MicroRNAs in maternal blood may predict development of preeclampsia

Small non-coding RNA molecules, called microRNAs (miRNAs), found and measured in the blood plasma of asymptomatic pregnant women may predict development of preeclampsia, a condition characterized by high blood pressure and abnormal kidney function that affects roughly 5 to 8 percent of all pregnancies.

Preeclampsia is responsible for a significant proportion of maternal and neonatal deaths, low birth weight and is a primary cause of premature birth.

The findings are reported in the May 19, 2020 issue of Cell Reports Medicine by researchers at University of California San Diego School of Medicine and Sera Prognostics, Inc., a Salt Lake City-based company that makes diagnostics tests for predicting the risk of premature birth.

The ability to identify pregnancies at high risk for developing preeclampsia would be of great value to patients and their doctors to better personalize prenatal care.

This would enable prompt detection and optimal management of pregnancies that develop preeclampsia. And the information could be used to better identify participants for research studies testing preventive therapies."

Louise Laurent, MD, PhD, Study Senior Author and Professor, Department of Obstetrics, Gynecology and Reproductive Sciences, UC San Diego School of Medicine

Small non-coding RNA molecules, called microRNAs (miRNAs), found and measured in the blood plasma of asymptomatic pregnant women may predict development of preeclampsia, a condition characterized by high blood pressure and abnormal kidney function that affects roughly 5 to 8 percent of all pregnancies.

Preeclampsia is responsible for a significant proportion of maternal and neonatal deaths, low birth weight and is a primary cause of premature birth.

The findings are reported in the May 19, 2020 issue of Cell Reports Medicine by researchers at University of California San Diego School of Medicine and Sera Prognostics, Inc., a Salt Lake City-based company that makes diagnostics tests for predicting the risk of premature birth.

Source: news-medical.net