Identification of novel cell-free RNAs in maternal plasma as preterm biomarkers in combination with placental RNA profiles

Abstract

Background Preterm birth (PTB) is the main driver of newborn deaths. The identification of pregnancies at risk of PTB remains challenging, as the incomplete understanding of molecular mechanisms associated with PTB. Although several transcriptome studies have been done on the placenta and plasma from PTB women, a comprehensive description of the RNA profiles from plasma and placenta associated with PTB remains lacking. Methods Candidate markers with consistent trends in the placenta and plasma were identified by implementing differential expression analysis using placental tissue and maternal plasma RNA-seq datasets, and then validated by RT-qPCR in an independent cohort. In combination with bioinformatics analysis tools, we set up two protein–protein interaction networks of the significant PTB-related modules. The support vector machine (SVM) model was used to verify the prediction potential of cell free RNAs (cfRNAs) in plasma for PTB and late PTB. Results We identified 15 genes with consistent regulatory trends in placenta and plasma of PTB while the full term birth (FTB) acts as a control. Subsequently, we verified seven cfRNAs in an independent cohort by RT-qPCR in maternal plasma. The cfRNA ARHGEF28 showed consistence in the experimental validation and performed excellently in prediction of PTB in the model. The AUC achieved 0.990 for whole PTB and 0.986 for late PTB. Conclusions In a comparison of PTB versus FTB, the combined investigation of placental and plasma RNA profiles has shown a further understanding of the mechanism of PTB. Then, the cfRNA identified has the capacity of predicting whole PTB and late PTB.

A Comprehensive Review on Circulating cfRNA in Plasma: Implications for Disease Diagnosis and Beyond

“…Next-generation sequencing (NGS) provides the ability to comprehensively detect RNA sequencing (RNA-seq) in plasma with high throughput, including known and unknown sequences, making it suitable for the discovery of new RNA markers and offering detailed transcriptomic information [10,81]. Despite these advantages, it comes with relatively high costs and data analysis difficulties, particularly in large-scale epidemiological studies [76,82]. Polyadenylation ligation-mediated sequencing (PALM-Seq), also known as RNA sequencing, is a technique used to study RNA molecule sequences and is often associated with the presence of Polyadenosine (PolyA) in RNA.…”