Shi Bo, Chen Fei, Gong Jianmin, Khan Adeel, Qian Xiang, Xu Zhipeng, Yang Ping
Department of Clinical Laboratory, Nanjing Jiangning District Hospital of Traditional Chinese Medicine (TCM), Nanjing, China.
Department of Clinical Laboratory, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu, China.
Front Cell Infect Microbiol. 2024 Dec 3;14:1364333. doi: 10.3389/fcimb.2024.1364333. eCollection 2024.
Bacteriome alterations have been implicated in the pathogenesis of systemic lupus erythematosus (SLE). However, the relationship between SLE and the urinary microbiome remains underexplored. This study aimed to characterize the urinary microbiome of SLE patients using 16S rRNA sequencing and to investigate its correlations with clinical parameters through integrative analyses.
Urine sediment samples were collected from individuals with SLE and lupus nephritis (LN) (n = 20), SLE without LN (n = 22), and healthy controls (HCs) (n = 23). DNA was extracted and subjected to 16S rRNA sequencing to profile the urinary microbiome. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the diagnostic efficacy of urinary microbiota, while Spearman's correlation analysis was employed to identify links between specific microbial taxa and clinical parameters. Functional predictions of bacterial roles were performed using Picrust2.
The urinary microbiota diagnostic model exhibited excellent performance in distinguishing SLE patients from HCs. Spearman's analysis revealed significant correlations between the urinary microbiome and clinical parameters. Specifically, and genera showed positive correlations with vitamin D levels, cylinderuria, and proteinuria, while , , , and displayed negative correlations with proteinuria and albumin-to-creatinine ratio (ACR). Functional predictions indicated that the urinary microbiome might influence immune regulation through modulation of signaling pathways and metabolic processes.
Our study is the first to reveal dysbiosis in the urinary microbiome of patients with SLE. Certain bacterial taxa in the urinary microbiome were identified as potential diagnostic biomarkers for SLE. Furthermore, the functional implications of these bacterial communities suggest their involvement in immune modulation, highlighting the potential for further investigation into their roles in SLE pathogenesis and diagnosis.
细菌群落的改变与系统性红斑狼疮（SLE）的发病机制有关。然而，SLE与尿液微生物群之间的关系仍未得到充分研究。本研究旨在通过16S rRNA测序对SLE患者的尿液微生物群进行特征分析，并通过综合分析研究其与临床参数的相关性。
收集系统性红斑狼疮（SLE）和狼疮性肾炎（LN）患者（n = 20）、无LN的SLE患者（n = 22）和健康对照者（HCs）（n = 23）的尿沉渣样本。提取DNA并进行16S rRNA测序以分析尿液微生物群。进行受试者操作特征（ROC）曲线分析以评估尿液微生物群的诊断效能，同时采用Spearman相关性分析来确定特定微生物分类群与临床参数之间的联系。使用Picrust2对细菌作用进行功能预测。
尿液微生物群诊断模型在区分SLE患者和健康对照者方面表现出优异的性能。Spearman分析显示尿液微生物群与临床参数之间存在显著相关性。具体而言，[具体菌属1]和[具体菌属2]与维生素D水平、管型尿和蛋白尿呈正相关，而[具体菌属3]、[具体菌属4]、[具体菌属5]和[具体菌属6]与蛋白尿和白蛋白与肌酐比值（ACR）呈负相关。功能预测表明，尿液微生物群可能通过调节信号通路和代谢过程影响免疫调节。
我们的研究首次揭示了SLE患者尿液微生物群的失调。尿液微生物群中的某些细菌分类群被确定为SLE的潜在诊断生物标志物。此外，这些细菌群落的功能意义表明它们参与免疫调节，突出了进一步研究它们在SLE发病机制和诊断中的作用的潜力。
