KR101355394B1 - method on providing information on early diagnosis of gestational diabetes and kit for providing information on early diagnosis of gestational diabetes - Google Patents

Abstract

The present invention is a method for early diagnosis of gestational diabetes, which can be applied to pregnant women between 16 and 20 weeks of pregnancy, apolipoprotein C3 protein used as a biomarker for diagnosing gestational diabetes mellitus, and apolipoprotein C3 for biodiagnosis. The present invention relates to a method for treating gestational diabetes early diagnosis information, a kit for gestational diabetes monitoring, diagnosis and screening.
The present invention can predict the onset of gestational diabetes or early diagnosis by quantifying apolipoprotein C3 in pregnant women from 16 to 20 weeks of gestation, and thus can be effectively used to cope with the onset early.

Description

Method for providing information on early diagnosis of gestational diabetes and kit for providing information on early diagnosis of gestational diabetes}

The present invention relates to a method for providing early diagnosis information for gestational diabetes and a kit for monitoring, diagnosing and screening gestational diabetes for use in providing early diagnosis information for gestational diabetes, and more particularly, to pregnant women between 16 and 20 weeks of gestation. A method for providing early diagnosis information for gestational diabetes that may be applied, and a kit for gestational diabetes monitoring, diagnosis, and screening for use in providing early diagnosis information for gestational diabetes.

Diabetes mellitus is one of the most common chronic adult diseases, and it is estimated that at least 2.5 million diabetics in Korea account for about 5% of the total population. In developed countries, diabetic patients are reported to 10% of the total population. In Korea, diabetic patients are gradually increasing due to the improvement of living standards and westernized lifestyle.

Diabetes is divided into type 1 diabetes (insulin-dependent), which is largely destroyed by insulin-secreting cells, and type 2 diabetes (insulin-independent), which develops insulin resistance in the organ where insulin acts. More than 90% of all diabetics have type 2 diabetes. The causes of diabetes include genetic factors, age increase, obesity, medications, pregnancy, high blood pressure, and hyperlipidemia. The usual diet and regular exercise should prevent the onset. To date, there is no biomarker that can diagnose people who may develop diabetes in the future.

A proteomic study of the apolipoproteins in LDL subclasses in patients with the metabolic syndrome and type 2 diabetes / J Lipid Res is known to increase apolipoprotein C3 protein in the blood of patients with type 2 diabetes. 2005 Sep; 46 (9): 1999-2006). However, it is not known that the apolipoprotein C3 protein is already increased in the blood collected during the normal state before the onset of diabetes.

A biomarker refers to a protein that indicates a specific disease or condition in blood or body fluid. If a protein that is absent or different from a normal person is found in blood or body fluid of a patient with a specific disease, the biomarker may determine whether the disease is present or not. Accumulation of such disease-related biomarker data can be important for improving the level of public health, from disease prevention to early diagnosis and treatment. Traditionally, it took a lot of time and effort to discover biomarkers and use them for clinical diagnosis through validation.

2-Dimensional Gel Electrophoresis, Matrix-assisted laser desorption and ionization time-of-flight (MALDI-TOF), surface-enhanced laser desorption and ionization time-of-flight (SELDI-TOF) mass spectrometry methods With high-throughput proteome analysis methods, the techniques allow for the profile of the expression of all proteins and modified proteins over a very wide range of molecular weights (Richter R. et al., Composition of the peptide fraction in human blood plasma: database of circulating human peptides.J Chromotogr B Biomed Sci Appl 726, 2535, 1999., Paweletz CP et al., Rapid protein display profiling of cancer progression directly from human tissue using a protein biochip Drug Dev Research 49, 3442, 2000).

Ciphergen's SELDI-TOF MS (Ciphergen Biosystems Inc., Fremont, CA, USA) is a device designed for high sensitivity and excellent reproducibility, and can be used to discover biomarkers by profiling proteins. The SELDI-TOF MS combines the crude sample protein directly on a protein chip array with a special chromatographic surface treatment, and then analyzes the mass by the time it reaches the detector after laser desorption / ionization. Complex biochemicals such as cell lysate, serum, plasma, urine and tissue homogenate can be applied in a variety of applications, and can be used immediately without purification even with very small protein samples. In addition, compared to the two-dimensional electrophoresis method, it is relatively easy to analyze low molecular weight proteins of 20 kDa or less.

The definition of gestational diabetes is diabetes first diagnosed during pregnancy. During pregnancy, resistance to insulin is inherently developed, so that fasting some hypoglycemia and some postprandial hyperglycemia are normal. Gestational diabetes is a case where the blood glucose control is beyond the physiologic range and, by definition, the first diabetic diagnosed during pregnancy is called gestational diabetes.

Gestational diabetes causes complications related to macrosomia in the fetus, high blood pressure in the mother, and increased cesarean section rate.In particular, gestational diabetes with high fasting blood glucose levels increases the risk of intrauterine fetal death, just as with diabetes mellitus. have. Proper diagnosis and treatment of gestational diabetes is very important in reducing these pregnancy-related complications and improving the prognosis. To screen for gestational diabetes, a 50g glucose test is usually performed between 24 and 28 weeks of pregnancy in pregnant women. If the blood glucose level exceeds 130 mg / dl or 140 mg / dl after 1 hour of this test, a 100 g glucose test is used for diagnosis. After fasting for 8-14 hours, a 100g glucose load test is performed and two or more of the values shown in Table 1 are diagnosed as gestational diabetes.

On an empty stomach 95 mg / dl After 1 hour 180 mg After 2 hours 155 mg After 3 hours 140 mg

A 50g glucose load test between 24 and 28 weeks of pregnancy in pregnant women shows that about 15% of women have blood sugar levels above 130 mg / dl or 140 mg / dl after 1 hour and 100 g glucose load for these women. About 15% of the tests diagnose gestational diabetes. There has been some recent support for the 75g glucose test and there is still controversy over which method is the most ideal gestational diabetes test.

If you have gestational diabetes, your blood sugar control will normalize after delivery, but some of you may have had diabetes before, but you may have been diagnosed during pregnancy. To differentiate this, mothers diagnosed with gestational diabetes are given an oral glucose tolerance test after 6-12 weeks of delivery to confirm that the test is negative. If you were diabetic and you didn't know it before, and you were diagnosed during pregnancy, you can be diagnosed with diabetes.

Currently, gestational diabetes screening should be performed after 24 weeks of pregnancy, and even before the test, it is known that it is not well diagnosed. If you do the test early, there is a risk of false negative results. Because the cause of gestational diabetes is known to be caused by various hormones, anti-insulin hormones such as somatomammotropin (placental lactogen) or placental growth hormone seem to play a major role. These hormones can only be diagnosed by gestational diabetes until the placenta develops enough to interfere with glucose homeostasis. For this reason, it is common to perform tests 24 weeks after pregnancy.

However, if it is possible to effectively predict gestational diabetes, which may occur in the future before this time, at a faster time, it may be possible to start a variety of preventions, measures or therapies early, ultimately improving the pregnancy outcome. . Accordingly, there is a need for the development of a method for effectively predicting gestational diabetes before 24 weeks gestation.

The first technical problem to be achieved by the present invention is to propose a method for early diagnosis of gestational diabetes using apolipoprotein C3 expression and blood glucose quantitative results.

The second technical problem to be achieved by the present invention is to propose apolipoprotein C3 protein that is used as a biomarker for the diagnosis of gestational diabetes.

The third technical problem to be achieved by the present invention is to propose a method of using apolipoprotein C3 protein as a biomarker for the diagnosis of gestational diabetes.

The fourth technical problem to be achieved by the present invention is to propose a method for monitoring, diagnosing and screening gestational diabetes using apolipoprotein C3 expression and blood glucose quantitative results.

The fifth technical problem to be achieved by the present invention is to propose a method for processing early diagnosis information on gestational diabetes using apolipoprotein C3 expression information and blood glucose quantification information.

The sixth technical problem to be achieved by the present invention is to provide a kit for gestational diabetes monitoring, diagnosis and screening comprising an antibody that specifically binds to apolipoprotein C3 protein.

In order to achieve the technical problem to be achieved by the present invention, (A) quantifying the expression level of apolipoprotein C3 of blood, plasma or serum isolated from the mother; (B) quantifying blood glucose in the blood, plasma or serum; And (C) confirming that the expression level of the apolipoprotein C3 is not included in a predetermined apolipoprotein C3 category, wherein the blood, plasma or serum reaches the first trimester or 16 to 20 weeks of gestation. A method for early diagnosis of gestational diabetes, characterized in that isolated from the mother.

Quantifying the expression level of the apolipoprotein C3 is preferably measured using two-dimensional electrophoresis, biochips or antibodies that can specifically bind to the protein.

In order to achieve the technical problem to be achieved by the present invention, it proposes apolipoprotein C3 protein that is used as a biomarker for the diagnosis of gestational diabetes in blood, plasma or serum isolated from the mother of 16 to 20 weeks gestation.

In order to achieve the technical problem to be achieved by the present invention, a method of using apolipoprotein C3 as a biomarker for the diagnosis of gestational diabetes in blood, plasma or serum isolated from the mother 16 weeks to 20 weeks pregnant.

In order to achieve the technical problem to be achieved by the present invention, gestational diabetes monitoring, diagnosis and screening comprising an antibody that specifically binds to apolipoprotein C3 protein in blood, plasma or serum isolated from the mother 16 to 20 weeks pregnant Quantifying the expression level of apolipoprotein C3 using the kit; And when the expression level of the apolipoprotein C3 is included in the predetermined apolipoprotein C3 category, judging as a gestational diabetes risk group; provides a method for monitoring, diagnosing and screening gestational diabetes, characterized in that it comprises a.

In order to achieve the technical problem to be achieved by the present invention, (K) obtaining apolipoprotein C3 expression amount quantitative information of blood, plasma or serum isolated from the mother 16 weeks to 20 weeks pregnant; (L) confirming whether the apolipoprotein C3 expression amount quantitative information is included in a predetermined apolipoprotein C3 category; And (M) generating gestational diabetes risk information using the apolipoprotein C3 expression amount information when the conditions of step (L) are met; A method for processing early diagnosis information on gestational diabetes using apolipoprotein C3 expression amount information, comprising:

In order to achieve the technical problem to be achieved by the present invention, gestational diabetes monitoring, diagnosis and screening comprising an antibody that specifically binds to apolipoprotein C3 protein in blood, plasma or serum isolated from the mother 16 to 20 weeks pregnant Present the kit.

The present invention can predict the possibility of diabetes in advance or early diagnosis by quantifying apolipoprotein C3 in pregnant women 16 to 20 weeks pregnant, it can be used to effectively cope with the early onset.

1 and 2 is a diagram comparing the spectrum of the plasma of normal and gestational diabetes patients.
3 and 4 are gel view pictures of spectral images of plasma of normal and gestational diabetes patients.
5 is a scatter diagram showing that the intensity of the peak of 9,411 Da is increased in the spectral analysis of the plasma of gestational diabetes patients compared to the normal.
6 shows the results of electrophoresis on a 15% running gel.
7 shows a passive elution result.
FIG. 8 shows Mascot Search Results. FIG.
9 shows the amino acid sequence of apolipoprotein C3.
FIG. 10 shows a box plot of the results of quantification of apolipoprotein C3 for control and patient groups (GDM).
11 is a graph showing the results of comparing the m / z 9,411 intensity and the apolipoprotein C3 quantitative correlation between the SELDI intensity and the ELISA quantitative value.

Apolipoprotein C3 can be used as a biomarker to predict the possibility of developing gestational diabetes in the future in non-diabetic pregnant women between 16 and 20 weeks before 24 weeks gestation, so gestational diabetes using apolipoprotein C3 as a biomarker Suggest early diagnosis.

First, the following experiment revealed that apolipoprotein C3 acts as an effective predictive biomarker for gestational diabetes between 16 and 20 weeks of gestation.

The materials used in this experiment were as follows.

<Materials>

Ultrafree-MC, DV 0.65 ㎛ (Millipore, UFC30DV00)

Protein G Agarose (Upstate, 16-266)

Octyl-Sepharose CL-4B resin (Sigma, O6001)

Coomassie G-250 (Fluka, 27815)

5.Formic acid (Fluka, 94318)

6. Isopropanol (Sigma, I9516)

Apolipoprotein C3 protein (Fitzgerald, 30-AA28)

8.Apolipoprotein C3 Antibody (Capture Ab.): (Chemicon, AB821)

9.apolipoprotein C3 Antibody (detection Ab.): (Biodesign, K97113R)

For effective experiments, normal and patient groups were composed as follows.

<Normal person and patient group>

Profiling was performed on 12 pregnant women with similar age, obstetric history, gestational weeks and body mass index, and 12 pregnant women with gestational diabetes. The pregnant women who were the case in the study had all HbA1c levels in the normal range at the time of gestational diabetes mellitus, and none of them were diagnosed as diabetic on oral glucose tolerance test after delivery. Therefore, the above patient group is not a person who originally had diabetes, but a gestational diabetes patient who was temporarily impaired by glucose tolerance due to pregnancy.

Plasma Acquisition and Storage

For clinical indications such as chromosome tests between 16 and 20 weeks of pregnancy, 5 mL of peripheral blood from pregnant women visited for amniotic fluid was taken and placed in a tube containing ethylene-diamine-tetra-acetic acid (EDTA) for 10 minutes at 700 g. After centrifugation, the supernatant was taken to obtain plasma and stored in -70 ℃ until used in a polypropylene tube. In these pregnant women, gestational diabetes was diagnosed by oral glucose tolerance test after 24 weeks of gestation.

Plasma Protein Mass Profile

1. Plasma was analyzed by Anion Exchange (Q10) Protein Chip array (Ciphergen). 2 μl of plasma was mixed with 9 μl of 9M Urea and 3 μl of 2% CHAPS solution and allowed to stand at room temperature for 30 minutes. 5 μl of Q10 binding buffer (0.05% Triton X-100 in 50 mM HEPES, pH7.0) Μl was added. Mix well with Vortex.

2. Q10 Chip Equilibration was loaded with 10 [mu] l of binding buffer solution every spot and left for 5 minutes at room temperature. After removing the binding buffer solution, 10 μl of the binding buffer solution was loaded into the spot, and the mixture was left at room temperature for 5 minutes.

3. The plasma mixture (plasma sample + solubilization buffer + binding buffer solution) was loaded into the spot by 5 mu l, and then reacted in a humidity chamber at room temperature for 1 hour.

4. The plasma mixture was removed, 10 l of binding buffer solution was loaded, and the binding buffer solution was immediately removed four times. The binding buffer solution was removed, 5 μl of HPLC water was loaded, and HPLC water was removed twice.

5. HPLC water was removed and dried at room temperature.

6. 1 μl of SPA (5 mg in 50% Acetonitrile (ACN), 0.5% Trifluoroacetic Acid (TFA) was loaded onto the dried spot, and 1 μl more when the SPA was dried.

7. Once the spots were completely dried, the chips were spectra taken with ProteinChip System Series 4000 (Ciphergen, Biosystems Inc., Fremont, CA, USA). The conditions were Focus mass 8,000 / 28,000, laser energy 3000 nJ, 265 shots, and 1000-200000 Da ranges.

<Spectrum Analysis>

Bovine Superoxide dismutase, equine Myoglobin, bovine beta-lactoglobulin A and horseradish peroxidase (Ciphergen, Biosystems Inc., Fremont, CA, USA) were calibrant externally calibrated and normalized using total ion current. Ciphergen Express Client ver. Using the 3.0 software, 159 peak clusters were generated by automatic peak detection under signal-to-noise 5, valley depth 5, minimum peak threshold of 0%, and cluster mass window of 0.3% MW.

Mann-Whitney U-test p-values for these peaks were compared between normal and gestational diabetic patients. Of all the peaks, 9,411 Da peak increased significantly with the normal group (p-value 0.000128). The result is in FIG. 5. First, the separation of 9,411 (m / z) will be described. The present inventors experimented with the following method.

I. Preparation of Thermostable Plasma Samples

1. 1ml of normal plasma (Normal plasma) was boiled at 100 ℃ in a 1L beaker and 250μL each of the plasma in four 1.7ml effendorf tube and boiled for 10 minutes. At this time, take out the tube every 2 minutes and vortex mix.

2. After boiling for 10 minutes, it was left at room temperature for 10 minutes.

3. After 10 minutes, remove the supernatant by centrifuging for 10 minutes at 4 ℃ at 13,000 rpm. When suspended in the supernatant was filtered by chromatography. About 200 μl of boiled plasma was obtained.

II. Hydrophobic Chromatography (Batchwise Method)

200 μl of boiled plasma (boiled plasma) was diluted with 200 μl of 1% TFA at a ratio of 1: 1 (200 μl of boiled plasma + 200 μl of 1% TFA = 400 μl).

2. Pack the octyl-Sepharose beads to 200 ㎕ in one centrifuge column and centrifuge at 3,000 rpm for 2 minutes to spin out the stock solution. out), beads were pre-equilibrated with 400 μl of 1% TFA. At this time, the balance was centrifuged by adjusting the balance to the column under the same conditions as used column (2 ~ 3 times).

3. 400 μl of the diluted plasma made in step 1 was bound to the beads packed column for 20 minutes. The column was centrifuged at 3,000 rpm for 2 minutes to spin out unbound protein.

4. The beads were washed three times with 0.1% TFA solution (2 min, 3 times).

5. After washing, the proteins bound to the beads were elution with 400 μl of 0.1% TFA / 10%, 20%, 30%, 50% ACN. (5 minutes, 2 times at each ACN%)

6. The fractions eluted at each step were identified by SELDI-TOF on Au-chip, and the m / z 9,411 peak was identified at 30% ACN elution step. .

7. The identified fractions were collected and dried by lyophilizer. In order to remove TFA and ACN remaining in the fraction, the process of dissolving again after complete drying using HPLC D.W was repeated 10 times and confirmed by pH paper.

8. The dried sample was finally dissolved in 40 μl DW and stored at -70 ° C.

Ⅲ. One-dimensional electrophoresis

1.40 μl of stored sample was added to 5 × sample buffer (60 mM Tris-HCl, pH 6.8), 25% Glycerol, 2% sodium dodecyl sulfate (SDS), 14.4 mM 2-mercaptoethanol, 0.1% bromophenol blue 10 μl was mixed and boiled at 100 ° C. for 5 minutes, cooled, and then loaded into a well.

2. Electrophoresis was performed for 6 hours in a 15% running gel. Electrophoresis was performed for 30 minutes at 10 mA in one step with constant current, and 5.5 hours at 20 mA in two steps.

3. After running, overnight staining was performed with Coomassie G-250.

IV. Passive elution

1. Pick the portion to elute from the stained gel.

2. The picked band was washed to remove coomassie blue dye. This operation was carried out under 3 times with 20 ul of 50% ACN (acetonitrile) and 50 mM ammonium bicarbonate mixed solution for 5 minutes, and the number of washes could be adjusted according to the degree of staining. .

3. The washed gel bands were dehydrated with 100% ACN for about 20 minutes.

4. 5-10 μl of eluent was added to the dehydrated gel band. Eluent was 10% formic acid (30% ACN, 20% isopropanol), 40% HPLC water.

5. Eluent was added and vigorous shaking at room temperature for 2 hours.

6. 2 μl of the eluted protein was placed on an Au-chip and confirmed by SELDI-TOF MS.

FIG. 6 shows electrophoresis results on a 15% running gel, and FIG. 7 shows passive elution results.

Then, 9,411 (m / z) identification.

Ⅴ. ESI-Q-TOF MS

One-dimensional electrophoresis was performed in step III and the band of 9,411 (m / z) protein was identified by passive elution in step IV.

The identified bands were cut out and placed in 1.7 ml effendorf tubes washed with methanol for analysis by ESI-Q-TOF MS.

8 is Mascot Search Results.

9 is the amino acid sequence of apolipoprotein C3.

ⅤI. Sandwich ELISA Assay

1. Capture antibody was diluted in coating buffer (15 mM Na ₂ CO ₃ , 35 mM NaHCO ₃ , pH 9.6) (2 μg / ml) and the microplate NUNC Immuno ^TM Module, 469914 50 μl each was coated and then overnight at 4 ° C.

2. Washing was repeated three times using PBS-T (0.05% Tween20) (Sigma, P5927).

3. 5 μl skim milk (skim milk) / PBS-T was added to 300 μl per well and incubated at room temperature for 2 hours.

4. Washing was repeated three times using PBS-T. (Repeat 3 times)

5. Plasma samples were diluted 1: 10,000 in assay diluent (1% BSA / PBS-T) and put in 50 μl per well, followed by incubation at room temperature for 2 hours. At this time, the plasma used was the same plasma sample used in the SELDI-TOF experiment.

6. Wash with PBS-T. (Repeat 3 times)

7. The biotinylated detection antibody was diluted in assay diluent (1% BSA / PBS-T) (1µg / ml), 50µl per well, and incubated at room temperature for 1 hour.

8. Washing was repeated three times for 3 minutes using PBS-T.

9. Streptavidin-HRP (Horse Radish Peroxidase; Sigma, S5512) was diluted in assay diluent (1% BSA / PBS-T) (1: 1,000), and 50 μl per well was added and incubated at room temperature for 30 minutes.

10. Wash three times for 3 minutes using PBS-T.

11. TMB (KPL, 52-00-00) solution was added 50 ㎕ per well to develop (15 minutes), the reaction stop solution (2N-H ₂ SO ₄ ) was added 50 ㎕ each.

12. Absorbance was measured at 450 nm. (ELISA reader, Emax, U.S.A)

FIG. 10 shows a box plot of the quantitative values of apolipoprotein C3 for control and patient groups (GDM). As can be seen from the box plot, the quantitative value of apolipoprotein C3 shows a distinct difference in both.

Table 2 shows the experimental results for the control.

Sample number Group SELDI Intensity (ApoC3) m / z 9,411 ApoC3 ELISA Quantitation
(占 퐂 / ml) 1.1 Normal 246.9 96.1 2.1 Normal 303.6 98.1 3.1 Normal 215.4 137.2 4.1 Normal 261.3 120.3 5.1 Normal 319.6 111.7 6.1 Normal 278.3 108.6 7.1 Normal 274.7 - 8.1 Normal 368.4 114.9 9.1 Normal 295.4 104.2 10.1 Normal 272.2 94.7 11.1 Normal 238.9 119.9 12.1 Normal 244.6 91.5

Table 3 shows the experimental results for the patient group (GDM).

Sample number Group SELDI Intensity (ApoC3) m / z 9,411 ApoC3 ELISA Quantitation
(占 퐂 / ml) One Patient group 379.8 129.3 2 Patient group 272.3 119.9 3 Patient group 466.5 156.0 4 Patient group 431.0 156.1 5 Patient group 311.9 - 6 Patient group 385.3 117.9 7 Patient group 406.9 136.3 8 Patient group 353.5 121.8 9 Patient group 360.5 117.9 10 Patient group 341.8 115.0 11 Patient group 355.6 163.6 12 Patient group 308.6 97.8

As can be seen from Table 2 and Table 3, it was found that there is a significant difference between the SELDI intensity and ELISA quantitative value between the normal group and the patient group. In particular, as can be seen in Figure 10, it can be seen that there is a significant difference in the apolipoprotein C3 ELISA quantitative value between the normal group and the patient group. By analyzing the experimental results as shown in Table 2 and Table 3, it will be possible to set the gestational diabetes risk group categories based on the SELDI intensity and ELISA quantitative value. In addition, it will be clear that the determination of the gestational diabetes risk group category can determine a relatively more valid statistical category as the experimental results are accumulated. However, when there are SELDI intensity and ELISA quantitative values associated with a specific pregnant woman, decision making regarding gestational diabetes may vary slightly depending on the specialist, and thus, the setting of the gestational diabetes risk group category may be changed accordingly.

11 is a correlation comparison between SELDI intensity (m / z 9,411) and ELISA quantitative results. As can be seen in Figure 11, it can be seen that the correlation is quite high.

As can be seen in the above process, in the present invention, apolipoprotein C3 protein in the blood collected before the onset of gestational diabetes is already in a markedly increased state as compared to normal pregnant women who do not develop gestational diabetes. We found that apolipoprotein C3 is a biomarker that can be used to predict diabetes potential.

As described above, the present inventors used the SELDI-TOF MS method and protein sequencing method in plasma collected before clinically confirmed gestational diabetic patients were diagnosed as diabetic. The SELDI-TOF MS peak (9,411 m / z) was found to show a significant increase compared to the normal pregnant women. The peak was separated by chromatography and one-dimensional electrophoresis, and confirmed by apolipoprotein C3 through ESI-Q-TOF MS analysis. Subsequently, apolipoprotein C3 was quantified by Sandwich ELISA (enzyme-linked immunosorbent assay), and apolipoprotein C3 was increased in plasma collected before the gestational diabetic group was diagnosed with gestational diabetes. It was confirmed. In addition, hemoglobin A1C, a widely used indicator for monitoring the blood glucose level of patients with diabetes (last 1 to 3 months), was normal at the time of diagnosis of gestational diabetes in all pregnant women diagnosed with gestational diabetes. It was found that the protein responds to diabetes earlier than A1C.

Accordingly, it has been demonstrated that apolipoprotein C3 can be an effective biomarker for early diagnosis of gestational diabetes in pregnant women between 16 and 20 weeks of pregnancy. Since apolipoprotein C3 may be a biomarker for diagnosing gestational diabetes of pregnant women between 16 and 20 weeks of gestation, the use of apolipoprotein C3 will be possible.

Next, a method for early diagnosis of gestational diabetes will be described. Early diagnosis of gestational diabetes mellitus of the present invention comprises the steps of: (A) quantifying the expression level of apolipoprotein C3 in blood, plasma or serum isolated from the mother at the beginning of the second trimester or 16 to 20 weeks of gestation; (B) quantifying blood glucose in the blood, plasma or serum; And (C) determining whether the expression level of the apolipoprotein C3 falls within a predetermined risk apolipoprotein C3 category. In particular, pregnant women in which the expression level of apolipoprotein C3 belongs to the predetermined risk apolipoprotein C3 category and blood sugar is in the normal category may be diagnosed as having high possibility of gestational diabetes. Quantifying the expression level of the apolipoprotein C3 is preferably measured using two-dimensional electrophoresis, a biochip or an antibody that can specifically bind to the protein, and the biochip may be a protein chip or a nucleic acid array. .

Next, gestational diabetes monitoring, diagnosis, and screening methods will be described. The method is characterized by the expression of apolipoprotein C3 using a gestational diabetes monitoring, diagnosis and screening kit comprising antibodies specifically binding to apolipoprotein C3 protein in blood, plasma or serum isolated from mothers 16 to 20 weeks pregnant. Quantifying the amount; And determining whether the expression level of the apolipoprotein C3 belongs to a predetermined risk apolipoprotein C3 category.

Subsequently, it is a method of processing early diagnosis information of gestational diabetes. The gestational diabetes early diagnosis information system implementing the method for processing gestational diabetes early diagnosis information includes (K) obtaining quantitative information of apolipoprotein C3 expression amount of blood, plasma or serum separated from the mother; (L) confirming whether the apolipoprotein C3 expression amount quantitative information belongs to a predetermined apolipoprotein C3 risk group category; And (M) generating gestational diabetes risk information using the apolipoprotein C3 expression amount information when the conditions of step (L) are satisfied. Early diagnosis of gestational diabetes using apolipoprotein C3 expression amount information in a manner further comprising: Information processing method can be performed. At this time, the gestational diabetes early diagnosis system obtains the blood glucose quantitative information in the blood, plasma or serum, and when the blood glucose quantitative information belongs to a normal category, the gestational diabetes with apolipoprotein C3 expression amount information has a higher probability. Risk information can be generated. The gestational diabetes risk information may further include information on apolipoprotein C3 expression level information and the relationship between the numerical information and the degree of risk of gestational diabetes.

Finally, the present invention provides a kit for gestational diabetes monitoring, diagnosis and screening, comprising an antibody specifically binding to apolipoprotein C3 protein in blood, plasma or serum isolated from mothers 16 to 20 weeks pregnant. Antibodies that specifically bind to the apolipoprotein C3 protein include apolipoprotein C3 Antibody: (chemicon, AB821), apolipoprotein C3 Antibody: (biodesign, K97113R), apolipoprotein C3 Antibody: (usbiological, A2299-68A), apolipoprotein C3 Antibody: (abcam , ab31528), apolipoprotein C3 Antibody: (abcam, ab77664), apolipoprotein C3 Antibody: (Abnova Corporation, H00000345-M06), apolipoprotein C3 Antibody: (GenWay Biotech, Inc., 18-272-197661), apolipoprotein C3 Antibody: ( LifeSpan BioSciences, LS-C20742), apolipoprotein C3 Antibody: (Abgent, AP7797b), apolipoprotein C3 Antibody: (MyBioSource.com, MBS316057), apolipoprotein C3 Antibody: (Sigma-Aldrich, SAB1300918).

On the other hand, when the biomarker is present, the structure of the kit using an antibody or the like that can be specifically bound to these biomarkers can be utilized kits commonly used by those skilled in the art.

The present invention can be widely used in the medical industry, the health industry, and the diagnostic industry.

Claims (7)

(A) quantifying the expression level of apolipoprotein C3 in blood, plasma or serum isolated from the mother;
(B) quantifying blood glucose in the blood, plasma or serum; And
(C) determining whether the expression level of the apolipoprotein C3 falls within a predetermined risk apolipoprotein C3 category; and
The blood, plasma or serum is isolated from the mother at the beginning of the second trimester or 16 to 20 weeks of gestation, characterized in that for providing early diagnosis information for gestational diabetes. The method of claim 1,
The method for providing early diagnosis information on gestational diabetes mellitus, characterized in that quantifying the expression level of apolipoprotein C3 is measured using two-dimensional electrophoresis, biochips or antibodies that can specifically bind to the protein. delete  A method for providing early diagnosis of gestational diabetes mellitus by using apolipoprotein C3 as a biomarker for diagnosing gestational diabetes mellitus in blood, plasma or serum isolated from mothers 16 to 20 weeks of gestation. Determination of the expression level of apolipoprotein C3 using a kit for monitoring, diagnosing or screening gestational diabetes, including antibodies specifically binding to apolipoprotein C3 protein, in blood, plasma or serum isolated from mothers 16 to 20 weeks pregnant Making; And
Determining whether the expression level of the apolipoprotein C3 belongs to a predetermined risk apolipoprotein C3 category; and providing early diagnosis information for gestational diabetes mellitus. (K) obtaining quantitative information of apolipoprotein C3 expression amount of blood, plasma or serum isolated from the mother of 16 to 20 weeks of gestation;
(L) confirming whether the apolipoprotein C3 expression amount quantitative information belongs to a predetermined apolipoprotein C3 risk group category; And
(M) if the conditions of step (L) is met, generating gestational diabetes risk information using the apolipoprotein C3 expression amount information; providing a method for providing early diagnosis of gestational diabetes, characterized in that it comprises a. Including antibodies that specifically bind to apolipoprotein C3 protein in blood, plasma or serum isolated from mothers 16 to 20 weeks pregnant,
Kit for monitoring, diagnosing and screening gestational diabetes, characterized in that it is used to provide early diagnosis information for gestational diabetes.

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