Extracellular RNAs as potential biomarkers for placental dysfunction
Leonardo, Trevor Robert Thomas
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Placental dysfunction affects approximately 1 in 10 pregnant women in both the developed and developing worlds. Most commonly, it is manifested as preeclampsia or fetal growth restriction. Over the past two decades, an increasing body of research into the developmental biology of the placenta has been amassed, which points to defects in the differentiation of the trophoblast cell lineage as a key player in the pathophysiology of placental dysfunction. A number of clinical parameters are known to be associated with an elevated risk of placental dysfunction. These include maternal risk factors (such as chronic hypertension, renal disease, and lupus), history of placental dysfunction in a prior pregnancy, abnormalities in the levels of certain proteins in the maternal blood that are commonly used to estimate the risk of fetal genetic defects, and abnormalities in uterine artery Doppler waveforms. These current methods have significant drawbacks, including low specificity and sensitivity, high cost, lack of widespread availability, and lack of validity early in pregnancy. In order to provide a more cost-effective and reliable method to detect an elevated risk for placental dysfunction early in pregnancy, we explored the potential for extracellular RNAs (exRNA) in the maternal serum to be used as biomarkers. In our study, we used next generation sequencing technologies to compare extracellular microRNA (miRNA) levels in serum samples of pregnant women of different gestational ages, nonpregnant women, and placental tissue samples. We discovered that the large majority of microRNAs that were present at higher levels in pregnant serum samples than nonpregnant serum samples and were likely of placental origin. We also found that these pregnancy-specific miRNAs were enriched for miRNAs encoded on chromosomes (Chr) 14 and 19, with changes in the relative expression of these two groups of miRNAs throughout pregnancy. Moreover, the miRNA signatures of late gestational pregnant samples correlated more closely with placental tissue samples than those of early pregnant samples, which could be related to the increasing impact of a larger placenta on the maternal serum exRNA profile. Our results demonstrate the potential utility of next generation sequencing technologies in regards to differentiating between different conditions using clinical samples.