bims-reprim 2021-07-04 papers

Issue of 2021‒07‒04
two papers selected by
Iva Filipovic
Karolinska Institutet

Sci Rep. 2021 Jun 29. 11(1): 13481

The amniotic fluid cell-free transcriptome in spontaneous preterm labor.

Gaurav Bhatti, Roberto Romero, Nardhy Gomez-Lopez, Roger Pique-Regi, Percy Pacora, Eunjung Jung, Lami Yeo, Chaur-Dong Hsu, Mahendra Kavdia, Adi L Tarca.

The amniotic fluid (AF) cell-free RNA was shown to reflect physiological and pathological processes in pregnancy, but its value in the prediction of spontaneous preterm delivery is unknown. Herein we profiled cell-free RNA in AF samples collected from women who underwent transabdominal amniocentesis after an episode of spontaneous preterm labor and subsequently delivered within 24 h (n = 10) or later (n = 28) in gestation. Expression of known placental single-cell RNA-Seq signatures was quantified in AF cell-free RNA and compared between the groups. Random forest models were applied to predict time-to-delivery after amniocentesis. There were 2385 genes differentially expressed in AF samples of women who delivered within 24 h of amniocentesis compared to gestational age-matched samples from women who delivered after 24 h of amniocentesis. Genes with cell-free RNA changes were associated with immune and inflammatory processes related to the onset of labor, and the expression of placental single-cell RNA-Seq signatures of immune cells was increased with imminent delivery. AF transcriptomic prediction models captured these effects and predicted delivery within 24 h of amniocentesis (AUROC = 0.81). These results may inform the development of biomarkers for spontaneous preterm birth.

DOI: https://doi.org/10.1038/s41598-021-92439-x

Cell Rep Med. 2021 Jun 15. 2(6): 100323

Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth.

Adi L Tarca, Bálint Ármin Pataki, Roberto Romero, Marina Sirota, Yuanfang Guan, Rintu Kutum, Nardhy Gomez-Lopez, Bogdan Done, Gaurav Bhatti, Thomas Yu, Gaia Andreoletti, Tinnakorn Chaiworapongsa, , Sonia S Hassan, Chaur-Dong Hsu, Nima Aghaeepour, Gustavo Stolovitzky, Istvan Csabai, James C Costello.

Identification of pregnancies at risk of preterm birth (PTB), the leading cause of newborn deaths, remains challenging given the syndromic nature of the disease. We report a longitudinal multi-omics study coupled with a DREAM challenge to develop predictive models of PTB. The findings indicate that whole-blood gene expression predicts ultrasound-based gestational ages in normal and complicated pregnancies (r = 0.83) and, using data collected before 37 weeks of gestation, also predicts the delivery date in both normal pregnancies (r = 0.86) and those with spontaneous preterm birth (r = 0.75). Based on samples collected before 33 weeks in asymptomatic women, our analysis suggests that expression changes preceding preterm prelabor rupture of the membranes are consistent across time points and cohorts and involve leukocyte-mediated immunity. Models built from plasma proteomic data predict spontaneous preterm delivery with intact membranes with higher accuracy and earlier in pregnancy than transcriptomic models (AUROC = 0.76 versus AUROC = 0.6 at 27-33 weeks of gestation).

Keywords: aptamers; collaborative competition; human transcriptome arrays; machine learning; plasma proteomics; predictive modeling; preterm labor and delivery; spontaneous preterm birth; whole blood transcriptomics

DOI: https://doi.org/10.1016/j.xcrm.2021.100323