Stroke is an acute neurological deficit that results from abnormal blood flow to the brain. The term stroke encompasses two primary subgroups: hemorrhagic stroke that is due to extravasation of blood and ischemic stroke that is due to vessel obstruction. Determining stroke type and underlying etiology is a crucial step in patient management as it influences treatment strategies. Currently diagnosis of stroke relies on clinical examination and neuroimaging, but there is a lack of rapid diagnostic and prognostic testing. Using microarray technology we identified a novel association between elevated peripheral blood expression of MCEMP1 and stroke. We have also shown that MCEMP1 discriminates between primary stroke types and predicts one-month post-stroke prognosis. Since genetic mechanisms underlying stroke remain incompletely understood we next conducted a global gene network analysis. Network analysis identified four large groups of co-expressed genes associated with ischemic stroke. NLRC4, CKLF, and HS.546375 were the most interconnected genes within unique modules and each was also independently associated with ischemic stroke. We show that multi-gene models have greater discriminative capacity for stroke and stroke prognosis, than single gene models. In addition to stroke biomarkers we also identified biomarkers of atrial fibrillation (AF), a known risk factor of stroke. Currently our understanding of the molecular mechanisms underlying AF remains incompletely understood. Thus we conducted whole blood expression profiling in patients with persistent AF before and after successful electrical cardioversion, a procedure that aims to restore sinus rhythm to the heart. We identified elevated expression of SLC25A20 and PDK4 during AF as compared with sinus rhythm. Furthermore we show that SLC25A20, PDK4 and NT-proBNP have incremental utility to discriminate AF from sinus rhythm. Taken together, the thesis implicates new genes with stroke and AF, and also indicates that whole blood RNA biomarkers may have clinical utility. / Thesis / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/19022 |
| Date | January 2016 |
| Creators | Raman, Kripa |
| Contributors | Paré, Guillaume, Medical Sciences |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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