Risk Prediction and Personalizing Therapy to Reduce Major Vascular, Heart Failure, and Renal Events in Diabetes

Project: SFRN

Investigators

  • Marc Sabatine (PI)

Description

Patients with diabetes remain at unacceptably high risk of cardiovascular complications. Recent randomized trials have demonstrated cardiovascular clinical benefit from therapies, including certain glucose-lowering agents as well as other risk-factor modifying therapies. However, there is heterogeneity in baseline risk and magnitude of benefit.Our central hypothesis is that risk scores combining clinical variables, protein and RNA biomarkers, and genetic variants can define a robust spectrum of risk for major vascular events, hospitalization for heart failure, and progression of kidney disease, and can be used to identify subgroups of patients who derive the greatest benefit from specific therapies.We will leverage 12 large, randomized, controlled trials from the TIMI Study Group that tested therapies to reduce the risk of major vascular events, hospitalization for HF, and progression of kidney disease. These trials had 100,522 patients with diabetes who were well characterized with long-term follow-up during which 10,757 experienced MACE (CV death, MI, or ischemic stroke), 4126 were hospitalized for heart failure, and 4503 had progression of kidney disease. In addition, we have 14,335 patients with pre-diabetes, 1539 of whom converted to diabetes. A unique strength is the randomized allocation to different therapies (SGLT2i; DPP4i; lorcaserin; ezetimibe; PCSK9i; ticagrelor). In addition, biosamples (plasma, serum, DNA) available across these datasets enable us to evaluate a large population of patients with diabetes (and pre-diabetes) using omics.Specific Aims1: To develop and validate clinical risk scores to predict specific adverse events including major adverse cardiovascular events (MACE; CV death, MI, and stroke), hospitalization for heart failure, and progression of kidney disease in patients with diabetes. 2: To use "omics"-based technologies (including proteomics, transcriptomics, and genomics) to further refine the clinical risk scores developed in Aim 1. 3: To combine the clinical predictors and "omics"-derived and validated biomarkers to enable personalized strategies to prevent cardiovascular morbidity and mortality in patients with diabetes.4: To use the aforementioned approaches to analogously develop risk scores to determine which patients with pre-diabetes (a) are at highest risk to develop diabetes and (b) benefit the most from an intervention to prevent the conversion to diabetes.
Award amount$1,021,178.00
Award date01/01/2020
Program typeStrategically Focused Research Network
Award ID20SFRN35120087
Effective start/end date01/01/202012/31/2023
StatusActive