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Maternal Serum Meteorin Levels and the Risk of Preeclampsia
Authors:María F Garcés  Elizabeth Sanchez  Luisa F Cardona  Elkin L Simanca  Iván González  Luis G Leal  José A Mora  Andrés Bedoya  Juan P Alzate  ángel Y Sánchez  Javier H Eslava-Schmalbach  Roberto Franco-Vega  Mario O Parra  Ariel I Ruíz—Parra  Carlos Diéguez  Rubén Nogueiras  Jorge E Caminos
Abstract:

Background

Meteorin (METRN) is a recently described neutrophic factor with angiogenic properties. This is a nested case-control study in a longitudinal cohort study that describes the serum profile of METRN during different periods of gestation in healthy and preeclamptic pregnant women. Moreover, we explore the possible application of METRN as a biomarker.

Methods and Findings

Serum METRN was measured by ELISA in a longitudinal prospective cohort study in 37 healthy pregnant women, 16 mild preeclamptic women, and 20 healthy non-pregnant women during the menstrual cycle with the aim of assessing serum METRN levels and its correlations with other metabolic parameters. Immunostaining for METRN protein was performed in placenta. A multivariate logistic regression model was proposed and a classifier model was formulated for predicting preeclampsia in early and middle pregnancy. The performance in classification was evaluated using measures such as sensitivity, specificity, and the receiver operating characteristic (ROC) curve. In healthy pregnant women, serum METRN levels were significantly elevated in early pregnancy compared to middle and late pregnancy. METRN levels are significantly lower only in early pregnancy in preeclamptic women when compared to healthy pregnant women. Decision trees that did not include METRN levels in the first trimester had a reduced sensitivity of 56% in the detection of preeclamptic women, compared to a sensitivity of 69% when METRN was included.

Conclusions

The joint measurements of circulating METRN levels in the first trimester and systolic blood pressure and weight in the second trimester significantly increase the probabilities of predicting preeclampsia.
Keywords:
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