Data Catalog

Data from "The prediction of late-onset preeclampsia: Results from a longitudinal proteomics study"

WSU Dataset

Authors

Offer Erez

Roberto Romero

Eli Maymon

Piya Chaemsaithong

6 more author(s)...

Description

Preeclampsia, a frequent complication of pregnancy that affects 5%-8% of all gestations, is a leading cause of maternal, and perinatal morbidity and mortality. Over the last decade, it has become clear that preeclampsia is not a single disorder but a syndrome with many etiologies, such as abnormal placentation, utero-placental ischemia, vascular disorders of the placenta, insulin resistance, systemic maternal inflammation, endothelial dysfunction, and imbalance of angiogenic and anti-angiogenic proteins. A case-control longitudinal study was conducted, including 90 patients with normal pregnancies and 76 patients with late-onset preeclampsia (diagnosed at ≥34 weeks of gestation). Maternal plasma samples were collected throughout gestation (normal pregnancy: 2–6 samples per patient, median of 2; late-onset preeclampsia: 2–6, median of 5). The abundance of 1,125 proteins was measured using an aptamers-based proteomics technique. Protein abundance in normal pregnancies was modeled using linear mixed-effects models to estimate mean abundance as a function of gestational age. Data was then expressed as multiples of-the-mean (MoM) values in normal pregnancies. Multi-marker prediction models were built using data from one of five gestational age intervals.

Subject

Medicine & Health

Timeframe

2007 - 2013

Access Rights

Free to all