biomarkers of cash

Conditions: Cerebral Cavernous Malformation; Cavernous Angioma; Hemorrhagic Microangiopathy

Summary: 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.

Eligibility criteria:
aim 1 and 2: inclusion criteria: 1. clinical diagnosis of ca 2. age 18 or older 3. solitary or multiple 4. familial or sporadic 5. with or without prior symptoms exclusion criteria: 1. prior excision of a solitary ca lesion 2. prior stereotactic radiosurgery or any brain irradiation 3. spinal cavernoma without brain lesion 4. other brain pathology unrelated to ca (demyelinating disease, brain tumor) 5. seizures or stroke unrelated to ca in the prior year 6. current pregnancy or within 6 months postpartum 7. reluctance to undergo venipuncture or donate blood specimen, or be called for clinical follow-up for up to one year 8. homeless or incarcerated persons, or other reason a subject will be unable/unlikely to be reached for follow-up aim 3: inclusion criteria: 1. \< 30 years of age 2. one or more seizures (with or without medical therapy) in the prior year or 1. \> 50 years of age 2. having received an mri of the brain with swi (susceptibility weighted imaging) sequences for any indication in the year prior to enrollment 3. no hma on brain mri swi sequences or 1. \> 50 years of age 2. having received an mri of the brain with swi sequences for any indication in the year prior to enrollment 3. two or more microbleeds on swi brain mri sequences, adjudicated by neuroradiologist exclusion criteria: 1. concurrent brain disease or structural brain pathology 2. medical illness requiring hospitalization or surgery, seizure or stroke in the prior 12 months 3. active use of prescription medications in the prior 12 months 4. current pregnancy or within 6 months postpartum 5. reluctance to undergo venipuncture or donate blood specimen or 1. concurrent brain disease or structural brain pathology 2. medical illness requiring hospitalization or surgery, or stroke in the prior 12 months other than seizure disorder 3. active use of prescription medications in the prior 12 months except anticonvulsants 4. current pregnancy or within 6 months postpartum 5. reluctance to undergo venipuncture or donate blood specimen or 1. concurrent brain disease or structural brain pathology 2. medical illness requiring hospitalization or surgery within the prior year 3. any history of stroke or epileptic seizure within the prior year 4. current pregnancy or within 6 months postpartum 5. reluctance to undergo venipuncture or donate blood specimen or 1. concurrent brain disease or structural brain pathology 2. medical illness requiring hospitalization or surgery within the prior year 3. any history of stroke or epileptic seizure within the prior year 4. current pregnancy or within 6 months postpartum 5. reluctance to undergo venipuncture or donate blood specimen

Keywords: plasma biomarker imaging biomarker machine learning