Mammalian gut microbiomes are highly dynamic communities that shape and are shaped by host aging, including age-related changes to host immunity, metabolism, and behavior. As such, gut microbial composition may provide valuable information on host biological age. Here, we test this idea by creating a microbiome-based age predictor using 13,563 gut microbial profiles from 479 wild baboons collected over 14 years. The resulting 'microbiome clock' predicts host chronological age. Deviations from the clock's predictions are linked to some demographic and socio-environmental factors that predict baboon health and survival: animals who appear old-for-age tend to be male, sampled in the dry season (for females), and have high social status (both sexes). However, an individual's 'microbiome age' does not predict the attainment of developmental milestones or lifespan. Hence, in our host population, gut microbiome age largely reflects current, as opposed to past, social and environmental conditions, and does not predict the pace of host development or host mortality risk. We add to a growing understanding of how age is reflected in different host phenotypes and what forces modify biological age in primates.
Keywords: Papio cynocephalus; age; aging clock; evolutionary biology; machine learning; mammalian gut microbiome.
As we age, our bodies undergo a variety of physical changes. However, the pace at which these changes occur (known as our biological age) often does not reflect the number of years we’ve lived (known as our chronological age). Various markers have been proposed to predict biological age, including the composition of bacteria living in the gut. Which bacterial species reside in the gut is influenced by multiple factors, such as diet, living conditions and social interactions. This makes the microbiome unique to each individual, and potentially a rich indicator of age-related processes. To explore this idea, Dasari et al. studied a large dataset containing thousands of gut microbiome samples from almost 500 wild baboons, collected over 14 years. Several machine learning algorithms were applied to the data to estimate the ‘microbiome age’ of each individual. Dasari et al. found that these estimates correlated well with the baboons’ chronological ages, and mirrored known patterns of biological aging, such as male baboons aging faster than females. Environmental and social factors – such as a baboon’s social rank within a group – also influenced the relationship between chronological and biological age. During the dry season, for instance, female baboons had a higher microbiome age compared to their actual age, and baboons with low social status had a lower microbiome age than expected. Although life expectancy has steadily increased over the last century, our healthspan (the period of life spent in good health) has not kept pace with it. Understanding how our bodies age is key to prolonging healthspan. The findings of Dasari et al. suggest that the gut microbiome is a good predictor of biological age, and future work investigating this relationship could provide valuable clues for slowing down the aging process.
© 2024, Dasari et al.