Screening of Differential Metabolites and Metabolic Pathway Analysis Related to Colorectal Adenoma Recurrence

ABSTRACT:

Background To analyze the differences in gut metabolites between the CRA (colorectal adenoma) recurrence and non-recurrence groups, to identify characteristic metabolites and related metabolic pathways associated with recurrence, and to provide new evidence for risk stratification and intervention.

Methods 30 participants with CRA recurrence and 15 participants without CRA recurrence were selected. Demographic data, baseline characteristics of adenomas, and other clinical information of each participant were collected. Additionally, fecal samples from each participant were gathered, and fecal metabolomic analysis was performed using ultra-performance liquid chromatography and tandem-mass spectrometry (UPLC-MS/MS). Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were employed to screen differential metabolites, followed by pathway enrichment analysis via the KEGG database. Firth Logistic regression analysis was employed to conduct a joint analysis of clinical variables and differential metabolites.

Results Univariate analysis revealed statistically significant differences between the two groups in terms of age, body mass index (BMI), diabetes, smoking history, adenoma size, number of adenomas, and advanced adenomas (P < 0.05). There were significant differences in gut metabolites between the two groups. A total of 69 differential metabolites, including GABA (γ-Aminobutyric acid) and TDCA (Taurodeoxycholic acid), were identified. These metabolites were significantly enriched in 26 pathways, such as arginine and proline metabolism, bile secretion, secondary bile acid biosynthesis and primary bile acid biosynthesis (P < 0.05). Multivariate analysis identified smoking history, number of adenomas, and GABA were independent risk factors for CRA recurrence (all P < 0.05).

Conclusion Significant differences in fecal metabolite profiles were observed between the two groups. These metabolites are mainly involved in pathways related to bile acid and amino acid metabolism. By integrating clinical risk factors with characteristic intestinal metabolites, it is hoped that a more precise predictive model for CRA recurrence can be constructed, which will provide theoretical support for future intervention strategies targeting the intestinal metabolites and related metabolic pathways.

INSTRUMENT(S): Liquid Chromatography MS - positive - hilic, Liquid Chromatography MS - negative - hilic

PROVIDER: MTBLS15298 | MetaboLights | 2026-08-08

REPOSITORIES: MetaboLights