Comprehensive bioinformatics analyses reveal immune genes responsible for altered immune microenvironment in intervertebral disc degeneration

A diagnostic signatures for intervertebral disc degeneration using TNFAIP6 and COL6A2 based on single-cell RNA-seq and bulk RNA-seq analyses

OBJECTIVES

Intervertebral disc degeneration (IVDD) is a prevalent degenerative condition associated with a high incidence rate of low back pain and disability. This study aimed to identify potential biomarkers and signaling pathways associated with IVDD.

METHODS

Biomarkers were discerned through bulk-RNA and single-cell RNA sequencing (scRNA-Seq) investigations of IVDD cases from the Gene Expression Omnibus (GEO) database. Following this, two central genes were identified. Furthermore, gene set enrichment analysis (GSEA) and receiver operating characteristic (ROC) curve analysis were conducted. The transcriptional factor (TF) derived from nucleus pulposus (NP) cells was examined through the DoRothEA R package. RT-qPCR and IHC techniques were employed to confirm the expression of the two hub genes and their associated genes in tissue samples.

RESULTS

The proteins Tumor necrosis factor-inducible gene 6 protein (TNFAIP6) and collagen VI-α2 (COL6A2) were frequently analyzed using a combination of DEGs from datasets GSE70362, GSE124272, and scRNA-seq. Examination of gene expression across multiple datasets indicated significant differences in TNFAIP6 and COL6A2 levels in IVDD compared to control or normal groups (p < 0.05). These two central genes demonstrated strong diagnostic utility in the training cohort and reliable predictive value in the validation datasets. Our study verified the potential role of ZEB2 as a TF in regulating two key genes associated with IVDD. Furthermore, qPCR and IHC confirmed elevated expression levels of the hub genes and transcription factor.

CONCLUSION

We identified biomarkers, specifically TNFAIP6 and COL6A2, that have the potential to predict disease activity and aid in the diagnosis of IVDD.

Exploring the molecular mechanisms underlying intervertebral disc degeneration by analysing multiple datasets

The purpose of this study was to explore the genetic characteristics and immune cell infiltration related to intervertebral disc degeneration through multidataset analysis, predict potential therapeutic drugs, and provide a theoretical basis for clinical treatment. The gene expression profile data of the GSE70362, GSE186542, and GSE245147 datasets were downloaded from the Gene Expression Omnibus (GEO) database, and the hub genes were identified through differentially expressed gene analysis, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) functional annotation and Mendelian randomization analysis were performed. Hub genes and immune cells were identified. Infiltration status was determined through GSEA and GSVA to clarify the specific signalling pathways associated with key genes and explore the potential molecular mechanisms by which key genes affect disease progression. The key genes were reversely predicted using miRNA grid construction and transcription factor regulation, and genes related to disease regulation were obtained from the GeneCards database. Finally, the differentially expressed genes were used for drug prediction through the Connectivity Map database to identify potential drugs for the treatment of intervertebral disc degeneration. The feasibility of the predicted drugs was tested by molecular docking technology. Real-time quantitative PCR was used to confirm the expression of key genes in the tissue samples.A total of 126 differentially expressed genes were identified in the GEO database, and 4 differentially expressed hub genes (COL6A2, DCXR, GLRX, and PDGFRB) were identified through bioinformatics methods. Immune infiltration analysis revealed that NK cells, macrophages, and eosinophils were activated during IVDD, whereas mast cells and T cells were suppressed. GO and KEGG analyses revealed that key genes are involved in the development of this disease through signalling pathways such as the glycolysis pathway, the oxidative phosphorylation pathway, the cholesterol regulatory pathway, and the haem metabolism pathway. Analysis of the constructed miRNA grid revealed that key genes are jointly regulated by multiple transcription factors, among which the most important motif is cisbp_M5578. Disease regulation-related genes were obtained through the GeneCards database, analysis of the correlation with key genes was performed, and the expression levels of the two mRNA and miRNA were significantly correlated. Finally, drug prediction performed through the Connectivity Map database revealed that drugs such as Abt-751, LY-2183240, podophyllotoxin, and vindesine can alleviate or even reverse the disease state. Finally, we collected 10 IVDD and 10 healthy disc tissue samples, and the RT‒qPCR results were consistent with the bioinformatics results. We identified COL6A2, DCXR, GLRX, and PDGFRB as key genes involved in IVDD. In addition, drugs such as Abt-751 are expected to control and reverse the progression of the disease. In the future, these key genes and predicted drugs may provide new directions for further mechanistic studies as well as new therapies for IVDD patients.

Analyzing gene-based apoptotic biomarkers in insomnia using bioinformatics

Insomnia is increasingly common and poses significant health risks. The aims of this study are to identify apoptosis-related genes and potential biomarkers for insomnia and to find new therapeutic targets. Insomnia gene expression profiles were downloaded from the Gene Expression Omnibus database, and differentially expressed genes in normal and insomnia samples were identified by limma rapid differential analysis, and then the major modular genes with clinical relevance to insomnia were analyzed using the Weighted Gene Co-Expression Network Analysis, and intersections were obtained with the differentially expressed genes as well as with apoptotic gene databases. We validated apoptosis-related differentially expressed genes, enriched and analyzed the specific biological process of insomnia and related signaling pathways. In addition, we constructed a protein-protein interaction network and obtained Top10 hub genes using Cytoscape. We selected 3 of them as hub genes and compared their expression in normal hippocampal neuronal cells and hippocampal neuronal cells of the model group exposed to corticosterone induction by Western Blot and qRT-PCR experiments. A total of 190 differentially expressed apoptosis-related genes were identified in insomnia, and BCL2, SOCS3, and IL7R were identified as important hub genes. Enrichment analysis showed that the occurrence of apoptosis in insomnia was mainly related to "PI3K-Akt signaling pathway," "JAK-STAT signaling pathway," "P53 signaling pathway" and so on. GO analysis showed that apoptosis in insomnia was mainly related to "immune response," "T cell differentiation in thymus," and "positive regulation of MAPK cascade." Western Blot and qRT-PCR experiments showed that BCL2, SOCS3, IL7R antiapoptotic indexes were under-expressed in modeled hippocampal neuronal cells compared to normal hippocampal neuronal cells. This study emphasizes the role of apoptosis-related genes in insomnia and preliminarily predicts that the occurrence of insomnia is closely related to apoptosis. Compared to the normal group, the antiapoptotic ability of hippocampal neurons in the model group is reduced. Although BCL2 has been studied in the context of sleep deprivation, SOCS3 and IL7R have not yet been explored in insomnia. Insomnia and sleep deprivation involve similar pathways, but due to different mechanisms and types of insomnia, gene expression may vary.

Integrating bioinformatics and experimental validation to Investigate IRF1 as a novel biomarker for nucleus pulposus cells necroptosis in intervertebral disc degeneration

Intervertebral disc degeneration (IDD) is a prevalent spinal disorder and the principal cause of lower back pain (LBP). Diverse forms of programmed cell death (PCD) have been identified as the key phenotypes of the disease and have the potential to serve as new indicators for the diagnosis and prognosis of IDD. However, the mechanism underlying necroptosis in IDD remains unclear. This study aimed to identify novel biomarkers that promote nucleus pulposus cell necroptosis in IDD using bioinformatic analysis and experimental validation. We analyzed multiple datasets of IDD from the Gene Expression Omnibus (GEO) database to identify necroptosis-related IDD differential genes (NRDEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed, followed by logistic least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive (SVM) algorithms to identify key genes. Gene set enrichment analysis (GSEA) and logistic regression analysis were used to ascertain the potential functions of these genes and to identify key genes, respectively. We then constructed mRNA-miRNA, mRNA-TF, mRNA-drug, and functional similarity gene interaction networks for the seven key genes identified. We used IDD clinical samples and necroptotic cell model to validate our findings. Immunohistochemical staining, RT-qPCR, and western blotting results indicated that IRF1 may be a hub necroptosis-related gene. To further elucidate the function of IRF1, we constructed IRF1 knockdown and overexpression models, which revealed that IRF1 promotes necroptosis in rat nucleus pulposus cells, increases mitochondrial ROS levels, and decreases ATP levels. These findings provide new insights into the development of necroptosis in IDD and, for the first time, validate the role of IRF1 as a novel biomarker for the diagnosis and treatment of IDD.

Identifying critical modules and biomarkers of intervertebral disc degeneration by using weighted gene co-expression network

Background

Intervertebral disc degeneration (IVDD) is an age-related orthopedic degenerative disease characterized by recurrent episodes of lower back pain, the pathogenesis of which is not fully understood. This study aimed to identify key biomarkers of IVDD and its causes.

Methods

We acquired three gene expression profiles from the Gene Expression Omnibus (GEO) database, GSE56081, GSE124272, and GSE153761, and used limma fast differential analysis to identify differentially expressed genes (DEGs) between normal and IVDD samples after removing batch effects. We applied weighted gene co-expression network (WGCNA) to identify the key modular genes in GSE124272 and intersected these with DEGs. Next, A protein-protein interaction network (PPI) was constructed, and Cytoscape was used to identify the Top 10 hub genes. Functional enrichment analyses were performed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Three key genes were validated using Western Blot (WB) and qRT-PCR. Additionally, we predicted miRNAs involved in hub gene co-regulation and analyzed miRNA microarray data from GSE116726 to identify four differentially expressed miRNAs.

Results

We identified 10 hub genes using bioinformatics analysis, gene function enrichment analysis revealed that they were primarily enriched in pathways, such as the TNF signaling pathway. We chose JUNB, SOCS3, and CEBPB as hub genes and used WB and qRT-PCR to confirm their expression. All three genes were overexpressed in the IVDD model group compared to the control group. Furthermore, we identified four miRNAs involved in the co-regulation of the hub genes using miRNet prediction: mir-191-5p, mir-20a-5p, mir-155-5p, and mir-124-3p. Using limma difference analysis, we discovered that mir-191-5p, mir-20a-5p, and mir-155-5p were all down-regulated and expressed in IVDD samples, but mir-124-3p showed no significant change.

Conclusion

JUNB, SOCS3, and CEBPB were identified as key genes in IVDD, regulated by specific miRNAs, providing potential biomarkers for early diagnosis and therapeutic targets.

Comprehensive analysis of abnormal methylation modification differential expression mRNAs between low-grade and high-grade intervertebral disc degeneration and its correlation with immune cells

BACKGROUND

Intervertebral disc degeneration (IDD) is an important cause of low back pain. The aim of this study is to identify the potential molecular mechanism of abnormal methylation-modified DNA in the progression of IDD, hoping to contribute to the diagnosis and management of IDD.

METHODS

Low-grade IDD (grade I-II) and high-grade IDD (grade III-V) data were downloaded from GSE70362 and GSE129789 datasets. The abnormally methylated modified differentially expressed mRNAs (DEmRNAs) were identified by differential expression analysis (screening criteria were p < .05 and |logFC| > 1) and differential methylation analysis (screening criteria were p < .05 and |δβ| > 0.1). The classification models were constructed, and the receiver operating characteristic analysis was also carried out. In addition, functional enrichment analysis and immune correlation analysis were performed and the miRNAs targeted for the abnormally methylated DEmRNAs were predicted. Finally, expression validation was performed using real-time PCR.

RESULTS

Compared with low-grade IDD, seven abnormal methylation-modified DEmRNAs (AOX1, IBSP, QDPR, ABLIM1, CRISPLD2, ACTC1 and EMILIN1) were identified in high-grade IDD, and the classification models of random forests (RF) and support vector machine (SVM) were constructed. Moreover, seven abnormal methylation-modified DEmRNAs and classification models have high diagnostic accuracy (area under the curve [AUC] > 0.8). We also found that AUC values of single abnormal methylation-modified DEmRNA were all lower than those of RF and SVM classification models. Pearson correlation analysis found that macrophages M2 and EMILIN1 had significant negative correlation, while macrophages M2 and IBSP had significant positive correlation. In addition, four targeted relationship pairs (hsa-miR-4728-5p-QDPR, hsa-miR-4533-ABLIM1, hsa-miR-4728-5p-ABLIM1 and hsa-miR-4534-CRISPLD2) and multiple signalling pathways (for example, PI3K-AKT signalling pathway, osteoclast differentiation and calcium signalling pathway) were also identified that may be involved in the progression of IDD.

CONCLUSION

The identification of abnormal methylation-modified DEmRNAs and the construction of classification models in this study were helpful for the diagnosis and management of IDD progression.

JAK1, SKI, ZBTB16 as potential biomarkers mediate the inflammatory response in keratoconjunctivitis sicca

Keratoconjunctivitis sicca (KCS) is an ocular condition characterized by insufficient tear production and inflammatory irritation, with Sjögren's syndrome (SS) being a major causative factor. This study aimed to extract patient transcriptomic data from the GEO database to identify signature genes associated with the diagnosis and treatment of KCS and the expression of three key genes were experimentally verified. We performed a difference analysis on the SS patient dataset and performed a Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the resulting genes. Additionally, a Weighted Gene Co-expression Network Analysis (WGCNA) was constructed. Machine learning techniques were employed to analyze the most strongly correlated gene modules with SS traits. These findings were further validated using KCS immune-correlation microarrays as a validation set. The correlation of the three identified genes with 22 immune cells was assessed through immune infiltration analysis. Subsequently, a rat model of desiccated keratoconjunctivitis was established, and the modeling situation and expression of characteristic genes were analyzed at the morphological, tissue, and molecular levels. Bioinformatic prediction revealed that the expression of JAK1, SKI, ZBTB16 not only differed in the machine learning validation set, but also correlated with some immune cells in the immune infiltration analysis. The results of animal experiments showed that the transcription and expression levels of these three genes were significantly different in rat KCS tissues and normal tissues, and there were also differences in the expression of JAK1 and SKI in rat peripheral blood, as well as significant up-regulation of the expression of related inflammatory factors in KCS tissues. Through bioinformatics prediction and animal experimental validation, this study identified three differentially expressed genes in SS mediated KCS patients, which provide new potential biological targets for the diagnosis and treatment of KCS.

A novel spherical GelMA-HAMA hydrogel encapsulating APET×2 polypeptide and CFIm25-targeting sgRNA for immune microenvironment modulation and nucleus pulposus regeneration in intervertebral discs

METHODS

Single-cell transcriptomics and high-throughput transcriptomics were used to screen factors significantly correlated with intervertebral disc degeneration (IDD). Expression changes of CFIm25 were determined via RT-qPCR and Western blot. NP cells were isolated from mouse intervertebral discs and induced to degrade with TNF-α and IL-1β. CFIm25 was knocked out using CRISPR-Cas9, and CFIm25 knockout and overexpressing nucleus pulposus (NP) cell lines were generated through lentiviral transfection. Proteoglycan expression, protein expression, inflammatory factor expression, cell viability, proliferation, migration, gene expression, and protein expression were analyzed using various assays (alcian blue staining, immunofluorescence, ELISA, CCK-8, EDU labeling, transwell migration, scratch assay, RT-qPCR, Western blot). The GelMA-HAMA hydrogel loaded with APET×2 polypeptide and sgRNA was designed, and its effects on NP regeneration were assessed through in vitro and mouse model experiments. The progression of IDD in mice was evaluated using X-ray, H&E staining, and Safranin O-Fast Green staining. Immunohistochemistry was performed to determine protein expression in NP tissue. Proteomic analysis combined with in vitro and in vivo experiments was conducted to elucidate the mechanisms of hydrogel action.

RESULTS

CFIm25 was upregulated in IDD NP tissue and significantly correlated with disease progression. Inhibition of CFIm25 improved NP cell degeneration, enhanced cell proliferation, and migration. The hydrogel effectively knocked down CFIm25 expression, improved NP cell degeneration, promoted cell proliferation and migration, and mitigated IDD progression in a mouse model. The hydrogel inhibited inflammatory factor expression (IL-6, iNOS, IL-1β, TNF-α) by targeting the p38/NF-κB signaling pathway, increased collagen COLII and proteoglycan Aggrecan expression, and suppressed NP degeneration-related factors (COX-2, MMP-3).

CONCLUSION

The study highlighted the crucial role of CFIm25 in IDD and introduced a promising therapeutic strategy using a porous spherical GelMA-HAMA hydrogel loaded with APET×2 polypeptide and sgRNA. This innovative approach offers new possibilities for treating degenerated intervertebral discs.

Identification of Biomarkers, Pathways, Immune Properties of Mitophagy Genes, and Prediction Models for Intervertebral Disc Degeneration

Background

Intervertebral disc degeneration (IDD) is the leading cause of low back pain (LBP). The mechanism of IDD development and progression is not fully understood. Peripheral biomarkers are increasingly vital non-radioactive methods in early detection and diagnosis for IDD. Nevertheless, less attention has been paid to the role of mitophagy genes in the progress of IDD. This study aimed to identify the mitophagy disease-causing genes in the process of IDD and mitophagy diagnostic biomarkers for IDD.

Methods

Mitophagy-related differentially expressed genes (MRDEGs) related to IDD were investigated by analyzing the microarray datasets of IDD cases from GEO, PathCards and Molecular Signatures Databases. We used R software, WGCNA, PPI, mRNA-miRNA, mRNA-TF, GO, KEGG, GSEA, GSVA and Cytoscape to analyze and visualize the data. We further used ssGSEA for immunoinfiltration analysis to obtain different immune cell infiltration. LASSO model was developed to screen for genes that met the diagnostic gene model requirements. Finally, qRT-PCR, Western blotting and HE were used to verify hub genes and their expression from clinical IDD samples.

Results

We identified 14 MRDEGs and 12 hub genes. GO, KEGG, GSEA and GSVA analyses demonstrated that hub genes were critical for the development of IDD. LASSO diagnostic model consisted of six hub genes, among which SQSTM1, ATG7 and OPTN were significantly different between the two IDD disease subtypes. At the same time, SQSTM1 also had a high correlation with immune characteristic subtypes. The results of qRT-PCR and Western blotting also indicated that these genes were significantly differentially expressed in nucleus pulposus cells (NPCs) of the IDD group.

Conclusion

We explored an association between MRDEGs-associated signature in IDD and validated that hub genes like SQSTM1 might serve as biomarkers for diagnostic and therapeutic targets for IDD. Meanwhile, this study can provide new insights into the functional characteristics and mechanism of mitophagy in the development of IDD.

Diagnostic model based on key autophagy-related genes in intervertebral disc degeneration

BACKGROUND

Current research on autophagy is mainly focused on intervertebral disc tissues and cells, while there is few on human peripheral blood sample. therefore, this study constructed a diagnostic model to identify autophagy-related markers of intervertebral disc degeneration (IVDD).

METHODS

GSE150408 and GSE124272 datasets were acquired from the Gene Expression Omnibus database, and differential expression analysis was performed. The IVDD-autophagy genes were obtained using Weighted Gene Coexpression Network Analysis, and a diagnostic model was constructed and validated, followed by Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA). Meanwhile, miRNA-gene and transcription factor-gene interaction networks were constructed. In addition, drug-gene interactions and target genes of methylprednisolone and glucosamine were analyzed.

RESULTS

A total of 1,776 differentially expressed genes were identified between IVDD and control samples, and the composition of the four immune cell types was significantly different between the IVDD and control samples. The Meturquoise and Mebrown modules were significantly related to immune cells, with significant differences between the control and IVDD samples. A diagnostic model was constructed using five key IVDD-autophagy genes. The area under the curve values of the model in the training and validation datasets were 0.907 and 0.984, respectively. The enrichment scores of the two pathways were significantly different between the IVDD and healthy groups. Eight pathways in the IVDD and healthy groups had significant differences. A total of 16 miRNAs and 3 transcription factors were predicted to be of great value. In total, 84 significantly related drugs were screened for five key IVDD-autophagy genes in the diagnostic model, and three common autophagy-related target genes of methylprednisolone and glucosamine were predicted.

CONCLUSION

This study constructs a reliable autophagy-related diagnostic model that is strongly related to the immune microenvironment of IVD. Autophagy-related genes, including PHF23, RAB24, STAT3, TOMM5, and DNAJB9, may participate in IVDD pathogenesis. In addition, methylprednisolone and glucosamine may exert therapeutic effects on IVDD by targeting CTSD, VEGFA, and BAX genes through apoptosis, as well as the sphingolipid and AGE-RAGE signaling pathways in diabetic complications.

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.

Cellular senescence - Molecular mechanisms of intervertebral disc degeneration from an immune perspective

Intervertebral disc degeneration (IVDD) is a frequent and intractable chronic condition in orthopedics that causes enormous discomfort in patients' lives and thoughts, as well as a significant economic burden on society and the nation. As a result, understanding the pathophysiology of IVDD is critical. The pathophysiology of IVDD has been linked to numerous variables, including oxidative stress, apoptosis, matrix metalloproteinases, and inflammatory factors. Cellular senescence has recently attracted a lot of attention in the study of age-related diseases. It has been discovered that IVDD is intimately linked to human senescence, in which nucleus pulposus cell senescence may play a significant role. Previously, our group did a comprehensive and systematic clarification of the pathogenesis of IVDD from an immune perspective and discovered that the fundamental pathogenesis of IVDD is inflammatory upregulation and nucleus pulposus cell death caused by an imbalance in the immune microenvironment. In this review, we will treat nucleus pulposus cell senescence as a novelty point to clarify the pathophysiology of IVDD and further explore the probable relationship between senescence and immunity along with the dysregulation of the immunological microenvironment to propose new therapeutic approaches for IVDD.

Intervertebral disc degeneration and how it leads to low back pain

The purpose of this review was to evaluate data generated by animal models of intervertebral disc (IVD) degeneration published in the last decade and show how this has made invaluable contributions to the identification of molecular events occurring in and contributing to pain generation. IVD degeneration and associated spinal pain is a complex multifactorial process, its complexity poses difficulties in the selection of the most appropriate therapeutic target to focus on of many potential candidates in the formulation of strategies to alleviate pain perception and to effect disc repair and regeneration and the prevention of associated neuropathic and nociceptive pain. Nerve ingrowth and increased numbers of nociceptors and mechanoreceptors in the degenerate IVD are mechanically stimulated in the biomechanically incompetent abnormally loaded degenerate IVD leading to increased generation of low back pain. Maintenance of a healthy IVD is, thus, an important preventative measure that warrants further investigation to preclude the generation of low back pain. Recent studies with growth and differentiation factor 6 in IVD puncture and multi-level IVD degeneration models and a rat xenograft radiculopathy pain model have shown it has considerable potential in the prevention of further deterioration in degenerate IVDs, has regenerative properties that promote recovery of normal IVD architectural functional organization and inhibits the generation of inflammatory mediators that lead to disc degeneration and the generation of low back pain. Human clinical trials are warranted and eagerly anticipated with this compound to assess its efficacy in the treatment of IVD degeneration and the prevention of the generation of low back pain.