RESUMO
Cerebral arteriovenous malformations (AVMs) are common vascular malformations, which may result in hemorrhagic strokes and neurological deficits. Bone morphogenetic protein (BMP) and Notch signaling are both involved in the development of cerebral AVMs, but the cross-talk between the two signaling pathways is poorly understood. Here, we show that deficiency of matrix Gla protein (MGP), a BMP inhibitor, causes induction of Notch ligands, dysregulation of endothelial differentiation, and the development of cerebral AVMs in MGP null (Mgp(-/-)) mice. Increased BMP activity due to the lack of MGP induces expression of the activin receptor-like kinase 1, a BMP type I receptor, in cerebrovascular endothelium. Subsequent activation of activin receptor-like kinase 1 enhances expression of Notch ligands Jagged 1 and 2, which increases Notch activity and alters the expression of Ephrin B2 and Ephrin receptor B4, arterial and venous endothelial markers, respectively. Reducing the expression of Jagged 1 and 2 in the Mgp(-/-) mice by crossing them with Jagged 1 or 2 deficient mice reduces Notch activity, normalizes endothelial differentiation, and prevents cerebral AVMs, but not pulmonary or renal AVMs. Our results suggest that Notch signaling mediates and can modulate changes in BMP signaling that lead to cerebral AVMs.
Assuntos
Proteínas Adaptadoras de Transdução de Sinal/metabolismo , Proteínas de Ligação ao Cálcio/deficiência , Proteínas de Ligação ao Cálcio/metabolismo , Proteínas da Matriz Extracelular/deficiência , Guanilato Quinases/metabolismo , Peptídeos e Proteínas de Sinalização Intercelular/metabolismo , Malformações Arteriovenosas Intracranianas/etiologia , Malformações Arteriovenosas Intracranianas/prevenção & controle , Proteínas de Membrana/metabolismo , Receptores Notch/metabolismo , Análise de Variância , Animais , Proteínas Morfogenéticas Ósseas/antagonistas & inibidores , Proteínas de Ligação ao Cálcio/genética , Diferenciação Celular/fisiologia , Células Endoteliais/fisiologia , Efrina-B2/metabolismo , Proteínas da Matriz Extracelular/genética , Deleção de Genes , Immunoblotting , Proteína Jagged-1 , Proteína Jagged-2 , Camundongos , Camundongos Knockout , RNA Interferente Pequeno/genética , Reação em Cadeia da Polimerase em Tempo Real , Receptores da Família Eph/metabolismo , Proteínas Serrate-Jagged , Microtomografia por Raio-X , Proteína de Matriz GlaRESUMO
RATIONALE: Vascular calcification is a regulated process that involves osteoprogenitor cells and frequently complicates common vascular disease, such as atherosclerosis and diabetic vasculopathy. However, it is not clear whether the vascular endothelium has a role in contributing osteoprogenitor cells to the calcific lesions. OBJECTIVE: To determine whether the vascular endothelium contributes osteoprogenitor cells to vascular calcification. METHODS AND RESULTS: In this study, we use 2 mouse models of vascular calcification, mice with gene deletion of matrix Gla protein, a bone morphogenetic protein (BMP)-inhibitor, and Ins2Akita/+ mice, a diabetes model. We show that enhanced BMP signaling in both types of mice stimulates the vascular endothelium to contribute osteoprogenitor cells to the vascular calcification. The enhanced BMP signaling results in endothelial-mesenchymal transitions and the emergence of multipotent cells, followed by osteoinduction. Endothelial markers colocalize with multipotent and osteogenic markers in calcified arteries by immunostaining and fluorescence-activated cell sorting. Lineage tracing using Tie2-Gfp transgenic mice supports an endothelial origin of the osteogenic cells. Enhancement of matrix Gla protein expression in Ins2Akita/+ mice, as mediated by an Mgp transgene, limits the generation of multipotent cells. Moreover, matrix Gla protein-depleted human aortic endothelial cells in vitro acquire multipotency rendering the cells susceptible to osteoinduction by BMP and high glucose. CONCLUSIONS: Our data suggest that the endothelium is a source of osteoprogenitor cells in vascular calcification that occurs in disorders with high BMP activation, such as deficiency of BMP-inhibitors and diabetes mellitus.
Assuntos
Calcinose/fisiopatologia , Proteínas de Ligação ao Cálcio/fisiologia , Transdiferenciação Celular/fisiologia , Angiopatias Diabéticas/fisiopatologia , Células Endoteliais/patologia , Endotélio Vascular/fisiopatologia , Proteínas da Matriz Extracelular/fisiologia , Insulina/fisiologia , Células-Tronco Multipotentes/patologia , Doenças Vasculares/fisiopatologia , Animais , Aorta/citologia , Proteínas de Ligação ao Cálcio/deficiência , Proteínas de Ligação ao Cálcio/genética , Linhagem da Célula , Células Cultivadas/efeitos dos fármacos , Diabetes Mellitus Tipo 2/genética , Angiopatias Diabéticas/genética , Modelos Animais de Doenças , Endotélio Vascular/patologia , Proteínas da Matriz Extracelular/deficiência , Proteínas da Matriz Extracelular/genética , Glucose/farmacologia , Heterozigoto , Humanos , Insulina/genética , Camundongos , Camundongos Endogâmicos C57BL , Camundongos Knockout , Camundongos Transgênicos , Proteínas dos Microfilamentos/fisiologia , Proteínas Musculares/fisiologia , RNA Interferente Pequeno/farmacologia , Receptor TIE-2/genética , Proteínas Recombinantes de Fusão/fisiologia , Transdução de Sinais , Proteína de Matriz GlaRESUMO
The importance of morphogenetic proteins (BMPs) and their antagonists in vascular development is increasingly being recognized. BMP-4 is essential for angiogenesis and is antagonized by matrix Gla protein (MGP) and crossveinless 2 (CV2), both induced by the activin receptor like-kinase 1 (ALK1) when stimulated by BMP-9. In this study, however, we show that CV2 preferentially binds and inhibits BMP-9 thereby providing strong feedback inhibition for BMP-9/ALK1 signaling rather than for BMP-4/ALK2 signaling. CV2 disrupts complex formation involving ALK2, ALK1, BMP-4, and BMP-9 required for the induction of both BMP antagonists. It also limits VEGF expression, proliferation, and tube formation in ALK1-expressing endothelial cells. In vivo, CV2 deficiency translates into a dysregulation of vascular BMP signaling, resulting in an abnormal endothelium with increased endothelial cellularity and expression of lineage markers for mature endothelial cells. Thus, mutual regulation by BMP-9 and CV2 is essential in regulating the development of the vascular endothelium.
Assuntos
Proteínas de Transporte/fisiologia , Endotélio Vascular/metabolismo , Fator 2 de Diferenciação de Crescimento/antagonistas & inibidores , Fator 2 de Diferenciação de Crescimento/metabolismo , Receptores de Ativinas Tipo I/antagonistas & inibidores , Receptores de Ativinas Tipo I/metabolismo , Receptores de Activinas Tipo II/antagonistas & inibidores , Receptores de Activinas Tipo II/metabolismo , Animais , Proteína Morfogenética Óssea 4/metabolismo , Proteínas de Transporte/genética , Proteínas de Transporte/metabolismo , Bovinos , Células Cultivadas , Endotélio Vascular/efeitos dos fármacos , Endotélio Vascular/fisiologia , Regulação da Expressão Gênica/efeitos dos fármacos , Fator 2 de Diferenciação de Crescimento/farmacologia , Humanos , Camundongos , Camundongos Endogâmicos C57BL , Camundongos Transgênicos , Ligação Proteica/efeitos dos fármacos , Especificidade por SubstratoRESUMO
OBJECTIVES: Asthma is a heterogenous condition with significant diagnostic complexity, including variations in symptoms and temporal criteria. The disease can be difficult for clinicians to diagnose accurately. Properly identifying asthma patients from the electronic health record is consequently challenging as current algorithms (computable phenotypes) rely on diagnostic codes (e.g., International Classification of Disease, ICD) in addition to other criteria (e.g., inhaler medications)-but presume an accurate diagnosis. As such, there is no universally accepted or rigorously tested computable phenotype for asthma. METHODS: We compared two established asthma computable phenotypes: the Chicago Area Patient-Outcomes Research Network (CAPriCORN) and Phenotype KnowledgeBase (PheKB). We established a large-scale, consensus gold standard (n = 1,365) from the University of California, Los Angeles Health System's clinical data warehouse for patients 5 to 17 years old. Results were manually reviewed and predictive performance (positive predictive value [PPV], sensitivity/specificity, F1-score) determined. We then examined the classification errors to gain insight for future algorithm optimizations. RESULTS: As applied to our final cohort of 1,365 expert-defined gold standard patients, the CAPriCORN algorithms performed with a balanced PPV = 95.8% (95% CI: 94.4-97.2%), sensitivity = 85.7% (95% CI: 83.9-87.5%), and harmonized F1 = 90.4% (95% CI: 89.2-91.7%). The PheKB algorithm was performed with a balanced PPV = 83.1% (95% CI: 80.5-85.7%), sensitivity = 69.4% (95% CI: 66.3-72.5%), and F1 = 75.4% (95% CI: 73.1-77.8%). Four categories of errors were identified related to method limitations, disease definition, human error, and design implementation. CONCLUSION: The performance of the CAPriCORN and PheKB algorithms was lower than previously reported as applied to pediatric data (PPV = 97.7 and 96%, respectively). There is room to improve the performance of current methods, including targeted use of natural language processing and clinical feature engineering.