KLHL24-Mediated Hair Follicle Stem Cells Structural Disruption Causes Alopecia

Identification and validation of ferroptosis-related biomarkers in intervertebral disc degeneration

Introduction

Ferroptosis plays a significant role in intervertebral disc degeneration (IDD). Understanding the key genes regulating ferroptosis in IDD could reveal fundamental mechanisms of the disease, potentially leading to new diagnostic and therapeutic targets.

Methods

Public datasets (GSE23130 and GSE70362) and the FerrDb database were analyzed to identify ferroptosis-related genes (DE-FRGs) involved in IDD. Single-cell RNA sequencing data (GSE199866) was used to validate the specific roles and expression patterns of these genes. Immunohistochemistry and Western blot analyses were subsequently conducted in both clinical samples and mouse models to assess protein expression levels across different tissues.

Results

The analysis identified seven DE-FRGs, including MT1G, CA9, AKR1C1, AKR1C2, DUSP1, CIRBP, and KLHL24, with their expression patterns confirmed by single-cell RNA sequencing. Immunohistochemistry and Western blot analysis further revealed that MT1G, CA9, AKR1C1, AKR1C2, DUSP1, and KLHL24 exhibited differential expression during the progression of IDD. Additionally, the study highlighted the potential immune-modulatory functions of these genes within the IDD microenvironment.

Discussion

Our study elucidates the critical role of ferroptosis in IDD and identifies specific genes, such as MT1G and CA9, as potential targets for diagnosis and therapy. These findings offer new insights into the molecular mechanisms underlying IDD and present promising avenues for future research and clinical applications.

Identification of EGFR as an essential regulator in chondrocytes ferroptosis of osteoarthritis using bioinformatics, in vivo, and in vitro study

Objective

The mechanisms of chondrocytes ferroptosis in osteoarthritis (OA) have not yet been fully elucidated. This study aimed to identify key ferroptosis related genes (FRGs) involved in chondrocytes ferroptosis.

Methods

LASSO, SVM-RFE, and receiver operating characteristic curve (ROC) were performed to screen key differentially expressed FRGs (DEFRGs). Functional analyses were conducted using GO, and KEGG analyses. Unsupervised clustering analysis was used to identify ferroptosis related patterns. The CeRNA network was constructed to predict the upstream miRNAs and lncRNAs. Finally, we validated the role of EGFR in chondrocytes ferroptosis using in vivo and in vitro experiments.

Results

A total of 42 DEFRGs were identified between OA and normal cartilages. GO and KEGG analyses indicated that these DEFRGs were significantly engaged in ferroptosis related biological processes and pathways, such as cellular response to oxidative stress, positive regulation of programmed cell death, MAPK and PI3K-Akt signaling pathways. Moreover, four key DEFRGs, including ACSF2, AURKA, EGFR, and KLHL24, were considered as potential biomarkers of OA. Moreover, two distinct ferroptosis related patterns were determined, and a total of 882 differentially expressed genes were identified which might participate in extracellular matrix degradation and inflammatory response. In addition, the CeRNA network showed that EGFR could be competitively regulated by 3 lncRNAs and 4 miRNAs. Significantly, the expression of EGFR was downregulated in human OA cartilages, OA mouse model, and erastin induced chondrocytes. EGFR inhibition could induce the occurrence of chondrocytes ferroptosis and ECM degradation which could be reversed by the addition of Ferrostatin-1.

Conclusion

Our study has identified ACSF2, AURKA, EGFR, and KLHL24 as ferroptosis-related biomarkers in OA. Furthermore, we have conducted a preliminary investigation into the role of EGFR in regulating chondrocytes ferroptosis. These findings offer novel insights into the molecular mechanisms underlying OA.

Excess KLHL24 Impairs Skin Wound Healing through the Degradation of Vimentin

Start codon variants in ubiquitin ligase KLHL24 lead to a gain-of-function mutant KLHL24-ΔN28, which mediates the excessive degradation of keratin 15, desmin, and keratin 14, resulting in alopecia, cardiopathy, and epidermolysis bullosa syndrome. Patients with alopecia, cardiopathy, and epidermolysis bullosa syndrome normally present atrophic scars after wounds heal, which is rare in KRT14-related epidermolysis bullosa. The mechanisms underlying the formation of atrophic scars in epidermolysis bullosa of patients with alopecia, cardiopathy, and epidermolysis bullosa syndrome remain unclear. This study showed that KLHL24-ΔN28 impaired skin wound healing by excessively degrading vimentin. Heterozygous Klhl24c.3G>T knock-in mice displayed delayed wound healing and decreased wound collagen deposition. We identified vimentin as an unreported substrate of KLHL24. KLHL24-ΔN28 mediated the excessive degradation of vimentin, which failed to maintain efficient fibroblast proliferation and activation during wound healing. Furthermore, by mediating vimentin degradation, KLHL24 can hinder myofibroblast activation, which attenuated bleomycin-induced skin fibrosis. These findings showed the function of KLHL24 in regulating tissue remodeling, atrophic scarring, and fibrosis.

Towards a Better Understanding of Genotype-Phenotype Correlations and Therapeutic Targets for Cardiocutaneous Genes: The Importance of Functional Studies above Prediction

Genetic variants in gene-encoding proteins involved in cell−cell connecting structures, such as desmosomes and gap junctions, may cause a skin and/or cardiac phenotype, of which the combination is called cardiocutaneous syndrome. The cardiac phenotype is characterized by cardiomyopathy and/or arrhythmias, while the skin particularly displays phenotypes such as keratoderma, hair abnormalities and skin fragility. The reported variants associated with cardiocutaneous syndrome, in genes DSP, JUP, DSC2, KLHL24, GJA1, are classified by interpretation guidelines from the American College of Medical Genetics and Genomics. The genotype−phenotype correlation, however, remains poorly understood. By providing an overview of variants that are assessed for a functional protein pathology, we show that this number (n = 115) is low compared to the number of variants that are assessed by in silico algorithms (>5000). As expected, there is a mismatch between the prediction of variant pathogenicity and the prediction of the functional effect compared to the real functional evidence. Aiding to improve genotype−phenotype correlations, we separate variants into ‘protein reducing’ or ‘altered protein’ variants and provide general conclusions about the skin and heart phenotype involved. We conclude by stipulating that adequate prognoses can only be given, and targeted therapies can only be designed, upon full knowledge of the protein pathology through functional investigation.