Ferroptosis is a type of regulated cell death driven by iron dependent accumulation of cellular reactive oxygen species (ROS) when glutathione (GSH)-dependent lipid peroxidation repair systems are compromised. Nuclear receptor co-activator 4 (NCOA4)-mediated selective autophagy of ferritin, termed ferritinophagy, involves the regulation of ferroptosis. Emerging evidence has revealed that ferritinophagy and ferroptosis exert a significant role in the occurrence and development of cardiovascular disease. In the present review, we aimed to present a brief overview of ferritinophagy and ferroptosis focusing on the underlying mechanism and regulations involved. We summarize and discuss relevant research progress on the role of ferritinophagy and ferroptosis in cardiovascular diseases accompanied with potential applications of ferritinophagy and ferroptosis modulators in the treatment of ferroptosis-associated cardiovascular diseases.

Contrast-induced acute kidney injury (CI-AKI) causes clinically acquired nephropathy in patients who undergo coronary interventions. Hypoxic injury to proximal tubular epithelial cells is a pathological mechanism of CI-AKI. Previous studies have shown that hypoxia activates HIF-1α/HE4/NF-κB to enhance renal fibrosis, and the SGLT-2 inhibitor luseogliflozin inhibits hypoxia-inducible factor (HIF)-1α expression to reduce the progression of diabetic nephropathy. However, the therapeutic effects and mechanisms of SGLT-2 inhibitors on CI-AKI are unclear. We explored the role of the HIF-1α/HE4/NF-κB pathway in CI-AKI and how dapagliflozin effectively treats CI-AKI by inhibiting this pathway. In vitro, cells were divided into the control, hypoxia, hypoxia + dapagliflozin, and hypoxia + pSilencer-HIF-1α groups. Cellular hypoxia, apoptosis, and related protein expression were evaluated by immunofluorescence, western blotting, and flow cytometry, respectively. Dapagliflozin significantly decreased oxygen consumption, HIF-1α, human epididymis protein 4 (HE4), NF-κB expression, and apoptotic cells compared with the control (P < 0.01). In vivo, rats were divided into the control (C), diabetes (D), diabetes + contrast media, and diabetes + contrast media + dapagliflozin groups. Rats in the latter 2 groups were treated with dapagliflozin for 2 days. CI-AKI was induced by intravenously injecting indomethacin, N-nitro-l-arginine methyl ester, and iohexol. The effects of dapagliflozin on CI-AKI rats were elucidated by assessing renal function, H&E staining, and immunohistochemistry. Serum creatinine, urea nitrogen, TUNEL-positive tubular cells, HIF-1α, HE4, NF-κB expression, and histopathological scores were increased in diabetes + contrast media rats compared with C, D, and diabetes + dapagliflozin + contrast media rats (P < 0.01). Thus, dapagliflozin may ameliorate CI-AKI through suppression of HIF-1α/HE4/NF-κB signaling in vitro and in vivo.

Previous studies showed that fibrinogen‐to‐albumin ratio (FAR) regarded as a novel inflammatory and thrombotic biomarker was the risk factor for coronary artery disease (CAD). In this study, we sought to evaluate the relationship between FAR and severity of CAD, long‐term prognosis in non‐ST elevation acute coronary syndrome (NSTE‐ACS) patients firstly implanted with drug‐eluting stent (DES). A total of 1138 consecutive NSTE‐ACS patients firstly implanted with DES from January 2017 to December 2018 were recruited in this study. Patients were divided into tertiles according to FAR levels (Group 1: ≤8.715%; Group 2: 8.715%~10.481%; and Group 3: >10.481%). The severity of CAD was evaluated using the Gensini Score (GS). The endpoints were major adverse cardiovascular events (MACE), including all‐cause mortality, myocardial reinfarction, and target vessel revascularization (TVR). Positive correlation was detected by Spearman’s rank correlation coefficient analysis between FAR and GS (r = 0.170, P < 0.001). On multivariate logistic analysis, FAR was an independent predictor of severe CAD (OR: 1.060; 95% CI: 1.005~1.118; P < 0.05). Multivariate Cox regression analysis indicated that FAR was an independent prognostic factor for MACE at 30 days, 6 months, and 1 year after DES implantation (HR: 1.095; 95% CI: 1.011~1.186; P = 0.025. HR: 1.076; 95% CI: 1.009~1.147; P = 0.026. HR: 1.080; 95% CI: 1.022~1.141; P = 0.006). Furthermore, adding FAR to the model of established risk factors, the C‐statistic increased from 0.706 to 0.720, 0.650 to 0.668, and 0.611 to 0.632, respectively. And the models had incremental prognostic value for MACE, especially for 1‐year MACE (NRI: 13.6% improvement, P = 0.044; IDI: 0.6% improvement, P = 0.042). In conclusion, FAR was associated independently with the severity of CAD and prognosis, helping to improve risk stratification in NSTE‐ACS patients firstly implanted with DES.

Background: Pulmonary arterial hypertension (PAH) is a devastating chronic cardiopulmonary disease without an effective therapeutic approach. The underlying molecular mechanism of PAH remains largely unexplored at single-cell resolution. Methods: Single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database (GSE210248) was included and analyzed comprehensively. Additionally, microarray transcriptome data including 15 lung tissue from PAH patients and 11 normal samples (GSE113439) was also obtained. Seurat R package was applied to process scRNA-seq data. Uniform manifold approximation and projection (UMAP) was utilized for dimensionality reduction and cluster identification, and the SingleR package was performed for cell annotation. FindAllMarkers analysis and ClusterProfiler package were applied to identify differentially expressed genes (DEGs) for each cluster in GSE210248 and GSE113439, respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) were used for functional enrichment analysis of DEGs. Microenvironment Cell Populations counter (MCP counter) was applied to evaluate the immune cell infiltration. STRING was used to construct a protein-protein interaction (PPI) network of DEGs, followed by hub genes selection through Cytoscape software and Veen Diagram. Results: Nineteen thousand five hundred seventy-six cells from 3 donors and 21,896 cells from 3 PAH patients remained for subsequent analysis after filtration. A total of 42 cell clusters were identified through UMAP and annotated by the SingleR package. 10 cell clusters with the top 10 cell amounts were selected for consequent analysis. Compared with the control group, the proportion of adipocytes and fibroblasts was significantly reduced, while CD8+ T cells and macrophages were notably increased in the PAH group. MCP counter revealed decreased distribution of CD8+ T cells, cytotoxic lymphocytes, and NK cells, as well as increased infiltration of monocytic lineage in PAH lung samples. Among 997 DEGs in GSE113439, module 1 with 68 critical genes was screened out through the MCODE plug-in in Cytoscape software. The top 20 DEGs in each cluster of GSE210248 were filtered out by the Cytohubba plug-in using the MCC method. Eventually, WDR43 and GNL2 were found significantly increased in PAH and identified as the hub genes after overlapping these DEGs from GSE210248 and GSE113439. Conclusion: WDR43 and GNL2 might provide novel insight into revealing the new molecular mechanisms and potential therapeutic targets for PAH.