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Gut microbiome signatures distinguish type 2 diabetes mellitus from non-alcoholic fatty liver disease

Cited 13 time in Web of Science Cited 16 time in Scopus
Authors

Si, Jiyeon; Lee, Giljae; You, Hyun Ju; Joo, Sae Kyung; Lee, Dong Hyeon; Ku, Bon Jeong; Park, Seoyeon; Kim, Won; Ko, Gwang Pyo

Issue Date
2021-01
Publisher
Research Network of Computational and Structural Biotechnology
Citation
Computational and Structural Biotechnology Journal, Vol.19, pp.5920-5930
Abstract
Non-alcoholic fatty liver disease (NAFLD) is closely associated with type 2 diabetes mellitus (T2D), and these two metabolic diseases demonstrate bidirectional influences. The identification of microbiome profiles that are specific to liver injury or impaired glucose metabolism may assist understanding of the role of the gut microbiota in the relationship between NAFLD and T2D. Here, we studied a biopsy-proven Asian NAFLD cohort (n = 329; 187 participants with NAFLD, 101 with NAFLD and T2D, and 41 with neither) and identified Enterobacter, Romboutsia, and Clostridium sensu stricto as the principal taxa associated with the severity of NAFLD and T2D, whereas Ruminococcus and Megamonas were specific to NAFLD. In particular, the taxa that were associated with both severe liver pathology and T2D were also significantly associated with markers of diabetes, such as fasting blood glucose and Hb1Ac. Enterotype analysis demonstrated that participants with NAFLD had a significantly higher proportion of Bacteroides and a lower proportion of Ruminococcus than a Korean healthy twin cohort (n = 756). However, T2D could not be clearly distinguished from NAFLD. Analysis of an independent T2D cohort (n = 185) permitted us to validate the T2D-specific bacterial signature identified in the NAFLD cohort. Functional inference analysis revealed that endotoxin biosynthesis pathways were significantly enriched in participants with NAFLD and T2D, compared with those with NAFLD alone. These findings may assist with the development of effective therapeutic approaches for metabolic diseases that are associated with specific bacterial signatures. (C) 2021 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
ISSN
2001-0370
URI
https://hdl.handle.net/10371/180018
DOI
https://doi.org/10.1016/j.csbj.2021.10.032
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  • College of Human Ecology
  • Department of Food and Nutrition
Research Area Biochemistry & Molecular Biology, Food Science & Technology, Microbiology, 미생물학, 분자생물학, 식품공학

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