Platelet systems biology using integrated genetic and proteomic platforms

Abstract Platelets retain megakaryocyte-derived mRNA, an abundant and diverse array of miRNAs, and have evolved unique adaptive signals for maintenance of genetic and protein diversity. Quiescent platelets generally display minimal translational activity, although maximally-activated platelets retain the capacity for protein synthesis. Progressive data using multiple platelet activation models clearly demonstrate that platelet responses to the majority (if not all) agonists are highly variable within the population, demonstrating considerable heritability in siblings, twins, and families with premature coronary artery disease. Research from our laboratory has adapted global profiling strategies to close the knowledge gap currently existing between genetic variability and platelet phenotypic responsiveness. We have applied iterative algorithms for genetic biomarker discovery and class prediction models of platelet phenotypes, with the goal of systematically analyzing integrated mRNA/miRNA/proteomic datasets for identification of regulatory networks that define phenotypic variability in platelet responses. This approach has the potential to define platelet genetic biomarkers predictive of thrombohemorrhagic outcomes in both normal and widely disparate clinical conditions.