Distinct microbial signatures and their predictive value in recurrent acute pancreatitis: insights from 5-region 16S rRNA gene sequencing.

BACKGROUND

Recurrent acute pancreatitis (RAP) poses significant clinical challenges, with 32.3% developing to chronic pancreatitis within 5 years. The underlying microbial factors contributing to RAP remain poorly understood. This study aims to identify blood microbial signatures associated with RAP and explore the potential microbial predictors for RAP.

METHODS

In this prospective cohort, 90 acute pancreatitis patients are classified into non-recurrent acute pancreatitis (NRAP, n=68) and RAP (n=22) groups based on the number of pancreatitis episodes. Microbial composition of blood samples is analyzed using 5-region (5R) 16S rRNA gene sequencing. Key microbial taxa and functional predictions are made. A random forest model is used to assess the predictive value of microbial features for RAP. The impact of Staphylococcus hominis (S. hominis) on RAP is further evaluated in an experimental mouse model.

RESULTS

Linear discriminant analysis effect size (LEfSe) analysis highlights significant microbial differences, with Paracoccus aminovorans, Corynebacterium glucuronolyticum and S. hominis being prominent in RAP. Functional predictions indicate enrichment of metabolic pathways in the RAP group. Random forest analysis identifies key microbial taxa with an AUC value of 0.759 for predicting RAP. Experimental validation shows that S. hominis exacerbates pancreatic inflammation in mice.

CONCLUSIONS

This study identifies distinct clinical and microbial features associated with RAP, emphasizing the role of specific bacterial taxa in pancreatitis recurrence. The findings suggest that microbial profiling could enhance the diagnosis and management of RAP, paving the way for personalized therapeutic approaches.