ArticleHeliyon2024
Identification of SOCS3 and PTGS2 as new biomarkers for the diagnosis of gout by cross-species comprehensive analysis.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Steaming and Sodium Bicarbonate-Assisted Aqueous Extraction ofFoods (Basel, Switzerland) · 2026Article
- Integrated discovery and mechanistic characterization of xanthine oxidase inhibitory peptides from sheep Milk.Food chemistry: X · 2026Article
- Gout Inflammation Time Programming: Molecular Clock from Crystal Triggering to Tissue Remodeling.International journal of molecular sciences · 2026Review
- Traditional Chinese Medicine in Hyperuricemia: Current Advances, Mechanistic Insights, and Clinical Challenges.International journal of general medicine · 2026Review
- Identification of key oxidative phosphorylation-related genes in systemic lupus erythematosus based on transcriptomics and bioinformatics analysis.Journal of translational autoimmunity · 2025Article
- Exploring Therapeutic Potential of Bi-Qi Capsules in Treatment of Gout by Discovering Crucial Drug Targets.Pharmaceuticals (Basel, Switzerland) · 2025Article
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Authors and funding
10 authors.
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Abstract
Background: Gout is the most common inflammatory arthritis in adults. Gout is an arthritic disease caused by the deposition of monosodium urate crystal (MSU) in the joints, which can lead to acute inflammation and damage adjacent tissue. Hyperuricemia is the main risk factor for MSU crystal deposition and gout. With the increasing burden of gout disease, the identification of potential biomarkers and novel targets for diagnosis is urgently needed. Methods: For the analysis of this subject paper, we downloaded the human gout data set GSE160170 and the gout mouse model data set GSE190138 from the GEO database. To obtain the differentially expressed genes (DEGs), we intersected the two data sets. Using the cytohubba algorithm, we identified the key genes and enriched them through GO and KEGG. The gene expression trends of three subgroups (normal control group, intermittent gout group and acute gout attack group) were analyzed by Series Test of Cluster (STC) analysis, and the key genes were screened out, and the diagnostic effect was verified by ROC curve. The expression of key genes in dorsal root nerve and spinal cord of gout mice was analyzed. Finally, the clinical samples of normal control group, hyperuricemia group, intermittent gout group and acute gout attack group were collected, and the expression of key genes at protein level was verified by ELISA. Result: We obtained 59 co-upregulated and 28 co-downregulated genes by comparing the DEGs between gout mouse model data set and human gout data set. 7 hub DEGs(IL1B, IL10, NLRP3, SOCS3, PTGS2) were screened out via Cytohubba algorithm. The results of both GO and KEGG enrichment analyses indicate that 7 hub genes play a significant role in regulating the inflammatory response, cytokine production in immune response, and the TNF signaling pathway. The most representative hub genes SOCS3 and PTGS2 were screened out by Series Test of Cluster, and ROC analysis results showed the AUC values were both up to 1.000. In addition, we found that PTGS2 expression was significantly elevated in the dorsal root ganglia and spinal cord in monosodium urate(MSU)-induced gout mouse model. The ELISA results revealed that the expression of SOCS3 and PTGS2 was notably higher in the acute gout attack and intermittent gout groups compared to the normal control group. This difference was statistically significant, indicating a clear distinction between the groups. Conclusion: Through cross-species comprehensive analysis and experimental verification, SOCS3 and PTGS2 were proved to be new biomarkers for diagnosing gout and predicting disease progression.
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