Serum metabolism marker for diagnosis of gestational diabetes mellitus and application of serum metabolism marker
A technology of diabetes and biomarkers, applied in the field of serum metabolic markers, can solve problems such as delayed time, unfavorable treatment, and lack of diagnostic criteria
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Embodiment 1
[0075] The inventors identified metabolic markers based on the analysis of metabolites in serum samples of a total of 21 patients with gestational diabetes mellitus (GDM) and 22 age-matched healthy pregnant women in the GDM group.
[0076] 1. Patient enrollment and sample collection
[0077] Peripheral blood samples were all from He Xian Memorial Hospital, Panyu District, Guangzhou. Pregnant women were recruited in Guangzhou during 2019-2020. Mothers with obvious diabetes before pregnancy were not included. After obtaining written consent, a structural medical history was recorded.
[0078] All pregnant women included in the study were registered at the Perinatal Medicine Outpatient Clinic of He Xian Memorial Hospital and followed up on a regular basis. They met the inclusion and exclusion criteria. Special personnel collected the basic information of the patients, such as height, weight, age, etc. Pre-pregnancy body mass index (BMI) is calculated by dividing the weight (kg) ...
Embodiment 2
[0108] Further use the receiver operating characteristic (ROC) curve to consider the diagnostic performance of two differential metabolites. The ROC curve is based on a series of different binary classification methods (cut-off value or decision threshold), with the true positive rate (sensitivity) as the vertical axis , the false positive rate (1-specificity) is a curve drawn on the abscissa. The closer the ROC curve is to the upper left corner, the higher the diagnostic accuracy of the marker. The point of the ROC curve closest to the upper left corner is the best threshold with the least errors, and the total number of false positives and false negatives is the least. The area under the ROC curve (AUC) of each potential marker can be calculated to judge the diagnostic value of the potential marker, and the larger the AUC, the greater the diagnostic value.
[0109] The AUC values of the two differential metabolites were: sphingomyelin SM (8:0; 2O / 11:0): AUC=0.775, 95% CI: ...
Embodiment 3
[0117] Example 3 Detection Verification
[0118] Randomly select 100 blood samples clinically diagnosed as GDM and 100 healthy samples. The levels of sphingomyelin SM (8:0; 2O / 11:0) and oleoylcarnitine CAR (18:2) in the 200 samples were detected by referring to the method of Example 1.
[0119] The results showed that in 19 samples, the level of sphingomyelin SM (8:0; 2O / 11:0) was abnormally up-regulated, and in 9 samples, the level of oleoylcarnitine CAR (18:2) was abnormally down-regulated, of which 5 samples of sphingomyelin SM (8:0; 2O / 11:0) levels were abnormally upregulated and oleoylcarnitine CAR(18:2) levels were abnormally downregulated.
[0120] After reviewing the source of samples, the 23 abnormal samples were all from GDM patients.
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