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.
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.
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.
