Research Paper Volume 16, Issue 8 pp 6839—6851

Age and aging process alter the gut microbes

Qu Zhanbo1,2,3, *, , Zhuang Jing1,2,3, *, , Han Shugao4, , Wu Yinhang1,2,3, , Chu Jian1,2,3, , Yu Xiang1,2,3, , Zhao Feimin1,2,3, , Liu Jian1,2,3, , Wu Xinyue1, , Wu Wei1,2,3, , Han Shuwen1,2,3, ,

  • 1 Fifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital), Huzhou 313000, Zhejiang, China
  • 2 Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou 313000, Zhejiang, China
  • 3 Key Laboratory of Multiomics Research and Clinical Transformation of Digestive Cancer, Huzhou 313000, Zhejiang, China
  • 4 The Second Hospital Affiliated to Zhejiang University School of Medicine, Hangzhou 310017, Zhejiang, China
* Equal contribution and co-first author

Received: August 15, 2023       Accepted: March 5, 2024       Published: April 8, 2024
How to Cite

Copyright: © 2024 Zhanbo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Background: Gut microbes and age are both factors that influence the development of disease. The community structure of gut microbes is affected by age.

Objective: To plot time-dependent gut microbe profiles in individuals over 45 years old and explore the correlation between age and gut microbes.

Methods: Fecal samples were collected from 510 healthy individuals over 45 years old. Shannon index, Simpson index, Ace index, etc. were used to analyze the diversity of gut microbes. The beta diversity analysis, including non-metric multidimensional scaling (NMDS), was used to analyze community distribution. Linear discriminant analysis (LDA) and random forest (RF) algorithm were used to analyze the differences of gut microbes. Trend analysis was used to plot the abundances of characteristic gut microbes in different ages.

Results: The individuals aged 45-49 had the highest richness of gut bacteria. Fifteen characteristic gut microbes, including Siphoviridae and Bifidobacterium breve, were screened by RF algorithm. The abundance of Ligiactobacillus and Microviridae were higher in individuals older than 65 years. Moreover, the abundance of Blautia_A massiliensis, Lubbockvirus and Enterocloster clostridioformis decreased with age and the abundance of Klebsiella variicola and Prevotella increased with age. The functional genes, such as human diseases and aging, were significantly different among different aged individuals.

Conclusions: The individuals in different ages have characteristic gut microbes. The changes in community structure of gut microbes may be related to age-induced diseases.


HVR: Host_virus_ratio; LDA: Linear discriminant analysis; NMDS: Non-metric multidimensional scaling; RF: Random forest; KEGG: Kyoto Encyclopedia of Genes and Genomes.