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

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...

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Autores principales: Tarca, Adi L., Pataki, Bálint Ármin, Romero, Roberto, Sirota, Marina, Guan, Yuanfang, Kutum, Rintu, Gomez-Lopez, Nardhy, Done, Bogdan, Bhatti, Gaurav, Yu, Thomas, Andreoletti, Gaia, Chaiworapongsa, Tinnakorn, Hassan, Sonia S., Hsu, Chaur-Dong, Aghaeepour, Nima, Stolovitzky, Gustavo, Csabai, Istvan, Costello, James C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233692/
https://www.ncbi.nlm.nih.gov/pubmed/34195686
http://dx.doi.org/10.1016/j.xcrm.2021.100323
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author Tarca, Adi L.
Pataki, Bálint Ármin
Romero, Roberto
Sirota, Marina
Guan, Yuanfang
Kutum, Rintu
Gomez-Lopez, Nardhy
Done, Bogdan
Bhatti, Gaurav
Yu, Thomas
Andreoletti, Gaia
Chaiworapongsa, Tinnakorn
Hassan, Sonia S.
Hsu, Chaur-Dong
Aghaeepour, Nima
Stolovitzky, Gustavo
Csabai, Istvan
Costello, James C.
author_facet Tarca, Adi L.
Pataki, Bálint Ármin
Romero, Roberto
Sirota, Marina
Guan, Yuanfang
Kutum, Rintu
Gomez-Lopez, Nardhy
Done, Bogdan
Bhatti, Gaurav
Yu, Thomas
Andreoletti, Gaia
Chaiworapongsa, Tinnakorn
Hassan, Sonia S.
Hsu, Chaur-Dong
Aghaeepour, Nima
Stolovitzky, Gustavo
Csabai, Istvan
Costello, James C.
author_sort Tarca, Adi L.
collection PubMed
description 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).
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spelling pubmed-82336922021-06-29 Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth Tarca, Adi L. Pataki, Bálint Ármin Romero, Roberto Sirota, Marina Guan, Yuanfang Kutum, Rintu Gomez-Lopez, Nardhy Done, Bogdan Bhatti, Gaurav Yu, Thomas Andreoletti, Gaia Chaiworapongsa, Tinnakorn Hassan, Sonia S. Hsu, Chaur-Dong Aghaeepour, Nima Stolovitzky, Gustavo Csabai, Istvan Costello, James C. Cell Rep Med Article 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). Elsevier 2021-06-15 /pmc/articles/PMC8233692/ /pubmed/34195686 http://dx.doi.org/10.1016/j.xcrm.2021.100323 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Tarca, Adi L.
Pataki, Bálint Ármin
Romero, Roberto
Sirota, Marina
Guan, Yuanfang
Kutum, Rintu
Gomez-Lopez, Nardhy
Done, Bogdan
Bhatti, Gaurav
Yu, Thomas
Andreoletti, Gaia
Chaiworapongsa, Tinnakorn
Hassan, Sonia S.
Hsu, Chaur-Dong
Aghaeepour, Nima
Stolovitzky, Gustavo
Csabai, Istvan
Costello, James C.
Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth
title Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth
title_full Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth
title_fullStr Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth
title_full_unstemmed Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth
title_short Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth
title_sort crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233692/
https://www.ncbi.nlm.nih.gov/pubmed/34195686
http://dx.doi.org/10.1016/j.xcrm.2021.100323
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