Evidence map›Paper›PMID 39026683›Full record

ArticleFrontiers in immunology2024

Precision therapy for ulcerative colitis: insights from mitochondrial dysfunction interacting with the immune microenvironment.

Yi-Fan Zhang, Meng-Ying Fan, Qi-Rui Bai, Rong Zhao, Shan Song, Li Wu, Jun-Hui Lu, Jing-Wei Liu, Qi Wang, Yuan Li and 1 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

11 authors.

Yi-Fan Zhang *The First Clinical Medical College, Shanxi Medical University, Taiyuan, China.
Meng-Ying Fan *The Anesthesiology College, Shanxi Medical University, Taiyuan, China.
Qi-Rui BaiThe Second Clinical Medical College, Shanxi Medical University, Taiyuan, China.
Rong ZhaoThe Second Clinical Medical College, Shanxi Medical University, Taiyuan, China.
Shan SongThe Second Clinical Medical College, Shanxi Medical University, Taiyuan, China.
Li WuSchool of Basic Medical Sciences, Shanxi Medical University, Taiyuan, China.
Jun-Hui LuThe First Clinical Medical College, Shanxi Medical University, Taiyuan, China.
Jing-Wei LiuThe First Clinical Medical College, Shanxi Medical University, Taiyuan, China.
Qi WangSchool of Basic Medical Sciences, Shanxi Medical University, Taiyuan, China.
Yuan LiDepartment of Gastroenterology, The First Hospital of Shanxi Medical University, Taiyuan, China.
Xing ChenDepartment of Gastroenterology, The First Hospital of Shanxi Medical University, Taiyuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Accumulating evidence reveals mitochondrial dysfunction exacerbates intestinal barrier dysfunction and inflammation. Despite the growing knowledge of mitochondrial dysfunction and ulcerative colitis (UC), the mechanism of mitochondrial dysfunction in UC remains to be fully explored. Methods: We integrated 1137 UC colon mucosal samples from 12 multicenter cohorts worldwide to create a normalized compendium. Differentially expressed mitochondria-related genes (DE-MiRGs) in individuals with UC were identified using the "Limma" R package. Unsupervised consensus clustering was utilized to determine the intrinsic subtypes of UC driven by DE-MiRGs. Weighted gene co-expression network analysis was employed to investigate module genes related to UC. Four machine learning algorithms were utilized for screening DE-MiRGs in UC and construct MiRGs diagnostic models. The models were developed utilizing the over-sampled training cohort, followed by validation in both the internal test cohort and the external validation cohort. Immune cell infiltration was assessed using the Xcell and CIBERSORT algorithms, while potential biological mechanisms were explored through GSVA and GSEA algorithms. Hub genes were selected using the PPI network. Results: The study identified 108 DE-MiRGs in the colonic mucosa of patients with UC compared to healthy controls, showing significant enrichment in pathways associated with mitochondrial metabolism and inflammation. The MiRGs diagnostic models for UC were constructed based on 17 signature genes identified through various machine learning algorithms, demonstrated excellent predictive capabilities. Utilizing the identified DE-MiRGs from the normalized compendium, 941 patients with UC were stratified into three subtypes characterized by distinct cellular and molecular profiles. Specifically, the metabolic subtype demonstrated enrichment in epithelial cells, the immune-inflamed subtype displayed high enrichment in antigen-presenting cells and pathways related to pro-inflammatory activation, and the transitional subtype exhibited moderate activation across all signaling pathways. Importantly, the immune-inflamed subtype exhibited a stronger correlation with superior response to four biologics: infliximab, ustekinumab, vedolizumab, and golimumab compared to the metabolic subtype. Conclusion: This analysis unveils the interplay between mitochondrial dysfunction and the immune microenvironment in UC, thereby offering novel perspectives on the potential pathogenesis of UC and precision treatment of UC patients, and identifying new therapeutic targets.

Indexed as

Colitis, UlcerativeMitochondriaGene Expression ProfilingGene Regulatory NetworksHumansIntestinal MucosaMachine LearningMalePrecision Medicinebioinformatics analysisimmune infiltrationmachine learningmetabolismmitochondriaulcerative colitisunsupervised clustering

Identifiers

PMID39026683
PMCPMC11254623

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Registered trials

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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.