Building Extracellular Vesicle-Based Aging Clocks

Abstract

Chronological age refers to years an individual has been alive, whereas biological age reflects health and is influenced by genetics, lifestyle, and environment. Biological age can better predict health status. First-generation biological clocks relied on DNA methylation, whereas second-generation clocks incorporate methylation and biomarkers. For example, the DNAmFitAge (AgeAccelFit) clock considers blood-based biomarkers, DNA methylation, and fitness measures such as walking speed, lung function, and grip strength. This clock showed that extracellular vesicles (EVs) were associated with biological age, suggesting their potential as biomarkers. EVs are nanoparticles that facilitate cellular communication and contain protein cargo that changes over time and across disease states. We hypothesize that EVs could be used to construct an EV-based aging clock.  To construct an EV-based clock, training was obtained to be able to enrich for EVs from human plasma samples. Repeated EV isolations were performed using iodixanol density cushion (IDC) and size-exclusion chromatography (SEC). These techniques allowed for the separation of EVs from contaminating lipoproteins and particles of similar sizes. Quantitation of particles and protein were completed using the Zetaview Particle Matrix and Qubit fluorimeter respectively. Examining individual fractions allowed for the confirmation of EVs samples with minimum protein contamination. Isolations and analyses were completed on varying quantities of plasma to optimize EV collection from small volumes. We recruited over 40 human subjects that ranged from 22-80 years of ages and plan to complete EV isolation from these precious samples. Overall, continuation of this work has the potential to use EVs as an estimator for biological age and provide a novel health determinant indicator. Supervisor: Dr. Sheela Abraham