Revolutionizing Aging Science: Microbiome-Based Aging Clock Clarified
Copyright © 2020 Fedor Galkin et al. Open access article under the CC BY-NC-ND license.
Researchers from China, the UK, and the USA collaborated on a groundbreaking study published in the iScience Journal, introducing a pioneering concept for an aging clock rooted in microbiomic data. Deep Neural Networks (DNN) emerged as the most effective algorithm for age prediction, exhibiting a mean absolute error (MAE) of 10.60 years in cross-validation and 5.91 years in independent testing—outperforming the baseline median age assignment. The study revealed that Elastic Net (EN) proved unsuitable for predicting intestinal age.
A notable discovery was that all models predicted higher ages for younger donors with Type 1 Diabetes (T1D), indicating potential microbiome alterations linked to the disease. The researchers theorize that diabetes might accelerate aging through gut microbiome mechanisms.
While the primary function of the aging clock is to gauge biological time, it also provides insights into the aging process. Leveraging Accumulated Local Effects (ALE), the study identified gut microbes associated with aging. However, ALE results varied based on dataset structure and model implementation.
Specific gut microbes, such as Bacteroides and Bifidobacterium, exerted significant effects on age prediction. The study underscored the importance of Akkermansia muciniphila, associated with healthy aging, and butyrate-producing bacteria, which could influence aging.
The study observed poorly described bacteria in the human gut, possibly attributed to batch effects or offering new insights into intestinal aging. Further research with larger datasets and consideration of various variables is recommended.
The findings highlight the accuracy of microbiome profiles in predicting age for healthy individuals and signify accelerated aging in T1D patients. This breakthrough could pave the way for new aging biomarkers and applications, such as intestinal rejuvenation through dietary interventions, pending a more profound understanding of gut community dynamics and metabolism.