Application of rhizoma smilacis glabrae in preparation of medicine for treating intestinal flora and / or metabolic disorder caused by hyperuricemia

Abstract

The invention provides application of rhizoma smilacis glabrae in preparation of a medicine for treating intestinal flora and / or metabolic disorder caused by hyperuricemia. The application is realized by regulating and controlling the expression level of SUA-associated metabolic markers in serum. The SUA-associated metabolic markers comprise: metabolites positively associated with SUA, wherein the metabolites comprise chenodeoxycholic acid, nutritional cholic acid, 7alpha-hydroxy-3-oxo-4-cholesteric acid and ceramyl ethanolamide; eight metabolites which are in negative correlation with SUA comprise polyterpene alcohol group-beta-D-glucosyl phosphate, docosapentaenoic acid, 5, 8, 11-eicosatrienoic acid, adrenoic acid, diacylglycerol DG (16: 0 / 22: 5), phosphatidylcholine PC (14: 0 / 18: 1), phosphatidylcholine PC (18: 0 / 22: 6) and retinyl ester.

Description

Technical Field

[0001] This invention belongs to the field of pharmaceutical technology, specifically relating to the application of Smilax glabra in the preparation of drugs for treating intestinal flora and / or metabolic disorders caused by hyperuricemia. Background Art

[0002] Hyperuricemia is a metabolic disease caused by excessive production and / or insufficient excretion of uric acid (UA), often accompanied by urate crystal deposition. It is prevalent worldwide and a risk factor for gout, diabetes, hypertension, cardiovascular disease, and chronic kidney disease. Uric acid is mainly synthesized in the liver, intestines, and vascular endothelium. Uric acid is excreted through the kidneys and intestines, with the kidneys excreting approximately 70% of daily UA production and the remaining 30% excreted through the intestines. Clinically used uric acid-lowering drugs, allopurinol or febuxostat, are inhibitors of xanthine oxidase (XOD), the main rate-limiting enzyme in purine metabolism, but they have adverse reactions such as kidney damage or hypersensitivity. Furthermore, existing drugs only target uric acid lowering and cannot reverse pathological processes such as inflammation and fibrosis, nor can they provide intestinal and renal protection. Therefore, given the limitations of traditional therapies in terms of safety and efficacy, there is an urgent need to develop novel anti-hyperuricemia drugs that regulate uric acid metabolic homeostasis through multiple pathways and possess synergistic effects across multiple mechanisms.

[0003] Metabolomics has been widely used to discover biomarkers associated with different stages of disease and to explore potential targets and pathways for drug therapy. Metabolomics focuses on drug- or environmentally induced changes in small molecule metabolites and can comprehensively analyze metabolites in an organism, aligning with the holistic concept of traditional Chinese medicine. Ultra-high performance liquid chromatography (UHPLC) coupled with mass spectrometry (MS), especially high-resolution mass spectrometry (HRMS), has been widely used in metabolic analysis. Evidence from numerous metabolomics studies suggests that disorders of purine metabolism, bile acids, tryptophan, short-chain fatty acids (SCFAs), lipids, and amino acids are associated with hyperacidity (HUA).

[0004] The gut microbiome is a complex micro-ecosystem that develops alongside the human body, composed of trillions of microorganisms and their genetic material. Gut microbiota plays a vital role in various functions, including substance transformation, enhancing immunity, improving nerve signals, drug metabolism, endotoxin removal, energy regulation, and influencing host metabolites. Various mechanisms linking gut microbiota dysbiosis to the pathology of hyperuricemia have been proposed, including abnormal enterohepatic bile acid circulation exacerbating uric acid excretion disorders, imbalanced activity of intestinal uric acid metabolic enzymes leading to uric acid production and excretion disturbances, microbiota-derived uremic toxins activating NLRP3 inflammasomes triggering systemic inflammation, and impaired intestinal barrier function exacerbating abnormal uric acid gut-kidney axis circulation. Furthermore, various gut microbiota-derived metabolites, such as bile acids, tryptophan, and short-chain fatty acids (SCFAs), are important modifiers for improving susceptibility to hyperuricemia. Existing research confirms that dietary regulation or probiotic-based targeted remodeling of the gut microbiota structure and its metabolic profile, along with dietary standardization or probiotics to improve the gut microbiota and its metabolites, represent potential therapies for hyperuricemia.

[0005] Smilax glabra Roxb., also known as Tu Bi Xie, is the dried rhizome of Smilax glabra, a plant belonging to the Liliaceae family. Smilax glabra has a sweet and bland taste, is neutral in nature, and enters the liver and stomach meridians. Its main functions include removing dampness, detoxifying, promoting joint mobility, anti-inflammation, anti-oxidation, protecting kidney function, and treating syphilis and mercury poisoning. It is mainly used to treat hyperuricemia and gout. In 2002, Smilax glabra was listed as a traditional Chinese medicine that can be used in health food products. Therefore, to further clarify the uric acid-lowering effect and mechanism of Smilax glabra, this invention uses Smilax glabra extract as the research object. First, the uric acid-lowering activity of Smilax glabra extract was clarified through a hyperuricemia animal model study. Subsequently, by integrating 16S rRNA sequencing and non-targeted metabolomics technologies, the molecular mechanism by which it exerts its therapeutic effect by remodeling the intestinal flora structure and regulating serum metabolic pathways was systematically elucidated. This study provides a modern scientific explanation for the development, utilization, and pharmacodynamic research of Smilax glabra, and also provides a research method for developing traditional Chinese medicine preparations for treating hyperuricemia based on intestinal microecological regulation. Summary of the Invention

[0006] Therefore, the purpose of this invention is to provide the use of Smilax glabra in the preparation of a medicine for treating intestinal flora and / or metabolic disorders caused by hyperuricemia.

[0007] Specifically, this invention clarifies the uric acid-lowering activity and renal and intestinal protective effects of Smilax glabra extract through animal models of hyperuricemia. Subsequently, by integrating 16S rRNA sequencing and non-targeted metabolomics technologies, it systematically elucidates the molecular mechanism by which it exerts its therapeutic effect by reshaping the gut microbiota structure and improving serum metabolic pathways. This provides a modern scientific explanation for the development, utilization, and pharmacodynamic research of Smilax glabra, further promoting and leveraging the detoxification effect of traditional Chinese medicine in the treatment of hyperuricemia, and fully demonstrating its advantages in multi-target and holistic regulation.

[0008] The technical solution provided by this invention is as follows:

[0009] <First Aspect>

[0010] An application of Smilax glabra in the preparation of a drug for treating intestinal flora and / or metabolic disorders caused by hyperuricemia, wherein the application is achieved by regulating the expression levels of SUA-related metabolic markers in serum, including:

[0011] Metabolites positively correlated with SUA include chenodeoxycholic acid, nutritional cholic acid, 7α-hydroxy-3-oxo-4-cholestyric acid, and ceramide.

[0012] Eight metabolites negatively correlated with SUA include polyterpenoid-β-D-glucosyl phosphate, eicosapentaenoic acid, 5,8,11-eicosatrienoic acid, adrenal acid, diacylglycerol DG (16:0 / 22:5), phosphatidylcholine PC (14:0 / 18:1), phosphatidylcholine PC (18:0 / 22:6), and retinyl esters.

[0013] The Smilax glabra is a Smilax glabra decoction, and the preparation method of the Smilax glabra decoction includes:

[0014] (1) Soak the Smilax glabra medicinal material in water and decoct it twice. First, decoct it over high heat at 90-100℃ for 20-30 minutes, and then simmer it over low heat at 70-85℃ for 50-60 minutes; collect the decoction.

[0015] (2) After adding water to the dregs, boil them over high heat at 90-100℃ for 15-30 minutes, and then simmer over low heat at 70-85℃ for 40-60 minutes.

[0016] (3) Combine the two decoctions and concentrate them to obtain a decoction equivalent to 0.25g-0.5g / mL of raw medicinal material.

[0017] In step (1), the ratio of Smilax glabra medicinal material to water is 1:8-1:10.

[0018] <Second Aspect>

[0019] This invention provides a method for evaluating the efficacy of Smilax glabra in treating hyperuricemia, establishing a metabolic biomarker evaluation system through the following steps:

[0020] (i) Serum metabolomics were performed using liquid chromatography-mass spectrometry to screen differentially metabolites associated with the pathological state of hyperuricemia.

[0021] Chromatographic conditions: ACQUITYUPLC HSS T3 column, gradient elution time 0-12 min;

[0022] Mass spectrometry conditions: ion source temperature 320℃, lens voltage 50V, m / z scan range 67-1000;

[0023] Positive ion mode detection parameters: spray voltage 3.2kV;

[0024] Negative ion mode detection parameters: spray voltage -2.8kV.

[0025] (ii) The gut microbiota of fecal samples was analyzed by 16S rRNA gene sequencing technology to detect changes in the abundance of Turicibacter, Eubacterium_ventriosum_group and Helicobacter spp.

[0026] (iii) Construct a Spearman correlation network model between serum differential metabolites and gut microbiota abundance, and screen out SUA-related metabolic markers.

[0027] The SUA-associated metabolic biomarkers include:

[0028] Four metabolites positively correlated with SUA include chenodeoxycholic acid, nutritional cholic acid, 7α-hydroxy-3-oxo-4-cholestyric acid, and ceramide.

[0029] Eight metabolites negatively correlated with SUA include polyterpenoid-β-D-glucosyl phosphate, eicosapentaenoic acid, 5,8,11-eicosatrienoic acid, adrenal acid, diacylglycerol DG (16:0 / 22:5), phosphatidylcholine PC (14:0 / 18:1), phosphatidylcholine PC (18:0 / 22:6), and retinyl esters.

[0030] <Third Aspect>

[0031] This invention provides a method for preparing a decoction of Smilax glabra, the method comprising the following steps:

[0032] (1) Soak the Smilax glabra medicinal material in water and decoct it twice. First, decoct it over high heat at 90-100℃ for 20-30 minutes, and then simmer it over low heat at 70-85℃ for 50-60 minutes; collect the decoction.

[0033] (2) After adding water to the dregs, boil them over high heat at 90-100℃ for 15-30 minutes, and then simmer over low heat at 70-85℃ for 40-60 minutes.

[0034] (3) Combine the two decoctions and concentrate them to obtain a standard decoction equivalent to 0.25-0.5 g / mL of raw medicinal material.

[0035] <Fourth Aspect>

[0036] This invention provides a drug for treating hyperuricemia, comprising the above-mentioned Smilax glabra decoction as an active ingredient.

[0037] <Fifth Aspect>

[0038] This invention provides a biomarker combination for evaluating the efficacy of Smilax glabra preparations, comprising:

[0039] Microbial biomarkers: abundance reduction of ≥40% for Turicibacter, Eubacterium_ventriosum_group, and Spirulina genus;

[0040] Metabolic markers: Serum levels of chenodeoxycholic acid, nutritional cholic acid, 7α-hydroxy-3-oxo-4-cholestyric acid, and ceramide decreased; levels of polyterpenoid β-D-glucosyl phosphate, eicosapentaenoic acid, 5,8,11-eicosatrienoic acid, adrenal acid, diacylglycerol DG (16:0 / 22:5), phosphatidylcholine PC (14:0 / 18:1), phosphatidylcholine PC (18:0 / 22:6), and retinyl ester metabolites increased.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] This invention uses Smilax glabra extract as the research object. Specifically, this invention uses an animal model of hyperuricemia to clarify the uric acid-lowering activity and renal and intestinal protective effects of Smilax glabra extract. Subsequently, by integrating 16S rRNA sequencing and non-targeted metabolomics technologies, it systematically elucidates the molecular mechanism by which it exerts its therapeutic effect by reshaping the intestinal flora structure and improving serum metabolic disorder pathways. This provides a modern scientific explanation for the development, utilization, and pharmacodynamic research of Smilax glabra, further promoting and leveraging the detoxification effect of traditional Chinese medicine in the treatment of hyperuricemia, fully demonstrating its advantages of multi-target regulation and holistic regulation, and possessing good clinical application value.

[0043] This invention elucidates the mechanism of action of Smilax glabra in treating hyperuricemia from multiple perspectives and at a holistic level, providing a scientific basis for the analysis and development of the pharmacodynamic material basis of food-medicine homology drugs. Attached Figure Description

[0044] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0045] Figure 1This study investigated the regulation of uric acid (UA) levels and related biochemical indicators in hyperuricemic rats by SGR. Figure (A) shows a schematic diagram of the animal experiment; Figure (B) shows serum uric acid (SUA) levels; Figure (C) shows fecal uric acid (FUA) levels; Figure (D) shows blood urea nitrogen (BUN) levels; Figure (E) shows creatinine (CRE) levels; Figure (F) shows liver xanthine oxidase (XOD) activity; and Figure (G) shows serum XOD activity. Statistical significance was determined using one-way ANOVA. Compared with the NC group, *P<0.05, **P<0.01; compared with the HUA group, #P<0.05, ##P<0.01.

[0046] Figure 2 This is the effect of SGR on renal pathological morphological changes induced by hyperuricemia. (A) Image shows the appearance of the kidney; (B) Image shows an HE-stained section of the kidney. Black arrow: urate crystals; triangle: inflammatory cell infiltration; circle: tubular dilatation of renal tubules.

[0047] Figure 3 This relates to the effect of SGR on pathological changes in the small intestine induced by hyperuricemia.

[0048] Figure 4 The above are orthogonal partial least squares discriminant analysis (OPLS-DA) scores for plasma metabolites; (A) shows the orthogonal partial least squares discriminant analysis (OPLS-DA) of serum metabolites in six groups; (B) shows the OPLS-DA of serum metabolites between the NC group and the HUA group; (C) shows the OPLS-DA of serum metabolites between the HUA group and the ALL group; (D) shows the OPLS-DA of serum metabolites between the HUA group and the LSGR group; (E) shows the OPLS-DA of serum metabolites between the HUA group and the MSGR group; and (F) shows the OPLS-DA of serum metabolites between the HUA group and the HSGR group.

[0049] Figure 5 This is a differential metabolite and correlation analysis of SGR-regulated hyperuricemia rats. Figure (A) shows a cluster heatmap of 23 differential metabolites; Figure (B) shows the Spearman correlation analysis of key differential metabolites and biochemical indicators.

[0050] Figure 6 This is a metabolic pathway analysis of SGR treatment for hyperuricemia. Figure (A) shows the metabolic pathway enrichment analysis; Figure (B) shows the main metabolic pathway network of SGR-treated HUA rats.

[0051] Figure 7 This is an example of SGR restoring the gut microbiota in rats with hyperuricemia. Figure (A) shows the partial least squares discriminant analysis (PLS-DA) plot; Figure (B) is a bar chart of community composition at the genus level.

[0052] Figure 8 These are differentially expressed microorganisms in rats with hyperuricemia regulated by SGR. Figure (A) shows the Lefse analysis; Figure (B) shows the relative abundance of the three differentially expressed microbial genera.

[0053] Figure 9 This is a correlation analysis of key differentially expressed metabolites. Figure (A) shows the Spearman correlation analysis between differentially expressed microorganisms and biochemical indicators; Figure (B) shows the Spearman correlation analysis between differentially expressed microorganisms and key differentially expressed metabolites. Detailed Implementation

[0054] The present invention will be described in detail below with reference to embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several adjustments and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0055] Unless otherwise specified, the experimental conditions in the examples are conventional in the field or performed in accordance with the standards recommended by the reagent manufacturers. Unless otherwise specified, the materials and reagents used in the examples can be obtained from commercially available channels.

[0056] Example 1

[0057] 1. Experimental Methods

[0058] 1.1 Preparation of Standard Decoction of Smilax glabra

[0059] The sample of Smilax glabra (SGR) was purchased from Shanghai Wanshicheng Pharmaceutical Products Co., Ltd., and passed the test according to the 2020 edition of the Chinese Pharmacopoeia (moisture content ≤10%, ash content ≤5%). 100g of dried Smilax glabra was weighed, washed, dried and pulverized. It was soaked in 900mL of water for 30min, then decocted over high heat (100℃) for 20min and then over low heat (85℃) for 50min. The first decoction was filtered, and 800mL of water was added to the residue for a second decoction. The decoction was decocted over high heat (100℃) for 15min and then over low heat (85℃) for 40min. The two decoctions were combined and concentrated under reduced pressure to 400mL.

[0060] 1.2 Animal treatment and sample collection

[0061] 36 male SPF - grade SD rats (200 ± 20 g, from Shanghai Slake, license number: SCXK(Shanghai)2022 - 0004) were used. The experimental environment was set with a 12 - hour light / dark cycle, temperature of 22 ± 1 °C, and humidity of 45 - 55%. During the experiment, the rats were fed standard feed and water ad libitum. After one - week of adaptive feeding, the rats were randomly divided into 6 groups (n = 6), namely the control group (NC), the model group (HUA), the allopurinol group (ALL), the low - dose SGR group (LSGR), the medium - dose SGR group (MSGR), and the high - dose SGR group (HSGR).

[0062] Among them, rats in the HUA, SGR, and ALL groups were intragastrically administered potassium oxonate (PO) (0.3 g / kg / d) to induce hyperuricemia. Rats in the control group were orally administered an equal volume of normal saline every day, and the body weight of the rats was recorded and observed daily. Starting from the 3rd week, after intragastrically administering the modeling agent, the allopurinol group was intragastrically administered an allopurinol solution (0.01 g / kg / d), and the low - dose SGR group, medium - dose SGR group, and high - dose SGR group were intragastrically administered the standard decoction of Smilax glabra (3, 6, 9 g / kg / d) once in the morning and once in the afternoon every day. Blood was collected after the last dose of medication, and then all rats were sacrificed immediately, and the kidneys, livers, and small intestines were collected. All experimental procedures of the rats complied with the regulations of the Animal Ethics Committee of the Experimental Animal Center of Shanghai Jiao Tong University.

[0063] 1.2 Determination of biochemical indexes

[0064] According to the instructions of the reagent manufacturer, an Elabscience uric acid colorimetric assay kit, urea colorimetric assay kit, creatinine colorimetric assay kit, and xanthine oxidase colorimetric assay kit were used to measure the levels of serum uric acid (SUA), fecal uric acid (FUA), blood urea nitrogen (BUN), serum creatinine (CRE), and the activities of xanthine oxidase (XOD) in serum and liver.

[0065] 1.3 Histopathology

[0066] Kidney samples or small intestine samples were fixed in 4% paraformaldehyde, dehydrated and cleared in sequence, and then embedded in paraffin by an embedding machine. Paraffin sections were prepared by a microtome. Then, the sections were stained with hematoxylin - eosin (HE), dehydrated, clarified, and sealed. Histomorphological observation was carried out using a pathological section scanner.

[0067] 1.4 Plasma metabolomics study

[0068] 1.4.1 Sample preparation

[0069] Thaw plasma samples at 4°C. Place 50 μL of plasma sample in an EP tube, add 200 μL of methanol / acetonitrile (1:1, v / v) containing 2 μg / mL chlorophenylalanine, vortex to mix thoroughly, and incubate at -20°C for 2 hours. Then centrifuge at 12,000 rpm for 20 minutes at 4°C to precipitate proteins. Transfer 150 μL of the supernatant to a new centrifuge tube and concentrate using a centrifuge concentrator at room temperature for 1 hour, then at 45°C for 1 hour. Redissolve the dried residue with 50 μL of methanol / water (3:7, v / v), vortex to mix, and centrifuge at 12,000 rpm for 20 minutes at 4°C. Collect the supernatant in a sample vial for analysis. Take equal amounts of supernatant from all samples and mix them to form a QC sample for analysis.

[0070] 1.4.2 UPLC / Q-Exactive / MS Analysis

[0071] In a Thermofisher ultra-high performance liquid chromatography (UHPLC) system, an ACQUITY UPLC HSS T3 column (100 × 2.1 mm, 1.7 μm, Waters) was used for analysis. The mobile phase consisted of two parts: phase A was water / formic acid (99.9:0.1, v / v), and phase B was methanol / formic acid (99.9:0.1). The elution gradient was set as follows: from 0 to 5 minutes, the proportion of phase B increased from 1% to 100%; from 5 to 12 minutes, phase B was maintained at 100%. The column temperature was controlled at 45 °C, the flow rate was 0.4 mL / min, and the injection volume was 1 μL. A Q Exactive hybrid quadrupole orbitrap mass spectrometer (Thermofisher) was connected, and both positive and negative ion modes were used for detection. The spray voltage was 3.2 kV in positive ion mode and -2.8 kV in negative ion mode. The ion source temperature was maintained at 320 °C, and the lens voltage was set to 50 V. The scanning mode employed a data-dependent acquisition (DDA) approach, consisting of one full scan followed by ten MS / MS scans. Ion fragmentation was induced by setting collision energies to NEC 15 and 30, using 99.999% pure nitrogen as the collision-induced dissociation gas. The full scan parameters were set as follows: resolution 70,000, automatic gain control target below 1 × 10⁶, maximum isolation time 100 ms, and m / z scan range 67–1000. The secondary mass spectrometry parameters were set as follows: resolution 17,500, automatic gain control target below 5 × 10⁵, and maximum isolation time 50 ms. To evaluate system stability and reproducibility, equal volumes of samples were mixed from all samples to prepare quality control (QC) samples, with one QC sample inserted for every nine samples.

[0072] Table 123 Differential Metabolites

[0073]

[0074]

[0075]

[0076] 1.4.3 Data Processing and Statistical Analysis

[0077] All raw LC-MS / MS data were processed using Progenesis QI software (Nonlinear Dynamics), including retention time alignment, peak extraction, and normalization, removing data with a coefficient of variation (CV) > 30% for QC samples. Orthogonal partial least squares discriminant analysis (OPLS-DA) was performed on the preprocessed data using SIMCA14.1 (Umetrics AB). The predicted value (VIP) of the OPLS-DA model (VIP > 1), the p-value of the t-test (p < 0.05), and the fold change (FC) value (FC > 2) were used as indicators for screening differential metabolites. The structures of the selected differential metabolites were identified using multi-stage mass spectrometry information from the Human Metabolome Database (HMDB) and the LIPID MAPS database. MetaboAnalyst 5.0 was used for metabolic pathway enrichment analysis of the differential metabolites.

[0078] 1.516S rRNA sequencing analysis

[0079] Genomic DNA was extracted from rat fecal samples using a kit. DNA quality was assessed by 1% agarose gel electrophoresis. Primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′, as shown in SEQ ID No. 1) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′, SEQ ID No. 2) were used to amplify the V3-V4 region. The amplified products were used to construct sequencing libraries using the NEXTFLEX RapidDNA-Seq Kit, including adapter ligation, magnetic bead selection to remove self-connectors, PCR amplification to enrich the library template, and magnetic bead recovery of the PCR products to obtain the final library. Sequencing was then performed on the Illumina NovaSeq 2000 platform. The obtained PE sequences were first spliced ​​based on overlapping regions, with simultaneous quality control and filtering. OTUs were clustered using Usearch software with 97% similarity for non-repetitive sequences (excluding single sequences). The RDP classifier Bayesian algorithm was used to classify and annotate OTUs based on the Silva (Release138) database with 70% confidence. The bacterial community composition of the samples was statistically analyzed at each classification level.

[0080] PLS-DA was used to elucidate differences in microbial communities among groups. Genus-level taxonomic unit composition was analyzed, and heatmaps were plotted using abundance data from the top 20 genera by average abundance. Linear discriminant analysis (LDA) effect size (LEfSe) was employed to identify differentially expressed microorganisms among different taxa (LDA score > 2).

[0081] 1.6 Correlation analysis between gut microbiota, metabolites, and biochemical indicators

[0082] Correlation studies were conducted on metabolites and gut microbiota with biochemical indicators (SUA, FUA, BUN, CRE, XOD) using Spearman correlation analysis. Spearman correlation analysis was also performed on differentially expressed metabolites and differentially expressed gut microbiota.

[0083] 1.7 Statistical Analysis

[0084] Results are expressed as mean ± standard deviation (SD). If not specified, significant differences were calculated using one-way ANOVA across multiple groups, followed by a Tukey post-hoc test using GraphPad Prism software. Graphs were generated using GraphPad Prism software. A p-value < 0.05 was considered statistically significant.

[0085] 2. Experimental Results

[0086] 2.1 Biochemical Indicators

[0087] Animal experiments were conducted according to the method described in 1.2 (see...). Figure 1 (A). The standard decoction of Smilax glabra can significantly reduce serum uric acid (SUA), blood urea nitrogen (BUN), and serum creatinine (CRE) levels in hyperuricemic rats, and can significantly increase fecal uric acid (FUA) levels in hyperuricemic rats (see [reference]). Figure 1 (BE).

[0088] The standard decoction of Smilax glabra can significantly inhibit the activity of xanthine oxidase (XOD) in the serum and liver of rats with hyperuricemia, and reduce uric acid production. Figure 1 (FG).

[0089] Figure 1This study investigated the regulation of uric acid (UA) levels and related biochemical indicators in hyperuricemic rats by SGR. Figure (A) shows a schematic diagram of the animal experiment; Figure (B) shows serum uric acid (SUA) levels; Figure (C) shows fecal uric acid (FUA) levels; Figure (D) shows blood urea nitrogen (BUN) levels; Figure (E) shows creatinine (CRE) levels; Figure (F) shows liver xanthine oxidase (XOD) activity; and Figure (G) shows serum XOD activity. Statistical significance was determined using one-way ANOVA. Compared with the NC group, *P<0.05, **P<0.01; compared with the HUA group, #P<0.05, ##P<0.01.

[0090] The standard decoction of Smilax glabra can significantly improve the appearance and pathology of the kidneys in rats with hyperuricemia (e.g., Figure 2 ) and intestinal pathology (such as Figure 3 ).

[0091] Figure 2 This is the effect of SGR on renal pathological morphological changes induced by hyperuricemia. (A) Image shows the appearance of the kidney; (B) Image shows an HE-stained section of the kidney. Black arrow: urate crystals; triangle: inflammatory cell infiltration; circle: tubular dilatation of renal tubules.

[0092] 2.2 Results of plasma metabolomics testing

[0093] 2.2.1 Screening of differentially expressed metabolites

[0094] Multivariate statistical analysis was used to screen potential biomarkers: After obtaining mass spectrometry data, orthogonal partial least squares discriminant analysis (OPLS-DA) was performed on the serum sample data of six groups, namely the control group, the hyperuricemia rat model group, the allopurinol group, the low-dose group of Smilax glabra, the medium-dose group of Smilax glabra, and the high-dose group of Smilax glabra, using SIMCA14.1 software to observe the aggregation and dispersion of all samples.

[0095] Figure 4 The above are orthogonal partial least squares discriminant analysis (OPLS-DA) scores for plasma metabolites; (A) shows the orthogonal partial least squares discriminant analysis (OPLS-DA) of serum metabolites in six groups; (B) shows the OPLS-DA of serum metabolites between the NC group and the HUA group; (C) shows the OPLS-DA of serum metabolites between the HUA group and the ALL group; (D) shows the OPLS-DA of serum metabolites between the HUA group and the LSGR group; (E) shows the OPLS-DA of serum metabolites between the HUA group and the MSGR group; and (F) shows the OPLS-DA of serum metabolites between the HUA group and the HSGR group.

[0096] The results showed that the NC group and the HUA group were significantly separated, while the treatment groups, the SGR group and the ALL group, showed a difference between the NC group and the HUA group. Figure 4 (A). Data indicate that HUA rats exhibit metabolic disturbances, and SGR treatment improved these disturbances to some extent. To further determine the metabolic changes between HUA rats and NC or SGR rats, pairwise paired analysis was performed using OPLS-DA (…). Figure 4 (BF). The VIP value (variable importance in projection) of each metabolite was obtained using the OPLS-DA model. Differential metabolites with VIP > 1 were screened, and further significant differential metabolites with P < 0.05 and FC value (fold difference) > 1.5 were calculated and screened. To investigate the key differential metabolites in SGR treatment of HUA, cluster heatmap analysis was performed on the overlapping differential metabolites between the NC and HUA groups, as well as between the HUA group and LSGR, MSGR, and HSGR. Figure 5 (Table A). The results showed that SGR mainly restored 23 disordered metabolites in HUA rats (Table 1), including 10 bile acids and their derivatives, 5 fatty acids and their derivatives, 2 phospholipids, etc. The MSGR group restored 21 of the 23 metabolites, and the clustering results showed that the MSGR group and the NC group clustered together, indicating that the medium-dose SGR group had a better effect on restoring disorder in HUA rats. In addition, in order to verify the effect of SGR extract on hyperuricemic rats, the Spearman correlation between 23 key metabolites and rat biochemical indicators was further analyzed. Figure 5 (B) The results showed that SUA was significantly positively correlated with four metabolites: chenodeoxycholic acid, nutricholic acid, 7α-hydroxy-3-oxo-4-cholestenoate, and cervonoyl ethanolamide. It was also significantly positively correlated with dolichylβ-D-glucosyl phosphate, docosapentaenoic acid (22n-6), 5,8,11-eicosatrienoic acid, and adrenaline. Eight metabolites, including citric acid, diacylglycerol (DG) (16:0 / 22:5), phosphatidylcholine (PC) (14:0 / 18:1) and PC (18:0 / 22:6), and retinylester, were significantly negatively correlated. These 12 significantly correlated metabolites may serve as potential biomarkers for SGR treatment of HUA.

[0097] 2.2.2 Metabolic pathway analysis

[0098] To identify key metabolic pathways, pathway enrichment function analysis using MetaboAnalyst was performed to analyze metabolic pathways between the NC and HUA groups, and between the HUA and SGR groups. Figure 6 (A). The HUA model affected 16 metabolic pathways. Based on an impact value greater than 0.1, three major biological pathways were identified, including glycerophospholipid metabolism, retinol metabolism, and the interconversion of pentose and glucuronic acid. SGR treatment affected 17 metabolic pathways, of which five were major, including α-linolenic acid metabolism, tryptophan metabolism, glycerol metabolism, retinol metabolism, and starch and sucrose metabolism. Furthermore, to identify KEGG pathways with low abundance changes but significant biological importance, metabolite set enrichment analysis (MSEA) was performed (Tables 2 and 3), listing the top three significant pathways. Based on p-values ​​<0.05, two KEGG pathways associated with the HUA effect were screened: α-linolenic acid and linoleic acid metabolism, and bile acid biosynthesis. Two SGR-restored KEGG pathways were obtained: α-linolenic acid and linoleic acid metabolism, and bile acid biosynthesis. These findings indicate that SGR selectively regulates metabolic disorders in HUA rats. The network of major metabolic pathways targeted by SGR treatment in HUA rats is shown below. Figure 6 As shown in Figure B, it specifically regulates four key pathways: bile acid metabolism, tryptophan metabolism, α-linolenic acid and linoleic acid, and glycerophospholipid metabolism.

[0099] Table 2. Results of differential metabolic pathway enrichment between NC and HUA groups

[0100]

[0101] Table 3. Results of differential metabolic pathway enrichment between HUA and SGR groups

[0102]

[0103] 2.316S rRNA sequencing analysis results

[0104] To determine how Smilax glabra affects the gut microbiota, we analyzed the 16S rDNA of rats in the normal, HUA, ALL, and MSGR groups. Partial least squares discriminant analysis (PLS-DA) clearly separated the NC, HUA, and MSGR groups. Figure 7 (A). At the genus level ( Figure 7In the MSGR group (B group), compared with the HUA group, the abundance of some beneficial bacteria such as Lactobacillus, norank_f__Muribaculaceae, and Ruminococcus increased, while the abundance of some harmful bacteria such as Turicibacter and Clostridium sensu stricto 1 decreased. Similarly, in the ALL group, the abundance of some beneficial bacteria such as norank_f__Muribaculaceae and Ruminococcus increased, while the abundance of some harmful bacteria such as Clostridium sensu stricto 1 decreased. However, the abundance of the harmful bacteria Turicibacter increased in the ALL group, suggesting intestinal flora dysbiosis. To identify the differentially expressed flora improved by Smilax glabra, linear discriminant analysis and coupling effect size measure (LEfSe) were used to further investigate the biomarkers with rich differences between the NC and HUA groups, the HUA and MSGR groups, and the HUA and ALL groups. Figure 8 (A). LEfSe analysis showed that MSGR treatment reversed the abnormal levels of three microorganisms—Turicibacter, Eubacterium_ventriosum_group, and Mucispirillum—in HUA rats, while ALL treatment reversed the abnormal level of Eubacterium_ventriosum_group. The abundance of the three differentially expressed microorganisms is presented as a box plot (A). Figure 8 (B). Spearman correlation analysis was performed on the three differentially expressed microorganisms and rat biochemical indicators. Figure 9 The results showed that SUA was positively correlated with all three differentially expressed gut microbiota.

[0105] Spearman correlation analysis was performed on 3 differentially expressed microorganisms and 23 differentially expressed metabolites. Figure 9The results showed that at least one of the differentially expressed microorganisms, *Turicibacter*, *Eubacterium_ventriosum_group*, and *Mucispirillum*, was significantly positively correlated with intestinal metabolites of primary bile acids (cholic acid and chenodeoxycholic acid), secondary bile acids and their metabolites (deoxycholic acid and muricholic acid), tryptophan metabolite (6-hydroxymelatonin), fatty acids and their derivatives (heptadecadienoic acid and docosahexaenoic acid), and cervonoyl ethanolamide; and with polyterpenoids (dolichylb-D-glucosyl phosphate), docosapentaenoic acid (22n-6), and 5,8,11-eicosatrienoic acid. The levels of adrenaline, adrenaline, diacylglycerol (DG) (16:0 / 22:5), oleamide, phosphatidylcholine (PC) (18:0 / 22:6), and retinyl ester were significantly negatively correlated.

[0106] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various modifications or variations within the scope of the claims, which do not affect the essence of the present invention.

Claims

1. A use of Smilax glabra in preparing a medicament for treating intestinal flora and / or metabolic disorders caused by hyperuricemia, characterized in that: The application is achieved by regulating the expression level of SUA-associated metabolite markers in serum. The SUA-associated metabolite markers include: Metabolites positively correlated with SUA include chenodeoxycholic acid, nutritional bile acid, 7α-hydroxy-3-oxo-4-cholestenic acid, and cerylethanolamide; Eight metabolites negatively correlated with SUA included dolichol-β-D-glucosyl phosphate, docosapentaenoic acid, 5,8,11-eicosatrienoic acid, adrenic acid, diacylglycerol (DG) (16:0 / 22:5), phosphatidylcholine (PC) (14:0 / 18:1), phosphatidylcholine (PC) (18:0 / 22:6), and retinyl esters.

2. The use according to claim 1, characterized in that The Chinese smilax glabra is a Chinese smilax glabra decoction, and the preparation method of the Chinese smilax glabra decoction comprises: (1) Soak the Chinese smilax glabra in water and then decoct it twice: first, decoct it at high heat of 90-100°C for 20-30 minutes, and then decoct it at low heat of 70-85°C for 50-60 minutes; collect the decoction; (2) Add water to the residue and boil it at high heat of 90-100℃ for 15-30 minutes, or at low heat of 70-85℃ for 40-60 minutes; (3) The two decoctions were combined and concentrated to obtain a decoction equivalent to 0.25 g to 0.5 g / mL of crude drug.

3. The use according to claim 2, characterized in that In step (1), the material-liquid ratio of the Chinese smilax glabra medicinal material and water is 1:8-1:

10.

4. A method for evaluating the effectiveness of Smilax glabra in treating hyperuricemia, characterized in that: The metabolic marker evaluation system was established through the following steps: (i) Metabolomics analysis of serum was performed using liquid chromatography-mass spectrometry to screen for differentially expressed metabolites associated with the pathological state of hyperuricemia; Chromatographic conditions: ACQUITY UPLC HSS T3 column, gradient elution time 0-12 min; Mass spectrometry conditions: ion source temperature 320°C, lens voltage 50 V, m / z scan range 67–1000; Positive ion mode detection parameters: spray voltage 3.2 kV; Negative ion mode detection parameters: spray voltage -2.8kV. (ii) Intestinal microbiota analysis was performed on fecal samples using 16S rRNA gene sequencing to detect changes in the abundance of Turicibacter, Eubacterium_ventriosum_group, and Myxospira; (iii) A Spearman correlation network model of serum differential metabolites and intestinal flora abundance was constructed to screen out SUA-associated metabolic markers.

5. The method according to claim 6, characterized in that The SUA-associated metabolic markers include: Four metabolites positively correlated with SUA included chenodeoxycholic acid, nutritional bile acid, 7α-hydroxy-3-oxo-4-cholestenic acid, and cerylethanolamide; Eight metabolites negatively correlated with SUA included dolichol-β-D-glucosyl phosphate, docosapentaenoic acid, 5,8,11-eicosatrienoic acid, adrenic acid, diacylglycerol (DG) (16:0 / 22:5), phosphatidylcholine (PC) (14:0 / 18:1), phosphatidylcholine (PC) (18:0 / 22:6), and retinyl esters.

6. A method for preparing a smilax glabra decoction, characterized in that: The preparation method comprises the following steps: (1) Soak the Chinese smilax glabra in water and then decoct it twice: first, decoct it at high heat of 90-100°C for 20-30 minutes, and then decoct it at low heat of 70-85°C for 50-60 minutes; collect the decoction; (2) Add water to the residue and boil it at high heat of 90-100℃ for 15-30 minutes, or at low heat of 70-85℃ for 40-60 minutes; (3) The two decoctions were combined and concentrated to obtain a standard decoction equivalent to 0.25-0.5 g / mL of crude drug.

7. A drug for treating hyperuricemia, characterized in that: The invention comprises the smilax glabra decoction prepared according to claim 6 as an active ingredient.

8. A biomarker combination for evaluating the efficacy of a Smilax glabra preparation, characterized in that: Include: Bacterial markers: Turicibacter, Eubacterium_ventriosum_group, and Myxospira abundance reduction values ≥ 40%; Metabolic markers: Serum levels of chenodeoxycholic acid, nutritional bile acid, 7α-hydroxy-3-oxo-4-cholestenic acid, and cerylethanolamide decreased; while levels of dolichol-β-D-glucosyl phosphate, docosapentaenoic acid, 5,8,11-eicosatrienoic acid, adrenic acid, diacylglycerol DG (16:0 / 22:5), phosphatidylcholine PC (14:0 / 18:1), phosphatidylcholine PC (18:0 / 22:6), and retinyl ester metabolites increased.

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