A Novel Multiomic AI Approach for Early Prediction of Preeclampsia in Pregnancy Using Maternal Gut Microbiota and Immune Response

What this Trial Is About

Preeclampsia (PE) is a serious condition affecting 3-8% of pregnancies and is a leading cause of illness and death for mothers and babies. It involves high blood pressure and organ damage or growth problems in the fetus. There are two main types: placental PE, linked to problems with the placenta and early pregnancy complications, and metabolic PE, related to maternal metabolic issues like obesity and inflammation. Recent research suggests that changes in the mother's gut bacteria may influence the immune system and play a role in PE development. This study aims to better understand the gut microbiota differences in these two PE types to improve prediction and prevention. The study observes pregnant women from 11 to 13 weeks gestation who are either at high risk or low risk for developing PE based on early screening. Participants include women over 18 with a single pregnancy and a live fetus. Researchers will monitor maternal gut microbiota, metabolic markers, and immune system characteristics during the first trimester without providing any treatments. The study includes a control group of low-risk pregnancies followed throughout pregnancy to compare with the high-risk group. Participants will undergo assessments including gut microbiota analysis, metabolic profiling, and immune function tests during early pregnancy. Researchers will track outcomes related to PE development and fetal growth restriction, aiming to identify biomarkers that could help predict PE types. The study lasts about one year per participant, with data collected during pregnancy and after delivery. This observational study does not involve treatment but focuses on collecting detailed biological and clinical information to improve understanding of PE.

A Novel Multiomic AI Approach for Early Preeclampsia Prediction in Pregnancy