Low back pain (LBP) is a prevalent health problem worldwide that affects over 80% of adults during their lifetime. Intervertebral disc degeneration (IDD) is a well-recognized leading cause of LBP. IDD is classified into five grades according to the Pfirrmann classification system. The purpose of this study was to identify potential biomarkers in different IDD grades through an integrated analysis of proteome sequencing (PRO-seq), bulk RNA sequencing (bRNA-seq) and single-cell RNA sequencing (scRNA-seq) data. Eight cases of grade I-IV IDD were obtained. Grades I and II were considered non-degenerative discs (relatively normal), whereas grades III and IV were considered degenerative discs. PRO-seq analysis was performed to identify differentially expressed proteins (DEPs) in various IDD grades. Variation analysis was performed on bRNA-seq data to differentiate expressed genes (DEGs) in normal and degenerated discs. In addition, scRNA-seq was performed to validate DEGs in degenerated and non-degenerated nucleus pulposus (NP). Machine learning (ML) algorithms were used to screen hub genes. The receiver operating characteristic (ROC) curve was used to validate the efficiency of the screened hub genes to predict IDD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to analyze function enrichment and signaling pathways. Protein-protein interaction (PPI) network was used to prioritize disease-related proteins. SERPINA1, ORM2, FGG and COL1A1 were identified through PRO-seq as the hub proteins involved in regulating IDD. ML algorithms selected ten hub genes, including IBSP, COL6A2, MMP2, SERPINA1, ACAN, FBLN7, LAMB2, TTLL7, COL9A3, and THBS4 in bRNA-seq. Since serine protease inhibitor clade A member 1 (SERPINA1) was the only common gene, its accuracy in degenerated and non-degenerated NP cells was validated using scRNA-seq. Then, the rat degeneration model of caudal vertebra was established. The expression of SERPINA1 and ORM2 was detected using immunohistochemical staining of human and rat intervertebral discs. The results showed that SERPINA1 was poorly expressed in the degenerative group. We further explored the potential function of SERPINA1 by Gene Set Enrichment Analysis (GSEA) and cell-cell communication. Therefore, SERPINA1 can be used as a biomarker to regulate or predict the progress of disc degeneration.

中文翻译：

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整合蛋白质组测序、批量 RNA 测序和单细胞 RNA 测序，以识别不同程度椎间盘退变的潜在生物标志物

腰痛 (LBP) 是全球普遍存在的健康问题，80% 以上的成年人在其一生中都会受到影响。椎间盘退变 (IDD) 是 LBP 公认的主要原因。根据 Pfirrmann 分类系统，IDD 分为五个等级。本研究的目的是通过对蛋白质组测序 (PRO-seq)、大量 RNA 测序 (bRNA-seq) 和单细胞 RNA 测序 (scRNA-seq) 数据的综合分析，确定不同 IDD 等级的潜在生物标志物。获得了 8 例 I-IV 级 IDD。I 级和 II 级被认为是非退化性椎间盘（相对正常），而 III 级和 IV 级被认为是退化性椎间盘。进行 PRO-seq 分析以鉴定不同 IDD 等级的差异表达蛋白 (DEP)。对 bRNA-seq 数据进行变异分析，以区分正常和退化椎间盘中的表达基因 (DEG)。此外，还进行了 scRNA-seq 以验证退化和未退化髓核 (NP) 中的 DEG。机器学习 (ML) 算法用于筛选中心基因。接受者操作特征 (ROC) 曲线用于验证筛选的中枢基因预测 IDD 的效率。进行基因本体论 (GO) 和京都基因和基因组百科全书 (KEGG) 分析以分析功能富集和信号通路。蛋白质-蛋白质相互作用 (PPI) 网络用于确定与疾病相关的蛋白质的优先级。SERPINA1、ORM2、FGG 和 COL1A1 通过 PRO-seq 被鉴定为参与调节 IDD 的中枢蛋白。ML算法选取了10个hub基因，包括IBSP、COL6A2、MMP2、SERPINA1、bRNA-seq 中的 ACAN、FBLN7、LAMB2、TTLL7、COL9A3 和 THBS4。由于丝氨酸蛋白酶抑制剂进化枝 A 成员 1 (SERPINA1) 是唯一的常见基因，因此使用 scRNA-seq 验证了其在退化和非退化 NP 细胞中的准确性。然后，建立大鼠尾椎退变模型。使用人和大鼠椎间盘的免疫组织化学染色检测 SERPINA1 和 ORM2 的表达。结果显示，SERPINA1在退行性组中表达较差。我们通过基因集富集分析 (GSEA) 和细胞间通讯进一步探索了 SERPINA1 的潜在功能。因此，SERPINA1可以作为生物标志物来调节或预测椎间盘退变的进展。由于丝氨酸蛋白酶抑制剂进化枝 A 成员 1 (SERPINA1) 是唯一的常见基因，因此使用 scRNA-seq 验证了其在退化和非退化 NP 细胞中的准确性。然后，建立大鼠尾椎退变模型。使用人和大鼠椎间盘的免疫组织化学染色检测 SERPINA1 和 ORM2 的表达。结果显示，SERPINA1在退行性组中表达较差。我们通过基因集富集分析 (GSEA) 和细胞间通讯进一步探索了 SERPINA1 的潜在功能。因此，SERPINA1可以作为生物标志物来调节或预测椎间盘退变的进展。由于丝氨酸蛋白酶抑制剂进化枝 A 成员 1 (SERPINA1) 是唯一的常见基因，因此使用 scRNA-seq 验证了其在退化和非退化 NP 细胞中的准确性。然后，建立大鼠尾椎退变模型。使用人和大鼠椎间盘的免疫组织化学染色检测 SERPINA1 和 ORM2 的表达。结果显示，SERPINA1在退行性组中表达较差。我们通过基因集富集分析 (GSEA) 和细胞间通讯进一步探索了 SERPINA1 的潜在功能。因此，SERPINA1可以作为生物标志物来调节或预测椎间盘退变的进展。使用人和大鼠椎间盘的免疫组织化学染色检测 SERPINA1 和 ORM2 的表达。结果显示，SERPINA1在退行性组中表达较差。我们通过基因集富集分析 (GSEA) 和细胞间通讯进一步探索了 SERPINA1 的潜在功能。因此，SERPINA1可以作为生物标志物来调节或预测椎间盘退变的进展。使用人和大鼠椎间盘的免疫组织化学染色检测 SERPINA1 和 ORM2 的表达。结果显示，SERPINA1在退行性组中表达较差。我们通过基因集富集分析 (GSEA) 和细胞间通讯进一步探索了 SERPINA1 的潜在功能。因此，SERPINA1可以作为生物标志物来调节或预测椎间盘退变的进展。