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Br J Haematol ; 174(5): 786-98, 2016 09.
Artigo em Inglês | MEDLINE | ID: mdl-27161653

RESUMO

Sickle cell anaemia (SCA) is the most frequent genetic haemoglobinopathy, which exhibits a highly variable clinical course characterized by hyper-coagulable and pro-inflammatory states, as well as endothelial dysfunction. Extracellular microvesicles are released into biological fluids and play a role in modifying the functional phenotype of target cells. We hypothesized that potential differences in plasma-derived extracellular microvesicles (EV) function and cargo from SCA patients may underlie divergent clinical trajectories. Plasma EV from SCA patients with mild, intermediate and severe clinical disease course were isolated, and primary endothelial cell cultures were exposed. Endothelial cell activation, monocyte adhesion, barrier disruption and exosome cargo (microRNA microarrays) were assessed. EV disrupted the endothelial barrier and induced expression of adhesion molecules and monocyte adhesion in a SCA severity-dependent manner compared to healthy children. Microarray approaches identified a restricted signature of exosomal microRNAs that readily distinguished severe from mild SCA, as well as from healthy children. The microRNA candidates were further validated using quantitative real time polymerase chain reaction assays, and revealed putative gene targets. Circulating exosomal microRNAs may play important roles in predicting the clinical course of SCA, and in delineation of individually tailored, mechanistically-based clinical treatment approaches of SCA patients in the near future.


Assuntos
Anemia Falciforme/patologia , Exossomos/patologia , MicroRNAs/análise , Adolescente , Anemia Falciforme/diagnóstico , Animais , Linhagem Celular , Micropartículas Derivadas de Células/patologia , Criança , Pré-Escolar , Exossomos/genética , Espaço Extracelular/química , Feminino , Humanos , Masculino , Camundongos , MicroRNAs/isolamento & purificação , Análise de Sequência com Séries de Oligonucleotídeos , Fenótipo , Prognóstico , Índice de Gravidade de Doença
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