SBIR-STTR Award

Rupture of intracranial aneurysms (IAs) causes intracranial hemorrhaging that leads to high rates of neurological deficits and death. Although rupture rates are low, clinicians must decide whether to treat or monitor these potentially dangerous lesions. In the current clinical practice, the most common metric to measure risk of rupture is aneurysm size (?7 mm or ?5 mm). However, clinical data show that small aneurysms can also rupture. As a result, alternative clinical stratification scores have been proposed, including the PHASES (Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, and Site) score based on patient demographics and IA characteristics to stratify ruptured and unruptured IAs, and the Rupture Resemblance Score (RRS) that stratifies ruptured and unruptured IAs based on hemodynamic and morphological properties. However, all metrics require imagining on digital subtraction angiography (DSA), which is invasive, expensive, requires the use of X-rays, and is associated with transient or permanent neurological and non-neurological complications. In previous studies, we found that patients with and without IAs have RNA expression differences in their circulating blood that reflect leukocyte activation and inflammatory signaling. Expression differences could both identify the presence of IAs and stratify IA samples by size. We therefore hypothesize that individuals with dangerous IAs have detectable gene expression differences in their blood that could be used as biomarkers to determine rupture risk. In this Phase-I study, we propose to use whole blood transcriptomes to develop a “one- stop” diagnostic test that can detect the presence of IAs and determine the risk of rupture based on circulating RNA expression biomarkers using our prototype AneuScreenTM platform. We aim to: 1) Develop and validate biomarkers to predict risk indicated by the currently-used size metric, 2) Develop and validate biomarkers to predict risk indicated by the clinical PHASES score, and 2) Develop and validate biomarkers to predict risk indicated by the RRS. These biomarkers will save the healthcare millions in unnecessary high-cost imaging procedures and unnecessary aneurysm treatments.

Public Health Relevance Statement:
Project Narrative Intracranial aneurysms (IAs) can lead to devastating health consequences upon rupture. Because rupture is uncommon, there is a need for clinicians to have an objective metric of rupture risk that can help classify IAs as high-risk or low-risk lesions. In this project we aim to develop circulating whole blood gene expression biomarker of aneurysm risk. This biomarker once incorporated into our AneuScreenTM diagnostic platform will help avoid unnecessary aneurysm treatments by: (1) stratifying IA cases between those that are high-risk and require treatment, and those that are low-risk and can be periodically monitored; (2) enabling a low-cost, non-invasive alternative to frequently monitor IAs; and (3) determining the need for follow-up imaging in the case of a positive AneuScreenTM test, as low risk IAs may only need magnetic resonance angiography (MRA), while high risk IAs may directly receive DSA for imaging and possible preventive treatment. Successful completion of this Phase I will clarify if a pre-imaging blood test can stratifying IA risk. This augmented capability will lead to more vigilant and cost-effective IA management.

NIH Spending Category:
Bioengineering; Brain Disorders; Cerebrovascular; Neurosciences; Stroke

Project Terms:
3-Dimensional; Age; Algorithms; Aneurysm; Area; base; Biological; Biological Markers; biomarker development; Biomechanics; Blood; Blood Tests; Cells; Cerebrum; Cessation of life; Characteristics; Classification; Clinical; Clinical Data; clinical practice; Clinical stratification; cohort; Complex; Complication; cost; cost effective; Dangerousness; Data Set; Demographic Factors; demographics; Development; Diagnostic; Diagnostic tests; differential expression; Digital Subtraction Angiography; disability; Dose; Endothelium; Event; Face; follow-up; Gene Expression; Genes; Genetic Transcription; Growth; Health; Healthcare; hemodynamics; high risk; Hospitals; Hypertension; Image; image processing; Imaging Techniques; indexing; Individual; Inflammatory; Intracranial Aneurysm; Intracranial Hemorrhages; Lead; Lesion; leukocyte activation; Liquid substance; machine learning algorithm; Magnetic Resonance Angiography; Measures; Mediating; Modeling; molecular marker; Monitor; Morphology; mortality; Natural History; Nature; Neurologic; Neurologic Deficit; Pathway interactions; patient population; Patients; Phase; phase 1 study; Population; Preventive treatment; Property; prototype; response; Risk; Risk stratification; RNA; Roentgen Rays; Rupture; Ruptured Aneurysm; Sample Size; Sampling; shear stress; Signal Transduction; Site; Small Business Innovation Research Grant; Subarachnoid Hemorrhage; Surface; Survivors; Testing; Three-Dimensional Image; Training; transcriptome; Whole Blood

Intracranial aneurysm (IA) rupture is the primary cause of non-traumatic subarachnoid hemorrhage, acatastrophic event that carries high rates of mortality (>50%) and permanent disability (>50% among survivors).When an unruptured IA is discovered, clinicians face the difficult decision of whether or not it should be treated.Since rupture rates are low (risk of rupture ~ 0.5-1% per year), while complication risks of intervention can besignificant, it is critical to stratify rupture risk such that the dangerous IAs are treated right away while lessdangerous ones can be periodically monitored. In clinical practice, aneurysm size has been the principal criterionfor treatment, but it is not always reliable. Recently, other clinical metrics, such as the PHASES (Population,Hypertension, Age, Size of IA, Earlier subarachnoid hemorrhage, and Site of IA) score, which use IAcharacteristics and patient demographics, have been developed and validated in attempts to better stratify risk.However, like IA size, such risk metrics can only be accurately assessed after the patient has received digitalsubtraction angiography (DSA), which is invasive, expensive ($5,000-8,500 per scan), and risky for transient orpermanent complications. Furthermore, these metrics lack information about biological differences underlyingIAs that may better discriminate high- vs low-risk cases. A blood-based diagnostic of dangerous IAs wouldenable more informed IA management and could offer a low-cost, non-invasive way to monitor patientsduring watchful waiting or after treatment (between follow-up imaging). Over the past several years, Neurovascular Diagnostics has been developing a blood-based IA diagnosticcalled AneuScreenTM. During development, we found that expression differences of certain genes also stratifiedIA cases by IA size in a "dose-dependent" manner, leading us to hypothesize that patients with high-risk IAshave distinguishable gene expression patterns in their blood. In a successfully completed Phase I SBIR project,we used whole blood transcriptomes from a modestly-sized dataset of IA patients to develop and test machinelearning classifiers of high-risk aneurysm cases (delineated by PHASES score). This model had 88% testingaccuracy, 78% sensitivity, and 95% specificity. Despite these exciting results, further work is needed to translatethis biomarker into a diagnostic test, which is the focus of this Phase II SBIR project. In Aim 1, we will validatethe genes within the IA risk biomarker in a large dataset of previously-collected blood samples that will besubjected to RNA sequencing. In Aim 2, we will standardize the assessment of the biomarker on an establishedclinical platform that utilizes qPCR and capillary electrophoresis for expression readout. The models will be re-trained to perform well using this new output data-type. Lastly, in Aim 3, we will test the developed assay, whichwe call AneuScreenTM+(or AneuScreenTM Plus), in a prospective cohort of n=400 patients with IA and n=200controls. Successful completion of this Phase II will determine if our prototype IA diagnostic can expand itscapabilities and increase its value by stratifying IA risk, in addition to identifying IA.

Public Health Relevance Statement:
Narrative In this Phase II proposal, Neurovascular Diagnostics aims to develop a blood-based RNA expression diagnostic to assess intracranial aneurysm rupture risk. To do this, we will validate our preliminary expression- based risk biomarker (successfully developed in Phase I) in a new dataset of sequencing data (n=200), standardize the assessment of the biomarker on an established clinical testing platform, and then test the developed, research-use-only assay in a large prospective cohort of 600 patient blood samples collected from 5 centers across the US. Successful completion of this study will produce an aneurysm risk blood test that will enable more vigilant aneurysm management and low-cost, non-invasive monitoring of patients during watchful waiting or between follow-up imaging after treatment.

Project Terms: