Liu Yishan, Li Yang, Liu Yixuan, Gao Zhongya, Zhang Jianjun, Qiu Youcai, Wang Can, Lu Xuhua, Yang Jiandong
Institute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, People's Republic of China.
Department of Orthopaedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai, China.
Global Spine J. 2025 Jan;15(1):161-174. doi: 10.1177/21925682241255894. Epub 2024 May 17.
Bioinformatics analysis of Gene Expression Omnibus (GEO).
Ossification of the ligamentum flavum (OLF) and ankylosing spondylitis (AS) represent intricate conditions marked by the gradual progression of endochondral ossification. This investigation endeavors to unveil common biomarkers associated with heterotopic ossification and explore the potential molecular regulatory mechanisms.
Microarray and RNA-sequencing datasets retrieved from the Gene Expression Omnibus (GEO) repository were harnessed to discern differentially expressed genes (DEGs) within the OLF and AS datasets. Subsequently, Weighted Gene Co-expression Network Analysis (WGCNA) was implemented to pinpoint co-expression modules linked to OLF and AS. Common genes were further subjected to an examination of functional pathway enrichment. Moreover, hub intersection genes were identified using the Least Absolute Shrinkage and Selection Operator (LASSO) regression, followed by an evaluation of diagnostic performance in external OLF and AS cohorts. Lastly, an analysis of immune cell infiltration was conducted to scrutinize the correlation of immune cell presence with shared biomarkers in OLF and AS.
A total of 1353 and 91 Differentially Expressed Genes (DEGs) were identified in OLF and AS, respectively. Using the Weighted Gene Co-expression Network Analysis (WGCNA), 2 modules were found to be notably significant for OLF and AS. The integrative bioinformatic analysis revealed 3 hub genes (MAB21L2, MEGF10, ISLR) as shared risk biomarkers, with MAB21L2 being the central focus. Receiver Operating Characteristic (ROC) analysis exhibited a strong diagnostic potential for these hub genes. Gene Ontology (GO) analysis indicated their involvement in the positive regulation of myoblast proliferation. Notably, MAB21L2 was singled out as the optimal common biomarker for OLF and AS. Furthermore, an analysis of immune infiltration demonstrated a correlation between MAB21L2 expression and changes in immune cells. Activated CD8 T cells were identified as shared differential immune infiltrating cells significantly linked to MAB21L2 in both OLF and AS.
This study represents the first instance of identifying MAB21L2 as a prospective diagnostic marker for patients contending with OLF associated with AS. The research results indicate that the ECM-receptor interaction and the cell-cell adhesion may play a role in both disease processes. This newfound knowledge not only enhances our understanding of the pathogenesis behind spinal ligament ossification but also uncovers potential targets for therapeutic interventions.
基因表达综合数据库（GEO）的生物信息学分析。
黄韧带骨化（OLF）和强直性脊柱炎（AS）是以内软骨骨化逐渐发展为特征的复杂病症。本研究旨在揭示与异位骨化相关的共同生物标志物，并探索潜在的分子调控机制。
利用从基因表达综合数据库（GEO）存储库中检索到的微阵列和RNA测序数据集，以识别OLF和AS数据集中的差异表达基因（DEG）。随后，实施加权基因共表达网络分析（WGCNA），以确定与OLF和AS相关的共表达模块。对共同基因进行功能通路富集检查。此外，使用最小绝对收缩和选择算子（LASSO）回归识别枢纽交叉基因，随后评估外部OLF和AS队列中的诊断性能。最后，进行免疫细胞浸润分析，以研究免疫细胞存在与OLF和AS中共享生物标志物的相关性。
在OLF和AS中分别鉴定出1353个和91个差异表达基因（DEG）。使用加权基因共表达网络分析（WGCNA），发现2个模块对OLF和AS具有显著意义。综合生物信息学分析揭示了3个枢纽基因（MAB21L2、MEGF10、ISLR）作为共同的风险生物标志物，其中MAB21L2是核心关注点。受试者工作特征（ROC）分析显示这些枢纽基因具有强大的诊断潜力。基因本体（GO）分析表明它们参与成肌细胞增殖的正调控。值得注意的是，MAB21L2被选为OLF和AS的最佳共同生物标志物。此外，免疫浸润分析表明MAB21L2表达与免疫细胞变化之间存在相关性。活化的CD8 T细胞被确定为在OLF和AS中均与MAB21L2显著相关的共同差异免疫浸润细胞。
本研究首次将MAB21L2鉴定为与AS相关的OLF患者的潜在诊断标志物。研究结果表明，细胞外基质受体相互作用和细胞间粘附可能在这两种疾病过程中起作用。这一新知识不仅增进了我们对脊柱韧带骨化发病机制的理解，还揭示了治疗干预的潜在靶点。
