ArticleEuropean journal of medical research2025
Diagnostic and prognostic significance of Super-enhancer-associated genes in Crohn's disease and immune regulatory roles.
Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSuper-enhancers (SEs) are implicated in the regulation of the onset and progression of Crohn's disease (CD). However, the precise mechanisms remain unclear. This study aims to investigate the diagnostic potential and molecular mechanisms of SE-related genes (SERGs) as biomarkers for CD from a transcriptomics perspective.
methodsData on CD and SERGs were retrieved from public databases. Differential expression analysis, the Maximal Clique Centrality algorithm, and two machine learning methods were applied, complemented by receiver operating characteristic analysis and expression level assessment to identify biomarkers and construct a nomogram for evaluating their diagnostic value. Enrichment and immune infiltration analyses were performed subsequently. Unsupervised clustering categorized CD samples into distinct subtypes based on the biomarkers, and functional and immune microenvironmental differences among these subtypes were examined. Immunohistochemical experiments confirmed the elevated protein expression of hub genes in colonic tissues from patients with CD relative to healthy controls (P < 0.05).
resultsPAQR5, IFITM3, PSMB8, and IRF1, were identified as biomarkers for CD, demonstrating robust diagnostic performance, with area under curve (AUC) values of 0.988, 0.973, 0.959, and 0.940, respectively. When integrated into a nomogram, the AUC reached 0.991. Except for PAQR5, the other three genes showed significantly higher expression in CD samples, a trend confirmed clinically by immunohistochemical experiments. These biomarkers were involved in areas such as immune regulation, cell biology, and sensory perception. Immunoassays further elucidated the specific infiltration patterns of different immune cells in CD and highlighted the importance of these biomarkers in regulating immune cell functions. Additionally, we classified the CD samples into two subtypes, with the biomarkers exhibiting significant expression differences between the subtypes. These two subtypes possessed distinct immune microenvironments, with the biomarkers showing moderate correlation with the differential immune cells between the subtypes.
conclusionPAQR5, IFITM3, PSMB8, and IRF1 serve as biomarkers for CD, offering substantial diagnostic and immune regulatory value. These biomarkers differentiate CD into two subtypes, providing insights for personalized therapeutic strategies.
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.