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Table of Contents
ORIGINAL ARTICLE
Year : 2022  |  Volume : 8  |  Issue : 1  |  Page : 141-152

Ultra-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry based bile and urine metabonomics study on the ameliorative effects of Curcuma wenyujin rhizoma on acute blood stasis in rats


1 Chinese Medicine Processing Engineering Center, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, China
2 Chinese Medicine Processing Laboratory, School of Pharmacy, Guizhou University of Traditional Chinese Medicine, Guizhou, China
3 Department of Pharmacy, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
4 Chinese Medicine Processing Laboratory, College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China

Date of Submission04-Mar-2021
Date of Acceptance06-May-2021
Date of Web Publication29-Jan-2022

Correspondence Address:
Prof. Chun-Qin Mao
College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing
China
Prof. Tu-Lin Lu
College of pharmacy, Nanjing University of Chinese medicine, Nanjing 210023
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/wjtcm.wjtcm_55_21

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  Abstract 


Background: Curcuma wenyujin rhizome (CWR) is a commonly used Chinese herbal medicine for treating blood stasis in China for 1000 of years. However, the underlying mechanism of CWR remains unclear. Aims and Objectives: The purpose of this study is to clarify the bioactive mechanism of CWR in treating blood stasis. Materials and Methods: In this study, pharmacological indexes, including hemorheology and four blood coagulation indexes were tested. Bile and urine metabolomics were engaged by UPLC-Q/TOF-MS. Multivariate statistical analysis were used to screen out differential endogenous metabolites. Results: The results indicated that CWR significantly ameliorated the hemorheology and coagulation functions of acute blood stasis (ABS) model rats. Moreover, 27 endogenous metabolites between the CWR group and the ABS group were screened, and the levels were all improved to certain degrees by CWR preadministration. Metabonomics results indicated that ABS was mainly related to linoleic acid metabolism, arachidonic acid metabolism, glycerophospholipid metabolism, sphingolipid metabolism, pentose and glucuronate intercereasonversions, steroid hormone biosynthesis, and primary bile acid biosynthesis. Conclusion: In a word, the metabolomics method is consistent with the holistic view of traditional Chinese medicine (TCM) that can be a powerful means to illustrate the biological activity mechanism of CWR in treating blood stasis and to offer research demonstration for further study on the effector mechanism of TCM.

Keywords: Bile, Curcuma wenyujin rhizome; metabolomics; ultra-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry; urine


How to cite this article:
Hao M, Zhao MT, Tong HJ, Ji D, Li L, Su LL, Gu W, Mao CQ, Lu TL. Ultra-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry based bile and urine metabonomics study on the ameliorative effects of Curcuma wenyujin rhizoma on acute blood stasis in rats. World J Tradit Chin Med 2022;8:141-52

How to cite this URL:
Hao M, Zhao MT, Tong HJ, Ji D, Li L, Su LL, Gu W, Mao CQ, Lu TL. Ultra-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry based bile and urine metabonomics study on the ameliorative effects of Curcuma wenyujin rhizoma on acute blood stasis in rats. World J Tradit Chin Med [serial online] 2022 [cited 2022 Aug 8];8:141-52. Available from: https://www.wjtcm.net/text.asp?2022/8/1/141/336836




  Introduction Top


Blood stasis syndrome (BSS), named “Xueyu Zheng” in China, is an important pathologic condition in traditional Chinese medicine (TCM). The historical records of BSS can date back to “The Yellow Emperor's Classic of Medicine” in the pre-Qin times. Modern medical research has shown that the pathologic change in BSS is associated with an abnormal blood rheology index, including blood viscosity, hematocrit, erythrocyte sedimentation rate, red cell aggregation index, coagulant function, and microcirculation disturbance.[1],[2],[3] Furthermore, studies have also reported that BSS is closely related to thrombosis, inflammatory response, edema hyperplasia, and immunoreaction due to abnormal blood circulation and the viscous state of the whole body or individual organs.[4] The continuous progress of BSS can induce various diseases, including coronary heart disease, hypertension, cerebral infarction, dysmenorrhea, gastritis, and even cancer.[5],[6] In China, TCM doctors often use Chinese herbal medicine (CHM) and prescription to treat BSS, which has obtained significant clinical effects.[7] Curcuma wenyujin rhizome (CWR), which is known as “EZhu” in China, is one of the most commonly used CHMs for treating BSS.[8] It mainly contains sesquiterpene volatile oils and slight curcuminoids. Previous studies have shown that β-elemene, curcumol, germacrone, curdione, and curcumin are the potential active material bases in CWR.[9],[10],[11] In clinical practice in China, CWR has a significant therapeutic effect in various BSSs, such as amenorrhea, dysmenorrhea, atherosclerosis, and other diseases. However, until now, its biological activity mechanism remains unclear because of the multi-component and multi-target nature of the curative effect of CHMs.

Dynamic balance is a common characteristic of every life system. When living organisms are stimulated by exogenous stimuli such as drug treatment, environmental influences, and dietary habits, the dynamic balance of the life system changes over time. In addition, the occurrence and development of diseases can cause homeostasis disorders in living organisms. At present, systems biology offers a holistic integrative approach for studying complicated, dynamic life systems.[12] Metabolomics is an important method in the field of systems biology that uses advanced analytical chemistry technology combined with complicated statistical methods to comprehensively characterize the complete collection of metabolites, or small molecule chemicals, found in a given cell, organ, biofluid (plasma, bile, or urine), or organism.[13] In recent years, metabolomics has been widely applied as an innovative, integral diagnostic tool to identify biomarkers in living organisms and helps to promote the modernization of CHM. Therefore, it is meaningful to apply metabolomics to study the therapeutic effects and mechanisms of CWR in BSS. Urine and bile are important body fluids for animal bodies, which mainly reflect the metabolism of the kidneys and liver. Changes in their metabolites are of great significance to the health of the body. Most of the current research on metabolomics is directed at blood samples. There are relatively few studies on urine metabolomics and fewer studies on bile metabolomics.

In this study, bile and urine metabolomics combined with ultra-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry (UPLC-Q/TOF-MS) methods were used to explore the mechanism of CWR in the treatment of BSS. Potential biomarkers associated with the disordered pathways of CWR in treating BSS were screened to better understand the pharmacological mechanisms of CWR.


  Materials and Methods Top


Chemicals and materials

Acetonitrile, methanol, and formic acid were obtained from Merck. Co. Inc. (Darmstadt, Germany). Ultrapure water (electrical resistivity >18MΩ cm, 25°C) was obtained from a Milli-Q system (Millipore, Bedford, MA, USA). Prothrombin time (PT), activated partial thrombin time (APTT), thromboplastin time (TT), and fibrinogen (FIB) were obtained from Beijing Steellex Scientific Instrument Co., Ltd., (Beijing, China). Adrenaline hydrochloride injection (AHI) was purchased from Suicheng Pharmaceutical Co., Ltd. (Henan, China). Compound salvia tablets (CST) were purchased from Yunnan Tongda Biopharmaceutical Co., Ltd. (Yunnan, China).

CWR was purchased from Rui-an city in Zhejiang province and was identified by Professor Tulin Lu at the College of Pharmacy, Nanjing University of Chinese Medicine. The samples were steamed for 1.5 h and cut into 3 mm-thick sections, then oven-dried at 60°C according to the Chinese Pharmacopeia 2020 Edition.

Preparation of water extract of Curcuma wenyujin rhizome

One kilogram of CWR sample was added with tenfold aqua destillata and immersed for 30 min. Then, the samples were decocted for 30 min and percolated with four layers of gauze. The residue was extracted again using the same method. After that, the two extracts were merged and concentrated under reduced pressure to a volume of 500 mL (equivalent to 2 g/mL) of crude medicinal herb, using Heidolph Laborota at 55°C. CST was dissolved in aqua destillata to a concentration of 1 mg/mL. The samples were stored at 4°C for subsequent experiments.

Animal model and protocol

Thirty-two male standard deviation rats (Qinglong Mountain Animal Breeding Farm, Nanjing, China) weighing 180 ± 20 g were used in this study (animal license no.: SYXK (Su) 2017-0001). The acute blood stasis (ABS) rat model was built following the method in the literature.[14],[15] Prior to the experiment, the rats were acclimated in a laboratory animal room at 20°C ± 2°C, 55% ±5% humidity, and a periodic cycle of 12 h light/darkness. The rats were fed standard food with free water intake. After 7 days of acclimatization, the rats were used for the experiment. The research protocol was approved by the Animal Laboratory Ethics Committee of Nanjing University of Chinese Medicine (SYXK (Su) 2017-0001).

Thirty-two rats were stochastically distributed into four groups with eight rats per group: Normal control (NC) group, ABS group, CWR group, and CST group (positive control). The CWR and CST groups were administered with CWR (4.5 g/kg per day) and CST (1.5 g/kg per day) extracts, respectively, by gavage for 7 days. The dosage was transformed according to the clinical equivalent dose for rats (4.5 g/kg = 10 g/70 kg × 6.3 × 5; 10 g is the human clinical dose, 70 kg is the average body weight of humans, 6.3 represents the conversion coefficient for rats, and 5 represents five times the human clinical dose). The NC and ABS groups were intragastrically infused with normal saline. The ABS model was built on the 14th day, 1 h after hypodermic injection of 0.1% AHI 0.8 mL/kg. After 2 h, the rats were allowed to swim in 0–4°C ice water for 5 min. After another 2 h, a hypodermic injection of 0.1% AHI 0.8 mL/kg was administered again. The experimental cycle is shown in [Figure 1]. Afterward, 12 h of urine was collected using metabolic cages. Then, the rats were anesthetized by hypodermic injection with 10% chloraldurate. Four hours of bile samples were collected by common bile duct drainage, and blood samples were collected from the aorta abdominalis. During the experiment, all rats had free access to tap water.
Figure 1: Rat experimental cycle

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Pharmacological indexes detection

Whole blood viscosity (WBV) and plasma viscosity (PV) were measured using a blood rheometer (SA-5000; Beijing Steellex Scientific Instrument Company, China). APTT, PT, TT, and FIB were detected according to the manufacturer's instructions.

Bile and urine test products preparation

The bile and urine samples were taken from a −80°C refrigerator and unfrozen to ambient temperature. A 0.2 mL aliquot of bile sample was added with 1.2 mL methyl alcohol. The samples were shaken fiercely for 0.5 min by a mixer. The samples were centrifuged at 12,000 rpm at 4°C for 10 min. The supernate was transferred to a 1.5 mL centrifuge tube and freeze-dried for 4 h to complete solvent volatilization. Then, 400 μL of methanol was added to redissolve the bile sample. The mixture was centrifuged at 12,000 rpm at 4°C for 10 min. Then, 100 μL of the supernate was placed in a sample bottle for subsequent detection. For the urine sample, 0.8 mL methyl alcohol was added to 0.2 mL of urine sample. The samples were shaken violently for 0.5 min by a mixer. The mixture was centrifuged at 12,000 rpm at 4°C for 10 min. Then, 100 μL of the supernate was placed in a sample bottle for subsequent detection.

Ultra-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry analysis condition

Mass spectrum analysis was performed using a Shimadzu UPLC (Japan) combined with an AB SCIEX Triple TOF 5600 + system. The chromatographic conditions were: Agilent C18 reversed phase column (2.1 mm × 100 mm, 1.8 μm); mobile phase A (acetonitrile), mobile phase B (0.1% formic acid water); gradient elution method: 0–1 min, 5%~25% A, 95%~75% B; 1–3 min, 25%~30% A, 75%~70% B; 3–13 min, 30%~55% A, 70%~45% B; 13–15 min, 55%~70% A, 45%~30% B; 15–25 min, 70%~100% A, 30%~0% B; velocity of flow: 0.3 mL/min; column temperature: 35°C; injection volume: 1 μL. The mass spectrometer conditions were: Electrospray ionization source, positive and negative ion mode; declustering potential: +60/−60 V; ion spray voltage floating: +4500/−4500 V; source temperature: 550°C; collision energy: +35/−35 eV; atomizing gas: N2; curtain gas: 35 psi; gas1 (nebulizer gas): 55 psi; gas2 (heater gas): 55 psi; MS/MS spectrometry mode; MS spectrometer ion scanning range: 100–2000 m/z; MS/MS spectrometer ion scanning range: 50–1000 m/z; dynamic background subtraction: Turned on.

Methodology verification

Quality control (QC) samples were prepared by taking 10 μL of each bile/urine sample from the four groups and evenly mixing them. Before testing, the QC sample was continuously injected 6 times to ensure system suitability. In addition, the QC sample was injected after every 5 samples to ensure system consistency. The relative standard deviations of the intensity and retention time of the identified metabolites were <3% indicating that the system suitability and consistency were fine.

Data analysis

The original UPLC-Q/TOF-MS data were acquired using Analyst TF 1.6 software (AB Sciex, USA). Peak detection, alignment, and normalization were performed using MarkerView 1.2.1 software (AB Sciex, USA). The detailed parameters were set as follows: Minimum peak width: 25 ppm; noise threshold: 100; minimum RT peak width: 6 scans; RT tolerance: Within 0.5 min; mass tolerance: Within 10 ppm. After that, the original UPLC-Q/TOF-MS data were converted into a three-dimensional (3D) information matrix containing RT-m/z values, sample numbers, and normalized peak areas. The 3D information matrix was then input to Simca-P14.1 software (Umetrics AB, Sweden) for multivariate statistical analysis, including principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA). The PCA models were used to overview the metabolic fingerprint spectrum of bile/urine samples in the NC, ABS, and CWR groups. OPLS-DA models were used to filter the metabolites between the ABS and CWR groups.[16] The R2X (cum), R2Y (cum), and Q2X (cum) values of the model were important parameters for estimating its feasibility. The R2X (cum) value represents the cumulative interpretability of the variables in the X axis, the R2Y (cum) value represents the cumulative interpretability of the variables in the Y-axis, and the Q2 (cum) value indicates the predictive ability of the model. The closer the values of R2X (cum), R2Y (cum), and Q2 (cum) parameters are to 1, the better the prediction performance of the model. Permutation tests were conducted to verify the reliability of the established OPLS-DA models. The number of permutations for the permutation test was 200.[17] A scatter plot (S-plot) was used to identify possible endogenous biomarkers among the different groups. The variable importance in projection (VIP) value of the OPLS-DA model represents the contribution degree of the variables.[18]

One-way analysis of variance was conducted using SPSS 20.0 (Chicago, IL, USA) to estimate the pharmacological indexes. The significance threshold was set at P < 0.05. T-test was conducted using SPSS 20.0 (Chicago, IL, USA) to estimate the identified potential biomarkers. The significance threshold was set at P < 0.05.

Metabolic pathway analysis

MetaboAnalyst 5.0 online software was used to discover significant changes in metabolic pathways that were affected by the preadministration of CWR in the ABS model. The specific analysis parameters were as follows: Visualization method: Scatter plot; enrichment method: Hypergeometric test; topology analysis: Relative betweenness centrality; reference metabolome: Use all compounds in the selected pathway library; pathway library: Rattus norvegicus (rat).


  Results Top


Pharmacological indexes evaluation

At present, hemorheology and blood coagulation factors are the primary effect parameters for ABS. In this study, WBV, PV, APTT, TT, PT, and FIB were tested, and the results are shown in [Table 1] and [Table 2]. Compared with the NC group, WBV, PV, and the four blood coagulation indexes in the ABS group were significantly increased (P < 0.05). Compared with the ABS group, these parameters in the CWR groups were significantly decreased (P < 0.05). This result indicates that the ABS model was successfully built and the CWR groups had a significant curative effect on ABS.
Table 1: Effect of curcuma wenyujin rhizome on hemorheology of acute blood stasis rats (x¯ ± s, n = 10)

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Table 2: Effect of curcuma wenyujin rhizome on thromboplastin time, prothrombin time, activated partial thrombin time and fibrinogen of acute blood stasis rats (x¯ ± s, n = 10)

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Bile and urine metabolomics analysis

The total ion chromatograms (TIC) of the bile and urine metabolic profiles from different groups are shown in [Figure 2]. Based on the TICs, the metabolic profiles of the different groups have no significant variation. Thus, unsupervised PCA and supervised OPLS-DA models were conducted to delve further into small molecule metabolites in each group. The PCA and OPLS-DA models of bile and urine samples in different groups are shown in [Figure 3] and [Figure 4]. Each point in the PCA or OPLS-DA model represents a bile/urine sample. As shown in [Figure 3] and [Figure 4], it can be seen that the NC, ABS, and CWR groups were separated from each other significantly, which indicates that the small molecule metabolites were significantly changed after CWR preadministration. The parameters of the PCA and OPLS-DA models are shown in [Table 3]. The main parameters of the PCA and OPLS-DA models were >0.65 indicating that the predictive ability of the models was fine. The permutation test results are shown in [Figure 5]. Q2 <0 indicates that the OPLS-DA models are valid. S-plots of the OPLS-DA model are shown in [Figure 6], where each dot in the S-plot represents a fragment ion (ion m/z-RT pair). The X and Y axes of the S-plot represent the contribution degree and confidence coefficient of the variables, respectively. The greater the distance from a dot to the origin, the greater the contribution to the classification. Thus, the dots at both ends of the S-plot represent potential biomarkers with the highest contribution.[19]
Figure 2: Ultra-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry total ion chromatograms of bile samples among normal control, acute blood stasis, and Curcuma wenyujin rhizome groups in electrospray ionization + mode (a) and electrospray ionizationI − mode (b); ultra-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry total ion chromatograms of urine samples among normal control, acute blood stasis, and Curcuma wenyujin rhizome groups in electrospray ionization + mode (c) and electrospray ionization − mode (d)

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Figure 3: Principal component analysis score plots of bile metabolic profiling of normal control, acute blood stasis and Curcuma wenyujin rhizome in electrospray ionization + mode (a) and electrospray ionization − mode (b); principal component analysis score plots of urine metabolic profiling of normal control, acute blood stasis and Curcuma wenyujin rhizome in electrospray ionization + mode (c) and electrospray ionization − mode (d) (One dot represent a bile or urine sample. Samples from different groups can be clearly distinguished, which indicating significant differences of different groups. The R2X (cum) and Q2 (cum) of principal component analysis model were all bigger than 0.65, indicating the model has good applicability)

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Figure 4: Orthogonal partial least squares-discriminant analysis model results of bile metabolic profiling of normal control/acute blood stasis and acute blood stasis/Curcuma wenyujin rhizome in electrospray ionization + mode (a and c) and electrospray ionization - mode (b and d); orthogonal partial least squares-discriminant analysis s-plots of urine metabolic profiling of normal control/acute blood stasis and acute blood stasis/Curcuma wenyujin rhizome in electrospray ionization + mode (e and g) and electrospray ionization - mode (f and h). (One dot represent a bile or urine sample. Samples from different groups can be clearly distinguished, which indicates significant differences of different groups. The R2X (cum), R2Y (cum) and Q2 (cum) of principal component analysis model were all bigger than 0.70, indicating the model has good applicability)

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Figure 5: Permutation test results of orthogonal partial least squares-discriminant analysis model of bile metabolic profiling of normal control/acute blood stasis and acute blood stasis/Curcuma wenyujin rhizome in electrospray ionization + mode (a and c) and electrospray ionization - mode (b and d); Permutation test results of orthogonal partial least squares-discriminant analysis model of urine metabolic profiling of normal control/acute blood stasis and acute blood stasis/Curcuma wenyujin rhizome in electrospray ionization + mode (e and g) and electrospray ionization - mode (f and h). (Q2 <0 indicated that the orthogonal partial least squares-discriminant analysis models are valid)

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Figure 6: Orthogonal partial least squares-discriminant analysis s-plots of bile metabolic profiling of normal control/acute blood stasis and acute blood stasis/Curcuma wenyujin rhizome in electrospray ionization + mode (a and c) and electrospray ionization − mode (b and d). orthogonal partial least squares-discriminant analysis s-plots of urine metabolic profiling of normal control/acute blood stasis and acute blood stasis/Curcuma wenyujin rhizome in electrospray ionization + mode (e and g) and electrospray ionization − mode (f and h).(each dot in the S-plot on behalf of a fragment ion (ion m/z-Rt pair). The X/Y axis of S-plot represented the contribution degree/confidence coefficient of the variables, respectively. The distance from a dot to the origin more further, the greater contribution to classification. Thus, the dots at both ends of the S-plot represented potential biomarkers with the highest contribution)

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Table 3: Parameters of principal component analysis and orthogonal partial least squares-discriminant analysis models

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Potential metabolite biomarkers identification

The significant fragment ions (ion m/z-RT pair) that contributed to classification were screened by VIP >1.0 and P < 0.05 of the t-test. Afterward, the identification of these fragment ions was done using the Human Metabolome Database, MassBank, Chemspider, and Pubcompound databases and references. The potential metabolite biomarkers that were identified are listed in [Table 4].
Table 4: Potential biomarkers in bile and urine associated with acute blood stasis based on the ultra-performance liquid chromatography-quadrupole-time-of-flight/mass spectrometry analysis

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Metabolic pathway analysis result

A summary of the metabolic pathway analysis with Met PA is shown in [Figure 7], in which the X-axis represents the metabolic pathway impact value according to the topology analysis. The Y-axis (-logP) represents the significance of the pathway enrichment analysis. The larger the X-and Y-axis values, the stronger the correlation between the metabolic differences among the NC, ABS, and CWR groups. In [Figure 7], the circle changing from yellow to red indicates that the pathway impact value increased, and the circle becoming larger indicates that the-log P value is enhanced. The red block represents the identified potential endogenous metabolite markers. In this research, when the X-axis is >0.10, the metabolic pathway has a significant effect on ABS, according to reference.[19] The pathway analysis results show that the disordered pathways of ABS and CWR treatment were linoleic acid metabolism, arachidonic acid metabolism, glycerophospholipid metabolism, pentose and glucuronate interconversions, sphingolipid metabolism, steroid hormone biosynthesis, primary bile acid (BA) biosynthesis, pentose phosphate pathway, and glycine, serine, and threonine metabolism [Table 5]. In order to visually display the differences between different groups, the area normalization values of the 27 differential metabolites in bile and urine samples are displayed with box plots in [Figure 8].
Figure 7: Summary of pathway analysis with MetPA. (The x axis represents pathway impact value. The y axis (-logP) represents the significance of the metabolic pathway. The circle from yellow to red indicates pathway impact value increased, and the circle tend big represents the –logP value enhanced. The red block represents the identified potential endogenous metabolite markers.)

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Figure 8: The box plots of 27 Potential biomarkers. (#, compared with normal control group, P < 0.05; ##, compared with normal control group, P < 0.01; *, compared with acute blood stasis group, P < 0.05; **, compared with acute blood stasis group, P < 0.01.)

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Table 5: Pathway analysis result with MetaboAnalyst 5.0

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  Discussion Top


Model evaluation

Hemorheology is an emerging branch of biomechanics and biorheology, which studies the macroscopic flow properties of blood, blood flow, and cell deformation in humans and animals, and the interaction between blood, blood vessels, and the heart, as well as the flow properties of blood cells. Blood coagulation is a process in which the blood state changes from a normal flowing state to a nonflowing gel state. This is an important process in physiological hemostasis. The intrinsic quality of blood coagulation involves a series of enzymatic activation of coagulation factors. Currently, doctors primarily assess the state of the intrinsic and exogenous coagulation systems in patients according to four coagulation indexes involving PT, APTT, TT, and FIB. TT refers to the time it takes for FIB to convert into fibrin, which reflects the common coagulation pathway. APTT reflects the inherent coagulation pathway. PT reflects the exterior coagulation pathway.[20] FIB refers to the FIB content. Hemorheology and the four-blood coagulation parameters are the main parameters used to assess blood stasis-related diseases. In this study, CWR had a significant effect on ABS model rats according to the hemorheology and four blood coagulation parameters.

Metabolic pathway analysis

According to the metabolic pathway analysis results, ABS was mainly correlated with lipid metabolism, including linoleic acid metabolism, arachidonic acid metabolism, glycerophospholipid metabolism, and sphingolipid metabolism, which is consistent with previous reports.[21],[22] In addition to lipid metabolism, ABS also has a certain relationship with pentose and glucuronate interconversions, steroid hormone biosynthesis, primary BA biosynthesis, pentose phosphate pathway, and glycine, serine, and threonine metabolism. CWR preadministration can significantly improve abnormal levels of metabolites in these pathways.

Linoleic acid is an n-6 polyunsaturated fatty acid (PUFA), which is also the most abundant PUFA in human food. Linoleic acid is regarded as an essential fatty acid because human cells cannot insert double bonds beyond C9, and hence neither in the n-6 nor in the n-3 position in the fatty acid chain. In a living organism, linoleic acid can be extended and desaturated into other bioactive γ6 PUFAs, including γ-linolenic acid and arachidonic acid. Afterward, arachidonic acid can be transformed into abundant bioactive components named eicosanoids, such as thromboxane A2, prostaglandins, and leukotrienes. These eicosanoids are crucial in the daily metabolic response of cells and tissue organs in the body, and when continuously overproduced, they are considered to lead to various chronic diseases, such as inflammation and cancer. For instance, abnormal TXA2 may stimulate platelet aggregation, angiospasm, and thrombogenesis, which can be induced to stenocardia, coronary occlusion, and cerebrovascular accidents.[23] This conversion to arachidonic acid may be the reason linoleic acid obtained the most infamy.[24] However, in recent years, vast observational data have indicated that increased food intake or tissue content of linoleic acid is related to a decreased morbidity of cardiovascular functional disorders (primarily coronary diseases) and of new-onset metabolic syndrome or type 2 diabetes. The function of linoleic acid in other pathophysiological fields is poorly understood. High-quality clinical tests are necessary to evaluate the actual value and potential mechanisms of the health influences related to food intake of this essential fatty acid.[25] In this study, arachidonic acid and linoleic acid from the ABS group to the NC group were significantly upregulated and reversed by CWR preadministration. Thus, we considered that the pro-inflammatory role of arachidonic acid might be one of the reasons for the formation of BSS.

Lysophosphatidylcholine (LPC), the main active component of oxidized low-density lipoprotein (ox-LDL), is a crucial endogenous metabolite in lipid metabolism, which also has a wide range of biological effects. LPC is a main ingredient of platelet-derived microvesicles, which can induce platelet activation, proliferation, migration, and aggregation, and finally leading to vascular inflammation by its mutual effect with the G2A receptor on platelets.[26] Previous studies have shown that LPC can induce the migration of leukomonocytes and macrophagocytes, stimulate the generation of proinflammatory cytokines, promote oxidative stress, and induce apoptosis, which can aggregate inflammation and promote the development of diseases. The functions of LPC in endothelial cells, vascular smooth muscle cells, and arteries play an important role in the process of atherosclerosis and other cardiovascular disorders. Moreover, the regulation of inflammation by LPC plays different roles in inflammatory and infectious diseases.[27] In this study, metabolites in glycerophospholipid metabolism, including PC (14:0/20:2 [11Z,14Z]), PE (15:0/22:2 [13Z,16Z]), phosphorylcholine, glycerylphosphorylethanolamine, PE (22:6 [4Z,7Z,10Z,13Z,16Z,19Z]/20:0), and LysoPC (16:0), returned to normal levels by CWR preadministration, indicating that glycerophospholipid metabolism plays an important role in the formation and cure of BSS.

Sphingolipids are a class of amphoteric lipids containing a sphingosine backbone. One end is connected to a long-chain fatty acid, and the other end is a polar alcohol. It is well known that sphingolipid metabolites play a crucial role in inflammatory signaling, differentiation, senescence, and apoptosis. Sphingomyelin, sphinganine, and phytosphingosine are the primary metabolites of the sphingolipid metabolic pathway. Previous reports have shown that all three - sphingomyelin, sphinganine, and phytosphingosine - take part in the regulation of vascular growth and vascular tone that might be the potential mechanism by which these putative biochemical modulators of hypertension and atherosclerosis act.[28] In this study, metabolites in sphingolipid metabolism, including Sm (d18:1/16:0), sphinganine, and phytosphingosine, were all returned to normal levels by CWR preadministration. Aside from the above metabolic pathways, metabolites in pentose and glucuronate interconversions, steroid hormone biosynthesis, primary BA biosynthesis, and pentose phosphate pathway also recovered to the level of the NC group. In addition, BA is an important component of bile and plays an important role in lipid metabolism. BA is the end product of cholesterol metabolism. Abnormal BA metabolism is closely associated with abnormal regulation of blood lipids.[29] In this study, Sm (d18:1/16:0), sphinganine, and phytosphingosine identified from urine samples were important components of lipid metabolism. Taurocholic acid, taurochenodesoxycholic acid, chenodeoxycholic acid glycine conjugate, and cholic acid were important components of BA metabolism. These metabolites were all restored to the level of the NC group after CWR preadministration. However, the relationship between the metabolites from bile and urine samples needs to be further studied.


  Conclusions Top


In short, metabolomics combined with multivariate statistical analysis provides a useful means to explore the pharmacological mechanism of CWR on ABS. The pharmacological results indicated that CWR could significantly reduce the hemorheology and four blood coagulation indexes of ABS model rats. In addition, bile and urine metabolomics revealed that 27 potential metabolite biomarkers in linoleic acid metabolism, arachidonic acid metabolism, glycerophospholipid metabolism, pentose and glucuronate interconversions, sphingolipid metabolism, steroid hormone biosynthesis, primary BA biosynthesis, pentose phosphate pathway, and glycine, serine, and threonine metabolism might be linked to CWR prevention in ABS. Therefore, our research illustrates that the liquid chromatography-MS metabolomics method would be powerful for clarifying the mechanisms of CWR in blood stasis.

Financial support and sponsorship

This research was financially supported by the National Natural Science Foundation of China (81673598, 81973483, 82003948), Natural Science Foundation of Zhejiang Province (LQ21H280002), The National Key Research and Development Program of China (2018YFC1707000), the National traditional Chinese medicine industry special project (2015468002-2), National Standardization Program for Chinese Medicine (ZYBZH-Y-SC-40), and Zhejiang Chinese Medicine University School-level Scientific Research Fund for Talents (2020ZR14).

Conflicts of interest

There are no conflicts of interest.



 
  References Top

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    Figures

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