Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, PR China.
Int Immunopharmacol. 2023 Mar;116:109588. doi: 10.1016/j.intimp.2022.109588. Epub 2023 Feb 9.
Due to a lack of studies on immune-related pathogenesis and a clinical diagnostic model, the diagnosis of Spinal Tuberculosis (STB) remains uncertain. Our study aimed to investigate the possible pathogenesis of STB and to develop a clinical diagnostic model for STB based on immune cell infiltration.
Label-free quantification protein analysis of five pairs of specimens was used to determine the protein expression of the intervertebral disc in STB and non-STB. GO enrichment analysis, and KEGG pathway analysis were used to investigate the pathogenesis of STB. The Hub proteins were then eliminated. Four datasets were downloaded from the GEO database to analyze immune cell infiltration, and the results were validated using blood routine test data from 8535TB and 7337 non-TB patients. Following that, clinical data from 164 STB and 162 non-STB patients were collected. The Random-Forest algorithm was used to screen out clinical predictors of STB and build a diagnostic model. The differential expression of MMP9 and STAT1 in STB and controls was confirmed using immunohistochemistry.
MMP9 and STAT1 were STB Hub proteins that were linked to disc destruction in STB. MMP9 and STAT1 were found to be associated with Monocytes, Neutrophils, and Lymphocytes in immune cell infiltration studies. Data from 15,872 blood routine tests revealed that the Monocytes ratio and Neutrophils ratio was significantly higher in TB patients than in non-TB patients (p < 0.001), while the Lymphocytes ratio was significantly lower in TB patients than in non-TB patients (p < 0.001). MMP9 and STAT1 expression were downregulated following the anti-TB therapy. For STB, a clinical diagnostic model was built using six clinical predictors: MR, NR, LR, ESR, BMI, and PLT. The model was evaluated using a ROC curve, which yielded an AUC of 0.816.
MMP9 and STAT1, immune-related hub proteins, were correlated with immune cell infiltration in STB patients. MR, NR, LR ESR, BMI, and PLT were clinical predictors of STB. Thus, the immune cell Infiltration-related clinical diagnostic model can predict STB effectively.
由于缺乏对免疫相关发病机制的研究和临床诊断模型，脊柱结核（STB）的诊断仍不确定。本研究旨在探讨 STB 的可能发病机制，并基于免疫细胞浸润建立 STB 的临床诊断模型。
采用无标记定量蛋白质分析技术对 5 对 STB 和非 STB 椎间盘标本进行检测，确定 STB 椎间盘的蛋白表达。采用 GO 富集分析和 KEGG 通路分析探讨 STB 的发病机制。然后消除枢纽蛋白。从 GEO 数据库下载了 4 个数据集，分析免疫细胞浸润情况，并使用 8535 例 TB 和 7337 例非 TB 患者的血常规检测数据进行验证。随后收集了 164 例 STB 和 162 例非 STB 患者的临床资料。采用随机森林算法筛选 STB 的临床预测指标，并建立诊断模型。采用免疫组化法验证 MMP9 和 STAT1 在 STB 及对照组中的差异表达。
MMP9 和 STAT1 是 STB 的枢纽蛋白，与 STB 中的椎间盘破坏有关。在免疫细胞浸润研究中，发现 MMP9 和 STAT1 与单核细胞、中性粒细胞和淋巴细胞有关。15872 例血常规检测数据显示，TB 患者的单核细胞比和中性粒细胞比显著高于非 TB 患者（p<0.001），而 TB 患者的淋巴细胞比显著低于非 TB 患者（p<0.001）。抗结核治疗后 MMP9 和 STAT1 的表达下调。对于 STB，使用 6 个临床预测指标（MR、NR、LR、ESR、BMI 和 PLT）构建临床诊断模型。该模型的 ROC 曲线评估结果为 AUC=0.816。
MMP9 和 STAT1 是与免疫相关的枢纽蛋白，与 STB 患者的免疫细胞浸润有关。MR、NR、LR、ESR、BMI 和 PLT 是 STB 的临床预测指标。因此，基于免疫细胞浸润的临床诊断模型可以有效地预测 STB。
