The biomarker data in Aging Cell article was 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). The researchers found that a large number of people--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 eight years later.
For example, 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, the researchers generated 26 different predictive biomarker signatures. Instances where similar biomarker data were available from the long-running Framingham Heart Study allowed for about one-third 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. They indicated that 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.
The study is an example of the usefulness of big data and the less-rigorous fields of proteomics and metabolomics, and may lead to being able to predict who is at risk of a wide range of diseases -- long before any clinical signs become apparent. The analytic methods used in the research 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."