Lumbar intervertebral disc herniation (LDH) is a prevalent musculoskeletal disorder that leads to low back pain, productivity loss, and disability, imposing substantial socioeconomic burdens37,38. Given the multitude of high-risk factors implicated, the pathogenesis of lumbar disc herniation is notably intricate39. Consequently, timely and precise diagnosis, treatment, and management are of paramount importance for effective management of LDH. In recent decades, considerable advancements have been achieved in the symptomatic alleviation and mitigation of this condition40. The present study reveals that6 the observed instances of copper-dependent cell death are predominantly attributed to the accumulation of lipid acylation-related proteins, depletion of iron-sulfur cluster proteins, and a range of additional stress responses. These cascading events ultimately culminate in cellular demise and exhibit diverse connections with LDH16. However, there is currently a dearth of research investigating the precise mechanisms and impacts of copper in the modulation of cell death in diverse diseases. Consequently, the objective of this study is to elucidate the correlation between CRGs and LDH phenotype, examine their distinct functions in the immune microenvironment, and employ CRGs to forecast LDH subtypes.This study presents a comprehensive analysis of differentially expressed CRGs in patients with LDH and healthy controls, marking the first investigation of its kind. The findings reveal the identification of nine distinct CRGs that exhibit differential expression. Notably, NLRP3, ATP7B, ATP7A, and MTF1 demonstrate significant upregulation in LDH compared to non-LDH levels, while LIPT1, DLAT, PDHA1, GCSH, and DLST exhibit significant downregulation in LDH compared to non-LDH levels. These results suggest a strong correlation between CRGs and the onset and progression of LDH. Following this, we conducted an immune infiltration analysis on samples from individuals with LDH and those without LDH. The findings revealed elevated levels of plasma cells, neutrophils, and monocytes infiltrating LDH patients, whereas the expression of γδT cells was diminished. This suggests a significant association between the progression of LDH and the immune system. Based on this, we proceeded to examine the correlation between CRGs and expounded upon the connection between CRGs and LDH. In CRG cluster C2, the genes LIPT1, DLAT, PDHB, DLST, and GCSH exhibited elevated expression levels, whereas in CRG cluster C1, NLRP3, ATP7B, and MTF1 displayed high expression levels. Cluster C1 demonstrated higher levels of macrophages M0, while CRGcluster C2 exhibited increased expression in CD4 naive T cells, activated macrophages M0, activated mast cells, and neutrophils. Our GSVA analysis revealed that the CRGclustes associated with cell death play a role in the regulation of immune response in LDH. This study employed the WGCNA algorithm to analyze the gene modules closely associated with CRG cluster, aiming to deepen the understanding of its biological role in LDH. Four gene modules, namely the blue module, turquoise module, brown module, and yellow module, were identified. Notably, the ME Blue module exhibited the highest gene significance, warranting additional investigation. The GO enrichment analysis demonstrated that genes within the blue module exhibited enrichment in various terms, including structural constituent of ribosome, peptide binding, amide binding, ribosome, cytosolic ribosome, ribosomal subunit, large ribosomal subunit, cytoplasmic translation, monosaccharide biosynthetic, among others (Fig. 7A). Moreover, based on the findings of the KEGG enrichment analysis, it was observed that genes within the blue module exhibited significant enrichment in various biological processes, including ribosome biogenesis, the pentose phosphate pathway, oxidative phosphorylation, as well as diseases such as coronavirus disease (COVID-19) and diabetic cardiomyopathy. Additionally, the pentose phosphate pathway was identified as another notable enrichment within this module (Fig. 7B).In recent times, machine learning (ML) has gained significant traction in the clinical domain and is recognized as a crucial instrument in healthcare41. In contrast to conventional statistical models, the extensive analysis facilitated by machine learning guarantees the resilience of models and enhances prediction accuracy through iterative algorithms42,43. This study undertakes a comparative evaluation of the predictive capabilities of four machine learning models (RF, SVM, GLM, and XGB). These models are constructed based on 61 genes that exhibit a close association with the CRG cluster within the MEblue module of the GSE124272 and GSE150408 datasets. The XGBoost-based prediction model was developed and yielded the most accurate predictive outcome, with an AUC value of 0.715. Consequently, a total of five significant predictive genes (CKS2, LRG1, RAB43, DYSF, and G6PD) were identified through the utilization of XGB. CKS2, specifically, is a small, highly conserved cyclin-dependent kinase (CDK) interaction protein (10 kDa). As a crucial member of the CKS family, CKS2 plays a pivotal role in human embryogenesis, regulation of the cell cycle, somatic cell division, and apoptosis regulation. Moreover, CKS2 exhibits abnormal expression in various malignant tumor tissues and is closely linked to the biological characteristics of tumor initiation, progression, and metastasis44. Prior research has extensively examined CKS2, indicating its ability to augment the expression of cell cycle proteins, namely cyclin A, cyclin B1, and CDK1, thereby facilitating the proliferation of cancer cells. Moreover, multiple investigations have underscored the significance of CKS2 in preserving the functionality of hematopoietic stem cells45. Furthermore, evidence suggests that46 CKS2 might contribute to the advancement of rheumatoid arthritis. Nonetheless, the precise role and underlying mechanisms of CKS2 remain elusive. The findings of our research indicate that CKS2 could potentially serve as a novel functional regulator in the progression of LDH.Leucine-rich α-2 glycoprotein 1 (LRG1) is a secreted member of the leucine-rich repeat (LRR) protein family, which has been identified as a pattern recognition system in the innate immune system. It is capable of recognizing motifs and engaging in protein–protein interactions, thereby contributing to various biological processes47. Notably, LRG1 has been found to be significantly upregulated in cancer and diabetes, indicating its potential involvement in these pathologies. Moreover, LRG1 exhibits multifunctionality as a pathogenic signaling molecule, with notable expression in a range of diseases including infection, cardiovascular, renal, pulmonary, neural, and autoimmune disorders. While the correlation between LRG1 levels and diseases does not establish causality, substantial evidence exists indicating that heightened levels or aberrant expression of LRG1 actively contribute to pathological alterations in various diseases48. Prior studies have identified49 serum LRG1 as a significant diagnostic indicator for monitoring autoimmune conditions such as lupus nephritis, psoriasis, rheumatoid arthritis, and vasculitis50,51,52,53. Research conducted by Codina R et al. has indicated that54 LRG1 functions as an acute-phase protein, exhibiting a swift rise in serum levels following microbial infection and other inflammatory triggers. Furthermore, LRG1 plays a crucial role in facilitating immune cell participation at sites of inflammation, promoting the extravasation and activation of neutrophils, and augmenting the differentiation of naïve CD4pos T cells into pro-inflammatory Th17 lymphocytes49. The aforementioned findings contribute to the existing body of evidence that establishes a correlation between the overexpression of LRG1 and various inflammatory conditions. To summarize, LRG1 assumes a significant role in immune cell signaling, immune responses, and the inflammatory process.Ras-related GTP-binding protein 43 (RAB43) is a constituent of the Ras superfamily, predominantly localized within the endoplasmic reticulum and Golgi apparatus. It serves as a pivotal regulatory element in membrane transport, vesicle mobility, signal transduction, and tethering occurrences55. Prior investigations have demonstrated56 the involvement of RAB43 in the modulation of diverse signal transduction pathways linked to cellular invasion, apoptosis, and immune response. In their study, Li et al. made the discovery that an elevated expression of RAB43 is indicative of a poor prognosis and is associated with the occurrence of epithelial-mesenchymal transition in glioblastoma57. The Rab43 GTPase plays a critical role in facilitating the post-synaptic transport and neuron-specific sorting of G protein-coupled receptors58. Another research investigation has provided evidence that the administration of HMGB1 can impede the forward transport of CD91, which is regulated by Rab43, from the endoplasmic reticulum to the cell surface. This inhibition subsequently suppresses BMDM-mediated phagocytosis and delays the resolution of inflammation59. Notably, both the endoplasmic reticulum and immune response play pivotal roles in the pathogenesis of LDH and are intricately linked to Ras-related GTP-binding protein 43 (RAB43)60. Consequently, it is hypothesized that RAB43 may be closely associated with LDH by modulating various signal transduction pathways implicated in the endoplasmic reticulum and immune response.Dysferlin, also known as Dysferlin or DYSF, is a transmembrane glycoprotein belonging to the ferlin family. It is predominantly found in skeletal muscle and cardiac tissue, where it is situated on the plasma membrane. Dysferlin interacts with Caveolin 3 (Cav3) and Mitsgumin 53 (MG53), key components of the membrane repair system, and is essential for vesicle fusion during the process of plasma membrane repair61. In the absence of Dysferlin, muscle tissues exhibit inflammatory foci, infiltration of monocytes, and heightened activation of the NFκB signaling pathway62. The dysregulation of DYSF expression has been found to be closely linked to various hereditary muscle diseases and autoimmune disorders. In a study conducted by Xiao et al.63,64, the significant role of DYSF in the progression of two subgroups of idiopathic inflammatory myopathies (IIM), namely dermatomyositis (DM) and polymyositis (PM), was reported. In addition, DYSF is one of the cuproptosis-related asthma diagnostic genes65. Dysferlin has the potential to regulate LDH by influencing the secretion of multiple inflammatory factors and the metabolism of mononuclear cells. This suggests that dysferlin could play a role in the immune response and cellular processes associated with LDH.The primary role of Glucose-6-phosphate dehydrogenase (G6PD) is to facilitate the production of ribose and the reducing equivalent nicotinamide adenine dinucleotide phosphate (NADPH) via the pentose phosphate pathway (PPP)66. Plays a critical role in the synthesis of various biomolecules, including nucleic acids and fatty acids. Inadequate G6PD activity can result in hindered cell growth and increased mortality rates. Profound G6PD deficiency can impede embryonic development and hinder the growth of organisms. The present study reveals that alterations in G6PD activity are linked to autophagy, insulin resistance, infection, inflammation, and the pathophysiology of diabetes, and hypertension. Furthermore, abnormal activation of G6PD in various types of cancer results in increased cell proliferation and improved adaptability67. Moreover, G6PD may play a role in viral replication and the regulation of vascular smooth muscle function68. G6PD represents a newly identified gene signature linked to cuproptosis, with significant implications for the prognosis, clinical management, and potential immunotherapeutic strategies in hepatocellular carcinoma69. Notably, our findings demonstrate that G6PD exhibits a heightened diagnostic significance.This study represents the initial exploration of the role of CRGs in LDH, drawing upon existing knowledge. Although promising findings have been obtained, it is crucial to acknowledge the limitations inherent in our research, which primarily relies on bioinformatics analysis. To establish a more robust understanding of the relationship between candidate genes implicated in copper-induced cell death and LDH, future investigations should encompass more extensive clinical or experimental studies.
