The gut microbiota features and the application value in predicting recurrent risks for gallstone patients who underwent laparoscopic cholecystectomy

Abstract

Gut microbiota is associated with gallstone occurrence and recurrence. But whether they can predict post-cholecystectomy choledocholithiasis recurrence needs to be investigated. From September 2020 to June 2021, a total of 100 symptomatic gallstone patients scheduled for laparoscopic cholecystectomy were enrolled in the Disease group in the Department of Hepatobiliary Surgery at Quanzhou First Hospital. Meanwhile, a total of 50 age- and sex-matched healthy controls were included in the Control group. Fecal specimens were collected from both groups and subjected to 16S rDNA sequencing (V3V4 region) for microbiologic analysis. After laparoscopic cholecystectomy, patients were followed up, and recurrent cases were recorded. Finally, a nomogram for predicting recurrent risks was built. The gut microbial diversity in the Disease group was significantly lower than that of the Control group (all P < 0.05). The Chao1 index of the recurrent group was remarkably lower than the control group (P < 0.05). Linear discriminant analysis (LDA) effect size (LEfSe) analysis showed that Phocaeicola dorei (LDA score = 4.2, P < 0.05) was the feature microbiota in the recurrent group. Logistic regression analysis showed that the composition of stones, the high abundances of P. dorei and Fusobacterium necrogenes were potential risk factors for recurrent choledocholithiasis, and a nomogram based on these factors demonstrated high accuracy and excellent calibration. This study has identified potential risk factors for recurrent choledocholithiasis and built a nomogram that can well predict recurrent risks for patients who undergo cholecystectomy, which might serve as a useful tool for patients' stratification and post-surgery management.IMPORTANCEThis study identifies specific gut microbiome signatures of gallstone patients and indicates that reduced diversity and high abundances of Phocaeicola dorei and Fusobacterium necrogenes might be potential predictors for choledocholithiasis recurrence after cholecystectomy. By demonstrating a link between gut microbiota composition and post-surgical recurrence risk, it advances our understanding beyond simple association with predictive capability. The development of a nomogram incorporating these microbial markers provides a novel, clinically applicable tool for accurate risk stratification of patients undergoing cholecystectomy, therefore bridging the gap between microbial ecology and clinical practice. The significance of this study lies in that it aims to address a critical unmet need in gallstone disease management by offering a more cost-effective and non-invasive tool to improve long-term patient outcomes and pave the way for microbiome-targeted interventions.CLINICAL TRIALSThis study is registered with Chinese Clinical Trial Registry Center as ChiCTR2400090232.

Keywords: choledocholithiasis; gallstones; gastrointestinal microbiome; laparoscopic cholecystectomy.

Fig 1

The flowchart of the study design. Four patients were excluded from microbiome analysis due to poor quality of fecal samples.

Fig 2

Differences in gut microbiota diversity and taxa composition between the Control group and the Gallstone group. Differences in α-diversity between two groups regarding Shannon index (A), Simpson index (B), Chao1 index (C), Observed species (D), and ACE index (E). Differences in β-diversity between the two groups regarding the unweighted unifrac PCA plot (F) and the unweighted unifrac PCoA plot (G). Bar plot (H) and pie plot (I) of the taxa distribution of the two groups at the genus level.

Fig 3

Feature microbiota and functional prediction of gallstone patients. LEfSe analysis results (A, B) showed that phylum Bacteroidota and genus Phocaeicola were the feature microbiota in gallstone patients. (C) Venn diagram of differential abundance analysis results by LEfSe, ANCOM-BC2, and DEseq2 analyses. (D) Relative abundance of the six differentially abundant taxa between the two groups. (E) Random forest analysis of the feature microbiota.

Fig 4

Gut microbiome characteristics of recurrent gallstone patients. (A) Differences in α-diversity among the control, recurrent, and non-recurrent groups. (B) Differences in weighted unifrac PCA analysis. (C) Differences in weighted unifrac PCoA analysis. (D) LEfSe analysis result showed that the recurrent patients were featured by phylum Bacteroidota and phylum Fusobacteriota. (E) Heatmap of the top 50 differentially abundant species with LDA score >2. (F) Bar plot of the abundance of the species Phocaeicola dorei and the species Fusobacterium necrogenes. (G) Spearman correlation analysis of the differentially abundant species and clinical laboratory indicators.

Fig 5

Gut microbiome characteristics of pigment and cholesterol gallstones. (A) Differences in α-diversity among the control, pigment, and cholesterol gallstone groups. (B) Cladogram of the featured microbiota. (C) LEfSe analysis result showed that P. dorei and P. vulgatus were enriched in the cholesterol gallstone group. (D) Heatmap of the differentially abundant species and their correlations with blood bilirubin.

Fig 6

Clinical prediction model built by logistic regression analysis. (A) ROC curves of the training set and validation set. (B) Calibration performance of the clinical prediction model. (C) Decision curve analysis of the clinical prediction model. (D) Nomogram of the clinical prediction model. Composition 1 refers to pigment stones; composition 2 refers to cholesterol stones.