PDF(Pubmed)
Abstract：
UNASSIGNED: Inflammation and immune factors are the core of intervertebral disc degeneration (IDD), but the immune environment and epigenetic regulation process of IDD remain unclear. This study aims to identify immune-related diagnostic candidate genes for IDD, and search for potential pathogenesis and therapeutic targets for IDD.
UNASSIGNED: Gene expression datasets were obtained from the Gene Expression Omnibus (GEO). Differential expression immune genes (Imm-DEGs) were identified through weighted gene correlation network analysis (WGCNA) and linear models for microarray data analysis (Limma). LASSO algorithm was used to identify feature genes related to IDD, which were compared with core node genes in PPI network to obtain hub genes. Based on the coefficients of hub genes, a risk model was constructed, and the diagnostic value of hub genes was further evaluated through receiver operating characteristic (ROC) analysis. Xcell, an immunocyte analysis tool, was used to estimate the infiltration of immune cells. Finally, nucleus pulposus cells were co-cultured with macrophages to create an M1 macrophage immune inflammatory environment, and the changes of hub genes were verified.
UNASSIGNED: Combined with the results of WGCNA and Limma gene differential analysis, a total of 30 Imm-DEGs were identified. Imm-DEGs enriched in multiple pathways related to immunity and inflammation. LASSO algorithm identified 10 feature genes from Imm-DEGs that significantly affected IDD, and after comparison with core node genes in the PPI network of Imm-DEGs, 6 hub genes (NR1H3, SORT1, PTGDS, AGT, IRF1, TGFB2) were determined. Results of ROC curves and external dataset validation showed that the risk model constructed with the 6 hub genes had high diagnostic value for IDD. Immunocyte infiltration analysis showed the presence of various dysregulated immune cells in the degenerative nucleus pulposus tissue. In vitro experimental results showed that the gene expression of NR1H3, SORT1, PTGDS, IRF1, and TGFB2 in nucleus pulposus cells in the immune inflammatory environment was up-regulated, but the change of AGT was not significant.
UNASSIGNED: The hub genes NR1H3, SORT1, PTGDS, IRF1, and TGFB2 can be used as immunorelated biomarkers for IDD, and may be potential targets for immune regulation therapy for IDD.
UNASSIGNED: Gene expression datasets were obtained from the Gene Expression Omnibus (GEO). Differential expression immune genes (Imm-DEGs) were identified through weighted gene correlation network analysis (WGCNA) and linear models for microarray data analysis (Limma). LASSO algorithm was used to identify feature genes related to IDD, which were compared with core node genes in PPI network to obtain hub genes. Based on the coefficients of hub genes, a risk model was constructed, and the diagnostic value of hub genes was further evaluated through receiver operating characteristic (ROC) analysis. Xcell, an immunocyte analysis tool, was used to estimate the infiltration of immune cells. Finally, nucleus pulposus cells were co-cultured with macrophages to create an M1 macrophage immune inflammatory environment, and the changes of hub genes were verified.
UNASSIGNED: Combined with the results of WGCNA and Limma gene differential analysis, a total of 30 Imm-DEGs were identified. Imm-DEGs enriched in multiple pathways related to immunity and inflammation. LASSO algorithm identified 10 feature genes from Imm-DEGs that significantly affected IDD, and after comparison with core node genes in the PPI network of Imm-DEGs, 6 hub genes (NR1H3, SORT1, PTGDS, AGT, IRF1, TGFB2) were determined. Results of ROC curves and external dataset validation showed that the risk model constructed with the 6 hub genes had high diagnostic value for IDD. Immunocyte infiltration analysis showed the presence of various dysregulated immune cells in the degenerative nucleus pulposus tissue. In vitro experimental results showed that the gene expression of NR1H3, SORT1, PTGDS, IRF1, and TGFB2 in nucleus pulposus cells in the immune inflammatory environment was up-regulated, but the change of AGT was not significant.
UNASSIGNED: The hub genes NR1H3, SORT1, PTGDS, IRF1, and TGFB2 can be used as immunorelated biomarkers for IDD, and may be potential targets for immune regulation therapy for IDD.
摘要：
■炎症和免疫因素是椎间盘退变（IDD）的核心，但IDD的免疫环境和表观遗传调控过程仍不清楚。本研究旨在确定IDD的免疫相关诊断候选基因，寻找IDD的潜在发病机制和治疗靶点。
■从基因表达综合(GEO)获得基因表达数据集。通过加权基因相关网络分析(WGCNA)和用于微阵列数据分析的线性模型(Limma)鉴定差异表达免疫基因(Imm-DEGs)。LASSO算法用于识别与IDD相关的特征基因，将其与PPI网络中的核心节点基因进行比较以获得集线器基因。根据枢纽基因的系数，建立了风险模型，并通过受试者工作特征（ROC）分析进一步评估了hub基因的诊断价值。Xcell,一种免疫细胞分析工具，用于估计免疫细胞的浸润。最后,将髓核细胞与巨噬细胞共培养，以创建M1巨噬细胞免疫炎症环境，并验证了hub基因的变化。
■结合WGCNA和Limma基因差异分析的结果，总共鉴定出30Imm-DEG。Imm-DEGs富含与免疫和炎症相关的多种途径。LASSO算法从Imm-DEG中鉴定出10个显著影响IDD的特征基因,在与Imm-DEG的PPI网络中的核心节点基因进行比较后，6个hub基因(NR1H3、SORT1、PTGDS、AGT,测定了IRF1、TGFB2)。ROC曲线和外部数据集验证结果表明，6个hub基因构建的风险模型对IDD具有较高的诊断价值。免疫细胞浸润分析显示退行性髓核组织中存在各种失调的免疫细胞。体外实验成果显示NR1H3、SORT1、PTGDS、IRF1、TGFB2在免疫炎症环境中髓核细胞表达上调,但AGT变化不显著。
■中枢基因NR1H3、SORT1、PTGDS、IRF1和TGFB2可用作IDD的免疫相关生物标志物，可能是IDD免疫调节治疗的潜在靶点。
■从基因表达综合(GEO)获得基因表达数据集。通过加权基因相关网络分析(WGCNA)和用于微阵列数据分析的线性模型(Limma)鉴定差异表达免疫基因(Imm-DEGs)。LASSO算法用于识别与IDD相关的特征基因，将其与PPI网络中的核心节点基因进行比较以获得集线器基因。根据枢纽基因的系数，建立了风险模型，并通过受试者工作特征（ROC）分析进一步评估了hub基因的诊断价值。Xcell,一种免疫细胞分析工具，用于估计免疫细胞的浸润。最后,将髓核细胞与巨噬细胞共培养，以创建M1巨噬细胞免疫炎症环境，并验证了hub基因的变化。
■结合WGCNA和Limma基因差异分析的结果，总共鉴定出30Imm-DEG。Imm-DEGs富含与免疫和炎症相关的多种途径。LASSO算法从Imm-DEG中鉴定出10个显著影响IDD的特征基因,在与Imm-DEG的PPI网络中的核心节点基因进行比较后，6个hub基因(NR1H3、SORT1、PTGDS、AGT,测定了IRF1、TGFB2)。ROC曲线和外部数据集验证结果表明，6个hub基因构建的风险模型对IDD具有较高的诊断价值。免疫细胞浸润分析显示退行性髓核组织中存在各种失调的免疫细胞。体外实验成果显示NR1H3、SORT1、PTGDS、IRF1、TGFB2在免疫炎症环境中髓核细胞表达上调,但AGT变化不显著。
■中枢基因NR1H3、SORT1、PTGDS、IRF1和TGFB2可用作IDD的免疫相关生物标志物，可能是IDD免疫调节治疗的潜在靶点。
