Investigation of pathogenesis of hyperuricemia based on untargeted and targeted metabolomics

Abstract

Hyperuricemia (HUA) seriously harms human health but the exact etiology and pathogenesis of HUA are not fully understood. Therefore, it is still of great significance to find effective biomarkers and explore the pathogenesis of HUA. Metabolomics reflects the influence of internal and external factors on system metabolism, explains the changes in metabolite levels during the development of diseases, and reveals the molecular mechanism of pathogenesis. Metabolomics is divided into untargeted metabolomics and targeted metabolomics according to different research modes. Each other's advantages can be fully utilized by combining the two so that the results of metabolomics research can be consummated. 20 HUA patients and 20 healthy individuals participated in the experiment, and untargeted metabolomics was employed to find 50 differential metabolites in HUA serum samples. Twelve candidate biomarkers were screened based on literature research and ROC Curve analysis for subsequent verification. Based on the UPLC-TQ-MS analysis platform, the targeted metabolomics detection methods were established and the content of 12 candidate biomarkers was precisely quantified. Compare with the results of untargeted metabolomics, the targeted metabolomics results were considered more reliable.

The biomarkers discovery of hyperuricemia and gout: proteomics and metabolomics

“…Similar to purine metabolism, other metabolic pathways influence hyperuricemia and gout in one way or another. In both untargeted and lipid-targeted metabolomics studies, serum samples from patients with hyperuricemia have detected metabolites related to glycerophospholipid metabolism and sphingolipid metabolism ( Qin et al, 2021 ; Qin et al, 2022 ). Li et al (2018) also found significant differences in glycerophospholipid metabolism between gout patients and controls.…”

Non-destructive diagnostic testing of cardiac myxoma by serum confocal Raman microspectroscopy combined with multivariate analysis

“…The marked increase in peak intensity at 2929 cm −1 indicates an increased lipid content in the CM group, and we hypothesize that such an elevated peak may represent an essential and significant feature in the classification of serum spectra of CM patients and healthy individuals. The Raman bands at 2929 cm −1 were derived from fatty acids, and the disruptive effects of fatty acid accumulation in cardiac cells lead to mitochondrial dysfunction, 42 and mitochondrial dysfunction may also cause reduced activity of biochemical properties, 43 and the phenylalanine content can characterize the level of biochemical activity of the substance, 44,45 and the reduced intensity of the Raman peak at 1008 cm −1 may indicate a weaker biochemical activity in the CM group. Another report suggested that changes in serum phenylalanine concentrations were a powerful predictor of the risk of cardiovascular disease.…”

The Therapeutic Effect and the Potential Mechanism of Flavonoids and Phenolics of Moringa oleifera Lam. Leaves against Hyperuricemia Mice

“…The variable importance in the projection (VIP) value of each variable in the OPLS-DA model was calculated to indicate its contribution to the classification. Metabolites with VIP greater than 1, p values of t -test ( p ) less than 0.05, and a fold change (FC) of greater than 2.0 or FC less than 0.5 were selected as differential metabolites [ 50 ].…”