Observational studyJournal of translational medicine2024
Intestinal mRNA expression profiles associated with mucosal healing in ustekinumab-treated Crohn's disease patients: bioinformatics analysis and prospective cohort validation.
Observational study in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05542459 (Multi-omics to Predict Responses to Biologics in Inflammatory Bowel Disease), which is not on this map. Cited by 4 papers.
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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.
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.
Multi-omics to Predict Responses to Biologics in Inflammatory Bowel Disease
Who cites it
4 citing papers in PubMed.
- Identification and preliminary clinical validation of type 2 diabetes signature genes through machine learning analysis of scRNA-seq data.Frontiers in medicine · 2026Article
- Exploratory transcriptomic analysis suggests candidate genes associated with loss of response to ustekinumab in Crohn's disease.Frontiers in genetics · 2026Article
- Distinct B Cell Subsets Changes as Potential Biomarkers of Response to Biologic Therapy in Crohn's Disease.International journal of molecular sciences · 2025Article
- Development of Predictive Models for Long-Term Endoscopic Response to Ustekinumab in Crohn's Disease Based on Plasma Proteomics.Journal of inflammation research · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundVariations exist in the response of patients with Crohn's disease (CD) to ustekinumab (UST) treatment, but the underlying cause remains unknown. Our objective was to investigate the involvement of immune cells and identify potential biomarkers that could predict the response to interleukin (IL) 12/23 inhibitors in patients with CD.
methodsThe GSE207022 dataset, which consisted of 54 non-responders and 9 responders to UST in a CD cohort, was analyzed. Differentially expressed genes (DEGs) were identified and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Least absolute shrinkage and selection operator (LASSO) regression was used to screen the most powerful hub genes. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performances of these genes. Single-sample Gene Set Enrichment Analysis (ssGSEA) was used to estimate the proportions of immune cell types. These significantly altered genes were subjected to cluster analysis into immune cell-related infiltration. To validate the reliability of the candidates, patients prescribed UST as a first-line biologic in a prospective cohort were included as an independent validation dataset.
resultsA total of 99 DEGs were identified in the integrated dataset. GO and KEGG analyses revealed significant enrichment of immune response pathways in patients with CD. Thirteen genes (SOCS3, CD55, KDM5D, IGFBP5, LCN2, SLC15A1, XPNPEP2, HLA-DQA2, HMGCS2, DDX3Y, ITGB2, CDKN2B and HLA-DQA1), which were primarily associated with the response versus nonresponse patients, were identified and included in the LASSO analysis. These genes accurately predicted treatment response, with an area under the curve (AUC) of 0.938. T helper cell type 1 (Th1) cell polarization was comparatively strong in nonresponse individuals. Positive connections were observed between Th1 cells and the LCN2 and KDM5D genes. Furthermore, we employed an independent validation dataset and early experimental verification to validate the LCN2 and KDM5D genes as effective predictive markers.
conclusionsTh1 cell polarization is an important cause of nonresponse to UST therapy in patients with CD. LCN2 and KDM5D can be used as predictive markers to effectively identify nonresponse patients.
trial registrationTrial registration number: NCT05542459; Date of registration: 2022-09-14; URL: https://www. CLINICALTRIALS: gov .
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