Electronic Thesis/Dissertation
Identification of Aspirin Resistant Biomarkers Using Whole Blood Genome Profiling Open Access
Background: Anti-platelet therapy with aspirin has been proven to decrease atherothrombotic events and mortality in patients at high risk for cardiovascular disease. Despite this benefit, studies have shown that as many as 20% of patients taking aspirin will have recurrent ischemic vascular events. Many patients demonstrate inadequate anti-platelet response to aspirin on laboratory testing. We hypothesize that changes in gene expression in blood cells may shed light on the mechanisms of AR in adults at risk for ischemic events. Objective: To identify genetic markers associated with aspirin resistance in a middle-aged population with known atherosclerosis or at elevated risk for coronary or peripheral vascular atherosclerosis.Methods and Results: Blood samples were obtained from 131 patients with known cardiovascular diseases or at risk and divided into two groups (aspirin resistant and aspirin sensitive) according to their platelet function test results using VerifyNow® System. Whole blood total RNA was purified from 16 samples (8 resistant and 8 sensitive) with PAXgene Blood RNA kit for microarray assays. The RNA samples were reverse-transcripted and labeled with NuGen OvationTM Amp V2 and FL-OvationTM Biotin V2 Kits before being hybridized to the Affymetrix GeneChip® HG-U133 plus 2.0 arrays. The microarray data generated by the Affymetrix Command Console (.chp file) were exported to the GeneSpring 10.0.2 for further analysis. A total of 284 genes passed the statistical (p ≤ 0.05) and fold-change (≥ 1.8) threshold filtering. In order to gain functional insight into how the 284 genes might be related to aspirin resistance. We employed core analysis function of Ingenuity Pathway Analysis (IPA) to further explore statistically significant biological functions, molecular interaction networks and potential pathways associated with this gene list. Several pathways and gene markers, including THBS1 and PTGES were identified as possible explanations of the mechanisms of AR. Conclusions: Whole blood gene expression profiling strategy may help solve the mystery of AR. Gene markers identified could be used as both diagnostic and therapeutic targets.
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Li_gwu_0075M_10360.pdf | 2018-01-15 | Open Access |
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