Identification of Novel Molecular Markers for Cerebral Ischemia From Patients With Minor and Devastating Ischemic Injury

Ischemic stroke is one of the top causes of morbidity and mortality in the United States. Despite a great deal of effort to improve outcomes of patients with ischemic cerebral strokes, the lack of a bona fide animal model representative of cerebral ischemia in man makes the study of the pathological processes involved difficult. Additionally, the subtle but significant differences between biology of animal models and the biology of humans make translatability of animal results to humans difficult.

The purpose of this study is to use an iatrogenic model of stroke, meaning those strokes inadvertently caused by endovascular coiling of elective aneurysms, to study the biology of stroke in humans. Clinical evidence suggests that simple catheterization of cerebral vasculature causes small, usually clinically silent, embolic strokes. These strokes are evident on MRI scans. Additionally, since the practitioner knows the onset of an interventional procedure, he by default knows the timing of injury. This simple model allows one to study stroke in real-time with knowledge of the time of onset. Magnetic resonance imaging (MRI) evaluation allows the practitioner to identify the volume of stroke caused by the intervention. Alternatively, patients who present to the emergency room with large ischemic infarcts provide a natural control population for this study. These patients present with large, usually devastating strokes. In most cases the timing of the onset of deficit is known. The investigators propose to use the simple model of ischemia from endovascular interventions with the more obvious devastating cases of ischemic stroke who present to the emergency room to better understand the molecular pathways involved in stroke.

Rationale: Global analysis of biological markers is an established mechanism to study complex disease processes. The introduction of microarray technology and systems wide analysis has improved the understanding of various biological and disease processes. This revolution has been ongoing since the early 1990's. The rationale for performing these studies is to augment the understanding of the basic mechanisms of stroke in humans. As previously mentioned, there is no bona fide model of stroke and the researchers' experimental design provides a rather simple in human model for cerebral ischemia.

The study requires four blood draws, each 5 mL in volume; blood draws are timed with normal times of blood draw these patients would be experiencing and do not place the patient at any additional risk.

The blood samples will be analyzed as follows: total ribonucleic acid (RNA), including the microRNA fraction, and protein will be isolated and quantified from the blood samples. The researchers will load the RNA samples onto Febit microRNA arrays. The Febit miRNA chip has all of the known human miRNAs and miRNA star sequences from Sanger's miRBase 14. With this platform total RNA is loaded directly onto the array. There are no RNA labeling or amplification steps. miRNA hybridization on the chip is followed by a microfluidic primer extension assay. In this case, only hybridization of the correct miRNA to the probe allows the primer extension step to proceed efficiently, giving the array high sensitivity and specificity. In addition, the researchers have created custom microarrays, adding several spike-in controls. Our spike-ins provide feedback on the variability in RNA isolation and are an additional signal for array normalization. The protein fraction will be analyzed using Ray Biotech's Quantibody Arrays. These are arrays of antibodies that are designed to capture specific protein species (the researchers will target approximately 120 unique proteins) in a fully quantitative fashion. These arrays essentially function as the traditional enzyme-linked immunosorbent assay (ELISA) but on a glass slide substrate. The assays offer several advantages over ELISA's, including the requirement for very low amounts of sample input but, perhaps more importantly, they facilitate the quantitative investigation of hundreds of proteins at once and therefore greatly accelerate the ability to search for and identify protein-based signatures and/or biomarkers. The data will be statistically analyzed using statistical tools that are deemed appropriate at the time of data analysis by investigators from TGen and Dr. Kalani. Drs. Kalani and Nakaji will then correlate the identity and quantity of identified molecular markers, their temporal appearance, concentration, and disappearance to the collected clinical data.