Blood test predicts pregnancy due date
A simple blood test that assesses certain RNAs in the bloodstream of pregnant women can predict delivery date and, in the future, it may be able to identify women at risk of preterm birth, a new study reports.
The research, conducted by Stanford University, USA, and published in Science, describes a technique that offers an affordable and convenient means to plan births and has the potential to identify pregnancies of concern.
Doctors currently rely on ultrasound imaging and/or the mother’s estimate of her last menstrual period to predict the gestational age of a foetus, but the former can be expensive and the latter can be imprecise. Inaccurate estimates can sometimes lead to unnecessary induction of labour and Cesarean sections, extended postnatal care and/or increased medical expenses.
Researcher Thuy Ngo and colleagues previously found that changes in both the mother and the foetus could be monitored by non-invasively measuring cell-free RNA (cfRNA) transcripts from fetal tissues in maternal blood. Here, they analysed blood samples from a cohort of women over the course of their pregnancies to identify cfRNA indicative of the foetuses’ gestational age.
The blood test they developed based on these data could predict the gestational age (where the birth occurred within 14 days of the estimated due date) with 45% accuracy, which is comparable to estimates of gestational age and due date based on ultrasound, at 48%.
In related work, the researchers compared cfRNAs in the blood of women who had healthy pregnancies with those in the blood of women who were known to be at elevated risk of preterm delivery. By assessing cfRNA transcripts of just seven genes, they accurately classified six of eight preterm cases and misclassified only one of 26 full-term cases. While promising, the studies were small. The next important step is to assess the reliability of the tests in large, blinded clinical trials.
Professor Mark Vickers, Associate Director of the Liggins Institute at the University of Auckland, New Zealand, cautions that while the research is important, it needs to be extended across larger sample groups and independent cohorts.
“Indeed, in this paper, the authors note the important limitations including the need for larger sample size, representation across diverse ethnicities and use of a broader unselected population (the cohort in this paper were pre-selected based on the elevated risk for preterm birth),’ Prof. Vickers said.
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