|Year : 2019 | Volume
| Issue : 2 | Page : 71-80
Standardized Xin-Ke-Shu tablets improves the disturbances of lipid, energy, and amino acid metabolism in a rabbit model of atherosclerosis
Yong Yang, Jing-Bo Peng, Meng Yu, Hong-Mei Jia, Hong-Wu Zhang, Zhong-Mei Zou
Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
|Date of Submission||19-Jan-2019|
|Date of Acceptance||28-Mar-2019|
|Date of Web Publication||20-Jun-2019|
No. 151, Malianwa North Road, Haidian District, Beijing 100193
Source of Support: None, Conflict of Interest: None
Objective: Xin-Ke-Shu (XKS), a patent drug, used to treat coronary artery diseases in China for many years. Previous research indicates that XKS has similar therapeutic effect as atorvastatin (AS) against atherosclerotic in rabbits. However, biochemical assays demonstrate that XKS could have a different therapeutic mechanism from AS. The aim of this study is to explore the mechanism of XKS therapeutic effect, especially those different from AS. Materials and Methods:1H nuclear magnetic resonance-based metabonomics were applied to profile the low-molecular-weight polar metabolites in the plasma of rabbits fed a high cholesterol diet. Results: Seven of the eleven pathological biomarkers related to atherosclerosis in rabbits were mediated by XKS treatment, namely low-density lipoprotein/very-low-density lipoprotein (LDL/VLDL), lactate, citrate, phosphatidylcholine, glutamine, creatinine, and methionine, as well as two characteristic metabolites of pyruvate and α-glucose. These metabolites involved lipid, energy, and amino acid metabolism, and all could be considered XKS treatment targets. However, AS only affected the metabolic disorders associated with LDL/VLDL and phosphatidylcholine, which is mainly target lipid metabolism. Conclusions: This study indicates that the anti-atherosclerosis effects of AS mainly involve reducing blood–lipid levels, but those of XKS involve a multitargeted activity.
Keywords: 1H nuclear magnetic resonance, atherosclerosis, plasma metabonomics, polar small molecules metabolites, Xin-Ke-Shu
|How to cite this article:|
Yang Y, Peng JB, Yu M, Jia HM, Zhang HW, Zou ZM. Standardized Xin-Ke-Shu tablets improves the disturbances of lipid, energy, and amino acid metabolism in a rabbit model of atherosclerosis. World J Tradit Chin Med 2019;5:71-80
|How to cite this URL:|
Yang Y, Peng JB, Yu M, Jia HM, Zhang HW, Zou ZM. Standardized Xin-Ke-Shu tablets improves the disturbances of lipid, energy, and amino acid metabolism in a rabbit model of atherosclerosis. World J Tradit Chin Med [serial online] 2019 [cited 2019 Jul 19];5:71-80. Available from: http://www.wjtcm.net/text.asp?2019/5/2/71/257412
| Introduction|| |
Coronary artery disease (CAD), a combination of fatty material, calcium, and plaque buildup inside the coronary arteries, is the most frequent cause of death worldwide. The underlying pathological process includes lipid deposition, oxidation, and modifications that provoke chronic inflammation at susceptible sites in the walls of all major conduit arteries. Hence, an effective therapy should reduce hyperlipidemia and prevent thrombosis. Statins are well known to reduce major cardiovascular events by lowering low-density lipoprotein (LDL) cholesterol levels. However, despite the promising effects of statins on CAD, their adverse effects (including glucose metabolic disorder, myolysis, and hepatotoxicity) during long-term administration are still a concern.,, This has provided worldwide incentive to continue to discover new drugs for CAD prevention and therapy.
Traditional Chinese medicine (TCM) formula are multicomponent medicines that have a holistic therapeutic effect with better therapeutic efficacy and fewer side effects., The use of TCM for the treatment of complex, multifactorial diseases, such as CAD, has garnered much interest, especially in the past decades. Xin-Ke-Shu (XKS) tablet, an herbal compound prescription composed of the root of Aucklandia lappa Decne (Mu-Xiang), fruit of Crataegus pinnatifida Bge. (Shan-Zha), root of Panax notoginseng (Burk.) F. H. Chen. (San-Qi), root of Pueraria lobata (Willd.) Ohwi. (Ge-Gen), and root of Salvia miltiorrhiza Bge. (Dan-Shen), is a standardized patent medicine extensively used in the clinical treatment of CAD in China. It has been manufactured by good manufacturing practice pharmaceutical company and quality-controlled using liquid chromatography (LC)-LTQ-Orbitrap mass spectrometry (MS). Previous research indicates that XKS has similar therapeutic effect as atorvastatin (AS) against atherosclerotic in rabbits. However, biochemical assays demonstrate that XKS could have a different therapeutic mechanism from AS, which the molecular mechanism is still not fully clear.
Evaluation the efficacy and reveal the underlying pathophysiologic mechanism of TCM is a great challenge. The emergence of metabonomics approach provides a powerful method for the study of TCM prescription, which the integrity and systemic features of metabonomics highly coincide with the holistic basis for TCM. It has been widely used in pharmaceutical research and development, including drug therapy monitoring and drug safety assessment., As the two main analytical spectroscopic approaches in metabonomics, MS and 1H nuclear magnetic resonance (1H NMR) spectroscopy usually offering complementary information, but with different operational performance characteristics. 1H NMR-based metabonomics has the advantages of being rapid, unbiased, reproducible, quantitative, nondestructive, and amenable to high-throughput analyses. It is a powerful approach to selectively profile specific metabolites (e.g. polar small metabolites) in complex biological systems,, which these metabolites are difficult to detect by MS spectrometry because of the limitation of the polar small metabolites hard retained on an LC column, not ionizable in MS sources and suffer severe matrix effects during MS analysis.
Our previous LC-MS-based metabolomics study demonstrates that the action of XKS against AS primarily inhibit the perturbation of small, nonpolar metabolites, which involve lipid-related pathways, including arachidonic acid metabolism, glycerophospholipid metabolism, and fatty acid β-oxidation. Some small polar metabolites, especially amino acid and energy metabolism-related metabolites, which are hard to detect by LC-MS technique, play vital roles in the formation of AS.,, However, the regulatory effects of XKS on these specific metabolites are still unclear.
Therefore, in the present study, to unveil a more detailed mechanism of XKS activity, we used 1H NMR-based metabonomics, to profile the small, polar metabolites in the plasma of rabbits fed a high cholesterol diet (HCD). In addition, multivariate analysis and pattern recognition were used to assess the therapeutic effects of XKS and to identify significantly altered metabolites, and the metabolic pathways involved in XKS or AS treatment.
| Materials and Methods|| |
Materials and reagents
Standard XKS tablets, containing the root of A. lappa (Mu-Xiang), the root of P. notoginseng (San-Qi), the fruit of C. pinnatifida Bge. (Shan-Zha), the root of P. lobata (Ge-Gen), and the root of S. miltiorrhiza (Dan-Shen) (1:1:15:15:15, w/w), were produced by Wohua Pharmaceutical Co., China (batch No. 090629). Quality control of the XKS tablets was accomplished using an LC-LTQ-Orbitrap approach. Cholesterol was purchased from Tian Qi Chemical Engineering Co., China. AS was purchased from Jialin Pharmaceutical Co., China. Deuterium oxide (D2O, 99.9%) was purchased from Sigma-Aldrich (St. Louis, USA). Ultrapure water (18.2 MΩcm) was prepared with a Milli-Q® Water Purification System (Millipore, France). All other chemicals were of analytical grade.
Twenty-four male Japanese white rabbits (weighing 2.2 ± 0.2 kg, aged 3 weeks) were purchased from the Laboratory Animal Institute of the Chinese Academy of Medical Science (Beijing, China). All animal experiments were performed under the Control and Approval of the Ethics Committee of the Institute of Medicinal Plant Development, CAMS (Beijing, China). The rabbits were housed individually in cages with food and water freely available. The rabbits were acclimatized to the facilities for a week prior to experimentation. All of the animals were handled humanely throughout the experiment.
Animal handling and sample collection
Establishment of the HCD-induced AS rabbit model, drug administration, and plasma sample collection was the same as described previously. Briefly, after 1 week of acclimatization, the rabbits were randomly divided into four groups (n = 6 per group) according to their body weights: (A) control group, (B) model group, (C) AS group, (D) XKS-fed group. The rabbits in Group A were fed with standard rabbit chow (SC), those in Group B were fed with HCD (standard rabbit chow supplemented with 0.1% thiamazole, 3% cholesterol, 0.7% sodium cholate, w/w/w), those in Group C fed with HCD and AS (4 mg/kg/day), and those in Group D were fed with HCD and XKS tablets (0.34 g/kg/day). The duration of the treatment was 12 weeks.
Blood samples were collected from the ear vein with sodium-heparin tubes. Then, the plasma was separated by centrifugation at 3600 rmp for 10 min at 4°C and stored at −80°C until analysis. At the end of the experiment, all rabbits were euthanatized and autopsied. The aortas were separated from aortic arch to the end piece of the thoracic aorta, then immediately fixed in 10% neutral-buffered formalin (w/v) for histopathological evaluation.
Plasma biochemistry assays and histopathology
The degree of atherosclerosis was evaluated by determining the total cholesterol (TC), triglyceride (TG), and low-density lipid-cholesterol (LDL) activities in the plasma using HITACHI 7060 automatic analyzer.
Histopathological changes of aortas were investigated by Sudan IV staining to measuring the atherosclerotic plaques ratio on the aortas. The aortas were scanned using NanoZoomer Digital Pathology image analysis system (Hamamatus, JAP). Image analysis was carried out using Image-Pro Plus (Version 5.0). Coronary stenosis ratio (%) was expressed as lesion area/total area of the aorta × 100%.
1H nuclear magnetic resonance spectroscopic analysis
The NMR analysis methods have been described previously. Briefly, 300 μL of 0.9% NaCl (w/v) solution containing 20% D2O as a field lock was added to 300 μL aliquots of plasma samples and then thoroughly mixed. The mixture was centrifuged at 12,000 rmp at 4°C for 10 min. The supernatant (550 μL) of each sample was then transferred into a 5-mm o.d. NMR tube for analysis. All of the samples were acquired at 300 K using a Bruker AVIII 600 MHz spectrometer (Karlsruhe, Germany) equipped with an inverse 5-mm Bruker probe at 600.13 MHz 1H frequency.
1H NMR spectra of plasma were acquired using the water-suppressed CPMG spin-echo pulse sequence (RD-90°-(τ-180°-τ)n-ACQ). Spin-echo loop times (2nτ) of 35 ms were applied to attenuate broad NMR signals from proteins and lipids and retain those from small metabolites and some lipid components. The 90° pulse length was adjusted to approximately 10 μs; and 128 transients were collected into 72 k data points for each spectral width of 20 ppm with a recycle delay (RD) of 4 s. The acquisition time was 3.07 s.
Nuclear magnetic resonance data preprocessing
The NMR data preprocessing protocol was described previously. Before Fourier transformation, all acquired free induction decay data points were zero filled to 128 K and multiplied by an exponential function equivalent to a 0.5 Hz line-broadening factor. The NMR spectra were automatically phased and baseline-corrected using Topspin 2.1 software (Karlsruhe, Germany). All of the spectra were referenced internally to the methyl resonance of lactate at δ 1.33. The region δ 4.67–5.10 was removed to avoid the effect of water suppression. Using the AMIX software package (v3.9.2, Karlsruhe, Germany), the spectral region δ 0.5–4.67 and δ 5.10–9.5 were divided, and the signal integrals computed in 0.01 ppm intervals. Before analysis, the data were normalized to the total sum of the spectra.
Multivariate statistical analysis
The integral data were imported into SIMCA software (v13.0, Umeå, Sweden) for multivariate statistical analysis and modeling. After Pareto scaling, principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal PLS-DA (OPLS-DA) were employed to process the acquired NMR data. PCA was performed to discern unsupervised separation among different groups of samples. The OPLS-DA model was used to screen variant ions contributing to the discrimination of different groups. On the basis of these analyses, according to the criteria of the variable importance for projection (VIP) > 1 and P < 0.05, variables were selected as key metabolites that contributed to differentiating control versus model group, XKS versus model group, and AS versus model group. The reliability of the PLS model was further validated rigorously by permutation test with a permutation number of 200.
Metscape (http://metscape.ncibi.org), a plugin for Cytoscape (v3.4.0, http://www.cytoscape.org), was used to construct the metabolic networks to further understand the pathogenesis of AS and the pharmacological mechanisms of XKS. The Human Metabolome Database (HMDB, www.hmdb.ca) and Kyoto Encyclopedia of Genes and Genomes (KEGG, www.genome.jp/kegg/) database were queried with the chemical shift of the metabolites.
Experimental values are presented as the mean ± standard deviation SPSS software package (v 20.0, Chicago, USA) was used for one-way ANOVA. The significance threshold was set at P < 0.05.
| Results|| |
Plasma biochemistry assays and histopathology
As shown in [Figure 1], compared with those in the control group, the concentrations of LDL, TC, and TG were markedly elevated (P < 0.001) in the model group. Compared with the model group, AS and XKS 12-week treatments resulted in a significant decrease of LDL, TC, and TG levels. However, the regulatory effect of AS on LDL, TC, and TG were more pronounced than the effect of XKS, indicating that the anti-AS effects of AS mainly by reduce blood–lipid levels.
|Figure 1: Low-density lipoprotein, total cholesterol, and triglyceride levels (mmol/L) in control, model-, atorvastatin (positive)-, and Xin-Ke-Shu-treated groups. Data were expressed as mean ± standard deviation (n = 6). ***P < 0.001 compared with control group;#P < 0.05;##P < 0.01;###P < 0.001 compared with model group|
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As shown in [Figure 2]a, pathological changes of atherosclerotic plaques in the initial surface of the aortas were apparent in the model group after 12-week feeding with HCD. Treatment with AS and XKS for 12-week induced a significantly reduce in atherosclerotic plaques area ratio compared to the model group [Figure 2]b. In addition, AS and XKS treatment have similar therapeutical effect on atherosclerotic plaques. Biochemistry assays combined with histopathology results indicated that treatment with XKS and with AS may utilize different mechanisms against AS induced by HCD.
|Figure 2: (a) Representative photographs of the atherosclerotic plaques on aortas by Sudan IV staining. A: Control group; B: Model group; C: Atorvastatin group; D: Xin-Ke-Shu group. (b) Graph shows the mean values of atherosclerotic plaques area ratio in each group (data were expressed as mean ± standard deviation, n = 6). ***P < 0.001 compared with control group;##P < 0.01 compared with model group|
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1H nuclear magnetic resonance spectra of plasma samples
Representative 600 MHz 1H NMR CPMG spectra of plasma from control, model, AS treatment, and XKS treatment groups are shown in [Figure 3]. Major metabolite resonances were assigned and were labeled in the spectra.
|Figure 3: 600 MHz Typical 1H nuclear magnetic resonance (δ 8.6–6.8, 5.4–5.10, 4.70–0.50) CPMG spectra of plasmas sample of control group (C), model group (M), atorvastatin treatment group (A), and Xin-Ke-Shu treatment group (X). Key: NAG: N-acetyl-glycoprotein; OAG: O-acetyl-glycoprotein; PC: Phosphatidylcholine|
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Statistical analysis of plasma samples
To evaluate the treatment effects of XKS and AS, unsupervised PCA and supervised PLS-DA were employed. The PCA score plots show that there are no outliers (beyond the 95% confidence interval) in any of the samples [Figure S1]. PLS-DA [Figure 4] score plots show obvious separation between the model and control groups, suggesting that metabolic profiles significant changes induced by HCD. The metabolic profiles of rabbits in both the XKS- and AS -treated groups deviate from that of the model group and are close to that of the control group. XKS treatment normalized the metabolic profile better than AS treatment did, indicating that XKS treatment might be more effective at improving the deviations induced by AS. To validate the performance of the PLS-DA model, a permutation test (number: 200) was performed. The validation plot demonstrates that the original PLS-DA model was not overfit as both the R2 intercept (0.179) and Q2 intercept (-0.243) values are significantly lower than the corresponding original values [top right in [Figure 4].
|Figure 4: Partial least squares discriminant analysis score plot (a: R2X = 0.348, R2Y = 0.929, Q2=0.354) of plasma samples from control group (blue box), model group (red circle), atorvastatin group (black box), and Xin-Ke-Shu group (green box); (b) Validation of partial least squares discriminant analysis score plot. Permutation test parameters (n = 200): R2intercept = 0.179, Q2intercept = −0.243|
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OPLS-DA models were built to distinguish the differences between experimental groups and screen the variations contributing to the corresponding classification [Figure 5]a, [Figure 5]b, [Figure 5]c. The VIP value (VIP > 1) combined with P < 0.05 was used as the criteria for selecting the differential variables. As a result, 20 variables were screened as differential variables. Among them, 13 metabolites were identified by literature and database resources (e.g., HMDB). Compared to that of the control group, the model group had higher LDL/VLDL (B1), lactate (B2), N-acetyl glycoproteins (B5), phosphatidylcholine (B6), glutamine (B8), betaine (B9), and individual amino acid levels (glycine B7, methionine B11, and tyrosine B12), but lower citrate (B3) and creatinine (B10) levels. Compared to that of the model group, the XKS group had lower levels of pyruvate (B4) and α-glucose (B13) [Table 1].
|Figure 5: Orthogonal partial least squares discriminant analysis score plots (left) and s-plots (right). Model group versus Control group (a: R2X = 0.609, R2Y = 0.998, Q2=0.953); Model group versus Atorvastatin treatment group (b: R2X = 0.384, R2Y = 0.906, Q2=0.446); Model group versus Xin-Ke-Shu treatment group (c: R2X = 0.655, R2Y = 0.999, Q2=0.950)|
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|Table 1: The potential biomarkers detected by 1H nuclear magnetic resonance of high cholesterol diet-induced atherosclerosis and their variation tendency|
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Metabolic changes of the biomarkers in atorvastatin rabbits associated with Xin-Ke-Shu and atorvastatin treatments
To further analyze the metabolic changes, the peak areas of these identified metabolites were compared using one-way ANOVA among the experimental groups. As shown in [Table 1] and [Figure 6], compared with that of the AS group, XKS treatment significantly reverses the levels of LDL/VLDL (B1), lactate (B2), citrate (B3), pyruvate (B4), phosphatidylcholine (B6), glutamine (B8), creatinine (B10), methionine (B11), and α-glucose (B13). Meanwhile, AS regulates only the metabolites of LDL/VLDL (B1) and phosphatidylcholine (B6). The results suggest that XKS treatment has more therapeutic targets against AS than AS does. It is worth noting that pyruvate (B4) and α-glucose (B13) were not significantly changed in the model group, but treatment with XKS significantly decreased their levels, suggesting that α-glucose and pyruvate might be related to the drug regulation effects of XKS treatments.
|Figure 6: The network of the potential biomarkers changing for atorvastatin, Xin-Ke-Shu, and atorvastatin modulation according to the KEGG pathway database. Column value in histograms is expressed as mean ± standard deviation (n = 6), the blue name means detected potential biomarkers in this work, blue box represents regulated metabolites both by Xin-Ke-Shu and atorvastatin treatment, green box represents regulated metabolites only by Xin-Ke-Shu treatment|
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Perturbed metabolic pathways in AS rabbits associated with Xin-Ke-Shu and atorvastatin treatments
Based on the identified biomarkers of pathological changes and drug regulation, the metabolic network was mapped using the KEGG database. Eight metabolic pathways, namely lipid metabolism (P1); glycolysis/gluconeogenesis (P2); citrate cycle (P3); glycine, serine, and threonine metabolism (P5); alanine, aspartate, and glutamate metabolism (P6); arginine and proline metabolism (P7); cysteine and methionine metabolism (P8); and tyrosine metabolism (P9) were altered in the plasma of HCD-induced AS rabbits. XKS treatment was able to normalize seven of the altered pathways, namely lipid metabolism (P1); glycolysis/gluconeogenesis (P2); citrate cycle (P3); alanine, aspartate, and glutamate metabolism (P6); arginine and proline metabolism (P7); cysteine and methionine metabolism (P8); and pyruvate metabolism (P4). However, AS treatment could only normalize one altered pathway, namely lipid metabolism (P1) [Table 1].
In addition, the most relevant pathways were identified by the metabolic pathway analysis (MetPA) on MetaboAnalyst 3.0 (http://www.metaboanalyst.ca/MetaboAnalyst/). The impact value of pathway analysis with MetPA was applied to evaluate the importance of the pathways on the pathological changes or drug targets [Figure 7] and [Table S1]. Four altered metabolic pathways were considered as the most relevant pathways involved in pathological changes or drug targets (Impact >0.1). They were citrate cycle (a); alanine, aspartate, and glutamate metabolism (b); pyruvate metabolism (c); and glycine, serine, and threonine metabolism (d). Citrate (B3), pyruvate (B4), glycine (B7), glutamine (B8), and betaine (B9) are involved in the four key pathways that may denote the most important drug targets. Among them, citrate cycle (a); alanine, aspartate, and glutamate metabolism (b); and pyruvate metabolism (c) are the targeted pathways related to the therapeutic effects of XKS treatment. However, AS treatment has no effects on these pathways.
|Figure 7: Summary of pathway analysis with MetPA. Each point represents one metabolic pathway; the size of dot and shades of color are positive correlation with the impaction of metabolic pathway (a. tricarboxylic acid cycle; b. Alanine, aspartate and glutamate metabolism; c. Pyruvate metabolism; d. Glycine, serine and threonine metabolism)|
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| Discussion|| |
With their multiple components, holistic therapeutic effects, and fewer side effects, TCMs are a promising therapy for CAD. Clinical research has confirmed that XKS can improve arterial elasticity and heart rate variability, and reduce episodes of angina pectoris in CAD. According to our histopathology study, treatment with XKS or AS caused a notable decrease in the atherosclerotic plaque area, suggesting that XKS and AS have similar anti-AS effects. However, AS treatment showed more effect on TC and LDL levels than XKS did in plasma biochemical assays. Therefore, we concluded that treatment with XKS and with AS may utilize different mechanisms against AS.
To understand the mechanism of XKS against AS, a metabonomics approach was used in this study. With the multivariate analysis of 1H NMR data, the alterations induced by AS were significantly improved after treatment with XKS or AS [Figure 4], suggesting that their anti-AS effects are most likely ameliorating the metabolic disorders induced by HCD. Eleven pathological biomarkers were identified to differentiate the metabolic profiles of AS rabbits from those of normal rabbits. XKS treatment mediated the changes of nine metabolites related to pathological changes, as well as two metabolites related to drug regulation. They are LDL/VLDL (B1), lactate (B2), citrate (B3), pyruvate (B4), phosphatidylcholine (B6), glutamine (B8), creatinine (B10), methionine (B11), and α-glucose (B13). All of these metabolites are considered potential pharmacological biomarkers for XKS treatment targets. However, AS only affected the metabolic disorders of LDL/VLDL (B1) and phosphatidylcholine (B6). Pathological combined with metabonomics findings demonstrate that the anti-AS effects of AS mainly target blood-lipid metabolism, but XKS treatment shows multi-targeted effects against AS.
Nine pharmacological biomarkers are relevant to the therapeutic targets of XKS, which primarily involve lipid metabolism (P1); glycolysis/gluconeogenesis (P2); citrate cycle (P3); alanine, aspartate, and glutamate metabolism (P6); arginine and proline metabolism (P7); cysteine and methionine metabolism (P8); as well as the characteristic pathway of pyruvate metabolism (P4) and the α-glucose-related glycolysis/gluconeogenesis pathway (P2) [Table 1].
Disorders in lipid metabolism, which play a crucial role in the initiation and progression of AS, are considered to cause CAD. A marked decrease in lipid metabolism (LDL/VLDL B1 and phosphatidylcholine B6) was observed in the XKS and AS groups compared with that in the model group. LDL particles are atherogenic risk factors, especially if oxidized and accumulated in the arterial wall, and are major cholesterol carriers in the circulation. Endothelial cell inflammation and apoptosis could be induced by oxidized LDL overexpression, resulting in vascular endothelial cell expression of adhesion molecules, and leading to enhanced adherence of monocytes to the vascular endothelium. Phosphatidylcholine (B6), a common constituent of platelet-activating factor-like lipids, can lead to higher concentrations of oxidized LDL. The anti-PC IgM has anti-inflammatory properties and can be used as a therapy in atherosclerotic disease. Our metabonomics study demonstrated that XKS and AS can significantly reduce the levels of LDL/VLDL and phosphatidylcholine, but AS treatment showed greater regulatory effects on lipid metabolism disorder compared with that of XKS treatment, which is consisted with clinical chemical analysis results.
The tricarboxylic acid (TCA) cycle is a central pathway in the metabolism of sugars, lipids, and amino acids for energy homeostasis and cell metabolism. Accumulating evidence supports that TCA cycle dysfunction plays a key role in the pathogenesis of AS., Citrate (B3) is an intermediate in the TCA cycle. Our previous study demonstrated that citrate had a highly negative association with atherogenic outcomes, and was a better predictor of AS than lipoprotein lipids (e.g., HDL and LDL/VLDL). The decreased citrate in the model group in this study indicates that the formation of ATP is inhibited, which is closely related to the formation of AS. Treatment with XKS corrected the citrate levels, suggesting that XKS ameliorates the dysfunction of the TCA cycle.
Pyruvate (B4) is the end product of glycolysis. Pyruvate is crucial for mitochondrial ATP generation and for several major biosynthetic pathways that feed into the TCA cycle. Under hypoxic conditions, pyruvate can also be converted to lactate (B2) by lactate dehydrogenase (LDH, EC188.8.131.52) [Figure 8] and [Table S2]. The hypoxia induced by the AS state is suggested to be a major stimulator of lactate synthesis from pyruvate. In the present study, the increased levels of lactate suggest the upregulation of glycolysis in atherogenesis, and treatment with XKS reduces the lactate and pyruvate levels in carbohydrate metabolism. In addition, oxidation of long-chain fatty acids in the mitochondria generates the main TCA cycle substrate, acetyl-CoA. Therefore, we conclude that HCD induces lipid accumulation in rabbit plasma, but XKS treatment activates the degradation of fatty acids for energy demand and decreases glycolytic metabolism, which is further supported by the down-regulation of α-glucose (B13) after XKS treatment. The results indicate that the regulatory effects of XKS on glycolysis and TCA cycle intermediates may promote fatty acid degradation and metabolism. As a result, lipid levels are decreased in rabbit plasma by XKS treatment.
|Figure 8: A fully compound (pink hexagons)–reaction (gray squares)–enzyme (green squares)–gene (blue circles) network of nine metabolites detected in the high cholesterol diet-induced AS. Metabolites include pyruvate, citrate, lactate, phosphatidylcholine, glycine, tyrosine, glutamine, methionine, betaine and α-glucose are shown in red|
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Amino acid metabolism
The homeostasis of amino acids could be significantly altered by HCD, leading to a metabolic amino acid disorder., Glutamine (B8), a free amino acid, exists in blood and skeletal muscle tissue at high concentrations. It is a physiological inhibitor of nitric oxide (NO) synthesis in intact blood vessels and endothelial cells. Therefore, glutamine accumulation in plasma could inhibit NO generation in endothelial cells, which is responsible for impeding endothelium-dependent vasodilation. The increased concentration of glutamine in the model group indicates that NO biosynthesis in endothelial cells could have been inhibited, causing endothelial function disorder. Conversely, the decreased concentration of glutamine in the XKS treatment group indicates that XKS may regulate the NO-related pathway to improve endothelial function.
Creatinine (B10) is a primary breakdown product of creatine, which is released from the muscle tissue. Studies have reported that creatine supplementation is associated with decreased homocysteine levels in humans. A high level of homocysteine is an independent cardiovascular risk factor associated with ischemic heart attacks and atherosclerotic vascular diseases. In our study, the decreased concentrations of creatinine were detected by NMR in the model group, suggesting that its biosynthesis was inhibited in the development of AS. However, the concentration of creatinine increased in the XKS treatment group, indicating that XKS may regulate homocysteine to improve the AS risk, but AS treatments had no such effect.
Methionine (B11) can be converted to homocysteine through the transmethylation/transsulfuration pathway, which may have atherogenic effects through several mechanisms (including lipid peroxidation). Accumulating evidence suggests that excess dietary methionine can induce the development of AS. Injury/dysfunction of the vascular endothelium is considered the main mechanism of the atherogenic effect induced by methionine., In the present study, the increased concentration of methionine in the model group was reversed by treatment with XKS. However, treatment with AS had no such modulating effect. The results indicate that the therapeutic targets of XKS may inhibit lipid peroxidation to improve endothelial function.
In addition, to identify the metabolite-related genes and proteins, ten representative metabolite biomarkers derived from the plasma-based 1H NMR profiling (i.e., pyruvate, citrate, lactate, phosphatidylcholine, glycine, tyrosine, glutamine, methionine, betaine, and α-glucose) were entered into Metscape, and the compound–reaction–enzyme–gene networks were constructed by the software [Figure 8]. As a result, 78 proteins and 142 genes were found to be involved in AS progression induced by HCD and ameliorated by XKS-related metabolites [Table S2]. Among them, 24 enzymes and 38 genes are involved in the three most relevant pathways (Impact > 0.1 based on MetPA, including citrate cycle; alanine, aspartate, and glutamate metabolism; and pyruvate metabolism) associated with the therapeutic effects of XKS treatment, which confirmed that these enzymes and genes play key roles in the therapeutic targets of XKS.
| Conclusions|| |
In this study, biochemical assays of the plasma and histological analyses of the aortas revealed that treatment with XKS and with AS may utilize different mechanisms against AS. To understand the mechanism of XKS against AS, we applied 1H NMR-based metabonomics to profile small, polar metabolites in blood. This was combined with multivariate analysis and pattern recognition to identify metabolites with significantly changed levels, and metabolic pathways that were normalized with XKS or AS treatment, to assess the therapeutic effects of XKS. Eleven significantly changed metabolites in plasma were identified, which involved alterations of lipid, energy, and amino acid metabolism, as potential pathological biomarkers related to AS. Further, we applied a metabonomics method to systematically assess the therapeutic effects of XKS and AS against AS. Treatment with XKS could effectively regulate the metabolic alternations of LDL/VLDL (B1), lactate (B2), citrate (B3), phosphatidylcholine (B6), glutamine (B8), creatinine (B10), and methionine (B11), as well as the characteristic metabolites of pyruvate (B4) and α-glucose (B13); these may be the pharmacological targets of XKS against AS. However, AS only regulated the metabolites of LDL/VLDL (B1) and phosphatidylcholine (B6). This study indicates that the anti-AS effects of AS mainly reduce blood-lipid levels, but those of XKS were multi-targeted. Furthermore, the 1H NMR-based metabonomics approach could offer information on small, polar metabolites, which complements information obtained with MS, to explore the therapeutic mechanisms of TCMs. Due to the relatively limited number of XKS doses test and end-points, more doses and end-points are necessary for future studies.
Financial support and sponsorship
This work has been financially supported by National Natural Science Foundation of China (No. 81473332).
Conflicts of interest
There are no conflicts of interest.
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