Biomarkers of CASH

Cavernous Angioma, Cerebral Cavernous Malformation, Hemorrhagic Microangiopathy

plasma biomarker, imaging biomarker, machine learning

The project aims to develop prognostic and diagnostic blood tests for symptomatic brain hemorrhage in patients diagnosed with cavernous angiomas, a critical clinical challenge in a disease affecting more than a million Americans. We further examine whether blood biomarkers can replace or enhance the accuracy of advanced imaging in association with lesional bleeding. The project tests a novel integrational approach of biomarker development in a mechanistically defined cerebrovascular disease, with a clinically relevant context of use.

Cerebral cavernous angioma (CA) is a capillary microangiopathy affecting more than a million Americans, predisposing them to a premature risk of brain hemorrhage. Fewer than 200,000 cases who have suffered a recent symptomatic hemorrhage (SH) are most likely to re-bleed again with serious clinical sequelae, and are the primary focus of therapeutic development. Genetic mechanisms of CA have been extensively studied, and consequent signaling aberrations in the neurovascular unit. These include proliferative dysangiogenesis, blood-brain barrier hyperpermeability, inflammation and immune mediated processes, anticoagulant vascular domain, and gut microbiome-driven mechanisms. Plasma levels of molecules reflecting these mechanisms and measures of vascular permeability and hemorrhage leak on magnetic resonance imaging (MRI) have been correlated with CA hemorrhage in pilot studies. It would be desirable to optimize these biomarkers to accurately diagnose CASH, to prognosticate the risk of future SH, and to monitor cases after a bleed and in response to therapy. This would influence clinical management, and select higher risk cases for clinical trials. Additional candidate biomarkers are emerging from ongoing mechanistic and differential transcriptome studies, which would be expected to further enhance the sensitivity and specificity of diagnosis and prediction of CASH. Weighed combinations of levels of plasma proteins and characteristic micro-ribonucleic acids (miRNA) may further strengthen biomarker associations. Plasma biomarkers may reflect (and potentially replace) more cumbersome and expensive imaging biomarkers for monitoring CA hemorrhage. We here assemble CA researchers and propose to deploy advanced statistical and computational biology approaches for the integration of novel candidate biomarkers. In Specific Aim 1 we assess these biomarkers in a large CA cohort to discover the best plasma biomarkers and validate them in sex, age and relevant clinical subgroups. In Specific Aim 2 we compare changes in MRI measures of vascular permeability and hemorrhage with plasma biomarkers over time. In Specific Aim 3 we query the biomarkers in non-CA subjects, to identify potential confounders in the clinical context. This project integrates analytic and computational biology expertise to develop blood tests for better CASH diagnosis and prognosis. The project tests a novel integrational approach of biomarker development in a mechanistically defined cerebrovascular disease with a relevant context of use. This approach is applicable to other neurological diseases with similar pathobiologic features.

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United States