ArticleFrontiers in cardiovascular medicine2024
Identification of key genes in gout and atherosclerosis and construction of molecular regulatory networks.
Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Trained immunity in gout: epigenetic and metabolic reprogramming of innate immune memory.Frontiers in immunology · 2026Review
- Transcriptional regulatory network analysis uncovers modular gene control and potential key regulators in diabetic cardiomyopathy.Frontiers in cell and developmental biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Gout is a type of chronic inflammatory disease linked to the accumulation of monosodium urate crystals, leading to arthritis. Studies have shown that patients with gout are more likely to develop atherosclerosis, but the specific mechanisms involved remain unknown. The purpose of the research was to explore the key molecules and potential mechanisms between gout and atherosclerosis. Methods: Gene expression profiles for gout as well as atherosclerosis were obtained from the Gene Expression Omnibus (GEO) database, then differential analysis was utilized to identify common differentially expressed genes (DEGs) between the two diseases. The analysis of functional enrichment was conducted to investigate the biological processes that the DEGs might be involved in. The Cytoscape software was utilized to develop a protein-protein interaction (PPI) network as well as identify hub genes, while LASSO analysis was employed to select key genes. The TRRUST database was utilized to forecast transcription factors (TFs), and the miRTarBase database was utilized to forecast miRNAs. Results: Four key genes, CCL3, TNF, CCR2, and CCR5, were identified. The receiver operating characteristic (ROC) curves showed that the areas under ROC curve (AUC) for these four key genes in both gout and atherosclerosis were greater than 0.9. The analysis of functional enrichment revealed that the DEGs were primarily involved in "regulation of T-cell activation", "chemokine signaling pathway", and other biological processes. The TRRUST prediction results indicated that RELA and NFKB1 are common regulatory transcription factors for CCR2, CCR5, CCL3, and TNF. The miRTarBase prediction results showed that hsa-miR-203a-3p is a common regulatory miRNA for TNF and CCR5. Conclusion: This study preliminarily explored the potential key molecules and mechanisms between gout and atherosclerosis. These findings provide new insights for further research into identifying potential biomarkers and clinical treatment strategies for these two diseases.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.