Background: Aging can impair the ability of elderly individuals to fight infections and trigger persistent systemic inflammation, a condition known as inflammaging. However, the mechanisms underlying the development of inflammaging remain unknown.
Methods: We conducted 16S rRNA sequencing of intestinal contents from young and old C57BL/6J mice to elucidate changes in gut microbiota diversity and microbial community composition after aging. Aging-related differential bacterial taxa were then identified, and their abundance trends were validated in human samples. The variances in intestinal barrier function and circulating endotoxin between groups were also assessed. Furthermore, widely targeted metabolomics was conducted to characterize metabolic profiles after aging and to investigate the key metabolic pathways enriched by the differential metabolites.
Results: Our findings demonstrated an increase in relative proportion of pathogenic bacteria with age, a trend also revealed in healthy populations of different age groups. Additionally, aging individuals exhibited reduced intestinal barrier function and increased circulating endotoxin levels. Widely targeted metabolomics revealed a significant increase in various secondary bile acid metabolites after aging, positively correlated with the relative abundance of several aging-related bacterial taxa. Furthermore, old group had lower levels of various anti-inflammatory or beneficial metabolites. Enrichment analysis identified the starch and sucrose metabolism pathway as potentially the most significantly impacted signaling pathway during aging.
Conclusion: This study aimed to provide insights into the complex interactions involved in organismal inflammaging through microbial multi-omics. These findings lay a solid foundation for future research aimed at identifying novel biomarkers for the clinical diagnosis of aging-related diseases or potential therapeutic targets.
Keywords: aging; gut microbiota; inflammaging; intestinal epithelial cells; metabolism.
Copyright © 2024 Chen, Wang, Zou, Li, Yang, Su and Mo.