Editorial for “Ensemble Learning for Early‐Response Prediction of Antidepressant Treatment in Major Depressive Disorder”

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

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

Biomarkers of cavernous angioma with symptomatic hemorrhage

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

Biomarkers of cavernous angioma with symptomatic hemorrhage

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

Permissive microbiome characterizes human subjects with a neurovascular disease cavernous angioma.

Cavernous angiomas (CA) are common vascular anomalies causing brain hemorrhage. Based on mouse studies, roles of gram-negative bacteria and altered intestinal homeostasis have been implicated in CA pathogenesis, and pilot study had suggested potential microbiome differences between non-CA and CA individuals based on 16S rRNA gene sequencing. We here assess microbiome differences in a larger cohort of human subjects with and without CA, and among subjects with different clinical features, and conduct more definitive microbial analyses using metagenomic shotgun sequencing. Relative abundance of distinct bacterial species in CA patients is shown, consistent with postulated permissive microbiome driving CA lesion genesis via lipopolysaccharide signaling, in humans as in mice. Other microbiome differences are related to CA clinical behavior. Weighted combinations of microbiome signatures and plasma inflammatory biomarkers enhance associations with disease severity and hemorrhage. This is the first demonstration of a sensitive and specific diagnostic microbiome in a human neurovascular disease

PIK3CA and CCM mutations fuel cavernomas through a cancer-like mechanism

Vascular malformations are thought to be monogenic disorders that result in dysregulated growth of blood vessels. In the brain, cerebral cavernous malformations (CCMs) arise owing to inactivation of the endothelial CCM protein complex, which is required to dampen the activity of the kinase MEKK31–4. Environmental factors can explain differences in the natural history of CCMs between individuals5, but why single CCMs often exhibit sudden, rapid growth, culminating in strokes or seizures, is unknown. Here we show that growth of CCMs requires increased signalling through the phosphatidylinositol-3-kinase (PI3K)–mTOR pathway as well as loss of function of the CCM complex. We identify somatic gain-of-function mutations in PIK3CA and loss-of-function mutations in the CCM complex in the same cells in a majority of human CCMs. Using mouse models, we show that growth of CCMs requires both PI3K gain of function and CCM loss of function in endothelial cells, and that both CCM loss of function and increased expression of the transcription factor KLF4 (a downstream effector of MEKK3) augment mTOR signalling in endothelial cells. Consistent with these findings, the mTORC1 inhibitor rapamycin effectively blocks the formation of CCMs in mouse models. We establish a three-hit mechanism analogous to cancer, in which aggressive vascular malformations arise through the loss of vascular ‘suppressor genes’ that constrain vessel growth and gain of a vascular ‘oncogene’ that stimulates excess vessel growth. These findings suggest that aggressive CCMs could be treated using clinically approved mTORC1 inhibitors

Plasma metabolites with mechanistic and clinical links to the neurovascular disease cavernous angioma

BackgroundCavernous angiomas (CAs) affect 0.5% of the population, predisposing to serious neurologic sequelae from brain bleeding. A leaky gut epithelium associated with a permissive gut microbiome, was identified in patients who develop CAs, favoring lipid polysaccharide producing bacterial species. Micro-ribonucleic acids along with plasma levels of proteins reflecting angiogenesis and inflammation were also previously correlated with CA and CA with symptomatic hemorrhage.MethodsThe plasma metabolome of CA patients and CA patients with symptomatic hemorrhage was assessed using liquid-chromatography mass spectrometry. Differential metabolites were identified using partial least squares-discriminant analysis (p < 0.05, FDR corrected). Interactions between these metabolites and the previously established CA transcriptome, microbiome, and differential proteins were queried for mechanistic relevance. Differential metabolites in CA patients with symptomatic hemorrhage were then validated in an independent, propensity matched cohort. A machine learning-implemented, Bayesian approach was used to integrate proteins, micro-RNAs and metabolites to develop a diagnostic model for CA patients with symptomatic hemorrhage.ResultsHere we identify plasma metabolites, including cholic acid and hypoxanthine distinguishing CA patients, while arachidonic and linoleic acids distinguish those with symptomatic hemorrhage. Plasma metabolites are linked to the permissive microbiome genes, and to previously implicated disease mechanisms. The metabolites distinguishing CA with symptomatic hemorrhage are validated in an independent propensity-matched cohort, and their integration, along with levels of circulating miRNAs, enhance the performance of plasma protein biomarkers (up to 85% sensitivity and 80% specificity).ConclusionsPlasma metabolites reflect CAs and their hemorrhagic activity. A model of their multiomic integration is applicable to other pathologies

Comprehensive transcriptome analysis of cerebral cavernous malformation across multiple species and genotypes

The purpose of this study was to determine important genes, functions, and networks contributing to the pathobiology of cerebral cavernous malformation (CCM) from transcriptomic analyses across 3 species and 2 disease genotypes. Sequencing of RNA from laser microdissected neurovascular units of 5 human surgically resected CCM lesions, mouse brain microvascular endothelial cells, Caenorhabditis elegans with induced Ccm gene loss, and their respective controls provided differentially expressed genes (DEGs). DEGs from mouse and C. elegans were annotated into human homologous genes. Cross-comparisons of DEGs between species and genotypes, as well as network and gene ontology (GO) enrichment analyses, were performed. Among hundreds of DEGs identified in each model, common genes and 1 GO term (GO:0051656, establishment of organelle localization) were commonly identified across the different species and genotypes. In addition, 24 GO functions were present in 4 of 5 models and were related to cell-to-cell adhesion, neutrophil-mediated immunity, ion transmembrane transporter activity, and responses to oxidative stress. We have provided a comprehensive transcriptome library of CCM disease across species and for the first time to our knowledge in Ccm1/Krit1 versus Ccm3/Pdcd10 genotypes. We have provided examples of how results can be used in hypothesis generation or mechanistic confirmatory studies

Additional file 1 of Transcriptomic signatures of individual cell types in cerebral cavernous malformation

Additional file 1: Supplemental Methods, Supplemental Results, Figure S1, Figure S2 and Table S1