ArticleJournal of thoracic disease2024
Transcriptomic analysis reveals the potential crosstalk genes and immune relationship between Crohn's disease and atrial fibrillation.
Article in Journal of thoracic disease, 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
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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.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Integrated bioinformatic analysis reveals the underlying mitochondria-associated endoplasmic reticulum membranes-related biomarkers for atrial fibrillation.Frontiers in physiology · 2025Article
- Exploring the Role of Chemokine-Related Gene Deregulation and Immune Infiltration in Ischemic Stroke: Insights into CXCL16 and SEMA3E as Potential Biomarkers.Journal of molecular neuroscience : MN · 2024Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: At present, there is a paucity of research on the link between Crohn's disease (CD) and atrial fibrillation (AF). Nevertheless, both ailments are thought to entail inflammatory and autoimmune processes, and emerging evidence indicates that individuals with CD may face an elevated risk of AF. To shed light on this issue, our study seeks to explore the possibility of shared genes, pathways, and immune cells between these two conditions. Methods: We retrieved the gene expression profiles of both CD and AF from the Gene Expression Omnibus (GEO) database and subjected them to analysis. Afterward, we utilized the weighted gene co-expression network analysis (WGCNA) to identify shared genes, which were then subjected to further Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Furthermore, we employed a rigorous analytical approach by screening hub genes through both least absolute shrinkage and selection operator (LASSO) regression and support vector machine (SVM), and subsequently constructing a receiver operating characteristic (ROC) curve based on the screening outcomes. Finally, we utilized single-sample gene set enrichment analysis (ssGSEA) to comprehensively evaluate the levels of infiltration of 28 immune cells within the expression profile and their potential association with the shared hub genes. Results: Using the WGCNA method, we identified 30 genes that appear to be involved in the pathological progression of both AF and CD. Through GO enrichment analysis on the key gene modules derived from WGCNA, we observed a significant enrichment of pathways related to major histocompatibility complex (MHC) and antigen processing. By leveraging the intersection of LASSO and SVM algorithms, we were able to pinpoint two overlapping genes, namely Conclusions: By employing bioinformatics tools, we conducted an investigation with the objective of elucidating the genetic foundations that connect AF and CD. This study culminated in the identification of
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