The researchers identified 110 participants with IBS and 39 health participants, including 232 fecal samples and 59 mucosal biopsy samples. They investigated whether composition of the intestinal microbiota was associated with clinical features of IBS.
Here’s what you need to know:
1. The researchers leveraged a machine learning procedure to identify a microbial signature for severe IBS, which encompassed 90 bacterial operational taxonomic units.
2. IBS symptom severity was negatively associated with microbial richness, exhaled CH4, presence of methanogens and enterotypes enriched with Clostridiales or Prevotella species.
3. In a validation set, the researchers were able to use the signature to differentiate between patients with severe symptoms, patients with mild or moderate symptoms and healthy subjects.
4. This intestinal microbiota profile could not be explained by differences in diet or use of medications, which suggests an independent association with IBS symptoms.
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