Paola Sebastiani, Bharat Thyagarajan, Fangui Sun, Nicole Schupf, Anne B. Newman, Monty Montano, Thomas T. Perls. Biomarker signatures of aging. Aging Cell, 2017; DOI: 10.1111/acel.12557
Levels of specific biomarkers can be combined to produce patterns that signify how well a person is aging and his or risk for future aging-related diseases, according to a new study by researchers at the Boston University Schools of Public Health and Medicine and Boston Medical Center. The study used biomarker data collected from the blood samples of almost 5,000 participants in the Long Life Family Study, funded by the National Institute on Aging (NIA) at the National Institutes of Health (NIH).
A large number – about half – had an average “signature,” or pattern, of 19 biomarkers. But smaller groups of people had specific patterns of those biomarkers that deviated from the norm and that were associated with increased probabilities of association with particular medical conditions, levels of physical function, and mortality risk 8 years later. Eg, one pattern was associated with disease-free aging, another with dementia, and another with disability-free aging in the presence of cardiovascular disease.
In all, they generated 26 different predictive biomarker signatures. Instances where similar biomarker data were available from the long-running Framingham Heart Study allowed for about 1/3 of the signatures to be replicated. “These signatures depict differences in how people age, and they show promise in predicting healthy aging, changes in cognitive and physical function, survival and age-related diseases like heart disease, stroke, type 2 diabetes and cancer,” the authors said. Their analysis “sets the stage for a molecular-based definition of aging that leverages information from multiple circulating biomarkers to generate signatures associated with different mortality and morbidity risk,” adding that further research is needed to better characterize the signatures.
Prof. Perls said the study is an example of the usefulness of “big data” and the emerging research fields of proteomics and metabolomics. “We can now detect and measure thousands of biomarkers from a small amount of blood, with the idea of eventually being able to predict who is at risk of a wide range of diseases – long before any clinical signs become apparent,” said Perls, who also is affiliated with Boston Medical Center.
The analytic methods used make studies of drug and other medical interventions to prevent or delay age-related diseases much more plausible, since clinical trials “may not have to wait years and years for clinical outcomes to occur.” Instead, trials may be able to rely on biomarker signatures much earlier “to detect the effects, or absence of effects, that they are searching for,” she said. “Following all the recent advances in genetics, the science of proteomics and metabolomics is the next big revolution in predictive medicine and drug discovery,” Perls said. https://www.bu.edu/sph/2017/01/06/patterns-of-biomarkers-predict-how-well-people-age-risks-of-age-related-disease/ http://onlinelibrary.wiley.com/doi/10.1111/acel.12557/abstract
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