“To test whether these signatures were associated with differences in biological aging, we correlated them with longitudinal changes in physiological functions and incident risk of cancer, cardiovascular disease, type 2 diabetes, and mortality using longitudinal data collected in the LLFS,” the authors explained. “Signature 2 was 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.”
Dr. Sebastiani pointed out that the analytic methods used in the current study could make studies of drug and other medical interventions to prevent or delay age-related diseases much more plausible, since clinical trials #8220;may not have to wait years and years for clinical outcomes to occur.#8221; Instead, trials may be able to rely on biomarker signatures much earlier #8220;to detect the effects, or absence of effects, that they are searching for.#8221;
The authors noted that the predictive values of seven signatures were replicated in an independent dataset from the Framingham Heart Study, which showed comparable significant effects, and an additional three signatures showed consistent effects. The authors also indicated that their analysis #8220;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,#8221; adding that further research is needed to better characterize the signatures.
Drs. Sebastiani and Perls said that researchers are just beginning to break ground on the usefulness of biomarker signatures. #8220;Following all the recent advances in genetics, the science of proteomics and metabolomics is the next big revolution in predictive medicine and drug discovery,#8221; Dr. Perls predicted.