Purpose: Preeclampsia (PE) is one of the most common and serious complications of pregnancy, and novel methods for the early prediction of PE are needed for clinical application.
Methods: In this study, a circulating cell-free RNA (cfRNA) panel of target genes for PE prediction was designed and validated in a case-control cohort and a nested case-control cohort. The QPCR was applied to quantify the copy number of cfRNA, and the data were normalized as multiples of the median. Ratios of serum placental growth factor (PIGF) and soluble fms-like tyrosine kinase 1 (sFLT-1) were also measured, and transabdominal ultrasonography was conducted for subjects in the prospective cohort. Binary logistic regression models for PE prediction were constructed and tested.
Results: Our results revealed that the women with PE showed significant alterations in serum cfRNA profiles from early pregnancy onward and before the onset of PE symptoms. Compared with PIGF/sFLT-1 measurement and ultrasonographic imaging, cfRNA test can detect PE at a very early stage of pregnancy. The predictive model exhibited the best performance at gestation week 32, with a detection rate of 100%. At 12 weeks of gestation, the model still manifested an area under curve (AUC) of 0.9144, and sensitivity of 1.0000. If combined with clinical parameters and ultrasonographic indicators, the model can achieve the highest AUC for PE prediction at early gestation.
Conclusion: Measurement of cfRNA can be used to effectively predict PE with high performance, providing an additional method for monitoring PE throughout the course of pregnancy.
Keywords: Circulating mRNA; Predictive model; Preeclampsia.
© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.