Integrated metagenome and metabolome analyses of blood pressure studies in early postmenopausal Chinese women

Objective: We carried out sensitivity analyses on gut microbiota metagenomic sequencing, untargeted metabolome, targeted metabolome for short-chain fatty acids (SCFAs) and human whole genome sequencing from 402 early postmenopausal Chinese women to search for early omics-biomarkers and gain novel insights into the potential mechanisms of BP regulation in postmenopausal women.

Methods: Clusters of co-abundant gut bacterial species and serum untargeted metabolites were identified by weighted gene co-expression network analysis (WGCNA). Partial least square analysis and joint analysis were performed to detect BP-associated omics-variables. Partial Pearson correlation was conducted to identify the interactions of microbe--host for host BP variation. Mendelian randomization analysis and causal inference test were used to examine causal relationships among gut microbiota, metabolites and BP variation.

Results: In the present study, 651 bacterial species and 296 metabolites were binned into 53 and 26 co-abundance clusters by WGCNA, respectively. Then, we totally identified four gut bacterial species, one host metabolites and two SCFAs that were significantly associated with both SBP and DBP. Moreover, we found that gut microbiota would play important roles in host metabolic activity. Finally, our results revealed that increased Bacteroides fragilis could elevate BP via decreased caproic acid, and phenylacetylglutamine mediated the causal relationships of both B. fragilis and Clostridium sp.CAG.226 on DBP variation.

Conclusion: Multi-omics datasets integration has the potential to capture complementary effect and their interactions for BP variation, revealed the potential pathogenesis of BP variation and may be useful for studying other complex diseases/traits.