endogenous RNA (ceRNA) regulatory network is structured to explore their potential molecular mechanism.

METHODS

We obtained mRNA expression profile dataset GSE60436 from the Gene Expression Omnibus (GEO) database and collected 51 pyroptosis-related genes from the PubMmed database. The differentially expressed pyroptosis-related genes were obtained by bioinformatics analysis with R software, and then eight key genes of interest were identified by correlation analysis, Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction (PPI) network analysis. Then, the expression levels of these key pyroptosis-related genes were validated with quantitative real-time polymerase chain reaction (qRT-PCR) in human retinal endothelial cells with high glucose incubation, which was used as an in vitro model of diabetic retinopathy. Western blot was performed to measure the protein levels of gasdermin D (GSDMD), dasdermin E (GSDME) and cleaved caspase-3 in the cells. Moreover, the aforementioned genes were further confirmed with the validation set. Finally, the ceRNA regulatory network was structured, and the miRNAs and lncRNAs which interacted with CASP3, TLR4, and GBP2 were predicted.

RESULTS

A total of 13 differentially expressed pyroptosis-related genes were screened from six proliferative diabetic retinopathy patients and three RNA samples from human retinas, including one downregulated gene and 12 upregulated genes. A correlation analysis showed that there was a correlation among these genes. Then, KEGG pathway and GO enrichment analyses were performed to explore the functional roles of these genes. The results showed that the mRNA of these genes was mainly related to inflammasome complex, interleukin-1 beta production, and NOD-like receptor signaling pathway. In addition, eight hub genes-CASP3, TLR4, NLRP3, GBP2, CASP1, CASP4, PYCARD, and GBP1-were identified by PPI network analysis using Cytoscape software. High glucose increased the protein level of GSDMD and GSDME, as critical effectors of pyroptosis, in retinal vascular endothelial cells. Verified by qRT-PCR, the expression of all these eight hub genes in the in vitro model of diabetic retinopathy was consistent with the results of the bioinformatics analysis of mRNA chip. Among them, CASP4, GBP1, CASP3, TLR4, and GBP2 were further validated in the GSE179568 dataset. Finally, 20 miRNAs were predicted to target three key genes-CASP3, GBP2, and TLR4, and 22 lncRNAs were predicted to potentially bind to these 20 miRNAs. Then, we constructed a key ceRNA network that is expected to mediate cellular pyroptosis in diabetic retinopathy.

CONCLUSION

Through the data analysis of the GEO database by R software and verification by qRT-PCR and validation set, we successfully identified potential pyroptosis-related genes involved in the occurrence of diabetic retinopathy. The key ceRNA regulatory network associated with these genes was structured. These findings might improve the understanding of molecular mechanisms underlying pyroptosis in diabetic retinopathy.