Plasma metabolism marker for early diagnosis or prediction of gestational diabetes and application
By screening plasma metabolic markers such as L-lysine, propargylglycine, N6-acetyl-L-lysine, cyclic leucine, and glycine deoxycholic acid, and combining LC-MS detection and multivariate statistical analysis, the problem of early diagnosis of gestational diabetes mellitus has been solved, achieving efficient early diagnosis and prediction, and improving the diagnostic accuracy of gestational diabetes mellitus.
Patent Information
- Application Number
- CN202610181544.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-02-09
- Publication Date
- 2026-05-26
AI Technical Summary
In current technology, the diagnosis of gestational diabetes is mainly carried out in the second trimester, which may lead to missed opportunities for early intervention, increase the risk of adverse maternal and fetal outcomes, and lack effective methods for early diagnosis or prediction.
Using plasma metabolic markers such as L-lysine, propargylglycine, N6-acetyl-L-lysine, cyclic leucine, and glycine deoxycholic acid, and by LC-MS detection, combined with multivariate statistical analysis and receiver operating characteristic curves, a model for early diagnosis or prediction of gestational diabetes was constructed.
It improves the early diagnosis rate of gestational diabetes mellitus, enhances the accessibility of disease prognosis management, and has clinical application and promotion value. The AUC value of a single biomarker is greater than 0.6, and the AUC value of multiple biomarkers can reach 0.987, which significantly improves the diagnostic accuracy.