Predictive, Preventive, Participatory, and Personalized Health

Introduction to Personalized Medicine in Diabetes Mellitus

Harry S. Glauber, Naphtali Rishe, and Eddy Karnieli


The world is facing an epidemic rise in diabetes mellitus (DM) incidence, which is challenging health funders, health systems, clinicians, and patients to understand and respond to a flood of research and knowledge. Evidence-based guidelines provide uniform management recommendations for “average” patients that rarely take into account individual variation in susceptibility to DM, to its complications, and responses to pharmacological and lifestyle interventions. Personalized medicine combines bioinformatics with genomic, proteomic, metabolomic, pharmacogenomic (“omics”) and other new technologies to explore pathophysiology and to characterize more precisely an individual’s risk for disease, as well as response to interventions. In this review we will introduce readers to personalized medicine as applied to DM, in particular the use of clinical, genetic, metabolic, and other markers of risk for DM and its chronic microvascular and macrovascular complications, as well as insights into variations in response to and tolerance of commonly used medications, dietary changes, and exercise. These advances in “omic” information and techniques also provide clues to potential pathophysiological mechanisms underlying DM and its complications.

Rambam Maimonides Med J 2014;5(1):e0002