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

Identification of signature genes and relationship with immune cell infiltration in intervertebral disc degeneration

Background

Early diagnosis of intervertebral disc (IVD) degeneration is of great significance for prevention of the disease from progressing to a serious stage. This study aimed to investigate the signature genes and their association with immune cells in IVD degeneration.

Methods

We analyzed differentially expressed genes (DEGs) in a dataset of IVD degeneration samples from the GEO database. Weighted gene coexpression network analysis (WGCNA) and DEGs were employed to pinpoint the key modules and IVD degeneration genes. Functional enrichment analysis was performed for these IVD degeneration genes. Signature genes were identified using least absolute shrinkage and selection operator (LASSO) analysis. Gene set enrichment analysis (GSEA) was used to explore signaling pathways related to signature genes, and CIBERSORT® was used to classify immune cell infiltration. Function of the hub gene was confirmed by PCR, Western blotting and ELISA.

Results

2,254 DEGs were identified from GSE56081, and WGCNA grouped the data into 9 modules. MEbrown module had a significant correlation with IVD degeneration (cor = 0.99, P = 8.00 × 10-8). LASSO analysis selected HSPA1B, TOB1, ECM1, PTTG1IP as signature genes with excellent diagnostic efficiency. Furthermore, we assessed the diagnostic efficacy of every signature gene in predicting IVD degeneration using an external validation group (GSE70362). The results showed that two of the signature genes (TOB1, ECM1) had significant diagnostic effect in predicting the degeneration of IVD. GSEA analysis showed TOB1 and ECM1 involve in NOD like receptor signaling pathway, phenylalanine metabolism. Ether lipid metabolism, glycosaminoglycan biosynthesis keratin sulfate, RNA degradation pathway. CIBERSORT® suggested TOB1 and ECM1 may participate in immune cells infiltration. Finally, we identified TOB1 as a crucial molecule in the process of NP cell pyroptosis and NLRP3 inflammasome activation.

Conclusion

TOB1 may show remarkable diagnostic performance in IVD degeneration and may be implicated in the infiltration of immune cells.

Downregulation of Gldc attenuates myocardial ischemia reperfusion injury in vitro by modulating Akt and NF-κB signalings

Myocardial ischemia/reperfusion injury (MIRI) is a serious clinical complication that is caused by reperfusion therapy following myocardial infarction (MI). Mitochondria-related genes (Mito-RGs) play important roles in multiple diseases. However, the role of mitochondria-related genes in MIRI remains largely unknown. The GSE67308 dataset from the GEO database was utilized to identify MIRI-related gene modules through WGCNA. Meanwhile, differential expression analysis was conducted to identify differentially expressed genes (DEGs) in the GSE61592 dataset. Next, candidate Mito-RGs related to MIRI were screened by Venn analysis. Thereafter, a myocardial hypoxia/reperfusion (H/R) H9C2 cell model and a mouse ischemia/reperfusion (I/R) model were established to verify the expression level of glycine decarboxylase (Gldc) in MIRI in vitro and in vivo. Based on data from the GEO database, Gldc levels were notably upregulated in murine MIRI samples, compared to the control group. RT-qPCR and western blot confirmed that Gldc levels were obviously elevated in the heart of I/R mice and H/R-exposed cardiomyocytes. Moreover, the deficiency of Gldc notably increased the viability and reduced the apoptosis and inflammatory responses in H9C2 cells exposed to H/R. Meanwhile, Gldc downregulation significantly reduced p-NF-κB p65, Bax and cleaved caspase 3 levels and elevated p-Akt and Bcl-2 levels in H9C2 cells exposed to H/R. The ROC curve analysis further demonstrated that Gldc gene exhibited good diagnostic value for MIRI. Collectively, Gldc deficiency could attenuate H/R injury in cardiomyocytes in vitro through activating Akt and inactivating NF-κB signalings. These data suggested that GLDC may serve as both a diagnostic and therapeutic target for MIRI.

Machine learning-based diagnostic model of lymphatics-associated genes for new therapeutic target analysis in intervertebral disc degeneration

Background

Low back pain resulting from intervertebral disc degeneration (IVDD) represents a significant global social problem. There are notable differences in the distribution of lymphatic vessels (LV) in normal and pathological intervertebral discs. Nevertheless, the molecular mechanisms of lymphatics-associated genes (LAGs) in the development of IVDD remain unclear. An in-depth exploration of this area will help to reveal the biological and clinical significance of LAGs in IVDD and may lead to the search for new therapeutic targets for IVDD.

Methods

Data sets were obtained from the Gene Expression Omnibus (GEO) database. Following quality control and normalization, the datasets (GSE153761, GSE147383, and GSE124272) were merged to form the training set, with GSE150408 serving as the validation set. LAGs from GeneCards, MSigDB, Gene Ontology, and KEGG database. The Venn diagram was employed to identify differentially expressed lymphatic-associated genes (DELAGs) that were differentially expressed in the normal and IVDD groups. Subsequently, four machine learning algorithms (SVM-RFE, Random Forest, XGB, and GLM) were used to select the method to construct the diagnostic model. The receiver operating characteristic (ROC) curve, nomogram, and Decision Curve Analysis (DCA) were used to evaluate the model effect. In addition, we constructed a potential drug regulatory network and competitive endogenous RNA (ceRNA) network for key LAGs.

Results

A total of 15 differentially expressed LAGs were identified. By comparing four machine learning methods, the top five genes of importance in the XGB model (MET, HHIP, SPRY1, CSF1, TOX) were identified as lymphatics-associated gene diagnostic signatures. This signature was used to predict the diagnosis of IVDD with strong accuracy and an area under curve (AUC) value of 0.938. Furthermore, the diagnostic model was validated in an external dataset (GSE150408), with an AUC value of 0.772. The nomogram and DCA further prove that the diagnosis model has good performance and predictive value. Additionally, drug regulatory networks and ceRNA networks were constructed, revealing potential therapeutic drugs and post-transcriptional regulatory mechanisms.

Conclusion

We developed and validated a lymphatics-associated genes diagnostic model by machine learning algorithms that effectively identify IVDD patients. These five key LAGs may be potential therapeutic targets for IVDD patients.

Unravelling diagnostic clusters and immune landscapes of cuproptosis patterns in intervertebral disc degeneration through dry and wet experiments

Cuproptosis is a manner of mitochondrial cell death induced by copper. However, cuproptosis modulators' molecular processes in intervertebral disc degeneration (IDD) are still unclear. To better understand the processes of cuproptosis regulators in IDD, a thorough analysis of cuproptosis regulators in the diagnostic biomarkers and subtype determination of IDD was conducted. Then we collected clinical IDD samples and successfully established IDD model in vivo and in vitro, and carried out real-time quantitative polymerase chain reaction (RT-qPCR) validation of significant cuproptosis modulators. Totally we identified 8 crucial cuproptosis regulators in the present research. Using a random forest model, we isolated 8 diagnostic cuproptosis modulators for the prediction of IDD risk. Then, based on our following decision curve analysis, we selected the five diagnostic cuproptosis regulators with importance scores greater than two and built a nomogram model. Using a consensus clustering method, we divided IDD patients into two cuproptosis clusters (clusterA and clusterB) based on the important cuproptosis regulators. Additionally, each sample's cuproptosis value was evaluated using principal component analysis in order to quantify the cuproptosis clusters. Patients in clusterB had higher cuproptosis scores than patients in clusterA. Moreover, we found that clusterB was involved in the immunity of natural killer cell, while clusterA was related to activated CD4 T cell, activated B cell, etc. Notably, cuproptosis modulators detected by RT-qPCR showed generally consistent expression levels with the bioinformatics results. To sum up, cuproptosis modulators play a crucial role in the pathogenic process of IDD, providing biomarkers and immunotherapeutic approaches for IDD.

Analysis of global research hotspots and trends in immune cells in intervertebral disc degeneration: A bibliometric study

Intervertebral disc degeneration is an important pathological basis for spinal degenerative diseases. The imbalance of the immune microenvironment and the involvement of immune cells has been shown to lead to nucleus pulposus cells death. This article presents a bibliometric analysis of studies on immune cells in IDD in order to clarify the current status and hotspots. We searched the WOSCC, Scopus and PubMed databases from 01/01/2001 to 08/03/2023. We analyzed and visualized the content using software such as Citespace, Vosviewer and the bibliometrix. This study found that the number of annual publications is increasing year on year. The journal study found that Spine had the highest number of articles and citations. The country/regions analysis showed that China had the highest number of publications, the USA had the highest number of citations and total link strength. The institutional analysis found that Shanghai Jiao Tong University and Huazhong University of Science Technology had the highest number of publications, Tokai University had the highest citations, and the University of Bern had the highest total link strength. Sakai D and Risbud MV had the highest number of publications. Sakai D had the highest total link strength, and Risbud MV had the highest number of citations. The results of the keyword analysis suggested that the current research hotspots and future directions continue to be the study of the mechanisms of immune cells in IDD, the therapeutic role of immune cells in IDD and the role of immune cells in tissue engineering for IDD.

Identification of novel gene signatures and immune cell infiltration in intervertebral disc degeneration using bioinformatics analysis

Background: Intervertebral disc degeneration (IDD) is the leading cause of lower back pain, and an overall understanding of the molecular mechanisms related to IDD is still lacking. The purpose of this study was to explore gene signatures and immune cell infiltration related to IDD via bioinformatics analysis. Methods: A total of five expression profiles of mRNA and non-coding RNA were downloaded from the Gene Expression Omnibus (GEO) database. The potentially involved lncRNA/circRNA-miRNA-mRNA networks and protein-protein interaction networks were constructed by miRNet, circBank, STRING, and the Cytoscape database. Gene ontology, Kyoto Encyclopaedia of Genes and Genomes Analysis, Gene Set Enrichment Analysis, Gene Set Variation Analysis, Immune Infiltration Analysis, and Drug-Gene Interaction were used to analyse the top 20 hub genes. RT-qPCR was conducted to confirm the 12 differential expressions of genes both in the nucleus pulposus and annulus fibrosus tissues Results: There were 346 differentially expressed mRNAs, 12 differentially expressed miRNAs, 883 differentially expressed lncRNAs, and 916 differentially expressed circRNAs in the GEO database. Functional and enrichment analyses revealed hub genes associated with platelet activation, immune responses, focal adhesion, and PI3K-Akt signalling. The apoptotic pathway, the reactive oxygen species pathway, and oxidative phosphorylation play an essential role in IDD. Immune infiltration analysis demonstrated that the Treg cells had significant infiltration, and three levels of immune cells, including dendritic cells, Th2 cells, and tumour-infiltrating lymphocytes, were inhibited in IDD. Drug-gene interaction analysis showed that COL1A1 and COL1A2 were targeted by collagenase clostridium histolyticum, ocriplasmin, and PDGFRA was targeted by 66 drugs or molecular compounds. Finally, 24 cases of IDD tissues and 12 cases of normal disc tissues were collected, and the results of RT-qPCR were consistent with the bioinformatics results. Conclusion: Our data indicated that the 20 hub genes and immune cell infiltration were involved in the pathological process of IDD. In addition, the PDGFRA and two potential drugs were found to be significant in IDD development.

Identification of mitophagy-related genes with potential clinical utility in myocardial infarction at transcriptional level

Background

Myocardial infarction (MI) ranks among the most prevalent cardiovascular diseases. Insufficient blood flow to the coronary arteries always leads to ischemic necrosis of the cardiac muscle. However, the mechanism of myocardial injury after MI remains unclear. This article aims to explore the potential common genes between mitophagy and MI and to construct a suitable prediction model.

Methods

Two Gene Expression Omnibus (GEO) datasets (GSE62646 and GSE59867) were used to screen the differential expression genes in peripheral blood. SVM, RF, and LASSO algorithm were employed to find MI and mitophagy-related genes. Moreover, DT, KNN, RF, SVM and LR were conducted to build the binary models, and screened the best model to further external validation (GSE61144) and internal validation (10-fold cross validation and Bootstrap), respectively. The performance of various machine learning models was compared. In addition, immune cell infiltration correlation analysis was conducted with MCP-Counter and CIBERSORT.

Results

We finally identified ATG5, TOMM20, MFN2 transcriptionally differed between MI and stable coronary artery diseases. Both internal and external validation supported that these three genes could accurately predict MI withAUC = 0.914 and 0.930 by logistic regression, respectively. Additionally, functional analysis suggested that monocytes and neutrophils might be involved in mitochondrial autophagy after myocardial infarction.

Conclusion

The data showed that the transcritional levels of ATG5, TOMM20 and MFN2 in patients with MI were significantly different from the control group, which might be helpful to further accurately diagnose diseases and have potential application value in clinical practice.