A biomarker combination for diagnosing gestational diabetes and application thereof

Abstract

The present application relates to the technical field of medical detection, in particular to a biomarker combination for diagnosing gestational diabetes mellitus and application thereof. The present application provides application of SHBG protein and Vaspin protein in preparation of a product for diagnosing gestational diabetes mellitus. When SHBG and Vaspin are used in combination for diagnosing gestational diabetes mellitus, the diagnostic efficiency is extremely high, the AUC value reaches 0.934, the accuracy is 0.91, the sensitivity is 0.872, and the specificity is 0.949. The biomarker combination of the present application can be used for early diagnosis of whether there is a risk of GDM, so as to provide a basis for timely intervention, reduce the complication risk of pregnant women and fetuses, and improve the health outcomes of mothers and infants.

Description

Technical Field

[0001] This invention relates to the field of medical testing technology, specifically to a combination of biomarkers for diagnosing gestational diabetes and their applications. Background Technology

[0002] Gestational diabetes mellitus (GDM) refers to diabetes mellitus first diagnosed or occurring during pregnancy, and its incidence is increasing year by year. GDM not only increases the risk of gestational hypertension, preeclampsia, and cesarean section in pregnant women, but may also lead to complications such as macrosomia, neonatal hypoglycemia, and respiratory distress syndrome. Furthermore, pregnant women with GDM and their offspring have a significantly increased risk of developing type 2 diabetes, obesity, and cardiovascular disease postpartum. Therefore, early prediction and intervention of GDM are of great significance for improving maternal and infant health.

[0003] Currently, the commonly used clinical screening method for GDM is the oral glucose tolerance test (OGTT) performed between 24 and 28 weeks of gestation. However, this screening method has certain limitations, such as late screening time, insufficient intervention time, and difficulty in effectively improving pregnancy outcomes. In addition to the OGTT experiment, non-patent literature (Tawfeek, MA, Alfadhli, EM, Alayoubi, AM et al. Sex hormone binding globulin as a valuable biochemical marker in predicting gestational diabetes mellitus. BMC Women's Health 17, 18 (2017). https: / / doi.org / 10.1186 / s12905-017-0373-3) and non-patent literature (Li Rui, Su Yeqing, An Yan, et al. The value of omentin-1 and vaspin in early warning of gestational diabetes mellitus [J]. Journal of Xuzhou Medical University, 2022, 42(07): 491-494.) have also disclosed biomarkers for predicting GDM, such as Hs-CRP, omentin-1, APN, vaspin, SHBG, etc.

[0004] In fact, individual biomarkers are highly influenced by individual factors and have poor predictive accuracy. However, simply combining clinically valuable biomarkers arbitrarily does not guarantee good results. Therefore, developing specific combinations of biomarkers for the diagnosis of gestational diabetes mellitus has significant clinical value. Summary of the Invention

[0005] In a first aspect, the present invention provides the use of SHBG protein and Vaspin protein in combination in the preparation of products for diagnosing gestational diabetes mellitus or predicting the risk of developing gestational diabetes mellitus.

[0006] Preferably, the SHBG protein and Vaspin protein are SHBG protein and Vaspin protein found in serum or plasma.

[0007] Preferably, the diagnosis of gestational diabetes mellitus or the prediction of the risk of developing gestational diabetes mellitus includes detecting the expression levels or concentrations of SHBG protein and Vaspin protein in serum or plasma.

[0008] Preferably, the diagnosis of gestational diabetes mellitus or prediction of the risk of developing gestational diabetes mellitus further includes comparing the expression levels or concentrations of the detected SHBG protein and Vaspin protein with thresholds.

[0009] When the expression levels or concentrations of the detected SHBG and Vaspin proteins differ from or are significantly different from the threshold, gestational diabetes is diagnosed, or a high risk of developing gestational diabetes is predicted.

[0010] The threshold mentioned above was obtained from previous experiments, that is, the threshold was determined by the degree of difference in the expression level or concentration of biomarkers between pregnant women without gestational diabetes and pregnant women with gestational diabetes through experiments and data analysis.

[0011] When the expression levels or concentrations of SHBG and Vaspin proteins in this application are significantly different from or substantially different from the threshold (the difference is statistically significant, e.g., p < 0.05, p < 0.01, p < 0.001, p < 0.0001), a diagnosis of gestational diabetes mellitus or the absence of gestational diabetes mellitus is made, or a high or low risk of developing gestational diabetes mellitus is predicted. For example:

[0012] 1) When the expression level or concentration of SHBG is below or significantly below the threshold, a diagnosis of gestational diabetes mellitus, or a high risk of gestational diabetes mellitus, is made; and / or,

[0013] 2) When the expression level or concentration of Vaspin is higher than or significantly higher than the threshold, gestational diabetes mellitus is diagnosed, or the risk of gestational diabetes mellitus is high.

[0014] In one specific embodiment of the present invention, when the expression level or concentration of SHBG is lower than or significantly lower than a threshold, and the expression level or concentration of Vaspin is higher than or significantly higher than a threshold, a diagnosis of gestational diabetes mellitus or a high risk of gestational diabetes mellitus is made.

[0015] In one specific embodiment of the present invention, the threshold of SHBG protein is 453.5 nmol / L.

[0016] In one specific embodiment of the present invention, the threshold for Vaspin protein is 2.75 ng / mL.

[0017] Preferably, the product includes one or more of the following: chip, reagent kit, test strip, membrane strip, or device.

[0018] Preferably, the product testing targets pregnant women at various stages of pregnancy, preferably pregnant women in early pregnancy, and more preferably pregnant women in the 6th to 13th week of pregnancy.

[0019] In one specific embodiment of the present invention, the application includes:

[0020] Sample collection: In early pregnancy (e.g., 6–13 weeks), blood samples (e.g., venous blood) are collected from fasting pregnant women, and serum is separated.

[0021] Detection indicators: Detect the levels of SHBG and Vaspin in serum (e.g., using enzyme-linked immunosorbent assay (ELISA)).

[0022] Data analysis: Based on the levels of SHBG and Vaspin, and combined with the preset optimal cutoff value (i.e., threshold), the risk of GDM occurrence is calculated through a logistic regression analysis model.

[0023] Joint prediction: The results of SHBG and Vaspin detection are jointly analyzed, and the AUC, accuracy, sensitivity and specificity of the joint prediction are evaluated using receiver operating characteristic (ROC) curves.

[0024] In a second aspect, the present invention provides a biomarker for predicting the risk of gestational diabetes mellitus, said biomarker including SHBG protein and Vaspin protein.

[0025] A third aspect of the present invention provides a biomarker for diagnosing gestational diabetes mellitus, said biomarker comprising SHBG protein and Vaspin protein.

[0026] in,

[0027] SHBG: Sex hormone-binding globulin;

[0028] Vaspin: a visceral adipose tissue-derived serine protease inhibitor, is an adipokine.

[0029] A fourth aspect of the present invention provides a method for constructing a diagnostic model or risk prediction model for gestational diabetes mellitus, the method comprising:

[0030] 1) Collect samples from the gestational diabetes mellitus group and the non-gestational diabetes mellitus group, and detect the expression level or concentration of biomarkers;

[0031] 2) Construct a diagnostic model or risk prediction model based on the information collected in step 1);

[0032] Alternatively, the construction method may include:

[0033] I) Collect samples from the subjects and detect the expression levels or concentrations of biomarkers;

[0034] II) Clinical diagnosis was performed on the subjects, and the subjects were divided into gestational diabetes group and non-gestational diabetes group;

[0035] III) Construct a diagnostic model or risk prediction model based on the test results of I) and the clinical diagnosis results of II).

[0036] The biomarkers mentioned are SHBG protein and Vaspin protein.

[0037] Preferably, the sample includes serum or plasma. In one specific embodiment of the invention, the sample is serum.

[0038] Preferably, the algorithm used to construct the diagnostic model or risk prediction model is a logistic regression model, such as a binary logistic regression model.

[0039] Preferably, the method for detecting the expression level or concentration of biomarkers includes one or more of chemiluminescence, immunofluorescence, colorimetric assay, ELISA, protein chip, liquid chromatography, or mass spectrometry.

[0040] Preferably, the subjects, the gestational diabetes group, and the non-gestational diabetes group can be pregnant women at various stages of pregnancy, preferably pregnant women in early pregnancy, and more preferably pregnant women in the 6th to 13th week of pregnancy.

[0041] In a fifth aspect, the present invention provides a diagnostic model or risk prediction model obtained by the above-described construction method.

[0042] In a sixth aspect, the present invention provides a method for diagnosing gestational diabetes mellitus or predicting the risk of developing gestational diabetes mellitus, the method comprising detecting the expression level or concentration of the aforementioned biomarker in a subject sample, or the method comprising using the aforementioned diagnostic model or risk prediction model or a diagnostic model or risk prediction model obtained by the aforementioned construction method.

[0043] In a seventh aspect, the present invention provides the application of the above-described biomarker or the diagnostic model or risk prediction model obtained by the above-described construction method, and the above-described diagnostic model or risk prediction model in the preparation of products for diagnosing gestational diabetes or predicting the risk of developing gestational diabetes.

[0044] Preferably, the diagnosis of gestational diabetes mellitus or the prediction of the risk of developing gestational diabetes mellitus includes detecting the expression level or concentration of biomarkers.

[0045] Preferably, the diagnosis of gestational diabetes mellitus or the prediction of the risk of developing gestational diabetes mellitus further includes comparing the expression level or concentration of the detected biomarker with a threshold.

[0046] Preferably, the product includes one or more of the following: chip, reagent kit, test strip, membrane strip, or device.

[0047] In an eighth aspect, the present invention provides a chip, reagent kit, test strip, membrane strip, or device, wherein the chip, reagent kit, test strip, membrane strip, or device comprises a reagent for detecting the aforementioned biomarkers.

[0048] Preferably, the chip, reagent kit, test strip, membrane strip, or device further includes reagents for processing samples.

[0049] The term "diagnosis" as used in this invention refers to determining whether a patient has had a disease or condition in the past, at the time of diagnosis, or in the future, or determining the progression of a disease or its possible future progression.

[0050] The "subject" mentioned in this invention can be a human or a non-human animal, including "patients" and "healthy people," etc. The non-human animals can be wild animals, zoo animals, economically produced animals, pets, laboratory animals, etc. Preferably, the non-human animals include, but are not limited to, pigs, cattle, sheep, horses, donkeys, foxes, minks, camels, dogs, cats, rabbits, mice (e.g., rats, mice, guinea pigs, hamsters, gerbils, chinchillas, squirrels) or monkeys, etc.

[0051] The term "and / or" as used in this invention includes all combinations of items connected by the term, and should be regarded as each combination having been individually listed in this application. For example, "A and / or B" includes "A", "B", and "A and B"; and "A, B and / or C" includes "A", "B", "C", "A and B", "A and C", "B and C", and "A and B and C".

[0052] The use of "comprising" or "including" in this invention is an open-ended description, encompassing the specified ingredients or steps, as well as other specified ingredients or steps that do not substantially affect the description.

[0053] The "method" or "application" described in this invention may be for diagnostic purposes or for non-diagnostic purposes.

[0054] Technical effects of the present invention:

[0055] 1) Improved diagnostic efficacy: The combined detection of SHBG and Vaspin for diagnosing gestational diabetes mellitus (GDM) had an AUC of 0.934, accuracy of 0.91, sensitivity of 0.872, and specificity of 0.949, significantly higher than single-indicator detection. 2) Early prediction: It can predict the risk of GDM in pregnant women during early pregnancy (6–13 weeks), providing a window for early intervention. This allows for timely lifestyle interventions, dietary adjustments, and close monitoring, reducing the risk of maternal and infant complications, and has high clinical application value. Detailed Implementation

[0056] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Some of the experimental methods used in this invention are as follows:

[0058] (I) Sample Collection and Processing

[0059] 1. Sample collection: Collect 5 mL of fasting venous blood from pregnant women between 6 and 13 weeks of gestation.

[0060] 2. Sample processing: Centrifuge the collected blood samples at 3000 rpm for 10 minutes to separate the serum, and aliquot it into labeled cryovials and store at -80℃ until analysis.

[0061] (II) Detection Methods

[0062] 1. SHBG detection

[0063] (1) Use Sigma-Aldrich ELISA kit (product number: RAB0734).

[0064] (2) The serum sample was diluted 2000 times before testing.

[0065] 2. Vaspin detection

[0066] (1) Use the ELISA kit (product number: PV970) from Beyotime Biotechnology Co., Ltd.

[0067] (2) Serum samples are tested directly without dilution.

[0068] (III) Data Analysis

[0069] 1. Statistical Analysis

[0070] (1) Data analysis was performed using SPSS software.

[0071] (2) One-way ANOVA was used to compare the differences in means between the two groups.

[0072] (3) The association between SHBG and Vaspin levels and the risk of GDM was calculated using a logistic regression model.

[0073] 2. ROC curve analysis

[0074] (1) Construct ROC model to evaluate the performance of SHBG and Vaspin alone and in combination in diagnosing GDM.

[0075] (2) Calculate the area under the ROC curve (AUC), accuracy, sensitivity, specificity, positive predictive value and negative predictive value.

[0076] (IV) Diagnostic criteria for gestational diabetes mellitus

[0077] An oral glucose tolerance test (OGTT) is performed on pregnant women between the 24th and 28th weeks of pregnancy. The woman must fast for 8 hours after dinner the day before the OGTT until 9:00 AM the following morning. She should maintain normal physical activity and a normal diet for 3 consecutive days prior to the OGTT. During the test, the woman ingests 300 mL of a glucose solution containing 75 grams of glucose within 5 minutes. Venous blood samples are then drawn before, 1 hour after, and 2 hours after glucose ingestion (timing starts from the time the glucose solution is ingested). Glucose levels are measured using the oxidase method. Diagnostic criteria for OGTT: A fasting blood glucose level of 5.1 mmol / L, 10.0 mmol / L, or 8.5 mmol / L or higher at any point on the fasting side, 1 hour after glucose ingestion, and 2 hours after glucose ingestion, respectively, is diagnostic of gestational diabetes mellitus (GDM).

[0078] Example 1

[0079] Data from pregnant women: 300 pregnant women undergoing prenatal checkups at the Department of Obstetrics and Gynecology, Beijing Aerospace General Hospital, were randomly selected as study subjects. Each subject had 5 mL of fasting venous blood collected from each of the subjects between 6 and 13 weeks of gestation. After blood collection, the blood was centrifuged at 3000 rpm for 10 minutes to separate the serum, which was then stored at -80℃ for centralized testing of SHBG and Vaspin levels. The selected pregnant women attended prenatal checkups on time, provided complete documentation, and demonstrated good compliance. Pregnant women with pre-existing diabetes, hypertension, cardiovascular disease, or other organ diseases were excluded. Finally, 50 pregnant women diagnosed with gestational diabetes mellitus (GDM) were selected as the GDM group, and 50 normal pregnant women were selected as the control group (see Table 1 below).

[0080] Table 1

[0081]

[0082] The expression levels of Vaspin and SHBG in pregnant women were detected. It was found that the expression level of Vaspin was abnormally high (p<0.001) and the expression level of SHBG was significantly low (p<0.001) in the gestational diabetes mellitus (GDM) group compared with the control group.

[0083] Furthermore, this embodiment compares the optimal cutoff values ​​(thresholds), AUC values, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of Vaspin and SHBG alone and in combination for predicting the risk of GDM.

[0084] Optimal cutoff values: The optimal cutoff value for Vaspin is 2.75 ng / mL, for SHBG it is 453.5 nmol / L, and for combined diagnosis it is 0.436. These optimal cutoff values ​​were determined through ROC curve analysis to maximize diagnostic accuracy and sensitivity.

[0085] AUC values: Vaspin's AUC value was 0.794, SHBG's AUC value was 0.904, and the combined diagnosis (Vaspin and SHBG) had an AUC value of 0.934. Higher AUC values ​​indicate stronger diagnostic capabilities of the model. The combined diagnosis's AUC value was significantly higher than that of Vaspin or SHBG alone, indicating that the combined diagnosis significantly improves the diagnostic efficacy of GDM.

[0086] Accuracy: The accuracy of Vaspin alone was 0.744, the accuracy of SHBG alone was 0.785, and the accuracy of the combined diagnosis was 0.91. The accuracy of the combined diagnosis was significantly higher than that of Vaspin or SHBG alone, indicating that the combined diagnosis can more accurately predict GDM.

[0087] Sensitivity and specificity: Vaspin had a sensitivity of 0.769 and a specificity of 0.718; SHBG had a sensitivity of 0.795 and a specificity of 0.774; and the combined diagnostic method had a sensitivity of 0.872 and a specificity of 0.949. The combined diagnostic method showed significantly higher sensitivity and specificity than Vaspin or SHBG alone, indicating that the combined diagnostic method can more effectively identify patients with GDM and those without GDM.

[0088] Positive and negative predictive values: Vaspin's positive predictive value was 0.732, and its negative predictive value was 0.757; SHBG's positive predictive value was 0.769, and its negative predictive value was 0.826; the combined diagnosis's positive predictive value was 0.944, and its negative predictive value was 0.951. Both the positive and negative predictive values ​​of the combined diagnosis were significantly higher than those of Vaspin or SHBG alone, indicating that the combined diagnosis can more accurately predict the risk of GDM.

[0089] The above results demonstrate that the diagnostic efficacy (including AUC, accuracy, sensitivity, and specificity) of the combined diagnostic approach is significantly superior to that of Vaspin or SHBG alone, supporting the superiority of the combined approach. The clinical application of the combined approach can provide a scientific basis for early screening and intervention in GDM, improving maternal and infant health outcomes. It has significant clinical application value.

[0090] Example 2: Validation of Biomarker Combinations

[0091] To verify the effectiveness of the biomarker combination in this application, fasting venous blood was collected from five other pregnant women at 6-13 weeks of gestation, and serum was separated to verify the effect of the combination of SHBG and Vaspin in early prediction of GDM risk.

[0092] Using an oral glucose tolerance test (OGTT) performed at 24-28 weeks as the gold standard for diagnosis, early prediction using a combination of SHBG and Vaspin yielded results completely consistent with the gold standard. Specifically, pregnant women in samples 1-4 were diagnosed with GDM using both early prediction with SHBG and Vaspin and the OGTT results performed at 24-28 weeks. Conversely, pregnant woman in sample 5 was diagnosed without GDM using both early prediction with SHBG and Vaspin and the OGTT results performed at 24-28 weeks. Sample details and SHBG and Vaspin expression levels are shown in Table 2.

[0093] Table 2

[0094]

[0095]

[0096] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

[0097] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not describe the various possible combinations separately.

Claims

1. Application of SHBG protein and Vaspin protein in the preparation of products for predicting the risk of gestational diabetes in pregnant women at 6-13 weeks of gestation; The method for predicting the risk of gestational diabetes in pregnant women at 6-13 weeks of gestation includes detecting the expression levels or concentrations of SHBG and Vaspin proteins and comparing them to thresholds. The threshold for SHBG protein is 453.5 nmol / L; The threshold for Vaspin protein is 2.75 ng / mL; When the expression level or concentration of SHBG is below a threshold, it predicts a high risk of gestational diabetes. When the expression level or concentration of Vaspin is above a threshold, it predicts a high risk of gestational diabetes.

2. The application according to claim 1, characterized in that, When the expression level or concentration of SHBG is significantly lower than the threshold, it predicts a high risk of gestational diabetes. When the expression level or concentration of Vaspin is significantly higher than the threshold, it predicts a high risk of gestational diabetes.

3. The application according to claim 1, characterized in that, The SHBG protein and Vaspin protein are SHBG protein and Vaspin protein in serum or plasma.

4. The application according to claim 1, characterized in that, The products include one or more of the following: chips, reagent kits, test strips, membrane strips, or devices.

5. The application according to claim 1, characterized in that, The methods for detecting the expression levels or concentrations of SHBG and Vaspin proteins include one or more of the following: chemiluminescence, immunofluorescence, colorimetric assay, ELISA, protein chip, liquid chromatography, or mass spectrometry.

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