ArticleDiabetology & metabolic syndrome2023
Integrated biomarker profiling of the metabolome associated with type 2 diabetes mellitus among Tibetan in China.
Article in Diabetology & metabolic syndrome, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- DiabetesXpertNet: An innovative attention-based CNN for accurate type 2 diabetes prediction.PloS one · 2025Article
- Precision Medicine in Type 2 Diabetes Mellitus: Utility and Limitations.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023Review
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13 authors.
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Abstract
introductionMetabolomic signatures of type 2 diabetes mellitus (T2DM) in Tibetan Chinese population, a group with high diabetes burden, remain largely unclear. Identifying the serum metabolite profile of Tibetan T2DM (T-T2DM) individuals may provide novel insights into early T2DM diagnosis and intervention.
methodsHence, we conducted untargeted metabolomics analysis of plasma samples from a retrospective cohort study with 100 healthy controls and 100 T-T2DM patients by using liquid chromatography-mass spectrometry.
resultsThe T-T2DM group had significant metabolic alterations that are distinct from known diabetes risk indicators, such as body mass index, fasting plasma glucose, and glycosylated hemoglobin levels. The optimal metabolite panels for predicting T-T2DM were selected using a tenfold cross-validation random forest classification model. Compared with the clinical features, the metabolite prediction model provided a better predictive value. We also analyzed the correlation of metabolites with clinical indices and found 10 metabolites that were independently predictive of T-T2DM.
conclusionBy using the metabolites identified in this study, we may provide stable and accurate biomarkers for early T-T2DM warning and diagnosis. Our study also provides a rich and open-access data resource for optimizing T-T2DM management.
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