Evidence map›Paper›PMID 41173896›Full record

ArticleScientific reports2025

Prediction of irritable bowel syndrome by integrating urine metabolites and gut microbiota.

Gayoun Lee, Mee-Hyun Lee, Seong-Eun Park, Juhan Pak, Soobin Bae, Suryang Kwak, Young-Ho Moon, Hong-Seok Son

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

8 authors.

Gayoun Lee *Department of Biotechnology College of Life Sciences and Biotechnology , Korea University , 02841, Seoul, Republic of Korea.
Mee-Hyun Lee *College of Korean Medicine , Dongshin University , 58245, Naju, Republic of Korea.
Seong-Eun ParkDepartment of Biotechnology College of Life Sciences and Biotechnology , Korea University , 02841, Seoul, Republic of Korea.
Juhan PakDepartment of Biotechnology College of Life Sciences and Biotechnology , Korea University , 02841, Seoul, Republic of Korea.
Soobin BaeDepartment of Biotechnology College of Life Sciences and Biotechnology , Korea University , 02841, Seoul, Republic of Korea.
Suryang KwakDepartment of Bio and Fermentation Convergence Technology, College of Science and Technology, Kookmin University, 02707, Seoul, Republic of Korea.
Young-Ho MoonMokpo Korean Medicine Hospital, Dongshin University , 58665, Mokpo, Republic of Korea. doc4you@hanmail.net.
Hong-Seok SonDepartment of Biotechnology College of Life Sciences and Biotechnology , Korea University , 02841, Seoul, Republic of Korea. sonhs@korea.ac.kr.

Funding

National Research Foundation of Korea 2022R1A5A2029546National Research Foundation of Korea RS-2024-00333618
6 · The paper itself

Abstract

Irritable bowel syndrome (IBS) is a functional gastrointestinal disorder characterized by recurrent abdominal pain and altered bowel habits. While gut microbiota alterations and metabolic disturbances have been implicated in IBS, their potential role in classification and patient stratification remains unclear. This study aimed to evaluate the potential of integrating gut microbiota profiling and urinary metabolomics for improved IBS classification. Fifty-four participants (27 healthy controls, 27 IBS patients) were recruited for gut microbiota and urinary metabolite analysis. Gut microbiota composition was assessed via 16S rRNA gene sequencing, and urinary metabolites were profiled using gas chromatography-mass spectrometry (GC-MS). Receiver operating characteristic (ROC) curve analysis was performed to assess the predictive accuracy of gut microbiota, urinary metabolites, and their combined model. LEfSe analysis identified that Clostridia and Prevotella as enriched in IBS patients, whereas Bacteroidales and Faecalitalea were predominant in healthy individuals. Urinary metabolite analysis revealed significant alterations in metabolite profiles, with IBS patients exhibiting elevated fructose levels and trends of increased serine, mannose, and galactose. ROC curve analysis demonstrated that urinary metabolomics (AUC = 0.65) outperformed gut microbiota profiling (AUC = 0.54), while a combined approach integrating both datasets achieved the highest predictive accuracy (AUC = 0.74). These findings indicate that integrating urinary metabolomics with gut microbiota profiling may provide preliminary insights into IBS classification. Given the small sample size, potential risk of overfitting, absence of external validation, and possible dietary or medication confounding, the observed performance of the combined approach should be regarded as hypothesis-generating rather than confirmatory. Nevertheless, the results highlight the potential utility of integrative omics strategies in IBS research, underscoring the need for validation in larger, sex-balanced, and clinically diverse cohorts to establish their robustness and broader relevance.

Indexed as

Gastrointestinal MicrobiomeIrritable Bowel SyndromeAdultCase-Control StudiesFemaleGas Chromatography-Mass SpectrometryHumansMaleMetabolomeMetabolomicsMiddle AgedRNA, Ribosomal, 16SROC CurveRNA, Ribosomal, 16SGut microbiotaIrritable bowel syndromeMetabolomicsNext-generation sequencingUrinary metabolites

Identifiers

PMID41173896
PMCPMC12578838

What Socratic holds

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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 Socratic graph.