Serum and urinary amino acid profiling analysis for urinary stone disease using GC-MS / 中华检验医学杂志

ABSTRACT

Objective:To analyze the serum and urinary amino acid (AA) profiles of urolithiasis patients to explore the potential biomarkers for clinical screening and early diagnosis.Methods:Case-control study. Serum and urine samples were collected from 74 urolithiasis patients (aged 20-82 years, 41 men, 33 female) in the department of urology of the First Affiliated Hospital of Fujian Medical University and 35 healthy controls (HC, aged 22-80 years old, 20 men, 15 female) from the health examination center from February 2015 to October 2017. Serum and urinary AA levels of patients and HC were analyzed using Gas Chromatography-Mass Spectrometry (GC-MS) based metabolomic strategy. The multivariate statistical analysis methods of principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA) were employed for modeling. The variable importance projection (VIP) value of OPLS-DA model>1 and P<0.05 of t test were selected to screen the differential amino acid metabolites. The diagnostic capabilities of potential markers were evaluated by receiver operating characteristic (ROC) curve and binary logistic regression analysis. Results:Five AA metabolites including serine, glutamate, aspartic acid, isoleucine and glycine were found, which had statistically significant differences between the patient group and the control group ( P<0.05) and were associated with seven metabolic pathways. Serum serine, glutamate, aspartic acid, isoleucine and urine glycine and aspartic acid were combined into an integrated marker panel whose AUC value was 0.890, the sensitivity was 78.0%, and the specificity was 96.4%. Conclusion:Five amino acids in serum and urine could be used as an integrated biomarker panel for the clinical screening and early diagnosis of urolithiasis, which could provide some experimental basis for molecular urolithiasis research.