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Investigating the Molecular Mechanism of Quercetin Protecting against Podocyte Injury to Attenuate Diabetic Nephropathy through Network Pharmacology, MicroarrayData Analysis, and Molecular Docking. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2022; 2022:7291434. [PMID: 35615688 PMCID: PMC9126727 DOI: 10.1155/2022/7291434] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 03/03/2022] [Accepted: 04/29/2022] [Indexed: 12/17/2022]
Abstract
Quercetin (QUE), a health supplement, can improve renal function in diabetic nephropathy (DN) rats by ameliorating podocyte injury. Its clinical trial for renal insufficiency in advanced diabetes (NCT02848131) is currently underway. This study aimed to investigate the mechanism of QUE protecting against podocyte injury to attenuate DN through network pharmacology, microarray data analysis, and molecular docking. QUE-associated targets, genes related to both DN, and podocyte injury were obtained from different comprehensive databases and were intersected and analyzed to obtain mapping targets. Candidate targets were identified by constructing network of protein-protein interaction (PPI) of mapping targets and ranked to obtain key targets. The major pathways were obtained from Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) term enrichment analysis of candidate targets via ClueGO plug-in and R project software, respectively. Potential receptor-ligand interactions between QUE and key targets were evaluated via Autodocktools-1.5.6. 41. Candidate targets, of which three key targets (TNF, VEGFA, and AKT1), and the major AGE-RAGE signaling pathway in diabetic complications were ascertained and associated with QUE against podocyte injury in DN. Molecular docking models showed that QUE could closely bind to the key targets. This study revealed that QUE could protect against podocyte injury in DN through the following mechanisms: downregulating inflammatory cytokine of TNF, reducing VEGF-induced vascular permeability, inhibiting apoptosis by stimulating AKT1 phosphorylation, and suppressing the AGE-induced oxidative stress via the AGE-RAGE signaling pathway.
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Wen Z, Zou X, Xie X, Zheng S, Chen X, Zhu K, Dong S, Liang J, Huang X, Liu D, Wang Y, Liu Y, Wu J, Ying Y, Liu K, Lu C, Zhang B, Yang G, Jing C, Nie L. Association of Polymorphisms in miRNA Processing Genes With Type 2 Diabetes Mellitus and Its Vascular Complications in a Southern Chinese Population. Front Endocrinol (Lausanne) 2019; 10:461. [PMID: 31354628 PMCID: PMC6639830 DOI: 10.3389/fendo.2019.00461] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2018] [Accepted: 06/25/2019] [Indexed: 01/12/2023] Open
Abstract
Objective: To evaluate the potential association between the genetic variants in miRNA processing genes (RAN, XPO5, DICER1, and TARBP2) and susceptibility to type 2 diabetes mellitus (T2DM) and its vascular complications, as well as to further investigate their interaction with environmental factors in type 2 diabetes. Methods: We conducted a case-control study in genotyping of five polymorphic loci, including RAN rs14035, XPO5 rs11077, DICER1 rs13078, DICER1 rs3742330, and TARBP2 rs784567, in miRNA processing genes to explore the risk factors for T2DM and diabetic vascular complications. Haplotype analyses, interactions of gene-gene and interactions of gene-environment were performed too. Results: We identified a 36% decreased risk of developing T2DM in individuals with the minor A allele in DICER1 rs13078 (OR: 0.64; 95%CI: 0.42-0.95; P: 0.026). The AA haplotype in DICER1 was also associated with a protective effect on T2DM compared with the AT haplotype (OR: 0.63; 95%CI: 0.42-0.94; P-value: 0.023). T2DM patients with the TT+TC genotype at RAN rs14035 had a 1.89-fold higher risk of developing macrovascular complications than patients with the CC genotype (OR: 1.89; 95%CI: 1.04-3.45; P-value: 0.037). We also identified two three-factor interaction models. One is a three-factor [DICER1 rs13078, body mass index (BMI), and triglyceride (TG)] interaction model for T2DM (OR: 5.93; 95%CI: 1.25-28.26; P = 0.025). Another three-factor [RAN rs14035, hypertension (HP), and duration of T2DM (DOD)] interaction model was found for macrovascular complications of T2DM (OR = 41.60, 95%CI = 11.75-147.35, P < 0.001). Conclusion: Our study provides new evidence that two single nucleotide polymorphisms (SNPs) of the miRNA processing genes, DICER1 and RAN, and their interactions with certain environmental factors might contribute to the risk of T2DM and its vascular complications in the southern Chinese population.
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Affiliation(s)
- Zihao Wen
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Xiaoqian Zou
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Xin Xie
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Shaoling Zheng
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Xiaojing Chen
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Kehui Zhu
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Shirui Dong
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Jiayu Liang
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Xiuxia Huang
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Dandan Liu
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Yao Wang
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Yumei Liu
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Jing Wu
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Yuting Ying
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Kailiang Liu
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Congying Lu
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Baohuan Zhang
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
| | - Guang Yang
- Department of Pathogen Biology, School of Medicine, Jinan University, Guangzhou, China
- Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, China
- *Correspondence: Guang Yang
| | - Chunxia Jing
- Department of Epidemiology, School of Medicine, Jinan University, Guangzhou, China
- Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, China
- Chunxia Jing
| | - Lihong Nie
- Department of Endocrine, The First Affiliated Hospital of Jinan University, Guangzhou, China
- Lihong Nie
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