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Journal of applied microbiology · 2026

Multi-omics analysis identify novel microbiome-metabolome signatures associated with obesity.

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Tian Bo, Liu Yong, Su Kuan-Jui, Jiang Lin-Dong, Lin Xu, Qiu Chuan, Luo Zhe, Tian Qing, Shen Jie, Shen Hui, Zhang Li-Shu, Xiao Hong-Mei, Deng Hong-Wen

Аннотация

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.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты