CN109507337B - Novel method for predicting mechanism of Gandi capsule for treating diabetic nephropathy based on metabolites in hematuria - Google Patents
Novel method for predicting mechanism of Gandi capsule for treating diabetic nephropathy based on metabolites in hematuria Download PDFInfo
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Abstract
The invention provides a method for predicting a diabetic nephropathy mechanism by using Gandi capsules based on metabolites in hematuria, which is characterized by comprising the following specific steps of selecting a test group and a control group in a ratio of S1 to 1: 1; s2, collecting samples to be detected periodically; s3, processing the sample of S2, and carrying out UPLC-Q-TOF/MS separation analysis; s4, carrying out metabolic profile analysis on the UPLC-Q-TOF/MS spectrum data obtained in the S3 to obtain a data set; s5, constructing a PLS-DA model according to the data set obtained in S4; s6, screening out a metabolic marker capable of distinguishing a blank group and a sweet land capsule administration group according to an S-PLOT load graph and a VIP score of a model of the S5 component; and S7, carrying out enrichment analysis on the metabolic markers obtained by screening the S6 by adopting an IPA analysis method, and sequencing the metabolic markers according to the enrichment efficiency. The pharmacological mechanism of the gandi capsule for treating the diabetic nephropathy can be predicted by the method.
Description
Technical Field
The invention relates to the field of metabonomics, in particular to a method for predicting a diabetic nephropathy treatment mechanism by using Gandi capsules based on metabolites in blood/urine.
Background
Metabonomics is an important branch in the field of systematic biological research, provides massive information for explaining a complex mechanism by analyzing biochemical changes and metabolic profiles caused by pathophysiological factors or gene modification, and is contrary to the characteristics of multiple components and complex pharmacological mechanisms of a Chinese medicinal compound preparation, so that the metabonomics can be used for the pharmacological research of the Chinese medicinal compound preparation. At present, metabonomics research methods are widely applied to the research of pathological mechanisms and drug action mechanisms of various metabolic diseases. Nuclear Magnetic Resonance (NMR), gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-mass spectrometry (LC-MS) techniques are three modern analytical techniques commonly used for metabolomic analysis.
The incidence of microangiopathy of diabetic nephropathy patients is high, blood pressure is an independent risk factor of renal function damage, if hypertensive patients suffer from diabetes at the same time, the incidence of diabetic nephropathy is remarkably improved, the clinical manifestation is persistent proteinuria, patients enter a renal failure stage, and the mortality rate is remarkably increased. At present, few Chinese and western medicines aiming at the treatment of diabetic nephropathy are available on the market. Clinical verification of years shows that the liquorice capsule preparation in hospital has the function of obviously reducing proteinuria, and can be used for treating microangiopathy such as diabetic nephropathy for a long time in hospital. The early clinical test data show that the gandi capsule can obviously reduce 24h urine microalbumin excretion of diabetic nephropathy patients, delay the progress of diabetic nephropathy and protect and improve kidney functions, thereby improving the life quality of the patients, and the patients can obviously improve after taking the gandi capsule for 2 courses of treatment (4 months). However, the molecular mechanism of the gandi capsule for treating diabetic nephropathy is still unclear. Therefore, a method for defining the action mechanism of the medicine is urgently researched.
Disclosure of Invention
The invention aims to overcome the defects and provide a mechanism for treating diabetic nephropathy by using a liquorice capsule.
The invention provides a method for predicting diabetic nephropathy mechanism based on metabolites in blood/urine, which is characterized by comprising the following specific steps:
s1, 1:1, selecting a test group and a control group;
the test group refers to patients taking gandi capsules;
the control group refers to patients who did not take Gandian capsules.
S2, collecting samples to be detected periodically;
the samples were collected from both groups of patients in the same test period.
S3, processing the sample of S2, and carrying out UPLC-Q-TOF/MS separation analysis;
s4, carrying out metabolic profile analysis on the UPLC-Q-TOF/MS spectrum data obtained in the S3 to obtain a data set;
the metabolic profile analysis refers to quantitative determination of preset metabolites with similar structures or related properties in a specific metabolic process by using a targeted analysis technology, such as: a certain class of compounds with similar structures and related properties, and the like.
S5, constructing an OPLS-DA model (in a mode of using analysis software SIMCA-P11.0(Umetrics AB, Umea, Sweden) and the like) according to the data set obtained in S4 to construct an OPLS-DA model;
s6, calculating a VIP value according to an S-PLOT load graph in the model constructed by the S5, obtaining a corresponding P value at the same time, and screening out a metabolic marker capable of distinguishing a blank group from a gandi capsule administration group under the condition that the VIP value is more than 1.0 and the P value is less than 0.05. This step can be achieved using the analytical software SIMCA-P11.0(Umetrics AB, Umea, Sweden).
And S7, carrying out enrichment analysis on the metabolic markers obtained by screening the S6 by adopting an IPA analysis method, and sequencing the metabolic markers according to the enrichment efficiency.
Further, the invention relates to a method for predicting the mechanism of treating diabetic nephropathy by using the gandi capsules based on metabolites in blood/urine, which is also characterized in that: namely, the metabolic profile analysis comprises the following specific steps: and (3) adopting a peak filtering technology, only retaining a plurality of ion fragments with the strongest abundance within the same retention time, and deleting other fragments.
Or the metabolic profile analysis comprises the following specific steps:
s4-1, carrying out nonlinear correction and normalization on the data, and keeping variables with RSD less than X% (X% can be customized, such as 30%) in QC samples;
before the data is processed in S4-1, the LC-MS data in the special format of the instrument can be converted into the mzData format by using a data analysis module built in the Masshunter;
s4-2, the LC-MS data for each sample was normalized to the sum of all peak areas for each sample, resulting in a new data set. This step can be achieved by importing data into MATLAB7.0 software (The MathWorks, Inc.) and The like.
Further, the invention relates to a method for predicting the mechanism of treating diabetic nephropathy by using the gandi capsules based on metabolites in blood/urine, which is also characterized in that: namely, the multivariate statistical performance parameter of the OPLS-DA model is R2X＝0.599，R2Y＝0.921，Q2＝0.745。
Further, the invention relates to a method for predicting the mechanism of treating diabetic nephropathy by using the gandi capsules based on metabolites in blood/urine, which is also characterized in that: namely, the sample to be tested is a blood sample or a urine sample. Other samples can be used according to the difference of the detection objects.
Further, the invention relates to a method for predicting the mechanism of treating diabetic nephropathy by using the gandi capsules based on metabolites in blood/urine, which is also characterized in that: that is, the method of processing the S2 sample includes: and adding a mixed solution of methanol and acetonitrile into the sample, uniformly mixing, performing centrifugal separation, and taking out the supernatant to be tested.
Further, the invention relates to a method for predicting the mechanism of treating diabetic nephropathy by using the gandi capsules based on metabolites in blood/urine, which is also characterized in that: namely, the volume ratio of the methanol to the blood sample or urine sample is 4-8: 1.
further, the invention relates to a method for predicting the mechanism of treating diabetic nephropathy by using the gandi capsules based on metabolites in blood/urine, which is also characterized in that: that is, the parameters of the above UPLC-Q-TOF/MS separation analysis are as follows:
the composition of the mobile phase of the chromatogram was: b: 0.1% formic acid acetonitrile, gradient elution setup as follows: 3% of B in 0-2min, 3-15% of B in 2-11min, 15-30% of B in 11-16min, 30-95% of B in 16-18min, 95% of B in 18-19.5min, and 95-3% of B in 19.5-20 min; then balancing for 4 min; the flow rate is 400 mu L/min, and the sample injection amount is 4 mu L; (ii) a
The flight mass spectrum adopts an ESI source, and the parameters are set to be in a positive ion mode;
capillary voltage: 3500V; flow rate of drying gas: 11L/min; spraying air pressure: 45 psig; temperature of the drying gas: 350 ℃; fragmentation voltage: 120V; the mass range is as follows: m/z is 50-1000; the collision energy for MS/MS secondary mass spectrometry is set to 10-30 eV.
Further, the invention relates to a method for predicting the mechanism of treating diabetic nephropathy by using the gandi capsules based on metabolites in blood/urine, which is also characterized in that: that is, whether the differential metabolite has statistical significance is determined by using Student's T-test statistical analysis (for example, calculation using SPSS software).
Further, the invention relates to a method for predicting the mechanism of treating diabetic nephropathy by using the gandi capsules based on metabolites in blood/urine, which is also characterized in that: that is, the metabolites are mainly lipid metabolites and amino acid metabolites.
Further, the invention relates to a method for predicting the mechanism of treating diabetic nephropathy by using the gandi capsules based on metabolites in blood/urine, which is also characterized in that: namely, it can be applied to the study of the therapeutic mechanism of other drugs.
The invention has the following functions and effects:
diabetic nephropathy is a typical metabolic disease, and its occurrence and development are closely related to energy metabolism, sugar metabolism, amino acid metabolism, and lipid metabolism. Therefore, the application of the UPLC-Q-TOF/MS-based metabonomics technology to the metabolic profiling analysis of serum and urine samples of a patient clinically treated by the Gandi capsule is an effective means for revealing the pharmacodynamic mechanism of the Gandi capsule for treating diabetic nephropathy. Meanwhile, a serum sample and a urine sample are collected for integrated metabonomics analysis, so that the trace and the efficiency of the glycogenomics capsule in regulating and controlling metabolic pathways in a human body can be more comprehensively represented.
In the study, the UPLC-Q-TOF/MS technology is adopted to analyze the metabolic profile changes of the serum and urine of patients in a sweet land capsule administration group and a control group, and then the change of the metabolic markers after the sweet land capsule is treated for 6 months is screened by adopting the multivariate statistical analysis method of partial least squares discriminant analysis (OPLS-DA). As the clinical metabonomics research of the Gandi capsule for the first time, the influence of the metabolism level of the Gandi capsule is discovered, the action mechanism of the Gandi capsule is preliminarily explained at the level of the metabolism path, and a new method is provided for predicting the pharmacological mechanism of the Gandi capsule for treating the diabetic nephropathy.
Drawings
FIG. 1, a UPLC-Q-TOF/MS total ion flow chromatogram of a typical patient serum;
wherein: (A) the blank group (B) is a group administered with the gandi capsule for 6 months.
FIG. 2, a UPLC-Q-TOF/MS chromatogram of total ion flux of typical patient urine;
wherein: (A) the blank group (B) is a group administered with the gandi capsule for 6 months.
FIG. 3, OPLS-DA score plots (A) and S-plot (B) for serum samples from blank (light color) and 6 month administration of Glycine capsules (dark black) based on UHPLC-Q-TOF/MS data.
FIG. 4, urine sample OPLS-DA score plot (A) and S-plot (B) for blank group (light color) and 6 month administration group (dark black color) of GANDIJI capsule based on UHPLC-Q-TOF/MS data.
Figure 5, graph of metabolic pathway IPA analysis results for serum and urine biomarkers.
FIG. 6 is a diagram of metabolic pathway analysis of the intervention of GANDIJI Capsule in diabetic nephropathy.
Detailed Description
The present example was carried out using the following method:
data acquisition
In this example, diabetic nephropathy patients were used as subjects, and were randomly divided into test groups and control groups of 30 persons.
Wherein the test groups: the GANDI Capsule is taken by diabetic nephropathy patients 3 times daily, 3 capsules each time, and is continuously administered for 6 months.
Control group: the medicine residue capsule is taken 3 times a day, 3 capsules each time, and is continuously used for 6 months by patients with diabetic nephropathy.
Patients were sampled 24h urine and blood every 2 months. Blood and urine samples were subjected to sample pretreatment and then chromatographed using an Acquity UPLC BEH C18 column (2.1mm × 100mm,1.7 μm, Waters,) chromatography column. The composition of the mobile phase was: b: 0.1% formic acid acetonitrile, gradient elution setup as follows: 3 percent of B in 0-2min, 3-15 percent of B in 2-11min, 15-30 percent of B in 11-16min, 30-95 percent of B in 16-18min, 95 percent of B in 18-19.5min, and 95-3 percent of B in 19.5-20 min; then balancing for 4 min; the flow rate is 400 mu L/min, and the sample injection amount is 4 mu L; . Data acquisition was performed using an Agilent 6530Accurate-Mass Q-TOFMS tandem quadrupole-time-of-flight Mass spectrometer with ESI source and parameters set to positive ion mode. Capillary voltage: 3500V; flow rate of drying gas: 11L/min; spraying air pressure: 45 psig; temperature of the drying gas: 350 ℃; fragmentation voltage: 120V; the mass range is as follows: m/z is 50-1000. The collision energy for MS/MS secondary mass spectrometry is set to 10-30 eV.
(II) data acquisition and processing
The data with LC-MS was converted to NetCDF and mzData format by MassHunter software. In MATLAB7.0 software, a peak filtering technology inside a subject group is used, namely only the ion fragment with the strongest abundance in the same retention time is retained, and other fragments are deleted. Next, the data is further processed with XCMS software. The XCMS software mainly functions to perform non-linear correction and normalization on data. The parameters are set as Full Width Half Maximum (FWHM) 10, bandwidth (bw) 10 and signal to noise ratio (snthresh) 5, and the other parameters are default values. Using the metabonomically accepted 80% rule, those variables with RSD less than 30% in QC samples were retained and these data were imported into MATLAB7.0 software and normalized for total peak area. And finally, integrating the processed data to obtain a new data set, and performing multivariate statistical analysis.
Serum and urine samples from selected blanks and patients 6 months after administration of the gandi capsules were subjected to metabolic profiling using the method described above. The serum UPLC-Q-TOF/MS profiles of the typical blank group and the 6-month administered group are shown in fig. 1, and the urine UPLC-Q-TOF/MS profile is shown in fig. 2. The screened data set has a higher peak capacity, wherein the serum data set contains 579 peaks, and the urine data set contains 998 peaks.
(III) Metabonomics data analysis
Partial least squares discriminant analysis (OPLS-DA) is a supervised multivariate statistical method, and analysis is performed by adopting the 13.0 version of SIMCA-P software, and data is subjected to log transformation in order to reduce unit errors. And (3) screening potential metabolic markers with the strongest distinguishing capability between the two groups by analyzing a Loading graph and a score graph of the OPLS-DA model and combining the conditions that the VIP value of the importance parameter is more than 1.0 and the P value is less than 0.05.
The following three parameters (R) are mainly adopted for evaluating the quality of the model2X,R2Y and Q2Y), calculated by the default leave-one-out procedure. R2X and R2Y is for evaluating goodness of fit, Q2Y is used to evaluate model predictability.
In order to obtain characteristic ions which can distinguish two groups, the method is adopted by UPLC-Q-TOF/MS in the embodiment, and an OPLS-DA model is constructed according to collected data. As shown in FIG. 3, the multivariate statistical Performance parameter is R2X＝0.599，R2Y＝0.921，Q20.745, indicating that both models have highly efficient prediction capabilities. The classification specificity of an OPLS-DA model constructed by a blank group and a data set of 6 months after administration of the gandi capsules also reaches 100 percent, and the sensitivity reaches 100 percent.
According to the S-plot load of the OPLS-DA model (shown in figures 3 and 4) and the VIP score, a metabolic marker capable of distinguishing a blank group from a sweet land capsule administration group is screened. Respectively finding 18 and 20 metabolic biomarkers in UPLC-Q-TOF/MS serum and urine data, wherein potential metabolic biomarkers in the serum mainly comprise lipid metabolites such as long-chain fatty acid and the like, purine and creatinine, and potential metabolic biomarkers in the urine mainly comprise amino acid, organic acid, purine, sphingosine and the like.
(IV) statistical analysis
Using SPSS software, Student's T-test statistical analysis was used to compare whether the different metabolites between the different treatment groups were statistically significant. When the P value is less than 0.05, the difference is considered significant.
By adopting the statistical method, the relative ionic strength of the metabolites is introduced into SPSS software for t-test analysis, and the result shows that the P values of all the different metabolites are less than 0.05, thereby proving the accuracy of identifying the different metabolic biomarkers by using the method.
(V) metabolic pathway enrichment analysis (IPA)
Ipa (intuition Pathway analysis) is an algorithm-based large-scale biological Pathway analysis software. On one hand, related information in the aspects of genes, proteins, medicines and the like can be searched, and an interaction network model of the related information is constructed; on the other hand, the method can also analyze experimental data from genome, micro-RNA, SNP, chip, metabolome, proteome and the like. This example uses IPA analysis to perform enrichment analysis on metabolic biomarkers screened from the previous OPLS-DA model, as shown in FIG. 5. The size and color depth of the circle are main indexes for judging the enrichment rate of the pathway, and the circle mainly comprises the reliability (-LogP) and the influence (Impact) of the pathway, as shown in the following table, the pathway with the highest enrichment efficiency is a purine metabolic pathway, the pathway arranged on the second is a glycerol phospholipid metabolic pathway, and other pathways also comprise various amino acid metabolic pathways. Therefore, purine, glycerophospholipid, phenylalanine, arginine, alanine, aspartic acid, proline and glutamine are metabolized, and the key way for the glycine-rehmannia capsule to play the efficacy of treating diabetic nephropathy and regulate the metabolic level of the organism is provided.
(VI) Metabolic pathway interaction map construction
In the present example, in the study of the metabolic biomarker differences between the gandi capsule administration group and the control group, 38 potential metabolic biomarkers were found. The changes of the markers are closely related to corresponding metabolic pathways, including lipid metabolism, sphingolipid metabolism, purine metabolism, phenylalanine, arginine, alanine, aspartic acid, proline, glutamine metabolism and the like. To mine the relationships between these marker metabolites, a metabolic pathway interaction map was constructed by searching KEGG PATHWAY the database as shown in FIG. 6. The pathway change of the gandi capsule administration group at the metabolic level can be better summarized and summarized through the visualization of the change of the metabolic biomarker.
Action and effect of the present embodiment:
in the embodiment, a metabonomic method for researching the mechanism of the gandi capsule for treating the diabetic nephropathy is constructed by combining UPLC-Q-TOF/MS data with a multivariate statistical analysis method (OPLS-DA). Through the research of the method, 39 metabolic markers of serum and/or urine are discovered, and the change of the markers is closely related to corresponding metabolic pathways, including lipid metabolism, sphingolipid metabolism, purine metabolism, phenylalanine, arginine, alanine, aspartic acid, proline, glutamine metabolism and the like.
Chronic inflammation caused by diabetes can cause kidney injury through various ways, cause obvious oxidative stress of the body, and generate a large amount of ROS (reactive oxygen species), and the ROS can damage blood vessel walls to cause vascular inflammation. In addition, CRP can also directly induce the expression of plasminogen activator inhibitor-1 (Pal-1) mRNA and Pal-1 protein by endothelial cells, and increase its activity, which aggravates kidney damage. Through synthesizing adhesion molecules and monocyte chemotactic protein-1, the leukocyte synthesis is promoted to release superoxide and proteolytic enzyme, so that kidney tissue damage is caused, and clinically, proteinuria and lipid metabolism disorder are shown.
Phospholipid metabolic disorders are key factors in the pathogenesis of diabetic nephropathy, and phospholipids are the major structural components of biological membranes and contain a variety of fatty acid components, such as Phosphatidylglycerol (PG), Phosphatidylimine (PE), Phosphatidylinositol (PI), Phosphatidylinositol (PS), Phosphatidylcholine (PC), Sphingomyelin (SM), and Lysophosphatidylcholine (LPC). In addition to this structural role, PC is involved in the process of deposition of emulsified neutral fat and cholesterol in blood vessels, improving intelligence, activating cells. In addition, their metabolism is closely related to many diseases such as alzheimer's disease, obesity, cancer, and the like. Due to these important biological functions, PC has gained increasing attention in many fields. Numerous studies have shown that disorders of lipid metabolism are directly associated with type II diabetes and diabetic nephropathy. In some disease models, PC molecules have become important biomarkers for the regulation or modulation of expression in type II diabetes and diabetic nephropathy.
In this example, it was found by a metabonomic method that the level of phospholipid metabolites in serum was significantly reduced in the gandi capsule-administered group compared to the control group, and that the phospholipid components, such as LysoPC (18:2(9Z,12Z)), PC (0:0/18:0), and LysoPE (20:0/0:0), were involved in the long-chain saturated or unsaturated phospholipid components. According to the OPLS-DA trend graph and the concentration change of potential biomarkers, abnormal phospholipid metabolism is shown to occur in diabetic nephropathy patients. The possible mechanisms include the three pathways of sorbitol, oxidative stress, Protein Kinase C (PKC) to be activated in the glucose high concentration environment of diabetes. Whereas activation of phospholipids (PLA2) is associated with activation of PKC. Phospholipase is an important enzyme in human body, and can catalyze the decomposition of phospholipid to generate free fatty acid. Thus, activated PLA2 will accelerate the breakdown of phospholipids. The results obtained in our experiments for increased levels of PC and LPC metabolism are consistent with this mechanism. With the development of diabetic nephropathy, PLA2 is activated, so the concentration of PC is reduced. PC loses one fatty acid chain under the catalysis of phosphatase, and the concentration of PC increases when PC is decomposed. Abnormal Phosphoinositide (PI) metabolism is a downward trend, a phenomenon that may be associated with the activation of the Sorbitol Pathway (SP). Under the intervention of the gandi capsules, the relative contents of phospholipid components such as lysoPC (18:2(9Z,12Z)), PC (0:0/18:0), lysoPE (20:0/0:0), PI (22:0/20:4(5Z,8Z,11Z,14Z)), PC (18:2(2E,4E)/0:0) and the like are remarkably reduced, which suggests that the gandi capsules can play a role in regulating the development of diabetic nephropathy by interfering in phospholipid metabolism and inhibiting phospholipid decomposition and metabolism. Many studies have shown that altered LysoPC content is associated with physiological changes in apoptosis, including mitochondrial dysfunction and oxidative stress. However, the specific mechanism is not clear, and the relationship between the change in the glycerocapsule and LysoPC needs to be further investigated.
In addition, the results of this example show that the level of metabolites such as uric acid, hypoxanthine and purine in the gan di capsule-administered group was significantly reduced compared to the control group. Uric acid is produced by purine metabolism, and therefore our findings suggest that xanthine oxidase activation is closely associated with the formation of microalbuminuria. In diabetic nephropathy patients, purine metabolism is closely associated with proteinuria, indicating that purine metabolism is disturbed during the course of the disease. Uric acid, hippuric acid, and hypoxanthine are all products produced from purine metabolism, and two key purine catabolism (xanthine and hypoxanthine) are produced by Xanthine Oxidase (XO), and the action of active oxygen. The result shows that the urine of the patient treated by the gandi capsule has obviously reduced levels of metabolites such as uric acid, hypoxanthine, purine and the like, which indicates that the activation of xanthine oxidase is obviously inhibited and the purine metabolic disorder tends to be mild.
Amino acid metabolism is also a key metabolic biomarker pointed out by IPA analysis, and metabolic pathways such as phenylalanine, tryptophan, aspartic acid, leucine and proline are involved. Recent studies have shown that Branched Chain Amino Acids (BCAAs) including valine, leucine, isoleucine, and aromatic amino acids such as tyrosine and phenylalanine are considered as strong predictors and biomarkers for serum and urine samples from diabetes. Similarly, serum leucine content or urine metabolites BCAA and aromatic amino acids have also changed significantly in diabetic nephropathy patients. Therefore, the change of amino acid metabolites has a significant influence on the destruction of the renal filtration state to a large extent, which is important in connection with the occurrence of diabetic nephropathy renal tissue pathology.
Therefore, the results that the gandi capsules mainly influence the amino acid metabolism, the lipid metabolism and the purine metabolism of diabetic nephropathy patients are obtained, and the gandi capsules can improve the proteinuria in clinical practice and are consistent with the previous research.
In conclusion, in the embodiment, the metabolic profile changes of the serum and urine of patients in the gandi capsule administration group and the control group are researched by using a UPLC-Q-TOF/MS metabonomics method, and the changes of the serum and urine metabolic markers of the patients after 6 months of treatment of the gandi capsule are screened by using a multivariate statistical analysis method of partial least squares discriminant analysis (OPLS-DA). The results show that UPLC-MS serum dataThe set contained 579 peaks, and the urine data set contained 998 peaks. The statistical performance parameter of the data is R2X＝0.599，R2Y＝0.921，Q2These parameters indicate that both models have a high degree of effective predictive power. The potential biomarkers are screened from the data of UPLC-Q-TOF/MS serum and urine, wherein the potential metabolic biomarkers in the serum mainly comprise lipid metabolites such as long-chain fatty acids and the like, and also comprise purine, creatinine and the like, and the potential metabolic biomarkers in the urine mainly comprise amino acids, organic acids, purine, sphingosine and the like. The key metabolic pathways were enriched using IPA analysis. The most efficient pathway for enrichment is the purine metabolic pathway, the second most important pathway is the phospholipid metabolic pathway, and other pathways for amino acid metabolism are also available. Therefore, purine, glycerophospholipid, phenylalanine, arginine, alanine, aspartic acid, proline and glutamine are metabolized, and the key way for the glycine-rehmannia capsule to play the efficacy of treating diabetic nephropathy and regulate the metabolic level of the organism is provided.
In this example, the effect of the change in metabolic markers in hematuria after administration of the gandi capsule on the improvement of purine metabolism, phospholipid metabolism, and amino acid metabolism was successfully predicted. This is consistent with the results of the clinical study of Gandi capsules, i.e., 24h reduction in urinary microalbumin. The embodiment also provides a feasible method for predicting the pharmacological mechanism of other Chinese herbal compound preparations.
Claims (6)
1. A method for predicting the mechanism of treating diabetic nephropathy by using Gandi capsules based on metabolites in blood/urine is characterized by comprising the following specific steps:
s1, 1:1, selecting a test group and a control group;
s2, collecting samples to be detected periodically;
s3, processing the sample of S2, and carrying out UPLC-Q-TOF/MS separation analysis;
s4, carrying out metabolic profile analysis on the UPLC-Q-TOF/MS spectrum data obtained in the S3 to obtain a data set;
s5, constructing an OPLS-DA model according to the data set obtained in the S4;
the multivariate statistical performance parameter of the OPLS-DA model is R2X = 0.599，R2Y = 0.921，Q2 = 0.745；
S6, simultaneously obtaining corresponding P values according to an S-PLOT load graph and a VIP value of the model of the S5 component, and screening out metabolic markers capable of distinguishing a blank group and a sweet land capsule administration group under the condition that the VIP value is more than 1.0 and the P value is less than 0.05;
s7, carrying out enrichment analysis on the metabolic markers obtained by screening the S6 by adopting an IPA analysis method, and sequencing the metabolic markers according to enrichment efficiency;
the metabolites are mainly lipid metabolites and amino acid metabolites;
the parameters of the UPLC-Q-TOF/MS separation analysis are as follows:
the composition of the mobile phase of the chromatogram was: b: 0.1% formic acid acetonitrile, gradient elution setup as follows: 3 percent of B in 0-2min, 3-15 percent of B in 2-11min, 15-30 percent of B in 11-16min, 30-95 percent of B in 16-18min, 95 percent of B in 18-19.5min, and 95-3 percent of B in 19.5-20 min; then balancing for 4 min; the flow rate is 400 mu L/min, and the sample injection amount is 4 mu L;
the flight mass spectrum adopts an ESI source, and the parameters are set to be in a positive ion mode;
capillary voltage: 3500V; flow rate of drying gas: 11L/min; spraying air pressure: 45 psig; temperature of the drying gas: 350 ℃; fragmentation voltage: 120V; the mass range is as follows: m/z is 50-1000; the collision energy for MS/MS secondary mass spectrometry is set to 10-30 eV.
2. The method of claim 1, wherein the method for predicting the mechanism of diabetes and nephropathy treatment by gandil capsule based on metabolites in blood/urine comprises:
the metabolic profile analysis is to adopt a peak filtering technology, only retain a plurality of ion fragments with the strongest abundance within the same retention time, and delete other fragments.
3. The method of claim 1, wherein the method for predicting the mechanism of diabetes and nephropathy treatment by gandil capsule based on metabolites in blood/urine comprises:
the steps of the metabolic profile analysis are as follows:
s4-1, carrying out nonlinear correction and normalization on the data, and reserving variables with RSD less than X% in QC samples;
s4-2, the LC-MS data for each sample was normalized to the sum of all peak areas for each sample, resulting in a new data set.
4. The method of claim 1, wherein the method for predicting the mechanism of diabetes and nephropathy treatment by gandil capsule based on metabolites in blood/urine comprises:
the method for processing the S2 sample is as follows: and adding a mixed solution of methanol and acetonitrile into the sample, uniformly mixing, performing centrifugal separation, and taking out the supernatant to be tested.
5. The method of claim 4, wherein the method for predicting the mechanism of diabetes and nephropathy treatment by gandi capsules based on metabolites in blood/urine comprises:
the volume ratio of the mixed solution of the methanol and the acetonitrile to the sample is 4-8: 1.
6. the method of claim 1, wherein the method for predicting the mechanism of diabetes and nephropathy treatment by gandil capsule based on metabolites in blood/urine comprises:
and judging whether the differential metabolite has statistical significance by using a Student's T-test statistical analysis method.
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