AUTHOR=Yao Shanxia , Xue Shenglong , Li Na , Shi Tian , Feng Yan , Maimaiti Munila , Maimaitireyimu Ayinuer , Halike Halina , Gao Feng 

TITLE=Integrated analysis of fecal microbiota and metabolomics reveals unique characteristics of asymptomatic and classic celiac disease

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2025.1636007

DOI=10.3389/fmicb.2025.1636007

ISSN=1664-302X

ABSTRACT=IntroductionCeliac Disease (CeD) is an autoimmune small intestinal disorder triggered by gluten, with clinical subtypes including typical, atypical, and asymptomatic forms.While classic CeD development is linked to microbes/metabolites, their relationships with other subtypes remain unclear.MethodsWe conducted 16S rDNA sequencing on fecal samples from 14 asymptomatic CeD (SCeD) patients and integrated this data with our team’s prior sequencing data of 30 classic CeD (CDF) patients and 30 healthy controls (CDFH).Results16S rDNA results showed: Compared to CDFH, SCeD had lower abundances of Bacteroides, Alistipes, CAG-352 and higher abundances of Blautia, Collinsella, Dorea, Mediterraneibacter, Gemmiger; a random forest model based on 8 differential microbes distinguished SCeD from CDFH (AUC = 0.97). Compared to CDF, SCeD had lower Bacteroides and higher Faecalibacterium, Blautia, Collinsella, Agathobacter—suggesting Bacteroides may relate to CeD symptoms, while Faecalibacterium and Agathobacter may alleviate symptoms. Metabolomic analysis identified differential metabolites between SCeD and CDFH (enriched in “Steroid Hormone Biosynthesis,” “Primary Bile Acid Biosynthesis,” “Tryptophan Metabolism” via KEGG) and between SCeD and CDF (enriched in “Tryptophan Metabolism,” “Biosynthesis of Plant Secondary Metabolites,” “Degradation of Flavonoids”). Spearman analysis showed correlations between differential microbes and metabolites.DiscussionIn conclusion, different CeD subtypes may involve a “host-microbe-metabolite” trinity network: A random forest model built with SCeD-CDFH differential microbes/metabolites is a high-efficacy SCeD diagnostic tool; modulating these microbes/metabolites could be a new entry point for CeD mechanism research and adjunctive therapy.