Metabolic profiling in personalized medicine: bridging the gap between knowledge and clinical practice in Type 2 diabetes

Abstract

Type 2 diabetes mellitus (DM2) is the most commonly diagnosed metabolic disease and its prevalence is expected to increase. Epidemiological studies clearly show excess mortality associated with DM2, as well as an increased risk of DM2-related complications. Advances in personalized medicine would greatly improve patient care in the field of diabetes and other metabolic diseases. Prediction of the disease in asymptomatic patients as well as its harsh complications in patients already diagnosed is becoming a necessity, with the considerable increase in the cost of the treatment. In the current article, we review the known clinical, molecular metabolic and genetic biomarkers that should be integrated in a future bioinformatic platform to be used at the point-of-care, and discuss the challenges we face in applying this vision of personalized medicine for diabetes into reality.