Evidence map›Paper›PMID 40821793›Full record

ArticleFrontiers in immunology2025

Multi-omics derivation of a core gene signature for predicting therapeutic response and characterizing immune dysregulation in inflammatory bowel disease.

Mingming Wang, Liping Liang, Zibo Tang, Jimin Han, Lele Wu, Le Liu, Ye Chen

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
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  3. Observational
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  5. The role ofFrontiers in immunology · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Mingming Wang *Department of Gastroenterology, State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Liping Liang *Department of Gastroenterology and Hepatology, Guangzhou Key Laboratory of Digestive Diseases, Guangzhou Digestive Disease Center, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China.
Zibo TangDepartment of Radiation Oncology, Shenzhen People's Hospital (The Second Clinical Medical College at Jinan University and The First Affiliated Hospital at the Southern University of Science and Technology), Shenzhen, China.
Jimin HanSchool of Life Sciences, Tsinghua University, Beijing, China.
Lele WuShenzhen Clinical Research Center for Digestive Disease, Integrative Microecology Clinical Center, Shenzhen Key Laboratory of Gastrointestinal Microbiota and Disease, Shenzhen Technology Research Center of Gut Microbiota Transplantation, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Le LiuShenzhen Clinical Research Center for Digestive Disease, Integrative Microecology Clinical Center, Shenzhen Key Laboratory of Gastrointestinal Microbiota and Disease, Shenzhen Technology Research Center of Gut Microbiota Transplantation, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Ye ChenDepartment of Gastroenterology, State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Inflammatory bowel disease (IBD) presents unpredictable therapeutic responses and complex immune dysregulation. Current precision medicine approaches lack robust molecular tools integrating transcriptomic signatures with immune dynamics for personalized treatment guidance. Methods: We performed multi-omics analyses of GEO datasets using machine learning algorithms (LASSO/Random Forest) to derive a four-gene signature. Validation employed ten algorithms and nomogram construction. Immune infiltration (CIBERSORT/ssGSEA), single-cell RNA sequencing, and DSS-colitis models characterized immune dynamics, cellular specificity, and therapeutic response modulation. Results: We identified 536 differentially expressed genes significantly enriched in IL-17 signaling, TNF signaling, and cytokine-cytokine receptor interactions. WGCNA revealed six co-expression modules with disease-specific correlations: turquoise module strongly correlated with Crohn's disease (r=0.6, P=4×10 Conclusion: This mechanistically grounded four-gene signature enables precise IBD patient stratification across distinct immunological subtypes and predicts biologic responses, providing validated molecular tools for precision immunotherapy and personalized treatment optimization.

Indexed as

Inflammatory Bowel DiseasesTranscriptomeAnimalsColitis, UlcerativeComputational BiologyCrohn DiseaseGene Expression ProfilingGene Regulatory NetworksHumansMiceMultiomicsNomogramsbiologic response predictionimmune infiltrationinflammatory bowel diseasemachine learningprecision medicine

Identifiers

PMID40821793
PMCPMC12350116

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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.