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Sci Rep. 2018 Oct 18;8(1):15451. doi: 10.1038/s41598-018-33571-z.

Evaluation of different mucosal microbiota leads to gut microbiota-based prediction of type 1 diabetes in NOD mice.

Author information

1
Section of Endocrinology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, 06510, USA.
2
Yale Center for Analytical Sciences, Yale University School of Public Health, New Haven, CT, 06510, USA.
3
Division of Infection and Immunity, School of Medicine, Cardiff University, Cardiff, UK. wongfs@cardiff.ac.uk.
4
Section of Endocrinology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, 06510, USA. li.wen@yale.edu.

Abstract

Type 1 diabetes (T1D) is a progressive autoimmune disease in which the insulin-producing beta cells are destroyed by auto-reactive T cells. Recent studies suggest that microbiota are closely associated with disease development. We studied gut, oral and vaginal microbiota longitudinally in non-obese diabetic (NOD) mice. We showed that the composition of microbiota is very different at the different mucosal sites and between young and adult mice. Gut microbiota are more diverse than oral or vaginal microbiota and the changes were more evident in the mice before and after onset of diabetes. Using alpha-diversity, Gram-positive/Gram-negative ratio as well as the relative abundance of Bacteroidetes and Erysipelotrichaceae in the gut microbiota, at 8 weeks of age, we formulated a predictive algorithm for T1D development in a cohort of 63 female NOD mice. Using this algorithm, we obtained 80% accuracy of prediction of diabetes onset, in two independent experiments, totaling 29 mice, with Area Under the Curve of 0.776 by ROC analysis. Interestingly, we did not find differences in peripheral blood mononuclear cells of the mice at 8 weeks of age, regardless of later diabetes development. Our results suggest that the algorithm could potentially be used in early prediction of future T1D development.

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