Significance of m6A regulatory factor in gene expression and immune function of osteoarthritis

RNA methylation: A new perspective in osteoarthritis research

Osteoarthritis (OA) is a prevalent degenerative joint disease characterized by cartilage degradation, osteophyte formation, and joint dysfunction, significantly impairing the quality of life in the elderly population. Recently, RNA modifications, as a dynamic and reversible epigenetic modification, have emerged as critical players in the onset and progression of OA. This review systematically summarizes the major types of RNA modifications involved in OA, including N6-methyladenosine (m6A), 5-methylcytosine (m5C), and 7-methylguanosine (m7G), and explores their roles in regulating chondrocyte autophagy, inflammatory responses, and key signaling pathways. with a primary focus on RNA methylation. Special emphasis is placed on the dynamic regulatory functions of key methyltransferases (e.g., METTL3, FTO, WTAP) and their potential contributions to OA pathogenesis. Furthermore, we address current research hotspots and controversies in the field, proposing future research directions, such as leveraging single-cell sequencing to decipher dynamic RNA modification changes during OA progression and uncovering the cooperative networks among various RNA modifications. Advancing our understanding of the biological roles and mechanisms of RNA modifications holds promise for innovative strategies in the early diagnosis, disease stratification, and targeted therapy of OA.

A lactate metabolism-related gene signature to diagnose osteoarthritis based on machine learning combined with experimental validation

BACKGROUND

Lactate is gradually proved as the essential regulator in intercellular signal transduction, energy metabolism reprogramming, and histone modification. This study aims to clarify the diagnosis value of lactate metabolism-related genes in osteoarthritis (OA).

METHODS

Lactate metabolism-related genes were retrieved from the MSigDB. GSE51588 was downloaded from the Gene Expression Omnibus (GEO) as the training dataset. GSE114007, GSE117999, and GSE82107 datasets were adopted for external validation. Genomic difference detection, protein-protein interaction network analysis, LASSO, SVM-RFE, Boruta, and univariate logistic regression (LR) analyses were used for feature selection. Multivariate LR, Random Forest (RF), Support Vector Machine (SVM), and XGBoost (XGB) were used to develop the multiple-gene diagnosis models. 12 control and 12 OA samples were collected from the local hospital for re-verification. The transfection assays were conducted to explore the regulatory ability of the gene to the apoptosis and vitality of chondrocytes.

RESULTS

Through the bioinformatical analyses and machine learning algorithms, SLC2A1 and NDUFB9 of the 273 lactate metabolism-related genes were identified as the significant diagnosis biomarkers. The LR, RF, SVM, and XGB models performed impressively in the cohorts (AUC > 0.7). The local clinical samples indicated that SLC2A1 and NDUFB9 were both down-regulated in the OA samples (both P < 0.05). The knockdown of NDUFB9 inhibited the viability and promoted the apoptosis of the CHON-001 cells treated with IL-1beta (both P < 0.05).

CONCLUSIONS

A lactate metabolism-related gene signature was constructed to diagnose OA, which was validated in multiple independent cohorts, local clinical samples, and cellular functional experiments.

Identification of the shared gene MXD3 signatures and biological mechanism in patients with hip pain and prostate cancer

Prostate cancer (PRAD) is recognized as having a significant effect on systemic illnesses. This study examined possible immune cells, metabolic pathways, and genes that may explain the interaction between PRAD and hip pain. We used information retrieved from the Cancer Genome Atlas and the Gene Expression Omnibus databases. To find common genes, we utilized differential expression analysis and weighted gene co-expression network analysis. The genes that were shared were subjected to pathway enrichment studies using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. Additionally, hub genes were analyzed using LASSO regression, and a receiver operating characteristic curve was generated based on the screening outcomes. The genes for the nodes were chosen in a protein-protein interaction network that was built. Single-sample gene-set enrichment analysis was performed to identify the differentially expressed genes. Immunohistochemistry staining confirmed hub gene expression, and single-sample gene-set enrichment analysis assessed immune cell infiltration. We concluded by comparing MAX dimerization protein 3 (MXD3) and MAX interactor 1 (MXI1) expression in tumor tissues using Uniform Manifold Approximation and Projection and violin plots in the Tumor lmmune Single-cell Hub database. After analyzing the intersection of the differentially expressed genes and weighted gene co-expression network analysis-significant module genes, we determined that MXD3 was the best shared diagnostic biomarker for PRAD and hip pain. One potential predictor of PRAD development was the MXI1 node gene, which was found in the protein-protein interaction network. The analyses revealed that MXD3 had a relatively positive correlation with neutrophil and T-helper cell infiltration levels, whereas MXI1 had a negative correlation with mast and Tgd cell levels. Tumors had lower levels of MXI1 expression and higher levels of MXD3 expression compared to normal tissues. Endothelial cells, induced pluripotent stem cells, and smooth muscle cells were all found to express MXI1. This is the first study to investigate the close genetic link between hip pain and PRAD using bioinformatics technologies. The 2 most significant genes involved in crosstalk between PRAD and hip pain were MXD3 and MXI1. The immunological responses triggered by T cells, mast cells, and neutrophils may be crucial in the relationship between PRAD and hip pain.

N6-Methyladenosine in Cell-Fate Determination of BMSCs: From Mechanism to Applications

The methylation of adenosine base at the nitrogen-6 position is referred to as "N6-methyladenosine (m6A)" and is one of the most prevalent epigenetic modifications in eukaryotic mRNA and noncoding RNA (ncRNA). Various m6A complex components known as "writers," "erasers," and "readers" are involved in the function of m6A. Numerous studies have demonstrated that m6A plays a crucial role in facilitating communication between different cell types, hence influencing the progression of diverse physiological and pathological phenomena. In recent years, a multitude of functions and molecular pathways linked to m6A have been identified in the osteogenic, adipogenic, and chondrogenic differentiation of bone mesenchymal stem cells (BMSCs). Nevertheless, a comprehensive summary of these findings has yet to be provided. In this review, we primarily examined the m6A alteration of transcripts associated with transcription factors (TFs), as well as other crucial genes and pathways that are involved in the differentiation of BMSCs. Meanwhile, the mutual interactive network between m6A modification, miRNAs, and lncRNAs was intensively elucidated. In the last section, given the beneficial effect of m6A modification in osteogenesis and chondrogenesis of BMSCs, we expounded upon the potential utility of m6A-related therapeutic interventions in the identification and management of human musculoskeletal disorders manifesting bone and cartilage destruction, such as osteoporosis, osteomyelitis, osteoarthritis, and bone defect.

Recent advances of m6A methylation in skeletal system disease

Skeletal system disease (SSD) is defined as a class of chronic disorders of skeletal system with poor prognosis and causes heavy economic burden. m6A, methylation at the N6 position of adenosine in RNA, is a reversible and dynamic modification in posttranscriptional mRNA. Evidences suggest that m6A modifications play a crucial role in regulating biological processes of all kinds of diseases, such as malignancy. Recently studies have revealed that as the most abundant epigentic modification, m6A is involved in the progression of SSD. However, the function of m6A modification in SSD is not fully illustrated. Therefore, make clear the relationship between m6A modification and SSD pathogenesis might provide novel sights for prevention and targeted treatment of SSD. This article will summarize the recent advances of m6A regulation in the biological processes of SSD, including osteoporosis, osteosarcoma, rheumatoid arthritis and osteoarthritis, and discuss the potential clinical value, research challenge and future prospect of m6A modification in SSD.

Key m6A regulators mediated methylation modification pattern and immune infiltration characterization in hepatic ischemia-reperfusion injury

BACKGROUND

N6-methyladenosine (m6A) mRNA modification plays a critical role in various human biological processes. However, there has been no study reported to elucidate its role in hepatic ischemia-reperfusion injury (IRI). This study was aimed to explore the expression pattern together with the potential functions of m6A regulators in hepatic IRI.

METHODS

The gene expression data (GSE23649) of m6A regulators in human liver tissue samples before cold perfusion and within 2 h after portal vein perfusion from Gene Expression Omnibus database was analyzed. The candidate m6A regulators were screened using random forest (RF) model to predict the risk of hepatic IRI. The evaluation of infiltrating abundance of 23 immune cells was performed using single sample gene set enrichment analysis. Besides, quantitative real time polymerase chain reaction (qRT-PCR) assay was carried out to validate the expression of key m6A regulators in mouse hepatic IRI model.

RESULTS

The expressions of WTAP, CBLL1, RBM15, and YTHDC1 were found to be increased in liver tissues 2 h after portal vein perfusion; in contrast, the expressions of LRPPRC, FTO, METTL3, and ALKBH5 were decreased. Based on RF model, we identified eight m6A methylation regulators for the prediction of the risk of hepatic IRI. Besides, a nomogram was built to predict the probability of hepatic IRI. In addition, the levels of WTAP, ALKBH5, CBLL1, FTO, RBM15B, LRPPRC and YTHDC1 were correlated with the immune infiltration of activated CD4 T cell, activated dendritic cell (DC), immature DC, mast cell, neutrophil, plasmacytoid DC, T helper (Th) cell (type 1, 2, and 17), gamma delta T cell, T follicular helper (Tfh) cell, myeloid-derived suppressor cell (MDSC), macrophage, natural killer cell, and regulatory Th cell. Among mouse hepatic IRI model, the mRNA level of CBLL1 and YTHDC1 was increased with statistical significance; however, the mRNA level of FTO and METTL3 was decreased among post-reperfusion liver samples compared with those in pre-reperfusion samples with statistical significance.

CONCLUSIONS

The m6A regulators exerted a pivotal impact on hepatic IRI. The m6A patterns that found in this study might provide novel targets and strategies for the alleviation/treatment of hepatic IRI in the future.

Integrative network-based analysis on multiple Gene Expression Omnibus datasets identifies novel immune molecular markers implicated in non-alcoholic steatohepatitis

Introduction

Non-alcoholic steatohepatitis (NASH), an advanced subtype of non-alcoholic fatty liver disease (NAFLD), has becoming the most important aetiology for end-stage liver disease, such as cirrhosis and hepatocellular carcinoma. This study were designed to explore novel genes associated with NASH.

Methods

Here, five independent Gene Expression Omnibus (GEO) datasets were combined into a single cohort and analyzed using network biology approaches.

Results

11 modules identified by weighted gene co-expression network analysis (WGCNA) showed significant association with the status of NASH. Further characterization of four gene modules of interest demonstrated that molecular pathology of NASH involves the upregulation of hub genes related to immune response, cholesterol and lipid metabolic process, extracellular matrix organization, and the downregulation of hub genes related to cellular amino acid catabolic, respectively. After DEGs enrichment analysis and module preservation analysis, the Turquoise module associated with immune response displayed a remarkably correlation with NASH status. Hub genes with high degree of connectivity in the module, including CD53, LCP1, LAPTM5, NCKAP1L, C3AR1, PLEK, FCER1G, HLA-DRA and SRGN were further verified in clinical samples and mouse model of NASH. Moreover, single-cell RNA-seq analysis showed that those key genes were expressed by distinct immune cells such as microphages, natural killer, dendritic, T and B cells. Finally, the potential transcription factors of Turquoise module were characterized, including NFKB1, STAT3, RFX5, ILF3, ELF1, SPI1, ETS1 and CEBPA, the expression of which increased with NASH progression.

Discussion

In conclusion, our integrative analysis will contribute to the understanding of NASH and may enable the development of potential biomarkers for NASH therapy.

Identification of mitochondria-related key gene and association with immune cells infiltration in intervertebral disc degeneration

Intervertebral disc (IVD) degeneration and its inflammatory microenvironment can result in discogenic pain, which has been shown to stem from the nucleus pulposus (NP). Increasing evidence suggests that mitochondrial related genes are strictly connected to cell functionality and, importantly, it can regulate cell immune activity in response to damaged associated signals. Therefore, identification of mitochondria related genes might offer new diagnostic markers and therapeutic targets for IVD degeneration. In this study, we identified key genes involved in NP tissue immune cell infiltration during IVD degeneration by bioinformatic analysis. The key modules were screened by weighted gene co-expression network analysis (WCGNA). Characteristic genes were identified by random forest analysis. Then gene set enrichment analysis (GSEA) was used to explore the signaling pathways associated with the signature genes. Subsequently, CIBERSORT was used to classify the infiltration of immune cells. Function of the hub gene was confirmed by PCR, Western blotting and ELISA. Finally, we identified MFN2 as a crucial molecule in the process of NP cell pyroptosis and NLRP3 inflammasome activation. We speculate that the increased MFN2 expression in NP tissue along with the infiltration of CD8⁺ T cells, NK cell and neutrophils play important roles in the pathogenesis of IVD degeneration.

Effect of M6A regulators on diagnosis, subtype classification, prognosis and novel therapeutic target development of idiopathic pulmonary fibrosis

Molecular biology studies show that RNA N6-methyladenosine (m6A) modifications may take part in the incidence and development of idiopathic pulmonary fibrosis (IPF). Nonetheless, the roles of m6A regulators in IPF are not fully demonstrated. In this study, 12 significant m6A regulators were filtered out between healthy controls and IPF patients using GSE33566 dataset. Random forest algorithm was used to identify 11 candidate m6A regulators to predict the incidence of IPF. The 11 candidate m6A regulators included leucine-rich PPR motif-containing protein (LRPPRC), methyltransferase-like protein 3, FTO alpha-ketoglutarate dependent dioxygenase (FTO), methyltransferase-like 14/16, zinc finger CCCH domain-containing protein 13, protein virilizer homolog, Cbl proto-oncogene like 1, fragile X messenger ribonucleoprotein 1 and YTH domain containing 1/2. A nomogram model was constructed based on 11 candidate m6A regulators and considered beneficial to IPF patients using decision curve analysis. Consensus clustering method was used to distinctly divide IPF patients into two m6A patterns (clusterA and clusterB) based on 12 significant m6A regulators. M6A scores of all IPF patients were obtained using principal component analysis to quantify the m6A patterns. Patients in clusterB had higher m6A scores than those in clusterA. Furthermore, patients in clusterB were correlated with Th17 and Treg cell infiltration, innate immunity and Th1 immunity, while those in clusterA were correlated with adaptive immunity and Th2 immunity. Patients in clusterB also had higher expressions of mesenchymal markers and regulatory factors of fibrosis but lower expressions of epithelial markers. Lastly and interestingly, two m6A regulators, LRPPRC (p = 0.011) and FTO (p = 0.042), were identified as novel prognostic genes in IPF patients for the first time using an external GSE93606 dataset. Both of them had a positive correlation with a better prognosis and may serve as therapy targets. Thus, we conducted virtual screening to discover potential drugs targeting LRPPRC and FTO in the treatment of IPF. In conclusion, m6A regulators are crucial to the onset, development and prognosis of IPF. Our study on m6A patterns may provide clues for clinical diagnosis, prognosis and targeted therapeutic drugs development for IPF.