CN112924689B - Diabetes diagnosis kit based on quantitative determination of polypeptide combined marker and method thereof - Google Patents

Abstract

The invention relates to the field of medical biological detection, in particular to a novel use of a polypeptide combination marker in the preparation of a diabetes diagnostic reagent or kit. The present invention provides a method and kit for quantitatively detecting endogenous polypeptides in serum by using liquid chromatography-mass spectrometry multiple reaction monitoring (MRM). The content of the four endogenous polypeptide markers is then calculated based on the binary logistic regression equation, and the combined marker variable and the determined cut-off value are used for early warning and/or diagnosis of diabetes. The kit and the detection method of the invention have good stability and high specificity, and have the potential of clinical promotion.

Description

Diabetes diagnostic kit and method based on quantitative determination of peptide combination markers

technical field

The present invention relates to medical biological detection technology and the fields of diagnosis, prevention and treatment of metabolic diseases, in particular, to the preparation of reagents for early warning and/or diagnosis of diabetes based on a method for quantitative determination of endogenous polypeptides in human plasma and a combination marker of polypeptides Box and method.

Background technique

According to data from the International Diabetes Federation in 2017, there are 415 million people with diabetes worldwide, of which type 2 diabetes (T2DM) accounts for more than 95%. The number of people with diabetes worldwide is expected to increase to 552 million by 2030. Diabetes is the third major disease that endangers human health after cardiovascular disease and tumor. At present, although the diagnostic criteria for type 2 diabetes have been clarified, and there are gold standards such as oral glucose tolerance test (OGTT), due to the lack of obvious symptoms and a long incubation period in the early stage of diabetes, intervention and treatment after symptoms appear or clinical diagnosis are often made. It is irreversible, and the best intervention period is lost by mistake. Finding biomarkers for early warning and diagnosis is of great significance for studying the pathology, classification, early diagnosis, delaying and preventing the occurrence of diabetes.

The use of multi-omics technology to discover new diagnostic markers is a current research hotspot. Polypeptides play an important role in the pathogenesis and intervention of diabetes, such as many peptide drugs such as glucagon-like peptide 1 (GLP-1) analogs, dulaglutide, brain Natriuretic peptide (brain natriureticpeptide, BNP) and other peptide preparations. Peptides can reflect the synthesis, processing and degradation of proteins under different physiological and pathological conditions, and at the same time, they have regulatory effects on gene expression, material metabolism and other processes. Early warning/diagnosis has great potential.

Marker verification: The potential biomarkers of type 2 diabetes that have been discovered so far include gene variants, RNA transcripts, polypeptides, proteins, lipids, and small molecule metabolites (branched-chain amino acids/aromatic amino acids), etc., but most of them come from complications Samples, such as diabetic nephropathy, diabetes with hypertension and hyperglycemia, gestational diabetes, etc. (Chinese Patent CN106645757A; Medical Review, 2019, (20), 4080-4086; Mol Cell Proteomics, 2010, 9(10), 2099-2108 ; Chinese Journal of Practical Diagnosis and Treatment, 2018, 32(01), 1-4), complications usually occur, diabetes is in the late stage of diagnosis and irreversibility, and there is a lack of biomarkers for diabetes itself and for early diagnosis; In addition, the use of multi-omics technology to screen out differential markers lacks further clinical sample verification work, resulting in limited clinical application value; or using ELISA or Western blot verification, the experimental cost is high and the throughput is insufficient (Chinese Patent CN108957011; Chromatography, 2019, 37(8): 853-862; Chinese General Medicine, 2014, (21), 2524-2527).

Based on the problems existing in the above research, the present invention adopts a method combining non-targeted peptidomics and targeted quantitative peptidomics, which has the characteristics of high throughput, good data repeatability and high sensitivity. Using a discovery-to-validation strategy to screen potential diagnostic markers, successfully screen and validate combined markers of endogenous polypeptides in human serum from pre-diabetic clinical samples (without complications), which can be used for early warning and/or diagnosis of diabetes , the diagnostic sensitivity and specificity of the combined marker are good, and a kit for quantitative determination of target polypeptide content and for early warning and/or diagnosis of diabetes has been prepared, which has not yet been reported.

SUMMARY OF THE INVENTION

The purpose of the present invention is to solve the problems of lack of early warning diagnostic markers for diabetes, low sensitivity and low specificity, and to provide a combination of peptide markers by using non-targeted peptidomics to discover differential peptides and targeted peptidomics to verify. The application and kit in early warning/diagnosis of diabetes also provide a method for quantitative analysis and detection of the above-mentioned combined polypeptide markers.

For achieving the above object, the technical scheme adopted in the present invention is as follows:

(1) Non-targeted analysis of serum endogenous polypeptides in normal people, patients with early stage diabetes, and diabetic patients (without complications such as hypertension and hyperlipidemia) using non-targeted peptide omics methods, using standard-free quantitative methods Screen the differential polypeptides, and the screening conditions include P value, credible confidence interval, etc., and retain the differential polypeptides that meet the conditions.

(2) For the differential peptides in (1), by synthesizing standard peptides and dimethyl labeling, using the method of targeted peptide omics, in another batch of healthy people/diabetic patients (without complications such as hypertension and hyperlipidemia) In clinical samples, the above differential peptides were verified. The stability of the peptide was also investigated, and the potential for the preparation and development of early warning/diagnosis kits for diabetes was preliminarily evaluated.

(3) Using SPSS statistical software, through binary logistic regression analysis, the regression was used as a combined marker variable, and the ROC (receiver operating characteristic) curve was used to evaluate the sensitivity and specificity of the combined marker.

(4) Use of combined markers: In diabetic patients, the contents of polypeptides GVLSSRQLGLPGPPDVPDHAAYHPF(245), GVLSSRQLGLPGPPDVPDHAA(244), GLPGPPDVPDHAAYHPF(251) and GSEMVVAGKLQ(261) changed significantly. The four polypeptides are regressed as the combined marker variable X, and the binary logistic regression equation is:

X=1.630+5.279×C(245)+8.971×C(244)-4.232×C(251)-14.175×C(261)

Prob(diabetes)=1/[1+e ^-X ]

Among them, C represents the concentration of plasma polypeptide; e is the Euler number, the base of the natural logarithmic function; Prob is the variable value of the combined marker. When the P value is greater than or equal to 0.55, a diabetic patient is diagnosed, otherwise it is a non-diabetic population.

(5) Devices included in the diagnostic system: a chromatographic column, and the detection instrument is a liquid chromatography-mass spectrometer.

(6) Determine the composition of the kit, including seven reagents or solutions of A, B, C, D, E, F, and G, specifically:

Dimethyl labeling reagent: A, PBS buffer (PH=8.0～8.4); B, 4% formaldehyde by volume (light standard treatment reagent) and/or 4% deuterated formaldehyde by volume (successful standard treatment reagent); C, 0.6M sodium cyanoborohydride (NaBH3CN); D, 1% ammonia water by mass; E, 5% formic acid solution by volume;

Standard solution F: The light standard solution obtained by the treatment of polypeptide (245, 244, 251, 261) with dimethyl light standard reagent, after drying, desalting and drying again, dissolved in 0.1%-1% formic acid by volume , and the final concentrations of the peptides were 10-40 μg/mL;

Internal standard solution G containing stable isotopes: The winning standard solution obtained by treating polypeptide (245, 244, 251, 261) with dimethyl-labeled winning standard reagent, after drying, desalting, and drying again, dissolved in a volume concentration of 0.1%-1 % formic acid, and the final concentrations of the peptides were 0.3-10 μg/mL, respectively.

The specific steps are:

1) Ultrafiltration: take 10-50 μL plasma sample, centrifuge the endogenous polypeptide in a 10K Da ultrafiltration tube; dry to obtain the endogenous polypeptide sample;

2) Light labeling: the endogenous polypeptide samples are sequentially treated with the above-mentioned dimethyl labeling light labeling reagents A, B, C, D, and E to obtain an endogenous polypeptide dimethyl labeling sample (light labeling), which is dried;

3) Desalting: use a C18 filler TIP head or solid phase extraction cartridge for desalting and drying; refrigerate at -80°C for later use;

4) Preparation of the test solution: reversely dissolve the endogenous polypeptide light-labeled sample with 10-50μL of 0.1%-1% formic acid solution, centrifuge at 20,000g for 5-8 minutes, take 10-40μL of the supernatant, add 10- 40 μL of internal standard solution G is the solution to be tested;

5) Preparation of standard curve: standard solution F is diluted with 0.1%-1% formic acid solution into a series of standard solution, take 1-10 μL standard solution, add 10-40 μL blank plasma sample and 10-40 μL internal standard solution G A series of standard curve samples can be obtained, with a final concentration range of 5ng/mL-1000ng/mL; the blank plasma sample is the endogenous polypeptide extracted by ultrafiltration, treated with A, D, E in turn, desalted and dried. Dissolved in 0.1%-1% formic acid solution; liquid chromatography-mass spectrometry multiple reaction monitoring (LC-MS/MRM) was used to measure the intensities of the light and middle standard ion peaks of the peptide, and the samples were compared with the ratio of the peak areas of the two. Concentration fitting standard curve;

6) Determination of polypeptide content: The prepared standard curve sample and the clinical sample test solution were analyzed by LC-MS/MRM respectively, and the content of the target polypeptide was calculated by the external standard method.

(7) Instrument analysis conditions

The liquid chromatography operating conditions: Waters UPLC liquid chromatograph, chromatographic column, Acquity UPLC@HSS, T3, 1.8 μm; mobile phase, acetonitrile-0.1% formic acid (A), 0.1% formic acid aqueous solution (B). The gradient conditions are as follows:

Table 1 Liquid chromatography conditions

The mass spectrometry conditions, Qtrap 5500 mass spectrometer, mass spectrometry multiple reaction monitoring (MRM), MRM quantitative transitions and mass spectrometry parameters of the target 4 polypeptides are shown in Table 2, and the mass spectrogram is shown in Figure 1.

Table 2 Quantitative transitions of target peptides

(7) Using serum samples to test the application effect of the present invention. Using the combined marker, normal subjects and diabetic subjects were well differentiated, as shown in Figure 2, with an AUC value of 0.864, a sensitivity of 0.78, and a specificity of 0.78. The optimal cut-off is 0.55. Diabetes mellitus is diagnosed if the value is greater than or equal to the cut-off point.

(8) Study on the stability of polypeptide markers: The four polypeptides involved in this patent can be stored in a refrigerator at 4°C for 2 months, and no significant degradation has occurred in either the light-labeled samples or the winning-labeled samples, indicating that the kit has good stability. .

The advantages of the present invention are:

1) The discovery process of the biomarkers of the present invention includes using non-targeted metabolomics to screen differential polypeptides, and then confirming the structure through polypeptide synthesis, and using mass spectrometry multiple reaction monitoring (multiple reaction monitoring, MRM) targeted quantitative peptidomics Methods Different batches of clinical samples were verified in three processes, and their clinical reference value and reliability were high.

2) The present invention provides a kit for early warning/diagnosis of diabetes. By applying the kit, accurate quantitative determination of target polypeptides in clinical samples to be tested can be conveniently achieved, and then the combination based on binary logistic regression equation can be calculated. The marker variable Prob and the cut-off value (cut-off) are used to make a preliminary judgment on the risk and diagnosis of diabetes in the sample to be tested. The kit has the characteristics of good stability, high diagnostic specificity and high sensitivity, is applied to assist early diagnosis, and has high development and application value.

Description of drawings

Figure 1 MRM detection map of peptides

Figure 2 ROC diagnostic model; legend: area under the AUC curve; sensitivity, specificity, criterion (cut-off value) threshold

Detailed ways

The specific embodiments provided by the present invention will be described in detail below with reference to the examples. However, these examples are only exemplary and do not constitute any limitation to the scope of the present invention. The details and forms of the technical solutions of the present invention may be modified or replaced without departing from the spirit and scope of the present invention, but these modifications and replacements all fall within the protection scope of the present invention.

Example 1: Screening of differential polypeptides by standard-free quantitative method

Clinical samples: 23 human serum samples (including 7 healthy people, 7 prediabetic patients, and 9 type 2 diabetes patients) were from Shanghai Sixth People's Hospital. Patients with prediabetes and type 2 diabetes were diagnosed or excluded by experts, and the three groups were matched for age, body mass index (BMI), blood sugar and other indicators. Blood samples were approved by the local hospital ethics committee, and all subjects signed informed consent. Blood samples were stored in a -80°C refrigerator after collection.

Extraction of serum endogenous polypeptides: Ultrafiltration centrifugation was used. Specific operation process: Take the blood sample from the -80°C refrigerator and thaw it in an ice bath, vortex to mix, and centrifuge at 20,000g for 5min to discard the lipid. Take 25 μL of each serum sample, add 125 μL of deionized water, and boil for 5 min for denaturation. After cooling to room temperature, 150 μL of an aqueous solution of 40% acetonitrile-0.1% formic acid by volume was added, mixed by vortex and left in an ice bath for 40 min. The sample was then transferred to an ultrafiltration tube with a molecular weight cut-off of 10 kDa, centrifuged at 6000 g for 20 min at 4°C, and the filter cake was washed twice with 300 μL of an aqueous solution of 20% acetonitrile-0.1% formic acid by volume. The filtrate was collected, freeze-dried, and stored in a -80°C refrigerator for later use after desalting. Before injection and analysis, the samples were redissolved in 25 μL of 0.1% FA solution, vortexed for 2 min, centrifuged at 20,000 g for 5 min at 4°C, and the supernatant was taken for nano-LC-MS/MS analysis.

LC-MS/MS data acquisition: Nano-RPLC-MS/MS system including high performance liquid chromatography with quaternary gradient pump (Ultimate 3000), autosampler and linear ion trap-static orbitrap (LTQ-Orbitrap Elite) ), trap column (3cm×200μm, C18); analytical column (12cm×150μm, C18). Mobile phase composition: A phase is 0.1% formic acid aqueous solution, B phase is 80% acetonitrile containing 0.1% formic acid solution. The separation gradient was set to: 0-2%B, 10min; 2-5%B, 3min; 5-28%B, 60min; 28-45%B, 15min; 45-95%B, 1min; 95%B, 5min . The flow rate was 0.5 μL/min. Mass spectrometry conditions: the temperature of the LTQ ion transfer tube was set to 275°C, and the electrospray voltage was set to 2.7 kV. All data acquisition modes were data-dependent mode (DDA), and the full scan of mass spectrometry was acquired in Orbitrap with a scan range of 200-2000 Da and a resolution of 12,000. MS scans were acquired in the LTQ using collision-induced dissociation (CID) fragmentation. System control and data collection were performed using Xcalibur software (version 2.1, Thermo Corporation).

Mass spectrometry data retrieval and analysis: Mass spectrometry data were retrieved using Mascot software, and the retrieval database was a human library (UniProt, about 170,000 proteins). The search parameters were set as follows: the methionine residue (+15.9949Da) was a variable modification, without enzyme digestion, the mass error of the parent ion was 20ppm, and the error of the secondary fragment ion was 0.8Da. Peptide screening thresholds were set to score values above 20 with a false positive rate (FDR) of less than 1%. Peptide quantification was performed using MaxQuant software for data analysis. The false positive rate (false discovery rate, FDR) was 0.01.

Differential peptide screening: A total of 163 differential peptides were screened. The 21 samples with large differential fold changes were further selected for further clinical sample verification. The differential peptide information is shown in Table 3:

Table 3 Differential peptide information to be further verified

polypeptide sequence Difference fold MW No. PI GRAVY GKSSSYSKQFTSSTSYNRGDDSTFES 2 times higher 2738.82 25 8.43 -1.34 GVLSSRQLGLPGPPDVPDHAAYHPF PRE up-regulated 3-fold 2627.94 25 5.98 -0.292 SSYSKQFTSSTSYNRGDDSTFES PRE, T2D down-regulated 4-5 times 2466.51 twenty two 5.79 -1.286 SYKMADEAGSEADHEGTHSTKR PRE down 5-fold 2407.51 twenty two 5.37 -1.582 GVLSSRQLGLPGPPDVPDHAA PRE up 2.4 times 2083.33 twenty one 5.21 -0.19 FTSSTSYNRGDSTFESKS T2D down-regulated 3-fold 2001.05 18 6.07 -1.217 DQEQSQVAEKPMEGESR PRE down 3-fold 1948.05 17 4.25 -1.888 GLGHGHEQQHGLGHGHKF PRE up-regulated 2-fold, T2D down-regulated 11-fold 1933.08 18 7.16 -1.244 HKSEVAHRFKDLGEEN T2D up-regulated 3-fold 1896.05 16 6.03 -1.55 SSSYSKQFTSSTSYNRG PRE down 3-fold 1886.95 17 9.7 -1.329 EALHNHYTQKSLSLSPG T2D up-regulated 5-fold 1882.06 17 7.01 -0.824 SSKITHRIHWESASLL PRE down-regulated 2-fold, T2D up-regulated 2-fold 1865.12 16 8.51 -0.294 GLPGPPDVPDHAAYHPF PRE up-regulated 3-fold 1786.96 17 5.05 -0.535 SKITHRIHWESASLL T2D down-regulated 2.8-3.8 times 1778.04 15 8.51 -0.26 SEETKENEGFTVTAEG PRE up-regulated 3-fold 1727.76 16 3.98 -1.238 SRQLGLPGPPDVPDHAA T2D down-regulated 3-fold 1726.91 17 5.19 -0.635 GVEVHNAKTKPREEQ T2D up-regulated 3-fold 1721.89 15 6.76 -1.7 DIQMTQSPSSVSASVGD T2D up-regulated 3-fold 1708.81 17 3.56 -0.241 DEAGSEADHEGTH PRE down 3-fold 1354.27 13 4.17 -1.738 GVNDNEEGFF T2D up-regulated 3-fold 1127.13 10 3.57 -0.85 GSEMVVAGKLQ T2D down 5-fold 1118.31 11 6 0.309

Note: Up-regulation and down-regulation mean the ratio of the content of polypeptides in the PRE group (initial diabetes group) or T2D group (diabetes group) to the corresponding polypeptide content in the control group. Greater than 1 means up-regulation; less than 1 means down-regulation.

Example 2: Dimethyl-labeled polypeptides and targeted MRM verification

Clinical samples: 18 human serum samples (including 9 serum samples from healthy individuals and 9 serum samples from patients with type 2 diabetes) were obtained from Shanghai Sixth People's Hospital. Type 2 diabetes patients were diagnosed or excluded by experts, and the three groups of subjects were matched for age, body mass index (BMI), blood sugar and other indicators. There were no complications such as hypertension and hyperglycemia in the diabetic patients. Blood samples were approved by the local hospital ethics committee, and all subjects signed informed consent. Blood samples were stored in a -80°C refrigerator after collection.

Extraction of Serum Endogenous Polypeptides: Reference Example 1.

Synthesis of peptides: According to the information in Table 3 above, the structure of the synthetic target peptides was reconfirmed by comparing their MS spectra.

Dimethyl labeling: Use the following kits to prepare the winning standard internal standard solution and prepare the standard curve sample and clinical sample test solution. Kit composition:

Dimethyl labeling reagent: A, PBS buffer (PH=8.0); B, 4% formaldehyde by volume (light standard treatment reagent) and/or 4% deuterated formaldehyde (successful standard treatment reagent) by volume; C, 0.6M Sodium cyanoborohydride (NaBH3CN); D, 1% ammonia water by mass; E, 5% formic acid solution by volume;

Standard solution F: The light standard solution obtained by the treatment of polypeptides (245, 244, 251, 261) with dimethyl light standard reagent, after drying, desalting, and drying again, dissolved in formic acid with a volume concentration of 1%. The final concentrations were 40 μg/mL;

Internal standard solution G containing stable isotopes: The winning standard solution obtained by treating polypeptide (245, 244, 251, 261) with dimethyl-labeled winning standard reagent, after drying, desalting, and drying again, dissolved in a volume concentration of 0.1%-1 % formic acid, and the final concentrations of the peptides were 10 μg/mL.

The specific steps are:

1) Ultrafiltration: take 25μL of plasma sample, centrifuge the endogenous polypeptide in a 10K Da ultrafiltration tube; dry to obtain the endogenous polypeptide sample;

2) Light labeling: the endogenous polypeptide samples are sequentially treated with the above-mentioned dimethyl labeling light labeling reagents A, B, C, D, and E to obtain an endogenous polypeptide dimethyl labeling sample (light labeling), which is dried;

3) Desalting: use a C18 filler TIP head or solid phase extraction cartridge for desalting and drying; refrigerate at -80°C for later use;

4) Preparation of test solution: reversely dissolve the endogenous polypeptide light-labeled sample with 30 μL of 1% formic acid solution, centrifuge at 20,000g for 8 minutes, take 25 μL of supernatant, and add 10 μL of internal standard solution G to obtain the test solution to be tested. ;

5) Preparation of standard curve: The standard solution F is diluted with 1% formic acid solution into a series of standard solutions, 5 μL of standard solution is taken, 40 μL of blank plasma sample and 10 μL of internal standard solution G are added to obtain a series of standard curve samples. The final concentration range is 5ng/mL, 10ng/mL, 50ng/mL, 100ng/mL, 500ng/mL, 1000ng/mL; the blank plasma sample is the endogenous polypeptide extracted by ultrafiltration, which is treated with A, D and E in turn After desalting and drying, it was dissolved in 1% formic acid solution; liquid chromatography-mass spectrometry multiple reaction monitoring (LC-MS/MRM) was used to determine the intensities of the light standard and medium standard ion peaks of the polypeptide, and the peak area of the two Fit the standard curve to the concentration of the sample;

6) Determination of polypeptide content: The prepared standard curve sample and the clinical sample test solution were analyzed by LC-MS/MRM respectively, and the content of the target polypeptide was calculated by the external standard method.

Instrument analysis conditions

The liquid chromatography operating conditions: Waters UPLC liquid chromatograph, chromatographic column, Acquity UPLC@HSS, T3, 1.8 μm; mobile phase, acetonitrile-0.1% formic acid (A), 0.1% formic acid aqueous solution (B). The gradient conditions are shown in Table 1.

The mass spectrometry conditions, Qtrap 5500 mass spectrometer, mass spectrometry multiple reaction monitoring (MRM), MRM qualitative and quantitative transitions and mass spectrometry parameters of the target 21 polypeptides are shown in Table 4.

Table 4 Qualitative and quantitative transitions of 21 polypeptides

Note: L means light bid, M means successful bid.

Targeted validation: Quantitative results show that 4 of the peptides are significantly different between normal and diabetic samples, which can be used for variable regression diagnostic models. Thus, the quantitative transitions of the four polypeptides were further optimized, as shown in Table 2.

Stability evaluation: The stability of the target polypeptide was further evaluated. The results showed that the four polypeptides were placed in a refrigerator at 4°C for 2 months, and no obvious degradation was found, and they had the potential to be used as diagnostic markers.

Example 3: Determination of Early Warning/Diagnostic Markers

From the above quantitative results, it can be seen that the contents of the polypeptides GVLSSRQLGLPGPPDVPDHAAYHPF(245), GVLSSRQLGLPGPPDVPDHAA(244), GLPGPPDVPDHAAYHPF(251) and GSEMVVAGKLQ(261) in the healthy and diabetic patients were significantly changed.

Using SPSS statistical software, through binary logistic regression analysis, the four peptides were regressed as combined marker variables, and the ROC (receiver operating characteristic) curve was used to evaluate the sensitivity and specificity of the combined markers. Candidate markers were identified with AUC greater than 0.8.

The four polypeptides are regressed as the combined marker variable X, and the binary logistic regression equation is:

X=1.630+5.279×C(245)+8.971×C(244)-4.232×C(251)-14.175×C(261)

Prob(diabetes)=1/[1+e ^-X ]

Among them, C represents the concentration of plasma polypeptide; e is the Euler number, the base of the natural logarithmic function; Prob is the variable value of the combined marker. When the P value is greater than or equal to 0.55, a diabetic patient is diagnosed, otherwise it is a non-diabetic population.

The cut-off value was determined based on the receiver operating characteristic curve (ROC curve) based on the P value of the combined marker variable, and the P value with the largest sum of sensitivity and specificity was taken as the best cut-off value.

Serum samples were used to test the application effect of the present invention. Using the combined marker, normal subjects and diabetic subjects were well differentiated, as shown in Figure 2, with an AUC value of 0.864, a sensitivity of 0.78, and a specificity of 0.78. It shows that the diagnostic model of the present invention has better clinical application effect.

Claims (4)

1. Application of the combined markers of the polypeptides GVLSSRQLGLPGPPDVPDHAAYHPF 245, GVLSSRQLGLPGPPDVPDHAA 244, GLPGPPDVPDHAAYHPF 251 and GSEMVVAGKLQ 261 in the preparation of diabetes early warning and/or diagnostic kits; Said diagnostic kit detects the content of polypeptides 245, 244, 251 and 261 in serum. 2. The application of the combination marker according to claim 1 in the preparation of a test kit for diagnosing diabetes mellitus in a subject, wherein the diagnostic kit is to detect polypeptide 245 by liquid chromatography-mass spectrometry , 244, 251 and 261 of the combination of the reagents. 3. A detection kit for early warning/diagnosis of diabetes, characterized in that the diagnosis or the kit comprises: (1) Dimethyl labeling reagent: A, PBS buffer pH=8.0~8.4; B, 4% volume concentration formaldehyde light standard treatment reagent and/or 4% volume concentration deuterated formaldehyde winning standard treatment reagent; C, 0.6M cyanide Sodium borohydride (NaBH3CN); D, 1% aqueous ammonia by mass; E, 5% formic acid solution by volume; (2) Standard solution F: The light standard solution obtained by the treatment of polypeptides 245, 244, 251 and 261 with dimethyl light standard reagent, after drying, desalting and drying again, dissolved in 0.1%-1% by volume concentration. Formic acid, the final concentration of the peptide is 10-40 μg/mL; (3) Internal standard solution G containing stable isotopes: The winning standard solution obtained by treating polypeptides 245, 244, 251 and 261 with dimethyl-labeled winning standard reagent, after drying, desalting and drying again, dissolved in a volume concentration of 0.1%- 1% formic acid, the final concentration of peptides was 0.3-10 μg/mL, respectively. 4. The application of the combination marker according to claim 1 in the preparation of a kit for diagnosing diabetic patients in a subject, wherein the combination marker variable and the cut-off value are used for the early stage of diabetes Diagnosis and early warning; the content of endogenous polypeptide markers in human serum can be quantitatively determined, and then the combined marker variables and the determined cut-off value can be calculated based on binary logistic regression equations for early warning and/or diagnosis of diabetes.

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