Noninvasive blood tests for fetal development predict gestational age and preterm delivery

Thuy T M Ngo, Mira N Moufarrej, Marie-Louise H Rasmussen, Joan Camunas-Soler, Wenying Pan, Jennifer Okamoto, Norma F Neff, Keli Liu, Ronald J Wong, Katheryne Downes, Robert Tibshirani, Gary M Shaw, Line Skotte, David K Stevenson, Joseph R Biggio, Michal A Elovitz, Mads Melbye, Stephen R Quake, Thuy T M Ngo, Mira N Moufarrej, Marie-Louise H Rasmussen, Joan Camunas-Soler, Wenying Pan, Jennifer Okamoto, Norma F Neff, Keli Liu, Ronald J Wong, Katheryne Downes, Robert Tibshirani, Gary M Shaw, Line Skotte, David K Stevenson, Joseph R Biggio, Michal A Elovitz, Mads Melbye, Stephen R Quake

Abstract

Noninvasive blood tests that provide information about fetal development and gestational age could potentially improve prenatal care. Ultrasound, the current gold standard, is not always affordable in low-resource settings and does not predict spontaneous preterm birth, a leading cause of infant death. In a pilot study of 31 healthy pregnant women, we found that measurement of nine cell-free RNA (cfRNA) transcripts in maternal blood predicted gestational age with comparable accuracy to ultrasound but at substantially lower cost. In a related study of 38 women (23 full-term and 15 preterm deliveries), all at elevated risk of delivering preterm, we identified seven cfRNA transcripts that accurately classified women who delivered preterm up to 2 months in advance of labor. These tests hold promise for prenatal care in both the developed and developing worlds, although they require validation in larger, blinded clinical trials.

Conflict of interest statement

M.N.M., S.R.Q., M.M., T.T.M.N., and J.C.-S. are inventors on a patent application (number 62/578,360) submitted by the Chan Zuckerberg Biohub that covers noninvasive estimates of gestational age, delivery, and preterm birth. The authors declare no other competing interests.

Copyright © 2018, American Association for the Advancement of Science.

Figures

Fig. 1
Fig. 1
Sample collection timelines from the Denmark, University of Pennsylvania, and University of Alabama cohorts. Squares, inverted triangles, and lines indicate sample collection times, delivery dates, and individual women, respectively.
Fig. 2
Fig. 2
Application of cfRNA measurements to predict gestational age. (A) For each gene, cfRNA transcript count measurements are shown over the course of gestation. Each point represents the mean cfRNA value ± SEM for either 31 women or 21 women (the latter denoted by †). The antepartum period is highlighted in gray. Placental, immune, and fetal liver–specific genes are highlighted in blue, green, and orange, respectively. (B) Heat map of the Pearson correlation coefficient for each gene pair shows that placental, immune, and fetal liver–specific cfRNA [same group colors as (A)] measurements are highly correlated with each other [median Pearson correlation r = 0.79 (placenta), 0.79 (immune), 0.74 (fetal liver); P < 10−14]. Placental and fetal liver–specific genes also show a weak degree of cross-correlation (r = 0.47, P < 10−15). Gene order matches order shown in (A), omitting genes denoted by † in (A). (C) Cross-validated random forest (RF) model predicts time to delivery from sampling time point (R = 0.91, P < 10−15, n = 21) for training cohort. (D) Cross-validated random forest model predicts time to delivery from sampling time point (R = 0.89, P < 10−15, n = 10) for validation cohort. (E) Distribution of difference in weeks between observed and predicted gestational age at delivery using cfRNA measurements from the second (T2), third (T3), or both (T2 & T3) trimesters (left to right) versus using ultrasound measurements from the first trimester (T1). AU, arbitrary units.
Fig. 3
Fig. 3
Application of cfRNA measurements to predict risk of spontaneous preterm delivery. (A) Heat map of the z-scores for 38 differentially expressed genes identified using cfRNA-seq (P < 0.001, exact test, likelihood ratio test, and quasi-likelihood F test) shows that genes distinguish women who delivered spontaneously preterm from women who delivered at full term. The two groups of women were separated using hierarchical clustering. (B) Means ± SD for differentially expressed genes validated using qRT-PCR in the discovery [University of Pennsylvania (I) and Denmark (II)] and validation [University of Alabama (III)] cohorts. *P < 0.05, **P < 0.01, ***P < 0.0005 (Fisher exact test). (C) Receiver operating characteristic curves for classifier designed to separate women who deliver spontaneously preterm from women who deliver at full term for both the discovery cohort (University of Pennsylvania and Denmark, AUC = 0.86) and the validation cohort (University of Alabama, AUC = 0.81).

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