Gut-microbiota in Obese Children and Adolescents: Inferred Functional Analysis and Machine-learning Algorithms to Classify Microorganisms

Research Square (Research Square)(2023)

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摘要
Abstract The fecal microbiome of 55 obese children and adolescents (BMI-SDS 3.2+/-0.7) and of 25 normal-weight subjects, matched both for age and sex (BMI-SDS -0.3+/-1.1). Streptococcus, Acidaminococcus, Sutterella, Prevotella, Sutterellawadsworthensis, Streptococcus thermophilus, and Prevotellacopri positively correlated with obesity. The inferred pathways strongly associated with obesity concern the biosynthesis pathways of tyrosine, phenylalanine, tryptophan and methionine pathways. Furthermore, polyamine biosynthesis virulence factors and pro-inflammatory lipopolysaccharide biosynthesis pathway showed higher abundances in obese samples, while the butanediol biosynthesis showed low abundance in obese subjects. Different taxa strongly linked with obesity have been related to an increased risk of multiple diseases involving metabolic pathways related to inflammation (polyamine and lipopolysaccharide biosynthesis). Cholesterol, LDL, and CRP positively correlated with specific clusters of microbial in obese patients. The Firmicutes/Bacteroidetes-ratio was lower in obese samples than in controls and differently from the literature we state that this ratio could not be a biomarker for obesity.
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obese children,inferred functional analysis,machine-learning machine-learning algorithms,machine-learning machine-learning,gut-microbiota
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