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

Romuald Girard; Yan Li; Agnieszka Stadnik; Robert Shenkar; Nicholas Hobson; Sharbel Romanos; Abhinav Srinath; Thomas Moore; Rhonda Lightle; Abdallah Shkoukani; Amy Akers; Timothy Carroll; Gregory A. Christoforidis; James I. Koenig; Cornelia Lee; Kristina Piedad; Steven M. Greenberg; Helen Kim; Kelly D. Flemming; Yuan Ji; Issam A. Awad

doi:10.1093/neuros/nyaa478

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

Romuald Girard, Yan Li, Agnieszka Stadnik, Robert Shenkar, Nicholas Hobson, Sharbel Romanos, Abhinav Srinath, Thomas Moore, Rhonda Lightle, Abdallah Shkoukani, Amy Akers, Timothy Carroll, Gregory A. Christoforidis, James I. Koenig, Cornelia Lee, Kristina Piedad, Steven M. Greenberg, Helen Kim, Kelly D. Flemming, Yuan JiIssam A. Awad

Neurology

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Pages (from-to)	686-697
Number of pages	12
Journal	Neurosurgery
Volume	88
Issue number	3
DOIs	https://doi.org/10.1093/neuros/nyaa478
State	Published - Mar 1 2021

Keywords

Biomarkers
Cavernous angioma
Cavernous angioma with symptomatic hemorrhage (CASH)
Cerebral cavernous malformation (CCM)
Machine learning
Plasma
QSM
Symptomatic hemorrhage

ASJC Scopus subject areas

Surgery
Clinical Neurology

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10.1093/neuros/nyaa478

Cite this

Girard, R., Li, Y., Stadnik, A., Shenkar, R., Hobson, N., Romanos, S., Srinath, A., Moore, T., Lightle, R., Shkoukani, A., Akers, A., Carroll, T., Christoforidis, G. A., Koenig, J. I., Lee, C., Piedad, K., Greenberg, S. M., Kim, H., Flemming, K. D., ... Awad, I. A. (2021). A Roadmap for Developing Plasma Diagnostic and Prognostic Biomarkers of Cerebral Cavernous Angioma with Symptomatic Hemorrhage (CASH). Neurosurgery, 88(3), 686-697. https://doi.org/10.1093/neuros/nyaa478

Girard, R, Li, Y, Stadnik, A, Shenkar, R, Hobson, N, Romanos, S, Srinath, A, Moore, T, Lightle, R, Shkoukani, A, Akers, A, Carroll, T, Christoforidis, GA, Koenig, JI, Lee, C, Piedad, K, Greenberg, SM, Kim, H, Flemming, KD, Ji, Y & Awad, IA 2021, 'A Roadmap for Developing Plasma Diagnostic and Prognostic Biomarkers of Cerebral Cavernous Angioma with Symptomatic Hemorrhage (CASH)', Neurosurgery, vol. 88, no. 3, pp. 686-697. https://doi.org/10.1093/neuros/nyaa478

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title = "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.",

keywords = "Biomarkers, Cavernous angioma, Cavernous angioma with symptomatic hemorrhage (CASH), Cerebral cavernous malformation (CCM), Machine learning, Plasma, QSM, Symptomatic hemorrhage",

author = "Romuald Girard and Yan Li and Agnieszka Stadnik and Robert Shenkar and Nicholas Hobson and Sharbel Romanos and Abhinav Srinath and Thomas Moore and Rhonda Lightle and Abdallah Shkoukani and Amy Akers and Timothy Carroll and Christoforidis, {Gregory A.} and Koenig, {James I.} and Cornelia Lee and Kristina Piedad and Greenberg, {Steven M.} and Helen Kim and Flemming, {Kelly D.} and Yuan Ji and Awad, {Issam A.}",

note = "Publisher Copyright: {\textcopyright} 2021 Congress of Neurological Surgeons 2021.",

year = "2021",

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doi = "10.1093/neuros/nyaa478",

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TY - JOUR

T1 - A Roadmap for Developing Plasma Diagnostic and Prognostic Biomarkers of Cerebral Cavernous Angioma with Symptomatic Hemorrhage (CASH)

AU - Girard, Romuald

AU - Li, Yan

AU - Stadnik, Agnieszka

AU - Shenkar, Robert

AU - Hobson, Nicholas

AU - Romanos, Sharbel

AU - Srinath, Abhinav

AU - Moore, Thomas

AU - Lightle, Rhonda

AU - Shkoukani, Abdallah

AU - Akers, Amy

AU - Carroll, Timothy

AU - Christoforidis, Gregory A.

AU - Koenig, James I.

AU - Lee, Cornelia

AU - Piedad, Kristina

AU - Greenberg, Steven M.

AU - Kim, Helen

AU - Flemming, Kelly D.

AU - Ji, Yuan

AU - Awad, Issam A.

PY - 2021/3/1

Y1 - 2021/3/1

N2 - 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.

AB - 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.

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KW - Cavernous angioma

KW - Cavernous angioma with symptomatic hemorrhage (CASH)

KW - Cerebral cavernous malformation (CCM)

KW - Machine learning

KW - Plasma

KW - QSM

KW - Symptomatic hemorrhage

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

Abstract

Keywords

ASJC Scopus subject areas

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