Published in:
01-12-2020 | Respiratory Microbiota | Research article
Intestinal Microbiota Composition in Iranian Diabetic, Pre-diabetic and Healthy Individuals
Published in: Journal of Diabetes & Metabolic Disorders | Issue 2/2020
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Background
Type 2 diabetes, as the most prevalent metabolic disorder, is one of the leading causes of death worldwide. Recent studies showed a significant association between intestinal microbiota and type 2 diabetes. These studies have shared evidences that alteration in the composition of intestinal microbiota can disrupt the balance of the host homeostasis and lead to metabolic disorders such as type 2 diabetes. In the present study, we compared the intestinal microbiota composition in three groups of type 2 diabetes patients, pre-diabetic patients and healthy individuals of Iranian population.
Methods
After obtaining informed consent, stool samples were collected from 90 individuals of three studied groups. The DNA was extracted using column-based method. Intestinal microbiota composition was evaluated by quantitative real-time PCR using specific bacterial 16S rRNA primers. The difference of bacterial load was compared between three groups.
Results
The prevalence of Akkermansia muciniphila and Bifidobacteria species in healthy group was higher than type 2 diabetes group (P Value 0.006 and 0.001, respectively). In contrast, the load of Lactobacillus (P Value 0.044), Escherichia coli (P Value 0.005), and Bacteroides fragilis (P Value 0.017) in type 2 diabetes group, and the frequency of E. coli (P Value 0.001) and Bacteroides fragilis (P Value 0.004) in pre-diabetic group was significantly higher than healthy group. Moreover, the frequency of Faecalibacterium prausnitzii in healthy group was significantly higher compared to two other groups (P Value 0.005).
Conclusion
There is a correlation between intestinal microbiota composition and type 2 diabetes. Determination and restoration of this microbiota composition pattern may have a possible role in prevention and control of type 2 diabetes in a certain population.