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Comparative analysis of gut microbiota associated with body mass index in a large Korean cohort

Title
Comparative analysis of gut microbiota associated with body mass index in a large Korean cohort
Authors
Yun Y.Kim H.-N.Kim S.E.Heo S.G.Chang Y.Ryu S.Shin H.Kim H.-L.
Ewha Authors
김형래김한나윤여준
SCOPUS Author ID
김형래scopusscopusscopus; 김한나scopusscopus; 윤여준scopus
Issue Date
2017
Journal Title
BMC Microbiology
ISSN
1471-2180JCR Link
Citation
BMC Microbiology vol. 17, no. 1
Keywords
Body mass index (BMI)Gut microbiotaObesity
Publisher
BioMed Central Ltd.
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
Background: Gut microbiota plays an important role in the harvesting, storage, and expenditure of energy obtained from one's diet. Our cross-sectional study aimed to identify differences in gut microbiota according to body mass index (BMI) in a Korean population. 16S rRNA gene sequence data from 1463 subjects were categorized by BMI into normal, overweight, and obese groups. Fecal microbiotas were compared to determine differences in diversity and functional inference analysis related with BMI. The correlation between genus-level microbiota and BMI was tested using zero-inflated Gaussian mixture models, with or without covariate adjustment of nutrient intake. Results: We confirmed differences between 16Sr RNA gene sequencing data of each BMI group, with decreasing diversity in the obese compared with the normal group. According to analysis of inferred metagenomic functional content using PICRUSt algorithm, a highly significant discrepancy in metabolism and immune functions (P < 0.0001) was predicted in the obese group. Differential taxonomic components in each BMI group were greatly affected by nutrient adjustment, whereas signature bacteria were not influenced by nutrients in the obese compared with the overweight group. Conclusions: We found highly significant statistical differences between normal, overweight and obese groups using a large sample size with or without diet confounding factors. Our informative dataset sheds light on the epidemiological study on population microbiome. © 2017 The Author(s).
DOI
10.1186/s12866-017-1052-0
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의과대학 > 의학과 > Journal papers
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