Around the world, the prevalence of type 2 diabetes mellitus (T2DM) has been increasing since the last two decades, with approximately 347 million patients with diabetes by 2013 according to the World Health Organization (WHO). This pronounced increase is due to an increase in the prevalence of obesity, reduction in physical activity levels, accelerated urbanization and aging of the population. In Colombia, T2DM ranks fifth in the main morbidity and mortality causes, including only deaths caused directly and without adding the strong influence that T2DM has on cardiovascular disease mortality.
Insufficient tissue response to normal insulin concentrations, called insulin resistance, is one of the central pathophysiological mechanisms in the development of T2DM. However, there is currently no simple, practical, safe and reproducible method that allows the diagnosis or identification of insulin resistance, nor the follow-up to its evolution. At the moment, the gold standard for assessing the degree of insulin sensitivity or resistance is the "hyperinsulinemic-euglycemic clamp", a laborious technique, of high cost and high technical difficulty, requiring specialized personnel and hospitalization. Non-invasive methods based on mathematical regressions, such as the Homeostatic Model Assessment (HOMA-IR), are imperfect and widely variable, and have not been validated in the Latin American population, less Still Colombian.
Therefore, the development of new, easily obtainable quantitative tools for the diagnosis of insulin resistance is required. This requires not only the identification of new and better biomarkers, but also the determination of their diagnostic performance and operational characteristics.
This project will investigate 3 molecular targets (myokines), novel and easy to measure, with high probability of being good biomarkers of insulin resistance. The research will include validation of its association with insulin resistance measured by the reference method, as well as its measurement in apparently healthy individuals. Finally, operator-receiver characteristics of each test will be analyzed, in order to propose a cutoff point for the diagnosis of insulin resistance.