Biomarker combination for evaluating progress of abdominal aortic aneurysm based on adventitia and application of biomarker combination

Abstract

The invention provides a biomarker combination for evaluating the progress of abdominal aortic aneurysm based on an adventitia and application of the biomarker combination, and the biomarker combination comprises at least two biomarkers selected from the following three independent groups, the at least two markers are from the same group or different groups: a myofibroblast transformation marker group: alpha-smooth muscle actin, monocyte chemotactic protein 1 and a tissue metalloproteinase inhibitor 1; the lipid metabolism related biomarker group comprises a lipid metabolism related protein CD36, carnitine palmitoyl transferase 1 and a fatty acid binding protein 4; and an inflammatory factor related biomarker group: IL-6, MCP-1 and TIMP1. According to the biological marker combination for evaluating the progress of the abdominal aortic aneurysm based on the adventitia, multi-channel biological markers are systematically integrated, an innovative tool is provided for accurate diagnosis, drug screening and curative effect monitoring of AAA, and meanwhile, an important foundation is laid for developing a collaborative treatment strategy based on adventitia fibroblast regulation.

Description

Technical Field

[0001] The present invention belongs to the field of biomedicine technology, and specifically relates to a biomarker combination based on the vascular adventitia for evaluating the progression of abdominal aortic aneurysm and its use. Background Art

[0002] Abdominal aortic aneurysm (AAA) is a fatal cardiovascular disease characterized by pathological dilatation of the aorta. It has a high risk of rupture and is insidious in onset, and has become a major challenge to global public health. The pathological mechanism of AAA involves the loss of mechanical integrity of the vessel wall, leading to irreversible dilatation and a high rupture rate. Although minimally invasive techniques such as endovascular repair (EVAR) have been widely used in clinical practice, they still face problems such as endoleaks, morphological limitations, and narrow surgical indications. In particular, there is a lack of effective intervention methods for small aneurysms with a diameter of less than 5.5 cm. In addition, existing treatment strategies mostly focus on end-stage interventions, and there is a lack of targeted drug therapies for early AAA progression, resulting in significant gaps in clinical management.

[0003] Existing biomarker research is often limited to single pathological processes (such as inflammation or fibrosis), lacking a systematic combination of biomarkers to comprehensively assess AAA progression. For example, while myofibroblast transformation markers such as α-smooth muscle actin (Acta2) have been extensively studied, their dynamic associations with lipid metabolism and inflammatory factors have yet to be integrated. Furthermore, traditional detection methods struggle to achieve combined analysis of multiple biomarkers, limiting the accuracy of early diagnosis and drug screening. Therefore, there is an urgent need to develop a biomarker combination based on multi-pathway regulation to guide early intervention and treatment evaluation for AAA. Summary of the Invention

[0004] The purpose of the present invention is to provide a biomarker combination based on the vascular adventitia for evaluating the progression of abdominal aortic aneurysm, systematically integrating multi-pathway biomarkers, providing an innovative tool for the precise diagnosis, drug screening and efficacy monitoring of AAA, and at the same time laying an important foundation for the development of synergistic treatment strategies based on the regulation of adventitial fibroblasts.

[0005] In a first aspect, the present invention provides a biomarker combination based on the vascular adventitia for assessing the progression of abdominal aortic aneurysm, wherein the biomarker combination comprises at least two biomarkers selected from the following three independent groups, wherein the at least two biomarkers are from the same group or different groups: a) Myofibroblast transformation marker panel: α-smooth muscle actin (Acta2), monocyte chemoattractant protein 1 (Ccl2), and tissue inhibitor of metalloproteinases 1 (Timp1); b) lipid metabolism-related biomarker panel: lipid metabolism-related protein CD36, carnitine palmitoyltransferase 1 (CPT1), and fatty acid binding protein 4 (FABP4); c) Inflammatory factor-related biomarker group: IL-6, MCP-1 and TIMP1.

[0006] The second aspect of the present invention provides the use of a detection reagent having specific binding affinity for the above-mentioned biomarker combination in the preparation of a kit for detecting the progression of an abdominal aortic aneurysm.

[0007] In one embodiment of the present invention, the detection reagent is used to specifically identify and quantify the expression level of the biomarker.

[0008] A third aspect of the present invention provides use of a biomarker combination in screening candidate drugs for inhibiting the progression of abdominal aortic aneurysm.

[0009] In one embodiment of the present invention, the candidate drug screening comprises the following steps: (i) Establishing abdominal aortic aneurysm models in vitro or in animals; (ii) applying a drug candidate to the model; (iii) detecting changes in the expression levels of the biomarker combination in adventitial fibroblasts in the model; (iv) Screening of effective drug candidates based on the following criteria: The expression of the myofibroblast transformation marker group is downregulated, and / or the expression of the lipid metabolism-related biomarker group is upregulated, and / or the expression of the inflammatory factor-related biomarker group is downregulated.

[0010] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention provides a biomarker combination based on the vascular adventitia for assessing the progression of abdominal aortic aneurysm. By integrating three independent groups of biomarkers: myofibroblast transformation markers (Acta2, Ccl2, Timp1), lipid metabolism-related proteins (CD36, CPT1, FABP4), and inflammatory factors (IL-6, MCP-1, TIMP1), it can reflect the pathological process of AAA in multiple dimensions, including the phenotypic transformation of adventitial fibroblasts, metabolic disorders, and the inflammatory microenvironment, significantly improving the accuracy of diagnosis and prognostic assessment.

[0011] 2. The adventitial biomarker combination provided by this invention for assessing abdominal aortic aneurysm progression can serve as a key indicator for screening candidate drugs for inhibiting AAA progression. By examining the regulatory effects of candidate drugs on myofibroblast transformation markers (downregulation), lipid metabolism markers (upregulation), and inflammatory factors (downregulation), drug efficacy can be rapidly assessed, accelerating the development of targeted treatment strategies.

[0012] 3. In the biomarker combination based on the vascular adventitia for evaluating the progression of abdominal aortic aneurysm provided by the present invention, the design of the marker combination takes into account the independence of different groups, allowing flexible selection of markers in the same group or across groups for testing according to clinical needs.

[0013] 4. The biomarker combination based on the vascular adventitia for evaluating the progression of abdominal aortic aneurysms provided by the present invention can help initiate intervention before the aneurysm reaches surgical indications by identifying abnormal activation and metabolic disorders of adventitial fibroblasts in early AAA, thereby reducing the risk of rupture and filling the current technical gap in the management of small aneurysms. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] 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: Figure 1 This is the UMAP distribution diagram of the tissue cells of the mouse abdominal aortic aneurysm and the control group in Example 1; Figure 2 This is a graph comparing the expression levels of Vimentin, Acta2, Ccl2, and Timp1 genes in fibroblast clusters of the AAA group and the control group in Example 1 (mouse single-cell sequencing results); Figure 3 Schematic diagram of the myofibroblast transformation of adventitial fibroblasts during abdominal aortic aneurysm; Figure 4 Figure 1 is the result of identification of the phenotype of cultured adventitial fibroblasts (AFs); Figure 5 The figure shows the results of Western blot analysis of the expression of myofibroblast markers (α-SMA and Collagen I) under treatment with different concentrations of Lanifibranor in Example 2; Figure 6 Representative images of α-SMA immunofluorescence staining under different concentrations of lanifibranor treatment in Example 2, used to evaluate the myofibroblast transformation of adventitial fibroblasts; scale bar = 100 μm; Figure 7 The figure shows the quantitative expression levels of myofibroblast markers (α-SMA and Collagen I) based on Western blot images in Example 2; *p < 0.05, **p < 0.01 and ***p < 0.001; Figure 8 Figure 2 shows the quantitative immunofluorescence staining of α-SMA-positive adventitial fibroblasts in Example 2; *p < 0.05, **p < 0.01 and ***p < 0.001; Figure 9The figure shows the results of determining the optimal concentration of Lanilanol to inhibit CaCl2-induced AFs migration; Figure 10 Volcano plot of differentially expressed genes (DEGs); Figure 11 GO and KEGG annotations related to abnormal lipid metabolism and cell proliferation in fibroblasts after LT treatment in Example 2; Figure 12 This is a heat map of differentially expressed genes related to lipid metabolism in Example 2; Figure 13 This is a heat map of differentially expressed genes related to cell proliferation in Example 2; Figure 14 This is the classic GSEA analysis of ether lipid metabolism and cell cycle in Example 2; Figure 15 Classic GSEA analysis for lipid metabolism-related annotations; Figure 16 Classic GSEA analysis for cell proliferation-related annotations; Figure 17 Western blot analysis of the expression levels of cell cycle and proliferation-related genes (CD36, CPT1, and FABP4); Figure 18 To quantitatively analyze the expression levels of cell cycle and proliferation-related genes (CD36, CPT1, and FABP4); Figure 19 Western blot analysis of the expression levels of lipid metabolism-related genes (CCND1, CDC6, and CDK1); Figure 20 The expression levels of lipid metabolism-related genes (CCND1, CDC6, and CDK1) were quantitatively analyzed; Figure 21 The OCR curve shows the difference in fatty acid metabolism levels between the control group and the Lanifibranor group; Figure 22 The ECAR curve shows the difference in overall cellular metabolism between the control group and the Lanifibranor group; Figure 23 Representative images and quantitative analysis of Oil Red O staining of adventitial fibroblasts (AFs) in the control and Lanilanol groups; Figure 24 The results of CCK-8 experiments were used to evaluate the proliferation ability of AFs after treatment with the lipid metabolism inhibitor etolimus (ETO). DETAILED DESCRIPTION

[0015] The present invention will be described in detail below with reference to specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those skilled in the art, several changes and improvements can be made without departing from the scope of the present invention. These all fall within the scope of protection of the present invention.

[0016] The present invention provides a biomarker combination based on the vascular adventitia for assessing the progression of abdominal aortic aneurysm, wherein the biomarker combination comprises at least two biomarkers selected from the following three independent groups, wherein the at least two biomarkers are from the same group or different groups: myofibroblast transformation marker panel: α-smooth muscle actin (Acta2), monocyte chemoattractant protein 1 (Ccl2), and tissue inhibitor of metalloproteinases 1 (Timp1); Lipid metabolism-related biomarker panel: lipid metabolism-related protein CD36, carnitine palmitoyltransferase 1 (CPT1), and fatty acid binding protein 4 (FABP4); Inflammatory factor-related biomarker group: IL-6, MCP-1 and TIMP1.

[0017] The present invention also provides use of a detection reagent having specific binding affinity to the above biomarker combination in preparing an abdominal aortic aneurysm progression kit.

[0018] In one embodiment, the detection reagent is used to specifically identify and quantify the expression level of the biomarker.

[0019] The present invention also provides use of the above biomarker combination in screening candidate drugs for inhibiting the progression of abdominal aortic aneurysm.

[0020] Specifically, the candidate drug screening includes the following steps: (i) Establishing abdominal aortic aneurysm models in vitro or in animals; (ii) applying a drug candidate to the model; (iii) detecting changes in the expression levels of the biomarker combination in adventitial fibroblasts in the model; (iv) Screening of effective drug candidates based on the following criteria: The expression of the myofibroblast transformation marker group is downregulated, and / or the expression of the lipid metabolism-related biomarker group is upregulated, and / or the expression of the inflammatory factor-related biomarker group is downregulated.

[0021] The present invention is described in detail below with reference to specific embodiments.

[0022] Example 1 In this example, the role of adventitial fibroblasts transformed from important myofibroblasts in AAA was verified.

[0023] An angiotensin II (Ang II)-induced abdominal aortic aneurysm (AAA) model was established in 12- to 16-week-old male mice as follows: Mice were anesthetized by isoflurane inhalation, and a mini-osmotic pump (Alzet model 2004; Durect Corporation, Cupertino, CA, USA) loaded with Ang II (1000 ng / min / kg; A9525; Sigma-Aldrich, St. Louis, MO, USA) or saline (0.9% NaCl) was implanted subcutaneously in the neck for 28 days. After the treatment period, mice were humanely euthanized by cervical dislocation after an overdose of isoflurane (5%), and the suprarenal abdominal aorta was harvested.

[0024] In this example, there were 3 mice in the AAA model group and 3 mice in the control group.

[0025] In this example, single-cell RNA sequencing was performed on AAA tissues from a mouse AAA model, with a normal abdominal aorta as a control group, to verify the role of adventitial fibroblasts transformed from important myofibroblasts in AAA (single-cell sequencing was performed for both healthy and diseased patients). The specific experimental steps are as follows: (1) To isolate single cells, the abdominal aorta was enzymatically digested using a combination of 1 mg / mL collagenase type I, 0.25% trypsin, and 0.1 mg / mL DNase I at 37°C for 1 hour with gentle intermittent shaking. Cell viability was assessed by trypan blue staining, and only samples with viability exceeding 80% were included in further analysis. A total of 20,000 cells were loaded at a concentration of 500 cells / µl and single-cell RNA sequencing was performed using the 10× Genomics Chromium platform. Alignment and counting were performed using the mouse mm10 reference genome. Cells with mitochondrial transcripts exceeding 10% were excluded from further analysis. The data were normalized using the “ScaleData” function in Seurat, followed by principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) for dimensionality reduction. Data visualization was generated using built-in functions in Seurat.

[0026] The specific steps of trypan blue staining in this embodiment are as follows: Cell suspension preparation: After enzymatic digestion, transfer the cell suspension to a centrifuge tube and gently resuspend the cells in culture medium or PBS buffer containing 10% FBS.

[0027] Staining steps: Take an appropriate amount of cell suspension (usually 100-200 μL), add an equal volume of 0.4% trypan blue staining solution, mix gently, and stain at room temperature for 3-5 minutes.

[0028] Cell counting: Pipette the stained cell suspension onto a cell counting chamber. Observe and count the cells under a microscope. Live cells are not stained and appear transparent; dead cells are stained blue. Calculate the live cell percentage: Live cell percentage = (number of live cells / total number of cells) × 100%.

[0029] Result evaluation: Only when the cell viability exceeded 80%, the samples were included in further analysis.

[0030] Through the above steps, cell activity can be accurately evaluated and samples that meet the experimental requirements can be screened out.

[0031] RNA sequencing of adventitial fibroblasts (RNA transcriptome sequencing after drug addition) Transcriptome sequencing was performed using the Illumina HiSeq4000 platform. Quality visualization of all raw reads was performed using FastQC (version 0.11.9). Sequencing reads were aligned to the rat genomic set GRCr8 using HISAT2 (default parameters). For the input library, FPKMs were calculated, and differential gene expression analysis was performed using the R package DESeq2 (version 1.36.0). A |log2FC| > 1 and a P-adjusted < 0.05 were used as filtering criteria.

[0032] (3) Bioinformatics analysis Volcano plots were created based on fold changes in gene expression and adjusted P values using GraphPad Prism 5.0 software (San Diego, CA, USA). Heat maps were created using the R package ComplexHeatmap (version 2.12.0). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed using the R package clusterProfiler based on the org.Mm.eg.db and GOplot packages. Gene set enrichment analysis (GSEA) was performed using GSEA 4.1.0 to identify significantly enriched pathways and gene sets.

[0033] The experimental results are as follows: Reference Figure 1As shown in the figure, eight different cell clusters were identified in AAA tissue, including B plasma cells, myeloid cells, T cells, fibroblasts, smooth muscle cells, endothelial cells, neurons, and NK cells. Among them, fibroblasts were the main cell type in the aortic adventitia and were slightly increased in the AAA group.

[0034] Reference Figure 2 As shown, myofibroblasts (myo-AFs) secrete more chemokines, such as monocyte chemoattractant protein 1 (MCP-1), are characterized by enhanced proliferation and migration activities, and the presence of α-SMA (PMID: 31346611). Among the fibroblast population, myofibroblast markers such as Acta2 (α-smooth muscle actin, α-SMA), Ccl2 (MCP-1), and Timp1 are significantly upregulated in the AAA group, while the expression of vimentin remains unchanged ( Figure 2 ), indicating that fibroblasts in AAA are significantly transformed into myofibroblasts ( Figure 3 ).

[0035] Example 2 This example verifies the effect of lanifibranor alone on fibroblasts Lanifibranor described in the present invention is a PPARγ agonist that can simultaneously activate all three PPAR subtypes (PPARα, PPARδ and PPARγ).

[0036] 1. Isolation and identification of adventitial fibroblasts This example used 8-week-old male SPF Sprague-Dawley (SD) rats. To isolate adventitial fibroblasts from the abdominal aorta, the rat abdominal aorta was excised and rinsed three times with cold phosphate-buffered saline (PBS). Under a sterile microscope, the intima and media were carefully stripped away, leaving the adventitia. The adventitia was cut into 1 mm³ pieces and digested with type II collagenase (17101015, Gibco) and elastase (A002290, Sangon Biotech) at 37°C for 1-2 hours. The enzymes were neutralized with culture medium containing fetal bovine serum (FBS), and after centrifugation, the cells were plated in DMEM supplemented with 10% FBS. Culture was carried out at 37°C with 5% CO2, with the culture medium changed every 2-3 days. The identity of fibroblasts was verified using vimentin (1:100; 10366-1-AP; Proteintech) and α-smooth muscle actin (α-SMA; 1:100; ab124964; Abcam) markers.

[0037] 2. Immunofluorescence staining of adventitial fibroblasts Cells were washed with phosphate-buffered saline (PBS) and fixed with 4% paraformaldehyde (PFA) for 30 minutes, permeabilized with 0.5% Triton X-100, and blocked with 10% bovine serum albumin (BSA). Primary antibodies against α-SMA (1:100, Abcam) and vimentin (1:100, Proteintech) were incubated overnight at 4°C, followed by incubation with a secondary antibody conjugated to AlexaFluor 488 (1:500, Proteintech) for 2 hours at room temperature in the dark. Cell nuclei were stained with 4'6-diamidino-2-phenylindole dihydrochloride (1:1000, Solarbio) (DAPI). Images were acquired under a fluorescence microscope.

[0038] 3. Use 24-well Transwell chambers (#3422, Corning) to assess the migration ability of AFs (fibroblasts). Transwell assay steps: First, AFs were pretreated with Ang II (100 nmol / L) at 37°C for 24 h. Subsequently, the cultured cells were digested and resuspended in serum-free DMEM medium for serum starvation, and 4 × 10 4 Cells were seeded into the upper chamber of a Transwell insert. After cell migration was complete, the cells were fixed with 70% ice-cold ethanol for 1 hour and then stained with 0.5% crystal violet stain (#C0121, Beyotime). Finally, the migrated cells in the lower chamber were observed and counted using a microscope.

[0039] result: In this example, adventitial fibroblasts (AFs) were isolated and cultured from SD rats. Immunofluorescence was then used to identify the VSMC marker α-SMA in early passage cells. α-SMA is expressed in both fibroblasts and VSMCs. Furthermore, vimentin, a specific marker for fibroblasts, was used. The results showed strong vimentin positive staining, while α-SMA staining was negative, indicating that the cultured AFs were of high purity ( Figure 4 ).

[0040] In this example, we further investigated whether lanifibranor inhibits AF phenotypic conversion and subsequent migration, as well as its optimal concentration. AFs treated with Ang II (100 nmol / L) showed a significant phenotypic conversion to myofibroblasts, as evidenced by increased α-SMA expression, and lanifibranor effectively inhibited this phenotypic conversion. Lanifibranor had the best effect at 5 μM, and higher concentrations did not enhance the effect ( Figure 5-8 ).

[0041] The above results were further confirmed by Transwell experiments, which showed that the inhibitory effect on Ang II-induced AF migration was maximal at 5 μM, and no further benefit was observed at 10 μM ( Figure 9 Therefore, 5 μM lanifibranor significantly inhibited Ang II-induced myofibroblast transformation and was used in subsequent experiments.

[0042] This example further demonstrates that lanifibranor effectively maintains the adventitial fibroblast phenotype by reprogramming lipid metabolism. To further elucidate the mechanism by which lanifibranor regulates the function of aortic adventitial fibroblasts, transcriptome analysis was performed on fibroblasts treated with lanifibranor. Lanifibranor was found to significantly upregulate 144 genes and downregulate 396 genes ( Figure 10 ).

[0043] GO and KEGG functional analysis showed that Lanifibranor upregulated pathways related to lipid metabolism in fibroblasts, such as lipid storage, neutral lipid metabolism, and lipid degradation, while inhibiting cell cycle and cell proliferation ( Figure 11 、 12 , 13). GSEA analysis further verified the abnormalities in lipid metabolism and cell cycle, showing that ether lipid metabolism increased and cell cycle activity decreased after Lanifibranor treatment ( Figure 14 Notably, the expression of lipid metabolism-related transporter CD36 was significantly upregulated after Lanifibranor treatment ( Figure 12 CD36 is a key scavenger receptor in lipid regulation, so we detected its protein expression by immunoblotting. In addition, in this example, the expression of proteins related to lipid metabolism and cell cycle activity under Ang II treatment was determined by Western blotting. After Ang II administration, lipid metabolism-related proteins including CD36, CPT1, and FABP4 showed an increasing trend ( Figure 17 、 18 These three proteins are involved in intracellular lipid transport, helping to transport lipids into cells and mitochondria, and promoting fatty acid β-oxidation. In addition, the expression of cell cycle activity-related proteins such as CCND1, CDC6, and CDK1 is reduced ( Figure 19 、 Figure 20Furthermore, myofibroblasts exhibit excessive lipid accumulation due to dysregulated lipid metabolism in fibrotic diseases, and lipid homeostasis plays a key role in maintaining cellular homeostasis. Therefore, in this example, a Seahorse experiment was performed to assess cellular metabolism in more detail. Lanifibranor treatment was observed to enhance lipid metabolism, as shown by the cellular oxygen consumption rate (OCR) curve ( Figure 21 The extracellular acidification rate (ECAR) curve showed that the overall metabolic activity of cells in the Lanifibranor group increased ( Figure 22 In addition, Oil Red O staining showed that lipid deposition in fibroblasts was reduced after treatment with 5 μM Lanifibranor ( Figure 23 The results of CCK-8 experiments showed that blocking lipid metabolism with etomoxir could reverse the reduction of myofibroblast migration induced by lanifibranor ( Figure 24 This suggests that lanifibranor maintains the phenotype of AFs by regulating lipid metabolism, thereby alleviating migration.

[0044] In summary, the biomarker combination provided by the present invention systematically integrates multi-pathway biomarkers. By integrating three independent groups of biomarkers: myofibroblast transformation markers (Acta2, Ccl2, Timp1), lipid metabolism-related proteins (CD36, CPT1, FABP4), and inflammatory factors (IL-6, MCP-1, TIMP1), it can reflect the pathological process of AAA in multiple dimensions, including the phenotypic transformation of adventitial fibroblasts, metabolic disorders, and the inflammatory microenvironment, significantly improving the accuracy of diagnosis and prognosis assessment.

[0045] The above describes specific embodiments of the present invention. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art may make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. In the absence of conflict, the embodiments of this application and the features in the embodiments may be combined with each other in any manner.

Claims

1. A biomarker combination based on the vascular adventitia for assessing the progression of abdominal aortic aneurysm, characterized in that: The biomarker combination comprises at least two biomarkers selected from the following three independent groups, wherein the at least two markers are from the same group or different groups: myofibroblast transformation marker panel: α-smooth muscle actin, monocyte chemoattractant protein 1, and tissue inhibitor of metalloproteinase 1; Lipid metabolism-related biomarker panel: lipid metabolism-related protein CD36, carnitine palmitoyltransferase 1, and fatty acid binding protein 4; Inflammatory factor-related biomarker group: IL-6, MCP-1 and TIMP1.

2. Use of a detection reagent having specific binding affinity for the biomarker combination according to claim 1 in the preparation of a kit for detecting the progression of an abdominal aortic aneurysm.

3. The use according to claim 3, characterized in that The detection reagent is used to specifically identify and quantify the expression level of the biomarker.

4. Use of the biomarker combination according to claim 1 in screening candidate drugs for inhibiting the progression of abdominal aortic aneurysm.

5. The use according to claim 4, characterized in that The candidate drug screening comprises the following steps: (i) Establishing abdominal aortic aneurysm models in vitro or in animals; (ii) applying a drug candidate to the model; (iii) detecting changes in the expression levels of the biomarker combination in adventitial fibroblasts in the model; (iv) Screening of effective drug candidates based on the following criteria: The expression of the myofibroblast transformation marker group is downregulated, and / or the expression of the lipid metabolism-related biomarker group is upregulated, and / or the expression of the inflammatory factor-related biomarker group is downregulated.

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