Evidence map›Paper›PMID 42125867›Full record

ArticleJournal of immunology research2026

Identification and Analysis of Biomarkers Associated With Lipid Metabolism and Ferroptosis in Ulcerative Colitis.

Xinmei Zhang, Xiufang Cui

Abstract read
In one paragraph

Article in Journal of immunology research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Xinmei ZhangDepartment of Gastroenterology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, China, njmu.edu.cn.ORCID https://orcid.org/0000-0003-3118-8520
Xiufang CuiDepartment of Gastroenterology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, China, njmu.edu.cn.ORCID https://orcid.org/0000-0003-2299-802X

Funding

Development Plan of Traditional Chinese Medicine Science and Technology in Jiangsu Province QN202217
6 · The paper itself

Abstract

backgroundMounting evidence shows that lipid metabolism and ferroptosis contribute to ulcerative colitis (UC), but the mechanism remains unclear. This study aimed to identify related biomarkers, clarify their roles in UC, and provide insights into optimized therapies.

methodsUC transcriptome, lipid metabolism, and ferroptosis-related gene (FRG) data were analyzed. Biomarkers were screened via differential expression analysis, consensus clustering, Venn, and machine learning, with expression validation. Receiver operating curve (ROC) analysis assessed predictive efficacy; functional enrichment, molecular regulatory, and immune infiltration analyses were performed. Real-time PCR verified candidate biomarkers in clinical samples.

resultsTwo biomarkers (acyl-CoA synthetase ligases 4 [ACSL4] and prostaglandin-endoperoxide synthase 2 [PTGS2]) were identified that distinguished UC from control samples. They may involve hematopoietic cell lines, cytokine-cytokine receptor interaction, and MALAT1 binding hsa-miR-576-5p/hsa-miR-503-5p. Notably, 27 differentially infiltrated immune cells were found (p  < 0.05), with CD56dim natural killer cells negatively correlating with ACSL4/PTGS2. Both genes were significantly upregulated in the UC clinical samples.

conclusionACSL4 and PTGS2 are lipid metabolism- and ferroptosis-related biomarkers of UC, laying a foundation for clinical treatment.

Indexed as

BiomarkersCoenzyme A LigasesColitis, UlcerativeCyclooxygenase 2FerroptosisLipid MetabolismGene Expression ProfilingHumansTranscriptomeBiomarkersCoenzyme A LigasesCyclooxygenase 2PTGS2 protein, humanbiomarkersferroptosislipid metabolismulcerative colitis

Identifiers

PMID42125867
PMCPMC13169151

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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.