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Clinical analysis

Characterization of the Metabolites and Construction of a Novel Diagnostic Panel in Calcium Oxalate Urolithiasis by Electrospray Ionization – Mass Spectrometry (ESI-MS) Metabolomics

ORCID Icon, , , , , , , & ORCID Icon show all
Pages 1997-2010 | Received 07 Dec 2021, Accepted 07 Feb 2022, Published online: 21 Feb 2022
 

Abstract

The metabolic differences between patients with calcium oxalate (CaOx) urolithiasis and the healthy population remain unclear. Currently there is no diagnostic panel for CaOx urolithiasis. This study aimed to identify the full-scale metabolic changes in the urine of CaOx urolithiasis patients and to establish a novel diagnostic panel as a noninvasive early prevention method. 240 urine samples were collected from 137 patients diagnosed with CaOx urolithiasis and 103 healthy controls. Electrospray ionization – mass spectrometry (ESI-MS) metabolomics and univariate, multivariate, and bioinformatic analyses were combined to identify the differential metabolites and related metabolic pathways between the groups. Integrated machine learning methods were adopted to discover potential biomarkers and establish a diagnostic panel. 79 differential metabolites were identified in the urine of patients compared with healthy controls. Pathways closely associated with these abnormal metabolites included metabolic pathways, amino acid biosynthesis, microbial metabolism in diverse environments, and protein digestion and absorption. Five potential metabolites, n-acetylputrescine, n-alpha-acetyl-L-arginine, ethyl 3-hydroxybutyrate, s-adenosylmethionine, and l-pyroglutamic acid, were selected as biomarkers by machine learning models, which included logistic regression (LR), random forest (RF), and support vector machine (SVM) models. The panel showed an excellent classification to differentiate patients from healthy controls with areas under the curve (AUC) of 0.998 in the training cohort and 0.993 in the validation cohort. The results revealed differential metabolites between the two groups. Furthermore, a panel of potential biomarkers was established for the first time and showed promising diagnostic value.

Acknowledgments

We thank the patients and the volunteers for their altruistic support.

Disclosure statement

The authors report no conflicts of interest.

Additional information

Funding

This work was supported by the Science and Technology Project of Tianjin [grant number 18PTLCSY00020] and the Science and Technology Planning Project of Tianjin [grant number 20KPHDRC00040].

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