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Introduction: Cavernous Angiomas (CAs) are vascular malformations characterized by clusters of blood-filled capillary spaces lined by “leaky” endothelium. While mutations in endothelial cells have long been recognized as necessary for lesion genesis, there is evidence of inflammation, response to hypoxia, and non-endothelial autonomous cell effects driving pathogenesis. Disrupted gene expression in the CA neurovascular unit (NVU) has been described but the contribution of each cell type has not been previously investigated. Methods: Six CA and four control brain samples were collected and frozen during surgical resection. The endothelial cells, pericytes, and neuroglia (astrocytes and neurons) were sorted, and the RNA was extracted and sequenced. The differentially expressed genes (DEGs) were identified ( p p p p Results: In endothelial cells, 362 DEGs were identified contributing to 54 enriched IPA pathways. In addition, 484 DEGs were found in pericytes and 50 IPA pathways were identified. The common functions between these two cell types were related to angiogenesis, extracellular matrix organization, cell adhesion, and platelet activation, while the function related to response to hypoxia was only shown in pericytes. Finally, 242 DEGs and 52 IPA pathways were identified in neuroglia cells. The associated pathway functions were related to inflammatory response and cell adhesion. The IPA results were further confirmed by the GO term and KEGG pathway analyses. Conclusion: We confirm that disrupted genes related to angiogenesis, blood-brain barrier integrity, cell adhesion and platelet activation in the CA lesion involve endothelial cells and pericytes primarily. Pericytes are particularly associated with disrupted genes related to response to hypoxia, while neuroglia is associated with greater gene disruptions related to inflammation. These results motivate novel mechanistic hypotheses regarding non-endothelial cell contributions to lesion pathobiology.

Background: Cerebral microbleeds (CMBs) are manifestations of age-related microangiopathies associated with an increased risk of hemorrhagic stroke and cognitive decline. The pathophysiology of this age-related breakdown of the neurovascular unit remain unclear. Understanding CMB cellular architecture is needed for gene, pathway, and mechanism analyses, to pave the way for biomarker and therapeutic development. Herein, we aim to systematically describe histopathological changes in the CMB lesional milieu. Methods: Eight CMBs, along with contralateral non-lesional tissue, were identified by gross appearance at autopsy by a neuropathologist. Samples were first stained with H&E, then Prussian blue for non-heme iron, to localize the lesion. This was followed by multiplex fluorescence staining of β-amyloid and individual cell types including astrocytes (GFAP + ), macrophages (CD163 + /Iba1 + ), microglia (CD163 - /Iba1 + ), B-cells (CD20 + ), T-cells (CD3 + ), and endothelium (CD31 + ). The cell types within the lesional milieu, defined as 200μm from the periphery of the CMB, were quantified using QuPath. Astrocyte and microglia morphology were assessed via fluorescence imaging. Results: One CMB contained dilated capillaries, 2 contained lipohyalinized arterioles, and 4 contained dystrophic arterioles due to amyloid angiopathy. Astrocytes and macrophages showed higher normalized cell counts in all CMB tissues compared with controls ( p and p , respectively). Astrocytes in 7 of 8 CMB milieux showed reactive morphological changes, including larger cell bodies with peripheral nuclei. Microglia had higher normalized cell counts in 4 CMB tissues, with senescence-associated amoeboid, as well as ramified, reactive morphologies. The lesional milieu also showed higher counts of B-cells in 7 CMB tissues and T-cells in 3 CMB tissues when compared with controls. Conclusions: We provide the first description of the cellular architecture of the CMB and the associated lesional milieu. Despite heterogeneity of disrupted vasculature, there are common features of glial reactive changes and inflammation in CMBs. These results offer a basis for additional study of the CMB transcriptome and individual roles of respective cell types in CMB pathology.

Introduction: Age-related cerebral microbleeds (CMBs) are vascular changes associated with an increased risk of intracerebral hemorrhage (ICH) and neurocognitive decline. CMBs share a strikingly similar appearance on MRI to cerebral cavernous malformations (CCMs), which are leaky capillary lesions predisposing patients to brain bleeding. Our team had previously shown increased vascular permeability in CCM and in the brain of older subjects, with common circulating biomarkers of angiogenesis and inflammation. We examine here whether vascular permeability is greater in the aging brain harboring CBMs. Methods: Dynamic Contrast-Enhanced Quantitative Perfusion (DCEQP) MRI, which assesses vascular permeability, was acquired for 7 patients with CMBs (>50 years old), 10 old (>50 years old), and 9 young (18-30 years old) healthy subjects without CMBs. Cases with active brain disease, stroke or seizure in the prior year were excluded. DCEQP scans were co-registered onto their respective T1-weighted images, normalized using the Desikan-Killiany atlas, and finally segmented into white and gray matter within frontal, temporal, parietal, and occipital lobes. The mean permeability was calculated within each segmented area, and values were compared between the 3 groups of interest. Results: Increased permeability was observed within the frontal white and gray matter as well as the parietal gray matter of patients with CMBs compared to age matched old healthy controls (both: p Conclusion: We confirm that the human brain exhibits increased vascular permeability with aging, and this is more pronounced in brains harboring CMBs. This may provide insight into the pathogenesis of CMBs, potentially reflecting end stage age-related failure of the blood brain barrier, associated with frank bleeding. These results offer a starting point for the development of diagnostic and prognostic imaging biomarkers of CMBs, which can help stratify patients at higher risk of future ICH and cognitive decline.

Background: Increases in mean lesional iron content (≥6%) measurement by QSM and vascular permeability (≥40%) assessed by DCEQP MRI have been associated with new bleeding, and are used as monitoring biomarkers in NINDS funded 1st clinical trial of pharmacotherapy (clinicaltrials.gov NCT02603328) in cavernous angiomas with symptomatic hemorrhage (CASH). Plasma protein levels previously associated with CASH in diagnostic and prognostic contexts have never been compared to lesional QSM and DCEQP in the same subjects. Methods: Plasma samples and MRI sequences were simultaneously acquired during 1 year-epochs of prospective follow-up of CASH patients. Plasma levels of 16 proteins were assayed by ELISA and correlated with lesional QSM and DCEQP during the same epochs. Univariate correlations were followed by multivariate analyses combining multiple protein levels to minimize Akaike Information Criterion (AIC) and increase R 2 . Accuracy (AUC on receiver operating curves) and sum of squared error (SSE) are reported for associations achieving statistical significance with FDR correction. Results: None of the proteins individually correlated with QSM/DCEQP (continuous or categorical). Relative change of angiopoietin2, and absolute change of the combination (endoglin+IL1B+IL16) had the highest accuracy (AUC 78.7%, SD 0.062 and 98.4%, SD 0.013 respectively) for lesional QSM increase ≥6%. Relative change of endoglin+IL1B, and absolute change of angiopoetin2+endoglin+thromobomodulin+VEGF, had the highest accuracy (AUC 64.6%, SD 0.057 and 93.2%, SD 0.040 respectively) for lesional DCEQP increase ≥40%. Relative change in angiopoetin1 had the lowest SSE (8.87) with QSM change as a continuous variable, and relative change in lipopolysaccharide binding protein had the lowest SSE (469.06) with DCEQP change as continuous variable. Conclusion: Circulating proteins reflect changes in lesional iron content and permeability in CASH during prospective follow-up. Results are a proof of concept that blood tests could replace more complex and costly imaging biomarkers in the monitoring of hemorrhage in cavernous angiomas. Additional mechanistic plasma molecules (miRNAs and metabolites) may further enhance the accuracy of these monitoring biomarkers.

Introduction: Cavernous Angioma (CA) is a hemorrhagic neurovascular disease characterized by either a familial form with autosomal dominant germline mutations in one of three CCM genes or a sporadic form with somatic mutations of the same genes. Circulating proteins have been previously investigated as possible diagnostic and prognostic biomarkers of disease activity, with up to 86% and 88% sensitivity and specificity, respectively. We hypothesize that differentially expressed (DE) plasma microRNAs and metabolites in CA patients can be integrated with plasma proteins to increase the sensitivity and specificity of circulating CA biomarkers. Methods: Mechanistically relevant homologous DE miRNAs were identified between familial CA patients and preclinical murine models and validated in an independent cohort of patients using real time qPCR. In conjunction, DE metabolites were determined in CA patients using liquid-chromatography mass spectrometry. The interactions of these metabolites with the previously established CA transcriptome, proteome, and microbiome were queried to assess for mechanistic relevance. Optimal diagnostic models of proteins, DE miRNAs, and DE metabolites alone were next established. Plasma metabolites and miRNAs were then separately integrated with protein, using a machine learning-implemented, Bayesian approach to develop diagnostic CA biomarkers. Results: The optimal diagnostic biomarker model with only DE miRNAs performed at up to 68%, while proteins and metabolites achieved up to 68%, and 82% accuracy respectively. The optimal combination for proteins with miRNAs improved the diagnostic association of familial-CA disease to up to 94.7% sensitivity and 100% specificity. Integrating metabolites and proteins improved the diagnosis of CA disease and its clinical manifestations to 100% sensitivity and 100% specificity. Conclusion: Combining plasma proteins with miRNAs or metabolites can improve diagnostic accuracy of CA disease and its disease characteristics above any single molecular modality alone. Future studies should incorporate proteins, miRNAs, and metabolites to further increase diagnostic accuracy, and validate these in a larger cohort with control for demographic and disease features.

Introduction: Hemorrhagic microangiopathies (HMAs) are age-related cerebral microbleeds associated with an increased risk of cognitive decline and intracerebral hemorrhage (ICH). HMAs share a strikingly similar appearance on MRI to cerebral cavernous malformations (CCMs), which are clusters of leaky capillaries predisposing patients to brain bleeding. We hypothesize that HMAs and CCMs share common dysregulated genes and pathways reflecting hemorrhagic failure of the neurovascular unit. Thus, biomarkers developed in CCM may be applicable to HMA. Methods: Extracted mRNA from 5 HMA lesions collected at autopsy along with 3 non-lesional brain sections from the same patients was sequenced, and differentially expressed genes (DEGs) were identified. Enrichment analyses were performed using the Reactome database. Pathways related to postulated mechanisms of HMA were identified, as well as those overlapping pathways with a previously published CCM transcriptome. Dynamic Contrast-Enhanced Quantitative Perfusion (DCEQP) and Quantitative Susceptibility Mapping (QSM) MRIs were performed on 11 HMA patients, 12 age-matched, and 22 young healthy subjects assessing vascular permeability and iron content, as previously done in CCM. Mean permeability and QSM values were calculated for white and gray matter in the frontal, temporal, parietal, and occipital lobes. Results: Differential analyses of the HMA transcriptome identified 376 DEGs ( p p Conclusion: Transcriptomic commonalities suggest that similar pipelines for plasma and imaging biomarkers developed in CCM research may be adapted for risk assessment and monitoring of HMA. These will help improve the understanding of HMA pathogenesis and assist in patient management, offering a large public health impact.

BACKGROUND Cerebral cavernous angioma (CA) is a capillary vasculopathy affecting more than a million Americans with a small fraction of cases demonstrating lesional bleed or growth with major clinical sequelae. Perfusion and permeability are fundamental features of CA pathophysiology, but their role as prognostic biomarkers is unclear. PURPOSE To investigate whether perfusion or permeability lesional descriptors derived from dynamic contrast-enhanced quantitative perfusion (DCEQP) magnetic resonance imaging (MRI) can predict subsequent lesional bleed/growth in the year following imaging. STUDY TYPE Single-site case-controlled study. SUBJECTS Two hundred and five consecutively enrolled patients (63.4% female). FIELD STRENGTH/SEQUENCE Three-Tesla/T1 -mapping with contrast-enhanced dynamic two-dimensional (2D) spoiled gradient recalled acquisition (SPGR) sequences. ASSESSMENT Prognostic associations with bleed/growth (present or absent) in the following year were assessed in 745 CA lesions evaluated by DCEQP in the 205 patients in relation to lesional descriptors calculated from permeability and perfusion maps. A subgroup of 30 cases also underwent peripheral blood collection at the time of DCEQP scans and assays of plasma levels of soluble CD14, IL-1β, VEGF, and soluble ROBO4 proteins, whose weighted combination had been previously reported in association with future CA bleeding. STATISTICAL TESTS Mann-Whitney U-test for univariate analyses. Logistic regression models minimizing the Bayesian information criterion (BIC), testing sensitivity and specificity (receiver operating characteristic curves) of weighted combinations of parameters. RESULTS The best prognostic biomarker for lesional bleed or growth included brainstem lesion location, mean lesional permeability, and low-value perfusion cluster mean (BIC = 201.5, sensitivity = 77%, specificity = 72%, P