Cytoskeleton-associated protein 2 (CKAP2) is regulated by vascular endothelial growth factor and p53 in retinal capillary endothelial cells under high-glucose conditions

Unveiling ferroptosis genes and inhibitors in diabetic retinopathy through single-cell analysis and docking simulations

Diabetic retinopathy (DR) is a common microvascular complication of diabetes and a leading cause of vision loss worldwide. Although several mechanisms have been implicated in the pathogenesis of DR, emerging evidence suggests a link between ferroptosis and DR. Unfortunately, the exact mechanism underlying this connection is not clear. Therefore, investigating the role of ferroptosis in diabetic retinopathy holds promise for advancing our understanding of this complex disease and developing innovative treatments. We have identified differentially expressed genes (DEGs) and differentially expressed marker genes (DEMGs) from open-source single-cell RNA sequencing datasets by using in depth in silico approach. Subsequently, ferroptosis-associated DEGs (FA-DEGs), ferroptosis-associated DEMGs (FA-DEMGs), and ferroptosis-associated Hub Genes (FAHGs) were identified. The FDA-approved drugs for our target proteins were also identified, and their ADMET properties were assessed. Molecular docking and simulation were utilized to explore the interaction stability of the compounds with the target proteins. Overall, we identified 63 FA-DEMGs that were significantly enriched in Peroxiredoxin activity, Ferroptosis, Mitophagy, and Autophagy. Further analysis predicted that PRDX1 and UBC are candidate target proteins. Molecular docking results showed that dexamethasone has a high binding affinity for both PRDX1 and UBC. Additionally, molecular dynamics simulations revealed that dexamethasone (which showed the best hit in the docking analysis) exhibited a 'stable effect' on both PRDX1 and UBC. To summarize, this study showed that PRDX1 and UBC could be suitable therapeutic targets for dexamethasone, which might be helpful in the advance of DR treatments in the future.

Differential Expression of mRNA in Peripheral Blood Mononuclear Cells May Predict Postoperative Atrial Fibrillation in Coronary Artery Bypass Surgery Patients

Postoperative Atrial Fibrillation (POAF) frequently follows Coronary Artery Bypass Grafting (CABG) surgery. This prospective study investigates genes linked to POAF in CABG patients, aiming to create a predictive model. Employing differential gene and methylation analyses, the study identified four genes (WARS2, CKAP2, CHI3L1, HSD17B6) associated with POAF. Preoperative plasma samples and clinical data were collected from 139 CABG patients, categorized into POAF (+) (43) and POAF (-) (96). Real-time quantitative PCR assessed gene expression, and a predictive model using the LASSO method demonstrated robust performance, with AUC values of 0.8895 in the training set and 0.7840 in the test set. This pioneering study integrates genomics and clinical data, suggesting WARS2, CKAP2, and CHI3L1 as potential indicators for POAF prediction.

Identification and validation of ferroptosis-related genes for diabetic retinopathy

Diabetic retinopathy (DR) is a leading cause of blindness, and ferroptosis may be an essential component of the pathological process of DR. In this study, we aimed to screen five hub genes (TLR4, CAV1, HMOX1, TP53, and IL-1B) using bioinformatics analysis and experimentally verify their expression and effects on ferroptosis and cell function. The online Gene Expression Omnibus microarray expression profiling datasets GSE60436 and GSE1025485 were selected for investigation. Ferroptosis-related genes that might be differentially expressed in DR were identified. Then, Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein-protein interaction (PPI) network analyses were conducted to characterize the differentially-expressed ferroptosis-related genes. After tissue-specific analyses and external dataset validation of hub genes, the mRNA and protein levels of hub genes in retinal microvascular endothelial cells (HRMECs) symbiotic with high glucose were verified using real-time quantitative PCR (qRT-PCR) and immunocytochemistry (ICC). Finally, hub genes were knocked down using siRNA, and changes in ferroptosis and cell function were observed. Based on the differential expression analysis, 19 ferroptosis-related genes were identified. GO and KEGG enrichment analyses showed that ferroptosis-related genes were significantly enriched in reactive oxygen species metabolic processes, necrotic cell death, hypoxia responses, iron ion responses, positive regulation of cell migration involved in sprouting angiogenesis, NF-kappa B signaling pathway, ferroptosis, fluid shear stress, and atherosclerosis. Subsequently, PPI network analysis and critical module construction were used to identify five hub genes. Based on bioinformatics analysis of mRNA microarrays, qRT-PCR confirmed higher mRNA expression of five genes in the DR model, and immunocytochemistry confirmed their higher protein expression. Finally, siRNA interference was used to verify the effects of five genes on ferroptosis and cell function. Based on bioinformatics analysis, five potential genes related to ferroptosis were identified, and their upregulation may affect the onset or progression of DR. This study sheds new light on the pathogenesis of DR.

Identification and comprehensive analysis of ferroptosis-related genes as potential biomarkers for the diagnosis and treatment of proliferative diabetic retinopathy by bioinformatics methods

Diabetic retinopathy (DR) is the most common retinal vascular disease. Proliferative DR (PDR) is the aggressive stage of DR with angiogenesis as a pathological hallmark, which is the main cause of blindness. There is growing evidence that ferroptosis plays a vital role in diabetics as well as its complications including DR. However, the potential functions and mechanisms of ferroptosis have not been completely elucidated in PDR. The ferroptosis-related differentially expressed genes (FRDEGs) were identified in GSE60436 and GSE94019. Then we constructed a protein-protein interaction (PPI) network and screened ferroptosis-related hub genes (FRHGs). The GO functional annotation and the KEGG pathway enrichment analyses of FRHGs were performed. The miRNet and miRTarbase databases were applied to construct the ferroptosis-related mRNA-miRNA-lncRNA network, and the Drug-Gene Interaction Database (DGIdb) was used for predicting potential therapeutic drugs. Finally, we identified 21 upregulated and 9 downregulated FRDEGs, among which 10 key target genes (P53, TXN, PTEN, SLC2A1, HMOX1, PRKAA1, ATG7, HIF1A, TGFBR1, and IL1B) were recognized with enriched functions, mainly relating to responses to oxidative stress and hypoxia in biological processes of PDR. HIF-1, FoxO and MAPK signalling may be the main pathways that influence ferroptosis in PDR. Moreover, a mRNA-miRNA-lncRNA network was constructed based on the 10 FRHGs and their co-expressed miRNAs. Finally, potential drugs targeting 10 FRHGs for PDR were predicted. Results of the receiver operator characteristic (ROC) curve indicated, with high predictive accuracy in two testing datasets (AUC>0.8), that ATG7, TGFB1, TP53, HMOX1 and ILB1 had the potential to be biomarkers of PDR.

Identification of potential ferroptosis-related biomarkers and a pharmacological compound in diabetic retinopathy based on machine learning and molecular docking

BACKGROUND

Diabetic retinopathy (DR), a neurovascular disease, is a leading cause of visual loss worldwide and severely affects quality of life. Several studies have shown that ferroptosis plays an important role in the pathogenesis of DR; however, its molecule mechanism remains incompletely elucidated. Hence, this study aimed to investigate the pathogenesis of ferroptosis and explore potential ferroptosis-related gene biomarkers and a pharmacological compound for treating DR.

METHODS

Ferroptosis-related differentially expressed genes (DEGs) were identified in the GSE102485 dataset. Functional enrichment analyses were then performed and a protein-protein interaction (PPI) network was constructed to screen candidates of ferroptosis-related hub genes (FRHGs). FRHGs were further screened based on least absolute shrinkage and selection operator (LASSO) regression and random forest algorithms, and were then validated with the GSE60436 dataset and previous studies. A receiver operating characteristic (ROC) curve monofactor analysis was conducted to evaluate the diagnostic performance of the FRHGs, and immune infiltration analysis was performed. Moreover, the pharmacological compound targeting the FRHGs were verified by molecular docking. Finally, the FRHGs were validated using quantitative real-time polymerase chain reaction (qRT-PCR) analysis.

RESULTS

The 40 ferroptosis-related DEGs were extracted, and functional enrichment analyses mainly implicated apoptotic signaling, response to oxidative stress, ferroptosis, and lipid and atherosclerosis pathways. By integrating the PPI, LASSO regression, and random forest analyses to screen the FRHGs, and through validation, we identified five FRHGs that performed well in the diagnosis (CAV1, CD44, NOX4, TLR4, and TP53). Immune infiltration analysis revealed that immune microenvironment changes in DR patients may be related to these five FRHGs. Molecular docking also showed that glutathione strongly bound the CAV1 and TLR4 proteins. Finally, the upregulated expression of FRHGs (CD44, NOX4, TLR4, and TP53) was validated by qRT-PCR analysis in human retinal capillary endothelial cells cultured under high-glucose environment.

CONCLUSIONS

CAV1, CD44, NOX4, TLR4, and TP53 are potential biomarkers for DR and may be involved in its occurrence and progression by regulating ferroptosis and the immune microenvironment. Further, glutathione exhibits potential therapeutic efficacy on DR by targeting ferroptosis. Our study provides new insights into the ferroptosis-related pathogenesis of DR, as well as its diagnosis and treatment.