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Association of Human Intestinal Microbiota with Lifestyle Activity, Adiposity, and Metabolic Profiles in Thai Children with Obesity
BACKGROUND: Dysbiosis of intestinal microbiota may be linked to pathogenesis of obesity and metabolic disorders. OBJECTIVE: This study compared the gut microbiome of obese Thai children with that of healthy controls and examined their relationships with host lifestyle, adiposity, and metabolic profi...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9146442/ https://www.ncbi.nlm.nih.gov/pubmed/35637874 http://dx.doi.org/10.1155/2022/3029582 |
Sumario: | BACKGROUND: Dysbiosis of intestinal microbiota may be linked to pathogenesis of obesity and metabolic disorders. OBJECTIVE: This study compared the gut microbiome of obese Thai children with that of healthy controls and examined their relationships with host lifestyle, adiposity, and metabolic profiles. METHODS: This cross-sectional study enrolled obese children aged 7–15. Body composition was evaluated using bioelectrical impedance analysis. Stool samples were analyzed by 16S rRNA sequencing using the Illumina MiSeq platform. Relative abundance and alpha- and beta-diversity were compared with normal-weight Thai children from a previous publication using Wilcoxon rank-sum test and ANOSIM. Relationships of gut microbiota with lifestyle activity, body composition, and metabolic profiles were assessed by canonical correlation analysis (CCA) and Spearman correlation. RESULTS: The study enrolled 164 obese children with a male percentage of 59%. Mean age was 10.4 ± 2.2 years with a BMI z-score of 3.2 ± 1. The abundance of Bacteroidetes and Actinobacteria were found to be lower in obese children compared to nonobese children. Alpha-diversity indices showed no differences between groups, while beta-diversity revealed significant differences in the family and genus levels. CCA revealed significant correlations of the relative abundance of gut microbial phyla with sedentary lifestyle and certain metabolic markers. Univariate analysis revealed that Actinobacteria and Bifidobacterium were positively correlated with HDL-C and negatively correlated with body weight and screen time. Additionally, Actinobacteria was also negatively associated with fasting insulin and HOMA-IR. Lactobacillus showed positive correlation with acanthosis nigricans and adiposity. Cooccurrence analysis revealed 90 significant bacterial copresence and mutual exclusion interactions among 43 genera in obese children, whereas only 2 significant cooccurrences were found in nonobese children. CONCLUSIONS: The composition and diversity of gut microbiota in obese Thai children were different from those of their normal-weight peers. Specific gut microbiota were associated with lifestyle, adiposity, and metabolic features in obese children. An interventional study is needed to support causality between specific gut microbiota and obesity. |
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