Biomarkers of Cavernous Angioma with Symptomatic Hemorrhage (CASH) [small RNA-seq]
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ABSTRACT:
PROVIDER: PRJNA534220 | ENA |
REPOSITORIES: ENA
Dataset's files
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| SRR8944250.fastq.gz | Fastqsanger.gz | |||
| SRR8944251.fastq.gz | Fastqsanger.gz | |||
| SRR8944252.fastq.gz | Fastqsanger.gz | |||
| SRR8944253.fastq.gz | Fastqsanger.gz | |||
| SRR8944254.fastq.gz | Fastqsanger.gz |
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Project description:Background: Cerebral cavernous angiomas with a symptomatic hemorrhage (CASH) have a high-risk of recurrent hemorrhage and serious morbidity. Methods: Eighteen plasma molecules with postulated mechanistic roles in cavernous angioma (CA) pathobiology were investigated in 114 patients and 12 healthy subjects. The diagnostic biomarker of a CASH in the prior year was derived as minimizing the Akaike Information Criterion (AIC) and validated using machine-learning, and then compared to the prognostic CASH biomarker predicting bleeding in the subsequent year. Both biomarkers were longitudinally followed in a subset of cases. The biomarkers were queried in the transcriptome of human lesional micro-dissected neurovascular units (NVUs) and in relation to plasma miRNAs from CASH and non-CASH patients. Results: The diagnostic CASH biomarker included a weighted combination of four molecules (sCD14, VEGF, CRP, and IL-10) distinguishing CASH patients with 76% sensitivity and 80% specificity (p=0.0003). The prognostic CASH biomarker included two of these molecules (sCD14 and VEGF) and two others (IL-1β and sROBO-4) was confirmed to predict a bleed in the subsequent year, with 83% sensitivity and 93% specificity (p=0.001). Genes associated with the diagnostic and prognostic CASH biomarkers were differentially expressed in CASH lesional NVUs. Thirteen miRNAs were also differentially expressed in the plasma of CASH patients compared to non-CASH. Conclusion: There are shared and unique biomarkers of recent symptomatic hemorrhage and of future bleeding in CA, and are mechanistically linked to the lesional transcriptome and miRNA regulation. The biomarkers may be applied for risk stratification in clinical trials and developed as a tool in clinical practice.
2019-05-13 | GSE130174 | GEO
Project description:Background: Cerebral cavernous angiomas with a symptomatic hemorrhage (CASH) have a high-risk of recurrent hemorrhage and serious morbidity. Methods: Eighteen plasma molecules with postulated mechanistic roles in cavernous angioma (CA) pathobiology were investigated in 114 patients and 12 healthy subjects. The diagnostic biomarker of a CASH in the prior year was derived as minimizing the Akaike Information Criterion (AIC) and validated using machine-learning, and then compared to the prognostic CASH biomarker predicting bleeding in the subsequent year. Both biomarkers were longitudinally followed in a subset of cases. The biomarkers were queried in the transcriptome of human lesional micro-dissected neurovascular units (NVUs) and in relation to plasma miRNAs from CASH and non-CASH patients. Results: The diagnostic CASH biomarker included a weighted combination of four molecules (sCD14, VEGF, CRP, and IL-10) distinguishing CASH patients with 76% sensitivity and 80% specificity (p=0.0003). The prognostic CASH biomarker included two of these molecules (sCD14 and VEGF) and two others (IL-1β and sROBO-4) was confirmed to predict a bleed in the subsequent year, with 83% sensitivity and 93% specificity (p=0.001). Genes associated with the diagnostic and prognostic CASH biomarkers were differentially expressed in CASH lesional NVUs. Thirteen miRNAs were also differentially expressed in the plasma of CASH patients compared to non-CASH. Conclusion: There are shared and unique biomarkers of recent symptomatic hemorrhage and of future bleeding in CA, and are mechanistically linked to the lesional transcriptome and miRNA regulation. The biomarkers may be applied for risk stratification in clinical trials and developed as a tool in clinical practice.
2019-05-13 | GSE130175 | GEO
Project description:Biomarkers of Cavernous Angioma with Symptomatic Hemorrhage (CASH)
| PRJNA534216 | ENA
Project description:Biomarkers of Cavernous Angioma with Symptomatic Hemorrhage (CASH) [RNA-seq]
| PRJNA534219 | ENA
Project description:BACKGROUNDCerebral cavernous angiomas (CAs) with a symptomatic hemorrhage (CASH) have a high risk of recurrent hemorrhage and serious morbidity.METHODSEighteen plasma molecules with mechanistic roles in CA pathobiology were investigated in 114 patients and 12 healthy subjects. The diagnostic biomarker of a CASH in the prior year was derived as that minimizing the Akaike information criterion and validated using machine learning, and was compared with the prognostic CASH biomarker predicting bleeding in the subsequent year. Biomarkers were longitudinally followed in a subset of cases. The biomarkers were queried in the lesional neurovascular unit (NVU) transcriptome and in plasma miRNAs from CASH and non-CASH patients.RESULTSThe diagnostic CASH biomarker included a weighted combination of soluble CD14 (sCD14), VEGF, C-reactive protein (CRP), and IL-10 distinguishing CASH patients with 76% sensitivity and 80% specificity (P = 0.0003). The prognostic CASH biomarker (sCD14, VEGF, IL-1β, and sROBO-4) was confirmed to predict a bleed in the subsequent year with 83% sensitivity and 93% specificity (P = 0.001). Genes associated with diagnostic and prognostic CASH biomarkers were differentially expressed in CASH lesional NVUs. Thirteen plasma miRNAs were differentially expressed between CASH and non-CASH patients.CONCLUSIONShared and unique biomarkers of recent symptomatic hemorrhage and of future bleeding in CA are mechanistically linked to lesional transcriptome and miRNA. The biomarkers may be applied for risk stratification in clinical trials and developed as a tool in clinical practice.FUNDINGNIH, William and Judith Davis Fund in Neurovascular Surgery Research, Be Brave for Life Foundation, Safadi Translational Fellowship, Pritzker School of Medicine, and Sigrid Jusélius Foundation.
| S-EPMC6629090 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2019-05-13 | GSE130176 | GEO
Project description:BackgroundCerebral 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.ObjectiveTo 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.MethodsAdditional 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 outcomesWith 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.DiscussionThe 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.
| S-EPMC7884145 | biostudies-literature
Project description:Microbiome signatures of diagnosis and aggressiveness of a neurovascular disease, cavernous angioma
| PRJEB37514 | ENA
Project description:Microbiome signatures of diagnosis and aggressiveness of a neurovascular disease, cavernous angioma
| PRJEB35505 | ENA
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.
| S-EPMC5993629 | biostudies-literature