Dataset Information

A Roadmap for Developing Plasma Diagnostic and Prognostic Biomarkers of Cerebral Cavernous Angioma With Symptomatic Hemorrhage (CASH).

ABSTRACT:

Background

Cerebral cavernous angioma (CA) is a capillary microangiopathy predisposing more than a million Americans to premature risk of brain hemorrhage. CA with recent symptomatic hemorrhage (SH), most likely to re-bleed with serious clinical sequelae, is the primary focus of therapeutic development. Signaling aberrations in CA include proliferative dysangiogenesis, blood-brain barrier hyperpermeability, inflammatory/immune processes, and anticoagulant vascular domain. Plasma levels of molecules reflecting these mechanisms and measures of vascular permeability and iron deposition on magnetic resonance imaging are biomarkers that have been correlated with CA hemorrhage.

Objective

To optimize these biomarkers to accurately diagnose cavernous angioma with symptomatic hemorrhage (CASH), prognosticate the risk of future SH, and monitor cases after a bleed and in response to therapy.

Methods

Additional candidate biomarkers, emerging from ongoing mechanistic and differential transcriptome studies, would further enhance the sensitivity and specificity of diagnosis and prediction of CASH. Integrative combinations of levels of plasma proteins and characteristic micro-ribonucleic acids may further strengthen biomarker associations. We will deploy advanced statistical and machine learning approaches for the integration of novel candidate biomarkers, rejecting noncorrelated candidates, and determining the best clustering and weighing of combined biomarker contributions.

Expected outcomes

With the expertise of leading CA researchers, this project anticipates the development of future blood tests for the diagnosis and prediction of CASH to clinically advance towards precision medicine.

Discussion

The project tests a novel integrational approach of biomarker development in a mechanistically defined cerebrovascular disease with a relevant context of use, with an approach applicable to other neurological diseases with similar pathobiologic features.

SUBMITTER: Girard R

PROVIDER: S-EPMC7884145 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Brain cavernous angiomas with symptomatic hemorrhage (CASH) are uncommon but exact a heavy burden of neurological disability from recurrent bleeding, for which there is no proven therapy. Candidate drugs to stabilize the CASH lesion and prevent rebleeding will ultimately require testing of safety and efficacy in multisite clinical trials. Much progress has been made in understanding the epidemiology of CASH, and novel biomarkers have been linked to the biological mechanisms and clinical activity in lesions. Yet, the ability to enroll and risk-stratify CASH subjects has never been assessed prospectively at multiple sites. Biomarkers and other outcomes have not been evaluated for their sensitivity and reliability, nor have they been harmonized across sites. OBJECTIVE:To address knowledge gaps and establish a research network as infrastructure for future clinical trials, through the Trial Readiness grant mechanism, funded by National Institute of Neurological Disorders and Stroke/National Institutes of Health. METHODS:This project includes an observational cohort study to assess (1) the feasibility of screening, enrollment rates, baseline disease categorization, and follow-up of CASH using common data elements at multiple sites, (2) the reliability of imaging biomarkers including quantitative susceptibility mapping and permeability measures that have been shown to correlate with lesion activity, and (3) the rates of recurrent hemorrhage and change in functional status and biomarker measurements during prospective follow-up. EXPECTED OUTCOMES:We propose a harmonized multisite assessment of enrollment rates of CASH, baseline features relevant to stratification in clinical trials, and follow-up assessments of functional outcomes in relation to clinical bleeds. We introduce novel biomarkers of vascular leak and hemorrhage, with firm mechanistic foundations, which have been linked to clinical disease activity. We shall test their reliability and validity at multiple sites, and assess their changes over time, with and without clinical rebleeds, hence their fitness as outcome instruments in clinical trials. DISCUSSION:The timing cannot be more opportune, with therapeutic targets identified, exceptional collaboration among researchers and the patient community, along with several drugs ready to benefit from development of a path to clinical testing using this network in the next 5 years.

Project description:RATIONALE:The clinical course of cerebral cavernous malformations is highly unpredictable, with few cross-sectional studies correlating proinflammatory genotypes and plasma biomarkers with prior disease severity. OBJECTIVE:We hypothesize that a panel of 24 candidate plasma biomarkers, with a reported role in the physiopathology of cerebral cavernous malformations, may predict subsequent clinically relevant disease activity. METHODS AND RESULTS:Plasma biomarkers were assessed in nonfasting peripheral venous blood collected from consecutive cerebral cavernous malformation subjects followed for 1 year after initial sample collection. A first cohort (N=49) was used to define the best model of biomarker level combinations to predict a subsequent symptomatic lesional hemorrhagic expansion within a year after the blood sample. We generated the receiver operating characteristic curves and area under the curve for each biomarker individually and each weighted linear combination of relevant biomarkers. The best model to predict lesional activity was selected as that minimizing the Akaike information criterion. In this cohort, 11 subjects experienced symptomatic lesional hemorrhagic expansion (5 bleeds and 10 lesional growths) within a year after the blood draw. Subjects had lower soluble CD14 (cluster of differentiation 14; P=0.05), IL (interleukin)-6 (P=0.04), and VEGF (vascular endothelial growth factor; P=0.0003) levels along with higher plasma levels of IL-1? (P=0.008) and soluble ROBO4 (roundabout guidance receptor 4; P=0.03). Among the 31 weighted linear combinations of these 5 biomarkers, the best model (with the lowest Akaike information criterion value, 25.3) was the weighted linear combination including soluble CD14, IL-1?, VEGF, and soluble ROBO4, predicting a symptomatic hemorrhagic expansion with a sensitivity of 86% and specificity of 88% (area under the curve, 0.90; P<0.0001). We then validated our best model in the second sequential independent cohort (N=28). CONCLUSIONS:This is the first study reporting a predictive association between plasma biomarkers and subsequent cerebral cavernous malformation disease clinical activity. This may be applied in clinical prognostication and stratification of cases in clinical trials.