ArticleHeliyon2024
Untargeted metabolomics combined with pseudotargeted lipidomics revealed the metabolite profiles of blood-stasis syndrome in type 2 diabetes mellitus.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Animal models for diabetic kidney disease: perspectives and prospects.Frontiers in veterinary science · 2026Article
- Illuminating diabetesWorld journal of diabetes · 2025Review
- A Direct Relationship Between 'Blood Stasis' and Fibrinaloid Microclots in Chronic, Inflammatory, and Vascular Diseases, and Some Traditional Natural Products Approaches to Treatment.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Exploring the molecular mechanism of EGCG in preventing obesity-induced precocious puberty based on serum metabolomics and molecular docking.Frontiers in nutrition · 2025Article
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Authors and funding
10 authors.
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Abstract
Objective: Blood-stasis syndrome (BSS), an important syndrome in Type 2 diabetes mellitus(T2DM), is associated with the pathophysiological mechanisms underlying diabetic vascular complications. However, BSS has not been fully characterized as of yet. Due to the strong correlation between BSS and vasculopathy, we hypothesized that the metabolic characteristics of BSS in T2DM (T2DM BSS) are highly specific. By combining untargeted metabolomics and pseudotargeted lipidomics approaches, this study aimed to comprehensively elucidate the metabolic traits of T2DM BSS, thereby providing novel insights into the vascular complications of diabetes and establishing a foundation for precision medicine. Methods: The survey was conducted in Haidian District of Beijing from October 2021 to November 2021, and data collection was completed in January 2022. Liquid chromatography-mass spectrometry (LC-MS) based untargeted metabolomics and liquid chromatography-tandem mass spectrometry (LC-MS/MS) based pseudotargeted lipidomics were performed to detect metabolites and lipids. Multivariate, univariate, and pathway analyses were utilized to investigate metabolic changes. The unique metabolites of BSS were obtained by inter-group comparisons and screening. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic accuracy of metabolites. Results: A total of 1189 participants completed the survey, of which 120 participants were recruited in this study and further divided into a discovery cohort (n = 90) and a validation cohort (n = 30). Among these, 21 participants were selected for psuedotargeted lipidomics analysis. 81 metabolites, mainly involving glycerophospholipids, were identified as unique metabolites of T2DM BSS, while fatty acyls (FAs) were identified as unique lipids. T2DM BSS was associated with significant dysregulation in glycerophospholipid metabolism and choline metabolism within cancer pathways as major metabolic disturbances. Furthermore, analyses of both the discovery and validation cohorts, indicated that LysoPC (20:5(5Z,8Z,11Z,14Z,17Z)/0:0) and LysoPC (15:0) had the greatest impact on distinguishing BSS. Conclusion: Altered levels of glycerophospholipids and FAs have been associated with T2DM BSS. These results provide valuable mechanistic insights linked with the development of BSS in T2DM subjects.
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