ArticleClinical and experimental medicine2023
Identification of antigen-presentation related B cells as a key player in Crohn's disease using single-cell dissecting, hdWGCNA, and deep learning.
Article in Clinical and experimental medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 8 citations in OpenAlex.
- Identification of a novel signature in progression of non-small cell lung cancer based on HdWGCNA and in vitro validation.BMC medical genomics · 2026Article
- Colonic spatial single-cell proteomics and murine models link mitochondrial dysfunction to dimeric IgA-secreting plasma cell deficiency in Crohn's disease.Nature communications · 2026Article
- Identification of key genes related to arginine metabolism in immunoglobulin A nephropathy through the combination of scRNA-seq and bulk RNA-seq data.Frontiers in immunology · 2026Article
- Mechanistic remodeling and immunoregulatory functions of the B cell-humoral immunity axis in inflammatory bowel disease.Frontiers in immunology · 2026Review
- Imbalanced IgA-IgG class switching recombination: a novel mechanism of gut immune dysregulation in inflammatory bowel disease.Frontiers in immunology · 2026Review
- Identification and Validation of Fibroblast-Associated Genes in Osteoarthritis Based on High-Dimensional Weighted Gene Coexpression Network Analysis.Journal of immunology research · 2025Article
- Artificial intelligence use for precision medicine in inflammatory bowel disease: a systematic review.American journal of translational research · 2025Review
- Comparing gene-gene co-expression network approaches for the analysis of cell differentiation and specification on scRNAseq data.Computational and structural biotechnology journal · 2025Article
- Integrating single-cell RNA-Seq and machine learning to dissect tryptophan metabolism in ulcerative colitis.Journal of translational medicine · 2024Article
- Mining single-cell data for cell type-disease associations.NAR genomics and bioinformatics · 2024Article
- Identification of platelet-related subtypes and diagnostic markers in pediatric Crohn's disease based on WGCNA and machine learning.Frontiers in immunology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
Abstract
Crohn's disease (CD) arises from intricate intercellular interactions within the intestinal lamina propria. Our objective was to use single-cell RNA sequencing to investigate CD pathogenesis and explore its clinical significance. We identified a distinct subset of B cells, highly infiltrated in the CD lamina propria, that expressed genes related to antigen presentation. Using high-dimensional weighted gene co-expression network analysis and nine machine learning techniques, we demonstrated that the antigen-presenting CD-specific B cell signature effectively differentiated diseased mucosa from normal mucosa (Independent external testing AUC = 0.963). Additionally, using MCPcounter and non-negative matrix factorization, we established a relationship between the antigen-presenting CD-specific B cell signature and immune cell infiltration and patient heterogeneity. Finally, we developed a gene-immune convolutional neural network deep learning model that accurately diagnosed CD mucosa in diverse cohorts (Independent external testing AUC = 0.963). Our research has revealed a population of B cells with a potential promoting role in CD pathogenesis and represents a fundamental step in the development of future clinical diagnostic tools for the disease.
Indexed as
Identifiers
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.