Methods for establishing subtypes of gout and damp-heat syndrome, applications and detection methods of biomarkers

Abstract

This invention belongs to the field of animal model analysis technology, specifically relating to a method for establishing a model of gouty rheumatic fever subtypes, the application of a biomarker group, and a detection method. This invention constructs two subtype models of gouty rheumatic fever with more emphasis on dampness and fever with more emphasis on dampness, and establishes a UPLC-MS detection method for serum biomarkers, obtaining a biomarker group including lauroylcarnitine, taurine, palmitoyl-L-carnitine, L-leucine, leukotriene A4, and 13-Oxo-9,11-tridecadienoic acid. Studies show that this biomarker group can simply and effectively distinguish between gouty rheumatic fever with more emphasis on dampness and fever with more emphasis on dampness, and determine the success of model establishment for the two subtypes. Therefore, it can replace conventional characterization and biochemical pathological evaluation methods, improving the objectivity and operability of the assessment.

Description

Technical Field

[0001] This invention belongs to the field of animal model analysis technology, specifically relating to a method for establishing a subtype model of gout and damp-heat syndrome, the use of biomarkers and their detection methods. Background Technology

[0002] Damp-heat syndrome is a key syndrome type in the clinical treatment of gouty arthritis, and the Lingnan region is known for its damp-heat constitution, with patients often exhibiting damp-heat in the spleen and stomach. Based on the syndrome predominance, damp-heat gout can be divided into two subtypes: dampness predominantly over heat and heat predominantly over dampness. According to the treatment principles of traditional Chinese medicine and ethnic minority medicine, clinical treatment of damp-heat gout requires differentiation of syndromes based on whether dampness or heat is predominantly dominant. In clinical treatment, the diagnosis and prescription of medication can be entirely based on the judgment of a professional physician.

[0003] In preclinical animal efficacy evaluations, it is often necessary to assess the efficacy of drugs on different damp-heat syndrome gout models (two subtypes: dampness predominantly over heat and heat predominantly over dampness). However, animals cannot be diagnosed through observation, auscultation, inquiry, and palpation. Extensive semi-quantitative subjective assessment is required. Semi-quantitative assessments based on body shape, urination and defecation, rectal temperature, coat color, and activity level often lack accuracy and have complex systems. This makes it difficult to differentiate between the two subtypes in animal model evaluations, and also makes it difficult to determine whether the model was successfully established. For example, Zhang Junying created dampness-predominant-heat and heat-predominant-dampness rat models (administered traditional Chinese medicine, high-fat diet, high-temperature and high-humidity environment, E. coli) using various environmental and dietary factors. She found that the heat-predominant model group had a faster rise in body temperature, lower food intake, higher water intake, drier stools, yellow and cloudy urine, and increased restlessness. This requires a combination of extensive behavioral, dietary, and urination observations, as well as histopathological observations that can only be conducted by euthanizing animals (Preliminary Study on the Construction of Models for Dampness Predominance over Heat and Heat Predominance over Dampness in Febrile Diseases, Graduation Thesis of Hubei University of Traditional Chinese Medicine, 2009).

[0004] As the two subtypes of gout with dampness predominating over heat and heat predominating over dampness, their metabolomics changes are extremely complex and difficult to distinguish or identify using a single blood biomarker. Therefore, developing a detection method that can simultaneously detect multiple biomarkers in animal models of gout with damp-heat syndrome, and screening biomarker groups that can easily and effectively identify or differentiate between the two subtypes of gout with dampness predominating over heat and heat predominating over dampness in animal models of gout with damp-heat syndrome, is of great practical significance for both traditional Chinese medicine evaluation and clinical diagnosis. Summary of the Invention

[0005] To address the aforementioned issues, the present invention aims to provide a method for establishing a subtype model of gouty rheumatic fever, the application of a biomarker group, and a detection method, thereby providing significant convenience for clinical diagnosis and animal model evaluation and assessment.

[0006] The basic idea of ​​this invention is as follows: First, using a recognized and mature modeling method, a gout dampness-predominant-heat subtype group and a gout heat-predominant-dampness subtype group are induced and established. Traditional methods based on traditional Chinese medicine animal model evaluation, along with behavioral and pathological approaches, are used to assess the success of model establishment. Then, a new UPLC-MS analysis method is established to analyze animal blood samples. Based on this, metabolomics evaluation is performed to identify potential biomarkers that can distinguish between the two models or determine the success of model establishment. Overlapping indicators among the differentially expressed metabolic biomarkers from the two groups are selected for receiver operating characteristic (ROC) analysis to obtain cutoff values ​​and recognition ability indicators. This establishes an objective, simple, and effective method for distinguishing between gout dampness-predominant-heat and heat-predominant-dampness animal models, and can be used to determine the success of either the gout dampness-predominant-heat or gout heat-predominant-dampness model. The technical solution of this invention is as follows:

[0007] A method for establishing a subtype model of gouty damp-heat syndrome includes inducing gout in animals using hypoxanthine, potassium oxonate, and sodium urate; inducing damp-heat syndrome in animals using high-fat diet, ethanol diet, dried ginger, and artificial climate chamber; and collecting animal blood samples for UPLC-MS analysis and screening. The animal model is a rodent model. The method for establishing the subtype model of gouty damp-heat syndrome further includes the following steps:

[0008] S1: After the modeling is completed, blood samples are taken from the animals to separate serum. The biomarker group in the serum of normal animals and model animals is analyzed by UPLC-MS. The biomarker group includes: lauroylcarnitine, taurine, palmitoyl-L-carnitine, L-leucine, leukotriene A4, and 13-Oxo-9,11-tridecadienoic acid.

[0009] S2: Normalize the values ​​of each biomarker by dividing the original index content of the biomarker group in S1 by the average value of the corresponding index in the normal group, and then screen the model animals based on the cutoff value.

[0010] Preferably, in step S2, when the desired gout model is the wet weight-more-thermal subtype, the normalized values ​​of lauroylcarnitine > 1.4330, taurine > 1.4463, palmitoyl-L-carnitine > 1.5429, L-leucine < 0.8317, leukotriene A4 > 2.8835, and 13-Oxo-9,11-tridecadienoic acid are present. A successful model is determined when at least three of the following conditions are met: the normalized value of acid is greater than 1.1770 and less than 1.3379; when the required gout model is the heat-weighted-more-wet subtype, the following conditions must be met: the normalized value of lauroylcarnitine is greater than 1.1361 and less than 1.4330; the normalized value of taurine is greater than 1.2556 and less than 1.4463; the normalized value of palmitoyl-L-carnitine is greater than 0.9739 and less than 1.5429; the normalized value of L-leucine is greater than 0.8317; the normalized value of leukotriene A4 is greater than 1.8198 and less than 2.8835; and the normalized value of 13-Oxo-9,11-tridecadienoic acid is greater than 1.3379.

[0011] A UPLC-MS detection method for a biomarker set in a subtype model of gouty-damp-fever syndrome, wherein the subtype model of gouty-damp-fever syndrome is a rodent model, and the biomarker set is a biomarker set for distinguishing between two subtypes of gouty-dampness-predominant-fever and gouty-fever-predominant-dampness, and / or a biomarker set for determining whether the two subtypes of gouty-dampness-predominant-fever and gouty-fever-predominant-dampness have been successfully established. The detection method includes the following steps:

[0012] J1. Take animal blood samples to separate serum, add methanol, vortex for 0.5 min to 1.5 min, centrifuge, and filter the supernatant through a 0.22 μm filter membrane to obtain the sample processing solution to be tested;

[0013] J2. Take the sample solution from step S1 and perform UPLC-MS analysis:

[0014] UPLC chromatographic conditions: ACQUITY UPLC HSS T3 column; column size 2.1 mm x 100 mm, particle size 1.8 μm; mobile phase A: acetonitrile, mobile phase B: 0.1% formic acid in water; column temperature: 30℃~35℃; flow rate: 0.3 mL / min; gradient elution program as follows:

[0015] Washing time (min) Mobile phase A (%) Mobile phase B (%) Initial 5.0 95.0 1.00 25.0 75.0 2.00 60.0 40.0 7.50 90.0 10.0 10.50 99.0 1.0 12.50 99.0 1.0 13.00 5.0 95.0 15.00 5.0 95.0

[0016] The mass spectrometry conditions were as follows: Positive ion mode: heater temperature 350℃, capillary temperature 330℃, sheath gas flow rate 40 arb, auxiliary gas flow rate 15 arb, purge gas flow rate 1 arb, electrospray voltage 3.5 kV, S-Lens RF Level 50%; Negative ion mode: heater temperature 350℃, capillary temperature 330℃, sheath gas flow rate 45 arb, auxiliary gas flow rate 15 arb, purge gas flow rate 1 arb, electrospray voltage 3.2 kV, S-Lens RF Level 50%; Scanning modes: Level 1 full scan: m / z 80–1200; Data-dependent Level 2 mass spectrometry scan: dd-MS2, Top N = 3; Resolution: Full MS 70,000, dd-MS2 13,500; Collision mode: high-energy collision dissociation, collision voltage: 10 V, 25 V, 40 V.

[0017] Preferably, the amount of methanol used is 200 μL of methanol added for every 50 μL of serum.

[0018] Preferably, the vortex duration is 1 minute.

[0019] Preferably, the column temperature is 35°C.

[0020] Preferably, the injection volume for UPLC detection is 3 μL.

[0021] Preferably, the rodent model is a mouse model.

[0022] The purpose of reagents containing a biomarker set in the preparation of a diagnostic kit for distinguishing between two subtypes of gouty rheumatism (rheumatism predominantly due to heat) and (heat predominantly due to dampness) and / or for determining the success of modeling these two subtypes, wherein the animal model is a rodent model, and the biomarker set includes the following six biomarkers: lauroylcarnitine, taurine, palmitoyl-L-carnitine, L-leucine, leukotriene A4, and 13-Oxo-9,11-tridecadienoic acid.

[0023] Preferably, the reagent is selected from rodent serum and / or artificially prepared solutions containing the biomarker.

[0024] That is, the reagent can be a synthetic compound or a substance isolated from animal serum.

[0025] The purpose of the reagent for detecting the biomarker set in the preparation of a detection kit for distinguishing between gouty dampness-predominant and heat-predominant models and / or determining the success of gouty dampness-predominant and heat-predominant models, is characterized in that the animal model is a rodent model, and the biomarker set includes the following 6 biomarkers: lauroylcarnitine, taurine, palmitoyl-L-carnitine, L-leucine, leukotriene A4, and 13-Oxo-9,11-tridecadienoic acid.

[0026] The beneficial effects of this invention are:

[0027] This invention establishes a novel UPLC-MS method that can be used to simultaneously detect six serum biomarkers and more than 40 other differentially expressed serum biomarkers for distinguishing between animal models of gout with dampness predominantly over heat and those with heat predominantly over dampness, and / or for determining the success of establishing these two animal models.

[0028] This invention discovers that the six serum biomarkers obtained can effectively distinguish between animal models of gouty dampness predominantly presenting as heat and those predominantly presenting as heat, and can also effectively determine whether the gouty dampness predominantly presenting as heat and those predominantly presenting as heat have been successfully established. This provides a simple, effective, and objective new method for the dialectical classification of animal models and the judgment of model establishment results. It overcomes the shortcomings of traditional methods based on animal coat color, behavior, urination and defecation, and pathological methods, which require insufficient professional personnel, lack objectivity in judgment, and may result in animal mortality. Attached Figure Description

[0029] Figure 1 A comparison of the general condition of mice in each group;

[0030] Figure 2 Comparison of ankle swelling in mice of different groups;

[0031] Figure 3 Comparison of serum uric acid, creatinine, and blood lipid levels in mice of different groups;

[0032] Figure 4 Comparison of pathological changes in the ankle joint and liver of mice in each group;

[0033] Figure 5 Comparison of pathological changes in the kidneys and small intestines of mice in different groups;

[0034] Figure 6 Comparison of immunofluorescence detection results of NLRP3, IL-6, and IL-1β in ankle joint tissues of mice in different groups;

[0035] Figure 7 This is a chromatogram of serum metabolomics from normal control mice under positive ion mode;

[0036] Figure 8 The chromatogram of serum metabolomics from mice in the wet weight-to-heat group under positive ion mode;

[0037] Figure 9 The chromatogram of serum metabolomics from mice in the thermogravimetric-humidity group under positive ion mode;

[0038] Figure 10 This is a chromatogram of serum metabolomics from mice in the normal control group under negative ion mode.

[0039] Figure 11 The chromatogram of serum metabolomics of mice in the wet weight-to-heat group under negative ion mode;

[0040] Figure 12 The image shows the serum metabolomics chromatogram of mice in the heat-gravity-humidity group under negative ion mode. Detailed Implementation

[0041] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the present invention.

[0042] The main instruments and reagents used in this invention, including their sources and models, are as follows: Dionex TM Ultimate TM RSLC3000 liquid chromatograph (Thermo Scientific); Q-Exactive-Focus-Orbitrap mass spectrometer (Thermo Scientific); Progenesis QI software (Waters). Customized high-fat diet (Guangdong Provincial Medical Laboratory Animal Center, composition: 80% ordinary feed, 12% lard, 8% honey); hypoxanthine (Aladdin); potassium oxonate, sodium urate (MSU) (Sigma); high-density lipoprotein cholesterol (HDL-C) test kit, low-density lipoprotein cholesterol (LDL-C) test kit, total cholesterol (TC) test kit, triglyceride (TG) test kit, uric acid test kit, creatinine test kit, xanthine oxidase (XOD) test kit (Nanjing Jiancheng); NLRP3 antibody, IL-6 antibody, IL-1β antibody (Saiwell).

[0043] Example 1: Modeling Method, Model Evaluation, Data Processing, and Statistical Analysis Method

[0044] 1. Construction of animal models

[0045] 1.1 Solution and Preparation

[0046] Preparation of 12.5% ​​ethanol solution: Take anhydrous ethanol and pure water to prepare a solution with an ethanol volume percentage of 12.5%.

[0047] Preparation of 0.013 g / mL dried ginger aqueous solution: Take 50.0 g of raw dried ginger, soak it in 500 mL of distilled water for 1 hour, bring it to a boil over high heat, then simmer over low heat for 1 hour. Filter the solution through gauze and place the filtrate in a beaker. Add 10 times the volume of distilled water and repeat the above process twice. Combine the three filtrates and concentrate them under reduced pressure to 500 mL. Store at -80℃. When needed, thaw 15.6 mL of the concentrate and dilute it with 104.4 mL of distilled water to prepare a dried ginger aqueous solution with a concentration of 0.013 g / mL.

[0048] Hypoxanthine gavage solution: Hypoxanthine was dissolved in 0.5% sodium carboxymethyl cellulose solution to prepare a hypoxanthine gavage solution with a concentration of 30 mg / mL.

[0049] Potassium oxazine injection: Dissolve potassium oxazine in physiological saline to prepare an injection solution with a concentration of 15 mg / mL.

[0050] MSU crystal suspension: Dissolve MSU in 1 mol / L NaOH, add sterile 0.9% sodium chloride solution, boil and stir until dissolved, cool, adjust the pH to 7.2 with 1 mol / L HCl, transfer the supernatant to a volumetric flask, and incubate overnight at room temperature. Centrifuge, dry the precipitate at 70℃, grind to obtain MSU crystals, and prepare a 60 mg / mL MSU crystal suspension with 0.9% sodium chloride solution.

[0051] 1.2 Laboratory Animals

[0052] SPF-grade male C57BL / 6 mice, weighing 18–22g and aged 7–8 weeks, were provided by Guangdong Sijiajingda Biotechnology Co., Ltd. They were acclimatized for one week with free access to water and food, following a 12-hour diurnal cycle.

[0053] 1.3 Grouping and Modeling

[0054] Mice were randomly divided into 3 groups. The conventional TCM animal modeling method was used, and the model was established according to the factors in Table 1. High-fat diet, ethanol, dried ginger, and climate chamber were the modeling factors for damp-heat syndrome. High-fat diet and ethanol emphasized dampness, while dried ginger and climate chamber emphasized heat.

[0055] Table 1. Modeling factors for each group in the subtype model of gouty rheumatic fever syndrome

[0056] Grouping High fat ethanol Dried ginger Climate Box hypoxanthine Potassium oxazine MSU normal - - - - - - - Dampness is more important than heat √ √ - - √ √ √ Heat is more important than humidity √ √ √ √ √ √ √

[0057] Normal control group: Mice were administered 0.5% CMC-Na solution (0.1 mL / 10 g) by gavage daily in the morning, and intraperitoneally injected with physiological saline (0.2 mL / 10 g). On day 28, mice were injected with 25 μL of 0.9% sodium chloride solution into the right hind leg ankle joint, and samples were collected 48 hours later. During the experiment, mice were fed a normal diet and had free access to water.

[0058] Model 1 (wet weight over heat group): Mice were administered 30 mg / mL hypoxanthine (0.1 mL / 10 g) by gavage in the morning and 15 mg / mL potassium oxonate (0.2 mL / 10 g) by intraperitoneal injection daily. In the afternoon, they were administered 12.5% ​​ethanol solution (0.1 mL / 10 g) by gavage. On day 28, 25 μL of 60 mg / mL MSU crystal suspension was injected into the right hind limb ankle joint of the mice, and samples were collected 48 hours later. During the experiment, mice in this group were fed a high-fat diet and had free access to water.

[0059] Model Group 2 (thermogravimetric group): Mice were administered 30 mg / mL hypoxanthine (0.1 mL / 10 g) by gavage and 15 mg / mL potassium oxonate (0.2 mL / 10 g) by intraperitoneal injection every morning. The mice were placed in an artificial climate chamber at a temperature of (32 ± 2℃) and humidity of (95% ± 2%) for 6 hours daily. In the afternoon, the mice were removed from the climate chamber and administered 12.5% ​​ethanol aqueous solution (0.1 mL / 10 g) and 0.013 g / mL dried ginger aqueous solution (0.1 mL / 10 g) by gavage. On day 28, 25 μL of 60 mg / mL MSU crystal suspension was injected into the right hind limb ankle joint of the mice, and samples were collected 48 hours later. During the experiment, the mice in this group were fed a high-fat diet and had free access to water.

[0060] 2. Sample Collection and Processing

[0061] On day 31 of the experiment, mice were anesthetized with sodium pentobarbital, and blood samples were collected from the eyeballs. After standing for 1 hour, the samples were centrifuged at 4000 rpm for 10 minutes at 4°C, and the supernatant (serum) was collected and stored at -80°C. Liver, kidney, small intestine, and ankle joint tissues were collected from the mice, and some were fixed with paraformaldehyde for HE staining. Some samples of liver, kidney, and small intestine tissues were embedded in OCT and stored at -80°C, while the remaining samples were stored at -80°C.

[0062] 3. Evaluation of animal models

[0063] 3.1 Evaluation of Macroeconomic Indicators

[0064] On day 30 of the experiment, the mice were observed for their overall demeanor, willingness to move, group behavior, fur condition, bowel and bladder function, weight, abdominal circumference, rectal temperature, 12-hour urine output, and average daily food and water intake over the past two weeks.

[0065] On day 28 of the experiment, after injection of MSU crystal suspension, the diameter of the right posterior ankle joint of mice was measured using electronic vernier calipers at 0, 12, 24, and 48 hours after injection, and the ankle joint swelling degree was calculated [(ankle joint diameter after modeling - ankle joint diameter before modeling) / ankle joint diameter before modeling]. A swelling curve from 0 to 48 hours was plotted based on the ankle joint swelling degree, and the area under the curve was calculated.

[0066] 3.2 Evaluation of Biochemical Indicators

[0067] Serum samples were collected, and the levels of TG, TC, HDL-C, LDL-C, creatinine, and uric acid in the serum of mice in different groups were detected using a kit. Serum samples were collected, and the levels of uric acid and creatinine in the serum of mice in each group were detected using a kit. The uric acid excretion fraction was calculated based on the serum uric acid and creatinine results [uric acid excretion fraction = urinary uric acid × serum creatinine / (serum uric acid × urinary creatinine)].

[0068] 3.3 Histopathological evaluation

[0069] Well-fixed liver, kidney, small intestine, and ankle joint tissues were routinely prepared into pathological sections and stained with hematoxylin and eosin (HE). The tissue sections were then examined in detail under a microscope at different magnifications. Basic pathological changes in the sections, such as congestion, ecchymosis, hemorrhage, edema, degeneration, necrosis, hyperplasia, fibrosis, organization, granulation tissue, and inflammatory changes, were observed. Pathological changes in selected tissues were scored, and the scoring criteria are shown in Table 2. Typical lesion sites were marked with arrows.

[0070] Table 2 Histopathological Scoring Criteria

[0071]

[0072] 3.4 Evaluation of ankle joint tissue inflammation

[0073] Ankle joint tissue was collected and paraffin sections were prepared. Immunofluorescence was used to measure the changes in the content of NLRP3, IL-6, and IL-1β in the ankle joint tissue sections. The results were expressed as positive cell density (number of positive cells / area of ​​tissue to be tested).

[0074] 3.5 Evaluation of Damp-Heat Syndrome

[0075] Referring to the "Evaluation Table of Animal (Mouse and Frog) Models of Dampness Syndrome in Traditional Chinese Medicine" and the "Guidelines for the Diagnosis and Treatment of Hyperuricemia and Gout Syndrome (2021-01-20)" and related research on damp-heat syndrome gout, the evaluation of damp-heat syndrome is divided into two parts: dampness syndrome score and heat syndrome score.

[0076] The dampness syndrome scoring includes: overall demeanor, group behavior, weight gain, abdominal circumference increase, elevated serum triglycerides (TG), elevated serum total cholesterol (TC), elevated serum uric acid, elevated serum creatinine, liver pathological damage, kidney pathological damage, and small intestine pathological damage. Overall demeanor and group behavior are scored based on the degree of abnormality (from low to high, 1-4 points). Other indicators are scored based on statistical significance: compared with the normal group, a trend-following result with p<0.05 earns 1 point, a trend-following result with p<0.01 earns 2 points, a trend-following result with p<0.001 earns 3 points, and a trend-following result with p<0.0001 earns 4 points.

[0077] The heat syndrome score includes: gait abnormalities, weight loss, increased joint swelling, elevated rectal temperature, decreased urine output, decreased food intake, increased water intake, pathological damage to the ankle joint, elevated ankle NLRP3, elevated ankle IL-6, and elevated ankle IL-1β. Gait analysis is scored according to the degree of abnormality (1-4 points from low to high). Other indicators are scored based on the significance of differences. Compared with the normal group, 1 point is awarded for conforming to the trend and p<0.05, 2 points for conforming to the trend and p<0.01, 3 points for conforming to the trend and p<0.001, and 4 points for conforming to the trend and p<0.0001.

[0078] The dampness and heat syndrome scores were combined to evaluate whether the gout-damp-heat syndrome model was successfully constructed. The dampness and heat syndrome scores were used to compare whether the two model groups (dampness predominantly in the heat group and heat predominantly in the dampness group) were successfully constructed.

[0079] 3.6 Serum metabolomics analysis

[0080] 3.6.1 Preparation and optimization of serum samples

[0081] Take 50 μL of serum sample, add 200 μL of methanol, vortex for 1 min, let stand for 20 min, centrifuge at 13000 rpm for 15 min at 4℃, and filter the supernatant through a 0.22 μm filter membrane for UPLC-MS analysis.

[0082] 3.6.2 Analysis Conditions

[0083] (1) Chromatographic conditions: ACQUITY UPLC TM HSS T3 column (2.1 mm x 100 mm, 1.8 μm) (Waters Corporation, USA); mobile phase A: acetonitrile, mobile phase B: 0.1% formic acid in water; column temperature: 35 °C; flow rate: 0.3 mL / min; injection volume: 3 μL; gradient elution program as follows:

[0084] Table 3 Gradient elution program

[0085]

[0086] (2) Mass spectrometry conditions: Positive ion mode: heater temperature 350℃; capillary temperature: 330℃; sheath gas flow rate: 40arb; auxiliary gas flow rate: 15arb; purge gas flow rate: 1arb; electrospray voltage: 3.5KV; S-Lens RF Level: 50%. Negative ion mode: heater temperature 350℃; capillary temperature: 330℃; sheath gas flow rate: 45arb; auxiliary gas flow rate: 15arb; purge gas flow rate: 1arb; electrospray voltage: 3.2KV; S-Lens RF Level: 50%. Scanning modes: full scan (m / z 80~1200) and data-dependent secondary mass spectrometry scan (dd-MS2, Top N=3); resolution: 70,000 (Full MS) & 13,500 (dd-MS2). Collision mode: High-energy collision dissociation (HCD), collision voltage (NCE): 10V, 25V, 40V.

[0087] 3.6.3 Data Processing

[0088] The obtained metabolic profile data were imported into the Progenesis QI software processing system for analysis, and data preprocessing was performed, including peak alignment, peak extraction, data normalization, and deconvolution analysis. Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discrimination Analysis (OPLS-DA) were performed using EZinfo 3.0 software. Ions with VIP>1 and p<0.05 in the t-test were considered potential biomarkers for further analysis. Element composition analysis was used to determine the possible molecular formula. Using precise mass, possible molecular formula, and MS / MS data as clues, databases and literature such as the Human Metabolome Database (HMDB, http: / / www.hmdb.ca) and Lipidomics Gatewa (http: / / www.lipidmaps.org / ) were searched. Based on the probability of chemical structure fragmentation and the fragmentation pattern of biomass spectrometry, biomarkers were characterized, and pathway analysis was performed using the MetaboAnalyst 3.0 network tool.

[0089] 3.7 Statistical Analysis

[0090] Experimental data were analyzed using IBM SPSS Statistics 25 software. Normally distributed continuous data were analyzed using one-way ANOVA. When variances were homogeneous, the LSD test was used for pairwise comparisons between groups; when variances were not homogeneous, Dunnett's T3 test was used. Continuous data were expressed as mean ± standard deviation. For non-normally distributed continuous and ordinal data, the Kruskal-Wallis test was used for nonparametric analysis, and the Mann-Whitney U test was used for pairwise comparisons between groups. Data were expressed as median and interquartile range. Results were considered statistically significant with p < 0.05.

[0091] Example 2: Screening of metabolomics biomarkers for subtype differentiation of gout and damp-heat syndrome model

[0092] In this study, an animal model was established according to the method in Example 1. After the model was successfully constructed, conventional evaluation methods were used to determine the marker groups used to distinguish between the two subtypes of wet weight over heat and heat weight over wet.

[0093] 1. Macroeconomic Indicators

[0094] 1.1 General Characteristic Changes

[0095] On day 30 of the experiment, compared with the normal group, the model group mice were generally lethargic and huddled together. The wet weight over heat group was generally worse in appearance than the heat weight over wet group, and their huddling behavior was more pronounced. The weight of mice in the normal control group remained stable, and there was no significant difference in weight between the wet weight over heat group, the heat weight over wet group, and the normal group (see...). Figure 1 A). On day 30 of the experiment, the abdominal circumference of mice in the wet weight-to-heat and heat weight-to-wet groups was significantly larger than that in the normal group (p<0.001, p<0.01, respectively) (see...). Figure 1 B); The rectal temperature of mice in the wet weight-more-heat and heat weight-more-wet groups was significantly higher than that in the normal group (p<0.05, p<0.01, respectively) (see B). Figure 1 C); The urine output of mice in the wet weight-more-heat and heat weight-more-humidity groups was significantly lower than that in the normal group (p<0.05) (see Figure 1 D); The daily food intake of mice in the heat-weight-over-humidity group was significantly lower than that in the normal group (p<0.001) (see D); Figure 1 E); The daily water intake of mice in the heat-weight-over-humidity group was significantly higher than that in the normal group (p<0.0001) (see Figure 1 F).

[0096] 1.2 Ankle swelling

[0097] On day 28 of the experiment, after injection of MSU suspension, mice in both the wet-weight-more-heat and heat-weight-more-wet groups showed varying degrees of ankle swelling (see...). Figure 2A). Swelling of the ankle joint at 0, 12, 24, and 48 hours after injection of MSU suspension was measured using vernier calipers. The swelling index was calculated, and a line graph was plotted to calculate the area under the curve. The results showed that compared with the normal group, the wet group had greater swelling than the hot group, and the hot group had greater swelling than the wet group (p<0.0001).

[0098] 2 Biochemical indicators

[0099] Serum biochemical marker test results (see) Figure 3 The serum uric acid levels in mice in the wet-weight-more-heat and heat-weight-more-humidity groups were significantly higher than those in the normal group (p<0.0001, p<0.01); the serum TG levels in the heat-weight-more-humidity group were significantly higher than those in the normal group (p<0.05); the serum TC levels in the wet-weight-more-heat and heat-weight-more-humidity groups were significantly higher than those in the normal group (p<0.0001, p<0.001); the serum HDL-C levels in the wet-weight-more-heat and heat-weight-more-humidity groups were significantly higher than those in the normal group (p<0.05); and the serum LDL-C levels in the wet-weight-more-heat and heat-weight-more-humidity groups were significantly higher than those in the normal group (p<0.0001).

[0100] 3. Evaluation results of histopathological changes

[0101] 3.1 Pathological changes and scores of ankle joint and liver

[0102] The results of HE staining of the ankle joint showed (see) Figure 4 A) In the normal group, the ankle joint structure was clear and uniformly stained. The tibial and talar cartilage surfaces were smooth, the chondrocyte morphology and structure were normal, and no obvious bone erosion was observed. No obvious proliferation or inflammatory cell infiltration was observed in the synovial membranes on both sides. In the wet-heavy group, there was mild proliferation of synovial cells, with a large number of necrosis and shedding of synovial cells, pyknosis, deep staining, and fragmentation of cell nuclei, and few cell fragments were observed in the joint cavity. Basophilic masses were rarely seen in the synovial connective tissue, and a large number of granulocytes and macrophages were observed infiltrating. In the heat-heavy group, a small number of synovial cells in the ankle joint were necrosis and shedding, with pyknosis, deep staining, and fragmentation of cell nuclei, and few cell fragments were observed in the joint cavity. Basophilic masses were observed locally in the tibial periosteum, with a small number of granulocytes and macrophages infiltrating around them. The pathological scoring results of the ankle joint showed that the scores of the wet-heavy group and the heat-heavy group were significantly higher than those of the normal group (p<0.05, p<0.01).

[0103] The results of liver HE staining showed (see) Figure 4B) In the normal group, the liver tissue showed a clear capsule structure with no obvious hyperplasia; the lobule boundaries were indistinct, with a central vein in the center of each lobule surrounded by hepatocytes and sinusoids arranged in a roughly radial pattern; the hepatocytes were round and plump; there was no obvious dilation or compression of the sinusoids; the portal areas showed no obvious abnormalities; and no obvious necrosis or inflammatory cell infiltration was observed. In the wet-more-hot group, a small number of hepatocytes showed watery degeneration, with loose and pale cytoplasm. In the heat-more-wet group, a small number of hepatocytes showed watery degeneration, with loose and pale cytoplasm. Liver pathological scoring results showed that the scores of the wet-more-hot group and the heat-more-wet group were significantly higher than those of the normal group (p<0.01, p<0.05).

[0104] 3.2 Pathological changes and scores of kidney and small intestine tissues

[0105] HE staining results of kidney tissue (see) Figure 5 A) In the normal control group, the kidney tissue surface capsule was composed of dense connective tissue of uniform thickness. Glomeruli were evenly distributed in the cortex, with uniform cell number and matrix within the glomeruli. The tubular epithelial cells were round and plump, with neat and regular brush borders, and no obvious abnormalities were observed in the medulla. The connective tissue between the urinary tubules was the renal interstitium, with no obvious interstitial proliferation. No obvious necrosis or inflammatory cell infiltration was observed. In the wet-weight-over-heat group, a small number of tubular epithelial cells in the kidney tissue showed hydropic degeneration, cell swelling, and loose, pale cytoplasm. In the heat-weight-over-humidity group, a small number of tubular epithelial cells showed hydropic degeneration, cell swelling, and loose, pale cytoplasm. Occasionally, dilated tubules were observed at the local margins, with flattened epithelium, increased lumen volume, and irregular shape. Eosinophilic material was visible within the lumen, and a small amount of mild connective tissue proliferation was observed around the tubules, accompanied by a small amount of lymphocyte infiltration. The kidney pathological scoring results showed that the kidney pathological damage in the wet-weight-over-heat group was significantly higher than that in the normal group (p<0.01).

[0106] HE staining results of small intestinal tissue (see...) Figure 5 B) In the normal group, the intestinal tissue surface was covered with intestinal villi, and the surface was composed of a single layer of columnar epithelium with normal morphology and structure. Goblet cells were distributed between the epithelial cells. The submucosa was composed of connective tissue. The remaining part of the intestinal wall, including the muscular layer composed of smooth muscle cells and the serosa, showed no obvious abnormalities. In the wet-weight-than-heat group, the intestinal tissue surface was covered with intestinal villi, which were short and the surface was composed of a single layer of columnar epithelium. More mucosal epithelial cells were shed, exposing the lamina propria. In the heat-weight-than-wet group, a large amount of mucosal epithelial cells were shed, exposing the lamina propria; the local mucosal structure was unclear, and a small amount of eosinophilic flocculent material was visible. The pathological scoring results of the small intestine tissue showed no significant difference in pathological damage between the wet-weight-than-heat and heat-weight-than-wet groups and the normal group.

[0107] 4. Evaluation results of ankle joint tissue inflammation

[0108] The levels of NLRP3, IL-6, and IL-1β, inflammatory markers, in ankle joint tissue were detected by immunofluorescence assay of paraffin sections. Results showed (see...) Figure 6 The levels of NLRP3, IL-6, and IL-1β were lower in the normal group, but increased in all model groups. The results of positive cell density for each indicator showed that, compared with the normal group, the density of NLRP3 positive cells was significantly increased in the wet-weight-over-heat and heat-weight-over-wet groups (p<0.05); the density of IL-6 positive cells was significantly increased in the wet-weight-over-heat and heat-weight-over-wet groups (p<0.01, p<0.05); and the density of IL-1β positive cells was significantly increased in the wet-weight-over-heat and heat-weight-over-wet groups (p<0.001, p<0.0001).

[0109] 5. Evaluation of Damp-Heat Syndrome (Evaluation of Dampness Syndrome, Evaluation of Heat Syndrome

[0110] The results of serum and pathological analysis of dampness syndrome scoring showed that the scores of the dampness-predominant-heat group and the heat-predominant-dampness group were higher than those of the normal group (see Tables 4 to 6). Furthermore, the dampness syndrome score of the dampness-predominant-heat group was significantly higher than that of the other two groups (p<0.05); the heat syndrome score of the heat-predominant-dampness group was significantly higher than that of the other two groups (p<0.05). All models were successfully constructed.

[0111] Table 4 Scoring Table for Dampness Syndrome Elements in Each Group

[0112]

[0113] Table 5 Scoring Table for Heat Syndrome Elements in Each Group

[0114]

[0115] Table 6 Scores of Damp-Heat Syndrome for Each Group (Dampness Syndrome Score + Heat Syndrome Score)

[0116] Grouping Dampness syndrome scoring Heat syndrome score Total (Damp-Heat Syndrome Score) normal 0 0 0 Dampness is more important than heat 26 13 39 Heat is more important than humidity 12 27 39

[0117] 6. Results of metabolomics experiments

[0118] Serum metabolomics chromatograms of control and model mice under positive and negative ion modes are as follows: Figure 7-12 As shown. Figure 7-9 Serum metabolomics chromatograms of the control group, wet weight-more-heat group, and heat weight-more-wet group under positive ion mode. Figure 10-12 Serum metabolomics chromatograms of the control group, wet weight greater than heat group, and heat weight greater than wet group under negative ion mode.

[0119] Serum metabolic profile data were imported into Progenesis QI for data preprocessing. Multivariate statistical analyses (PCA and OPLA-DA) were performed on each model group and control group. The results showed that there was a significant separation between the two model groups and the control group, and the metabolic profile data of the model group showed significant changes.

[0120] PCA and OPLS-DA analyses of the wet weight-to-heat group and the control group showed significant clustering and separation between the two groups. Comparison of the levels of indicators used to evaluate wet weight-to-heat revealed significant differences in 39 metabolites, including uric acid, prostaglandin E2, and leukotriene A4, compared to the normal group (see Table 7).

[0121] Table 7. Identification results of serum differential metabolites in the wet weight vs. heat group.

[0122]

[0123]

[0124]

[0125] PCA and OPLS-DA analyses of the heat-weight-over-humidity group and the control group showed significant clustering and separation between the two groups. Comparison of the levels of indicators used to evaluate heat-weight-over-humidity revealed significant differences in 30 metabolites, including uric acid, prostaglandin E2, and linoleic acid, compared with the normal group (see Table 8).

[0126] Table 8. Identification results of differentially expressed serum metabolites in the thermogravimetric-to-humidity group (30 items)

[0127]

[0128]

[0129] Sixteen differentially expressed metabolites were found between the two groups (Tables 7 and 8), indicating that these 16 differentially expressed metabolic biomarkers may be used to differentiate between the wet-weight-more-heat group, the heat-weight-more-humidity group, and the normal group. Based on this, ROC analysis was used to determine whether these 16 indicators could differentiate between the wet-weight-more-heat and heat-weight-more-humidity groups.

[0130] According to the method of Example 1, 30 SPF-grade C57BL / 6 male mice were taken and randomly divided into three groups: a normal group, a dampness-over-heat gout model group, and a heat-over-dampness gout model group. After determining that the model construction was successful using the conventional evaluation method of Example 1, blood was taken for testing. Numerical normalization was performed by dividing the original index content of each index by the average value of the corresponding normal group. According to the ROC curve, the discrimination ability of the above 16 indexes for the model was judged. Among them, 6 differential metabolic biomarkers, namely Dodecanoylcarnitine, Taurocholic acid, Palmitoylcarnitine, L-Leucine, Leukotriene A4, and 13-Oxo-9,11-tridecadienoic acid, had good discrimination ability for the model. An AUC higher than 0.85 had a good discrimination and judgment effect, and the sensitivity and 1-specificity met the requirements. For example, AUC = 0.5 was equivalent to judging by randomly flipping a coin; 0.5 < AUC < 0.7 had a poor effect, and the sensitivity and 1-specificity did not meet the requirements; 0.7 < AUC < 0.85 had a discrimination and judgment effect that was not as accurate as traditional Chinese medicine syndromes. Therefore, the discrimination ability of the 6 indexes combined as a biomarker group was investigated. At this time, the AUC was all 1, and the sensitivity and 1-specificity were greatly improved, reaching and exceeding the usage requirements of ordinary discrimination ability. The results are shown in Table 9.

[0131] Table 9 AUC of individual and combined diagnosis of six key indexes

[0132]

[0133] The Cut-off value corresponding to each index was obtained using the ROC curve. The results are shown in Table 10. The numerical range for the differential metabolic biomarker to distinguish different subtypes can be obtained through the Cut-off value (see Table 11).

[0134] Table 10 Cut-off values corresponding to six key indexes

[0135]

[0136] Table 11 Diagnostic ranges corresponding to six key indexes

[0137] name Moisture is heavier than heat Heat is more important than humidity Dodecanoylcarnitine >1.4330 1.4330>X>1.1361 Taurocholic acid >1.4463 1.4463>X>1.2556 Palmitoylcarnitine >1.5429 1.5429>X>0.9739 L-Leucine <0.8317 >0.8317 13-Oxo-9,11-tridecadienoic acid 1.3379>X>1.1770 >1.3379 Leukotriene A4 >2.8835 2.8835>X>1.8198

[0138] Example 3 Using the biomarker group to judge whether the dampness-over-heat and heat-over-dampness gout models are successfully constructed

[0139] Two gout models of damp-heat syndrome, one with dampness predominantly over heat and the other with heat predominantly over dampness, were induced using the method described in Example 1. The modeling success was assessed using the judgment method outlined in "5. Evaluation of Damp-Heat Syndrome (Evaluation of Dampness Syndrome and Evaluation of Heat Syndrome)" and the detection and data processing method outlined in "6. Metabolomics Experimental Results," based on the normalized values ​​of six biomarkers. The results are shown in Table 12. The modeling success rate for both the dampness-predominant-heat and heat-predominant-dampness models was 100%. The results from both methods were consistent. The judgment method based on six biomarker groups can evaluate the success of modeling in individual mice and can provide a reference for pharmacological research and new drug development.

[0140] Table 12 Success rate of mouse model in two groups

[0141] Group Mold quantity Unformed quantity Mold formation rate Wet weight is greater than hot weight (n=8) 8 0 100％ Thermogravimetric group (n=8) 8 0 100％

Claims

1. A method for establishing an animal model of a subtype of gouty damp-heat syndrome, comprising inducing gout in animals using hypoxanthine, potassium oxonate, and sodium urate; inducing damp-heat syndrome in animals using high-fat feeding, ethanol feeding, dried ginger, and an artificial climate chamber; and collecting animal blood samples for UPLC-MS analysis and screening; wherein the animal model of the subtype of gouty damp-heat syndrome is a rodent model, characterized in that... The method for establishing an animal model of the gout-damp-heat syndrome subtype further includes the following steps: S1: After the modeling is completed, blood samples are taken from the animals to separate serum. The biomarker group in the serum of normal animals and model animals is analyzed by UPLC-MS. The biomarker group includes: lauroylcarnitine, taurine, palmitoyl-L-carnitine, L-leucine, leukotriene A4, and 13-Oxo-9,11-tridecadienoic acid. S2: Normalize the values ​​of each biomarker by dividing the original index content of the biomarker group in S1 by the average value of the corresponding index in the normal group, and then screen the model animals based on the cutoff value. In step S2, when the required gout model is the wet weight-to-thermal subtype, the normalized values ​​are: lauroylcarnitine > 1.4330, taurine > 1.4463, palmitoyl-L-carnitine > 1.5429, L-leucine < 0.8317, leukotriene A4 > 2.8835, and 13-Oxo-9,11-tridecadienoic acid. A successful model is determined when at least three of the following conditions are met: the normalized value of acid is greater than 1.1770 and less than 1.3379; when the required gout model is the heat-weighted-more-wet subtype, the following conditions must be met: the normalized value of lauroylcarnitine is greater than 1.1361 and less than 1.4330; the normalized value of taurine is greater than 1.2556 and less than 1.4463; the normalized value of palmitoyl-L-carnitine is greater than 0.9739 and less than 1.5429; the normalized value of L-leucine is greater than 0.8317; the normalized value of leukotriene A4 is greater than 1.8198 and less than 2.8835; and the normalized value of 13-Oxo-9,11-tridecadienoic acid is greater than 1.3379.

2. The method for establishing an animal model of a subtype of gout and damp-heat syndrome according to claim 1, characterized in that, The UPLC-MS method includes the following steps: J1. Take animal blood samples to separate serum, add methanol, vortex for 0.5 min ~ 1.5 min, centrifuge, and filter the supernatant through a 0.22 µm filter membrane to obtain the sample processing solution to be tested; J2. Take the sample solution from step S1 and perform UPLC-MS analysis: UPLC chromatographic conditions: ACQUITY UPLC HSS T3 column; column size 2.1 mm x 100 mm, particle size 1.8 µm; mobile phase A: acetonitrile, mobile phase B: 0.1% formic acid in water; column temperature: 30℃~35℃; flow rate: 0.3 mL / min; gradient elution program as follows: ； The mass spectrometry conditions were as follows: Positive ion mode: heater temperature 350°C, capillary temperature 330°C, sheath gas flow rate 40 arb, auxiliary gas flow rate 15 arb, purge gas flow rate 1 arb, electrospray voltage 3.5 kV, S-Lens RF Level 50%; Negative ion mode: heater temperature 350°C, capillary temperature 330°C, sheath gas flow rate 45 arb, auxiliary gas flow rate 15 arb, purge gas flow rate 1 arb, electrospray voltage 3.2 kV, S-Lens RF Level 50%; Scanning modes: Level 1 full scan: m / z 80~1200, data-dependent Level 2 mass spectrometry scan: dd-MS2, TopN=3, resolution: Full MS 70,000, dd-MS2 13,500, collision mode: high-energy collision dissociation, collision voltage: 10V, 25V, 40V.

3. The method for establishing an animal model of a subtype of gout-damp-heat syndrome according to claim 2, characterized in that, In step J1, the amount of methanol used is 200µL of methanol added for every 50µL of serum.

4. The use of reagents containing a group of biomarkers in the preparation of a diagnostic kit for distinguishing between gouty rheumatism-predominant and heat-predominant models and / or determining the success of gouty rheumatism-predominant and heat-predominant models, characterized in that, The animal model is an animal model obtained by the method for establishing a subtype of gout and damp-heat syndrome according to claim 1. The biomarker group includes the following 6 biomarkers: lauroylcarnitine, taurine, palmitoyl-L-carnitine, L-leucine, leukotriene A4, and 13-Oxo-9,11-tridecadienoic acid.

5. The use of reagents for detecting biomarker groups in the preparation of a detection kit for differentiating between gouty rheumatism-predominant and heat-predominant models and / or determining the success of gouty rheumatism-predominant and heat-predominant models, characterized in that, The animal model is an animal model obtained by the method for establishing a subtype of gout and damp-heat syndrome according to claim 1. The biomarker group includes the following 6 biomarkers: lauroylcarnitine, taurine, palmitoyl-L-carnitine, L-leucine, leukotriene A4, and 13-Oxo-9,11-tridecadienoic acid.

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