Sun Haoyan, Xu Meng, Mi Dianlong, Li Qingyu, Sun Haipeng, Song Yang
Orthopedic Medical Center, The Second Affiliated Hospital of Jilin University, Changchun, Jilin, China.
Front Immunol. 2025 Sep 3;16:1640657. doi: 10.3389/fimmu.2025.1640657. eCollection 2025.
Osteonecrosis of the femoral head (ONFH) is a disabling orthopedic condition that remains challenging to diagnose at an early stage. Recent evidence suggests that immune dysregulation plays a central role in the development of both ONFH and metabolic syndrome (MetS), a cluster of metabolic abnormalities associated with increased ONFH risk. However, reliable noninvasive diagnostic biomarkers for ONFH, particularly in high-risk MetS populations, are still lacking. This study aimed to identify key diagnostic long non-coding RNAs (lncRNAs) in ONFH patients with MetS and to construct an immune-related competitive endogenous RNA (ceRNA) network. Plasma lncRNA and mRNA expression profiles from 9 ONFH patients and 6 healthy controls were analyzed to identify differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs), followed by ceRNA network construction. The MetS dataset from the Gene Expression Omnibus (GEO) was integrated, and weighted gene co-expression network analysis (WGCNA), functional enrichment, protein-protein interaction (PPI) network analysis, MCODE, CytoHubba-MCC, and random forest (RF) algorithms were employed to identify hub mRNAs and their associated lncRNAs. A nomogram model was developed, and diagnostic potential was evaluated using receiver operating characteristic (ROC) analysis and validation in an independent cohort (45 ONFH and 45 control samples). A total of 424 DElncRNAs and 1,431 DEmRNAs were identified, and a ceRNA network involving 7 lncRNAs, 24 miRNAs, and 683 mRNAs was constructed. Integration with the MetS dataset yielded 506 intersecting mRNAs, from which 11 hub mRNAs and 6 related lncRNAs were screened. Five key lncRNAs were selected by RF analysis to construct a diagnostic model with strong predictive performance (AUC > 0.7 in both RNA-seq and qRT-PCR validation). The immune-related ceRNA network also demonstrated significant associations with immune cell infiltration patterns. In conclusion, five candidate lncRNAs (MRPS30-DT, LINC01106, MIR100HG, WDR11-AS1, and PELATON) were identified as promising noninvasive diagnostic biomarkers for ONFH in MetS populations. These findings offer novel insights into immune-related regulatory mechanisms and may support early diagnosis using peripheral blood.
股骨头坏死（ONFH）是一种致残性骨科疾病，早期诊断仍具有挑战性。最近的证据表明，免疫失调在ONFH和代谢综合征（MetS）的发生发展中起核心作用，MetS是一组与ONFH风险增加相关的代谢异常。然而，仍缺乏可靠的ONFH非侵入性诊断生物标志物，尤其是在高危MetS人群中。本研究旨在识别MetS的ONFH患者中的关键诊断性长链非编码RNA（lncRNA），并构建一个免疫相关的竞争性内源性RNA（ceRNA）网络。分析了9例ONFH患者和6例健康对照的血浆lncRNA和mRNA表达谱，以识别差异表达的lncRNA（DElncRNA）和mRNA（DEmRNA），随后构建ceRNA网络。整合来自基因表达综合数据库（GEO）的MetS数据集，并采用加权基因共表达网络分析（WGCNA）、功能富集、蛋白质-蛋白质相互作用（PPI）网络分析、MCODE、CytoHubba-MCC和随机森林（RF）算法来识别枢纽mRNA及其相关lncRNA。开发了一个列线图模型，并在一个独立队列（45个ONFH样本和45个对照样本）中使用受试者操作特征（ROC）分析和验证来评估诊断潜力。共鉴定出424个DElncRNA和1431个DEmRNA，并构建了一个涉及7个lncRNA、24个miRNA和683个mRNA的ceRNA网络。与MetS数据集整合产生了506个交集mRNA，从中筛选出11个枢纽mRNA和6个相关lncRNA。通过RF分析选择了5个关键lncRNA来构建具有强大预测性能的诊断模型（RNA测序和qRT-PCR验证中的AUC均>0.7）。免疫相关的ceRNA网络也显示出与免疫细胞浸润模式有显著关联。总之，5个候选lncRNA（MRPS30-DT、LINC01106、MIR100HG、WDR11-AS1和PELATON）被确定为MetS人群中ONFH有前景的非侵入性诊断生物标志物。这些发现为免疫相关调节机制提供了新见解，并可能支持使用外周血进行早期诊断。
