Blood transcriptomics as CT adjuvant to exclude hemorrhage in acute stroke

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What? We will test the accuracy of an RNA-seq based biomarker assay to predict the diagnosis of stroke in a minority population (African American). We will investigate the impact of sex and race on test accuracy, and investigate novel sequencing approaches to speed up the time to obtain actionable results (Nanopores). Why? When using the thrombolytic tPA, time is of the essence, as the drug must be administered within 3-4.5 hrs of stroke onset. The sooner with in this time window that tPA can be administered, the greater the benefit. In addition, intracerebral hemorrhage must have been excluded by CT scanning; currently the sole method to make this therapeutically critical determination. Delays in radiologist interpretation of CT results, or lack of available imaging facilities is the most common reason for thrombolytic treatment not being initiated. . Thus corroborative use of a highly sensitive blood test would permit ER physicians to be confident of their CT interpretation in settings without onsite CT reading by a radiologist. Timely administration of tPA would thereby be permitted reducing stroke burden. Accordingly, a rapid biomarker test to exclude hemorrhage in acute stroke would reduce door to needle times, lower mortality, and improve outcome in stroke. Stroke burden is higher in African Americans and females, yet these populations have lower representation in genomic research. We test the impact of sex and race by assessing test accuracy derived from a single sex or race, and then tested in the opposite sex, or Caucasians. These experiments will determine whether mixed sex or race derived tests are more accurate than those derived from a single population. Finally, we investigate approaches to speed up testing using novel Nanopore sequencing technology. How? Our studies of blood biomarkers, developed at Grady Memorial Hospital Marcus Stroke Center, offers a diagnostic blood test that discriminates between ischemic and hemorrhagic stroke. We do not rely on single biomarkers but rather use analysis of the entire transcriptome (all RNA) in venous blood, by the use of next generation RNA sequencing. These data provide highly accurate stroke diagnosis, determine stroke subtype, offer powerful prediction of outcome, and show differences and treatment response by sex. We hypothesize transcriptome differences in peripheral blood can predict CT diagnosis of hemorrhagic vs. ischemic stroke. We propose to recruit patients from the Grady memorial hospital, and obtain blood samples for RNA sequencing. From this dataset we will test three specific aims: AIM ONE: Determine the accuracy of blood RNA profiles to predict CT documented hemorrhagic stroke. AIM TWO: Determine the effect of sex and race on transcriptomic profile accuracy. AIM THREE: Show the accuracy of rapid RNA measurement techniques to identify ischemic brain hemorrhage profiles. IMPACT: A rapid point of care blood test to diagnosis stroke and stroke subtype will increase the percentage of the acute stroke population eligible for tPA therapy, significantly reducing stroke morbidity and mortality.