Biomarker Signatures Predict Aging Health Quality

To establish these signatures, investigators at Boston University measured 19 blood biomarkers that included constituents of standard hematological measures, lipid biomarkers, and markers of inflammation and frailty in 4704 participants of the Long Life Family Study (LLFS). The biomarkers were selected based upon their noted quantitative change with age and specificity for inflammatory, hematological, metabolic, hormonal, or kidney functions.

The LLFS is a family-based study that enrolled 4935 participants including subjects and siblings (30%), their offspring (50%), and spouses (20%), with ages between 30 and 110 years. Approximately 40% of enrolled participants were born before 1935 and had a median age at enrollment of 90 years and 45% participants were male. Almost 55% of participants from the subject generation (birth year prior to 1935) have died since enrollment, with a median age at death of 96 years. Mortality in the generation born after 1935 is lower (3%) and among these few that have died, median age at death is currently 69 years.

The investigators used an agglomerative algorithm to analyze distribution of the 19 biomarkers and then grouped LLFS participants into clusters that yielded 26 different biomarker signatures.

To test whether these signatures were associated with differences in biological aging, the investigators correlated them with longitudinal changes in physiological functions and incident risk of cancer, cardiovascular disease, type II diabetes, and mortality using longitudinal data collected in the LLFS. One signature was found to be associated with significantly lower mortality, morbidity, and better physical function relative to the most common biomarker signature in LLFS, while nine other signatures were associated with less successful aging, characterized by higher risks for frailty, morbidity, and mortality.

"Many prediction and risk scores already exist for predicting specific diseases like heart disease," said first author Dr. Paola Sebastiani, professor of biostatistics at Boston University. "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. 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 II diabetes, and cancer."

The study was published in the January 6, 2017, online edition of the journal Aging Cell.