Abstract Objective To investigate the therapeutic effects of Guanxin Qiwei dropping pills (GXQW) on atherosclerosis (AS) and to delineate the mechanisms underlying these effects. Methods First, the chemical constituents of GXQW were identified using liquid chromatography-mass spectrometry (LC-MS). In addition, 15 batches of GXQW were used for fingerprint determination. Subsequently, an ApoE^−/− mouse model of AS induced by a high-fat diet was established. Lipid deposition, plaque coverage, and collagen fiber content in the aortic arch were evaluated using Oil Red O, H&E, and Masson’s trichrome staining, respectively. Enzyme-linked immunosorbent assay (ELISA) kits were employed to quantify serum oxidative stress markers, inflammatory cytokines, and lipid profiles. Additionally, fecal samples were subjected to 16S rRNA sequencing to investigate the effects of GXQW on intestinal dysbacteriosis. Differential gut microbiota were identified at the phylum-to-genus level. Furthermore, untargeted serum metabolomics was conducted to explore the potential metabolic pathways through which GXQW ameliorated AS. Results A total of 118 chemical constituents were identified in GXQW through database comparison. Compared to the model group, GXQW treatment attenuated lipid deposition and plaque coverage in the aortic arch and mitigated collagen depletion. Fingerprint analysis showed the consistency and stability of the quality of GXQW. Additionally, GXQW reduced total cholesterol (TC) and triglyceride (TG) levels, decreased the concentrations of inflammatory cytokines interleukin-6 (IL-6) and interleukin-1beta (IL-1β), suppressed malondialdehyde (MDA) activity, and elevated superoxide dismutase (SOD) levels. In terms of gut microbiota modulation, high-dose GXQW treatment promoted the abundance of Bacteroidota and decreased Firmicutes, particularly the Dubosiella genus within Firmicutes. KEGG pathway enrichment analysis of serum metabolites revealed that pathways associated with lipid metabolism, including Glycerophospholipid metabolism, Citric acid cycle (TCA cycle), and Arachidonic acid metabolism, were notably enriched. P-cresol sulfate (PCS) and other metabolites were identified as the potential metabolic biomarkers underlying the therapeutic effects of GXQW on AS. The correlation analysis further demonstrated a significant positive correlation between Dubosiella and the aforementioned metabolites. Conclusion The findings suggest that GXQW exerts evident therapeutic effects on AS by regulating gut microbiota and serum metabolic biomarkers. Keywords: atherosclerosis, Guanxin Qiwei dropping pills, metabolomics, gut microbiota, Dubosiella 1 Introduction Atherosclerosis (AS) is a severe vascular disease and the most prominent type of arteriosclerosis. Its pathological changes include arterial wall thickening, lipid deposition, and plaque formation and rupture, often accompanied by various clinical manifestations and risk factors ([43]Yuan et al., 2024). According to the 2023 “Global Cardiovascular Disease Burden” report published by the Journal of the American College of Cardiology (JACC), global mortality due to cardiovascular diseases increased from 12.4 million in 1990 to 19.8 million in 2022 ([44]Lei et al., 2023; [45]Kuang et al., 2024). If not properly managed, AS can lead to vascular stenosis, occlusion, organ ischemia, dysfunction, and severe complications, such as myocardial infarction, stroke, and renal failure, thereby posing a significant threat to patients’ health and survival ([46]Zheng et al., 2024). Metabolic diseases, such as AS, are garnering increasing attention due to the impact of gut microbiota on metabolic dysregulation ([47]Xu et al., 2025; [48]Sun et al., 2023). Gut microbiota is a complex community of microorganisms that interact closely with the host. Its potential roles in promoting, preventing, and treating human diseases, particularly metabolic disorders such as obesity and AS, are progressively gaining recognition. The composition and changes in the gut microbiota directly affect the host’s physiological balance ([49]Sun et al., 2021; [50]Chen et al., 2025). Furthermore, the metabolic potential of gut microbiota and its by-products are regarded as critical determinants influencing the host’s immune and metabolic functions ([51]Li et al., 2025). Given the essential role of gut microbiota and its metabolites in maintaining the host’s physiological homeostasis and metabolic equilibrium, interventions targeting these factors show substantial potential for modulating body functions and alleviating metabolic disturbances. Traditional Chinese Medicine (TCM) has been extensively accepted and applied in clinical settings in China, serving as a promising source for the development of new drugs ([52]Chen et al., 2023; [53]Zheng et al., 2022; [54]Li et al., 2023). Over the years, TCM has been reported to be effective in the treatment of AS ([55]Shao et al., 2024). For example, Fufang Danshen Dropping Pills, a traditional TCM formula, has been shown to improve blood flow, lower blood lipid levels, and enhance microcirculation, thereby alleviating lipid deposition in the arterial walls and effectively relieving various symptoms associated with AS. It also helps increase cardiac blood supply and reduces the risk of cardiovascular events ([56]Yu Y. et al., 2024). Another TCM formulation, Shenqi, has been shown to alleviate lower limb AS by influencing blood glucose fluctuations ([57]Huang et al., 2024). Guanxin Qiwei dropping pills (GXQW), a TCM compound composed of seven medicinal botanical drugs, including Myristicae semen (dried seed kernels of Myristica fragrans Houtt.), Choerospondiatis fructus (dried fruits of Choerospondias axillaris (Roxb.) B.L.Burtt and A.W.Hill), Santali albi lignum (dried heartwood of Santalum album L.), Codonopisis radix (dried roots of Codonopsis pilosula (Franch.) Nannf.), Kaempferiae Rhizoma (dried rhizomes of Kaempferia galanga L.), Dalbergiae odoriferae lignum (dried heartwood of Dalbergia odorifera T.C.Chen) and Hippophae Fructus (dried fruits of Hippophae rhamnoides L.). It is recorded in the Mongolian Medicine Volume of the Drug Standards of the Ministry of Health of the People’s Republic of China. GXQW is primarily used in treating coronary heart disease, irritability, palpitations, and angina ([58]Liao et al., 2025; [59]Yu Z. et al., 2024). Codonopisis radix serves as the principal ingredient, containing various active components that promote blood circulation, reduce platelet aggregation, improve microcirculation, prevent thrombosis, and exhibit antioxidant, vasodilatory, and anti-inflammatory effects ([60]Sun et al., 2021; [61]Chen et al., 2025). Among these components, salvianolic acid B has been demonstrated to possess anti-AS and antioxidant pharmacological activities ([62]Li et al., 2025), while cryptotanshinone has shown properties such as anti-ischemic myocardial injury and suppression of inflammatory responses ([63]Chen et al., 2023). Additionally, the other botanical drugs in the formula, such as Santali albi lignum, can relieve pain and regulate qi; Dalbergiae odoriferae lignum has stasis-resolving and hemostatic effects; Myristicae semen exerts a warming effect on the middle Jiao and facilitates Qi circulation; Choerospondiatis fructus, Kaempferiae Rhizoma, and Hippophae Fructus can promote blood circulation and resolve blood stasis ([64]Zheng et al., 2022; [65]Li et al., 2023; [66]Shao et al., 2024; [67]Yu Y. et al., 2024; [68]Huang et al., 2024; [69]Liao et al., 2025; [70]Yu Z. et al., 2024). However, the specific mechanisms through which GXQW improves AS remain under debate. In response to this, this study first identified the chemical components of GXQW through liquid chromatography-mass spectrometry (LC-MS). Following this, an ApoE^−/− mouse model of AS induced by a high-fat diet was established. Lipid accumulation, plaque coverage, and collagen content in the aortic arch were assessed using Oil Red O, H&E, and Masson staining. Additionally, ELISA kits were used to measure serum oxidative stress, inflammatory cytokines, and blood lipid levels. Furthermore, 16S rRNA sequencing of feces was conducted to investigate the effect of GXQW on gut microbiota dysbiosis, with differential microbiota being selected at the phylum-to-genus level. Untargeted serum metabolomics was also employed to elucidate the potential mechanisms of GXQW in improving AS, with differential serum metabolites identified based on P < 0.05, VIP > 1, and Log[2]FoldChange > 2. Finally, a correlation analysis between characteristic gut microbiota and differential metabolites was conducted. This study aims to clarify the mechanisms through which GXQW improves AS, establishing a theoretical basis for future strategies aimed at regulating the gut microbiota through TCM to improve AS. 2 Materials and methods 2.1 Experimental materials Individual botanical drugs of GXQW were sourced from the markets in Sichuan and Anhui provinces (China). Enzyme-linked immunosorbent assay (ELISA) kits were purchased from Abbkine Biotechnology Co., Ltd. (China). For detailed information, please refer to [71]Supplementary Table S1. 2.2 Animals ApoE^−/− mice were purchased from Sipeifu Biotechnology Co., Ltd. (Beijing, China) (License No. SCXK (Beijing) 2019-0010) and housed at the Animal Experiment Center of Inner Mongolia Medical University (SPF, License No. SYXK (Meng) 2020-0003). At 6 weeks of age, Male mice (n = 12 per group). 2.3 Preparation of GXQW Guanxin Qiwei dropping pills (GXQW), a TCM compound composed of seven medicinal botanical drugs, including Myristicae semen (batch number: 220101-02, dried seed kernels of M. fragrans Houtt.), Choerospondiatis fructus (batch number: 170901, dried fruits of C. axillaris (Roxb.) B.L.Burtt and A.W.Hill), Santali albi lignum (batch number: 221001, dried heartwood of S. album L.), Codonopisis radix (batch number: 230601, dried roots of C. pilosula (Franch.) Nannf.), Kaempferiae Rhizoma (batch number: A220208, dried rhizomes of K. galanga L.), Dalbergiae odoriferae lignum (batch number: 210401, dried heartwood of D. odorifera T.C.Chen) and Hippophae Fructus (batch number: 710220901, dried fruits of H. rhamnoides L.). It is recorded in the Mongolian Medicine Volume of the Drug Standards of the Ministry of Health of the People’s Republic of China. The whole plant materials of the seven botanical drug materials were obtained from their original source and the botanic identification was confirmed by Professor ShengSang Na (Inner Mongolia Medical University, Hohhot, China). The specimens were deposited at the herbarium of medicinal plants (The Center for New Drug Safety Evaluation and Research, Inner Mongolia Medical University, Roudoukou20240016, Guangzao20240017, Tanxiang20240018, Danshen20240019, Shannai20240020, Jiangxiang20240021, Shaji20240022. The detailed botanical drugs parts of GXQW are shown in [72]Supplementary Table S2. The plant names were verified on 17 Jun 2025, from [73]https://mpns.science.kew.org/mpns-portal ([74]Heinrich et al., 2022). The clinical original dosage is 6.9 g per person per day, with extraction carried out in two parts. Choerospondiatis fructus, Codonopisis radix, and Hippophae Fructus were combined (4.6 g) for alcohol extraction, yielding 0.98 g of extract at a 21.3% extraction rate. Meanwhile, Myristicae semen, Santali albi lignum, Kaempferiae Rhizoma, and Dalbergiae odoriferae lignum (2.3 g) underwent supercritical CO[2] extraction, producing 0.23 g of volatile oil with a 10% extraction rate. This extract was then combined with 1.5 times polyethylene glycol and Tween 80 to prepare the drops, totaling 3.03 g. The preparation process of GXQW is shown in [75]Figure 1. Considering the average weight of a normal adult (60 kg) and the human-to-mouse conversion factor (9.1), the equivalent dosage for mice was calculated as follows: GXQW-low dose = 3.03 g × 9.1/60 kg = 460 mg/kg, GXQW-medium dose = 3.03 g × 9.1/60 kg × 2 = 920 mg/kg and GXQW-high dose = 3.03 g × 9.1/60 kg × 4 = 1840 mg/kg. Of which 3.03 g includes 1.21 g of drug dose (0.98 g + 0.23 g), and the other 1.82 g is the weight of excipients. Therefore, the actual drug dose given to the animal should be: GXQW-low dose = 1.21 g × 9.1/60 kg = 183.52 mg/kg, GXQW-medium dose = 1.21 g × 9.1/60 kg × 2 = 367.04 mg/kg, GXQW-high dose = 1.21 g × 9.1/60 kg × 4 = 734.08 mg/kg. Therefore, the actual high dose of GXQW does not exceed 1 g/kg. FIGURE 1. [76]Flowchart depicting the preparation of GXQW composition of Chinese medicine. It details alcohol extraction and CO₂ supercritical extraction methods. Ingredients include Choerospondiae fructus and Myristicae semen. The process involves grinding, ethanol extraction, filtration, and concentration. Volatile oils and items like PEG4000 are used. The solution is heat mixed with Tween 80, freeze dried, and formed into dropping pills. Pills are stored at two to four degrees Celsius. [77]Open in a new tab The preparation process of Guanxin Qiwei Dropping Pills GXQW. 2.4 Detection of GXQW components An ACQUITY UPLC I-Class HF ultra-high-performance liquid chromatography system combined with a QE high-resolution mass spectrometer was employed in the experiment. Chromatographic conditions: The chromatographic column was ACQUITY UPLC HSS T3, with a column temperature of 45°C. Mobile phase A consisted of water with 0.1% formic acid, and mobile phase B was acetonitrile, with a flow rate of 0.35 mL/min. Additionally, the PDA scanning range was between 210 and 400 nm. The elution gradients are detailed in [78]Supplementary Table S3. Mass spectrometry conditions: The ion source was HESI. The signal collection was carried out in both positive and negative ion scanning modes. The data acquisition mode was DDA. The scan mode was Full MS/dd-MS2 (TOP 8). Specific parameters are listed in [79]Supplementary Table S4. 2.5 GXQW fingerprint 2.5.1 Chromatographic conditions The chromatographic analysis was performed using a Shim-pack GIST-HP C18 column (2.1 mm × 100 mm, 3 μm). The mobile phase consisted of methanol (A) and 0.2% phosphoric acid aqueous solution (B), delivered at a flow rate of 0.8 mL/min. The column temperature was maintained at 35°C, with an injection volume of 5 μL. Detection was carried out at 254 nm. The gradient elution program was as follows: 0–8 min: 8% → 25% A; 8–20 min: 25% → 40% A; 20–30 min: 40% → 42% A; 30–40 min: 42% → 55% A; 40–45 min: 55% → 58% A; 45–60 min: 58% → 66% A; 60–75 min: 66% → 75% A; 75–78 min: 75% → 75% A; 75–78 min: 75% → 75% A; 78–82 min: 75% → 8% A; 82–90 min: 8% → 8% A. 2.5.2 Establishment of GXQW fingerprint Fifteen batches of GXQW samples were analyzed under the specified chromatographic conditions. The resulting chromatograms were converted into CDF format and imported into the 2012 version of the Chinese Medicine Chromatographic Fingerprint Similarity Evaluation System. Sample S1 of GXQW was selected as the reference chromatogram, and fingerprint analysis was performed using the median method with a time window of 0.1 min. After applying multi-point correction and marker peak alignment, the overlaid chromatograms and the reference fingerprint profile were successfully generated. 2.6 Animal administration and model construction ApoE^−/− male mice were used as the model animals. The mice were randomly divided into a control group, a model group, a high-dose GXQW group (1840 mg/kg), a medium-dose GXQW group (920 mg/kg), a low-dose GXQW group (460 mg/kg), and a positive drug simvastatin group (2.6285 mg/kg), with 12 mice per group. Except for the control group, all groups were fed a high-fat diet for 8 weeks to induce AS. Afterward, all groups except the control and model groups were given different concentrations of GXQW and simvastatin by gavage for eight consecutive weeks. The diet and body weight of the mice were monitored throughout the experiment. All animal experiments in this study were approved by the Animal Ethics Committee of Inner Mongolia Medical University (YKD202404035). 2.7 Serum biochemical analysis According to the instructions provided by the reagent kits, the levels of the following serum biochemical markers were measured: total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), interleukin-6 (IL-6), interleukin-1beta (IL-1β), superoxide dismutase (SOD), and malondialdehyde (MDA). 2.8 Histopathological analysis At the end of the experimental period, the mice were euthanized, and the aortas were collected and fixed in 4% paraformaldehyde for histological analysis. The abdominal aorta of ApoE^−/− mice was dissected and subjected to Oil Red O staining. The aortic sinuses were embedded in the OCT compound, frozen, and sectioned. Afterward, Oil Red O staining, Hematoxylin-Eosin (H&E) staining, and Masson’s Trichrome staining were performed to observe lipid content, plaque coverage, and collagen fiber content. Images were captured under a stereomicroscope. The lipid area ratio was calculated using Image-Pro Plus 6.0 software. 2.9 Sequencing of microbiota from colonic excrement samples and data analysis 2.9.1 DNA extraction and PCR amplification Genomic DNA was extracted from the colonic content using the MagPure Soil DNA LQ Kit (Magan) according to the manufacturer’s instructions. DNA concentration and purity were determined using a NanoDrop 2000 (Thermo Fisher Scientific, United States) and agarose gel electrophoresis. The extracted DNA was stored at −20°C. PCR amplification of the 16S rRNA gene was performed using barcoded specific primers and Takara Ex Taq high-fidelity polymerase. The universal primers 343F (5′-TACGGRAGGCAGCAG-3′) and 798R (5′-AGG​GTA​TCT​AAT​CCT-3′) were used to amplify the V3-V4 hypervariable region of the 16S rRNA gene for bacterial diversity analysis. 2.9.2 Library construction and sequencing The PCR products were verified using agarose gel electrophoresis and purified using AMPure XP beads. Subsequently, they were used as templates for a second round of PCR amplification and purification. The purified second-round products were quantified using the Qubit fluorometer, and the concentration was adjusted accordingly for sequencing. Sequencing was performed using the Illumina NovaSeq 6000 platform, generating 250 bp paired-end reads. 2.9.3 Bioinformatics analysis Raw sequence data were processed using Cutadapt software to trim primer sequences. Based on DADA2 ([80]Fan et al., 2023), The resulting qualified paired-end data were subjected to quality control analysis using QIIME2 ([81]Yang et al., 2024) with default parameters. This process included quality filtering, denoising, merging, and chimera removal, ultimately generating representative sequences and an ASV (Amplicon Sequence Variant) abundance table. Representative sequences for each ASV were selected using the QIIME2 pipeline and subsequently taxonomically annotated by aligning against the SILVA database (version 138). Taxonomic assignment was performed using the ‘q2-feature-classifier’ plugin with default parameters. Alpha and beta diversity analyses were conducted within the QIIME2 framework. Alpha diversity, including Good’s coverage ([82]Islam et al., 2025; [83]Gao et al., 2024), was adopted to evaluate sample alpha diversity. Unweighted UniFrac distance matrices were computed in R and used to perform Principal Coordinates Analysis (PCoA) to assess beta diversity. Differential abundance analysis was carried out using statistical methods such as ANOVA, Kruskal-Wallis, t-tests, and Wilcoxon tests in R packages. 2.10 Metabolomics analysis 2.10.1 Analytical conditions The analysis was conducted using a Waters ACQUITY UPLC I-Class plus coupled with a Thermo QE high-resolution mass spectrometer. Chromatographic conditions: column is ACQUITY UPLC HSS T3 (100 mm × 2.1 mm, 1.8 µm); column temperature is 45°C; mobile phase A is water (containing 0.1% formic acid); mobile phase B is acetonitrile; flow rate is 0.35 mL/min; injection volume is 3 μL. The elution gradient is presented in [84]Supplementary Table S5, and the mass spectrometry parameters are listed in [85]Supplementary Table S6. 2.10.2 Sample preparation Serum samples from ApoE^−/− mice were added a protein precipitation reagent (methanol-acetonitrile mixture, V1:V2 = 2:1, containing internal standard at 4 μg/mL), vortexed, allowed to stand, and then centrifuged. The supernatant was collected for LC-MS analysis. Quality control (QC) samples were prepared by mixing equal volumes of all extracted samples. All reagents for extraction were pre-cooled at −20°C before use. 2.10.3 Bioinformatics analysis First, unsupervised principal component analysis (PCA) was performed to observe the overall distribution of samples and assess the stability of the analysis process. Subsequently, supervised partial least squares discriminant analysis (PLS-DA) was applied to differentiate the metabolic profiles between the groups and identify the differential metabolites. 2.11 Statistical analysis Prior to analysis, all data were assessed for normality and homogeneity of variance. SPSS software was used for statistical analysis, and GraphPad Prism version 10 was used to generate graphs. For analysis of differences between the groups, we used one-way ANOVA and LSD post hoc tests. There was statistical significance at the P < 0.05 level. 3 Results 3.1 Comprehensive chemical profiling of GXQW using UPLC-QE Orbitrap MS In order to identify chemical components, GXQW was analyzed using the ACQUITY UPLC I-Class HF coupled with a Thermo Orbitrap QE high-resolution mass spectrometer. The base peak ion (BPC) chromatograms in both positive and negative ion modes were obtained ([86]Figures 2A,B). A total of 118 compounds from GXQW were identified by comparison with databases and references ([87]Supplementary Table