Interplay between dietary intake, gut microbiota, and metabolic profile in obese adolescents: Sex-dependent differential patterns

Yang Liu; Lei Chen; Lei Liu; Shan-Shan Zhao; Jun-Qiao You; Xin-Jie Zhao; Hui-Xin Liu; Guo-Wang Xu; De-Liang Wen

doi:10.1016/j.clnu.2022.10.009

Interplay between dietary intake, gut microbiota, and metabolic profile in obese adolescents: Sex-dependent differential patterns

Clin Nutr. 2022 Dec;41(12):2706-2719. doi: 10.1016/j.clnu.2022.10.009. Epub 2022 Oct 21.

Authors

Yang Liu¹, Lei Chen², Lei Liu¹, Shan-Shan Zhao², Jun-Qiao You¹, Xin-Jie Zhao³, Hui-Xin Liu⁴, Guo-Wang Xu⁵, De-Liang Wen⁶

Affiliations

¹ Health Sciences Institute, China Medical University, Shenyang 110122, Liaoning Province, PR China; Liaoning Key Laboratory of Obesity and Glucose/Lipid Associated Metabolic Diseases, China Medical University, Shenyang 110122, Liaoning Province, PR China.
² Health Sciences Institute, China Medical University, Shenyang 110122, Liaoning Province, PR China; Liaoning Key Laboratory of Obesity and Glucose/Lipid Associated Metabolic Diseases, China Medical University, Shenyang 110122, Liaoning Province, PR China; Institute of Life Sciences, China Medical University, Shenyang 110122, Liaoning Province, PR China.
³ CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, The Chinese Academy of Sciences, Dalian 116023, Liaoning Province, PR China. Electronic address: xj_zhao@dicp.ac.cn.
⁴ Health Sciences Institute, China Medical University, Shenyang 110122, Liaoning Province, PR China; Liaoning Key Laboratory of Obesity and Glucose/Lipid Associated Metabolic Diseases, China Medical University, Shenyang 110122, Liaoning Province, PR China; Institute of Life Sciences, China Medical University, Shenyang 110122, Liaoning Province, PR China. Electronic address: liuhx@cmu.edu.cn.
⁵ CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, The Chinese Academy of Sciences, Dalian 116023, Liaoning Province, PR China.
⁶ Health Sciences Institute, China Medical University, Shenyang 110122, Liaoning Province, PR China; Liaoning Key Laboratory of Obesity and Glucose/Lipid Associated Metabolic Diseases, China Medical University, Shenyang 110122, Liaoning Province, PR China. Electronic address: dlwen@cmu.edu.cn.

PMID: 36351362
DOI: 10.1016/j.clnu.2022.10.009

Abstract

Background & aims: The interplay among dietary intake, gut microbiota, gut metabolites and circulating metabolites in adolescents is barely known, not to mention sex-dependent pattern. We aimed to explore unique profiles of gut bacterial, gut metabolites and circulating metabolites from both genders of adolescents due to BMI and eating pattern.

Methods: Clinical indices, fecal gut microbiota, fecal and plasma metabolites, and diet intake information were collected in case-control sample matched for normal and obesity in girls (normal = 12, obesity = 12) and boys (normal = 20, obesity = 20), respectively. 16S rRNA gene sequencing and untargeted metabolomics was performed to analysis the signature of gut microbiota and metabolites. Unique profiles of girls associated with BMI and eating pattern was revealed by Spearman's correlations analysis, co-occurrence network analysis, Kruskal-Wallis test, and Wilcoxon rank-sum test.

Results: Gender difference was found between normal and obese adolescents in gut microbiota, fecal metabolites, and plasma metabolites. The Parabacteroides were only decreased in obese girls. And the characteristic of obese girls' and boys' cases in fecal and plasma was xanthine and glutamine, ornithine and LCA, respectively. Soy products intake was negatively associated with Parabacteroides. The predicted model has a higher accuracy based on the combined markers in obesity boys (AUC = 0.97) and girls (AUC = 0.97), respectively.

Conclusions: Reduced abundance of Phascolarctobacterium and Parabacteroides, as well as the increased fecal xanthine and ornithine, may provide a novel biomarker signature in obesity girls and boys. Soy products intake was positively and negatively associated with Romboutsia and Parabacteroides abundance, respectively. And the combined markers facilitate the accuracy of predicting obesity in girls and boys in advance.

Keywords: Eating patterns; Gender difference; Intervention; Metabolic syndrome; Metabolomics; Public health issue.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adolescent
Biomarkers
Eating
Feces / microbiology
Female
Gastrointestinal Microbiome* / genetics
Humans
Male
Metabolome
Ornithine
Pediatric Obesity*
RNA, Ribosomal, 16S
Xanthines

Substances

RNA, Ribosomal, 16S
Biomarkers
Ornithine
Xanthines