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Research

Researchers Identify Bile Acid and Steroid Signatures Tied to Extreme Longevity

New study points to metabolic pathways that could potentially be targeted to prevent or treat age-related conditions.

Centenarians often live to 100+ due to a combination of protective genetic factors, which account for up to 50%, and healthy lifestyles, such as plant-forward diets, regular, natural movement and strong social connections. While these “agers” often possess unique immune system signatures, understanding the metabolic signs of healthy aging is not yet fully understood.

In a new study from Boston University Chobanian & Avedisian School of Medicine, researchers have discovered that centenarians have a distinct blood metabolite pattern that is not just an extension of normal aging. In particular, they show uniquely higher levels of certain primary and secondary bile acids and preserved levels of several steroids, patterns that diverge from the typical age trends seen in non-centenarians and that are linked to lower death risk. 

“Our study points to measurable chemical fingerprints in the blood that are associated with living a very long and healthy life. If we can understand those fingerprints, we may identify biological pathways that could contribute to protecting people from age-related decline,” explains corresponding author Stefano Monti, PhD, professor of medicine at the school.

The researchers collected blood samples from 213 people (70 centenarians, their children (offspring), and age-matched controls) from the New England Centenarian Study, one of the largest studies of long-lived individuals in North America led by Thomas Perls, MD, professor of medicine at the school. Using an untargeted metabolomics assay, they measured levels of approximately 1,495 small molecules in serum. They then compared metabolite levels between centenarians, offspring, and controls, and looked for metabolites that change with chronological age. They compared their results with four other metabolomics studies (some that included long-lived people and some that did not) to see which signals were consistent. They also checked which metabolites or groups of metabolites predicted how long people lived after the blood draw (survival analysis). Finally, they trained a machine-learning model “metabolomic clock”) to predict biological age from metabolite levels and tested whether being biologically younger or older than your calendar age relates to survival.

According to the researchers, the identified metabolites and patterns could become biomarkers to estimate someone’s biological age, to identify people at higher or lower risk of age-related decline, or to monitor responses to lifestyle or drug interventions aimed at improving health with age. They believe some specific pathways (bile acids, NAD-related pathways, gut bacterial metabolites, oxidative stress markers and certain steroids) warrant further investigation as potential targets for therapies or dietary interventions in the future.

“We hope this study helps point to measurable metabolic signs of healthy aging that can be tracked and targeted. However, the study’s cross-sectional design means we cannot yet determine cause and effect, and these findings need validation in larger, diverse populations. Ultimately, our goal is to translate these insights into tests and safe interventions that help people stay healthier and more active for longer,” adds Monti.

These findings appear online in the journal GeroScience.