Acromegaly is associated with a distinct oral and gut microbiota

Sahin S., GÜNDOĞDU A., Nalbantoglu U., KADIOĞLU P., Karaca Z., HACIOĞLU A., ...More

Pituitary, vol.25, no.3, pp.520-530, 2022 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 25 Issue: 3
  • Publication Date: 2022
  • Doi Number: 10.1007/s11102-022-01223-1
  • Journal Name: Pituitary
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, MEDLINE
  • Page Numbers: pp.520-530
  • Keywords: Acromegaly, Microbiome, Microbiota, IGF-1, Anterior pituitary
  • Istanbul Medipol University Affiliated: Yes


Purpose: Our aim was to investigate the changes in the composition of oral and gut microbiota in patients with newly diagnosed acromegaly and their relationship with IGF-1 levels. Methods: Oral and fecal samples were collected from patients with newly diagnosed acromegaly without comorbidities and from healthy controls. The composition of the microbiota was analyzed. The general characteristics, oral and stool samples of the patients and healthy control subjects were compared. The changes in microbiota composition in both habitats, their correlations and associations with IGF-1 were statistically observed using machine learning models. Results: Fifteen patients with newly diagnosed acromegaly without comorbidities and 15 healthy controls were included in the study. There was good agreement between fecal and oral microbiota in patients with acromegaly (p = 0.03). Oral microbiota diversity was significantly increased in patients with acromegaly (p < 0.01). In the fecal microbiota, the Firmicutes/Bacteroidetes ratio was lower in patients with acromegaly than in healthy controls (p = 0.011). Application of the transfer learned model to the pattern of microbiota allowed us to identify the patients with acromegaly with perfect accuracy. Conclusions: Patients with acromegaly have their own oral and gut microbiota even if they do not have acromegaly-related complications. Moreover, the excess IGF-1 levels could be correctly predicted based on the pattern of the microbiome.