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Updated: Jul 12, 2026

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
Published on: May 6, 2022
Multi-omics analysis identify novel microbiome-metabolome signatures associated with obesity
Bo Tian1, Yong Liu1, Kuan-Jui Su2
1Center for System Biology, Data Sciences, and Reproductive Health, School of Basic Medical Science, Central South University, 172 Tongzipo Road, Yuelu District, Changsha 410013, Hunan Province, China.
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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