ArticleFrontiers in molecular biosciences2025
UHPLC-MS/MS-based plasma untargeted lipidomic analysis in patients with diabetes mellitus combined with hyperuricemia.
Article in Frontiers in molecular biosciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Integrated dual-MS platform lipidomics and transcriptomics approach to investigate the lipid-inflammatory crosstalk mechanism of Gushudan in preventing postmenopausal osteoporosis rats.Analytical and bioanalytical chemistry · 2026Article
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Abstract
Objective: To compare the differences in lipid metabolites between patients with diabetes mellitus combined with hyperuricemia (DH) and diabetes mellitus (DM) and healthy controls, and to initially reveal the changes in lipid metabolic pathways in DH. Methods: Using a present study method, 17 patients each diagnosed with diabetes mellitus and diabetes mellitus combined with hyperuric acid among permanent residents aged 18 years and above in Fuzhou City, Fujian Province, China, from June 2019 to July 2020 were selected, matched 1:1 by sex and age, and 17 healthy controls were randomly selected and fasting blood samples were collected. The untargeted lipid histology analysis was performed using ultra performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) based technique, and the Student's t-test and multiple of difference (FC) were used to initially screen the differential lipid molecules and determine their trends; principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to observe the overall distribution of the two groups of samples. Finally, we used Metabo Analyst 5.0 platform to analyze the differential lipid metabolism pathways. Results: We identified 1,361 lipid molecules across 30 subclasses. Multivariate analyses revealed a significant separation trend among the DH, DM, and NGT groups, confirming distinct lipidomic profiles. A total of 31 significantly altered lipid metabolites were pinpointed in the DH group compared to the NGT controls. Among the most relevant individual metabolites, 13 triglycerides (TGs), such as TG (16:0/18:1/18:2), 10 phosphatidylethanolamines (PEs), e.g., PE (18:0/20:4), and 7 phosphatidylcholines (PCs) including PC (36:1), were significantly upregulated, while one phosphatidylinositol (PI) was downregulated. The collective analysis of these metabolite groups revealed their enrichment in six major metabolic pathways. Crucially, glycerophospholipid metabolism with an impact value of 0.199 and glycerolipid metabolism with an impact value of 0.014 were identified as the most significantly perturbed pathways in DH patients. Furthermore, comparison of DH Conclusion: Patients with combined diabetes mellitus and hyperuricemia have significantly altered lipid metabolites compared to diabetic patients and healthy controls. A total of 31 significantly different lipid molecules were identified, and abnormalities in glycerophospholipid metabolism and glycerolipid metabolism pathways were found in DH patients.
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