鉴定人血浆中的氨基酸代谢组特征可区分狼疮肾炎与系统性红斑狼疮。

Identification of amino acids metabolomic profiling in human plasma distinguishes lupus nephritis from systemic lupus erythematosus.

机构信息

Traditional Chinese Medicine Integrated Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, P.R. China.

Research Institute of Nephrology, Zhengzhou University, Zhengzhou, 450052, P.R. China.

出版信息

Amino Acids. 2024 Sep 18;56(1):56. doi: 10.1007/s00726-024-03418-1.

Abstract

Lupus nephritis (LN) is an immunoinflammatory glomerulonephritis associated with renal involvement in systemic lupus erythematosus (SLE). Given the close relationship between plasma amino acids (AAs) and renal function, this study aimed to elucidate the plasma AA profiles in LN patients and identify key AAs and diagnostic patterns that distinguish LN patients from those with SLE and healthy controls. Participants were categorized into three groups: normal controls (NC), SLE, and LN. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was employed to quantify AA levels in human plasma. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were utilized to identify key AAs. The diagnostic capacity of the models was assessed using receiver operating characteristic (ROC) curve analysis and area under the ROC curve (AUC) values. Significant alterations in plasma AA profiles were observed in LN patients compared to the SLE and NC groups. The OPLS-DA model effectively separated LN patients from the SLE and NC groups. A joint model using histidine (His), lysine (Lys), and tryptophan (Trp) demonstrated exceptional diagnostic performance, achieving an AUC of 1.0 with 100% sensitivity, specificity, and accuracy in predicting LN. Another joint model comprising arginine (Arg), valine (Val), and Trp also exhibited robust predictive performance, with an AUC of 0.998, sensitivity of 93.80%, specificity of 100%, and accuracy of 95.78% in distinguishing between SLE and LN. The joint forecasting models showed excellent predictive capabilities in identifying LN and categorizing lupus disease status. This approach provides a novel perspective for the early identification, prevention, treatment, and management of LN based on variations in plasma AA levels.

摘要

狼疮性肾炎(LN)是一种与系统性红斑狼疮(SLE)相关的免疫炎症性肾小球肾炎,伴有肾脏受累。鉴于血浆氨基酸(AAs)与肾功能之间的密切关系,本研究旨在阐明 LN 患者的血浆 AA 谱,并确定区分 LN 患者与 SLE 患者和健康对照者的关键 AA 和诊断模式。参与者分为三组:正常对照组(NC)、SLE 和 LN。采用超高效液相色谱-串联质谱(UPLC-MS/MS)定量人血浆中的 AA 水平。采用主成分分析(PCA)和正交偏最小二乘判别分析(OPLS-DA)鉴定关键 AA。使用接收者操作特征(ROC)曲线分析和 ROC 曲线下面积(AUC)值评估模型的诊断能力。与 SLE 和 NC 组相比,LN 患者的血浆 AA 谱发生了显著变化。OPLS-DA 模型能够有效地区分 LN 患者与 SLE 和 NC 组。使用组氨酸(His)、赖氨酸(Lys)和色氨酸(Trp)的联合模型表现出出色的诊断性能,预测 LN 的 AUC 为 1.0,灵敏度为 100%,特异性为 100%,准确性为 100%。另一个包含精氨酸(Arg)、缬氨酸(Val)和 Trp 的联合模型也表现出强大的预测性能,区分 SLE 和 LN 的 AUC 为 0.998,灵敏度为 93.80%,特异性为 100%,准确性为 95.78%。联合预测模型在识别 LN 和分类狼疮疾病状态方面表现出出色的预测能力。这种方法为基于血浆 AA 水平的变化,提供了一种新的视角,用于 LN 的早期识别、预防、治疗和管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ed/11410987/b6e3674e99ae/726_2024_3418_Fig1_HTML.jpg

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