中国组织工程研究 ›› 2026, Vol. 30 ›› Issue (29): 7706-7714.doi: 10.12307/2026.273

• 生物材料相关大数据分析 Big data analysis of biomaterials • 上一篇    下一篇

痛风的潜在靶点及药物预测:可成药基因识别

田轩赫1 ,仝思宇2,滕  飞3,钟  帅1,赵啸虎1,张玉娅1,刘  源1,姜  萍1   

  1. 1山东中医药大学第一临床学院,山东省济南市   250014;2山东中医药大学中医学院,山东省济南市   250355;3北京中医药大学第三附属医院,北京市   100036
  • 收稿日期:2025-08-04 修回日期:2025-11-28 出版日期:2026-10-18 发布日期:2026-03-07
  • 通讯作者: 姜萍,博士,教授,山东中医药大学第一临床学院,山东省济南市 250014 共同通讯作者:刘源,在读博士,山东中医药大学第一临床学院,山东省济南市 250014
  • 作者简介:田轩赫,男,2000年生,在读硕士,主要从事中西医结合治疗风湿免疫疾病的机制研究。
  • 基金资助:
    国家自然科学基金项目(82274481),项目负责人:姜萍;国家中医药管理局科技司共建科技项目(GZY-KJS-SD-2023-041),项目负责人:姜萍;山东省自然科学基金项目(ZR2022LZY004),项目负责人:姜萍;山东省卫生健康科创团队建设项目(2024sdskctd-03),项目负责人:姜萍;山东中医药大学2024年博士研究生提质创新课题(YJSTZCX2024010),项目负责人:刘源;山东中医药大学2025年研究生提质创新课题(YJSTZCX2025120),项目负责人:田轩赫

Potential targets and drug prediction for gout: identification of druggable genes

Tian Xuanhe1, Tong Siyu2, Teng Fei3, Zhong Shuai1, Zhao Xiaohu1, Zhang Yuya1, Liu Yuan1, Jiang Ping1   

  1. 1First Clinical College, Shandong University of Traditional Chinese Medicine, Jinan 250014, Shandong Province, China; 2College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250355, Shandong Province, China; 3Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing 100036, China
  • Received:2025-08-04 Revised:2025-11-28 Online:2026-10-18 Published:2026-03-07
  • Contact: Jiang Ping, PhD, Professor, First Clinical College, Shandong University of Traditional Chinese Medicine, Jinan 250014, Shandong Province, China Co-corresponding author: Liu Yuan, PhD candidate, First Clinical College, Shandong University of Traditional Chinese Medicine, Jinan 250014, Shandong Province, China
  • About author:Tian Xuanhe, MS candidate, First Clinical College, Shandong University of Traditional Chinese Medicine, Jinan 250014, Shandong Province, China
  • Supported by:
    National Natural Science Foundation of China, No. 82274481 (to JP); Joint Scientific Research Project of the Science and Technology Department of the National Administration of Traditional Chinese Medicine, No. GZY-KJS-SD-2023-041 (to JP); Shandong Provincial Natural Science Foundation, No. ZR2022LZY004 (to JP); Construction Project of Shandong Health Technology Innovation Team, No. 2024sdskctd-03 (to JP); 2024 Doctoral Research Quality Enhancement and Innovation Project of Shandong University of Traditional Chinese Medicine, No. YJSTZCX2024010 (to LY); 2025 Postgraduate Quality Improvement and Innovation Project of Shandong University of Traditional Chinese Medicine, No. YJSTZCX2025120 (to TXH)

摘要:



文题释义:
痛风:是一种由嘌呤代谢异常和尿酸排泄减少导致血清尿酸盐水平升高,单钠尿酸盐晶体沉积于关节引发炎症反应和组织损伤的代谢性疾病。痛风急性期表现为以剧烈疼痛为主的外周关节滑膜炎,若未经有效控制最终可发展为关节损伤、畸形、功能障碍和皮下痛风石沉积,严重时会出现肾功能受损、动脉粥样硬化或心脑血管意外等并发症。
可成药基因:是指其调控翻译的蛋白质能被药物干预,从而实现疾病治疗目的基因。药物-基因相互作用数据库通过数据挖掘生成了关于突变基因如何成为治疗靶点或优先用于药物开发的假设,这些基因调控的蛋白质通常具有明确的生物学功能,能在疾病的发生、发展及治疗过程中起重要作用。

背景:痛风现有治疗药物有较大不良反应,因此寻找新的痛风潜在靶点和靶向治疗药物尤为重要。
目的:通过结合可成药基因数据集和孟德尔随机化、共定位分析等方法确定痛风的遗传靶点,预测具有潜在治疗作用的化合物和中药,为深入探究中国人群痛风发病机制提供依据,为痛风的临床治疗和新靶向药物开发提供思路。
方法:通过由芬兰国家基因研究项目构建的芬兰数据库FinnGenR11获得痛风相关数据集,使用由布里斯托大学医学研究理事会综合流行病学单位开发的全基因组关联研究(GWAS)目录网站获取暴露因素的血液表达数量性状位点数据,进行孟德尔随机化分析确定潜在靶点;通过共定位分析确定痛风关键易感基因;通过基因本体论和京都基因与基因组百科全书富集分析探索基因功能,通过蛋白互作网络筛选互作密切靶点;使用由美国圣路易斯华盛顿大学医学院开发的药物-基因相互作用数据库预测具有潜在治疗作用的化合物,通过分子对接预测化合物和核心靶点的结合程度,使用PubGene公司创立的Coremine Medical数据库预测筛选核心基因相关治疗中药,所使用数据库均为公开资源。采用单钠尿酸盐晶体诱导的RAW264.7细胞作为痛风细胞模型,初步验证关键基因的表达和化合物的干预效果,通过CCK-8实验和细胞侵袭实验筛选安全剂量和最佳给药浓度,ELISA测定炎症因子水平,实时荧光定量反转录PCR检测关键靶点和通路的mRNA表达。
结果与结论:①孟德尔随机化分析确定了40个与痛风显著相关的潜在基因靶点;共定位分析确定了Jun原癌基因为痛风关键易感基因;蛋白互作网络显示Jun原癌基因、丝裂原活化蛋白激酶3和3-羟基-3-甲基戊二酰辅酶A还原酶互作关系密切;②基因本体论和京都基因与基因组百科全书富集结果显示潜在靶点主要通过调节丝裂原活化蛋白激酶、肿瘤坏死因子、ErbB、白细胞介素17、缺氧诱导因子1、Toll样受体等信号通路,干预细胞外信号调节激酶1/2级联反应的正向调控、谷胱甘肽代谢、泛素蛋白的调节等过程发挥作用;③根据潜在靶点预测出辣椒素、5,6-苯并黄酮、L-谷氨酸、槲皮素、和厚朴酚、山柰酚、肉桂醛和穿心莲内酯等372种具有潜在干预作用的化合物;④分子对接显示辣椒素和5,6-苯并黄酮与Jun原癌基因等核心靶点结合度较高;⑤预测得到苍术、厚朴、土茯苓、泽泻、丹参等79味潜在靶向中药,功效主要集中在清热解毒、活血化瘀和祛痰化湿;⑥细胞实验中CCK-8和细胞侵袭实验结果显示辣椒素的最佳安全给药剂量为
50 μmol/L,模型组中关键基因Jun原癌基因的表达显著上调,同时辣椒素可以显著下调Jun原癌基因以及 c-Jun氨基末端激酶、细胞外信号调节激酶1/2、p38等丝裂原活化蛋白激酶通路相关mRNA的表达,降低细胞上清白细胞介素6、白细胞介素1β和肿瘤坏死因子α的水平;⑦数据挖掘结果提示辣椒素、5,6-苯并黄酮等化合物和苍术、土茯苓等中药可能通过干预Jun原癌基因、丝裂原活化蛋白激酶3等靶点,调节肿瘤坏死因子、Th-17、缺氧诱导因子1等通路和丝裂原活化蛋白激酶级联反应、蛋白泛素化和谷胱甘肽代谢等过程发挥干预痛风的作用,其中关键易感基因JUN可作为潜在的痛风诊断标志物,以清热解毒为主结合活血化瘀等治法可作为痛风治疗的关键;⑧细胞实验初步验证了JUN基因和丝裂原活化蛋白激酶通路在痛风细胞模型中的表达以及辣椒素的干预作用,为下一步痛风诊疗靶点和新药物的开发提供基础和依据。

https://orcid.org/0009-0001-6880-4692 (田轩赫) 


中国组织工程研究杂志出版内容重点:干细胞;骨髓干细胞;造血干细胞;脂肪干细胞;肿瘤干细胞;胚胎干细胞;脐带脐血干细胞;干细胞诱导;干细胞分化;组织工程

关键词: 痛风, 可成药基因, 孟德尔随机化, 药物预测, 中药预测, 共定位, Jun原癌基因, 辣椒素, 丝裂原活化蛋白激酶信号通路

Abstract: BACKGROUND: Existing pharmacological treatments for gout are frequently limited by substantial side effects, underscoring the urgent need to discover novel therapeutic targets and develop more targeted drugs.
OBJECTIVE: To identify genetic targets for gout, and to predict promising therapeutic compounds as well as traditional Chinese medicines by integrating druggable gene datasets with Mendelian randomization and colocalization analysis approaches. This work will lay a foundation for in-depth exploration of the pathogenesis of gout in the Chinese population, and provide insights for the clinical management of gout as well as the development of new targeted drugs. 
METHODS: The gout-related dataset was acquired from FinnGenR11, a database developed by the Finnish National Genetic Research Project. Blood expression quantitative trait loci data for exposure factors were obtained from the genome-wide association studies directory website maintained by the Integrative Epidemiology Unit at the University of Bristol's Medical Research Council. Mendelian randomization analysis was employed to identify potential therapeutic targets, while co-localization analysis helped determine key susceptibility genes for gout. Gene functions were investigated through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. Protein-protein interaction networks were utilized to screen closely interacting targets. Potential therapeutic compounds were predicted using the drug-gene interaction database developed by Washington University School of Medicine in St. Louis, USA. Molecular docking predicted binding affinities between compounds and core targets, while the Coremine Medical database by PubGene Company helped identify relevant traditional Chinese medicines. All databases used were publicly available resources. For experimental validation, a gout cell model was established using monosodium urate crystal-induced RAW264.7 cells to preliminarily assess key gene expression and compound intervention effects. Safe doses and optimal concentrations were determined through CCK-8 assays and cell invasion assays. Inflammatory factor levels were measured using enzyme-linked immunosorbent assay, and real-time PCR was employed to detect mRNA expression of key targets and pathway components.
RESULTS AND CONCLUSION: (1) Mendelian randomization analysis identified 40 potential gene targets significantly associated with gout. Colocalization analysis determined Jun as a key susceptibility gene for gout. The protein interaction network revealed that Jun proto-oncogene, mitogen-activated protein kinase 3, and 3-hydroxy-3-methylglutaryl-CoA reductase demonstrate close interactions. (2) Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that the potential targets primarily functioned through modulation of key signaling pathways, including mitogen-activated protein kinase, tumor necrosis factor, ErbB, interleukin-17, hypoxia-inducible factor-1, and Toll-like receptor pathways. These targets appear to mediate biological processes such as positive regulation of extracellular signal-regulated kinase 1/2 cascade, glutathione metabolism, and ubiquitin-protein regulatory systems. (3) Based on potential targets, 372 compounds with possible intervention effects were predicted, such as capsaicin, 5,6-benzoflavone, L-glutamic acid, quercetin, magnolol, kaempferol, cinnamaldehyde, and andrographolide. (4) Molecular docking analysis revealed that capsaicin and 5,6-benzoflavone had a high binding degree with core targets such as Jun. (5) Totally 79 potential targeted traditional Chinese medicines were identified through prediction, including Atractylodes lancea, Magnolia officinalis, Smilax glabra, Alisia orientalis, and Salvia miltiorrhiza, with primary therapeutic functions including heat clearance and detoxification, blood activation and stasis resolution, and phlegm-dampness dissipation. (6) CCK-8 and cell invasion assays demonstrated that the optimal safe concentration of capsaicin was 50 μmol/L. The expression of the key gene Jun proto-oncogene was significantly upregulated in the model group. Meanwhile, capsaicin markedly downregulated the expression of Jun proto-oncogene and mRNA associated with the mitogen-activated protein kinase pathway, including c-Jun amino-terminal kinase, extracellular signal-regulated kinase 1/2, and p38. Additionally, it reduced the levels of interleukin-6, interleukin-1β, and tumor necrosis factor α in the cell supernatant. (7) Data mining results indicate that compounds including capsaicin and 5,6-benzoflavonoids, along with traditional Chinese medicines such as Atractylodes lancea and Smilax glabra, may potentially intervene in gout by targeting molecules such as Jun proto-oncogene and mitogen-activated protein kinase 3. These interventions appear to regulate multiple pathways, including tumor necrosis factor signaling, Th-17 cell differentiation, hypoxia-inducible factor 1 signaling, mitogen-activated protein kinase cascades, protein ubiquitination, and glutathione metabolism. Notably, the key susceptibility gene JUN may serve as a potential diagnostic marker for gout. The primary therapeutic approach for gout involves clearing heat and toxins combined with promoting blood circulation and resolving blood stasis. (8) The cell experiments provided preliminary verification of JUN gene expression and mitogen-activated protein kinase pathway activity in the gout cell model, as well as the therapeutic effects of capsaicin intervention. These findings establish a foundation for subsequent research on gout diagnostic and therapeutic targets, as well as new drug development.  

Key words: gout, drugable gene, Mendelian randomization, drug prediction, traditional Chinese medicine prediction, co-localization, Jun proto-oncogene, capsaicin, mitogen-activated protein kinase signaling pathway

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