Evidence map›Paper›PMID 41777533›Full record

ArticleFrontiers in microbiology2026

16S ribosomal ribonucleic acid sequencing reveals bile microbiome features in gallstone disease and their links to blood lipid subtypes.

Shijie Wang, Yongxing Ding, Cheng Cai, Mingrui Ou, Chunshen Niu

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Article in Frontiers in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Shijie Wang *Department of Hepatobiliary Surgery, Third People's Hospital of Bengbu City, Bengbu, Anhui, China.
Yongxing Ding *Department of Hepatobiliary Surgery, Third People's Hospital of Bengbu City, Bengbu, Anhui, China.
Cheng CaiDepartment of Surgery, Bengbu Medical University (Residency Training Base of Surgery), Third People's Hospital of Bengbu City, Bengbu, Anhui, China.
Mingrui OuDepartment of Hepatobiliary Surgery, Third People's Hospital of Bengbu City, Bengbu, Anhui, China.
Chunshen NiuDepartment of Hepatobiliary Surgery, Third People's Hospital of Bengbu City, Bengbu, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gallstone disease (GSD) represents a major global health burden with complex pathophysiology involving bile microbiome dysbiosis and metabolic dysfunction. Although previous studies have examined bile microbial communities, the relationship between bile microbiome composition and specific lipid phenotypes remains incompletely understood. Methods: We conducted a cross-sectional study of 28 adults undergoing cholecystectomy for radiologically and pathologically confirmed gallstones. Bile samples were collected intraoperatively and subjected to 16S ribosomal ribonucleic acid V3-V4 region sequencing. Patients were stratified by lipid subtypes based on contemporary dyslipidaemia guidelines. Microbial diversity, community structure and differential abundance analyses were performed alongside machine learning classification. Results: The bile microbiome exhibited distinct compositional patterns between the hypertriglyceridaemia (HTG) and non-HTG (NTG) groups, with key phyla (Proteobacteria, Firmicutes) showing group-specific abundance trends and alpha diversity indices reflecting reduced evenness in HTG. Beta diversity analyses demonstrated mild-to-moderate separation between groups, and the linear discriminant analysis effect size technique identified discriminatory taxa with potential functional relevance. Random forest classification achieved moderate accuracy in predicting lipid subtypes based on microbial features. Conclusions: This study revealed associations between bile microbiome composition and systemic lipid metabolism in GSD, suggesting potential mechanistic links through bile acid metabolism and farnesoid X receptor-fibroblast growth factor 19 signaling pathways.

Indexed as

bilebile acids and saltsgallstoneshypertriglyceridaemiamicrobiota

Identifiers

PMID41777533
PMCPMC12951477

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