Literature DB >> 34255065

Comparing the Predictivity of Human Placental Gene, microRNA, and CpG Methylation Signatures in Relation to Perinatal Outcomes.

Jeliyah Clark1,2, Vennela Avula1,2, Caroline Ring3, Lauren A Eaves1,2, Thomas Howard2, Hudson P Santos2,4, Lisa Smeester1,2, Jacqueline T Bangma1, Thomas Michael O'Shea5, Rebecca C Fry1,2,6, Julia E Rager1,2,6.   

Abstract

Molecular signatures are being increasingly integrated into predictive biology applications. However, there are limited studies comparing the overall predictivity of transcriptomic versus epigenomic signatures in relation to perinatal outcomes. This study set out to evaluate mRNA and microRNA (miRNA) expression and cytosine-guanine dinucleotide (CpG) methylation signatures in human placental tissues and relate these to perinatal outcomes known to influence maternal/fetal health; namely, birth weight, placenta weight, placental damage, and placental inflammation. The following hypotheses were tested: (1) different molecular signatures will demonstrate varying levels of predictivity towards perinatal outcomes, and (2) these signatures will show disruptions from an example exposure (ie, cadmium) known to elicit perinatal toxicity. Multi-omic placental profiles from 390 infants in the Extremely Low Gestational Age Newborns cohort were used to develop molecular signatures that predict each perinatal outcome. Epigenomic signatures (ie, miRNA and CpG methylation) consistently demonstrated the highest levels of predictivity, with model performance metrics including R2 (predicted vs observed) values of 0.36-0.57 for continuous outcomes and balanced accuracy values of 0.49-0.77 for categorical outcomes. Top-ranking predictors included miRNAs involved in injury and inflammation. To demonstrate the utility of these predictive signatures in screening of potentially harmful exogenous insults, top-ranking miRNA predictors were analyzed in a separate pregnancy cohort and related to cadmium. Key predictive miRNAs demonstrated altered expression in association with cadmium exposure, including miR-210, known to impact placental cell growth, blood vessel development, and fetal weight. These findings inform future predictive biology applications, where additional benefit will be gained by including epigenetic markers.
© The Author(s) 2021. Published by Oxford University Press on behalf of the Society of Toxicology.All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Keywords:  computational toxicology; epigenomics; machine learning; multi-omics; placenta; predictive biology

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Year:  2021        PMID: 34255065      PMCID: PMC8478332          DOI: 10.1093/toxsci/kfab089

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.109


  70 in total

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Journal:  Bioinformatics       Date:  2014-01-28       Impact factor: 6.937

2.  ROBUST HYPERPARAMETER ESTIMATION PROTECTS AGAINST HYPERVARIABLE GENES AND IMPROVES POWER TO DETECT DIFFERENTIAL EXPRESSION.

Authors:  Belinda Phipson; Stanley Lee; Ian J Majewski; Warren S Alexander; Gordon K Smyth
Journal:  Ann Appl Stat       Date:  2016-07-22       Impact factor: 2.083

3.  svaseq: removing batch effects and other unwanted noise from sequencing data.

Authors:  Jeffrey T Leek
Journal:  Nucleic Acids Res       Date:  2014-10-07       Impact factor: 16.971

4.  Cadmium induces inflammatory cytokines through activating Akt signaling in mouse placenta and human trophoblast cells.

Authors:  Jun Hu; Hua Wang; Yong-Fang Hu; Xiao-Feng Xu; Yuan-Hua Chen; Mi-Zhen Xia; Cheng Zhang; De-Xiang Xu
Journal:  Placenta       Date:  2018-03-28       Impact factor: 3.481

5.  In vitro application of ribonucleases: comparison of the effects on mRNA and miRNA stability.

Authors:  Arian Aryani; Bernd Denecke
Journal:  BMC Res Notes       Date:  2015-04-22

6.  Salmon provides fast and bias-aware quantification of transcript expression.

Authors:  Rob Patro; Geet Duggal; Michael I Love; Rafael A Irizarry; Carl Kingsford
Journal:  Nat Methods       Date:  2017-03-06       Impact factor: 28.547

7.  Evidence for the placenta-brain axis: multi-omic kernel aggregation predicts intellectual and social impairment in children born extremely preterm.

Authors:  Hudson P Santos; Arjun Bhattacharya; Robert M Joseph; Lisa Smeester; Karl C K Kuban; Carmen J Marsit; T Michael O'Shea; Rebecca C Fry
Journal:  Mol Autism       Date:  2020-12-11       Impact factor: 7.509

8.  Low-level processing of Illumina Infinium DNA Methylation BeadArrays.

Authors:  Timothy J Triche; Daniel J Weisenberger; David Van Den Berg; Peter W Laird; Kimberly D Siegmund
Journal:  Nucleic Acids Res       Date:  2013-03-09       Impact factor: 16.971

9.  DNA methylation profiling of acute chorioamnionitis-associated placentas and fetal membranes: insights into epigenetic variation in spontaneous preterm births.

Authors:  Chaini Konwar; E Magda Price; Li Qing Wang; Samantha L Wilson; Jefferson Terry; Wendy P Robinson
Journal:  Epigenetics Chromatin       Date:  2018-10-29       Impact factor: 4.954

10.  National, regional, and worldwide estimates of low birthweight in 2015, with trends from 2000: a systematic analysis.

Authors:  Hannah Blencowe; Julia Krasevec; Mercedes de Onis; Robert E Black; Xiaoyi An; Gretchen A Stevens; Elaine Borghi; Chika Hayashi; Diana Estevez; Luca Cegolon; Suhail Shiekh; Victoria Ponce Hardy; Joy E Lawn; Simon Cousens
Journal:  Lancet Glob Health       Date:  2019-05-15       Impact factor: 26.763

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  5 in total

1.  The placenta epigenome-brain axis: placental epigenomic and transcriptomic responses that preprogram cognitive impairment.

Authors:  Anastasia N Freedman; Lauren A Eaves; Julia E Rager; Noemi Gavino-Lopez; Lisa Smeester; Jacqueline Bangma; Hudson P Santos; Robert M Joseph; Karl Ck Kuban; Thomas Michael O'Shea; Rebecca C Fry
Journal:  Epigenomics       Date:  2022-09-08       Impact factor: 4.357

2.  Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research.

Authors:  Kyle Roell; Lauren E Koval; Rebecca Boyles; Grace Patlewicz; Caroline Ring; Cynthia V Rider; Cavin Ward-Caviness; David M Reif; Ilona Jaspers; Rebecca C Fry; Julia E Rager
Journal:  Front Toxicol       Date:  2022-06-22

Review 3.  The Placental Epigenome as a Molecular Link Between Prenatal Exposures and Fetal Health Outcomes Through the DOHaD Hypothesis.

Authors:  Samantha Lapehn; Alison G Paquette
Journal:  Curr Environ Health Rep       Date:  2022-04-29

4.  Wildfires and extracellular vesicles: Exosomal MicroRNAs as mediators of cross-tissue cardiopulmonary responses to biomass smoke.

Authors:  Celeste K Carberry; Lauren E Koval; Alexis Payton; Hadley Hartwell; Yong Ho Kim; Gregory J Smith; David M Reif; Ilona Jaspers; M Ian Gilmour; Julia E Rager
Journal:  Environ Int       Date:  2022-07-16       Impact factor: 13.352

Review 5.  Approaches to incorporate extracellular vesicles into exposure science, toxicology, and public health research.

Authors:  Celeste K Carberry; Deepak Keshava; Alexis Payton; Gregory J Smith; Julia E Rager
Journal:  J Expo Sci Environ Epidemiol       Date:  2022-02-25       Impact factor: 6.371

  5 in total

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