Identification of immunodiagnostic biomarkers and drug screening for steroid-induced osteonecrosis of the femoral head

doi:10.12307/2025.973

Abstract

Abstract: BACKGROUND: The pathogenesis of steroid-induced osteonecrosis of the femoral head is not yet fully understood. A deep comprehension of the pathology and molecular mechanisms of steroid-induced osteonecrosis of the femoral head, as well as the search for diagnostic markers with high specificity and sensitivity, are crucial for the prevention and treatment of this condition.
OBJECTIVE: To identify immune diagnostic markers for steroid-induced osteonecrosis of the femoral head and predict potential drug targets through drug enrichment analysis and molecular docking techniques.
METHODS: The study utilized gene expression profile data (GSE123568 and GSE74089) from the GEO databases (a public gene expression database built by the U.S. National Center for Biotechnology Information). R software was used for data normalization and differential gene screening, followed by weighted gene co-expression network analysis (WGCNA) to identify disease-related genes. Immune-related genes were obtained from the GeneCards database and intersected with the differential genes and WGCNA gene sets to select immune-related genes for steroid-induced osteonecrosis of the femoral head. Mendelian randomization was used to validate the potential causal relationship between these immune-related genes and steroid-induced osteonecrosis of the femoral head. Gene Set Enrichment Analysis was conducted to analyze the immune-related pathways involved, and protein-protein interaction networks were used to assess functional associations. Finally, drug enrichment analysis and molecular docking were performed to predict potential drugs targeting these immune-related genes.
RESULTS AND CONCLUSION: Three key immune-related genes - RNASEL, SECTM1, and HSPA6 - were identified. These genes were highly expressed in steroid-induced osteonecrosis of the femoral head and exhibited good diagnostic potential, which were involved in multiple immune-related signaling pathways. Mendelian randomization analysis confirmed their potential causal relationship with steroid-induced osteonecrosis of the femoral head. Drug enrichment analysis and molecular docking identified nine potential drugs, including β-ecdysterone, showing the possibility of intervening in the pathological process of steroid-induced osteonecrosis of the femoral head by regulating the HSPA6 protein. These findings provide new biomarkers and drug targets for the early diagnosis and personalized treatment of steroid-induced osteonecrosis of the femoral head. They also highlight the potential application of bioinformatics in Chinese biomedical research, facilitating the integration and translational use of international data in local disease studies.

Key words: bioinformatics analysis, Mendelian randomization, immune-related genes, steroid-induced osteonecrosis of the femoral head, weighted correlation network analysis, engineered tissue construction

CLC Number:

Han Jie, Pan Chengzhen, Shang Yuzhi, Zhang Chi. Identification of immunodiagnostic biomarkers and drug screening for steroid-induced osteonecrosis of the femoral head[J]. Chinese Journal of Tissue Engineering Research, 2025, 29(35): 7690-7700.

Figures/Tables 11

2.2 WGCNA分析激素性股骨头坏死的特征基因采用WGCNA进一步校正后的全表达谱基因数据，该分析确定了9为最佳软阈值功率，确保基因网络中的无标度拓扑(图3A，B)。WGCNA结果显示绿色、黑色和红色模块的P均< 0.05，说明上述3个模块的基因与激素性股骨头坏死具有密切联系(图3C，D)。故将绿色、黑色和红色模块的306，506，760个基因取并集，得到1 572个激素性股骨头坏死的疾病特征基因，纳入后续研究。 2.3 激素性股骨头坏死免疫相关基因的筛选从GeneCards数据库获得了1 740个免疫相关基因，将这些免疫相关基因与激素性股骨头坏死的1 624个差异基因和WGCNA的1 572个疾病特征基因取交集，共得到78个激素性股骨头坏死的免疫相关基因(图4)。 2.4 孟德尔随机化分析验证激素性股骨头坏死的免疫相关基因孟德尔随机化分析结果表明，根据逆方差加权法从药物引起的骨坏死数据集中发现了3个与药物引起的骨坏死相关阳性基因(P < 0.05)，分别为RNASEL(2-5A依赖性核糖核酸酶)、SECTM1(分泌型跨膜蛋白1)、HSPA6(热休克70 kDa蛋白6)，它们均未出现显著异质性(P > 0.05)，亦未出现显著多效性(P > 0.05)，说明孟德尔随机化分析结果可靠(表1)。散点图表明RNASEL、SECTM1、HSPA6基因均是药物引起骨坏死的风险因素(图5A-C)，留一法敏感性分析图显示去除SECTM1的任一单核苷酸多态性均不影响整体结果，而去除RNASEL或HSPA6的某些单核苷酸多态性可能会导致整体结果转变为阴性(图5D-F)。上述3个免疫相关基因与药物引起的骨坏死之间具有潜在因果关系(图5G-I)。 2.5 免疫相关基因的诊断效能与相关性分析差异分析结果显示，与正常组相比，激素性股骨头坏死组中免疫相关基因RNASEL、SECTM1、HSPA6显著高表达(P < 0.05)，见图6A。染色体定位图显示，HSPA6和RNASEL位于1号染色体上，SECTM1位于17和18号染色体之间，见图6B。相关性分析结果表明，激素性股骨头坏死样本中RNASEL、SECTM1、HSPA6基"

因的表达量两两之间均呈显著的正相关性(P < 0.01)，见图6C。受试者工作特征曲线图显示上述3个基因在激素性股骨头坏死中的诊断效能均较高(曲线下面积AUC > 0.7)，见图6D-F。 2.6 单个基因的GSEA分析由于RNASEL、SECTM1、HSPA6在激素性股骨头坏死样本中显著高表达，因此进一步研究了RNASEL、SECTM1、HSPA6高表达组富集的相关通路与功能，进而分析上述3个基因在激素性股骨头坏死中的作用。GSEA富集结果表明，HSPA6高表达组涉及的KEGG信号通路包括NOD样受体信号通路、TOLL样受体信号通路、趋化因子信号通路、B细胞受体信号通路、 Janus激酶-信号转导与转录激活子信号通路、细胞周期、细胞凋亡等；生物学过程包括参与细胞对生物刺激的反应、白细胞介素1β生成的正向调节、白细胞介素8产生的正向调节、白细胞介素6的产生、淋巴细胞介导的免疫、炎症反应的正向调节等；细胞组分包括核糖体、典型炎性复合体、内吞囊泡等；分子功能包括TOLL样受体结合、未折叠蛋白结合、白细胞介素1受体结合、参与凋亡过程的肽酶激活剂活性等(图7A，B)。 RNASEL高表达组涉及的KEGG信号通路包括TOLL样受体信号通路、细胞黏附分子、胰岛素信号通路、细胞凋亡、NOD样受体信号通路、B细胞受体信号通路、T细胞受体信号通路、MTOR信号通路等；生物学过程包括干扰素介导的信号通路、白细胞介素1β生成的正向调节、对Ⅰ型干扰素的反应、干扰素β生成的正向调节、Ⅰ型干扰素产生的正向调节等；细胞组分包括核糖体、内吞囊泡、T细胞受体复合物等；分子功能包括核糖体的结构组成、TOLL样受体结合、白细胞介素1受体结合等(图7C，D)。 SECTM1高表达组涉及的KEGG信号通路包括TOLL样受体信号通路、NOD样受体信号通路、Janus激酶-信号转导与转录激活子信号通路、白细胞经内皮细胞迁移、细胞黏附分子、细胞周期、胰岛素信号通路等；生物学过程包括白细胞介素1β生成的正向调节、白细胞介素6产生的正向调节、白细胞介素8产生的正向调"

节、中性粒细胞趋化性、细胞对Ⅱ型干扰素的反应、Ⅰ型干扰素产生的正向调节等；细胞组分包括核糖体、内吞囊泡、典型炎性复合体等；分子功能包括TOLL样受体结合、白细胞介素1受体结合、未折叠蛋白结合等(图7E，F)。 2.7 免疫浸润相关性分析结果显示RNASEL和HSPA6基因表达量均与中性粒细胞水平呈正相关(P < 0.05)，RNASEL、SECTM1、HSPA6基因表达量与CD8+ T细胞水平呈负相关性(P < 0.05)；RNASEL和SECTM1基因表达量与记忆B细胞水平呈负相关性(P < 0.05)，SECTM1基因表达量与M1型巨噬细胞呈正相关(P < 0.05)，见图8，9。 2.8 免疫相关蛋白互作网络互作分析得到了由23个蛋白和305条互作关系组成的网络，其中包含77.64%物理互作关系、8.01%共表达互作关系、5.37%预测互作关系、3.63%共定位互作关系、2.87%遗传互作关系、1.88%通路互作关系、0.60%共享蛋白结构域互作关系。据统计有7个、5个、15个蛋白分别与RNASEL、SECTM1、HSPA6蛋白具有互作关系。其中，SECTM1与HSPA6之间具有共表达互作关系，与此次研究的免疫相关基因表达量相关性分析结果相一致。富集的相关功能包括蛋白质折叠、对Ⅰ型干扰素的细胞反应、泛素样蛋白连接酶结合、对细胞因子介导的信号通路的调节、对细胞因子刺激的反应调节等(图10)，上述功能与此次研究GSEA富集的结果相类似。 2.9 潜在药物预测及分子对接根据药物富集分析筛选标准，未富集到RNASEL和SECTM1基因的潜在药物；富集得到74种HSPA6基因的潜在药物(校正后P < 0.05)。为进一步验证潜在药物，将HSPA6蛋白与74种潜在药物进行分子对接，结果显示共有9种潜在药物和HSPA6蛋白的结合能< -29.3 kJ/mol，分别为β-七叶素、氟尼酸、二氟拉松、依布硒啉、白桦脂酸、白屈菜碱、棉酚、莫米松、利美索龙，其中β-七叶素的结合能最佳，为-42.28 kJ/mol(表2)。HSPA6蛋白与9种潜在药物的分子对接模型详见图11。"

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