Studying Bile Acid Patterns in Pregnant Women with Intrahepatic Cholestasis of Pregnancy and Healthy Controls to Predict Risks to Mother and Baby
Led by Jena University Hospital · Updated on 2026-02-23
74
Participants Needed
1
Research Sites
52 weeks
Total Duration
AI-Summary
What this Trial Is About
Researchers are investigating whether analyzing bile acid patterns can help predict serious complications in pregnant women with intrahepatic cholestasis of pregnancy ICP, a liver condition that may affect the baby. This observational study also explores if these bile acid patterns activate certain receptors that could cause immune or heart rhythm problems in the baby, and how the mothers gut bacteria relate to ICP severity. The study compares three groups pregnant women with ICP, healthy pregnant women, and healthy non-pregnant women.
Participants will provide blood samples during routine bile acid checks throughout pregnancy and at delivery, stool samples to study gut bacteria and bile acids, and babys umbilical cord blood at birth. They will have standard heart rate monitoring CTG and an ultrasound of the babys heart echocardiography. The study aims to see if combining heart rate monitoring with bile acid measurements better identifies high-risk pregnancies.
During the study, researchers will monitor bile acid profiles from inclusion to delivery for pregnant women and at inclusion for non-pregnant women. They will also assess receptor activity, bile acid levels in stool, and bile acid transfer between mother and baby. Participants can expect regular sample collections and standard heart and ultrasound exams. The study will help clarify how bile acid patterns relate to pregnancy risks in ICP.
CONDITIONS
Brief Title
Serum Bile Acid Profiles in Patients With Intrahepatic Cholestasis of Pregnancy
Research Team
S
Silke Große, Dr. rer. nat.
J
Janine Zöllkau, Dr. med.
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Published Research Related To This Trial
Association of adverse perinatal outcomes of intrahepatic cholestasis of pregnancy with biochemical markers: results of aggregate and individual patient data meta-analyses.
Caroline Ovadia, Paul T Seed, Alexandros Sklavounos...