Big data shows how risk of heart disease impacts aging process

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Researchers have identified 26 different predictive biomarker signatures to help determine how well a person is aging.

A new study conducted by researchers at the Boston University Schools of Public Health and Medicine examined how levels of specific biomarkers can be combined to produce patterns to signify how well a person is aging and their risk for future aging-related diseases, including dementia and cardiovascular disease.

Biomarker data collected from 5,000 patients in the Long Life Family Study—funded by the National Institutes on Aging at the National Institutes of Health—found that half of participants had 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 medical conditions, levels of physical function, and mortality risk eight years later.

In total, 26 different predictive biomarker signatures were identified.

"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.

According to the authors the study makes a strong argument for a molecular-based definition of aging that factors in quality of life at a given age.

"Many prediction and risk scores already exist for predicting specific diseases like heart disease," Paola Sebastiani, professor of biostatistics at the BU School of Public Health, said. "Here, though, we are taking another step by showing that particular patterns of groups of biomarkers can indicate how well a person is aging and his or her risk for specific age-related syndromes and diseases."

Furthermore, the study validates the use 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 Thomas Perls, MD, MPH, professor of medicine at the BU, director of the New England Centenarian Study and one of the principal investigators of the Long Life Family Study.

Using biomarkers in this manner may speed up the research for drug and other medical interventions, Sebastiani said.