info:eu-repo/semantics/article
Current model systems for the study of preeclampsia
Fecha
2018-02-07Registro en:
1535-3702
Autor
Martínez Fierro, Margarita de la Luz
Hernández Delgadillo, Gloria Patricia
Flores Morales, Virginia
Cardenas Vargas, Edith
Mercado Reyes, Marisa
Rodríguez Sánchez, Iram Pablo
Delgado Enciso, Iván
Galván Tejada, Carlos Eric
Galván Tejada, Jorge Issac
Celaya Padilla, José María
Garza Veloz, Idalia
Institución
Resumen
Preeclampsia (PE) is a pregnancy complex disease, distinguished by high blood pressure and
proteinuria, diagnosed after the 20th gestation week. Depending on the values of blood pressure,
urine protein concentrations, symptomatology, and onset of disease there is a wide
range of phenotypes, from mild forms developing predominantly at the end of pregnancy to
severe forms developing in the early stage of pregnancy. In the worst cases severe forms of
PE could lead to systemic endothelial dysfunction, eclampsia, and maternal and/or fetal
death. Worldwide the fetal morbidity and mortality related to PE is calculated to be around
8% of the total pregnancies. PE still being an enigma regarding its etiology and pathophysiology,
in general a deficient trophoblast invasion during placentation at first stage of pregnancy, in combination with maternal conditions are accepted as a cause of endothelial dysfunction, inflammatory alterations and appearance of symptoms. Depending on the PE multifactorial origin, several in vitro, in vivo,andin silico models have been used to evaluate the PE pathophysiology as well as to identify or test biomarkers predicting, diagnosing or prognosing the syndrome. This review focuses on the most common models used for the study of PE, including those related to placental development, abnormal trophoblast invasion, uteroplacental ischemia, angiogenesis, oxygen deregulation, and immune response to maternal–fetal interactions. The advances in mathematical and computational modeling of metabolic network behavior, gene prioritization, the protein–protein interaction network, the genetics of PE, and the PE prediction/classification are discussed. Finally, the potential of these models to enable understanding of PE pathogenesis and to evaluate new preventative and therapeutic approaches in the management of PE are also highlighted.