Integrating Network Pharmacology and Experimental Validation to Reveal the Mechanism of Vine Grape Tea Polyphenols on Hyperuricemia-Induced Renal Injury in Mice

Abstract

Hyperuricemia (HUA) is a metabolic disease and contributes to renal injury (RI). Vine grape tea polyphenols (VGTP) have been widely used to treat HUA and RI. However, the potential mechanism of VGTP activity remains unclear. To explore the underlying mechanism of VGTP treatment for HUA-induced RI based on network pharmacology that is confirmed by an in vivo study. All ingredients of VGTP were retrieved using a Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and Comparative Toxicogenomics Database systems. The related targets of HUA and RI were obtained from GeneCards and National Center for Biotechnology Information (NCBI) databases. Some ingredients and targets were selected for molecular docking verification. One hour after administering potassium oxonate (300 mg/kg), VGTP (50, 100, and 200 mg/kg/d) was orally administered to HUA mice for 4 weeks. Histopathology and western blotting were performed in renal tissue. Our results showed that VGTP significantly reduced blood urea nitrogen, creatinine, uric acid, and significantly improved the RI and fibrosis of HUA mice. There were 54 active ingredients and 62 targets of HUA-induced RI. Further studies showed that VGTP decreased the expression of Bax, cleaved caspase 3, transforming growth factor-β (TGF-β1), CHOP, p-STAT3, and P53, and increased Bcl-2 expression in renal tissue. The related signaling pathways have apoptosis, TGF-β1, P53 and STAT, and endoplasmic reticulum stress (ERS). In this study, VGTP exerted antihyperuricemic and anti fibrosis effects by regulating the apoptosis and ERS signaling pathways. VGTP is expected to become a drug for combating HUA and RI.

INTRODUCTION

Hyperuricemia (HUA) is a metabolic disorder characterized by high uric acid (UA). It is an independent risk factor for gout, diabetic vascular complications, hypertension, cardiovascular, and kidney disease.¹ Many studies have shown that elevated serum UA levels can induce endoplasmic reticulum stress (ERS), oxidative stress and mitochondrial dysfunction, and fibrosis in the kidney.^2,3 HUA contributes to the occurrence and development of renal injury (RI) and chronic kidney disease.⁴ However, the causal relationship between HUA and RI, and the pathophysiological mechanism of HUA-induced RI are unclear. Therefore, there is significant clinical significance in clarifying the possible pathogenesis of HUA-induced RI and in searching for effective therapeutic drug targets.

The effective treatments of HUA include low-purine diets, urine alkalization, and antihypertensive drugs. Antihyperuricemic drugs include medications that promote UA excretion and those that inhibit UA production. Substantial evidence suggests that antihyperuricemic drugs have considerable side effects. Moreover, there is growing evidence to support that botanical drugs can decrease the level of serum UA and attenuate HUA-induced RI.⁵ Therefore, it is necessary to find the effective agents in the treatment of HUA and RI.

Plant polyphenols are natural substances in vegetables, fruits, and seeds such as vine tea, grapes, black and green tea, blueberries, and apples. Numerous studies have confirmed that plant polyphenols have a wide range effects, including antioxidation, anti-inflammation, hypouricemic, cardioprotection, and nephroprotection, but no toxicity.^6
–8 Studies have shown that vine tea, grape, and black and green tea polyphenols can protect against various kidney diseases, and inhibit renal fibrosis.^9,10 Tea, grape, and their components, such as resveratrol, quercetin, dihydromyricetin, epigallocatechin gallate (EGCG), and theaflavin can inhibit xanthine oxidase (XOD) and reduce the production of UA.^5,11
–13

Moreover, Cordyceps militaris has an antihyperuricemic effect by downregulating UA transporter 1 in kidney.¹⁴ Vine grape tea polyphenols (VGTP) include Ampelopsis grossedentata polyphenols (vine tea), Vitis vinifera polyphenols (grape), Camellia sinensis polyphenols (black and green tea), and C. militaris. Based on the information above, we hypothesized that VGTP could be used as a potential food resource to prevent HUA-induced RI. However, the drug targets and mechanism of VGTP treatment for HUA-induced RI remain unclear.

Plant polyphenols have synergistic regulatory effects on disease treatment with multiple components, targets, and pathways. Network pharmacology and molecular docking are important methods for obtaining targets of plant polyphenols. Growing evidence suggests that network pharmacology has a vital role in the research and development of botanical drugs.¹⁵ In this study, we utilized the methods of network pharmacology and molecular docking to explore the mechanism of VGTP for treating HUA-induced RI.

MATERIALS AND METHODS

Materials

VGTP (No: 20211216) was purchased from Wuxi Century Bioengineering Co., Ltd (Wuxi, China). Potassium oxonate (PO) was purchased from MedChem Express (New Jersey, USA). Sodium Carboxymethyl cellulose (CMC-Na) was acquired from Solarbio Science and Technology (Beijing, China). The XOD kit was obtained from Jiancheng Biotechnology Institute (Nanjing, China). Antibodies for B-cell lymphoma-2 (Bcl-2), Bcl2 associated protein X (Bax), caspase 3, CHOP, P53, signal transducer and activator of transcription 3 (STAT3), and GAPDH were all sourced from Proteintech (Wuhan, China). Antibodies for transforming growth factor-β (TGF-β1) and p-STAT3 (Ser727) were bought from ABclonal (Wuhan, China). All other chemical reagents were of analytical grade.

Network pharmacology analysis

Typical active ingredients of VGTP were sourced from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP; http://tcmspw.com/tcmsp.php) and the Comparative Toxicogenomics Database (CTD; https://ctdbase.org).

Relevant targets associated with HUA and RI were retrieved using GeneCards (http://www.genecards.org) and the NCBI (http://www.ncbi.nlm.nih.gov). Finally, we identified the relevant targets of HUA-induced RI. Using R software (version 4.0.3) and the Venn Diagram package, we acquired potential protein targets (for HUA-induced RI) and drug targets (for VGTP). Moreover, we identified the potential targets for VGTP treatment of HUA-induced RI. The drugs-ingredients-target network of VGTP was mapped by the Cytoscape software (version 3.8.2).

Gene Ontology, the analysis of Kyoto Encyclopedia of Genes and Genomes pathway enrichment and protein–protein interaction network

Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and analysis were performed by R software and Bioconductor cluster profiler package. GO enrichment was carried out in terms of cellular components (CC), biological processes (BP), and molecular functions (MF).

The related target sets for VGTP- and HUA-induced RI were imported into the String tool (https://string-db.org) to obtain the protein–protein interaction (PPI) network. The biological parameters were set to “Homo sapiens.” The score of interaction confidence was set to high confidence (0.400). Then, the PPI network was imported into Cytoscape software to investigate the key subnetworks. The importance of “nodes” was reflected by the node degree value.

Ingredients–target molecular docking

The three-dimensional structure of key targets was downloaded from PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the RCSB PDB database. We preprocessed key targets by PyMOL software, and saved in PDB format. Structural information for some ingredients was obtained from the TCMSP database. Ultimately, we performed the docking studies using the Glide version 5.5.

Animals

We purchased 7-week-old male C57BL/6J mice from SPF Biotechnology (Beijing, China; n = 50). They were raised in standardized housing conditions with a steady temperature range of 20–22°C and relative humidity maintained at 55 ± 5%. The mice had continuous access to conventional laboratory pellet food and tap water. They were adaptively fed for a week-long before the onset of experimental. All procedures were approved by the Animal Ethics Committee of Shandong University (Approval No: 22023).

All animal experiments were conducted in accordance with the guidelines of the Experimental Animal Center of Shandong University and the ARRIVE guidelines. C57BL/6J mice were earmarked as control group (CC, n = 10), while the remaining mice were orally administered PO 300 mg/kg once daily by gavage for 4 weeks. For HUA model, the subjects were assorted into five groups: receiving water (HUA, n = 10), low dose VGTP (VGTPL, 50 mg/kg, n = 10), medium dose VGTP (VGTPM, 100 mg/kg, n = 10), and high dose VGTP (VGTPH, 200 mg/kg, n = 10). The formulation of PO was freshly prepared in 0.5% CMC-Na. VGTP was dispensed via gavaging 1 h subsequent to PO administration, continuing for 4 weeks. Following the experimental period, euthanasia was performed under sodium pentobarbital, allowing collection of fasting blood and kidneys, which were subsequently preserved at −80°C for future assessments.

Determination of body weight, kidney weight, serum Cr, blood urea nitrogen, UA, and XOD

After the experiment, mice and kidney weight were determined. Kidney index was calculated by kidney weight/body weight (milligram per gram). Serum Cr, blood urea nitrogen (BUN), and UA contents were quantified using a DVI-1650 Automatic Biochemistry Analyzer (Bayer, Germany). Serum XOD activity was detected by the commercial XOD kit.

Light microscopy

Paraffin-embedded biopsies of the left kidney were sectioned into slices of 4 μm thickness and underwent staining with hematoxylin and eosin (HE) and Masson's Trichrome, and then examined with light microscopy. According to the histopathology of the kidney, the renal tubule injury score was calculated by semiquantitative appraisal, and the scores were 0, 1, 2, 3, and 4 corresponding to 0%, <25%, 26–50%, 51–75%, and ≥76%, respectively. Quantification of renal interstitial fibrosis staining was accurately performed using ImageJ software, with positive staining area percentages indicative of overall tissue staining.

Western blot analysis

Renal tissue samples were pulverized in a chilled protease-inhibited lysis buffer, specifically containing phenylmethanesulfonyl fluoride (Jiangsu Beyotime Biotechnology, China). Protein quantification ensured equal loading for electrophoresis on a 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis, subsequently translocated onto polyvinylidene fluoride membranes. These membranes were initially obstructed using phosphate buffered saline with tween 20 (PBST)-5% skimmed milk or PBST-5% bovine serum albumin, followed by an overnight incubation at 4°C with primary antibodies targeting Bax (1:5000), Bcl-2, caspase 3, TGF-β1, CHOP, P53 (1:1000), STAT3 (1:2000), pho-STAT3 (Ser727 1:1000), and GAPDH (1:2000). Blots were probed with secondary antibody (Beyotime, China) for an hour at room temperature. The intensity of western blots was quantified by densitometry using the ImageJ software.

Statistical analysis

Enrichment assessments for GO and KEGG were executed using Fisher's exact test, and false discovery rate correction was applied from multiple comparisons. The data are expressed as means ± standard deviations. Group comparisons were statistically analyzed through one-way analysis of variance and Student's t-test. P < .05 was considered statistically significant. All statistical computations were processed with SPSS version 22.0 software (SPSS, Chicago, IL, USA).

RESULTS

Potential targets of VGTP in treating HUA-induced RI and network analysis of botanical drugs‑active ingredients-targets

We obtained 13 active ingredients from A. grossedentata polyphenols, 22 in V. vinifera polyphenols, 17 from C. sinensis polyphenols, and 2 from C. militaris. (Table 1). We obtained 130 potential targets from the intersection of HUA (834) and RI (714), and mapped 62 potential therapeutic targets from the VGTP (436) and HUA-RI (130). These targets are considered potential targets of VGTP in treating HUA-induced RI (Fig. 1A, B, Tables 2 and 3).

FIG. 1.

Potential targets of VGTP in treating HUA-induced RI and botanical drugs-active ingredients-targets network analysis. (A) A total of 834 and 714 targets of HUA and RI, respectively, and they shared 130 overlapping targets. (B) A total of 436 and 130 targets of VGTP and HUA-RI, respectively, and they shared 62 overlapping targets. (C) Disease–ingredient–target network of VGTP. (D) Botanical drugs–ingredient–target network. HUA, hyperuricemia; RI, renal injury; VGTP, vine grape tea polyphenols.

Table 1.

Vine Grape Tea Polyphenols and Active Ingredients

No.	Mol (TCMSP)/MeSH (CTD) ID	Molecule name	Related target
Ampelopsis grossedentata polyphenols (13)
1	MOL000008	Apigenin	80
2	MOL013374	Dihydromyricetin	7
3	MOL002341	Hesperetin	9
4	MOL009801	Myricetin-3-O-beta-D-galactopyranoside	1
5	MOL004110	Quercetin-3-O-β-D-glucoside	1
6	MOL004576	Dihydroquercetin	12
7	MOL000635	Vanillin	11
8	MOL007930	Hesperidin	6
9	MOL002007	Myricetrin	2
10	MOL004925	Vitexin	6
11	MOL008888	Vitexin-2-O-rhamnoside	1
12	MOL000701	Quercitrin	9
13	MOL004368	Quercetin-3-galactoside	9
Vitis vinifera polyphenols (22)
1	MOL012744	Resveratrol	151
2	MOL000492	Catechin (C)	11
3	MOL006505	Epicatechin (EC)	32
4	MOL002249	Gallocatechin (GC)	6
5	MOL005467	Epicatechin gallate (ECG)	1
6	MOL000004	Procyanidin B1	11
7	MOL007283	Procyanidin B2	6
8	MOL000098	Quercetin	154
9	MOL006838	Anthocyanin	4
10	MOL001002	Ellagic Acid	20
11	MOL000006	Luteolin	57
12	MOL000481	Genistein	97
13	MOL004576	Taxifolin	12
14	MOL006791	Epigallocatechin (EGC)	8
15	MOL000002	Cyanidin	9
16	MOL006765	Peonidin	10
17	MOL004798	Delphinidin	8
18	MOL001004	Pelargonidin	15
19	MOL000490	Petunidin	8
20	MOL000499	Malvidin	11
21	MOL013289	Piceid	4
22	MOL011980	Pterostilbene	12
Camellia sinensis polyphenols (17)
1	MOL006821	Epigallocatechin gallate (EGCG)	140
2	MOL006775	Epiafzelechin (EZ)	10
3	MOL006504	Catechin gallate (CG)	1
4	MOL005830	Gallocatechin gallate (GCG)	1
5	MOL000422	Kaempferol	63
6	MOL002008	Myricetin	38
7	MOL000513	Gallic acid	15
8	MOL003066	5-Caffeoylquinic acid	1
9	MOL000415	Quercetin-3-rutinoside	21
10	MOL004368	Quercetin-3-galactoside	9
11	MOL001415	Kaempferol-3-glucoside	4
12	MOL000569	m-Digallic acid	3
13	MOL000415	Rutin	21
14	C056068	Theaflavin	26
15	C026133	Purpurogallin	1
16	D002726	Chlorogenic acid	159
17	C495469	P-Coumaric acid	49
Cordyceps militaris (2)
1	MOL000003	Cordycepic acid	2
2	C058120	Cordycepin	26

CTD, Comparative Toxicogenomics Database; TCMSP, Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform.

Table 2.

The Possible Targets of Vine Grape Tea Polyphenols Against Hyperuricemia-Induced Renal Injury

NO.	Target name	Gene symbol	Degree	Betweenness	Closeness centrality
1	Prostaglandin G/H synthase 2	PTGS2	29	0.294	0.586
2	Transcription factor p65	RELA	13	0.024	0.487
3	Caspase-3	CASP3	12	0.010	0.482
4	Tumor necrosis factor	TNF	11	0.007	0.477
5	Peroxisome proliferator-activated receptor gamma	PPARG	11	0.013	0.477
6	Apoptosis regulator Bcl-2	BCL2	11	0.009	0.477
7	Cellular tumor antigen p53	TP53	10	0.006	0.472
8	Nitric oxide synthase, endothelial	NOS3	10	0.013	0.472
9	Transcription factor AP-1	JUN	10	0.006	0.472
10	Cyclin-dependent kinase inhibitor 1	CDKN1A	10	0.013	0.472
11	Apoptosis regulator BAX	BAX	10	0.006	0.472
12	Xanthine dehydrogenase/oxidase	XDH	9	0.004	0.467
13	Interleukin-6	IL6	9	0.005	0.467
14	Intercellular adhesion molecule 1	ICAM1	9	0.010	0.467
15	Mitogen-activated protein kinase 1	MAPK1	8	0.003	0.462
16	Interleukin-8	CXCL8	8	0.014	0.462
17	Bcl-2-like protein 1	BCL2L1	8	0.004	0.462
18	Interleukin-1 beta	IL1B	7	0.002	0.458
19	78 kDa glucose-regulated protein	HSPA5	7	0.003	0.458
20	Small inducible cytokine A2	CCL2	7	0.003	0.458
21	Vascular cell adhesion protein 1	VCAM1	6	0.001	0.453
22	Transforming growth factor beta-1	TGFB1	6	0.001	0.453
23	Superoxide dismutase [Cu-Zn]	SOD1	6	0.002	0.453
24	E-selectin	SELE	6	0.001	0.453
25	Mitogen-activated protein kinase 8	MAPK8	6	0.002	0.453
26	Signal transducer and activator of transcription 3	STAT3	5	8.23E-04	0.449
27	Peroxisome proliferator-activated receptor alpha	PPARA	5	7.43E-04	0.449
28	Myc proto-oncogene protein	MYC	5	0.002101	0.449
29	Insulin-like growth factor 1 receptor	IGF1R	5	8.23E-04	0.449
30	Fatty acid synthase	FASN	5	9.86E-04	0.449
31	Catechol O-methyltransferase	COMT	5	0.001881	0.449
32	Catalase	CAT	5	0.001851	0.449
33	Toll-like receptor 4	TLR4	4	5.16E-04	0.444
34	Metalloproteinase inhibitor 1	TIMP1	4	5.54E-04	0.444
35	Poly [ADP-ribose] polymerase 1	PARP1	4	0.001213	0.444
36	Interferon gamma	IFNG	4	7.73E-04	0.444
37	3 hydroxy 3 methylglutaryl CoA reductase	HMGCR	4	6.08E-04	0.444
38	Forkhead box protein O1	FOXO1	4	4.45E-04	0.444
39	Endothelin-1	EDN1	4	4.45E-04	0.444
40	C-reactive protein	CRP	4	3.88E-04	0.444
41	CD44	CD44	4	0.00168	0.444
42	Apolipoprotein B-100	APOB	4	0.004326	0.444
43	Beta-2 adrenergic receptor	ADRB2	4	0.005522	0.444
44	DNA damage-inducible transcript 3	DDIT3	3	3.22E-04	0.440
45	Vascular endothelial growth factor A	VEGFA	3	3.22E-04	0.440
46	Thrombomodulin	THBD	3	1.82E-04	0.440
47	Tyrosine-protein kinase SYK	SYK	3	2.60E-04	0.440
48	Plasminogen activator inhibitor 1	SERPINE1	3	1.82E-04	0.440
49	Lipoprteinlipase	LPL	3	2.15E-04	0.440
50	Vascular endothelial growth factor receptor 2	KDR	3	2.19E-04	0.440
51	Insulin	INS	3	2.60E-04	0.440
52	Glutamic pyruvic transaminase	GPT	3	2.15E-04	0.440
53	Tumor necrosis factor receptor superfamily member 6	FAS	3	2.19E-04	0.440
54	Erythropoietin	EPO	3	2.15E-04	0.440
55	Cytochrome C	CYCS	3	2.15E-04	0.440
56	Cyclin-dependent kinase inhibitor 2	CDKN2A	3	8.32E-04	0.440
57	Apolipoprotein E	APOE	3	0.001188	0.440
58	Albumin	ALB	3	2.15E-04	0.440
59	Type-1 angiotensin II receptor	AGTR1	3	1.76E-04	0.440
60	Angiotensinogen	AGT	3	2.19E-04	0.440
61	Angiotensin-converting enzyme	ACE	3	9.80E-04	0.440
62	Multidrug resistance-associated protein 2	ABCC2	3	2.15E-04	0.440

Table 3.

The Possible Targets of the Main Active Ingredient of Vine Grape Tea Polyphenols Against Hyperuricemia-Induced Renal Injury

ID	Ingredient	Medicine	Targets for hyperuricemia-induced kidney injury
MOL012744	Resveratrol	V. vinifera polyphenols	AGTR1, BAX, BCL2, BCL2L1, CASP3, CCL2, CDKN1A, CRP, CXCL8, EDN1, FOXO1, HSPA5, ICAM1, IGF1R, IL1B, IL6, JUN, MAPK1, MAPK8, MYC, NOS3, PPARA, PPARG, PTGS2, RELA, SELE, SOD1, STAT3, TGFB1, TNF, TP53, VCAM1, XDH
MOL000098	Quercetin	V. vinifera polyphenols, C. sinensis polyphenols, A. grossedentata polyphenols	ADRB2, BAX, BCL2, BCL2L1, CASP3, CCL2, CDKN1A, CRP, CXCL8, HSPA5, ICAM1, IFNG, IL1B, IL6, JUN, MAPK1, MYC, NOS3, PARP1, PPARA, PPARG, PTGS2, RELA, SELE, SERPINE1, SOD1, TGFB1, THBD, TNF, TP53, VCAM1, XDH
MOL006821	Epigallocatechin gallate(EGCG)	V. vinifera polyphenols, C. sinensis polyphenols	AGT, BAX, BCL2, BCL2L1, CASP3, CDKN1A, COMT, EDN1, FAS, FASN, FOXO1, HSPA5, IGF1R, IL6, JUN, KDR, MAPK1, MAPK8, PPARG, PTGS2, RELA, SOD1, STAT3, TIMP1, TLR4, TNF, TP53, XDH
D002726	Chlorogenic acid	C. sinensis polyphenols	ABCC2, ALB, BAX, BCL2, CASP3, CAT, CCL2, CD44, COMT, CXCL8, CYCS, EPO, FASN, GPT, HMGCR, IL1B, IL6, JUN, LPL, MAPK1, NOS3, PPARG, PTGS2, RELA, TLR4, TNF, TP53, XDH
MOL000481	Genistein	V. vinifera polyphenols	BAX, BCL2, CASP3, CCL2, CDKN1A, CXCL8, ICAM1, IGF1R, IL1B, INS, JUN, MAPK1, NOS3, PPARA, PPARG, PTGS2, RELA, SELE, STAT3, SYK, TGFB1, TIMP1, TNF, TP53, VCAM1
C495469	P-Coumaric acid	C. sinensis polyphenols	BAX, BCL2, BCL2L1, CASP3, CAT, DDIT3, FASN, HMGCR, HSPA5, IL1B, IL6, MAPK8, NOS3, PPARG, PTGS2, RELA, TGFB1, TNF, TP53, VEGFA, XDH
MOL000422	Kaempferol	C. sinensis polyphenols, A. grossedentata polyphenols	BAX, BCL2, CASP3, ICAM1, JUN, MAPK8, NOS3, PPARG, PTGS2, RELA, SELE, TNF, VCAM1, XDH
MOL000006	Luteolin	V. vinifera polyphenols, A. grossedentata polyphenols	BCL2L1, CASP3, CDKN1A, ICAM1, IFNG, IL6, JUN, MAPK1, PPARG, PTGS2, RELA, TNF, TP53, XDH
C058120	Cordycepin	Cordyceps militaris	BAX, BCL2, BCL2L1, CASP3, CAT, CDKN1A, CDKN2A, HSPA5, PARP1, SOD1, TP53
MOL006505	Epicatechin (EC)	V. vinifera polyphenols, C. sinensis polyphenols	ACE, CASP3, CCL2, COMT, IL6, JUN, PTGS2, TNF
C056068	Theaflavin	C. sinensis polyphenols	APOE, BCL2, CD44, CDKN1A, MYC, NOS3, PTGS2
MOL004576	Dihydroquercetin	A. grossedentata polyphenols	APOB, ICAM1, PTGS2, RELA
MOL004576	Taxifolin	V. vinifera polyphenols	APOB, ICAM1, PTGS2, RELA
MOL001002	Ellagic Acid	V. vinifera polyphenols	CDKN1A, CXCL8, RELA
MOL000004	Procyanidin B1	V. vinifera polyphenols	NOS3, PTGS2
MOL011980	Pterostilbene	V. vinifera polyphenols	ADRB2, PTGS2
MOL001004	Pelargonidin	V. vinifera polyphenols	PPARG, PTGS2
MOL006791	Epigallocatechin (EGC)	V. vinifera polyphenols, C. sinensis polyphenols	CXCL8, PTGS2
MOL007283	Procyanidin B2	V. vinifera polyphenols	PTGS2
MOL006765	Peonidin	V. vinifera polyphenols	PTGS2
MOL000490	Petunidin	V. vinifera polyphenols	PTGS2
MOL013289	Piceid	V. vinifera polyphenols	PTGS2
MOL000499	Malvidin	V. vinifera polyphenols	PTGS2
MOL000569	m-Digallic acid	C. sinensis polyphenols	PTGS2
MOL002249	Gallocatechin (GC)	V. vinifera polyphenols, C. sinensis polyphenols	PTGS2
MOL000002	Cyanidin	V. vinifera polyphenols	PTGS2
MOL004798	Delphinidin	V. vinifera polyphenols	PTGS2
MOL006838	Anthocyanin	V. vinifera polyphenols	PTGS2
MOL000492	Catechin(C)	V. vinifera polyphenols	PTGS2

The network of disease‑ingredient-target involved 93 nodes (including 62 targets) and 375 edges (Fig. 1C). The network of botanical drugs-ingredient-targets involved 95 nodes (including 4 botanical drugs, 54 ingredients, and 62 targets) and 289 edges (Fig. 1D). The majority of active ingredients possessed multiple targets, with each target being associated with several active ingredients.

Best active ingredients-drug targets network analysis

The top 15 active ingredient-related targets are shown in Figure 2A. The active ingredients with the interaction with drug targets included resveratrol, quercetin, EGCG, chlorogenic acid, genistein, p-Coumaric acid, cordycepin, and taxifolin (Fig. 2B–I). The most important ingredients were identified as MOL012744 (resveratrol, 33 targets), MOL000098 (quercetin, 32 targets), MOL006821 (EGCG, 28 targets), and D002726 (chlorogenic acid, 28 targets), respectively. This also shows that resveratrol, quercetin, EGCG, and chlorogenic acid have broad pharmacological effects, such as hypouricemic, anti-inflammation, antiapoptotic, antifibrotic, and nephroprotective ability.

FIG. 2.

Part active ingredients-drug targets network analysis. (A) Top 15 active ingredient-related targets. (B–I) Resveratrol, quercetin, epigallocatechin gallate, chlorogenic acid, genistein, p-Coumaric acid, cordycepin, and taxifolin with the interaction with drug targets.

Best drug targets-active ingredients network analysis

The top 15 targets of active ingredients are shown in Figure 3A. The drug targets with the interaction with active ingredients included transcription factor p65 (RELA), prostaglandin G/H synthase 2 (PTGS2), caspase 3, Bcl-2, TP53, Bax, xanthine dehydrogenase (XDH), TGF-β1, and STAT3 (Fig. 3B–I). These targets are mainly related to apoptosis, ERS, TGF-β1, P53, and STAT signaling pathway.

FIG. 3.

Part drug targets-active ingredients network analysis. (A) Top 15 targets of active ingredients. (B–I) Prostaglandin G/H synthase 2, transcription factor p65, caspase-3, BCL2, TP53, BAX, xanthine dehydrogenase, TGF-β1, STAT3.

GO function and the analysis of KEGG pathway enrichment, and PPI network

There were 62 drug targets of VGTP in treating HUA-induced RI by GO enrichment analysis (Fig. 4A). BP enriched targets consist of response to organic substance, response to stress, regulation of cell apoptosis, and response to oxygen-containing compound. CC-enriched targets mainly include extracellular regions, extracellular spaces, cytoplasmic vesicles, and ER lumens. Enriched MF is related to enzyme binding, signaling receptor binding, cytokine receptor, and protein-containing complex binding. The significant signaling pathways involved apoptosis, TGF-β1, P53 and Jak-STAT, and protein processing in ER, and so on. (Table 4, Fig. 4B). There were 62 nodes (representing targets) and 415 edges (representing the interaction between proteins), with an average node degree of 13.83 (Fig. 4C). The larger the node the greater the degree value. There were 29 targets which exceeded the average node degree.

FIG. 4.

GO function and KEGG pathway enrichment analysis, and PPI network analysis. (A) Drug targets of VGTP by GO function enrichment analysis. (B) Drug targets of VGTP by KEGG pathway enrichment analysis. (C) Drug targets of VGTP by PPI network analysis. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes, PPI, protein–protein interaction.

Table 4.

Pathway Enrichment Analysis of Vine Grape Tea Polyphenols Against Hyperuricemia-Induced Renal Injury

Pathway ID	Pathway name	Identified components	P value	P adjust	Count
hsa05200	Pathways in cancer	BAX/BCL2/BCL2L1/CASP3/CDKN1A/CXCL8/FAS/FOXO1/IGF1R/IL6/JUN/MAPK1/MAPK8/MYC/PPARG/PTGS2/RELA/STAT3/TGFB1/TP53/CDKN2A/VEGFA/CYCS	1.42E-14	1.65E-12	23
hsa05142	Chagas disease (American trypanosomiasis)	ACE/CCL2/CXCL8/FAS/IFNG/IL1B/IL6/JUN/MAPK1/MAPK8/RELA/SERPINE1/TGFB1/TLR4/TNF	3.75E-14	2.17E-12	15
hsa05144	Malaria	CCL2/CXCL8/ICAM1/IFNG/IL1B/IL6/SELE/TGFB1/TLR4/TNF/VCAM1	1.33E-12	5.15E-11	11
hsa05210	Colorectal cancer	BAX/BCL2/CASP3/JUN/MAPK1/MAPK8/MYC/TGFB1/TP53/CYCS	3.29E-10	9.53E-09	10
hsa05323	Rheumatoid arthritis	CCL2/CXCL8/ICAM1/IFNG/IL1B/IL6/JUN/TGFB1/TLR4/TNF/VEGFA	1.10E-09	2.28E-08	11
hsa05143	African trypanosomiasis	FAS/ICAM1/IFNG/IL1B/IL6/SELE/TNF/VCAM1	1.18E-09	2.28E-08	8
hsa05014	Amyotrophic lateral sclerosis	BAX/BCL2/BCL2L1/CASP3/SOD1/TNF/TP53/CAT/CYCS	2.01E-09	3.33E-08	9
hsa05145	Toxoplasmosis	BCL2/BCL2L1/CASP3/IFNG/MAPK1/MAPK8/RELA/STAT3/TGFB1/TLR4/TNF/CYCS	4.80E-09	6.96E-08	12
hsa04210	Apoptosis	BAX/BCL2/BCL2L1/CASP3/FAS/IL1B/RELA/TNF/TP53/CYCS	1.26E-08	1.63E-07	10
hsa05212	Pancreatic cancer	BCL2L1/MAPK1/MAPK8/RELA/STAT3/TGFB1/TP53/CDKN2A/VEGFA	2.17E-08	2.52E-07	9
hsa05140	Leishmaniasis	IFNG/IL1B/JUN/MAPK1/PTGS2/RELA/TGFB1/TLR4/TNF	3.17E-08	3.34E-07	9
hsa04621	NOD-like receptor signaling pathway	CCL2/CXCL8/IL1B/IL6/MAPK1/MAPK8/RELA/TNF	9.22E-08	8.91E-07	8
hsa05219	Bladder cancer	CDKN1A/CXCL8/MAPK1/MYC/TP53/CDKN2A/VEGFA	1.44E-07	1.28E-06	7
hsa04115	p53 signaling pathway	BAX/CASP3/CDKN1A/FAS/SERPINE1/TP53/CDKN2A/CYCS	3.22E-07	2.66E-06	8
hsa04380	Osteoclast differentiation	IFNG/IL1B/JUN/MAPK1/MAPK8/PPARG/RELA/SYK/TGFB1/TNF	4.18E-07	3.23E-06	10
hsa05220	Chronic myeloid leukemia	BCL2L1/CDKN1A/MAPK1/MYC/RELA/TGFB1/TP53/CDKN2A	5.01E-07	3.63E-06	8
hsa04620	Toll-like receptor signaling pathway	CXCL8/IL1B/IL6/JUN/MAPK1/MAPK8/RELA/TLR4/TNF	5.98E-07	4.08E-06	9
hsa05146	Amoebiasis	CASP3/CXCL8/IFNG/IL1B/IL6/RELA/TGFB1/TLR4/TNF	8.31E-07	5.36E-06	9
hsa05020	Prion diseases	BAX/HSPA5/IL1B/IL6/MAPK1/SOD1	1.20E-06	7.31E-06	6
hsa05215	Prostate cancer	BCL2/CDKN1A/FOXO1/IGF1R/INS/MAPK1/RELA/TP53	2.33E-06	1.35E-05	8
hsa05160	Hepatitis C	CDKN1A/CXCL8/MAPK1/MAPK8/PPARA/RELA/STAT3/TNF/TP53	6.32E-06	3.49E-05	9
hsa04010	MAPK signaling pathway	CASP3/FAS/IL1B/JUN/MAPK1/MAPK8/MYC/RELA/TGFB1/TNF/TP53/DDIT3	1.01E-05	5.31E-05	12
hsa05222	Small cell lung cancer	BCL2/BCL2L1/MYC/PTGS2/RELA/TP53/CYCS	1.88E-05	9.49E-05	7
hsa04060	Cytokine-cytokine receptor interaction	CCL2/CXCL8/FAS/IFNG/IL1B/IL6/KDR/TGFB1/TNF/VEGFA/EPO	5.04E-05	2.44E-04	11
hsa05332	Graft-versus-host disease	FAS/IFNG/IL1B/IL6/TNF	6.09E-05	2.82E-04	5
hsa04940	Type I diabetes mellitus	FAS/IFNG/IL1B/INS/TNF	7.61E-05	3.39E-04	5
hsa05216	Thyroid cancer	MAPK1/MYC/PPARG/TP53	1.78E-04	7.67E-04	4
hsa05010	Alzheimer's disease	CASP3/FAS/IL1B/MAPK1/TNF/APOE/LPL/CYCS	2.37E-04	9.81E-04	8
hsa04722	Neurotrophin signaling pathway	BAX/BCL2/JUN/MAPK1/MAPK8/RELA/TP53	2.46E-04	9.83E-04	7
hsa05131	Shigellosis	CXCL8/MAPK1/MAPK8/RELA/CD44	3.54E-04	1.37E-03	5
hsa04650	Natural killer cell mediated cytotoxicity	CASP3/FAS/ICAM1/IFNG/MAPK1/SYK/TNF	3.74E-04	1.40E-03	7
hsa05214	Glioma	CDKN1A/IGF1R/MAPK1/TP53/CDKN2A	4.42E-04	1.60E-03	5
hsa04920	Adipocytokine signaling pathway	MAPK8/PPARA/RELA/STAT3/TNF	5.45E-04	1.86E-03	5
hsa05120	Epithelial cell signaling in Helicobacter pylori infection	CASP3/CXCL8/JUN/MAPK8/RELA	5.45E-04	1.86E-03	5
hsa04614	Renin-angiotensin system	ACE/AGT/AGTR1	5.86E-04	1.94E-03	3
hsa05218	Melanoma	CDKN1A/IGF1R/MAPK1/TP53/CDKN2A	6.65E-04	2.14E-03	5
hsa04370	VEGF signaling pathway	KDR/MAPK1/NOS3/PTGS2/VEGFA	9.08E-04	2.85E-03	5
hsa04930	Type II diabetes mellitus	INS/MAPK1/MAPK8/TNF	1.27E-03	3.87E-03	4
hsa04350	TGF-beta signaling pathway	IFNG/MAPK1/MYC/TGFB1/TNF	1.51E-03	4.48E-03	5
hsa04012	ErbB signaling pathway	CDKN1A/JUN/MAPK1/MAPK8/MYC	1.67E-03	4.84E-03	5
hsa04640	Hematopoietic cell lineage	IL1B/IL6/TNF/CD44/EPO	1.76E-03	4.97E-03	5
hsa05221	Acute myeloid leukemia	MAPK1/MYC/RELA/STAT3	2.57E-03	7.10E-03	4
hsa04510	Focal adhesion	BCL2/IGF1R/JUN/KDR/MAPK1/MAPK8/VEGFA	3.56E-03	9.61E-03	7
hsa04630	Jak-STAT signaling pathway	BCL2L1/IFNG/IL6/MYC/STAT3/EPO	4.28E-03	1.11E-02	6
hsa04660	T cell receptor signaling pathway	IFNG/JUN/MAPK1/RELA/TNF	4.30E-03	1.11E-02	5
hsa05211	Renal cell carcinoma	JUN/MAPK1/TGFB1/VEGFA	5.08E-03	1.28E-02	4
hsa04622	RIG-I-like receptor signaling pathway	CXCL8/MAPK8/RELA/TNF	5.34E-03	1.32E-02	4
hsa04662	B cell receptor signaling pathway	JUN/MAPK1/RELA/SYK	6.49E-03	1.57E-02	4
hsa05330	Allograft rejection	FAS/IFNG/TNF	6.74E-03	1.60E-02	3
hsa04664	Fc epsilon RI signaling pathway	MAPK1/MAPK8/SYK/TNF	7.79E-03	1.81E-02	4
hsa04110	Cell cycle	CDKN1A/MYC/TGFB1/TP53/CDKN2A	8.76E-03	1.99E-02	5
hsa05410	Hypertrophic cardiomyopathy	ACE/IL6/TGFB1/TNF	9.25E-03	2.06E-02	4
hsa05016	Huntington's disease	BAX/CASP3/PPARG/SOD1/TP53/CYCS	9.50E-03	2.08E-02	6
hsa04914	Progesterone-mediated oocyte maturation	IGF1R/INS/MAPK1/MAPK8	1.09E-02	2.34E-02	4
hsa04910	Insulin signaling pathway	FASN/FOXO1/INS/MAPK1/MAPK8	1.19E-02	2.51E-02	5
hsa04150	mTOR signaling pathway	INS/MAPK1/VEGFA	1.49E-02	3.03E-02	3
hsa05213	Endometrial cancer	MAPK1/MYC/TP53	1.49E-02	3.03E-02	3
hsa05223	Non-small cell lung cancer	MAPK1/TP53/CDKN2A	1.65E-02	3.29E-02	3
hsa04623	Cytosolic DNA-sensing pathway	IL1B/IL6/RELA	1.81E-02	3.57E-02	3
hsa04141	Protein processing in endoplasmic reticulum	BAX/BCL2/HSPA5/MAPK8/DDIT3	2.57E-02	4.97E-02	5

Botanical drugs-active ingredients-drug targets-biological process-signaling pathway network analysis

We mapped a “botanical drugs-active ingredients-drug targets-biological process-signaling pathway” network (Fig. 5). In this network, we selected 20 important active ingredients from VGTP. Then, the 20 critical targets corresponding to the active ingredients were analyzed by GO and KEGG. Enriched BP mainly includes regulation of apoptotic, ERS, inflammatory, metabolic process of reactive oxygen species, cellular response to cytokine stimulus, and signal transduction. KEGG signaling pathways are related to apoptosis, protein processing in ER, TGF-β1, P53, Jak-STAT, and mTOR signaling pathways.

FIG. 5.

Botanical drugs-active ingredient-drug target-biological process-signaling pathway network analysis.

Docking prediction of active ingredients and key target molecules

The active ingredients (resveratrol, quercetin, EGCG, chlorogenic acid, genistein, p-Coumaric acid, cordycepin, and theaflavin) in the VGTP and key targets (Bcl-2, caspase3, Bax, TGF-β1, XDH, P53, and STAT3) were selected for molecular docking studies (Table 5 and Fig. 6).

FIG. 6.

Molecular docking diagram and visualization of the major active ingredients of VGTP and the key targets.

Table 5.

The Molecular Docking Result of Major Active Ingredients of Vine Grape Tea Polyphenols with Key Target Proteins

	Glide score (kcal/mol)
Active ingredients	Bcl-2	caspase 3	Bax	TGF-β1	XDH	P53	STAT3
Resveratrol	–6.2	–5.4	–5.6	–3.0	–4.8	–4.0	–4.1
Quercetin	–5.9	–6.1	–6.0	–4.2	–4.9	–5.5	—
EGCG	–6.4	–5.4	–5.5	—	–5.6	–4.8	–4.4
chlorogenic acid	–3.8	–5.7	–5.4	—	–4.6	–4.8	—
Genistein	–5.9	–5.6	–5.9	–4.4	—	–4.8	–5.0
p-Coumaric acid	–4.4	–5.5	–3.8	–3.2	–3.8	–4.3	—
Cordycepin	–5.6	–5.7	–5.5	—	—	–5.5	—
Theaflavin	–5.5	—	—	—	—	—	—

Effects of VGTP on kidney index, serum BUN, Cr, UA, and XOD in mice

After the experiment, the kidney index, serum BUN, Cr, UA, and XOD significantly increased in the HUA group (P < .01). VGTP (50, 100, and 200 mg/kg) could markedly decrease kidney index, serum BUN, Cr, UA, and XOD (P < .05; Fig. 7A–E). Moreover, the VGTPH group had the most significant effect in reducing kidney index, serum BUN, Cr, UA, and XOD. This showed that VGTP improved PO-induced HUA and kidney injury in mice.

FIG. 7.

Effects of VGTP on kidney index, serum BUN, Cr, UA, and XOD. (A) Kidney index changes of the mice. (B) Serum BUN changes of the mice. (C) Serum Cr changes of the mice. (D) Serum UA changes of the mice. (E) Serum XOD activity changes in the mice. **P < .01 compared with CC group; ^# P < .05, ^## P < .01 compared with HUA group. BUN, blood urea nitrogen; CC, control group; HUA, hyperuricemia; HUA, potassium oxonate-induced HUA group; UA, uric acid; VGTPH, high-dose VGTP-treated HUA group; VGTPL, low-dose VGTP-treated HUA group; VGTPM: medium-dose VGTP-treated HUA group; VGTP, plant polyphenol extracts; XOD, xanthine oxidase.

Effect of VGTP on pathological changes in the kidneys

The HUA group developed tubular injury, which was characterized by tubular atrophy and dilatation, tubular epithelial vacuolation or flatness, brush border loss, and atrophic glomerular forms by HE staining. RI was improved in the VGTPL, VGTPM, and VGTPH groups when treated with VGTP (Fig. 8A). Compared to CC group, the renal collagen content and fibrosis were significantly increased in the HUA group by Masson's staining. VGTP (50, 100, 200 mg/kg) decreased the fibrotic formation in the kidney of the HUA group (Fig. 8C; P < .01). Moreover, the tubular injury score and Masson trichrome staining positive area significantly increased in the HUA group (P < .01). VGTP (50, 100, 200 mg/kg) treatment group significantly decreased them (Fig. 8B, D; P < .01).

FIG. 8.

Effect of VGTP on pathological changes in the kidneys. (A) Representative light micrographs of the kidney tissue (Hematoxylin Eosin; bar: 100 μm). (B) Tubular injury score changes of kidney histopathology in the mice. (C) Representative light micrographs of the kidney tissue (Masson's Trichrome; bar: 100 μm). (D) Masson trichrome staining positive area of renal fibrosis in the mice. **P < .01 compared with CC group; ^## P < .01 compared with HUA group.

Verification of drug targets by western blot

The proteins of Bax, Bcl-2, caspase 3, TGF-β1, CHOP, P53, and p-STAT3 (Ser727) were measured by western blotting. Compared to the CC group, the HUA group displayed marked upregulation of Bax, cleaved caspase 3, TGF-β1, CHOP, P53, and p-STAT3 (Ser727) in renal tissues (P < .01). VGTP (50, 100, and 200 mg/kg) effectively reduced the expression of those in the renal tissue. Furthermore, Bcl-2 expression was decreased in the renal tissues of the HUA group (P < .01). VGTP increased Bcl-2 expression in the HUA mice (Fig. 9A–H; P < .01).

FIG. 9.

Validation of drug targets of network pharmacology with western blot. (A): Western blot images of Bax, Bcl-2, cleaved caspase 3, TGF-β1, CHOP, P53, p-STAT3, and STAT3 in the kidney tissue. (B–H) Data were expressed as the expression ratio of Bax/GAPDH, Bcl-2/GAPDH, cleaved caspase 3/caspase 3, TGF-β1/GAPDH, CHOP/GAPDH, P53/GAPDH, and p-STAT3/STAT3. **P < .01 compared with CC group; ^# P < .05, ^## P < .01 compared with HUA group.

DISCUSSION

With the changes in lifestyle, the prevalence of HUA is increasing worldwide. Chronic HUA has pathological causes in gout and kidney disease, and plays a presumptive role in metabolic syndrome and cardiovascular disease.^16
–18 The application of chemical drugs in the treatment of HUA and RI is limited by toxicity and side effects, and increasing numbers of researchers are turning to botanical drugs. Moreover, many researchers have reported that grape seed procyanidins, resveratrol, EGCG, theaflavin, and cordycepin can significantly reduce the level of serum UA, and have strong nephroprotective ability.^9,14,19,20 Therefore, it is necessary for us to develop anti-HUA drugs with good efficacy and fewer side effects.

At present, many research reports that PO-induced rodents have been used as useful models for evaluating possible therapeutic agents or drugs that decrease the level of serum UA and prevent target organ damage.²¹ As a natural polyphenol extract, the active ingredients of VGTP have been proven to have the effects of reducing UA and kidney protection.^22,23 In this study, the HUA mouse model was successfully induced by PO, which showed HUA, renal dysfunction, and fibrosis. Moreover, VGTP reduced serum UA and alleviated the RI in the HUA mice model. Therefore, identifying potential targets in treatment of HUA-induced RI and revealing the mechanism of VGTP is of great significance.

In our experiment, we investigated the main active ingredients of VGTP in the therapy of HUA-induced RI, and revealed its mechanism and targets by network pharmacology, molecular docking and experimental validation. We also found that Bax, Bcl-2, Caspase 3, TGF-β1, CHOP, STAT3, and P53 are core targets in the VGTP in the therapy of HUA-induced RI. We validated the relationship of ingredients and targets with molecular docking and the protein expression of them with western blot.

HUA-induced RI involves many processes, of which apoptosis, oxidative stress, and ERS are the most important factors. Many studies have suggested that UA crystal deposition can lead to renal cell apoptosis.²⁴ The Bcl-2 family is an important regulatory factor for cell apoptosis. Bcl-2 and Bax form heterodimers, which can inhibit the proapoptotic effect of Bax. Bax can induce caspase activation and promotes cell apoptosis. It is notable that caspase 3 serves as a pivotal biomarker responsible for cellular apoptosis.^25,26 In the study of HUA after PO induction, several apoptosis indexes such as Bax and cleaved caspase 3 in renal tissues were increased, and Bcl-2 was reduced. Noteworthy, VGTP could alleviate apoptosis in the kidney. Our results found that caspase 3, Bax, and Bcl-2 exhibit interactions with up to 10 associated active ingredients, thereby representing crucial targets for VGTP treatment of RI.

HUA may disrupt ER homeostasis, resulting in ERS and subsequent unfolded protein response. Some studies have shown that ERS leads to CHOP expression and cell apoptosis in kidney disease models.^27,28 CHOP has been identified as a proapoptotic signal initiated by ER.²⁹ The study revealed the elevation in CHOP expression within renal tissues of HUA mice. VGTP can reduce the RI by attenuating UA‑induced ERS. Renal fibrosis is a result of chronic organ damage, resulting in the production of extracellular matrix components, structural deformation, and dysfunction.^30,31 TGF-β1 has been identified as a central contributor to renal fibrosis, fostering excessive extracellular matrix deposition, and exacerbating renal function deterioration.³²

Our results indicate that the HUA mice can cause RI and fibrosis, including apoptosis and ER dysfunction, which may be stimulated by UA. Our study found the protective efficacy of VGTP against HUA-induced RI by modulating the protein expression of apoptosis indexes, CHOP, and TGF-β1. In the treatment of HUA and RI patients, this may be a new treatment approach.

The signaling pathways mainly consist of apoptosis, protein processing in ER, TGF-β1, P53, and STAT according to network pharmacology methods. Moreover, TGF-β1, P53, and STAT3 play a role as molecular hubs connecting multiple signaling pathways such as ERS and cell apoptosis.^33,34 Inhibition of TGF-β1, P53, and STAT3 can suppress oxidative stress, ERS, and renal fibrosis.

In conclusion, HUA-induced RI treated with VGTP can be obtained by inhibiting apoptosis, decreasing the degree of ERS, and enhancing antioxidant effects by multiple targets and signaling pathways. This study elucidates the molecular mechanism and provides the theoretical basis for VGTP therapy against HUA and RI. Further research is needed to explore whether inhibition of ERS can become a new treatment for RI caused by HUA and research the detailed molecular mechanisms. Therefore, these active ingredients of VGTP can be used as dietary or nutritional supplements to treat RI-related diseases.

Footnotes

ACKNOWLEDGMENTS

The authors thank Dr. Hong Yu from Shanghai Bioprofile Biotechnology Co., Ltd and Hongjian Yu from Tianjin UBasio Biotechnology Group Co., Ltd.

AUTHOR DISCLOSURE STATEMENT

No competing financial interests exist.

FUNDING INFORMATION

No funding was received for this article.

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