Millions of individuals world-wide use aspirin for cardioprotection yet clinicians currently lack a reliable tool to accurately identify those patients who will develop myocardial infarction (MI) or stroke despite aspirin use. Our long-term goal is to personalize the aggressiveness of antiplatelet therapy to achieve the optimal risk:benefit ratio in patients at risk for MI/stroke. Although ex vivo tests of residual platelet function after aspirin use - indicators of risk for cardiovascular events - are available in research settings, they are not widely employed in clinical trials or patient care. Whole blood gene expression profiling is now being used clinically. Extensive work in our laboratories indicate that gene expression signatures can predict response or resistance to medications and that signatures from whole blood can classify a variety of relevant cardiovascular phenotypes. Our preliminary data demonstrate that combining multiple tests of platelet function can reliably identify a unique subgroup of individuals with the phenotype of high residual platelet function on aspirin (i.e. laboratory aspirin resistance). Therefore our central hypothesis is that a comprehensive model using whole blood gene expression signatures and clinical data can accurately identify laboratory aspirin resistance and individuals who would be suboptimally treated with conventional antiplatelet therapy. The overall objective of this proposal is to deliver a clinico-genomic tool that accurately predicts laboratory aspirin resistance and can be applied to patients at risk for MI/stroke. This objective will be achieved through the completion of three specific aims: 1) To develop whole blood gene expression signatures that predict and diagnose laboratory aspirin resistance in healthy volunteers;2) To validate whole blood gene expression signatures that predict and diagnose laboratory aspirin resistance in patients at risk for MI/stroke;and 3) To develop a comprehensive model that identifies laboratory aspirin resistance using clinical and molecular data. Under the first two aims, aspirin will be administered to healthy volunteers and patients with either type 2 diabetes or coronary artery disease. Whole blood gene expression signatures will be developed using sparse latent factor regression models of the gene expression data from those with laboratory aspirin resistance and sensitivity.
The third aim will include age, race, sex and other clinical covariates to deliver a comprehensive model. The proposed studies are innovative because we expect to develop diagnostic and predictive models using whole blood RNA profiling - a proven technology that is widely available - for multiple measurements of residual platelet function on aspirin that are only available in specialized centers. The proposed research is significant because it is expected to deliver an actionable tool that accurately identifies individuals with laboratory aspirin resistance such that clinicians can tailor the aggressiveness of antiplatelet therapies.

Public Health Relevance

The proposed studies are an important area of cardiovascular research that have the potential to deliver a reliable, translatable, and actionable tool that accurately identifies those patients at highest risk for developing myocardial infarction and stroke on aspirin alone. In addition, it lays the foundation for personalizing the aggressiveness of antiplatelet therapies with the ultimate goal of preventing myocardial infarction and stroke -- two leading causes of global morbidity and mortality.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
NIH Challenge Grants and Partnerships Program (RC1)
Project #
5RC1GM091083-02
Application #
7939832
Study Section
Special Emphasis Panel (ZRG1-VH-D (58))
Program Officer
Long, Rochelle M
Project Start
2009-09-30
Project End
2012-08-31
Budget Start
2010-09-01
Budget End
2012-08-31
Support Year
2
Fiscal Year
2010
Total Cost
$499,907
Indirect Cost
Name
Duke University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
Voora, Deepak; Rao, A Koneti; Jalagadugula, Gauthami S et al. (2016) Systems Pharmacogenomics Finds RUNX1 Is an Aspirin-Responsive Transcription Factor Linked to Cardiovascular Disease and Colon Cancer. EBioMedicine 11:157-164
Rose, Jason J; Voora, Deepak; Cyr, Derek D et al. (2015) Gene Expression Profiles Link Respiratory Viral Infection, Platelet Response to Aspirin, and Acute Myocardial Infarction. PLoS One 10:e0132259
Voora, Deepak; Cyr, Derek; Lucas, Joseph et al. (2013) Aspirin exposure reveals novel genes associated with platelet function and cardiovascular events. J Am Coll Cardiol 62:1267-1276
Voora, Deepak; Ortel, Thomas L; Lucas, Joseph E et al. (2012) Time-dependent changes in non-COX-1-dependent platelet function with daily aspirin therapy. J Thromb Thrombolysis 33:246-57