ArticleAnnals of translational medicine2021
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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
4 citing papers in PubMed, 10 citations in OpenAlex.
- Endosome traffic in rheumatic diseases: mechanistic insights and therapeutic opportunities.Nature reviews. Rheumatology · 2026Review
- Exploring the association between circadian rhythms and osteoporosis: new diagnostic and therapeutic targets identified via machine learning.Frontiers in molecular biosciences · 2025Article
- PLCG2 and IFNAR1: The Potential Biomarkers Mediated by Immune Infiltration and Osteoclast Differentiation of Ankylosing Spondylitis in the Peripheral Blood.Mediators of inflammation · 2024Article
- Article
Corrections and comments
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Authors and funding
15 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study aimed to identify the key genes related to male ankylosing spondylitis (AS) and to analyze the role of immune cell infiltration in the pathological process of this disease.
methodsThe AS dataset was downloaded from the Gene Expression Omnibus (GEO) public database, and the data of male healthy controls (M_HC) and male AS patients (M_AS) were extracted. R software was used to identify differentially expressed genes (DEGs). Functional and pathway enrichment analysis of the DEGs was performed. A protein-protein interaction (PPI) network was constructed, and the hub genes were screened out. All expression profile data were analyzed by weighted correlation network analysis (WGCNA) to screen out the hub genes, which were then intersected with the hub genes from the PPI network to obtain the key genes. Finally, the difference in immune cell infiltration in the two sets of samples was evaluated with CIBERSORT, and the correlation between the key genes and infiltrating immune cells was analyzed.
resultsA total of 689 DEGs were obtained, of which 395 genes were up-regulated and 294 genes were down-regulated. Functional and pathway enrichment analysis showed that DEGs were mainly enriched in pathways related to immune response. Based on the PPI analysis, five clusters with high scores were selected. Through WGCNA, 14 gene modules were obtained. The green module with the highest correlation was selected and intersected with the cluster previously obtained to obtain three key genes,
conclusions
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What OpenQuestion 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 OpenQuestion graph.