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

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 and development of new targeted drugs. METHODS: Gout-related datasets were obtained from the Finnish database FinnGen R11. Blood expression quantitative trait loci data were obtained from the GWAS catalog website developed by the MRC Integrative Epidemiology Unit at the University of Bristol. Mendelian randomization analysis was performed to identify potential targets; colocalization analysis was used to identify key susceptibility genes for gout. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were used to explore gene functions, and protein-protein interaction networks were used to screen closely interacting targets. The Drug-Gene Interaction Database developed by Washington University School of Medicine in St. Louis was used to predict compounds with potential therapeutic effects. Molecular docking was used to predict the binding degree of compounds to core targets. The Coremine Medical database founded by PubGene was used to predict traditional Chinese medicines related to core genes. All databases used are public resources. A gout cell model was established using monosodium urate crystal-induced RAW264.7 cells to preliminarily verify the expression of key genes and the intervention effect of compounds. CCK-8 assay and cell invasion assay were used to screen safe doses and optimal administration concentrations. ELISA was used to measure inflammatory factor levels, and real-time fluorescence quantitative reverse transcription PCR was used to detect mRNA expression of key targets and pathways. RESULTS AND CONCLUSION: (1) Mendelian randomization analysis identified 40 potential gene targets significantly associated with gout; colocalization analysis identified Jun proto-oncogene as a key susceptibility gene for gout; protein-protein interaction network showed that Jun proto-oncogene, mitogen-activated protein kinase 3, and 3-hydroxy-3-methylglutaryl-CoA reductase had close interactions. (2) Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment results showed that potential targets mainly regulate mitogen-activated protein kinase, tumor necrosis factor, ErbB, interleukin-17, hypoxia-inducible factor 1, Toll-like receptor and other signaling pathways, and intervene in positive regulation of extracellular signal-regulated kinase 1/2 cascade, glutathione metabolism, ubiquitin protein regulation and other processes. (3) Based on potential targets, 372 compounds with potential intervention effects were predicted, including capsaicin, 5,6-benzoflavone, L-glutamic acid, quercetin, honokiol, kaempferol, cinnamaldehyde, and andrographolide. (4) Molecular docking showed that capsaicin and 5,6-benzoflavone had high binding affinity with core targets such as Jun proto-oncogene. (5) 79 potential targeted traditional Chinese medicines were predicted, including Atractylodes, Magnolia officinalis, Smilax glabra, Alisma orientale, and Salvia miltiorrhiza, with efficacy mainly concentrated in clearing heat and detoxifying, promoting blood circulation and removing blood stasis, and resolving phlegm and dampness. (6) In cell experiments, CCK-8 and cell invasion assay results showed that the optimal safe dose of capsaicin was 50 μmol/L. In the model group, the expression of key gene Jun proto-oncogene was significantly upregulated, and capsaicin could significantly downregulate the mRNA expression of Jun proto-oncogene and mitogen-activated protein kinase pathway-related genes such as c-Jun N-terminal kinase, extracellular signal-regulated kinase 1/2, and p38, and reduce the levels of interleukin-6, interleukin-1β, and tumor necrosis factor α in cell supernatant. (7) Data mining results suggest that compounds such as capsaicin and 5,6-benzoflavone and traditional Chinese medicines such as Atractylodes and Smilax glabra may exert therapeutic effects on gout by intervening in targets such as Jun proto-oncogene and mitogen-activated protein kinase 3, regulating tumor necrosis factor, Th-17, hypoxia-inducible factor 1 and other pathways, and mitogen-activated protein kinase cascade, protein ubiquitination, and glutathione metabolism. Among them, the key susceptibility gene JUN can serve as a potential diagnostic marker for gout. Treatment methods mainly focusing on clearing heat and detoxifying combined with promoting blood circulation and removing blood stasis can be key to gout treatment. (8) Cell experiments preliminarily verified the expression of JUN gene and mitogen-activated protein kinase pathway in gout cell model and the intervention effect of capsaicin, providing a basis and foundation for the next step of gout diagnosis and treatment targets and new drug development.

1. Introduction

Gout is a metabolic disease characterized by hyperuricemia due to purine metabolism abnormalities and reduced uric acid excretion, leading to the deposition of monosodium urate crystals in joints, which triggers inflammatory responses and tissue damage. The acute phase of gout manifests as peripheral joint synovitis with severe pain. If not effectively controlled, it can eventually progress to joint damage, deformity, dysfunction, and subcutaneous tophi deposition. In severe cases, complications such as renal impairment, atherosclerosis, or cardiovascular and cerebrovascular accidents may occur.

Current pharmacological treatments for gout, such as nonsteroidal anti-inflammatory drugs, colchicine, and corticosteroids, are often associated with significant adverse effects, including gastrointestinal, renal, and cardiovascular toxicities. Therefore, there is an urgent need to identify novel therapeutic targets and develop more effective and safer drugs. Advances in genomics and bioinformatics have enabled the identification of druggable genes and the prediction of potential therapeutic agents through approaches like Mendelian randomization and colocalization analysis.

In this study, we integrated druggable gene datasets with Mendelian randomization and colocalization analysis to identify genetic targets for gout. We further predicted potential therapeutic compounds and traditional Chinese medicines, and validated the expression of key genes and the intervention effect of a candidate compound in a cellular model. Our findings provide a foundation for understanding the pathogenesis of gout in the Chinese population and for the development of new targeted therapies.