Multiple research agencies addressing the complex public health problem of preterm birth have emphasized conducting research to identify biomarkers that could improve clinical risk assessment for preterm birth. Late- preterm infants (34 to <37 weeks gestation) comprise 74% of premature births, and are most responsible for the increased rates of premature deliveries in the U.S. During this time, obstetricians struggle to make delivery- planning decisions where uncertainty exists regarding benefit vs. risk for mother and baby, and the only currently available fetal maturity testing focuses on the lung. For this high-risk late-preterm population, identification of fetal biomarkers that predict physiologic readiness for postnatal life is critical for obstetrical and neonatal risk assessment, particularly when maturational processes have different trajectories for individual infants. Amniotic fluid (AF) both contributes to and reflects fetal well-being, and contains an abundant proportion of cell- free fetal DNA and RNA that can be targeted quantitatively for ease of application, specificity, and broader representation of cell types than protein or metabolites. Our preliminary work has demonstrated that this cell- free fetal RNA/DNA can be isolated and analyzed to produce a snapshot of overall fetal maturity, thereby making analysis of amniotic fluid a practical first step to discovery of novel biomarkers that can then be identified in maternal serum. This R21 will continue our discovery driven preliminary work by further elucidating the following hypothesis: The AF RNA transcriptome will exhibit RNA expression patterns that identify the state of fetal organ maturity, and will predict neonatal morbidity.
Aim 1 will describe differences in the amniotic fluid transcriptome at 4 different time points in pregnancy to describe the trajectory of physiologic processes occurring with advancing gestation.
Aim 2 (a) will identify candidate biomarkers for lung and other organ maturity by determining differences in amniotic fluid RNA expression between preterm infants (32 to <38 weeks) with and without common adverse neonatal outcomes.
Aim 2 (b) will then test the predictive capacity of the candidate biomarkers identified using a separate validation cohort, and compare the specificity and sensitivity for predicting fetal maturity, compared to current methods of fetal lung maturity testing. The proposed research has the potential impact to illustrate the transcriptomic profiles that are dynamically changing across fetal development and to inform the timing of non-indicated deliveries, significantly reducing maternal complications and neonatal morbidity resulting from prematurity, or to allow for other interventions to be administered to ameliorate fetal maturity (antenatal corticosteroids). By better informing the timing of late- preterm deliveries, we can reduce maternal and neonatal complications resulting from prematurity, a major public health concern.
Current methods of fetal lung maturity testing have been shown to be inadequate to predict an infant?s readiness for postnatal life free of neonatal morbidity; however, over half of obstetricians and maternal-fetal medicine specialists utilize fetal maturity testing to guide delivery timing in certain high-risk situations. Furthermore, multiple research agencies acknowledge investigation into biomarkers to properly assess neonatal morbidity risk after preterm delivery is a priority. This application aims to demonstrate the heterogeneous processes of fetal organ maturation by elucidating a ?transcriptomic clock,? multiple distinct patterns of gene expression occurring throughout the course of pregnancy, by utilizing the amniotic fluid cell- free RNA transcriptome. These patterns will be used to identify biomarkers of fetal maturity in an unbiased fashion in amniotic fluid, a less complex fluid than blood or serum, as a practical prelude to the development of targeted molecular diagnostics that can obtained less invasively through maternal serum. These patterns may also be used as biomarkers to date a pregnancy or predict neonatal morbidity. Since our previous submission, we have additional preliminary data that strongly validate our proof of principle. The results of this proposal will then be applicable towards a larger validation study of candidate biomarkers, to directly impact obstetrical decision-making, treatment of ?immature? fetuses with antenatal corticosteroids, and delivery planning for better risk prediction of neonatal morbidity.
