Glucocorticoids are a common medication used to treat a myriad of inflammatory and autoimmune diseases. Their clinical use is limited by multiple side effects, the most common being hyperglycemia. Hyperglycemia has been shown to negatively impact disease progression, morbidity and mortality. Approximately 50% of patients taking glucocorticoids develop hyperglycemia, suggesting heterogeneity in this disease. Further understanding of who develops hyperglycemia may allow for prevention and earlier treatment such individuals. While the molecular mechanisms underlying glucocorticoid-induced hyperglycemia are not completely defined, there is evidence that the mechanisms of this disease mirror the mechanisms underlying type 2 diabetes (T2D). Glucocorticoid-induced hyperglycemia is thought to be caused by increased insulin resistance as well as decreased beta cell function. Our preliminary data suggest that genome-wide association studies (GWAS) of diabetes and insulin-related traits are enriched for glucocorticoid genes, further confirming the overlap between these two diseases. Therefore, we hypothesize that genetic risk scores for diabetes and insulin- related traits can be used to predict glycemic response to glucocorticoids.
In Specific Aim 1, we will solidify the relationship between glucocorticoid genes and diabetes by investigating how T2D genetic variation is found in glucocorticoid genes. Specifically, we will do a gene burden test on glucocorticoid related genes to evaluate if sequence variation in glucocorticoid genes differs between subjects with and without diabetes.
In Specific Aim 2, we will use a biobank resource to identify subjects with and without glucocorticoid-induced hyperglycemia. We will then construct genetic risk scores (GRS) for diabetes and insulin-related phenotypes. We will determine if there is a relationship between these GRS and the development of glucocorticoid-induced hyperglycemia. We will then leverage the newfound information found in Aim 1 to create a GRS of T2D-associated glucocorticoid-related genes. We will use this novel GRS to compare subjects with and without glucocorticoid-induced hyperglycemia. Thus, we will examine both if glucocorticoid-related genes affect diabetes risk and if diabetes-related genes affect risk of glucocorticoid- induced hyperglycemia.
These aims reflect a carefully planned training program directed at advancing the scientific career of the applicant. Resources at the Broad Institute and the MGH Center for Human Genetic Research and the mentorship of Jose Florez, a leading expert in the field of diabetes genetics, will allow cutting-edge genomic discovery and advanced analytical approaches to be applied to investigate the genetic variants of glucocorticoid-induced hyperglycemia.
Glucocorticoids are a common medication prescribed for numerous autoimmune and inflamatory disease. Glucocorticoid-induced hyperglycemia is a disease that impacts the health of close to 50% of patients who receive these medications and is thought to have a pathophysiology similar to that of type 2 diabetes. This application focuses on applying the latest discoveries in the genetic basis of type 2 diabetes to help predict those at risk of developing this complication.
