Gut Microbiota and Serum Metabolites in Individuals with Class III Obesity Without Type 2 Diabetes Mellitus: Pilot Analysis

被引:2
|
作者
Kubanova, Libusa [1 ,2 ]
Bielik, Viktor [1 ]
Hric, Ivan [2 ,3 ]
Ugrayova, Simona [1 ]
Soltys, Katarina [4 ,5 ]
Radikova, Zofia [2 ]
Baranovicova, Eva [6 ]
Grendar, Marian [6 ]
Kolisek, Martin [6 ]
Penesova, Adela [2 ]
机构
[1] Comenius Univ, Fac Phys Educ & Sport, Dept Biol & Med Sci, Bratislava 81469, Slovakia
[2] Slovak Acad Sci, Inst Clin & Translat Res, Biomed Ctr, Bratislava, Slovakia
[3] Comenius Univ, Fac Nat Sci, Dept Mol Biol, Bratislava, Slovakia
[4] Comenius Univ, Fac Nat Sci, Dept Microbiol & Virol, Bratislava, Slovakia
[5] Comenius Univ, Comenius Univ Sci Pk, Bratislava, Slovakia
[6] Comenius Univ, Jessenius Fac Med Martin, Biomed Ctr Martin, Martin, Slovakia
关键词
gut microbiome; class III obesity; energy metabolites; type 2 diabetes mellitus; prediabetes; CHAIN FATTY-ACIDS; AKKERMANSIA-MUCINIPHILA; COLORECTAL-CANCER; DIET; BUTYRATE; ACETATE; GLUCOSE; BACTERIA; CITRATE;
D O I
10.1089/met.2022.0071
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Background: Gut microbial composition seems to change in association with prediabetes. The purpose of this prospective cross-sectional study was to compare the composition of gut microbiota and energy metabolites between individuals with class III obesity but without type 2 diabetes mellitus (OB) and healthy normal weight controls. Methods: The subjects of this prospective cross-sectional study were participants recruited from a previous clinical trial (No: NCT02325804), with intervention focused on weight loss. We recruited 19 OB [mean age +/- standard deviation (SD) was 35.4 +/- 7.0 years, mean body mass index (BMI) +/- SD was 48.8 +/- 6.7 kg/m(2)] and 23 controls (mean age +/- SD was 31.7 +/- 14.8 years, mean BMI +/- SD was 22.2 +/- 1.7 kg/m(2)). Their fecal microbiota was categorized using specific primers targeting the V1-V3 region of 16S rDNA, whereas serum metabolites were characterized by nuclear magnetic resonance spectroscopy. Multivariate statistical analysis and Random Forest models were applied to discriminate predictors with the highest variable importance. Results: We observed a significantly lower microbial alpha-diversity (P = 0.001) and relative abundance of beneficial bacterium Akkermansia (P = 0.001) and the short-chain fatty acid-producing bacteria Eubacterium hallii (P = 0.019), Butyrivibrio (P = 0.024), Marvinbryantia (P = 0.010), and Coprococcus (P = 0.050) and a higher abundance of the pathogenic bacteria Bilophila (P = 0.018) and Fusobacterium (P = 0.022) in OB compared with controls. Notably, the Random Forest machine learning analysis identified energy metabolites (citrate and acetate), HOMA-IR, and insulin as important predictors capable of discriminating between OB and controls. Conclusions: Our results suggest that changes in gut microbiota and in serum acetate and citrate are additional promising biomarkers before progression to Type 2 diabetes. The non-invasive manipulation of gut microbiota composition in OB through a healthy lifestyle, thus, offers a new approach for managing class III obesity and associated disorders. ClinicalTrials.gov identifier: NCT02325804
引用
收藏
页码:243 / 253
页数:11
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