A liver metabolomics method for screening biomarkers in dysmenorrhea model mice

Abstract

The present invention discloses a liver metabolomics method for screening biomarkers of dysmenorrhea model mice, which relates to the field of traditional Chinese medicine research. The present invention uses metabolomics methods to analyze the liver samples of estradiol-induced dysmenorrhea mice, blank control group mice, and traditional Chinese medicine Angelica sinensis-Ligusticum wallichii treatment group mice. Based on 1H NMR metabolomics technology, spectral information is collected, liver metabolites are identified, and significantly different biomarkers are screened through statistical analysis methods. A total of 23 biomarkers with the effect of treating dysmenorrhea are found, and the metabolic pathways involved are analyzed by the online analysis software Metaboanalyst. Angelica sinensis-Ligusticum wallichii has a callback effect on the above-mentioned biomarkers, so as to realize the identification and high-throughput analysis of the mechanism of action of Angelica sinensis-Ligusticum wallichii in treating dysmenorrhea, comprehensively evaluate the mechanism of action of Angelica sinensis-Ligusticum wallichii in treating dysmenorrhea at the overall level, and provide a demonstration study for the elucidation of traditional Chinese medicine metabolomics and its mechanism of action.

Description

Technical Field

[0001] The present invention relates to the field of traditional Chinese medicine research, and in particular to a liver metabolomics method for screening biomarkers of dysmenorrhea model mice. Background Art

[0002] Dysmenorrhea is a common gynecological disease in all women regardless of age and race. When studies on the prevalence of dysmenorrhea are examined, the reported incidence rate is between 45.3% and 90%. This seriously affects the study, work and life of women of childbearing age. Women with dysmenorrhea are generally irritable. Among women around the world, there are always one or more days of absence from work due to dysmenorrhea. Clinically, dysmenorrhea is believed to be caused by excessive contraction of uterine smooth muscle, resulting in insufficient blood supply to the uterus, accompanied by abdominal cramps, and even worse, low back pain, headache and gastrointestinal symptoms. Dysmenorrhea recurs cyclically with the menstrual period and there is no identifiable pathological change in the reproductive system. Although nonsteroidal anti-inflammatory drugs (NSAIDs) are currently the first-line drugs for the treatment of dysmenorrhea, they are effective, but the inefficiency rate can reach 20-30%. Therefore, there is an urgent need to find more effective treatment drugs without side effects.

[0003] Traditional Chinese medicine believes that dysmenorrhea is caused by Chong and Ren meridians and the uterus. The main causes and mechanisms are depression, cold drinking, etc., which lead to poor circulation of qi and blood, qi blockage, and pain due to poor circulation or deficiency of qi and blood in the body, and malnutrition of the uterus. Dysmenorrhea is a disease, and pain relief is the symptomatic treatment, while pain conditioning is the root cause. Therefore, the most important thing to remove blood stasis is to promote qi circulation, and the most important thing to promote qi circulation is to soothe the liver. Traditional Chinese medicine theory believes that the normal function of the liver plays a leading role in the occurrence of female gynecological diseases, especially the liver's function of regulating qi circulation has important guiding significance for the treatment of primary dysmenorrhea. As stated in "Yi Ji", "If you are depressed, you will not feel comfortable, which is a disease of the liver wood". From the above theoretical analysis, whether menstrual blood is normal depends on whether the liver's function of regulating qi circulation is normal. "Danggui-Yi Mucao" originally originated from Yi Mu Wan recorded in "Zhulin Temple Women's Secret Recipe", which is a traditional ancient recipe for treating gynecological diseases and has the effect of treating qi stagnation and blood stasis. Motherwort is the main medicine and Angelica sinensis is the auxiliary medicine. Pharmacological studies have shown that Motherwort has the effects of anti-myocardial ischemia, anti-thrombosis and regulating uterine smooth muscle, while Angelica sinensis has the effects of regulating uterine smooth muscle, enhancing immunity, anti-arrhythmia, and anti-platelet aggregation. The combination of the two has the effect of treating qi stagnation and blood stasis syndrome.

[0004] Metabolomics is a comprehensive analysis of metabolites in biological samples (such as cells, body fluids, tissues, exhaled air, plants), and is widely used in disease diagnosis, drug development, biological function research, etc. It is of far-reaching significance to reveal the efficacy of traditional Chinese medicine through metabolomics combined with pattern recognition analysis.

[0005] However, so far, there has been no report on the use of metabolomics methods to study the effect of Angelica sinensis - Leonurus japonicus on treating dysmenorrhea. Therefore, it is necessary to develop a research method for the mechanism of action of treating dysmenorrhea based on liver metabolomics. Summary of the Invention

[0006] The purpose of the present invention is to provide a liver metabolomics method for screening biomarkers in dysmenorrhea model mice, perform metabolomics data analysis on samples, and search for specific biomarkers with the effect of treating dysmenorrhea (P < 0.05).

[0007] The technical solution adopted by the present invention is: using 1 1H NMR technology to detect liver samples and analyze the data. Specifically, it includes the following steps:

[0008] (1) Experimental grouping: Divide the mice into an estradiol model group, a blank control group, and a traditional Chinese medicine Angelica sinensis - Leonurus japonicus treatment group;

[0009] (2) Collect the serum and liver samples of the mice. The blood samples are used for ELISA analysis, and the liver samples are used for metabolomics analysis;

[0010] (3) Pretreatment of the samples and 1 1H NMR detection;

[0011] (4) Data processing, compare the blank control group with the model group, screen out the biomarkers of the dysmenorrhea model, and compare with the traditional Chinese medicine Angelica sinensis - Leonurus japonicus treatment group to screen out specific biomarkers with the mechanism of action against dysmenorrhea;

[0012] (5) Perform pathway analysis on the specific biomarkers obtained in the above steps through the MetaboAnalyst online analysis software.

[0013] Further, the specific method for animal treatment and sample collection in step (1) is as follows: Fifteen KM mice were randomly divided into two groups, a control group (n = 5) and a model group (n = 10). Oral administration of estradiol benzoate induced dysmenorrhea in mice. The mice in the model group were orally administered estradiol benzoate CMC suspension (2 mg / kg / d) for 10 consecutive days, and the mice in the control group were orally administered an equal volume of normal saline. On the 10th day, the estradiol-treated mice were divided into two groups (5 mice in each group), the model group and the traditional Chinese medicine Angelica sinensis-Ligusticum wallichii treatment group (Drug, dose 12.0 g / kg). The mice in the traditional Chinese medicine Angelica sinensis-Ligusticum wallichii treatment group were given an aqueous solution of Angelica sinensis-Ligusticum wallichii extract every day, and the mice in the model group and the control group were given the same volume of normal saline for 6 consecutive days. At the end of the 16th day, all mice were fasted overnight. On the 17th day, each group of mice was intraperitoneally injected with oxytocin (20 U / kg) 1 hour after the last administration, and the number of writhing responses of the mice within 30 min after injection was recorded. At the end of the drug administration on the 17th day, blood was collected from the abdominal aorta into a vacuum tube, the mice were sacrificed by cervical dislocation, and the skin was wiped with 75% ethanol and then the abdominal cavity was opened. Samples were obtained by cutting the liver tissue.

[0014] Further, the pretreatment method of the samples described in step (2) is as follows: The mouse serum samples were centrifuged at 3000 - 3500 revolutions per minute for 10 minutes, and the supernatant was taken for detection by an enzyme-linked immunosorbent assay reader; The liver samples were homogenized 2 - 3 times in 50% aqueous acetonitrile solution (5 mL / g tissue), and the mixture was ultrasonically treated for 10 min to make it uniformly mixed. Next, it was centrifuged at 4 °C and 12,000 rpm for 10 min. The supernatant was dried under nitrogen. The dried tissue extract was dissolved in 550 μL of D2O containing 0.01% TSP and transferred to a nuclear magnetic resonance tube for NMR analysis.

[0015] Further, the 1 The H NMR detection and analysis conditions are as follows: A Bruker AV III HD 400 MHz spectrometer (frequency 400 MHz) was used, and the experimental temperature was 297 K. Before the test, the instrument needed to be temperature-corrected and shim-corrected. The NOESY pulse sequence was used for analysis. The 90° pulse length was 10 μs, the mixing time tm was 100 ms, the spectral width was 20 ppm, the relaxation time was 2 s, the number of signal accumulations (NS) was 64, and the number of sampling points (TD) was 65536. Before Fourier transform, the FID was weighted using an exponential window function with a line broadening of 0.3 Hz.

[0016] Further, the dysmenorrhea model biomarkers are specifically as follows:

[0017]

[0018] Note: C is the blank control group, M is the model group, and Drug is the treatment group with traditional Chinese medicine Angelica sinensis - Leonurus japonicus. ↑ indicates a relative increase in the signal; ↓ indicates a relative decrease in the signal. * and ** represent statistical differences with P < 0.05 and P < 0.01, respectively.

[0019] Furthermore, the pathway analysis described in step (5) also includes importing 23 biomarkers into the MetaboAnalyst and KEGG databases to construct and analyze disease-related metabolic pathways, obtaining relevant metabolic pathways; the key pathways of Angelica sinensis - Leonurus japonicus in intervening dysmenorrhea are mainly related to pathways such as energy metabolism, glycerolipid metabolism, fatty acid metabolism, and amino acid metabolism.

[0020] The beneficial effects of the present invention are:

[0021] The present invention is based on 1 the research method of metabolomics based on 1H NMR technology to detect the liver metabolites of dysmenorrhea mice, search for differential metabolites through the metabolomics research method, obtain 23 biomarkers with the mechanism of treating dysmenorrhea through the screening and exclusion mechanism, and use the callback change of the biomarker content to realize the identification and high-throughput analysis of the mechanism of action of dysmenorrhea; perform pathway analysis on the differential metabolites through the MetaboAnalyst online analysis software, and comprehensively evaluate the mechanism of action of Angelica sinensis - Leonurus japonicus in treating dysmenorrhea from the overall level, providing a demonstrative study for the metabolomics and mechanism of action of traditional Chinese medicine. Description of the Drawings

[0022] Figure 1 It is a bar chart showing the effects of Angelica sinensis - Leonurus japonicus on the levels of target TNF-α, IL6, PTGS2, and VEGF in mice. C is the control group, M represents the model group, and Drug represents the treatment group with traditional Chinese medicine Angelica sinensis - Leonurus japonicus. *, ** respectively indicate significant differences (p < 0.05), extremely significant differences (p < 0.01) between each group and the model group.

[0023] Figure 2 It is the 1 1H NMR spectrum of the liver sample. a is the blank control group, b is the model group, and c is the treatment group with traditional Chinese medicine Angelica sinensis - Leonurus japonicus.

[0024] Figure 3 It is the PCA score plot and PLS-DA score plot of the liver sample and model validation (M represents the model group, C represents the blank control group, and Drug represents the treatment group with traditional Chinese medicine Angelica sinensis - Leonurus japonicus).

[0025] Figure 4 a is the OPLS-DA score plot of the liver control group and model group, Figure 4 b is the S-plot, Figure 4c is the OPLS-DA score plot of the liver model group and the traditional Chinese medicine Angelica sinensis-Leonurus japonicus treatment group. Figure 4 d is the S-plot.

[0026] Figure 5 It is a schematic diagram of the metabolic pathway relevance based on 23 metabolic markers.

[0027] Figure 6 It is a metabolic pathway relationship diagram based on 23 metabolic markers. Detailed implementation manners

[0028] The features and advantages of the present invention can be further understood through the following detailed description in conjunction with the accompanying drawings. The provided embodiments are only illustrative of the method of the present invention and do not limit the remaining content disclosed by the present invention in any way.

[0029]

Example 1

[0030] The specific methods for animal treatment and sample collection were as follows: 15 KM mice were randomly divided into 2 groups, a control group (n = 5) and a model group (n = 20). Oral administration of estradiol benzoate induced dysmenorrhea in mice. The mice in the model group were orally administered estradiol benzoate CMC suspension (2 mg / kg / d) for 10 consecutive days, and the mice in the control group were orally administered the same volume of normal saline. On the 10th day, the estradiol-treated mice were divided into 2 groups (5 mice in each group), the model group and the traditional Chinese medicine Angelica sinensis-Leonurus japonicus treatment group (Drug, dose 12.0 g / kg). The mice in the traditional Chinese medicine Angelica sinensis-Leonurus japonicus treatment group were given an aqueous solution of Angelica sinensis-Leonurus japonicus extract every day, and the mice in the model group and the control group were given the same volume of normal saline for 6 consecutive days. At the end of the 16th day, all mice were fasted overnight. On the 17th day, each group of mice was intraperitoneally injected with oxytocin (20 U / kg) 1 hour after the last administration, and the number of writhing responses of the mice within 30 min after injection was recorded. At the end of the drug administration on the 17th day, blood was taken from the abdominal aorta into a vacuum tube, the mice were sacrificed by cervical dislocation, and the skin was wiped with 75% ethanol and then the abdominal cavity was opened, and samples were obtained by shearing the liver tissue.

[0031]

Example 2

[0032] Mouse serum samples were centrifuged at 3000-3500 rpm for 10 minutes, and the supernatant was used for microplate reader detection; liver samples were taken out of the -80℃ low-temperature refrigerator, thawed on ice, homogenized 2-3 times in 50% acetonitrile aqueous solution (5mL / g tissue), and the mixture was ultrasonicated for 10 minutes to mix evenly, then centrifuged at 4℃ and 12,000rpm for 10 minutes, and the supernatant was blown dry under nitrogen. The dried tissue extract was dissolved in 550μL D2O containing 0.01% TSP and transferred to a nuclear magnetic tube for NMR analysis. A Bruker AV III HD 400MHz spectrometer (frequency of 400 MHz) was used, and the experimental temperature was 297K. The instrument needs to be temperature calibrated and shimmed before testing. NOESY pulse sequence was used for analysis. The 90° pulse length was 10 μs, the mixing time tm was 100 ms, the spectral width was 20 ppm, the relaxation time was 2 s, the number of signal accumulations (NS) was 64, and the number of sampling points (TD) was 65536. Before Fourier transformation, the FID was weighted using an exponential window function with a line broadening of 0.3 Hz.

[0033] [Example 3] Search and identification of biomarkers

[0034] All the samples were analyzed by TOPSPIN 3.5 (Bruker, Germany). 1 The H NMR raw data were phase corrected and baseline corrected, and the TSP was calibrated to δ0.00 ppm. The data were further preprocessed using MestReNova software (Bruker, Germany) and 1 The H-NMR spectrum was segmented and integrated at equal intervals of Δδ=0.01 from δ0.00 to 9.5ppm, and the water peak signal at δ4.70-5.20ppm was removed. The segmented integrated data was normalized according to the total area of ​​the spectrum to generate a data matrix, which was imported into the multivariate statistical analysis software for statistical analysis. First, principal component analysis (PCA) and partial least squares discrimination analysis (PLS-DA) were used to perform pattern recognition on the data. At the same time, orthogonal partial least squares discrimination analysis (OPLS-DA) was used to further analyze each of the two groups of samples. The corresponding model parameters R 2 X, R 2 Y and Q 2To evaluate the model quality. Secondly, the effectiveness of the model was further verified by permutation test, and the permutation test model was evaluated. S-Plot and Variable Importance in Projection (VIP) analysis can preliminarily screen out differential metabolites. Univariate statistical analysis uses the t-test, and when the significance criterion is p < 0.05, it indicates a significant difference between groups. In this experiment, VIP values (VIP > 1) and p-values of the t-test (p < 0.05) were used to find biomarkers. To explore the changes in metabolic pathways caused by dysmenorrhea and the effects of Angelica sinensis - Leonurus japonicus on these metabolic pathways, the differential metabolites screened from liver samples were imported into the online analysis software MetaboAnalyst 5.0 for metabolic pathway analysis. Through the impact value obtained from the metabolic pathway analysis, when the impact value is greater than 0.1, it is considered that this metabolic pathway has an important impact in the metabolic network.

[0035] Analysis of the number of writhing responses in mice

[0036] The effect of Angelica sinensis - Leonurus japonicus on estradiol-treated mice was evaluated by the writhing response. As shown in Table 1, compared with the control group, the writhing frequency of the model group increased significantly (p < 0.01), indicating that the model was successfully established. Compared with the model group, the number of writhing responses of the mice in the traditional Chinese medicine Angelica sinensis - Leonurus japonicus treatment group decreased significantly within 30 min, confirming that Angelica sinensis - Leonurus japonicus can significantly improve the symptoms of estradiol-treated mice.

[0037] Table 1 Comparison of writhing response experimental data among the normal control group, model group, and Angelica sinensis - Leonurus japonicus group

[0038]

[0039] Remarks: ** Indicates p < 0.01 compared with the model group.

[0040] Serum ELISA analysis

[0041] Detection was performed using a Multiskan Ascent enzyme-linked immunosorbent detector to measure the levels of TNF-α, IL6, PTGS2, and VEGF in serum samples. The results are as Figure 1 shown: Compared with the control group, the contents of IL-6, VEGF, TNF-α, and PTGS2 in the serum of the model group were significantly increased (P < 0.01), which further indicated that the dysmenorrhea mouse model was successfully established. The traditional Chinese medicine Angelica sinensis - Leonurus japonicus treatment group significantly downregulated the elevated levels of IL6, VEGF, TNF-α, and PTGS2 in dysmenorrhea mice.

[0042] 1 HNMR liver metabolomics analysis

[0043] (1) 1 The liver samples of the normal control group, model group, and the traditional Chinese medicine Angelica sinensis - Leonurus japonicus treatment group were detected by the above method for 1H NMR comparison. Figure 2 The 1H NMR spectra of the liver of the blank control group, model group, and the traditional Chinese medicine Angelica sinensis - Leonurus japonicus treatment group were shown, and the detection data were analyzed by principal component analysis (PCA) and partial least squares discriminant analysis (PLS - DA). The score plots are as 1 shown. It can be seen that the three groups of sample points of the blank control group, model group, and the traditional Chinese medicine Angelica sinensis - Leonurus japonicus treatment group are completely separated, indicating that there are differences among the three groups. The distance between the blank group and the traditional Chinese medicine Angelica sinensis - Leonurus japonicus treatment group is relatively close, indicating that Angelica sinensis - Leonurus japonicus has the tendency to restore the dysmenorrhea model to the normal state, and the PLS - DA model is reasonably constructed through verification. Figure 3 Shown. It can be seen that the three groups of sample points of the blank control group, model group, and the traditional Chinese medicine Angelica sinensis - Leonurus japonicus treatment group are completely separated, indicating that there are differences among the three groups. The distance between the blank group and the traditional Chinese medicine Angelica sinensis - Leonurus japonicus treatment group is relatively close, indicating that Angelica sinensis - Leonurus japonicus has the tendency to restore the dysmenorrhea model to the normal state, and the PLS - DA model is reasonably constructed through verification.

[0044] (2)OPLS - DA analysis of liver samples Only performing unsupervised PCA analysis is not sufficient to prove the differences among them. Supervised OPLS - DA analysis is also needed. By performing OPLS - DA analysis on the data, complete separation between the blank control group and the model group, and between the model group and the traditional Chinese medicine Angelica sinensis - Leonurus japonicus treatment group was observed in Figure 4 a, 4c, which indicates that there are significant metabolic profile differences among the three groups. Figure 4 b and 4d show the S - plots of the variables of the blank control group and the model group, and between the model group and the traditional Chinese medicine Angelica sinensis - Leonurus japonicus treatment group. The closer the variables in the S - Plot are to both ends of the "S", the greater the contribution rate to the model, and vice versa.

[0045] (3)Identification of dysmenorrhea model - marked metabolites The differences in the relative peak areas of endogenous liver metabolites were evaluated using the variable importance in projection parameter (VIP) and t - test. The differential metabolites must meet two conditions: VIP>1 and P<0.05. According to the above principle, the composition analysis of all signal peaks was carried out. According to relevant literature, relevant databases such as HMDB, 23 metabolites were identified as biomarkers related to dysmenorrhea, and the results are shown in Table 2. Based on the above results, 23 differential metabolites were determined as biomarkers of the dysmenorrhea mouse model.

[0046] Table 2 Biomarkers in the liver of dysmenorrhea mice

[0047]

[0048] C is the blank control group, M is the model group, and Drug is the traditional Chinese medicine Angelica sinensis - Leonurus japonicus treatment group. ↑ indicates a relative increase in the signal; ↓ indicates a relative decrease in the signal. * and ** represent statistical differences P<0.05 and P<0.01, respectively.

[0049] (4)Metabolic pathway analysis and mechanism exploration

[0050] Twenty-three biomarkers related to dysmenorrhea were input into the online MetaboAnalyst and KEGG databases to construct an analysis of disease-related metabolic pathways, and the relevant metabolic pathways were obtained. The results are shown in Table 3 and Figure 5 According to the analysis results, a metabolic pathway relationship diagram was constructed, as shown in Figure 6 Research shows that the key pathways of the pharmacological effects of Angelica sinensis-Eclipta prostrata in treating dysmenorrhea are mainly related to pathways such as amino acid metabolism, energy metabolism, and fatty acid metabolism, and there are significant callbacks to the abnormal expressions of phenylalanine, arginine, etc. These compounds are perturbed in the metabolic pathways, thus revealing the relevant biochemical basis for analgesia, anti-inflammatory, and promoting blood circulation to remove stasis and relieve pain.

[0051] Table 3 Based on 1 Results of the dysmenorrhea metabolic pathway constructed based on 1H NMR and the MetaboAnalyst database

[0052]

[0053] Phenylalanine is involved in two pathways: the biosynthesis of phenylalanine, tyrosine, and tryptophan and phenylalanine metabolism. As one of the aromatic amino acids, phenylalanine is a precursor of tyrosine. One of the most important functions of tyrosine is to be converted into catecholamines such as dopamine (DA), norepinephrine (NE), and epinephrine. Norepinephrine and dopamine can directly reduce the degree of dysmenorrhea pain and its accompanying symptoms. An increase in phenylalanine concentration will lead to the inhibition of the synthesis of DA and NE in the brain, resulting in clinical symptoms such as depression, irritability, and insomnia in dysmenorrhea patients. Therefore, the stability of phenylalanine metabolism has an important impact on the body's functions. In this study, the content of phenylalanine in the liver of the model group increased, and the phenylalanine level tended to the content level of the control group after treatment with Angelica sinensis-Eclipta prostrata. Therefore, the stability of phenylalanine metabolism has an important impact on the body's functions.

[0054] Arginine is involved in two related pathways: arginine biosynthesis and arginine and proline metabolism. Arginine is an essential semi-essential amino acid synthesized from glutamine and proline. Arginine generates nitric oxide under the action of nitric oxide synthase, and NO is a neurotransmitter involved in regulating peripheral and central pain levels. When NO increases, it has an inhibitory effect and relieves pain, while when NO decreases, it induces pain and causes dysmenorrhea. Our study shows that the level of arginine in the liver of the model group decreased, indicating that the production of nitric oxide generated by arginine was inhibited, which may be the cause of pain. The content of arginine increased after treatment, indicating an increase in NO content. Since NO is lipid-soluble, it can quickly penetrate the cell membrane and diffuse into the uterus, acting on uterine smooth muscle cells to relax them, thus playing an analgesic role.

[0055] Taurine can protect the antioxidant activity of blood cells and prevent tissue oxidation and free radical damage. Glutamic acid is directly or indirectly involved in the metabolism of oxygen free radicals, and the amount of oxygen free radicals in the body affects the occurrence of primary dysmenorrhea. After treatment with Angelica sinensis - Leonurus japonicus, the content of glutamic acid increases, and more antioxidants are produced, which can better scavenge oxygen free radicals to relieve the pain caused by uterine smooth muscle contraction. Threonine is an essential amino acid that can improve immunity, while the level of threonine in the liver of dysmenorrhea mice decreases, indicating that dysmenorrhea causes a decline in the immunity level of mice. 3-Hydroxybutyric acid in the liver can lead to a decrease in energy production by oxidizing fatty acids, which is related to energy metabolism.

[0056] Traditional Chinese medicine theory believes that the liver plays an important role in gynecological diseases. The liver is the hub of regulation to ensure the harmony of qi and blood and the balance of yin and yang in the body. Women take blood as the foundation. The liver stores blood. The Chong meridian starts from the uterus and connects to the liver, which is closely related to the menstruation of women. Pathologically, the so-called "the liver is the thief of the five zang-organs and six fu-organs". Whether it is external factors such as emotional stimulation, getting cold and drinking cold, and overwork, or internal factors such as abnormal regulation of the liver, and unsmooth qi and blood in the Chong and Ren meridians, all can lead to the failure of the liver to disperse and dredge, stagnation of liver qi, qi stagnation leading to blood stasis, and stasis in the uterus causing pain. Traditional Chinese medicine believes that the main pathogenesis of dysmenorrhea is "pain due to obstruction", and Angelica sinensis - Leonurus japonicus, as a classic medicinal pair for treating qi stagnation and blood stasis, is used to treat dysmenorrhea in this study, soothe the liver and regulate qi, and dissipate stasis and relieve pain. Professor Wang Cuixia believes that emotional depression or anger injuring the liver leads to dysmenorrhea, which becomes the main pathogenesis of dysmenorrhea, and proposes the treatment principles of soothe the liver and regulate qi before menstruation, promote qi and activate blood circulation, dissipate stasis and relieve pain during menstruation. Fu Qingzhu treated dysmenorrhea with "regulating the liver" as the center, emphasizing nourishing the liver first, and being good at using the method of nourishing blood and regulating the liver, reflecting that "women take the liver as the congenital foundation". Treating dysmenorrhea from the liver conforms to traditional Chinese medicine theory. Therefore, this study is of great significance for the accurate diagnosis and formulation of treatment strategies for primary dysmenorrhea.

[0057] To sum up, the metabolomics study of dysmenorrhea mice shows that there are abnormal metabolisms of micro-indexes such as amino acid metabolism, energy metabolism, and lipid metabolism in diseased mice, which is consistent with the research results of macro-indexes such as the writhing response of diseased mice and serum ELISA analysis. The key pathways of the pharmacological effects of Angelica sinensis - Leonurus japonicus in intervening in dysmenorrhea are mainly related to pathways such as amino acid metabolism, energy metabolism, and fatty acid metabolism, and have significant callbacks on the abnormal expressions of phenylalanine, arginine, etc. Thus, it reveals the relevant biochemical basis of analgesia, anti-inflammation, dissipating stasis and relieving pain. The present invention reveals the pathogenesis of dysmenorrhea and the mechanism of action of Angelica sinensis - Leonurus japonicus in treating dysmenorrhea.

[0058] The above embodiments are the preferred embodiments of the present invention, but the embodiments of the present invention are not limited by the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications made without departing from the spirit and principle of the present invention shall be equivalent replacement methods and are all included in the protection scope of the present invention.

Claims

1. A liver metabolomics method for screening biomarkers in dysmenorrhea model mice, comprising the following steps: (1) Experimental grouping: The mice are divided into a dysmenorrhea model group induced by estradiol and oxytocin, a blank control group fed with an equal amount of physiological saline, and a treatment group intragastrically administered with the Chinese herbal medicine pair of Angelica sinensis and Leonurus japonicus. (2) Observe the writhing response of mice on the last day after oxytocin injection, collect the serum and liver samples of mice. The blood samples are used for ELISA analysis, and the liver samples are used for metabolomics analysis; Pretreatment of samples and 1 H NMR detection; (3) Data processing: Compare the metabolites between the blank control group and the model group, screen out the biomarkers for dysmenorrhea model, and compare with the traditional Chinese medicine Angelica sinensis-Leonurus japonicus treatment group to screen out the biomarkers with the mechanism of action for treating dysmenorrhea; Use TOPSPIN 3.5 software and MestReNova software to process the 1 1H NMR data obtained in step 2 to obtain a data matrix, import the data matrix into SIMCA-P 14.0 software, perform unsupervised principal component analysis and supervised partial least squares discriminant analysis, and based on the S-plot and VIP values of OPLS-DA analysis, identify and reveal differential metabolites and separate them between different groups. Metabolites with a VIP value higher than 1 and a P value lower than 0.05 are biomarkers for the dysmenorrhea model. According to the biomarkers 1 1H NMR spectra and 2D NMR spectra, combined with the literature and the software AMIX for analysis. (4) Perform pathway analysis on the specific biomarkers obtained in the above steps through the online analysis software MctaboAnalyst; the pathway analysis also includes importing 23 dysmenorrhea model biomarkers into the MetaboAnalyst and KEGG databases to construct and analyze disease-related metabolic pathways, and obtaining relevant metabolic pathways; the key pathways for the pharmacological effect of the Chinese herbal medicine pair of Angelica sinensis and Leonurus japonicus in intervening in dysmenorrhea are mainly related to amino acid metabolism, energy metabolism, and fatty acid metabolism pathways, and have a significant callback on the abnormal expression of phenylalanine and arginine.

2. The liver metabolomics method for screening biomarker of dysmenorrhea model mice according to claim 1, wherein The drug used in the treatment group of the Chinese herbal medicine pair of Angelica sinensis and Leonurus japonicus is the water extract of Angelica sinensis and Leonurus japonicus, including two medicinal materials, Angelica sinensis and Leonurus japonicus, in a ratio of 3:

2. The water extract contains 1.5 g of crude drug per ml, and the daily dosage is 12 g / kg.

3. A liver metabolomics method for screening biomarker of dysmenorrhea model mice according to claim 1, characterized in that , The mouse serum sample in step 2) is taken from the 17th day by collecting blood from the abdominal aorta into a vacuum tube, centrifuging to obtain the supernatant, and finally sacrificing the mouse by cervical dislocation. After wiping the skin with 75% ethanol, the abdominal cavity is opened, and the sample is obtained by cutting the liver tissue.

4. A liver metabolomics method for screening biomarker of dysmenorrhea model mice according to claim 1, characterized in that , The pretreatment method of the sample in step 2) is as follows: Centrifuge the mouse serum sample at 3000 - 3500 revolutions per minute for 10 minutes, and take the supernatant for detection by an enzyme-labeled instrument; Homogenize the liver sample containing 5 mL / g of tissue 2 - 3 times in 50% aqueous acetonitrile solution, and ultrasonicate the mixture for 10 min to make it evenly mixed. Next, centrifuge at 4 °C and 12,000 rpm for 10 min; Dry the supernatant under nitrogen, dissolve the dried tissue extract in 550 μL of D2O containing 0.01% TSP, and transfer it to a nuclear magnetic resonance tube for NMR analysis.

5. A liver metabolomics method for screening biomarkers of dysmenorrhea model mice according to claim 1, characterized in that, The described 1 The conditions for 1H NMR detection and analysis are as follows: A Bruker AVIIHD 400 MHz spectrometer with a working frequency of 400 MHz is used. The experimental temperature is 297 K. Before the test, temperature correction and shimming correction of the instrument are required. The NOESY pulse sequence is used for analysis. The 90° pulse length is 10 μs, the mixing time tm is 100 ms, the spectral width is 20 ppm, the relaxation time is 2 s, the number of signal accumulations (NS) is 64, and the number of sampling points (TD) is 65536. Before Fourier transform, an exponential window function with a line broadening of 0.3 Hz is used to weight the FID.

6. A liver metabolomics method for screening biomarkers of dysmenorrhea model mice according to claim 1, characterized in that, The specific dysmenorrhea model biomarkers are as follows: Note: C is the blank control group, M is the model group, and Drug is the treatment group of the Chinese herbal medicine pair of Angelica sinensis and Leonurus japonicus; ↑ represents a relative increase in signal; ↓ represents a relative decrease in signal; * and ** represent statistical differences P < 0.05 and P < 0.01 respectively.

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