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

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.