Elucidating the Mechanism of Modified Yiguanjian against Anti‐Tuberculosis Drug‐Induced Liver Injury via Integrated Pharmacology and Metabolomics

ABSTRACT

This study aimed to investigate the therapeutic effects and molecular mechanisms of Modified Yiguanjian (MYGJ) in treating anti‐tuberculosis drug‐induced liver injury (ATB‐DILI). ATB‐DILI is a serious side effect of TB treatment, often leading to liver damage, drug resistance, or failure. The research integrated serum pharmacochemistry, network pharmacology, and metabolomics to uncover MYGJ's hepatoprotective mechanisms. Using ultra‐high‐performance liquid chromatography coupled with quadrupole‐electrostatic field orbitrap mass spectrometry, the study identified 11 prototype compounds of MYGJ in blood serum, including Apigenin and Lonicerin. The ATB‐DILI mouse model induced by isoniazid, rifampicin, and pyrazinamide showed MYGJ's effectiveness in reducing liver enzyme levels (alanine aminotransferase, aspartic transaminase, and alkaline phosphatase), improving histopathology, and lowering pro‐inflammatory cytokines (tumor necrosis factor‐α, interleukin [IL]‐1β, and IL‐6). Network pharmacology identified 128 shared targets, including key molecules like TP53 and AKT1, and suggested tyrosine and purine metabolism as critical pathways. Metabolomics identified 95 altered metabolites, with MYGJ reversing 38 of them. Molecular docking confirmed strong binding between MYGJ compounds and targets like adenosine deaminase and myeloperoxidase. Overall, MYGJ alleviated ATB‐DILI through multi‐target, multi‐pathway actions, demonstrating its potential for liver protection in clinical settings.

This study investigates the therapeutic mechanism of Modified Yiguanjian (MYGJ) against anti‐tuberculosis drug‐induced liver injury (ATB‐DILI). By integrating serum pharmacochemistry, network pharmacology, and metabolomics, the research identifies 11 bioactive blood‐borne components and key targets, including MPO and ADA. The results demonstrate that MYGJ alleviates liver damage by reducing inflammation, restoring purine and tyrosine metabolism, and regulating key enzymatic pathways, providing a scientific basis for its clinical use.

Abbreviations

ADA

adenosine deaminase

AGC

automatic gain control

ALP

alkaline phosphatase

ALT

alanine aminotransferase

ANOVA

analysis of variance

AST

aspartate aminotransferase

ATB‐DILI

anti‐tuberculosis drug‐induced liver injury

BC

betweenness centrality

BP

biological process

CC

cellular component

CC

closeness centrality

DC

degree centrality

ELISA

enzyme‐linked immunosorbent assay

GO

gene ontology

HE

hematoxylin‐eosin staining

IL‐1β

interleukin‐1β

IL‐6

interleukin‐6

INH

isoniazid

KEGG

Kyoto Encyclopedia of Genes and Genomes

KM

Kunming

MF

molecular function

MPO

myeloperoxidase

MYGJ

Modified Yiguanjian

MYGJ‐H

MYGJ high‐dose

MYGJ‐L

MYGJ low‐dose

MYGJ‐M

MYGJ medium‐dose

OPLS‐DA

orthogonal partial least squares discriminant analysis

PCA

principal component analysis

PDB

Protein Data Bank

PPI

protein‐protein interaction

PZA

pyrazinamide

QC

quality control

RFP

rifampicin

SD

Sprague‐Dawley

SM

silibinin meglumine

TB

tuberculosis

TCM

traditional Chinese medicine

TNF‐α

tumor necrosis factor‐alpha

UPLC‐Q‐Exactive Orbitrap‐MS

ultra‐high‐performance liquid chromatography coupled with quadrupole‐electrostatic field orbitrap mass spectrometry

VIP

variable importance in projection

XDH

xanthine dehydrogenase/oxidase

1. Introduction

Anti‐tuberculosis drug‐induced liver injury (ATB‐DILI) is recognized as one of the most common adverse reactions associated with ATB therapy. Characterized by a notable incidence rate, ATB‐DILI often leads to severe complications during ATB treatment and ranks among the most frequent subtypes of drug‐induced liver injury (DILI). The primary global strategy for TB management is the short‐course directly observed treatment, short‐course strategy recommended by the World Health Organization, which involves the combined administration of isoniazid (INH), rifampicin (RFP), pyrazinamide (PZA), and ethambutol [1, 2]. However, first‐line ATB drugs, including PZA, RFP, and INH, exhibit intrinsic hepatotoxic potential, which can induce ATB‐DILI. This condition may result in treatment failure, the emergence of drug‐resistant TB, and even life‐threatening outcomes such as liver failure and death in severe cases [3, 4, 5]. Reported prevalence rates of ATB‐DILI range from 2.0% to 28% among patients undergoing ATB therapy [6, 7, 8]. Clinical cases have shown that interruptions or adjustments in ATB regimens due to ATB‐DILI often exacerbate TB progression, leading to treatment failure and fatal liver failure. Therefore, investigating therapeutic agents for ATB‐DILI is critical to mitigate and prevent this condition during ATB treatment.

The pathogenesis of ATB‐DILI is multifactorial, involving direct hepatotoxicity of ATB drugs and their metabolites, inflammatory responses, oxidative stress, genetic polymorphisms [9], and perturbations in proteomic and metabolomic profiles, such as bile acids and amino acids [10, 11]. Consequently, antioxidant and anti‐inflammatory agents may serve as potential safeguards against ATB drug‐induced hepatotoxicity. Traditional Chinese medicine (TCM) has been extensively validated to exert notable hepatoprotective effects, including antioxidant, anti‐inflammatory, anti‐free radical, and hepatocyte enzyme‐lowering activities [12, 13], positioning it as a promising therapeutic option for ATB‐DILI. To date, the TCM field has developed approximately 100 000 therapeutic approaches for DILI, with over 80% based on compound Chinese herbal prescriptions [14].

Yiguanjian, a classic TCM formula, has been widely used in the clinical management of liver diseases. Originating from Xu Ming Yi Lei An (Records of Famous Physicians through the Ages) compiled by Zhixiu Wei, a renowned Qing Dynasty physician, it is hailed as “the preeminent formula for nourishing liver Yin (a concept in TCM referring to the cooling, structural, and nourishing aspects of the liver)” [15]. Traditionally, Yiguanjian has been applied to treat liver disorders such as liver injury, hepatitis, liver fibrosis, and cirrhosis [16, 17]. Previous studies on ATB‐DILI have demonstrated that modifying the Yiguanjian formula or integrating it with Western medicine can significantly enhance its efficacy [18, 19]. Given that ATB‐DILI often presents with liver yin deficiency and qi‐blood imbalance, our research team adopted a “clearing and supplementing” therapeutic strategy, optimized the traditional Yiguanjian formula, and developed the Modified Yiguanjian (MYGJ). Clinically, MYGJ has shown remarkable therapeutic effects in patients with ATB‐DILI. Composed of 15 herbal components—Shengdihuang (Rehmannia glutinosa (Gaertn.) DC.), Beishashen (Glehnia littoralis F. Schmidt ex Miq.), Danggui (Angelica sinensis (Oliv.) Diels), Maidong (Ophiopogon japonicus (Thunb.) Ker Gawl.), Gouqizi (Lycium barbarum L.), Danshen (Salvia miltiorrhiza Bunge), Mabiancao (Verbena officinalis L.), Mugua (Chaenomeles speciosa (Sweet) Nakai), Longdancao (Gentiana cruciata L.), Baijiangcao (Patrinia scabiosifolia Link), Baishao (Cyathella otophylla (C.K.Schneid.) C.Y.Wu & D.Z.Li), Wuweizi (Schisandra chinensis (Turcz.) Baill.), Jineijin (Gallus gallus domesticus Brisson), Sharen (Amomum villosum Lour.), and Gancao (Glycyrrhiza uralensis Fisch.)—MYGJ exerts a comprehensive liver yin‐nourishing effect, achieving superior therapeutic outcomes.

This study integrated serum pharmacochemistry, network pharmacology, and metabolomics to investigate the protective effects and underlying mechanisms of MYGJ against ATB‐DILI. Specifically, serum pharmacochemistry was employed to identify the blood‐borne components of MYGJ. Network pharmacology was used to analyze the complex interactions among herbal compounds, key targets, and signaling pathways. An ATB‐DILI mouse model was established to validate the pharmacodynamic effects of MYGJ. Non‐targeted metabolomics, utilizing ultra‐high‐performance liquid chromatography coupled with quadrupole‐electrostatic field orbitrap mass spectrometry (UPLC‐Q‐Exactive Orbitrap‐MS), was applied to explore the impact of MYGJ on endogenous metabolic processes. Finally, data from network pharmacology and metabolomics were integrated to comprehensively elucidate the pharmacodynamic mechanisms of MYGJ, providing theoretical support for its clinical application in ATB‐DILI management.

2. Materials and Methods

2.1. Main Drugs and Reagents

All herbal components of MYGJ were procured from Jingchang Traditional Chinese Medicine Co., Ltd. (Nanning, China). INH tablets (batch number: T22J090) were obtained from Hangzhou Minsheng Pharmaceutical Co., Ltd. (Hangzhou, China). RFP capsules (batch number: E2522031) and PZA tablets (batch number: 220290119) were purchased from Shenyang Hongqi Pharmaceutical Co., Ltd. (Shenyang, China) and Chongqing Huabang Pharmaceutical Co., Ltd. (Chongqing, China), respectively. Silibinin meglumine (SM) tablets (batch number: 230702) were supplied by Jiangsu Zhongxing Pharmaceutical Co., Ltd. (Jiangsu, China). Isoflurane for animal anesthesia (batch number: 20230320003) was provided by Shenzhen Reward Life Technology Co., Ltd. (Shenzhen, China). Enzyme‐linked immunosorbent assay (ELISA) kits for interleukin‐6 (IL‐6, batch number: 345133‐003), tumor necrosis factor‐α (TNF‐α, batch number: 286081‐012), and IL‐1β (batch number: 359880‐003) were purchased from Thermo Fisher Scientific (Waltham, MA, USA).

2.2. Animals Used in the Experiment

Specific pathogen‐free‐grade Sprague‐Dawley (SD) rats (10 males, 180–220 g) and Kunming (KM) mice (60, 18–22 g, equal male/female ratio) were sourced from the Experimental Animal Center of Guangxi Medical University (Nanning, China). The facility holds the experimental animal production license (SCXK Gui 2020‐0003) and animal use license (SYXK Gui 2020‐0004). Animals were housed under controlled conditions: temperature 25° ± 2°C, relative humidity 50% ± 5%, and a 12 h light/dark cycle. The animal experimental protocol was approved by the Animal Ethics Committee of Guangxi Medical University (ethical review number: 202309002).

2.3. Preparation of MYGJ

The composition and dosages of MYGJ components are listed in Table 1. The quality and quantity of all herbs used complied with the standards set by the Chinese Pharmacopoeia (2020 edition). Briefly, the 15 herbal materials were immersed in a 12‐fold volume of water (v/w) and decocted twice by boiling for 1.5 h each time. The combined decoctions were filtered, concentrated to a crude drug concentration of 1.5 g/mL, cooled, sealed, and stored at 4°C for subsequent use.

TABLE 1.

Composition and dosage of Modified Yiguanjian (MYGJ).

Herb Chinese name	Latin name	Dosage (g)
Shengdihuang	Rehmannia glutinosa (Gaertn.) DC.	10
Beishashen	Glehnia littoralis F. Schmidt ex Miq.	10
Danggui	Angelica sinensis (Oliv.) Diels	5
Maidong	Ophiopogon japonicus (Thunb.) Ker Gawl.	5
Gouqizi	Lycium barbarum L.	10
Danshen	Salvia miltiorrhiza Bunge	10
Mabiancao	Verbena officinalis L.	10
Mugua	Chaenomeles speciosa (Sweet) Nakai	10
Longdancao	Gentiana cruciata L.	5
Baijiangcao	Patrinia scabiosifolia Link	10
Baishao	Cyathella otophylla (C.K.Schneid.) C.Y.Wu & D.Z.Li	5
Wuweizi	Schisandra chinensis (Turcz.) Baill.	5
Jineijin	Gallus gallus domesticus Brisson	10
Sharen	Amomum villosum Lour.	3
Gancao	Glycyrrhiza uralensis Fisch.	5

2.4. Preparation of MYGJ Medicated Serum

SD rats were randomly divided into two groups (n = 5 per group): a control group and a MYGJ‐medicated serum group. The MYGJ group was administered MYGJ solution (20.286 g/kg) twice daily for five consecutive days via intragastric gavage, while the control group received an equal volume of distilled water. The dosing volume was 20 mL/kg. One hour after the final administration, rats were anesthetized with isoflurane, and blood was collected via abdominal aorta puncture. Blood samples were allowed to clot at room temperature for 1 h, centrifuged at 3000 rpm for 10 min, and the supernatant serum from animals within the same group was pooled to ensure sample homogeneity and minimize individual variation. Serum was heat‐inactivated at 56°C for 30 min, sterilized through a micropore filter, and stored at −80°C.

2.5. Serum Pharmacochemistry and Metabolomics Analysis

2.5.1. Sample Preparation

2.5.1.1. TCM Powder Sample

Approximately 1 g of herbal powder was extracted with 40 mL of 80% methanol via ultrasonic extraction for 1 h. The mixture was centrifuged at 12 000 rpm for 10 min at 4°C, and 100 µL of the supernatant was transferred to an injection vial for analysis.

2.5.1.2. Serum Sample

Control and MYGJ‐medicated serum (100 µL each) were mixed with 300 µL of methanol, vortexed for 10 min, and centrifuged at 12 000 rpm for 10 min at 4°C. The supernatant (100 µL) was transferred to an injection vial.

2.5.1.3. Standard Sample

Single‐standard solutions (1 mg/mL) were prepared with 50% methanol/water. A mixed standard solution (5 µg/mL per compound) was prepared by diluting the single standards with 50% methanol/water and injected for analysis.

2.5.1.4. Liver Tissue Sample for Metabolomics

Liver tissues (50 mg) from the Control, Model, and MYGJ‐H groups were weighed, homogenized with 100 µL of ultrapure water for 1 min, and mixed with 400 µL of water and 500 µL of methanol. Samples were vortexed for 30 min, centrifuged at 12 000 r/min for 10 min at 4°C, and 120 µL of the supernatant was transferred to a 250 µL insert vial for analysis. Quality control (QC) samples were prepared by pooling equal volumes of all experimental samples, with data acquisition consistent with that of experimental samples.

2.5.2. UPLC‐Q‐Exactive Orbitrap‐MS Analysis

Chromatographic separation for both serum and liver tissue samples was performed on an ACQUITY UPLC HSS T3 column (1.8 µm, 2.1 × 100 mm; Waters, Milford, MA, USA) with a mobile phase consisting of (A) 0.1% formic acid in water and (B) methanol. The elution gradient was: 0–1 min, 2% B; 1–41 min, 2%–100% B; 41–50 min, 100% B; 50–50.1 min, 100%–2% B; 50.1–52.0 min, 2% B. The flow rate was 0.3 mL/min, injection volume 10.0 µL, and column temperature 40°C.

MS was conducted using an electrospray ionization ion source in both positive and negative modes. Parameters were: ion source voltage, 3.7 kV (positive) and 3.5 kV (negative); capillary temperature, 320°C; sheath gas pressure, 30 psi; auxiliary gas pressure, 10 psi; auxiliary gas heater temperature, 300°C; collision gas (nitrogen), 1.5 mTorr. Full‐scan parameters: mass range 150–1500 m/z, resolution 70 000, automatic gain control (AGC) target 1 × 10⁶, maximum injection time 50 ms. Data‐dependent MS² (dd‐MS²) parameters: resolution 17 500, AGC target 1 × 10⁵, maximum injection time 50 ms, top 10 ions, isolation window 2 m/z, intensity threshold 1 × 10⁵, collision energy 30 eV. Data were acquired using Xcalibur 2.2 SP1.48 software.

For metabolomics data processing, Progenesis QI software (Nonlinear Dynamics, Newcastle, UK) was used to identify reproducible metabolites. Metabolites were annotated via matching with the Human Metabolome Database and LipidMaps. Multivariate statistical analysis, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS‐DA), was conducted using SIMCA 14.1 software (Umetrics, Umeå, Sweden). Differentially expressed metabolites were defined by variable importance in projection (VIP) > 1 and t‐test p < 0.05.

2.6. Network Pharmacology

2.6.1. Prediction of TCM and Disease Targets

Potential targets of MYGJ components were predicted using the SwissTargetPrediction database (http://www.swisstargetprediction.ch/) with a probability threshold >0.1. Disease‐related targets for ATB‐DILI and DILI were retrieved from DisGeNET (https://www.disgenet.org/), OMIM (https://www.omim.org/), and GeneCards (https://www.genecards.org/) using the keywords “antituberculous drug induced liver injury” and “drug‐induced liver injury.” GeneCards targets were filtered with a relevance score >20. Duplicate targets were removed to obtain a final set of DILI‐related targets.

2.6.2. Protein‐Protein Interaction Analysis and Core Target Screening

The intersection of MYGJ component targets and DILI‐related targets was visualized using a Venn diagram. Protein‐protein interaction (PPI) networks of the intersection targets were constructed using the STRING 11.5 database (https://cn.string‐db.org/) with a confidence score ≥0.9. The CytoNCA plugin in Cytoscape 3.10.2 was used to analyze network topology, including degree centrality (DC), betweenness centrality (BC), and closeness centrality (CC). Core targets were identified via two‐round screening: first, DC > 2 × median DC; second, DC > median DC, BC > median BC, and CC > median CC.

2.6.3. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes Enrichment Analysis

Intersection targets were uploaded to the DAVID database (https://david.ncifcrf.gov/) with identifiers set to “OFFICIAL_GENE_SYMBOL” and species “Homo sapiens.” Gene Ontology (GO) analysis (biological process [BP], molecular function [MF], and cellular component [CC]) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed with a threshold of p < 0.05.

2.6.4. Molecular Docking

Three‐dimensional structures of MYGJ components were downloaded from PubChem (https://pubchem.ncbi.nlm.nih.gov/) and converted to PDBQT format using Open Babel. Protein structures corresponding to core targets were retrieved from UniProt (https://www.uniprot.org/) and the Protein Data Bank (PDB, https://www.rcsb.org/). Water molecules and bound ligands were removed from protein structures using PyMOL. Molecular docking was performed using AutoDock Vina [20, 21], with binding energy calculated to evaluate ligand‐receptor interactions. The optimal docking conformations were analyzed for ligand‐receptor interactions using the PLIP web tool (https://plip‐tool.biotec.tu‐dresden.de/plip‐web/plip/index) [22] and visualized in PyMOL.

2.7. Animal Experiment

2.7.1. Animals and Administration

KM mice were randomly assigned to six groups (n = 10 per group): control, model (ATB‐DILI), SM (0.15 g/kg), MYGJ high‐dose (MYGJ‐H, 29.3 g/kg), MYGJ medium‐dose (MYGJ‐M, 14.65 g/kg), and MYGJ low‐dose (MYGJ‐L, 7.325 g/kg). The dosages were determined based on the human clinical dose (98 g/day for a 60 kg adult) and converted to a mouse‐equivalent dose using the body surface area normalization method, as described in the Guide for the Care and Use of Laboratory Animals. The medium dose (MYGJ‐M) of 14.65 g/kg is equivalent to the clinical dose, with the low (MYGJ‐L) and high (MYGJ‐H) doses set at 0.5 and 2 times this equivalent dose, respectively, to assess dose‐dependent effects. Mice were administered treatment intragastrically twice daily: at 10:00 AM, the control group received 0.5% sodium carboxymethylcellulose solution, while the remaining groups received the ATB‐DILI modeling fluid (INH: 0.15 g/kg; RFP: 0.3 g/kg; PZA: 0.63 g/kg). At 4:00 PM, the Control and Model groups were administered normal saline, the SM group received silibinin meglumine solution, and the MYGJ groups received MYGJ solutions at respective doses. The intragastric volume was 0.2 mL/10 g, and administration continued for 21 consecutive days. Animal body weights were measured every 3 days to adjust the dosing volume accordingly. After the final administration, mice were fasted for 16 h (with free access to water), anesthetized with isoflurane, and blood samples were collected via orbital puncture. Liver tissues were excised, with a portion fixed in 4% paraformaldehyde for histological analysis and the remainder stored at ‐80°C for subsequent assays.

2.7.2. Biochemical Testing

Serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and alkaline phosphatase (ALP) were measured using a Hitachi automatic biochemical analyzer (Hitachi, Tokyo, Japan) according to the manufacturer's protocols.

2.7.3. Histopathological Analysis

Fixed liver tissues were processed through standard histological procedures: trimming, dehydration in graded ethanol, clearing in xylene, embedding in paraffin, sectioning (4–5 µm thickness), and staining with hematoxylin‐eosin (HE). Stained sections were visualized under an Olympus BX53 upright light microscope (Olympus, Tokyo, Japan) for histopathological evaluation.

2.7.4. Enzyme‐Linked Immunosorbent Assay

Liver tissue homogenates (10%) were prepared by homogenizing 50 mg of liver tissue in ice‐cold phosphate‐buffered saline using a tissue homogenizer, followed by centrifugation at 12 000 r/min for 10 min at 4°C. Supernatants were collected, and serum levels of TNF‐α, IL‐1β, and IL‐6 were quantified using commercial ELISA kits (Thermo Fisher Scientific, USA) following the manufacturer's instructions. Absorbance was measured at 450 nm using a microplate reader (BioTek, Winooski, VT, USA).

2.8. Statistical Analysis

Statistical analysis was performed using IBM SPSS Statistics 27 software (IBM, Armonk, NY, USA). Data were first tested for normality (Shapiro‐Wilk test) and homogeneity of variance (Levene's test). For normally distributed data with equal variances, one‐way analysis of variance (ANOVA) followed by the least significant difference (LSD) test was used for pairwise comparisons. For data with unequal variances, Welch's ANOVA with Dunnett's T3 post‐hoc test was applied. Results are presented as mean ± standard deviation (SD). A p‐value < 0.05 was considered statistically significant. Graphical visualization was performed using GraphPad Prism 8 software (GraphPad Software, San Diego, CA, USA).

3. Results

3.1. Identification of Blood Components of MYGJ

A total of 99 components were identified in the serum of healthy rats following MYGJ administration, including 11 prototype components. These prototype components comprised Apigenin, 5,7‐dihydroxyflavanone, Bilatriene, Vanillic acid beta‐d‐glucopyranosyl ester, Gentiopicroside, Lonicerin, Isovitexin, Daidzein, 1‐acetoxy‐9,17‐octadecadiene‐12,14‐diyne‐11,16‐diol, Morusin, and Prehispanolone. The total ion current chromatograms are presented in Figure S1, and detailed information on these blood prototype components (including m/z, retention time, fragments, ion mode, formula, and source herb) is summarized in Table 2.

TABLE 2.

Blood‐entering prototype components of Modified Yiguanjian (MYGJ).

No.	Ingredient name	m/z	Retention time (min)	Fragments	Ion mode	Formula	Source herb	English name
1	Apigenin	271.0600532	22.37	271.0597, 153.0182, 137.0598, 215.0708, 91.0553, 84.9609, 81.071, 55.0558, 243.0655, 69.0714	[M + H]+	C15H10O5	Mabiancao	Common Verbena Herb
2	5,7‐dihydroxyflavanone	257.0806632	24.08	137.0233, 257.0797, 256.2626, 147.0438, 57.0713, 119.0495, 69.0711, 55.0557, 67.0555, 81.071	[M + H]+	C15H12O4	Gancao	Liquorice Root
3	Bilatriene	299.1265801	32.75	—	[M + H]+	C19H14N4	Jineijin	Chicken's Gizzard‐membrane
4	Vanillic acid beta‐d‐glucopyranosyl ester	329.0876002	6.93	—	[M − H]−	C14H18O9	Sharen	Villous Amomum Fruit
5	Gentiopicroside	355.1036243	11.67	—	[M − H]−	C16H20O9	Mabiancao, Longdancao	Common Verbena Herb, Gentian Root
6	Lonicerin	593.1511252	15.12	—	[M − H]−	C27H30O15	Mabiancao	Common Verbena Herb
7	Isovitexin	431.0976877	16.81	—	[M − H]−	C21H20O10	Bineijin	Chicken's Gizzard‐membrane
8	Daidzein	253.0497505	20.37	253.0501, 133.0268, 146.9836, 208.0512, 224.0464, 232.9835	[M − H]−	C15H10O4	Maidong	Dwarf Lilyturf Tuber
9	1‐acetoxy‐9,17‐octadecadiene‐12,14‐diyne‐11,16‐diol	331.1911176	32.24	331.1906, 92.9262, 152.8935, 92.9169, 61.9857, 196.8844, 179.399, 148.9167, 90.9307, 132.1433	[M − H]−	C20H28O4	Danggui	Chinese Angelica
10	Morusin	419.1519799	35.24	115.9179, 99.923, 91.5888, 419.1512, 172.8612, 83.9623, 146.9586, 116.9264, 61.9857, 394.8411	[M − H]−	C25H24O6	Gancao	Liquorice Root
11	Prehispanolone	317.2112926	35.50	—	[M − H]−	C20H30O3	Wuweizi	Chinese Magnoliavine Fruit

3.2. Network Pharmacology

3.2.1. Active Ingredients and Potential Targets of MYGJ for DILI

The 11 blood‐entering prototype components of MYGJ were input into the SwissTargetPrediction database, yielding 311 potential drug targets. Disease‐related targets for DILI were retrieved from GeneCards (556 targets), OMIM (336 targets), and DisGeNET (289 targets). After removing duplicates, a total of 1,026 DILI‐related disease targets were obtained. A Venn diagram was constructed to visualize the overlap between drug targets and disease targets, revealing 128 common targets (Figure 1A).

FIGURE 1.

 Network pharmacology analysis of the active ingredients, targets, and pathways of Modified Yiguanjian (MYGJ) on DILI. (A) Venn diagram of MYGJ targets and drug‐induced liver injury (DILI)‐related disease targets. (B) Protein‐protein interaction (PPI) network of the 128 intersection targets. (C) Combined histogram of the top 10 Gene Ontology (GO) terms for biological processes (BP), cellular components (CC), and molecular functions (MF). (D) Bubble chart of the top 20 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. (E) Sankey diagram illustrating the relationships between MYGJ active ingredients and the top 20 enriched pathways.

The STRING database was used to analyze the 128 intersection targets, resulting in a PPI network comprising 128 nodes and 307 edges. Using the CytoNCA plugin in Cytoscape 3.10.2, topological parameters (DC, BC, and closeness centrality [CC]) were calculated. Two rounds of screening were performed: first, with thresholds of DC > 4, BC > 45.5187, and CC > 0.1078 (primary screening yielding 32 core nodes); second, with stricter thresholds of DC > 9, BC > 595.0035, and CC > 0.1142 (secondary screening yielding seven core nodes: TP53, HSP90AA1, AKT1, SRC, ESR1, PIK3CA, and EGFR) (Figure 1B).

3.2.2. GO and KEGG Enrichment Analysis

A total of 584 BP terms, 79 cellular component (CC) terms, 137 MF terms, and 172 KEGG pathways were enriched. The top 10 terms for BP, CC, and MF are visualized in a histogram (Figure 1C), and the top 20 KEGG pathways are presented as a bubble chart (Figure 1D).

BP: Enriched terms included “response to external stimulus,” “negative regulation of apoptotic process,” “protein phosphorylation,” and “positive regulation of cell proliferation.”

CC: Key terms were “plasma membrane,” “extracellular region,” “cell membrane,” “membrane raft,” and “cell surface.”

MF: Dominant terms involved “enzyme binding,” “identical protein binding,” “protein serine/threonine kinase activity,” and “protein tyrosine kinase activity.”

KEGG pathway analysis highlighted enrichment in “pathways in cancer,” “PI3K‐Akt signaling pathway,” and “atherosclerosis,” among others. A “TCM compound‐component‐pathway‐disease” network was constructed, incorporating 10 active ingredients and 20 signaling pathways. The Sankey diagram (Figure 1E) indicated that 5,7‐dihydroxyflavanone, Apigenin, and Morusin may be critical bioactive ingredients.

3.3. Pharmacodynamic Experiments

3.3.1. Histopathological Analysis (HE Staining)

Compared with the Control group, the Model group exhibited extensive hepatocyte steatosis (characterized by cytoplasmic round vacuoles of varying sizes, indicated by black arrows), focal hepatocyte necrosis and karyorrhexis (blue arrows), mild lymphocyte infiltration (green arrows), and small‐area hemorrhage (red arrows) around the central vein. In contrast, the SM group and all MYGJ dose groups (MYGJ‐L, MYGJ‐M, and MYGJ‐H) significantly alleviated liver pathological damage, reducing steatosis, degeneration, necrosis, and inflammatory infiltration (Figure 2).

FIGURE 2.

Effect of Modified Yiguanjian (MYGJ) on liver histopathology in anti‐tuberculosis drug‐induced liver injury (ATB‐DILI) mice (HE staining, ×200 magnification). (A) Control group, showing normal liver architecture. (B) Model group, showing extensive hepatocyte steatosis (black arrows), focal necrosis and karyorrhexis (blue arrows), mild lymphocyte infiltration (green arrows), and hemorrhage (red arrows). (C) Silibinin meglumine (SM) group, (D) MYGJ low‐dose (MYGJ‐L) group, (E) MYGJ medium‐dose (MYGJ‐M) group, and (F) MYGJ high‐dose (MYGJ‐H) group, all showing significant alleviation of pathological damage.

3.3.2. Serum Biochemical Analysis

Compared with the Control group, serum activities of ALT, AST, and ALP were significantly elevated in the Model group (p < 0.05). Compared with the Model group:

All MYGJ dose groups and the SM group significantly reduced ALT activity (p < 0.05).

MYGJ‐M, MYGJ‐H, and SM groups significantly decreased AST and ALP activities (p < 0.05), whereas MYGJ‐L showed no significant effect on AST and ALP (Figure 3A–C).

FIGURE 3.

Effect of Modified Yiguanjian (MYGJ) on serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), interleukin (IL)‐6, IL‐1β, and tumor necrosis factor‐alpha (TNF)‐α in anti‐tuberculosis drug‐induced liver injury (ATB‐DILI) mice. Data are presented as mean ± SD (n = 10). ^# p < 0.05, ^## p < 0.01, ^### p < 0.001 versus Control group; ^* p < 0.05, ^** p < 0.01, ^*** p < 0.001 versus Model group. (A) ALT activity; (B) AST activity; (C) ALP activity; (D) TNF‐α level; (E) IL‐1β level; (F) IL‐6 level.

These results indicate that MYGJ effectively mitigates INH/RFP/PZA‐induced elevation of ALT, AST, and ALP.

3.3.3. Inflammatory Factor Analysis

Compared with the Control group, levels of TNF‐α, IL‐1β, and IL‐6 were significantly increased in the Model group (p < 0.05). Compared with the Model group:

MYGJ‐H and SM groups significantly reduced TNF‐α levels (p < 0.05).

MYGJ‐M, MYGJ‐H, and SM groups significantly decreased IL‐6 levels (p < 0.05).

All MYGJ dose groups and the SM group significantly reduced IL‐1β levels (p < 0.05) (Figure 3D–F).

These findings demonstrate that MYGJ potently inhibits INH/RFP/PZA‐induced hepatic inflammatory responses.

3.4. Untargeted Metabolomic Analysis

3.4.1. Metabolic Profiling

QC samples exhibited tight clustering in both positive and negative ion modes, confirming stable and reproducible data acquisition (Figure 4A,B). Unsupervised PCA revealed clear separation between the Model and Control groups, indicating that ATB drug treatment perturbed hepatic metabolism (Figure 4C,D). Supervised OPLS‐DA further distinguished the Model and Control groups, with high model fitness (R²Y = 0.993, Q² = 0.971 in positive mode; R²Y = 0.996, Q² = 0.971 in negative mode). Permutation tests (n = 200) confirmed no overfitting, as all Q² values on the left were lower than the true values, and Q² regression lines intersected the Y‐axis at negative values (Figure 4E–H).

FIGURE 4.

Multivariate statistical analysis of hepatic metabolomic data. (A, B) Principal component analysis (PCA) score plots of quality control (QC) samples in positive and negative ion modes, respectively. (C, D) PCA score plots of the Control, Model, and Modified Yiguanjian high‐dose (MYGJ‐H) groups in positive and negative ion modes, respectively. (E, F) Orthogonal partial least squares discriminant analysis (OPLS‐DA) score plots comparing the Model and Control groups in positive and negative ion modes, respectively. (G, H) Permutation test results for the OPLS‐DA model comparing the Model and Control groups in positive and negative ion modes, respectively (n = 200 permutations).

3.4.2. Differential Metabolite Screening

Metabolites with VIP > 1 and p < 0.05 were identified as differentially expressed. A total of 95 differential metabolites were detected between the Model and Control groups (detailed information, including VIP scores, fold changes, and p‐values, is provided in Table S1). MYGJ intervention reversed 38 of these, with five metabolites significantly normalized: 4‐pyridoxic acid, LysoPC (20:5/0:0), Xanthine, Inosine, and Nicotinic acid. The heat map in Figure 5 illustrates the hierarchical clustering of these differential metabolites.

FIGURE 5.

Heat map of differential metabolites between the Model and Control groups, and their modulation by Modified Yiguanjian high‐dose (MYGJ‐H). Rows represent metabolites, and columns represent sample groups. Color intensity reflects relative metabolite levels (red: upregulated; blue: downregulated).

3.4.3. Metabolic Pathway Analysis

Pathway enrichment analysis (impact value > 0.01, p < 0.05) revealed that MYGJ modulates 12 metabolic pathways to alleviate ATB‐DILI, including glycerophospholipid metabolism, sphingolipid metabolism, pyrimidine metabolism, nicotinate and nicotinamide metabolism, tryptophan metabolism, phenylalanine/tyrosine/tryptophan biosynthesis, cysteine/methionine metabolism, purine metabolism, glutathione metabolism, glycine/serine/threonine metabolism, phenylalanine metabolism, and ether lipid metabolism. Detailed pathway information is provided in Table 3 and Figure 6.

TABLE 3.

Potential metabolic pathway information.

Pathway name	−log(p)	Impact
Pyrimidine metabolism	2.4404	0.14933
Sphingolipid metabolism	1.8049	0.27767
Glycerophospholipid metabolism	1.6663	0.21631
Nicotinate and nicotinamide metabolism	1.5925	0.1943
Tryptophan metabolism	1.5167	0.20852
Phenylalanine, tyrosine, and tryptophan biosynthesis	1.1775	0.5
Cysteine and methionine metabolism	0.97194	0.12535
Purine metabolism	0.93305	0.03128
Phenylalanine metabolism	0.80071	0.35714
Ether lipid metabolism	0.53427	0.08176
Glutathione metabolism	0.41519	0.0246
Glycine, serine, and threonine metabolism	0.35079	0.04766

FIGURE 6.

Metabolic pathway enrichment analysis of differential metabolites. Pathways are ranked by −log(p) (statistical significance) and impact value (pathway perturbation). The top 12 enriched pathways are displayed.

3.5. Comprehensive Analysis of Metabolomics and Network Pharmacology

A compound‐reaction‐enzyme‐gene network was constructed by integrating metabolomic and network pharmacology data, highlighting two key metabolic pathways (tyrosine metabolism and purine metabolism), four key metabolites (L‐phenylalanine, Inosine, Xanthosine, and Xanthine), and three key targets (myeloperoxidase [MPO], xanthine dehydrogenase/oxidase [XDH], and adenosine deaminase [ADA]) (Figure 7). These elements are hypothesized to play critical roles in MYGJ's therapeutic mechanism. Detailed information is summarized in Table 4.

FIGURE 7.

Compound‐reaction‐enzyme‐gene network integrating metabolomics and network pharmacology data. (A) Tyrosine metabolism pathway; (B) Purine metabolism pathway. Nodes represent compounds (green), reactions (yellow), enzymes (blue), and genes (red). Key metabolites, enzymes, and genes are highlighted.

TABLE 4.

Key metabolites, targets, and metabolic pathway information.

Pathway	Key target	Key metabolite
Tyrosine metabolism	MPO	L‐Phenylalanine
Purine metabolism	ADA and XDH	Inosine, Xanthosine, and Xanthine

3.6. Molecular Docking

Molecular docking validated the binding of key targets MPO (PDBID: 4C1M) and ADA (PDBID: 3IAR) with active ingredients Apigenin and Lonicerin, respectively. Binding energy (<−5 kcal·mol^{− 1}) and interaction modes were analyzed.

3.6.1. Apigenin‐MPO

Apigenin formed hydrogen bonds with GLN‐257, HIS‐261, ARG‐405, ARG‐499, and GLY‐501 at the MPO active site, along with hydrophobic interactions with GLN‐257 and ARG‐499. Binding energy: −9.8 kcal·mol^{− 1}.

3.6.2. Lonicerin‐ADA

Lonicerin formed hydrogen bonds with ASN‐118, ILE‐115, TRP‐117, HIS‐17, GLY‐184, and PRO‐114 at the ADA active site, along with hydrophobic interactions with LEU‐62, PHE‐65, LEU‐106, and TRP‐117. Binding energy: −9.6 kcal·mol^{− 1}.

These results confirm strong binding between Apigenin‐MPO and Lonicerin‐ADA (Figure 8).

FIGURE 8.

Three‐dimensional structures of optimal ligand‐protein binding conformations from molecular docking. (A) Interaction between Apigenin and myeloperoxidase (MPO, PDBID: 4C1M). Hydrogen bonds are shown as green dashed lines; hydrophobic interactions are indicated by surrounding residues. (B) Interaction between Lonicerin and adenosine deaminase (ADA, PDBID: 3IAR). Hydrogen bonds and hydrophobic interactions are annotated.

4. Discussion

Traditional Chinese medicine (TCM) compounds exert therapeutic effects through the synergistic action of multiple components, pathways, and targets. Network pharmacology, as a novel approach, enables systematic exploration of the complex relationships between pharmaceuticals, targets (such as MPO and ADA), and diseases on a global scale [23, 24]. Contemporary pharmacological theory posits that the absorption of active components of TCM compounds into the bloodstream is a prerequisite for their efficacy. Serum pharmacochemistry, by identifying blood‐borne components and their metabolites, elucidates the roles of the body in drug absorption and metabolism, thereby revealing the compatibility rules and pharmacodynamic material basis of TCM [25, 26, 27]. UPLC‐Q‐Exactive Orbitrap‐MS, renowned for its high resolution and sensitivity, is highly effective for rapid characterization of TCM components in biological samples. Using this technique, we identified 99 components in the serum of MYGJ‐treated rats, including 11 prototype components: Apigenin, 5,7‐dihydroxyflavanone, Bilatriene, Vanillic acid beta‐d‐glucopyranosyl ester, Gentiopicroside, Lonicerin, Isovitexin, Daidzein, 1‐acetoxy‐9,17‐octadecadiene‐12,14‐diyne‐11,16‐diol, Morusin, and Prehispanolone. These 11 prototype components were subjected to network pharmacology analysis, yielding 311 predicted drug targets. An overlap with 1026 DILI‐related disease targets (from GeneCards, OMIM, and DisGeNET) identified 128 intersection targets. Subsequent PPI analysis and topological screening revealed seven core targets (TP53, HSP90AA1, AKT1, SRC, ESR1, PIK3CA, and EGFR). GO and KEGG enrichment further highlighted associations with protein phosphorylation, protein serine/threonine kinase activity, and the PI3K‐Akt signaling pathway, implicating these processes in MYGJ's mechanism of action.

ALT, AST, and ALP are critical biomarkers for assessing liver injury. ALT is primarily localized in hepatocyte cytoplasm, while AST is enriched in mitochondria; ALP is derived from the liver, bones, and intestines [28]. Liver injury increases cell membrane permeability, releasing these enzymes into the bloodstream and elevating serum levels [29]. Inflammation, driven by danger signals from dying hepatocytes, amplifies liver damage via pro‐inflammatory cytokines (e.g., TNF‐α, IL‐1β, IL‐6), which propagate the injury cascade [30, 31]. In this study, MYGJ mitigated INH/RFP/PZA‐induced hepatic histopathological damage (e.g., steatosis, necrosis, inflammation) and reduced serum ALT, AST, and ALP activities, as well as hepatic TNF‐α, IL‐1β, and IL‐6 levels. These findings confirm that MYGJ protects against ATB drug‐induced liver injury by improving liver function and suppressing inflammation [32].

The combined use of INH, RFP, and PZA is a standard clinical regimen for TB to prevent drug resistance and ensure therapeutic efficacy. However, these drugs exhibit intrinsic hepatotoxicity, mediated by direct toxicity, toxic metabolites, or immune responses, affecting hepatocytes, hepatic vasculature, and biliary epithelium  [33]. INH induces hepatotoxicity via its metabolites acetylhydrazine (AcHz) and hydrazine (Hz) [34], and triggers immune responses, oxidative stress, and apoptosis  [35, 36]. RFP exacerbates INH‐induced hepatotoxicity by inducing microsomal enzymes and amidases, increasing toxic hydrazine production [37]. PZA hepatotoxicity is primarily driven by its metabolites, pyrazinoic acid and 5‐hydroxypyrazinoic acid [38], with immune‐mediated mechanisms also contributing [39]. Thus, hepatic metabolism of ATB drugs is central to the pathogenesis of ATB‐DILI.

Untargeted metabolomic analysis of liver tissue from ATB‐DILI mice identified 95 differential metabolites between the Model and Control groups. MYGJ intervention reversed 38 of these, with 5 metabolites (4‐pyridoxic acid, LysoPC (20:5/0:0), Xanthine, Inosine, Nicotinic acid) significantly normalized. MYGJ primarily modulates 12 metabolic pathways: sphingolipid, pyrimidine, glycerophospholipid, tryptophan, cysteine/methionine, phenylalanine/tyrosine/tryptophan biosynthesis, nicotinate/nicotinamide, purine, ether lipid, phenylalanine, glycine/serine/threonine, and glutathione metabolism. Integrating network pharmacology data, we constructed a compound‐reaction‐enzyme‐gene network, identifying two key pathways (tyrosine metabolism, purine metabolism), four key metabolites (L‐phenylalanine, Inosine, Xanthosine, and Xanthine), and three key targets (MPO, XDH, and ADA).

Purine metabolism, involving adenosine, ATP, and key enzymes (ADA and XDH), is critical for energy balance and nucleotide synthesis [40]. ADA catalyzes adenosine deamination to hypoxanthine (then inosine) [41], while XDH oxidizes hypoxanthine to xanthine and subsequently to uric acid, a process that generates reactive oxygen species (ROS) [42]. Elevated uric acid not only promotes hyperuricemia and gout but also acts as a danger signal that triggers immune dysfunction and inflammation. In this study, Model mice exhibited increased inosine, xanthosine, and xanthine levels, which normalized with MYGJ treatment. This suggests MYGJ restores purine homeostasis by inhibiting ADA and XDH activities. By downregulating these enzymes, MYGJ could reduce the production of uric acid and associated ROS, thereby mitigating oxidative stress and the subsequent inflammatory cascade, ultimately protecting against ATB‐DILI.

L‐phenylalanine, an essential amino acid, is critical for protein synthesis and serves as the precursor for tyrosine production (via hepatic phenylalanine hydroxylase [PAH]), which supports neurotransmitter and hormone synthesis. Liver injury disrupts phenylalanine metabolism by impairing PAH activity, leading to perturbations in tyrosine metabolism [43]. MPO, an enzyme predominantly found in neutrophils, is a marker of neutrophil activation. It mediates host defense under physiological conditions but promotes oxidative stress and inflammation in pathological states [44]. MPO is a key enzyme that generates potent reactive oxidants such as hypochlorous acid (HOCl), contributing to lipid peroxidation, protein damage (e.g., formation of 3‐chlorotyrosine), and exacerbation of inflammation during liver injury [45]. Here, Model mice showed reduced L‐phenylalanine levels, which were reversed by MYGJ, suggesting MYGJ improves phenylalanine/tyrosine metabolism. Our results showed that L‐phenylalanine levels were restored by MYGJ, suggesting improved phenylalanine/tyrosine metabolism. Molecular docking confirmed a strong binding affinity between Apigenin, a key component of MYGJ, and MPO. This suggests that MYGJ may directly inhibit MPO activity, thereby reducing oxidative damage and inflammation, which helps restore overall metabolic homeostasis in the injured liver.

Regarding clinical translation, the dosages used in this study were pharmacologically relevant, with the medium dose corresponding to the standard human clinical dose based on body surface area conversion. MYGJ, being derived from a classic formula with a long history of clinical use, is generally considered to have a favorable safety profile. However, systematic toxicological studies are still necessary to fully characterize any potential adverse effects, especially in the context of co‐administration with ATB drugs. Future clinical trials should be designed to confirm the efficacy and safety of MYGJ in patients with ATB‐DILI, optimize dosing regimens, and explore its long‐term benefits in improving treatment adherence and outcomes in TB therapy.

However, this study has several limitations. First, the key targets identified through network pharmacology and integrated analysis, such as MPO, XDH, and ADA, were not experimentally validated at the protein or gene expression level using techniques like Western blotting or RT‐qPCR. Such validation would provide more direct evidence for their roles in MYGJ's mechanism. Second, our metabolomics analysis was untargeted; follow‐up studies using targeted metabolomics would be beneficial to more accurately quantify the changes in key differential metabolites. Finally, while we identified blood‐borne prototype components, the contribution of metabolites and the synergistic effects among different components require further investigation.

5. Conclusion

In conclusion, this study systematically elucidated the hepatoprotective mechanism of MYGJ against ATB‐DILI by integrating serum pharmacochemistry, network pharmacology, and metabolomics. We identified 11 key blood‐borne components and demonstrated that MYGJ alleviates liver injury by improving liver function, reducing inflammation, and restoring metabolic homeostasis. The integrated analysis pinpointed that MYGJ's therapeutic effects are mediated through the modulation of key targets like MPO and ADA, which are central to regulating purine and tyrosine metabolism pathways. These findings not only unravel the complex, multi‐target, multi‐pathway mechanism of MYGJ but also provide a strong scientific rationale for its clinical application in managing ATB‐DILI.

Author Contributions

Yu Tu: project administration, writing – original draft, methodology, validation, and visualization. Xuting Wu: conceptualization, project administration, and resources. Mingna Wei: data acquisition. Shunxia Du: supervision. Jian Ou: conceptualization. Jiangping Yang: writing – review – editing. Xuenian Liu: formal analysis. Jinglun Huang: formal analysis. Aijun Jiao: conceptualization. Changyuan Wu: conceptualization, funding acquisition, and writing – review – editing.

Funding

This research was sponsored by the 2022 Strategic Cooperation Fund between Shenzhen Third People's Hospital and Lianyungang Huilan Charity Foundation; self‐raised funds from Guangxi Central Administration Bureau (No. GXZYZ20210424); Nanning Fourth People's Hospital's Key Scientific Research Project (No. NNSY2021005).

Ethics Statement

The animal experimental protocol was approved by the Animal Ethics Committee of Guangxi Medical University (ethical review number: 202309002). For the participation in this research, ethical approval was obtained from the overseeing committee, as direct consent is not applicable in animal studies.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Supporting File 1: cbdv70862‐sup‐0001‐SuppMat.docx

Data Availability Statement

The data and materials used and/or analysed during the current study are available from the corresponding author on reasonable request.