Pregnancy is a peculiar and dynamic physiologic state, which presents the investigator with the unique opportunity of studying the role of ExRNAs in signaling between two individuals, the fetus and the mother. Critical to the success of the pregnancy is the rapid development of a new organ, the placenta, which is of fetal origin, but which must gain access to the maternal bloodstream. This direct contact between placental trophoblast cells and the maternal circulation facilitates the functions of these cells both as mediators of the exchange of materials between the fetus and the mother, and as sources of signaling molecules that induce changes in maternal physiology necessary for the establishment and maintenance of the pregnancy, such as progesterone, human chorionic gonadotropin and human placental lactogen. It is reasonable, then, to hypothesize that both the physiological changes occurring over the course of normal pregnancy and the pathological changes taking place with complications of pregnancy, are reflected in the ExRNA profiles of maternal biofluids, and may even be partially mediated by ExRNA signals. To promote research into the possible mechanisms through which ExRNAs may serve as signaling molecules in pregnancy and to realize the potential of ExRNAs as biomarkers for prediction and diagnosis of adverse pregnancy outcomes, there is a critical need to generate and disseminate high-quality, comprehensive ExRNA profiles from normal pregnancy. To this end, we propose to carry out our project in three Aims.
In Aim 1, we will perform comprehensive ExRNA profiling of previously collected plasma, serum and urine specimens from five existing prenatal cohorts, sampled at different gestational time points, and including subjects with diverse geographical and ethnic backgrounds. We will use existing RNA sequencing and bioinformatics techniques, as well as novel methods that are under development, in order to obtain comprehensive profiles on as many RNA species as possible, including short/long, coding/non-coding, linear/circular and polyadenylated/non-polyadenylated RNAs.
In Aim 2, we will purify and profile extracellular vesicles (EVs) of placental origin from maternal biofluids. Focusing on ExRNAs from placental EVs will allow us to discriminate between the ExRNAs from the fetal/placental compartment and ExRNAs from maternal tissues, which will be valuable for mechanistic studies on feto- maternal signaling. In addition, using data from purified placental EVs may be preferable for discovery of biomarkers for placental dysfunction or infection, because it avoids inter-individual variability from maternal tissue ExRNAs. Finally, in Aim 3, we will generate comprehensive total biofluid and placental EV ExRNA profiles for three small prospective cohorts. These cohorts are designed to interrogate specific sources of technical and biological variability, and will be extremely valuable for optimizing the ExRNA data generation and analysis from existing biorepositories, and for designing future studies.

Public Health Relevance

The primary goal of this project is to generate comprehensive reference profiles of extracellular RNAs from serum, plasma, and urine collected across gestation from normal pregnancies. This information is relevant to public health because dysregulated ExRNAs have the potential to serve as biomarkers for prediction and diagnosis of pregnancy-associated disorders, as well as to yield insights into disease pathophysiology.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01HL126494-01
Application #
8775105
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Srinivas, Pothur R
Project Start
2014-08-01
Project End
2019-04-30
Budget Start
2014-08-01
Budget End
2015-04-30
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of California San Diego
Department
Obstetrics & Gynecology
Type
Schools of Medicine
DUNS #
City
La Jolla
State
CA
Country
United States
Zip Code
92093
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