Chen Jianfeng, Qi Fuwei, Li Guanshen, Deng Qiaosong, Zhang Chenlin, Li Xiaojun, Zhang Yafeng
Department of Spine, Wuxi Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi 214000, China.
Department of Anesthesiology, The First People's Hospital of Taicang, Taicang Affiliated Hospital of Soochow University, Jiangsu Province, 215413 Suzhou City, China.
Stem Cells Int. 2023 Jan 24;2023:7055264. doi: 10.1155/2023/7055264. eCollection 2023.
Intervertebral disc degeneration (IDD), which is distinguished by a variety of pathologic alterations, is the major cause of low back pain (LBP). Nonetheless, preventative measures or therapies that may delay IDD are scarcely available. In this study, we sought to identify new diagnostic biological markers for IDD. In this first-of-a-kind study combining machine learning, stem cell treatment samples and single-cell sequencing data were collected. Differentially expressed genes (DEGs) were detected from the treatment group and clusters. To filter potential markers, support vector machine analysis and LASSO were performed. LAPTM5 was found to be the hub gene for IDD. In addition, the results of single-cell sequencing demonstrated the critical function of stem cells in IDD. Finally, we found that aging is significantly associated with the rate of stem cells. In general, our results may offer fresh insights that may be used in the investigation of innovative markers for diagnosing IDD. The critical genes identified by the machine learning algorithm could provide new perspectives on IDD.
椎间盘退变（IDD）以多种病理改变为特征，是腰痛（LBP）的主要原因。然而，几乎没有可延缓IDD的预防措施或治疗方法。在本研究中，我们试图识别用于IDD的新诊断生物标志物。在这项首次将机器学习、干细胞治疗样本和单细胞测序数据相结合的研究中，我们收集了相关数据。从治疗组和聚类中检测到差异表达基因（DEG）。为了筛选潜在标志物，进行了支持向量机分析和套索分析。发现LAPTM5是IDD的关键基因。此外，单细胞测序结果证明了干细胞在IDD中的关键作用。最后，我们发现衰老与干细胞速率显著相关。总体而言，我们的结果可能为IDD诊断新标志物的研究提供新的见解。通过机器学习算法确定的关键基因可为IDD提供新的视角。
