ArticleJournal of inflammation research2022
Screening Key lncRNAs of Ankylosing Spondylitis Using Bioinformatics Analysis.
Article in Journal of inflammation research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Diagnostic value of long noncoding RNAs as biomarkers for Ankylosing Spondylitis: A systematic review and meta-analysis.PloS one · 2025Pooled it
- Crucial role of lncRNA NONHSAG037054.2 and GABPA, and their related functional networks, in ankylosing spondylitis.Experimental and therapeutic medicine · 2024Article
- A review of long non-coding RNAs in ankylosing spondylitis: pathogenesis, clinical assessment, and therapeutic targets.Frontiers in cell and developmental biology · 2024Review
- Transcriptome organization of white blood cells through gene co-expression network analysis in a large RNA-seq dataset.Frontiers in immunology · 2024Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Long non-coding RNAs (lncRNAs) are important regulators in ankylosing spondylitis (AS). Few studies have examined the lncRNA-RNA binding protein (RBP) interaction in AS. This study performed bioinformatics analysis and clinical verification to identify key lncRNAs and propose their RBP interaction. Methods: Three GEO datasets of AS were analyzed by differential expression analysis. The differentially expressed lncRNAs between the AS and control groups were screened out, and the intersecting lncRNAs were regarded as target lncRNAs. Functional was performed to identify target lncRNAs by enrichment analysis, co-expressed RNA analysis, and lncRNA-RBP interaction analysis. Finally, this study analyzed the differential expression level and clinical value of lncRNAs between the AS and control groups. Results: Linc00304, linc00926, and MIAT were differentially expressed and upregulated. Enrichment analysis indicated that the key KEGG terms were the T-cell receptor signaling pathway and B-cell receptor signaling pathway. The key molecular function term was protein binding, and the key biological process term was adaptive immune response. In qRT-PCR results, 44 samples were validated. linc00304 expression was positively correlated with bath ankylosing spondylitis disease activity index (BASDAI), bath ankylosing spondylitis functional index (BASFI), erythrocyte sedimentation rate (ESR), and c-reactive protein (CRP). linc00926 expression was only positively correlated with ESR, whereas MIAT expression was positively correlated with BASFI, ESR, and CRP. Logistic regression revealed that linc00304, ESR, and CRP were the independent risk factors for BASDAI activation. The area under the curve (AUC) of serum linc00304 level in the diagnosis of AS was 0.687 (cutoff value: 0.413, specificity: 0.423, sensitivity: 0.900). AUC of linc00926 was 0.664 (cutoff value: 0.299, sensitivity: 0.882, specificity: 0.417). AUC of MIAT was 0.623 (cutoff value: 0.432, specificity: 0.443, sensitivity: 0.890) (all Conclusion: Overall, this study uncovered three novel lncRNAs, which were upregulated in AS, and proposed a new lncRNA-RBP-mRNA interaction that might regulate adaptive immune response.
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