Ni Yuanpiao, Zhong Linrui, Li Yanhui, Zhang Zeng, Ming Bin, Qing Yufeng, Zhang Quanbo
Research Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Department of Rheumatology and Immunology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Front Immunol. 2024 Dec 20;15:1480492. doi: 10.3389/fimmu.2024.1480492. eCollection 2024.
Inflammation of the spine and sacroiliac joints is a hallmark of the chronic, progressive inflammatory illness known as ankylosing spondylitis (AS). The insidious onset and non-specific early symptoms of AS often lead to delays in diagnosis and treatment, which may result in the onset of disability. It is therefore imperative to identify new biomarkers.
In this study, datasets GSE73754 and GSE25101 were derived from the Gene Expression Omnibus (GEO). Key genes were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA). A model was then established using LASSO regression, and then it was subjected to the receiver operating characteristic (ROC) curve analysis for evaluation of the diagnostic accuracy of the genes. Subsequently, immune infiltration analysis was conducted to demonstrate the immune infiltration status of the samples and the correlation between key genes and immune infiltration. Finally, the expression levels of key genes in peripheral blood mononuclear cells (PBMCs) and their correlation with clinical indicators were validated via RT-qPCR assay.
Through WGCNA and differential expression analysis, 6 genes were identified. Ultimately, five key genes (ACSL1, SLC40A1, GZMM, TRIB1, XBP1) were determined using LASSO regression. The area under the ROC curve (AUC) for these genes was greater than 0.7, indicating favorable diagnostic performance. Immune infiltration analysis showed that AS was associated with infiltration levels of various immune cells. RT-qPCR validated that the expression of ACSL1, SLC40A1, GZMM, and XBP1 was consistent with the predictive model, whereas TRIB1 expression was contrary to the predictive model. Clinical correlation analysis of key genes revealed that ACSL1 was positively linked to hsCRP levels, GZMM was negatively linked to, hsCRP levels, and neutrophil absolute values, SLC40A1 was positively linked to ESR, hsCRP levels and neutrophil absolute values, and XBP1 was negatively linked to ESR, hsCRP levels, and neutrophil absolute values.
This study identified key genes that may reveal a potential association between AS and ferroptosis, demonstrating high diagnostic value. Furthermore, the expression levels of these genes in peripheral blood mononuclear cells (PBMCs) are strongly correlated with disease activity. These findings not only suggest potential biomarkers for the diagnosis of AS but also offer important references for exploring new therapeutic targets, highlighting their substantial clinical applicability.
脊柱和骶髂关节炎症是强直性脊柱炎（AS）这种慢性进行性炎症性疾病的一个标志。AS隐匿性起病且早期症状不具特异性，常导致诊断和治疗延迟，进而可能导致残疾的发生。因此，识别新的生物标志物至关重要。
在本研究中，数据集GSE73754和GSE25101来源于基因表达综合数据库（GEO）。通过差异表达分析和加权基因共表达网络分析（WGCNA）识别关键基因。然后使用LASSO回归建立模型，并对其进行受试者工作特征（ROC）曲线分析以评估基因的诊断准确性。随后进行免疫浸润分析，以展示样本的免疫浸润状态以及关键基因与免疫浸润之间的相关性。最后，通过RT-qPCR检测验证关键基因在外周血单核细胞（PBMC）中的表达水平及其与临床指标的相关性。
通过WGCNA和差异表达分析，识别出6个基因。最终，使用LASSO回归确定了5个关键基因（ACSL1、SLC40A1、GZMM、TRIB1、XBP1）。这些基因的ROC曲线下面积（AUC）大于0.7，表明具有良好的诊断性能。免疫浸润分析表明，AS与多种免疫细胞的浸润水平相关。RT-qPCR验证ACSL1、SLC40A1、GZMM和XBP 的表达与预测模型一致，而TRIB1的表达与预测模型相反。关键基因的临床相关性分析显示，ACSL1与hsCRP水平呈正相关，GZMM与hsCRP水平以及中性粒细胞绝对值呈负相关，SLC40A1与ESR、hsCRP水平和中性粒细胞绝对值呈正相关，XBP1与ESR、hsCRP水平和中性粒细胞绝对值呈负相关。
本研究识别出可能揭示AS与铁死亡之间潜在关联的关键基因，显示出较高的诊断价值。此外，这些基因在外周血单核细胞（PBMC）中的表达水平与疾病活动度密切相关。这些发现不仅为AS的诊断提示了潜在的生物标志物，也为探索新的治疗靶点提供了重要参考，凸显了它们显著的临床适用性。
