Multi-omics Analysis Identify Novel Microbiome-Metabolome Signatures Associated with Obesity

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ID: 320451
2026
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Abstract
Abstract Aims Explore the potential microbiome and serum metabolome factors and their interactions associated with obesity. Methods and Results We performed a systematic multi-omics analysis using paired metagenomic and metabolomic profiles-including untargeted serum metabolomics, lipidomics, and short-chain fatty acids (SCFAs) with body mass index (BMI) from a cohort of 495 US men. Single omics analysis identified 52 gut bacteria species and 31 serum metabolites for potential associations with BMI. Among the identified bacteria, Collinsella stercoris (C.stercoris) (Coef.=-0.147, P=0.015) was negatively associated, whereas Bacteroides fragilis (B.fragilis) (Coef.=0.294, P=1.22E-04) and Veillonella dispar (V.dispar) (Coef.=0.135, P=0.001) were positively associated, these results were further validated by an independent Chinese cohort. Several of the identified metabolites including gamma-glutamylglycine (Coef.=-0.713, P=4.53E-06), asparagine (Coef.=-0.629, P=3.53E-05), glycine (Coef.=-0.952, P=5.28E-09) and serotonin (Coef.=0.566, P=1.78E-04) were associated with these significant bacteria (P<0.05). Conclusion This multi-omics study identifies key gut bacteria and serum metabolites that interact to associate with host obesity, providing systemic insight into microbiome-host metabolic interactions.
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Authors Bo Tian, Liu Y, Kuan-Jui Su, Lindong Jiang, Xu Lin, Chuan Qiu, Zhe Luo, Qing Tian, Jie Shen, Hui Shen, Li-Shu Zhang, Hong‐Mei Xiao, Hong‐Wen Deng
Journal Journal of applied microbiology
Year 2026
DOI
10.1093/jambio/lxag172
URL
https://doi.org/10.1093/jambio/lxag172
Keywords Keywords not found

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