Gut Microbiota: Critical Controller and Intervention Target in Brain Aging and Cognitive Impairment

Hui Li, Junjun Ni*, Hong Qing*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

24 Citations (Scopus)

Abstract

The current trend for the rapid growth of the global aging population poses substantial challenges for society. The human aging process has been demonstrated to be closely associated with changes in gut microbiota composition, diversity, and functional features. During the first 2 years of life, the gut microbiota undergoes dramatic changes in composition and metabolic functions as it colonizes and develops in the body. Although the gut microbiota is nearly established by the age of three, it continues to mature until adulthood, when it comprises more stable and diverse microbial species. Meanwhile, as the physiological functions of the human body deteriorated with age, which may be a result of immunosenescence and “inflammaging,” the guts of elderly people are generally characterized by an enrichment of pro-inflammatory microbes and a reduced abundance of beneficial species. The gut microbiota affects the development of the brain through a bidirectional communication system, called the brain-gut-microbiota (BGM) axis, and dysregulation of this communication is pivotal in aging-related cognitive impairment. Microbiota-targeted dietary interventions and the intake of probiotics/prebiotics can increase the abundance of beneficial species, boost host immunity, and prevent gut-related diseases. This review summarizes the age-related changes in the human gut microbiota based on recent research developments. Understanding these changes will likely facilitate the design of novel therapeutic strategies to achieve healthy aging.

Original languageEnglish
Article number671142
JournalFrontiers in Aging Neuroscience
Volume13
DOIs
Publication statusPublished - 25 Jun 2021

Keywords

  • Alzheimer’s disease
  • brain aging
  • cognitive impairment
  • diet
  • gut microbiota
  • machine learning
  • probiotics

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