Fecal microbiome analysis as a diagnostic test for diverticulitis.

Area of Science:

• Microbiome research
• Gastroenterology
• Diagnostic development

Background:

• Intestinal microbiome variations are linked to various gastrointestinal disorders.
• Limited knowledge exists regarding the specific microbiome alterations in diverticulitis.

Purpose of the Study:

• To compare fecal microbiota composition between diverticulitis patients and control subjects.
• To explore the potential of microbiota data for predictive diagnosis of diverticulitis.

Main Methods:

• Utilized high-throughput PCR-based profiling (IS-pro) on fecal samples from 31 diverticulitis patients and 25 controls.
• Assessed bacterial phylum abundance and diversity (Shannon index) using statistical analysis.
• Employed Principal Coordinate Analysis (PCoA) for microbiome dissimilarity and Partial Least Squares Discriminant Analysis (PLS-DA) for predictive modeling.

Main Results:

• Diverticulitis patients showed significantly higher fecal microbiota diversity, especially in Proteobacteria, compared to controls (p < 0.00002).
• Principal Coordinate Analysis revealed distinct clustering of patients and controls based on Proteobacteria profiles.
• A cross-validated PLS-DA model achieved 84% diagnostic accuracy for diverticulitis, with Enterobacteriaceae family species being highly discriminative.

Conclusions:

• Diverticulitis is characterized by increased fecal microbiota diversity, notably driven by the Proteobacteria phylum.
• Intestinal microbiota analysis presents a novel and accurate approach for diagnosing diverticulitis.
• The findings support the potential of microbiome profiling as a diagnostic tool in gastroenterology.