Urine metabolomics analysis of patients with acute pancreatitis / 中华胰腺病杂志

ABSTRACT

Objective To detect the small molecular metabolite profiles of urine from patients with acute pancreatitis (AP) in different severity,and screen the differential metabolites that have potential diagnostic value for AP and its severity.Methods Urine samples were collected from 65 AP patients (MSAP and SAP 29,MAP 36) in the First Affiliated Hospital of Soochow University,and 25 healthy volunteers served as controls.The liquid chromatograph mass spectrometer (LC-MS) combined method was used to detect urine small molecule metabolites of AP patients and healthy controls.Multivariate statistical analysis was used to establish and validate the principal component analysis (PCA) model and partial least squares discriminate analysis (PLS-DA) model to select the differential metabolites.Results PCA model had a good degree of interpretation (R2X ＞0.5),and each group of urine samples showed a good distinction between clustering trends,and good classification models were obtained.In the PLS-DA model,the differences among groups were further highlighted,and samples of each group showed distinct differentiation between clusters,with high predictability (Q2 ＞ 0.7).The model was reliable and effective indicated by the PLS-DA permutation test.17 differential metabolites were screened out by comparing AP with control.A diagnostic model constructed with 7 differential metabolites including nonanedioic acid,succinic acid semialdehyde,D-beta-hydroxy butyric acid,acetylcarnitine,angelic acid,sebacic acid and hippuric acid had a high diagnostic value for AP,with the sensitivity of 100％ and the specificity of 94％.Then control,MAP and MSAP + SAP group were compared with each other,and it was found that the model integrating urine succinic acid semialdehyde,angelic acid,D (-)-beta-hydroxy butyric acid,malic acid and acetylcarnitine had a good diagnostic value for SAP,with the sensitivity and specificity of both 90％.Conclusions LC-MS metabolomics can effectively identify the changes of urine metabolism in patients with different severity of AP.The screened differential metabolites have the potential clinical value in the diagnosis and classification of AP.