Publications
Below is a technology overview and a summary of 26 select publications, abstracts, presentations, regulatory and compliance data. More data and references available for interested parties. Whether your interest is science, clinical, health economics, or quality; we welcome any questions.
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Ischemia Care Technology Overview: RNA expression in stroke
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In acute settings distinguishing ischemic stroke from other neurological diseases can be challenging. Determining the cause of stroke can also be challenging and frequently remains unclear or even unknown based on current diagnostic investigations and classification features. Correct diagnosis of ischemic stroke and its causes is essential to optimally treat and prevent stroke. Just as neuroimaging, cardiac evaluation and arterial imaging are used in the diagnosis of stroke and determining its causes, molecular features in the form RNA expression also has utility.
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Given the heterogeneity in ischemic stroke, a single biomarker may not be able to sufficiently reflect the underlying complexity. A biomarker panel is a group of markers that reflect different pathophysiological processes of a disease. In stroke such markers might provide information about atherosclerosis, thrombus formation, inflammation, oxidative stress, endothelial injury, blood–brain barrier disruption, and cerebral ischemia.
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Ischemia Care believes biomarker panels may have several applications in stroke. They may be useful to differentiate ischemic stroke and transient ischemic attacks (TIAs) from hemorrhagic stroke and other stroke mimics. Biomarker panels may also find applications to stratify risk of future stroke, provide prognostic information, or potentially identify patients most likely to benefit from stroke treatments (such as intervention).
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Ischemia Care technology is based upon the discovery that changes in blood occur in response to stroke. These changes are measured by gene expression in RNA from whole blood. Gene expression is a process where a cell responds to its changing environment by creating instructions. In Ischemic stroke, changes in cells occur in the form of innate and adaptive immune responses. Advantages of an RNA based blood test are as follows:
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RNA is introduced rapidly within minutes of an ischemic event before events could be detected using protein markers. RNA has potential for point of care applications.
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Ischemia Care is built using almost all currently known coding RNAs through a single platform allowing examination of over 400,000 targets at the transcriptome level. RNA allows selection of best markers. Protein approaches by contrast are candidate bases and not all RNAs code to proteins.
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One example is ISCDX is built on genes from known pathways that differentially express based upon cause of ischemic event. Specifically, the interaction of leukocytes, platelets and red blood cells.
Figure 1
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Leukocyte RNA is meaningful in blood of stroke patient. Figure 1 illustrates Leukocyte interactions with intravascular elements relevant for stroke in humans. Leukocytes (neutrophils, lymphocytes, monocytes), platelets, red blood cells, and other cells interact with each other and with endothelial cells in normal vessels. Leukocyte interactions with endothelial cells, platelets, atherosclerotic plaque, blood clots, and intravascular molecules (cytokines, chemokines, hormones, others) likely account for some changes of gene expression following stroke. Leukocytes also signal to these other cell types, which also account for changes of gene expression. In simple terms, Leukocytes interact with cell types relevant to ischemic stroke.
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The Biomarkers of Acute Stroke Etiology (BASE NCT02014896) is an Ischemia Care sponsored clinical trial was designed by guideline authors and leaders across multiple health systems covering the stroke care continuum; emergency medicine, neurology, cardiology, pharmacology, health economics, population health, post-acute care, and other professionals involved in stroke care to understand the patient journey and gaps in care decisions, that could be improved to reduce cost of care and improve outcomes. BASE concluded enrollment in 2021 with recruitment of over 1700 patients over 20+ hospital systems and collecting 5,000 blood samples, the goal is commercialization of 10 or more test used to identify stroke and its causes used in the acute hospital setting, post hospitalization, ongoing monitoring for stroke risk, and someday predict patients at risk for stroke.
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Section 1 – Select published literature
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Jauch EC, Barreto AD, Broderick JP, et al. Biomarkers of Acute Stroke Etiology (BASE) Study Methodology [published online ahead of print, 2017 May 5]. Transl Stroke Res. 2017;8(5):424-428. doi:10.1007/s12975-017-0537-3
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Stamova B, Xu H, Jickling G, et al. Gene expression profiling of blood for the prediction of ischemic stroke. Stroke. 2010;41(10):2171-2177. doi:10.1161/STROKEAHA.110.588335
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Jickling GC, Xu H, Stamova B, et al. Signatures of cardioembolic and large-vessel ischemic stroke. Ann Neurol. 2010;68(5):681-692. doi:10.1002/ana.22187
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Jickling GC, Stamova B, Ander BP, et al. Prediction of cardioembolic, arterial, and lacunar causes of cryptogenic stroke by gene expression and infarct location. Stroke. 2012;43(8):2036-2041. doi:10.1161/STROKEAHA.111.648725
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Jickling GC, Sharp FR. Blood biomarkers of ischemic stroke. Neurotherapeutics. 2011;8(3):349-360. doi:10.1007/s13311-011-0050-4
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Zhan X, Jickling GC, Tian Y, et al. Transient ischemic attacks characterized by RNA profiles in blood. Neurology. 2011;77(19):1718-1724. doi:10.1212/WNL.0b013e318236eee6
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Jickling GC, Zhan X, Stamova B, et al. Ischemic transient neurological events identified by immune response to cerebral ischemia. Stroke. 2012;43(4):1006-1012. doi:10.1161/STROKEAHA.111.638577
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Jickling GC, Stamova B, Ander BP, et al. Profiles of lacunar and nonlacunar stroke. Ann Neurol. 2011;70(3):477-485. doi:10.1002/ana.22497
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Sharp FR, Jickling GC. Whole genome expression of cellular response to stroke. Stroke. 2013;44(6 Suppl 1):S23-S25. doi:10.1161/STROKEAHA.112.679357
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​Section 2 – Select abstracts and clinical presentations of clinical trial data
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Miller D on Behalf of BASE Investigators. RNA Expression Identifying Ischemic Stroke In Acute Hospital Setting: Interim Analysis From BASE Clinical Trial. 2020 Society of Vascular and Interventional Neurology (SVIN) International conference.
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Peacock WP on Behalf of BASE investigators. Cardioembolic stroke is much more common in patients presenting to the ER with suspected stroke: A BASE trial analysis. 2019 AHA International Stroke Conference.
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Barreto, A.D. on Behalf of BASE Investigators. Cardiogenic stroke versus controls. 2015 AHA International Stroke Conference
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Jickling GC, Xu H, Stamova B, et al. Signatures of cardioembolic and large-vessel ischemic stroke. Ann Neurol. 2010;68(5):681-692. doi:10.1002/ana.22187
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Jauch EC on behalf of BASE Investigators. RNA Expression Signature To Diagnosis Stroke Etiology By Atrial Fibrillation Versus Large Artery Atherosclerosis Cause: A BASE Clinical Trial Analysis, abstract presentation at the 2020 International Stroke Conference.
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Jauch EC on Behalf of BASE Investigators. Signatures of cardioembolic versus large vessel stroke using gene expression, 2016 International Stroke Conference
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Jauch on Behalf of BASE Investigators. RNA expression predicts cause in cryptogenic stroke. 2017 AHA International Stroke Conference
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Miller, J. on behalf of BASE Investigators. Biology Of Stroke: Role Of ELL2, GLIPR1, MAPKAPK3 Genes In Identifying Atrial Fibrillation Cause Of Stroke, abstract presentation at the 2020 International Stroke Conference.
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Jickling, GC on behalf of BASE Investigators. RNA Expression Signature To Diagnosis Stroke Etiology By Atrial Fibrillation Versus Large Artery Atherosclerosis Cause: A BASE Clinical Trial Analysis, abstract presentation at the 2020 International Stroke Conference.
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Jauch EC on Behalf of BASE Investigators. BASE: An ongoing clinical trial to validate a blood test for cause of stroke. 2014 AHA International Stroke Conference presentation
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Appendix 3 – Internal, regulatory, compliance, and commercial validations
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.CLIA data, internal document, Cardioembolic vs Large Artery Atherosclerotic Stroke
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Correlation of RefSeq genes to microarray data for point of care and scalability of applications (2017 internal study)
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Correlation of gene expression using 396 stroke gene candidates between microarray and multiplex system (2018 internal study)
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An artificial intelligence model for prediction of ischemic stroke cause by correlation of clinical factors with RNA expression
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Isolation of gene expression for complex clinical factors in determining predictors of ischemic stroke cause.
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Schoonover T. A case study on the impact of ISCDx testing at Kettering Medical Center.