Ferroptosis: A New Regulatory Mechanism in Osteoporosis

Ferroptosis as a mechanism of non-ferrous metal toxicity

Ferroptosis is a recently discovered form of regulated cell death, implicated in multiple pathologies. Given that the toxicity elicited by some metals is linked to alterations in iron metabolism and induction of oxidative stress and lipid peroxidation, ferroptosis might be involved in such toxicity. Although direct evidence is insufficient, certain pioneering studies have demonstrated a crosstalk between metal toxicity and ferroptosis. Specifically, the mechanisms underlying metal-induced ferroptosis include induction of ferritinophagy, increased DMT-1 and TfR cellular iron uptake, mitochondrial dysfunction and mitochondrial reactive oxygen species (mitoROS) generation, inhibition of Xc-system and glutathione peroxidase 4 (GPX4) activity, altogether resulting in oxidative stress and lipid peroxidation. In addition, there is direct evidence of the role of ferroptosis in the toxicity of arsenic, cadmium, zinc, manganese, copper, and aluminum exposure. In contrast, findings on the impact of cobalt and nickel on ferroptosis are scant and nearly lacking altogether for mercury and especially lead. Other gaps in the field include limited studies on the role of metal speciation in ferroptosis and the critical cellular targets. Although further detailed studies are required, it seems reasonable to propose even at this early stage that ferroptosis may play a significant role in metal toxicity, and its modulation may be considered as a potential therapeutic tool for the amelioration of metal toxicity.

Identification of ferroptosis-associated biomarkers for the potential diagnosis and treatment of postmenopausal osteoporosis

OBJECTIVE

Postmenopausal osteoporosis (PMOP) is one of the most commonly occurring conditions worldwide and is characterized by estrogen deficiency as well as persistent calcium loss with age. The aim of our study was to identify significant ferroptosis-associated biomarkers for PMOP.

METHODS AND MATERIALS

We obtained our training dataset from the Gene Expression Omnibus (GEO) database using GSE56815 expression profiling data. Meanwhile, we extracted ferroptosis-associated genes for further analysis. Differentially expressed ferroptosis-associated genes (DEFAGs) between OP patients and normal controls were selected using the "limma" package. We established a ferroptosis-associated gene signature using training models, specifically, random forest (RF) and support vector machine (SVM) models. It was further validated in another dataset (GSE56814) which also showed a high AUC: 0.98, indicating high diagnostic value. Using consensus clustering, the OP patient subtypes were identified. A ferroptosis associated gene (FAG)-Scoring scheme was developed by PCA. The important candidate genes associated with OP were also compared between different ferrclusters and geneclusters.

RESULTS

There were significant DEFAGs acquired, of which five (HMOX1, HAMP, LPIN1, MAP3K5, FLT3) were selected for establishing a ferroptosis-associated gene signature. Analyzed from the ROC curve, our established RF model had a higher AUC value than the SVM model (RF model AUC:1.00). Considering these results, the established RF model was chosen to be the most appropriate training model. Later, based on the expression levels of the five DEFAGs, a clinical application nomogram was established. The OP patients were divided into two subtypes (ferrcluster A, B and genecluster A, B, respectively) according to the consensus clustering method based on DEFAGs and differentially expressed genes (DEGs). Ferrcluster B and genecluster B had higher ferroptosis score than ferrcluster A and genecluster A, respectively. The expression of COL1A1 gene was significantly higher in ferrcluster B and gencluster B compared with ferrcluster A and gencluster A, respectively, while there is no statistical difference in term of VDR gene, COL1A2 genes, and PTH gene expressions between ferrcluster A and B, together with gencluster A and B.

CONCLUSIONS

On the basis of five explanatory variables (HMOX1, HAMP, LPIN1, MAP3K5 and FLT3), we developed a diagnostic ferroptosis-associated gene signature and identified two differently categorized OP subtypes that may potentially be applied for the early diagnosis and individualized treatment of PMOP. The ER gene, VDR gene, IL-6 gene, COL1A1 and COL1A2 genes, and PTH gene are important candidate gene of OP, however, more studies are still anticipated to further elucidate the relationship between these genes and ferroptosis in OP.

Ferroptosis: A potential target for the intervention of intervertebral disc degeneration

Ferroptosis, an iron-dependent form of programmed cell death marked by phospholipid peroxidation, is regulated by complex cellular metabolic pathways including lipid metabolism, iron balance, redox homeostasis, and mitochondrial activity. Initial research regarding the mechanism of ferroptosis mainly focused on the solute carrier family 7 member 11/glutathione/glutathione peroxidase 4 (GPX4) signal pathway. Recently, novel mechanisms of ferroptosis, independent of GPX4, have been discovered. Numerous pathologies associated with extensive lipid peroxidation, such as drug-resistant cancers, ischemic organ injuries, and neurodegenerative diseases, are driven by ferroptosis. Ferroptosis is a new therapeutic target for the intervention of IVDD. The role of ferroptosis in the modulation of intervertebral disc degeneration (IVDD) is a significant topic of interest. This is a novel research topic, and research on the mechanisms of IVDD and ferroptosis is ongoing. Herein, we aim to review and discuss the literature to explore the mechanisms of ferroptosis, the relationship between IVDD and ferroptosis, and the regulatory networks in the cells of the nucleus pulposus, annulus fibrosus, and cartilage endplate to provide references for future basic research and clinical translation for IVDD treatment.

Identification and validation of ferroptosis key genes in bone mesenchymal stromal cells of primary osteoporosis based on bioinformatics analysis

Primary osteoporosis has long been underdiagnosed and undertreated. Currently, ferroptosis may be a promising research direction in the prevention and treatment of primary osteoporosis. However, the specific mechanism of ferroptosis in primary osteoporosis remains a mystery. Differentially expressed genes (DEGs) were identified in bone mesenchymal stromal cells (BMSCs) of primary osteoporosis and heathy patients from the GEO databases with the help of bioinformatics analysis. Then, we intersected these DEGs with the ferroptosis dataset and obtained 80 Ferr-DEGs. Several bioinformatics algorithms (PCA, RLE, Limma, BC, MCC, etc.) were adopted to integrate the results. Additionally, we explored the potential functional roles of the Ferr-DEGs via GO and KEGG. Protein-protein interactions (PPI) were used to predict potential interactive networks. Finally, 80 Ferr-DEGs and 5 key Ferr-DEGs were calculated. The 5 key Ferr-DEGs were further verified in the OVX mouse model. In conclusion, through a variety of bioinformatics methods, our research successfully identified 5 key Ferr-DEGs associated with primary osteoporosis and ferroptosis, namely, sirtuin 1(SIRT1), heat shock protein family A (Hsp70) member 5 (HSPA5), mechanistic target of rapamycin kinase (MTOR), hypoxia inducible factor 1 subunit alpha (HIF1A) and beclin 1 (BECN1), which were verified in an animal model.