Metabolic Syndrome and Personalized medicine: Success and Challenges

Metabolic syndrome (MetS) is one of the most important health issues around the world and a major risk factor for both type 2 diabetes and cardiovascular diseases. The etiology of MetS is determined by the interaction between genetic and environmental factors. Effective prevention and treatment of MetS notably decreases the risk of its complications such as diabetes, obesity, hypertension, and dyslipidemia. According to recent genome-wide association studies, multiple genes are involved in the incidence and development of MetS. The presence of particular genes, such as those causing monogenic obesity, regulating free fatty acid metabolism, and affecting insulin sensitivity and lipid metabolism, as well as those associated with inflammation, can increase the risk of MetS. Better understanding of gene-gene, gene-nutrient, and gene-nutrient-environment interactions can explain the molecular basis of MetS. These molecular markers, together with clinical data and findings from proteomic, metabolomic, pharmacokinetic, and other methods, would clarify the etiology and pathophysiology of MetS and facilitate the development of personalized approaches to the management of MetS. The application of personalized medicine based on susceptible genome would help physicians recommend healthier lifestyle and prescribe medications to improve various aspects of health in patients with MetS. In recent years, personalized medicine by genetic testing has helped physicians determine genetic predisposition to MetS prevent the disease by behavioral, lifestyle-related, or therapeutic interventions, and detect, diagnose, treat, and manage the disease. Apparently, personalized medicine is providing effective strategies for the prevention and treatment of Mets by reducing the time, cost, and failure rate of pharmaceutical clinical trials. It is also eliminating trial-and-error inefficiencies that inflate health care costs and undermine patient care.

کلیدواژه ها:

Metabolic Syndrome ، Personalized medicine ، Pharmacogenomics