ArticleHuman genomics2025
Identification and experimental validation of ulcerative colitis-associated hub genes through integrated WGCNA and lysosomal autophagy analysis.
Article in Human genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 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
3 citing papers in PubMed.
- Article
- Bioinformatics combined with machine learning for the identification of malignant transformation markers in colorectal polyps.Frontiers in molecular biosciences · 2026Article
- Identification and validation of aryl hydrocarbon receptor-associated hub genes in ulcerative colitis via integrated bioinformatics analysis.Human genomics · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors.
Funding
Abstract
objectiveThis study aims to systematically identify differentially expressed genes associated with lysosomal autophagy in ulcerative colitis (UC) and validate key candidate genes in an animal model, thereby providing novel insights driving UC pathogenesis.
methodsThe GSE47908 dataset from the Gene Expression Omnibus (GEO) was subjected to principal component analysis (PCA), followed by stratified identification of differentially expressed genes (DEGs) across UC subtypes. Immune cell infiltration of these gene sets was evaluated using the CIBERSORT algorithm. Lysophagy-related genes set were retrieved from the GeneCards database. Bioinformatics methods were employed to stratify UC DEGs, weighted gene co-expression network analysis (WGCNA) module genes, and lysophagy-associated DEGs, which were then subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A protein-protein interaction (PPI) network was constructed via the STRING database, and Cytoscape was used to identify core genes highly associated with lysophagy. Core genes were validated using external datasets, and experimental UC mouse model was established to confirm their expression levels by real-time quantitative reverse transcription PCR (RT-qPCR).
resultsPCA of the GSE47908 dataset across UC subtypes revealed distinct spatial separation, integrated and subgroup analyses identified lysophagy-related key genes, and enrichment analyses demonstrated differences in core genes and pathways between overall UC and its subtypes. A PPI network highlighted five hub genes in UC (CASP1, CXCL1, LCN2, PSMB9, AGT). Upregulation of these genes was confirmed via external datasets and animal experiments. Moreover, immune infiltration analysis of UC samples demonstrated immune dysregulation during disease progression, underscoring the interplay between lysophagy and inflammation in UC.
conclusionThe five genes identified-CASP1, CXCL1, LCN2, PSMB9, and AGT-exhibit strong associations with lysosomal autophagy. Our findings suggest that these genes may function as critical regulators of lysosomal autophagy in UC.
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.