Cell-free RNA Profiles Gauge Preeclampsia Risk Months Before Symptoms

The period from conception to delivery represents the most rapid growth and development in an individual’s life. The ability to support this development requires dramatic and inadequately understood alterations in maternal physiology.

Preeclampsia, a pregnancy complication marked by the onset of hypertension, affects about 8% of pregnancies and contributes to maternal and neonatal morbidity and mortality. Signs of preeclampsia tend to arise late in pregnancy, and the disease is thought to originate with the establishment of the placenta in pregnancy.


A large team of clinical scientists including those at the Brigham and Women’s Hospital (Boston, MA, USA) and Mirvie, Inc., (South San Francisco, CA, USA) demonstrated the ability of plasma cell-free RNA (cfRNA) to reveal patterns of normal pregnancy progression and determine the risk of developing pre-eclampsia months before clinical presentation. The team gathered maternal transcriptome data from eight different prospective cohorts, pulling together data that encompassed 2,539 plasma samples and 1,840 pregnancies. This cohort included women of a range of ethnic, national, geographical, and socioeconomic backgrounds.

In particular, the scientists conducted a case-control study of 72 individuals with preeclampsia and 452 controls, including individuals with chronic hypertension and gestational hypertension using blood samples taken during the second trimester. They performed PCR with reverse transcription (RT–qPCR) analysis to assess the relative amount of cfRNA extracted from each sample. They measured and compared the threshold cycle (Ct) values from each RNA sample using a three-color multiplex qPCR assay. cfRNA libraries were prepared using the SMARTer Stranded Total RNAseq-Pico Input Mammalian kit (Takara Bio, Kusatsu, Japan). RNA measurements and fragment analysis was performed on a Fragment Analyzer 5300 (Agilent Technologies, San Diego, CA, USA).

The investigators identified seven genes whose signatures consistently separated cases and controls. Four of the genes, PAPPA2, CLDN7, TLE6, and FABP1, have functions linked to preeclampsia or to placental development and the three others, SNORD14A, PLEKHH1, and MAGEA10, have been tied bioinformatically to preeclampsia, though their functions are unclear.

At a sensitivity of 75%, a model based on these gene signatures had a positive predictive value of 32.3%, with a preeclampsia prevalence of 13.7% in the study. This, according to the team, is better than currently used clinical models, which have positive predictive values of 4.4%, and rely on maternal factors. The test also detected preeclampsia risk early in pregnancy. It correctly identified 73% of expectant mothers, who later had a medically indicated preterm birth three months before the onset of clinical symptoms or delivery.

The authors concluded that their findings can now be leveraged to more accurately provide information on future maternal and fetal health and disease. Thus, their approach opens new therapeutic windows to effectively decrease maternal and neonatal morbidity and mortality. The study was published on January 5, 2022 in the journal Nature.

Related Links:
Brigham and Women’s Hospital
Mirvie, Inc
Takara Bio
Agilent Technologies